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Perspectives

Precancer Atlas to Drive Precision Prevention TrialsAvrum Spira1,2, Matthew B. Yurgelun3, Ludmil Alexandrov4, Anjana Rao5,Rafael Bejar6, Kornelia Polyak3, Marios Giannakis3, Ali Shilatifard7, Olivera J. Finn8,Madhav Dhodapkar9, Neil E. Kay10, Esteban Braggio11, Eduardo Vilar12,Sarah A. Mazzilli1,2, Timothy R. Rebbeck13, Judy E. Garber3,Victor E.Velculescu14,15,Mary L. Disis16, Douglas C.Wallace17,18, and Scott M. Lippman6

ABSTRACT Cancer development is a complex process driven by inherited and acquired molecularand cellular alterations. Prevention is the holy grail of cancer elimination, but making

this a reality will take a fundamental rethinking and deep understanding of premalignant biology. In thisPerspective,wepropose anational concerted effort to create a Precancer Atlas (PCA), integratingmulti-omicsand immunity – basic tenets of the neoplastic process. The biology of neoplasia caused by germlinemutations has led to paradigm-changing precision prevention efforts, including: tumor testing formismatchrepair (MMR) deficiency in Lynch syndrome establishing a new paradigm, combinatorial chemopreventionefficacy in familial adenomatous polyposis (FAP), signal of benefit from imaging-based early detectionresearch in high-germline risk for pancreatic neoplasia, elucidating early ontogeny in BRCA1-mutationcarriers leading to an international breast cancer prevention trial, and insights into the intricate germline-somatic-immunity interaction landscape. Emerging genetic and pharmacologic (metformin) disruption ofmitochondrial (mt) respiration increased autophagy to prevent cancer in a Li-Fraumeni mouse model(biology reproduced in clinical pilot) and revealed profound influences of subtle changes in mt DNAbackground variationonobesity, aging, and cancer risk. The elaborate communication between the immunesystem and neoplasia includes an increasingly complex cellular microenvironment and dynamic interac-tions between host genetics, environmental factors, and microbes in shaping the immune response. Cancervaccines are in early murine and clinical precancer studies, building on the recent successes of immuno-therapy and HPV vaccine immune prevention. Molecular monitoring in Barrett's esophagus to avoidoverdiagnosis/treatment highlights an important PCA theme.Next generation sequencing (NGS)discoveredage-related clonal hematopoiesis of indeterminate potential (CHIP). Ultra-deep NGS reports over the pastyear have redefined the premalignant landscape remarkably identifying tiny clones in the blood of upto 95% of women in their 50s, suggesting that potentially premalignant clones are ubiquitous. Similar datafrom eyelid skin and peritoneal and uterine lavage fluid provide unprecedented opportunities to dissectthe earliest phases of stem/progenitor clonal (and microenvironment) evolution/diversity with new single-cell and liquid biopsy technologies. Cancer mutational signatures reflect exogenous or endogenousprocesses imprinted over time in precursors. Accelerating the prevention of cancer will require a large-scale, longitudinal effort, leveraging diverse disciplines (from genetics, biochemistry, and immunology tomathematics, computational biology, and engineering), initiatives, technologies, andmodels in developingan integrated multi-omics and immunity PCA – an immense national resource to interrogate, target, andintercept events that drive oncogenesis. Cancer Res; 77(7); 1510–41. �2017 AACR.

Perspective

Cancer Res; 77(7) April 1, 20171510

on January 1, 2021. © 2017 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from

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IntroductionIn 2016, a national commitment to eradicate cancer by

investing in greatly accelerating progress within diverse fieldsof cancer research, including prevention and early detection,was heralded with the creation of the Cancer Moonshot ini-tiative. Funding for this effort (and other cancer-related inno-vative initiatives, e.g., stem cell research) received strongbipartisan support and was signed into law as part of the 21stCentury Cures Act (1). The rate-limiting step for developingand implementing precision prevention approaches has beenour limited understanding of precancer biology in contrastto the extensive study of advanced disease. For example, TheCancer Genome Atlas (TCGA), with volumes of omics datafrom >11,000 patients across 33 tumor types, has transformed

our understanding of cancer biology, identifying hundreds ofdriver mutations, molecular subgroups, immense tumor het-erogeneity, and become a tremendous national resource fordiscovery, catalyzing the development of novel computationaltools. In contrast, although the seminal genetic model oftumorigenesis was defined in the colon nearly 30 years ago(2), limited numbers of adenomas have undergone NGS (3).The interaction between immunity and neoplasia is now estab-lished as a fundamental principle of cancer development andprogression. A diverse array of engineered models, single-celltechnologies, and broad disciplines are beginning to be lever-aged to probe early oncogenesis and malignant transformation.Large-scale longitudinal and systematic mapping is critical todevelop an integrated omics and immune PCA, allowing dis-section of the sequential molecular and cellular events that

1Department of Medicine, Boston University School of Medicine, Boston,Massachusetts. 2Department of Pathology and Bioinformatics, Boston Uni-versity School of Medicine, Boston, Massachusetts. 3Department of MedicalOncology, Dana-Farber Cancer Institute, Boston, Massachusetts. 4Theoret-ical Division, Center for Nonlinear Studies, Los Alamos National Laboratory,Los Alamos, New Mexico. 5Division of Signaling and Gene Expression, LaJolla Institute for Allergy and Immunology, La Jolla, California. 6Departmentof Medicine, Moores Cancer Center, University of California San Diego, LaJolla, California. 7Department of Biochemistry and Molecular Genetics,Northwestern University Feinberg School of Medicine, Chicago, Illinois.8Department of Immunology, University of Pittsburgh, Pittsburgh, Penn-sylvania. 9Department of Hematology and Immunology, Yale Cancer Center,New Haven, Connecticut. 10Department of Hematology, Mayo Clinic Hos-pital, Rochester, Minnesota. 11Department of Hematology, Mayo ClinicHospital, Phoenix, Arizona. 12Department of Clinical Cancer Prevention,The University of Texas MD Anderson Cancer Center, Houston, Texas.13Division of Hematology and Oncology, Dana-Farber Cancer Institute andHarvard T.H. Chan School of Public Health, Boston, Massachusetts.

14Department of Oncology, Sidney Kimmel Comprehensive Cancer Centerat Johns Hopkins, Baltimore, Maryland. 15Department of Pathology, SidneyKimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, Mary-land. 16Department of Medicine, Center for Translational Medicine inWomen's Health, University of Washington, Seattle, Washington. 17Centerfor Mitochondrial and Epigenomic Medicine, Children's Hospital of Phila-delphia, University of Pennsylvania, Philadelphia, Pennsylvania. 18Depart-ment of Pathology and Laboratory Medicine, Perelman School of Medicine,University of Pennsylvania, Philadelphia, Pennsylvania.

Note: A. Spira and M.B. Yurgelun contributed equally to this article.

Corresponding Author: Scott M. Lippman, UC San Diego Moores CancerCenter, La Jolla, CA 92093. Phone: 858-822-1222; Fax: 858-822-0207; E-mail:[email protected]

doi: 10.1158/0008-5472.CAN-16-2346

�2017 American Association for Cancer Research.

www.aacrjournals.org Cancer Res; 77(7) April 1, 2017 1511

The Precancer Atlas



promote oncogenesis, to drive novel prevention and intercep-tion (4–6) (Fig. 1).

Translating Inherited Risk into PrecisionPreventionGermline cancer susceptibility

The genetics of various hereditary forms of cancer risk havebeen investigated extensively and long been used to aid ourunderstanding of sporadic neoplasia. Historically, most cancersusceptibility genes were identified through linkage studies incancer families (7). Furthermore, the biology of germline muta-tions in certain cancer genes (e.g., BRCA1 carriers) is much better

understood than in the somatic setting and is now providingtremendous insight into precision interventions by leveraging thebiology of the mutated gene itself. Study of the biology of tumorsthat develop in BRCA1/2-mutation carriers has led to paradigm-changing precision therapy with PARP inhibitors (7), which havedemonstrated preventive activity in BRCA1-deficient mice (8).Similarly Lynch syndrome is serving as a model of immuneoncology for sporadic high level of microsatellite instability(MSI-H) tumors (9, 10). Understanding the convergence of Wntand EGFR signaling in FAP, characterized by germline APC muta-tions, led to a breakthrough trial of combination chemopreventionwitherlotiniband sulindac,which reducedduodenalneoplasia, theleading cause of cancer death following standard prophylactic

Immune Surveillance

VEGF, Cytokines(e.g., IL-6, IL-8, IL-17)

Innate and Adaptive Immune Cells:

Mutations and Neoantigens

Viral Antigens

Post-Translational

• Glycosylation

• Phosphorylation

• Splice Variants

LEGENDNaive lymphocytes

Activated CD8+ Cytotoxic T-cells

Exhausted CD8+ Cytotoxic T-cells

Regulatory T-cells

M1 Macrophages

M2 Macrophages

Dendritic Cells

Myeloid-Derived Suppressor Cells

Natural Killer Cells

Adipocytes

Neutrophils

Immune Suppression/EscapeImmune Suppressing Cells:

• Tumor-Associated Macrophages (TAMs/M2)

• Myeloid-Derived Suppressor Cells (MDSCs)

• Regulatory T-cells (Tregs)

• Adipocytes, Neutrophils, Fibroblasts

Immune Evasion Markers

• Checkpoint Inhibition of T-cells

• Somatic Copy Number Alterations

INFECTION

ImmunityAtlas

HPV, HBV, EBV

NORMAL PRECANCER

Multi-omics Atlas

CANCER

GERMLINEBRCA1, MMRD, APC

SOMATICKRAS, TET2, ND5

Figure 1.

An integrated multi-omics and immunity PCA. Inherited and acquired molecular alterations and their interaction with the microenvironment and immune systeminfluence oncogenic progression to invasive carcinoma. Three types of at-risk tissue fields exist from a neoplasia perspective: a normal, carcinogen-exposed, andgermline-predisposed (see text). Normal cells (light orange, far left) that havenuclear ormitochondrial germlinemutations (green nuclei) acquire somatic alterations(dark orange), including due to viral infection (purple). Driven by genomic instability, these events can alter the oncogenic state with loss of cell growth control,immune evasion andother hallmarks of cancer (6),which can then result in the development of advancedprecancers (multicolored cellmasswith subclonal diversity/heterogeneity) that immediately precede invasive cancer (red; far right). Molecular alterations, depicted by symbols in the nucleus, include mutations, SNPs, orepigenetic alterations. The accumulation ofmutations (e.g., UV, ABOBEC3, DNA repair defects) during life creates signatures (shown by the chromosomal insets andcolored dots in gradient from cancer to normal; right to left). These mutational signatures, often identified in cancers, may give clues about etiology and precursors.Functional assays in model systems (e.g., C. elegans and mouse embryonic fibroblasts) will help confirm genotoxic exposures and identify new ones. Mixedmutational processes are also active in normal tissues from conception, varying in strength over space and time. Multi-omic alterations interact (bidirectionally) withthe tissue microenvironment of well-established immune cells (tumor-associated macrophages/fibroblasts, MDSCs, NK and cytotoxic/regulatory T-cells), morerecently identified and less well understood cells in this context (e.g., adipocytes, myocytes, pericytes, chondrocytes, osteoblasts, neutrophils, fibroblasts, andvascular, epithelial, neuronal, mast and B-cells), microbes, and other cells/events that influence oncogenesis (see text). The continuum between immune statemodulated by cytokines and growth factors includes immune surveillance, composed of the antigenic repertoire, innate and adaptive immune cells (upper left box),and immune suppression/escape (upper right box) along with the cells andmarkers that can lead to immune escape. These complexmulti-omic and immunity fieldsare evolving rapidly, requiring a PCA mechanism/process of continuous updating.

Perspective

Cancer Res; 77(7) April 1, 2017 Cancer Research1512



colectomy for this devastating syndrome (11). Multigene NGS isbroadening the spectrumof cancer risk linked to various hereditarysyndromes, frequently identifying individuals with high-pene-trance germline mutations that are unexpected based on clinicalhistory, for example, colorectal cancer (CRC) in BRCA1/2- andTP53-mutationcarriers andbreast cancer in Lynchsyndrome(7, 12,13). Furthermore, broad NGS identified germline mutations incancer-predisposing genes in �10% of >1100 pediatric cancerpatients, most of whom lack suggestive family histories (14).

A fundamental question regarding inherited cancer susceptibilityis why germline mutations, which affect all cells, generally predis-pose to a particular spectrum and pattern of cancers (7). Althoughsome genes have organ-specific effects (e.g., mutations leading tohepatic overload which predispose to liver cancer), most cancersusceptibility genes have a broad range of functions (e.g., BRCA1essential functions include homologous recombination-type dou-ble-strand break repair [HR-DSBR]). It is unclear, therefore, whydifferent inherited DNA repair defects predispose to specific anddifferent cancers, such as mismatch repair (MMR) gene defects inLynch syndrome predisposing mostly to CRC and endometrialcancer, while HR-DSBR defects in BRCA1/2-mutation carriers asso-ciate mostly with breast and ovarian cancer and others, such asp53 mutations in Li Fraumani syndrome that are more generalandassociatedwithmanydifferent cancers.Evendefects indifferentMMR genes and location of mutations in the same gene can beassociated with differing clinical effects (7, 15). For example,mutations inMSH2 are linked to urothelial cancer, distinct BRCA1mutations differentially reduce hematopoietic stem cell (HSC)function, and central mutations in BRCA2 confer higher risks ofovarian (vs. breast) cancer anddiffer by context (e.g., family history,lifestyle, and other modifying factors; refs. 7, 15, 16). Interestingly,most cancer DNA repair genes are germline mutated. The basis oftissue specificity in this context remains a mystery after decades ofstudy and is still under active investigation (16).

BRCA1-mutation carriersPerhaps the most historically intriguing and enigmatic issue

in this field is the fact that BRCA1-mutation/haploinsufficientcarriers develop estrogen receptor (ER)-negative cancers inestrogen-regulated tissues and may be prevented by tamoxifenand related agents (which do not prevent ER-negative cancerin non-BRCA1, high-risk populations), a focus of increasinglyintensive research. Experimental evidence of this tissue speci-ficity in this setting demonstrated that BRCA1-haploinsufficientbreast epithelial (but not fibroblast) cells exhibit an increasedDNA damage response, genomic instability, telomere erosion,and premature senescence (17). Telomere-BRCA1 interactionsin genome instability also reports synergy between an ovariancancer risk SNP in OGG1 glycosidase (base excision repairpathway gene) and BRCA1-mutation carriers on telomere insta-bility (18) and profound alterations in telomere homeostasis inBRCA1-silenced nonmalignant breast epithelial cells (19).

Emerging data are now revealing potential underlyingmechan-isms, primarily involving hormonal/DNA repair interplay inthe early ontogeny of neoplasia in BRCA1-mutation carriers(20). BRCA1-haploinsufficient normal mammary epithelial cells(MECs) exhibit all the usual Brca1 functions except for defectivestalled replication fork (SRF) repair producing replication stress,among the earliest defects in this setting, which can be rescuedby reconstituting cells with WT BRCA1 (21). Interacting factorsrelevant to tissue specificity include BRCA1 haploinsufficiency

(heterozygosity) associatedwith high titers of circulating estrogenand progesterone and end-organ hormonal dysfunction (20).Furthermore, normal BRCA-mutant breast cells upregulate tran-scription of CYP1A1 (estrogen-metabolizing gene) and CYP19A1(estrogen-producing aromatase gene), the latter contributing tothe 6–7-fold higher estrogen levels in normal/benign breast andovary tissue than in the already high titers in the circulation (vs.nonmutant carriers). BRCA1-deficient, ERa-negative breast cellswere more susceptible to estrogen-induced DNA damage, DSB(via defective SFR), and genomic instability (not seen withBRCA2 loss), i.e., BRCA1-mutant breast cells have increasedrates of estrogenmetabolismand both ERa activation by estradioland the conversion of estrogen to genotoxicmetabolites can causeDSBs (22). Haploinsufficiency in replication stress suppressionis also a feature of apparently normal MECs with a PALB2mutation (a BRCA1/2-interacting suppressor protein), which alsocauses DNA replication and damage response defects (23). Takentogether, persistent replication stress inBRCA1-mutant breast cellspromotes defective HR-DSBR and genomic instability, whichdrives later tumorigenic events of p53 mutation and WT BRCA1loss of heterozygosity.

Bolstering these findings are experiments in which BRCA1haploinsufficiency: represses PR/ER transcriptional activity, dis-rupts receptor turnover innormal tissue adjacent toBRCA1-mutantbreast cancer and mammary epithelium of Brca1/p53-deficientmice, and cooperates with estrogen signaling to promote ERa-negative mammary tumorigenesis; enables targeted, conditionalERa overexpression (with p53 insufficiency) in MECs leading toER-negative neoplasia; stimulates estrogen-dependent prolifera-tionofpremalignant cells inBrca1-knockoutmice; causes impairedovarianhormone regulation, signaling, andgrowth factor responseandDNArepair innormalhumanBRCA1-mutantbreast tissue andgenetically engineered mouse model (GEMM) with disruptedBrca1 alleles (24); andprotectsMECs fromoxidative stress-inducedcell death by estrogen regulation of NRF2 pathway via PI3K-AKTsignaling, which promotes survival of BRCA1-deficient cells inestrogen-responsive tissues (25). The interplay between BRCA1and ESR1 (which encodes ERa) includes SWI/SNF subunit BRD7recruiting BRCA1 to the ESR1 promoter to transcriptionally reg-ulate ERa (26) and BRCA1/BARD1-mediated ubiquitination ofERa, which increases estrogen signaling and breast tumorigenesis(27).Genome-wide association studies (GWAS) are also leading toa better understanding of the biology of tumor development inBRCA1 carriers, including identifying SNPs at ESR1 (6q25.1)associated with breast cancer risk and linking low-frequencyBRCA1-coding variants to reproductive aging and breast cancersusceptibility, likely mediated by prolonged estrogen exposure/signaling and DNA repair defects (28). BRCA1-mutation has alsobeen associated with accelerated ovarian aging from preclinical,GWAS, and epidemiologic data. Germline BRCA1mutations alsocan reprogram breast metabolism towards mitochondrial-depen-dent biosynthetic intermediates (29), guiding metabolomic-epi-genetic prevention strategies. Finally, a report of ER-negativeovarian cancer found that ERa-dependent estrogen signaling pro-moted the JAK2-STAT3 pathway, which stimulated immunosup-pressive myeloid-derived suppressor cells (MDSCs; ref. 30), pro-viding a provocative perspective into how augmented estrogenicactivity could contribute to ER-negative tumor development (e.g.,in BRCA1-mutation carriers).

Large randomized, controlled trials of selective estrogenreceptor modulators (SERMs) (e.g., tamoxifen and raloxifene)

The Precancer Atlas




and aromatase inhibitors (e.g., anastrozole) show benefit inpreventing ER-positive breast cancer (31). Observational studies,however, unexpectedly indicate that tamoxifen can also reducebreast cancer risk, especially contralateral breast cancer, inBRCA1-mutation carriers (32). Further insight into this issue is comingfrom studies in which tamoxifen: inhibited proliferation in nor-mal breast epithelial tissue from BRCA1 carriers, similar to non-carriers at increased or population risk of breast cancer; preventedmammary preneoplasia in relation to BRCA1 gene dosage, MECsfrom conditional GEMMs with only one disrupted BRCA1 allele(more relevant to early human ontogeny; loss of WT BRCA1is a late event), were more sensitive to tamoxifen (vs. whenboth alleles were disrupted; ref. 33); and decreased MDSC andincreased cytotoxic T-cell infiltration in ER-negative ovarian can-cer, whereas the opposite effects were seen in response to estradiol(see above; ref. 30). BRCA1/2 defects have complex immuneinteractions, including BRCA1/interferon-g cooperation to acti-vate innate immune response gene subset (ref. 34; see FanconiAnemia and Big Genomics below). Tamoxifen resistance inBRCA1-deficient GEMMs was associated with gene dosage, animmune signature, and was reversed by the aromatase inhibitorletrozole (33, 35).

The earliest steps of BRCA1-mutant breast neoplasia mayinvolve defects in lineage commitment influencing tissue spec-ificity (36–38). Elegant studies of luminal progenitor biology(36, 37) have created a transformative potential to prevent/delay BRCA1-associated breast cancer, a disease for which thebest current preventive option is prophylactic surgery. A highlyproliferative subset of luminal progenitor cells (which lack ERaand PR) give rise to basal-like breast cancer, which constitutivelyexpress RANK and are hyper-responsive to RANK-L (producedby mature luminal cells that express PR), a key mediator ofprogestin-driven mammary tumorigenesis. In basal cells, pro-gesterone stimulates Wnt to promote basal progenitor expan-sion, proliferation and cancer precursor cells. These progenitorcell effects could explain the clinical hormone replacementfindings suggesting that progesterone increases breast cancerincidence (31). RANKþ cells were exquisitely sensitive to DNAdamage (e.g., stalled fork repair) in the BRCA1 haploinsufficientstate, with aberrant activation of RANK and NFkB (via double-stranded DNA break activation of ataxia-telangiectasia check-point kinase and NFkB essential modulator) pathways andneoplastic transformation (39). Remarkably, RANKþ (but notRANK�) BRCA1-mutant luminal progenitor cells shared amolecular profile more closely aligned with basal-like breasttumors than any other subtype (36). Analyses of human breasttissue found that cells from the luminal lineage containedprecursors to basal-like breast cancer and targeted loss of BRCA1in luminal cells (but not basal cells) produced basal-like tumors.Aberrant expression of the transcription factor SLUG can pro-mote cell fate-switching to a basal cell identity in BRCA1-mutation carriers (40). BRCA1 mutation stabilizes the protein,while mutant Slug in murine MECs prevents tumors. Both themutation of origin and order of mutations influence the pro-genitor/preneoplastic path (41).

Pharmacologic RANK-L inhibition or RANK deletion (inmam-mary epithelium) in several GEMMs markedly inhibits Brca1-driven mammary tumorigenesis (36, 37). High-level RANK-Lwith nonfunctional BRCA1 drives epithelial-mesenchymal tran-sition with invasion and correlates with high-grade ER/PR neg-ative disease and mammary stem cell number (in young breast

cancer patients; ref. 42). RANK-L/RANK signaling also can influ-ence innate and adaptive immunity (43, 44). RANK-L producedby regulatory T-cells (Treg) promotes mammary cancer and T-celltolerance to intestinal bacteria. Finally, NFkB hyperactivation inBRCA-mutant breast cancer cells appears to be associated withan immune signature (43). A second RANK-L receptor, LGR4,was just discovered and implicated in the regulation of multipledevelopmental pathways. Serum levels of osteoprotegerin (OPG),the endogenous RANK-L inhibitor, are significantly lower inBRCA1-mutation carriers (vs. controls) and levels correlatedinversely with germline BRCA1-mutation locations known toconfer highest breast cancer risk. Premenopausal women withlow OPG levels are also inversely associated with breast cancerrisk (45). Certain SNPs in the TNFRSF11A locus have beenassociated with increased RANK expression and breast cancer riskin BRCA1 carriers (37). Denosumab (a RANK-L mAb inhibitorFDA approved in 2010 with a well-established safety record fortreating postmenopausal osteoporosis and preventing skeletalevents in patients with bone metastases, espousing both efficacyand toxicity superior to bisphosphonates, which also haveimmune effects in the breast; refs. 43) blocked progesterone-induced proliferation in BRCA1-mutant human organoids andreduced breast epithelial cell proliferation and progenitorcell clonogenic potential in small pilot window trials of BRCA1carriers (36, 37). Also of interest, improved disease-free survivalwas recently reported in a randomized trial in which postmen-opausalwomen received low-dose denosumabwith anaromataseinhibitor as adjuvant therapy for hormone receptor–positivebreast cancer. Targeting RANKL directly is more selective and lesstoxic than targeting ER or NFkB (which can cause immunosup-pression) to prevent mammary cancer in the BRCA1-mutationsetting (43). Tamoxifen may further increase the risk of endome-trial cancer associated with BRCA1 mutation (46). In contrast,PR modulators (e.g., FDA-approved ulipristal acetate) have theopposite effect, suppressing endometrial proliferation in carriersand endometrial cancer development in mice (24) and can alsoblock RANK-L signaling.

Together, these studies suggest that steroid hormone regu-lation is perturbed in very early stem/progenitor cells of BRCA1carriers, creating a milieu in which breast epithelial cells arehyper-responsive to hormonal stimuli before transitioning toa hormone-independent (e.g., NFkB activated) state involvingp53 mutation and WT BRCA1 loss. RANK-L inhibition, there-fore, should work best to prevent/delay tumor onset for pre-menopausal BRCA1-mutation carriers based on the abovescience and recent clinical data indicating that risk-reducingsalpingo-oophorectomy is ineffective in this setting (47). Basedon these data, denosumab is in late-stage development for alarge-scale international breast cancer prevention trial in BRCA-mutation carriers (43), with potential secondary endpoints ofovarian and pancreatic cancer.

Fanconi Anemia (FA) is a rare hereditary syndrome character-ized by genomic/chromosomal instability, bone marrow failure,and cancer (7), and now involves 21 genes (including BRCA2/FANCD1 and BRCA1/FANCS). FA pathway required for efficientrepair of stress-induced DNA damage can lead to bone marrowfailure and has been linked to aging, HSC dysfunction, andreservoir depletion. Defects in BRCA1/FANCD1/BRG1-mediatedDNA repair and FANCM-nonsense mutations contribute tohormone-negative breast cancer. Cross-talk between FA (repairsDNA interstrand crosslinks and regulates cellular response to

Perspective




replication stress) and homologous recombination (e.g., BRCA1/2 repairs replication-associated DNA damage and protects stalledreplication forks) pathways is critical for genomic integrity.BRCA1/2-deficient tumors have a compensatory increase inFANCD2 activity, which orchestrates DNA pathway choice atreplication forks (48). FA patients have high risk of immunerelated complications (related to B- and T-cell defects) such asinfection. Loss of Fancc impairs B-cell function and antibody-secreting cell differentiation in mice through deregulating Wntsignaling. T-cell-specific conditional BRCA2/FANCD1 knockoutmice develop T-cell loss and immune dysfunction, which mayinvolve p53 activation (34). Interestingly, p53 downregulates theFA DNA repair pathway. FANCC and certain other FA pathwaygenes are linked tooxidative stress, cytokine sensitivity, and innateviral immunity. The above immunedefects andB-cell dysfunctionmay account for susceptibility to HPV (and other viral) infectionsand variable immune responses to HPV vaccines, which haveimplications for preventive cancer vaccine development. Somaticmutations or epigenetic silencing of FA genes is common insporadic breast, ovary, lung, and pancreatic cancer and leukemia.The FA pathway has also been linked to mitochondrial dysfunc-tion (49). Failure to remove damaged mitochondria can lead toincreased mt-ROS, genotoxic stress, and tumorigenesis in FA, andsomatic FA driver mutations in the sporadic setting (50).

Other hereditary forms of cancer riskMouse models of Lynch syndrome have begun to unravel key

mechanisms of the CRC predisposition by finding that butyrate,generatedby gutmicrobiota fromdietary carbohydrates, can act asan oncometabolite (51). Interestingly, butyrate can have theopposite effects in different CRC models, likely reflecting differ-ent germline backgrounds, e.g., reduced dietary butyrate (andantibiotics altering microbiota) markedly decreased adenomaand CRC development in an APCMin/þMSH2�/� mouse model.This butyrate effect was only seen in MMR-deficient, but notMMR-proficient mice. Butyrate can suppress carcinogenesis inother colonmodels (seemicrobiota discussion later). InAPCMin/þ

mice, genetically predisposed to intestinal neoplasia, celecoxib(a COX-2 inhibitor known to reduce intestinal adenoma burden)

increased gut Coriobacteriaceae, which suppressed production ofoncogenic metabolites (e.g., glycine and serine; ref. 52). CRCdevelopment was reduced in germ-free ApcMin/þ mice (comparedto conventionally housed controls) but increased after enteralFusobacterium nucleatum or enterotoxigenic Bacteroides fragilis(ETBF). Fusobacterium species have been discovered to be highlyenriched in human colorectal adenomas and potentiate intestinaltumorigenesis in APCMin/- mice, possibly through a mechanisminvolvingmacrophage recruitment and immune evasion fromNKcells (53). In this model, ETBF has been shown to induce T-helper17 cells in a B. fragilis toxin-dependent manner to reduce neo-plasia. Furthermore, IL-17promotes a pathologicmyeloid inflam-matory signature and colon tumorigenic response to ETBF, whosesecreted metalloprotease toxin cleaves E-cadherin and inducesepithelial signals to recruit Tregs that allow IL-17 polarization forearly transformation-colonized Min mice. IL-17 monoclonalantibody (mAb) and Treg cell depletion suppressed tumorigen-esis at the adenoma stage (54; see microbiota section below).Autophagy is activated in the intestinal epithelium inmurine andhuman CRC and conditional inactivation of Atg7 in intestinalepithelial cells inhibits the formation of precancers in Apcþ/�

mice, an effect requiring dysbiosis. This study reveals that inhi-bition of autophagy in cooperation with microbiota may preventCRC development in genetically predisposed patients (55).

The first real signal of benefit in early detection research inpancreatic cancer, imaging people with high-penetrance muta-tions, was recently reported (56). Unselected patients may havea very high (>15% in one clinic-based cohort) prevalence ofgermline mutations (particularly of BRCA1/2 and among Ash-kenazi Jewish individuals), most without suspicious familyhistories (57). Furthermore, precursor lesions in people withhigh-penetrance germline mutations may have a higher malig-nant potential (than other pancreas high-risk groups; ref. 58).These data are leading some centers to recommend germlinetesting for all new pancreatic cancer patients. Precedent for suchan approach already exists in NCCN guidelines for ovariancancer, where a substantial fraction of unselected patients willcarry BRCA1/2 mutations (most without consistent clinical/family histories) and screening has limited benefit (59). The

Table 1. Immunologic features of three distinct germline neoplastic pathways

Germline mechanism ofhypermutability

Characteristics ofcancers

Somatic mutations,signatures in cancers

Evidence of immunogeniccancer phenotype Precancer immune biology

DNA MMR mutations: MLH1,MSH2, MSH6, PMS2; BMMR-D

CRC, endometrial, andothers with MSI-H;pediatric CRC/adenomas,gliomas, lymphomas inBMMR-D

Hotspot microsatellites indriver genes, e.g.,TGFBR2, BAX in LS; POLE,POLD1 in BMMR-D;biallelic MSH3

MSI-induced FSPs found inassociated cancers; PD-1inhibitors active in LS,BMMR-D, sporadic MSI-H

MSI-H in precancers, e.g.,adenomas/crypt foci,IPMNs, DCIS; microbiota;FSP T-cell immunity; B2Mimmune escape

BRCA1/2 mutationsa

(HR deficiency)Breast, ovarian, pancreatic,prostate, and othercancers

Specific signatures oftandem duplications and/or deletions

Markers of immunity inBRCA1/2: breast, ovary,and pancreatic cancers

LPs, RANKL/RANK, NFkB,immunity; wild-type loss insome precancers

APOBEC3A/B chimeric deletionpolymorphism

Modest increased breastcancer risk, somatichypermutation

APOBEC-mutationalburden; hotspots withindriver genes, e.g., PIK3CA

Cytokine response,immunity genes;penetrance of immuneeffects appears high

APOBEC3 mutagenesis insporadic pre-invasivebladder carcinoma and CIN;innate immunity to infection

NOTE: Immune biology of precancers in three distinct inherited neoplastic pathways: high-penetrance MMR deficiency and BRCA1/2mutations, and low penetrancepolymorphisms of APOBEC3A/B. Cancers associated with all three pathways are associated with distinct, predictable forms of somatic hypermutability and havevarious features, suggesting an immunogenic phenotype. The PCA will be key to devising immune interception (see text).Abbreviations: BMMR-D, biallelic mismatch repair deficiency; B2M, b-2 microglobulin; CIN, cervical intraepithelial neoplasia; CRC, colorectal cancer; FSP, frameshiftpeptide; HR, homologous recombination; IPMN, intraductal papillarymucinous neoplasms; LP, luminal progenitor; LS, Lynch syndrome; MMR, mismatch repair; (highlevel) MSI, microsatellite instability.aFanconi anemia pathway (including BRCA1/2) defects associated with impaired immunity (see text).

The Precancer Atlas




development of molecular imaging techniques to detect high-grade lesions (pancreatic intraepithelial neoplasia; PanIN-3)may further improve prevention and early detection of thisfatal disease.

Immune interception may be effective in certain inheritedneoplasia settings characterized by immunogenic antigen pro-duction (Table 1). Cancers that arise in Lynch syndrome withinherited DNA MMR gene defects display a MSI-H and wide-spread accumulation of somatic frameshift mutations/neoanti-gens (60), thought to underlie the success of immune checkpointinhibitors in this disease (9, 10). Recent immune profiling studyof hereditary and sporadic MSI-H endometrial cancer found thatalthough both had stromal CD8þ T-cells, there were importantdifferences in the microenvironment (e.g., only sporadic caseshad PD-L1þ cells; ref. 61). A high degree of MSI-H CRC isassociated with intense T-cell immunity/infiltrates due to numer-ous frameshift mutations and truncated proteins. Translating thisbreakthrough advance in immunotherapy to the prevention set-ting is supported by evidence of early immunosurveillance(T-cells specific to MSI-related neoantigens (62)) in "healthy"Lynch syndrome carriers. Prophylactic HPV vaccine success couldtranslate to this mutation carrier setting with vaccines targetingpredictable frame shift mutation-derived peptides. Immuneescape in Lynch syndrome (but not sporadic MSI-H neoplasia)-associated CRC and adenomas can be due to b-2 microglobulinmutations (see below).

Universal CRC tumor testing for MMR deficiency to screenfor Lynch syndrome (LS), a paradigm-changing approach foridentifying inherited cancer risk, has become standard practiceand the main trigger for confirmatory germline testing. 2015 USestimates are that universal tumor screening will identify�21,000 people with LS, producing substantial public healthbenefits (cancers prevented, lives saved and cost effective). Thisbenefits both the patient and at-risk family members for inten-sive and early screening and aspirin or potentially other NSAIDprevention (63–65). The profound activity of immune check-point blockade in MMR deficient tumors (11) has added tothe enthusiasm of universal screening in this setting. Theestimated prevalence of LS in the general U.S. population is1:280 (1.1 million). NGS germline testing, however, has cre-ated a genetic conundrum and major clinical challenge byidentifying and reporting missense, small insertions, deletions,or splice variants of uncertain significance (VUS) in �30%(�300,000 people in the U.S.). As chemo- and immune-pre-vention continues advancing in this disease, the developmentof new tools to clarify the functional status of VUS in LS is apressing unmet need. In silico systems biology analyses haveproduced encouraging preliminary results (63), but a nationalconcerted effort involving MMR and biochemistry experts willbe required to resolve the VUS issue, which is also affectingother germline mutation testing (e.g., BRCA1/2). Leveragingthe Lynch syndrome demonstration project recommended bythe Blue Ribbon Panel (BRP) for the Cancer Moonshot will beimportant.

This tumor testing approach is being evaluated in newly diag-nosed lung cancer, where the �1% of patients with tumor EGFRT790Mmutationhave a very high risk of carrying germline T790Mmutation (66). Unaffected germline carriers routinely havelung nodules even in young nonsmokers and may benefit fromT790 inhibitor chemoprevention. These high-risk families couldbe a valuable complement to population-based cohorts

for studying lung cancer development in nonsmokers (67). PanTCGA analysis of tumor sequencing data (>4,000 tumors, 12cancer types) revealed rare germline mutations (e.g., BRCA1/2,FANCM, MSH6) in 4–19% of cancer types, unselected for familyhistory and associated with increased somatic mutation frequen-cies (68).Germline variants and somatic events are also intricatelylinked, with specific haplotypes of JAK2 V617F in myeloprolif-erative neoplasms (MPN; ref. 69), EGFR exon 19 microdeletionsin non-small cell lung cancer (70), and germline variation influ-ences on gene expression in breast cancer risk loci (71).

Translating GWAS to the clinic have been challenged bythe small-effect sizes of risk variants (see below). Recentpan-cancer study (22 tumor types, 5954 tumors) integratingcommon genotypes (412 germline loci) with somatic changesfound that inherited variation influenced somatic evolution ofneoplasia by directing where (organ site) and how (whichgenes are impacted transcriptionally) cancer develops –

highlighting the remarkable prospect of anticipating and inter-cepting key early events during tumor development (72). Thisgenome-wide analysis of germline-somatic interactions amongcancer patients identified common germline alleles that hadvery large effects on somatic events. New associations includeda 15q22.2 allele with >10-fold increased somatic alteration ofGNAQ and an intronic SNP in RBFOX1 with >8-fold increase inmutation rate of SF3B1 affecting RNA splicing. Interestingly,some frequently somatically mutated genes (e.g., TP53 andPIK3CA) were not found to be influenced by common germlinevariants. Recent studies, however, found a germline variantwhich strongly influenced somatic PIK3CA-mutation frequency(73) and another found an African American-specific SNP inthe TP53 gene, which impairs p53 tumor suppressor function(74). As broad NGS of blood and neoplasias become morewidely used and germline-somatic relationships comprehen-sively mapped, shared and distinct germline and/or somaticevents can be integrated into the PCA and exploited as pre-vention targets (7, 64).

GWAS have contributed to expanding catalogs of impli-cated genes and pathways for many multifaceted human dis-eases and are beginning to shed light on shared and uniqueetiological and pathological disease components. Combininglarge-scale GWAS findings across cancer types (breast, ovarian,and prostate) and using fine-mapping pathway analysis andpolygenic risk scores (PRS) discovered cross-cancer risk locihas the potential to shed light on shared biology under-lying these hormone-related cancers (75). While the low pen-etrance of most GWAS loci has limited clinical translation, thecombined effects of such SNPs to create robust PRS (64) maybe more useful clinically, especially, for example, as modifiersof high-risk BRCA1 and BRCA2-mutation carriers given thateven small relative risk changes translate into large absoluteeffects. Most general population breast cancer SNPs are asso-ciated with ER-negative or -positive disease and, respectively,in BRCA1- or BRCA2-mutation carriers. Similarly, only generalpopulation loci (e.g., 19p13.11) associated with high-gradeserous ovarian cancer modify risk of ovarian cancer in BRCA1-and BRCA2-mutation carriers, where tumors are of thishigh-grade subtype (64). The new OncoArray approach toinvestigate genetic architecture of common cancers, with densemapping of loci associated with single or multiple cancers,pleotropic effects and cancer related traits, will also build onfirst-generation GWAS findings (76). The first genome-wide

Perspective




copy-number variants (CNVs) association study of BRCA1carriers validated a CNV deletion at 19q13.2 with decreasedovarian cancer risk, matching a region displaying strong regu-latory potential in ovarian (but not breast) tissue (77). Finally,the ability of GWAS to discover novel cancer genes/pathwaysunderlying the observed risk (78) is now being exploited forfuture drug development or repositioning, aided by experi-ments in relevant preclinical models. These GWAS-initiatedefforts have already led to prevention-relevant drug targets,IL-17 and ESR1 (64).

A key challenge is that many GWAS-identified loci are notnear known coding or regulatory regions, leaving associatedmechanisms and functions unclear. Linking susceptibility var-iants to their respective causative genes and cell-specific regu-latory elements thus remains a high priority in order to realizethe full potential of association studies. For example, sections ofDNA called "enhancers" are increasingly found to bemutated ordisrupted as major causes of human cancer, though they havebeen difficult to locate. A recently developed computationalmethod greatly improves regulatory element prediction basedon tissue-specific local epigenomic signatures, a major advancefor cancer genomics (79). Deep characterization of transcrip-tional regulation of molecular events will greatly advancefunctional studies of human disease variants, identifying noveldisease mechanisms and prevention opportunities. CertainSNPs underlying cancer risk are linked to hypermutability andimmune activation (64; Table 1) and intestinal barrier function(discussed below). Germline variants can affect endogenousmutational signatures such as an APOBEC3 copy number poly-morphism. An APOBEC3A/3B-deletion allele (discussed morelater) confers breast and ovarian cancer risk and innate immu-nity to infection, suggesting strikingly disparate effects of thisSNP on infection, mutagenesis, and cancer (80, 81).

Mitochondrial biology and genetics in cancer predispositionMitochondrial DNA (mtDNA) with its mutations and poly-

morphisms is a relatively underappreciated field in cancerresearch. Human mtDNA is maternally inherited (and mappedinitially from Africa; ref. 82) and encodes 37 genes: 22 transferRNAs, 2 ribosomal RNAs and 13 protein subunits of the electrontransport chain (ETC) complexes and ATP synthase (mtOXPHOSproteins), essential for respiration. There are several mtDNAcopies per mitochondrion and hundreds of mitochondria percell. Generally, neoplastic cells possess functional mitochondriaand retain the ability to conduct oxidative phosphorylation.In fact, targeted depletion of mitochondrial DNA can reducetumorigenic potential in vivo (83). While it has long been knownthat somatic mtDNA alterations are frequently acquired duringoncogenesis (84), emerging data indicate that methylation andinherited mtDNA variants influence multiple innate mitochon-drial functions, including reactive oxygen species (ROS) produc-tion and redox control, signal transduction and epigenome sys-tems, autophagy, apoptosis, and immunity (82). Furthermore,mtDNA genes are intimately linked with �2000 nuclear genesencoding proteins that function within mitochondria, which canproduce Mendelian patterns of inheritance.

Inherited deleterious missense alterations in mtDNA genes,such asND6 andCOI (cytochrome oxidase subunit I), which codefor subunits ofOXPHOS complexes I and IV, have been associatedwith risks of various cancers. Inherited mutations in the COI gene(associated with increased ROS production, which contributes to

tumorigenesis) are associated with prostate cancer risk and mayexplain increased risks in African American men; certain AfricanmtDNA lineages harbor COI gene variants that may contributeto risk of other cancers among African Americans (85–87).mtDNA variants have been associated with risks of ovarian,bladder, breast, endometrial, and HPV-infection and cervicalcancers, among others (82, 84, 88–92). The progression ofnonalcoholic fatty liver disease to nonalcoholic steatohepatitis(NASH), which predisposes to hepatocellular carcinoma, hasbeen shown to be associated with a mtDNA SNP in the mt-Atp8gene (a subunit of OXPHOS V, ATP synthase). This variant hasprofound effects on hepatic lipid and acylcarnitine metabo-lism and susceptibility to high-fat diet-induced NASH (93).Generating preclinical models of these and other inheritedmtDNA mutations (94) will be critical to probing the contri-bution of mitochondrial biology to inherited cancer risk.

Deleterious alterations inmtDNA are inherently heteroplasmic(harboring amixture ofmutant and wild-typemtDNA) with highlevels of these severe mutations being lethal. Since mtDNAtransmission duringmitosis is the result of stochastic distributioninto daughter cells, milder mtDNA polymorphisms can shift tobecome predominantly enriched within individual cells andcloser to pure mutant (homoplasmy), potentially contributingto neoplastic transformation. The importance of this phenome-non for cancer predisposition has been demonstrated in a ped-igree in which a mtDNA complex IND5m.12425delA frameshiftmutation is present in homoplasmy in a nasopharyngeal onco-cytic tumor, which was inherited as a germline mutation, trans-mitted at lower heteroplasmy levels (5–10% mutant), and thusmasked by wild-type mtDNAs. Shift to homoplasmicND5muta-tion occurred exclusively in tumor cells and correlatedwith lack ofthe ND6 subunit, indicating that complex Imutationsmay have aselective advantage. Thus, while the transmission of the mutantmtDNA in this pedigree was phenotypically silent, the chanceincrease of the mutant mtDNA in somatic cells caused oncocytictransformation (95).

In contrast to Mendelian genetics, the heteroplasmic mtDNAgenotype is continuously changing during successive cytokine-sis to generate cells with varying oncogenic potential (82).Widespread heterogeneity has been reported in the mtDNA ofnormal human cells and heteroplasmic variants among differ-ent tissues within the same individual, highlighting the exis-tence of composite mixtures of related genotypes rather than asingle genotype. Mechanistic study of the regulation of mtDNAheteroplasmy may yield novel prevention insights. mtDNA ishighly polymorphic due to its very high mutation rate, greaterthan an order of magnitude higher than the nuclear genome,and harboring functional variants that can be beneficial ordeleterious depending on context. A subset of mtDNA variantscauses subtle changes in OXPHOS, which can modulate inflam-mation, stress, autophagy, and oncogenic responses to diet andother factors (82, 86, 96). Those functional mtDNA variantsthat were beneficial (adaptive) in a particular environmentincreased in number and gave rise to descendant mtDNAs,which share the 'founders' beneficial variant. Migration (orother major changes in diet, stress, etc.) can make previouslyadaptive variants become maladaptive and predisposed to awide range of common diseases (82).

Altered energy metabolism is now regarded as one of thehallmarks of cancer (6, 83). Recent murine work revealed pro-found influences of subtle changes in mtDNA genetic

The Precancer Atlas




background (haplotype/variation) on obesity, aging, and can-cer (97–101). Mitochondria are essential for cancer progres-sion; however, their role in tumor development has onlyrecently been confirmed. Murine study highlighted the effectsof mtDNA background on tumorigenesis by examining PyMTtransgenic mice (inherently predisposed to developing breastcancer) with identical nuclear genomes but varying mtDNAgenome backgrounds. The mtDNA background influencedboth the latency and progression of the primary breast tumors(97). This concept was confirmed and extended mechanistically(in different mouse strains), further indicating the substantialmtDNA haplotype influence on obesity and aging – two majorcancer risk factors (100). In normal mice, mitochondrial cat-alase transgene (mtCAT) reduces mitochondrial ROS produc-tion, somatic mtDNA mutations, and increases longevity (98).When mouse mtCAT transgene was crossed with PyMT, theincidence of invasive breast cancer was greatly reduced (99).Genetic or pharmacologic (metformin) disruption of mito-chondrial respiration increased autophagy and prevented can-cer development in a mouse model of Li-Fraumeni syndrome.Furthermore, in a pilot study of Li-Fraumeni patients, metfor-min was shown to decrease tissue mitochondrial activity andreproduced cell-signaling results observed in the mouse model,effects known to give rise to rhabdomyosarcoma, a componentcancer of this syndrome (102). Finally, a recent study estab-lished a mechanistic link between tumor formation and mito-chondrial respiration, and showed that mtDNA acquisitionoccurs via trafficking of whole mitochondria (103).

Adding to the tissue- and geographic-specific contextualbasis of themt effects discussed above, emerging data also suggestintricate communication between the nucleus and mitochondria(96). For example, nuclear BRCA1 has been found in the mito-chondria, where it may play a role in maintenance of mt genomeintegrity and DNA repair. Metformin beneficial effects onmtCOI in BRCA1 carriers was discussed above (29). Murinemodels with germline mutations in the nuclear gene SUV3,which encodes for amtRNA helicase, are characterized bymarkedsomatic mtDNA instability, hypermutability, shortened lifespan,and various cancers – a unique model to assess mitochondrialgenomic instability in cancer predisposition. Clinical relevancewas shown by reduced SUV3 expression in two independentcohorts of human breast cancer (104). SOD (mt antioxidantfunction) nuclear DNA germline mutations function in the mito-chondria and heterozygous Sod2 mice develop pulmonary fibro-sis and lung cancer. Mutations in nuclear DNA genes influencingtransformation involve some of the same targets/mechanismsaffected by mtDNA – TETs, succinate, fumarate, NRF2, anda-ketoglutarate dioxygenases (83, 96, 97, 104).

Mitochondria may also be intimately involved with T-cellimmune surveillance, since T-effector cells are more glycolyticwhile Treg cells are more oxidative. Within neoplastic cells,glucose is converted to lactate (which promotes inflammation,angiogenesis and tumorigenesis), thus inhibiting T-effector func-tion. Treg function is enhanced, which further inhibits the T-effec-tor cells, and suggests that immune rejection of neoplasiamight be boosted by mild complex I inhibitors such as metfor-min, whose effectiveness should be increased in neoplastic cellswith partial OXPHOS dysfunction (105). Mitochondria canalso influence the inflammasome, innate immunity, IL-1b andNFkB inflammatory pathways (96, 106). Certain mtDNA altera-tions modify (lower) risks of breast cancer in germline BRCA2

mutations (107). mt ETC gene variation may help explain breastcancer risk in BRCA1/2-negative women with strong family his-tory (108). Future GWAS integrating both nuclear andmitochon-drial data will provide a more comprehensive germline-somaticlandscape.

Big Genomics Data of PremalignantSomatic Tissues

The collection and analyses of NGS big data are beginningto provide biological insights into cancer prevention and earlydetection. It is worth noting that, in addition to comprehensiveanalyses of "big genomics data," several recent studies havealso examined cancer microbiomes (reviewed in (109, 110)),transcriptomes (111, 112) and epigenomes (reviewed in (113,114)). In addition to big data generated from somatic sequenc-ing efforts, GWAS has involved over one million cancer patientsworldwide across most organ sites identifying �3000 cancer-related genetic associations (115) and has been studied in someprecancers such as Barrett's esophagus (116–118), colorectaladenomas (119, 120), DCIS (121) and hematologic prema-lignancies (below). A recently discovered germline mutation infamilial Barrett’s esophagus may be involved in esophagealmaturation, consistent with GWAS findings (118).

The genome of a malignancy can be examined as an arche-ological record bearing the cumulative imprints of all mutationalprocesses that have been operative throughout the cellular lineagebetween the fertilized egg and cancer. Each mutational processleaves a characteristic imprint, termed mutational signature,which can change over time, and almost all mutational signaturesdetected in a cancer genome have been imprinted duringthe precursor phase of a cancer cell (122; Fig. 1). Examinationof the cancer genomes from >12,000 patients has revealedmore than 30 distinct mutational signatures, related to endoge-nous processes and environmental exposures, such as UV-light,aflatoxin, and tobacco (cancer.sanger.ac.uk/cosmic/signatures).Some of these signatures have already been used for identifyingthe presence of specific carcinogens, including aristolochic acid,one of the most potent known human carcinogens – a chemicalpresent in certain plants still in use even today especially inChina – with global public health risks of urologic and hepaticcancers (122). Mutational processes can cause clonal evolutionin normal, at-risk tissue, including skin, lung, kidney, brain,breast, fallopian tube, and intestine epithelium (111, 123–127;see below). Somatic mutation burden was age- and tissue-depen-dent and much greater in the mitochondrial vs. nuclear genome(123). Recent discovery of a novel mutational process linkingcellular lineage and cancer hasmajor implications on the study offield carcinogenesis, prevention, and early detection research,including liquid biopsies (124). It will be important for the PCAto incorporate both premalignant and normal-aged tissues withthe goal of identifying relevant mutational signatures that mayprovide important clues into premalignant oncogenesis, preven-tion, and interception. However, only half of the currently knowncancer signatures have unknown etiology. To address this andidentify new signatures, a large-scale initiative recently funded bya UKGrand Challenge Award will use NGS to identify mutationalsignatures from well-annotated samples from >5000 cancerpatients from five continents, with validation in experimentalsystems. This work will provide new preventive and global publichealth opportunities (122).

Perspective




Another set of widespread and extensively reported endog-enous mutational signatures are those attributed to ectopicactivity of the APOBEC family of deaminases (122). Examina-tion of more than 10,000 specimens from 36 distinct cancertypes revealed that signatures are found in more than 30%of cancer samples and account for approximately 15% of allsomatic mutations across these cancers. APOBEC3B expressionhas been linked to oncogene-induced replication stress andmutational signatures are especially strong in bladder andcervical cancer where they account for more than 75% of allsomatic mutations. In cancers of the cervix and oropharynx,these APOBEC mutational signatures are triggered early by HPVinfection (122). A recent study of APOBEC3A/B enzyme struc-tures revealed conserved features that may be useful for design-ing APOBEC inhibitors that could reduce mutation burdenand cancer (e.g., bladder) risk caused by these enzymes(128). The importance of APOBEC3B (A3B) has been ques-tioned by finding A3 signature mutations and cancer (e.g.,breast) risk in patients carrying an APOBEC3A/3B polymor-phism characterized by a 30-kb deletion that eliminates A3Band creates an A3A–A3B chimera (ref. 81, discussed above).Paradoxically, this A3B-deletion SNP leads to increased A3Aactivity thought to offset this deletion SNP and underlie breastcancer risk, A3mutation signatures, germline copy number, andimmune activation. A recent report investigating this enigma,however, strongly implicated APOBEC3H haplotype I (and notA3A) and suggested that A3B and A3H-I together explain thebulk of A3 signatures in cancers globally (129).

Multiple mutational signatures reflect failure of differentDNA repair pathways. Disruptive germline polymorphisms inMC1R, contributor to phosphorylation of DNA repair proteins,have been associated with increased UV somatic mutationburden and skin cancer risk (130). A specific mutational sig-nature, associated with both germline and somatic BRCA1 or2 mutations, is related to marked increases in the rate of pointmutations (131) and observed in breast, ovarian, pancreatic,gastric, and esophageal cancers (even those without BRCA1 or2 mutations; refs. 132–137), associated with markers of immu-nity in subsets of the former three cancers (Table 1), suggestinga potential role for immune-based prevention against suchcancers. A mutational signature reflecting the accumulation ofunrepaired reactive oxygen species, mainly 8-oxoguanine, hasbeen identified in CRC and adenomas arising in individualswith pathogenic germlineMUTYHmutations, which cause baseexcision repair (BER) defects (138). Additionally, a failure oftranscription-coupled nucleotide excision repair (NER) due toERCC2 somatic mutations in preinvasive bladder neoplasia hasbeen shown to exhibit a specific mutational signature (139).Germline defects in other NER genes can cause Xerodermapigmentosum, a rare autosomal recessive genetic disorder asso-ciated with UV-induced DNA damage, mutational signatures,and very high risk of non-melanoma skin cancer, which can bereduced using bacterial DNA repair enzymes or nicotinamide(140, 141), which can prevent UV-induced immune suppres-sion and enhance DNA repair.

Mutational signatures responsible for the unavoidable back-ground mutation rate in somatic cells have been identified.Notably, two unrelated mutational signatures have been foundto act as endogenous mutational "clocks," characterized by accu-mulating somaticmutationswithin all normal somatic cells of thehuman body with the progression of age (142, 143). One of these

mutational signatures has been attributed to spontaneous deam-ination of 5-methylcytosine in the context of CpG (its rate of"ticking" appears to be influenced by cellular division), while theetiology of the second clock-like signature remains unknown.Interestingly, a recent study demonstrated the increased rate ofone mutational clock to be mechanistically linked to tobaccosmoking (144). The somaticmutation loads in single-cell lineagesprovide information about an individual's lifetime history ofmutagenic exposure and the impact of intrinsic factors on muta-genesis. Expanding this work to precancers, more cell types andlarger populations in the PCA would further refine estimates ofthe rates of somatic changes in human genomes. Understandingthe contributions of environmental and endogenous mutagenicprocesses to somatic mutation loads is fundamental to developpreventive strategies.

Analyses of omics data from precancers and field defects arebeginning to emerge. Despite the relatively small sample sizeswithin such analyses, cross-sectional, precancer/cancer pairstudies suggest that many precancers share genomic alterationswith their respective invasive cancers, including prostate (145),ductal and lobular breast cancer (146, 147), pancreas (148),head and neck cancer (149), non-melanoma skin (126), mel-anoma (150), lung adenocarcinoma (151), and colorectalneoplasia and suggest that early lesions are often polyclonal(3, 138). Genomic, transcriptomic, and epigenomic alterationshave been detected in normal tissue fields as discussed above(123–127) and precancers. In-depth deep sequencing analysisof ongoing clonal competition in histologically normal-appear-ing eyelid epidermis (extensive somatic mutations, largely ofUV signature) suggested initial exponential growth of a clonalpopulation, due to acquisition of a driver mutation, followedby density-dependent or immune growth constraint (126), anissue relevant to other sites discussed below (e.g., clonal hema-topoiesis). Another study demonstrated that actinic keratosis, askin precancer, was closely related to squamous skin cancerby multiple genomic measures. Analyses of small adenocarci-nomas within high-grade adenomas found substantially morechromosome level changes in the cancer and suggestedthat gain of 20q was associated with transformation, consistentwith NGS of FAP adenomas (3). NGS revealed high mutationburdens in morphologically normal prostate tissue distantfrom the cancer, reflecting clonal expansions, and indicatingthat the underlying mutational processes in normal tissuewere also operative in cancer (145). Extensive data from manysites link transformation with DNA repair defects, genomicinstability, and replication stress (152). Barrett's esophagusis the best-studied epithelial precancer from an NGS, geno-mics, transcriptomics, and big data perspective (132, 152–156), with five GWAS (116, 117), including the most compre-hensive evaluation of inflammation-related germline variationsuggesting that variants in MGST1 influence disease suscepti-bility (117). Furthermore, recent study revealed that gramnegative microbiota in the esophagus produce lipopolysaccha-ride (a TLR4 ligand), which both primes and activates theNOD-like receptor 3 inflammasome to secrete IL-1b, IL-18 andother proinflammatory cytokines contributing to inflamma-tion-mediated oncogenesis in Barrett’s esophagus (157). Bar-rett's esophagus/esophageal cancer pairs revealed that the over-all somatic mutation rate (single-nucleotide variations) waslower in Barrett's esophagus than esophageal cancer but higherthan that of several invasive cancers (e.g., breast cancer,

The Precancer Atlas




multiple myeloma [MM]) and exome sequencing found thatmost (�80%) recurrently mutated genes in esophageal cancerwere remarkably similar to the matched Barrett's esophagus(132). A subsequent study assessed mutation order in theBarrett's esophagus-esophageal cancer sequence (155). Onlytwo genes, TP53 and SMAD4 displayed a stage-specific muta-tional pattern with TP53 present in high-grade dysplasia andcancer and SMAD4 only in cancer. Another study (153) per-formed whole genome sequencing on paired Barrett's esoph-agus and cancer samples with a Barrett's esophagus componentthat included biopsies over space and time. The analysesrevealed numerous somatic mutations, small insertions, anddeletions at all disease stages and that copy number increasesappeared to drive neoplastic transformation to esophagealcancer (156). In addition, the results indicate that Barrett'sesophagus is polyclonal with evidence of branched evolutionco-occurring with distinct localized clones. See longitudinalsection below for Barrett's esophagus SCNA data.

Two recent large-scale NGS reports of mtDNA in cancer(>2,000 human cancer specimens, 30 tumor types) identifieda mutational signature with unique heavy strand-specific C > Ttransition. More importantly, this missense mutational signa-ture was considered neutral (analogous to passenger mutationsin nuclear DNA), not compromising mitochondrial function(158). One of these studies further refined the mtDNA muta-tional map with matched transcriptome sequencing (RNA-seq)data (159). Although DNA/RNA allelic ratios generally wereconsistent, somemutations inmt-tRNAs displayed strong allelicimbalances caused by accumulation of unprocessed tRNA pre-cursors, indicative of impaired tRNA folding and maturation,which underlie a range of diseases. Both studies found a selec-tive pressure against deleterious coding mutations affectingoxidative phosphorylation, indicating that tumors require func-tional mitochondria. Unexpectedly, known dominant muta-gens, such as cigarette smoke or UV light, had a negligible effecton mtDNA mutations. Another new study has reported signif-icant correlations between mtRNA-Seq and mtDNA copy num-ber, with some important exceptions (e.g. MT-ND5 and MT-ND6) (160). mtDNA mutations are frequent in Barrett's esoph-agus without dysplasia and have been used to characterizegenetic lineages that assess clonal relationships, e.g., betweenBarrett's esophagus and esophageal squamous cells (161).Clonal expansion of mtDNAmutations can result in mitochon-drial dysfunction, such as decreased ETC enzyme activity andimpaired cellular respiration. NGS of mtDNA of oncocytomas,which are rare benign tumors of epithelial cells defined byexcessive amounts of mitochondria, has identified a pathogenicmutation signature that compromises the overall function ofthe mitochondria, proposed to serve as a metabolic barrierfor these benign tumors, and perhaps precancers, progressingto malignancy (162). A complex biochemical shift encompass-ing intra-lesional lactate metabolism helps drive Barrett's neo-plastic progression, possibly involving microbiota change topredominantly gram negative flora (163).

In addition to the results above, a systematic approach toclassify cancers using transcription profiles at both bulk tumorsand single-cell resolution has been described (see below).These profiles not only provide molecular bases for classifyingcancers with shared transcriptional programs across differentcancer types but also characterize heterogeneity that existswithin individual neoplasias (164, 165). Whole transcriptome

profiling using RNA-seq, pathway enrichment, and functionalassays of Barrett's esophagus found novel cell-cell communi-cation, with normal epithelial cells sensing and dramaticallysuppressing dysplastic cell behavior (e.g., motility, signalingpathways). These effects are distinct from the stromal andimmune cell microenvironment effects. Downregulated TGFb,EGF, and Wnt pathways associated with the differential tran-scriptional profiles observed in the dysplastic cells in co-culture(normal and dysplastic Barrett's epithelial cells, which oftencoexist in vivo; ref. 156). Single-cell approaches would allowanalysis of different subpopulations of cells within highly vari-able epithelial, immune, stromal, and other microenvironmentcellular components surrounding the neoplasias (Figure 1; refs.156, 164, 165). Furthermore, oncogenic pathways and devel-opmental- and immune-based gene expression signatures canbe used for "pathway/phenotype"-based molecular character-ization (166, 167).

Recently, a novel analytic approach to define oncogenic statesand produce functional maps of cancer has been established.This serves as a framework for combining experimental andcomputational strategies to deconvolve oncogenic pathways/signatures derived from oncogene activation into transcriptionalcomponents that can be used to determine oncogenic states. Bymapping precancers and cancers onto distinct oncogenic states,the resulting functional map can be used to characterize howthese states relate to omics features of NGS mutations, copynumber alterations, gene and protein expression, gene depen-dencies, and biological phenotypes; and to predict which inter-ventions are more likely to have a significant effect (168).This approach has been used to effectively map cancers withaltered KRAS/MAPK pathways into divergent functional states.Studies in pancreatic oncogenesis highlight the need for bigdata approaches to interpret elaborate KRAS mutation subtype,Hippo and other pathway interactions, profound effects oncell metabolism, DNA repair, immunity, mitochondrial biology,and distinct precursor pathways (169). Mutant Kras in pancreaticacinar cells induces expression of ICAM-1 to attract macrophagesand drive PanIN development: direct early cooperative mechan-isms between driver mutations and inflammatory environments(170). Evenmast and B-cells can initiate and promote pancreatictumorigenesis (171, 172). For example, primary human andmouse models found B-cell infiltration in proximity of PanINlesions, due to stromal secretion of the B-cell chemoattractantCXCL13 (171). Another study found highly expressed HIF1a inPanINs; deletion of HIF1a increased secretion of CXCL13 andrelated attractants and accelerated malignant transformation.Depletion of B-cells reduced PanIN progression (172). Thesedynamic maps can continually integrate new data, be general-ized to consider germline and somatic networks and interactions(173), and dissect the close interchange with the immunemicroenvironment. Integrating functional genomics data, suchas those described above, to the maps of oncogenic states willprovide further insight into the cellular contexts in which geno-mic alterations contribute to malignant transformation.

EpigeneticsPrevious work has yielded only a limited big data perspec-

tive of the neoplastic epigenome, primarily in hematologicneoplasia, where chromatin modifiers are in general amongthe most frequently mutated in cancer (114, 174). Most studies

Perspective




have focused on performing functional analysis on a few genesin a limited number of samples as reviewed below. Widespreadepigenetic field defects have been observed in apparently nor-mal breast tissue located adjacent to breast cancer (175)and also associated with inflammation-related cancers, suchas Helicobacter pylori-induced neoplasia (in which AID has beenimplicated; ref. 127), where NGS has revealed more cancerpathway-related genes affected by DNA methylation than bygenetic alterations (176). Field defects (involving methylationof MGMT and ADAMTS14 and cohesion SA1) in normal colontissue is more frequent in African-Americans than Caucasians,possibly providing insight into CRC racial disparities (177).The ten eleven translocation (TET) enzymes oxidize 5-methyl-cytosines (5mCs) and promote locus-specific reversal of DNAmethylation (discussed below).

An epigenetic mitotic clock was developed using a novelmathematical approach. A key feature underlying the construc-tion of this clock is the focus on Polycomb group target promoterCpGs, which are unmethylated in many different fetal tissuetypes, thus allowing defining a proper ground state from whichto then assess deviations in aged tissue. By correlating the tickrate predictions of this model to the rate of stem cell divisions innormal tissue, as well as to an mRNA expression-based mitoticindex in cancer tissue, this model approximates a mitotic-likeclock. The epigenetic mitotic clock-like signature exhibits a con-sistent, universal pattern of acceleration in cancer in normalepithelial cells exposed to a major carcinogen. Epigenetic clonalmosaicism is maximal before cancer emerges. Unlike the muta-tional clock-like signatures discussed above, this epigeneticclock is based on clinical DCIS and lung CIS progression to cancerand normal at-risk tissue; a concrete example of a molecularmitotic-like clock that predicts universal acceleration in precancer(178). Smoking was associated with an increased rate of thismutational clock. Another approach to intratumoral heterogene-ity analyzed DNA methylation patterns at two genomic loci thatwere assumed to have no role in gene regulation, in contrast todriver methylation changes. Methylation at such neutral loci wereunlikely to be under selective pressure and therefore, couldserve as a "molecular clock" to measure mitotic divisions basedon the higher error rate of DNAmethylationmaintenance relativeto the error rate of DNA polymerase (179).

Aberrations of the epigenetic modulator TET2 are amongthe first alterations identified in several hematologic prema-lignancies. The TET family of proteins was originally nameddue to the TET1 fusion partner in mixed-lineage leukemia(MLL)-rearranged AML (see "biochemistry" subsection below),however, this translocation is rare, and its significance inleukemogenesis is unclear. In contrast, TET2 mutations arefound in premalignant HSCs and aged healthy individuals(180) with propensity to transform (see clonal hematopoiesisbelow). Disruption of TET2 in mouse models increases HSCproliferation and clonal expansion, prone to additional onco-genic events generally required for malignant transformation(177). Mouse models found that co-occurring Tet2 disruptionwith Asxl, Ezh2, or Jak2 V617F results in MDS or MPN. Recur-rent dominant point mutations in IDH1 and IDH2 are earlyevents in some hematologic neoplasias that lead to loss of TETactivity and other epigenetic changes (181). In addition, TET2,IDH1, and IDH2 mutations are frequently observed in lym-phoma precursors (182–184), and the frequency of TET loss-of-function (which can drive hematologic transformation) in

these settings supports testing TET activators. TET modulators(185), can enhance antigen presentation, increase IL-6 produc-tion by macrophages (186), affect Tregs (187), and alterexpression of endogenous retroviruses, cancer testis antigens,and stem cell antigens in premalignant lesions resulting inenhanced immunogenicity.

Another epigenetic mechanism found to be important inpremalignant biology involves RNA editing by ADAR enzymes(188–190), which results in adenosine-to-inosine conversionof RNA thereby inducing virtual adenosine-to-guanine muta-tions (since inosine bears molecular resemblance to guanine;ref. 189). Depending on whether the editing events occur incoding regions or 30 UTRs, ADAR-mediated editing of mRNAscan result in post-transcriptional protein coding mutationsor altered susceptibility to microRNAs (190). Germline varia-tion of ADAR genes may influence ovarian cancer suscepti-bility (188). ADAR1 editase activity has been implicated in theoncogenic transformation of premalignant progenitors thatharbor clonal self-renewal, survival, and cell cycle-alteringmutations (191, 192), such as in hepatocellular carcinoma pre-cursors, where aberrant RNA editing of AZIN1 has been foundto be a key oncogenic driver (189–193). ADAR1 is associatedwith CIN development in transformation (194) and appears toplay a critical role in cancer stem cell-related diseases (195).Inflammatory cytokine networks and JAK2/STAT signaling acti-vate ADAR1 during relapse/progression in leukemia stem cellrenewal, linking RNA editing to the development of innateimmunity and potential preventive activity (112). Finally, studyof ADAR1 regulation of APOBEC3 in neoplasia will be critical,potentially suppressing hypermutation and immunity (196).

Emerging data also suggest that some premalignant lesionsmay progress to cancer via fundamental epigenetic/transcription-al reprogramming to a progenitor-like state required for drivermutations to induce tumorigenesis (197). The role of BRAFmutations in benign nevi is a major historical conundrum(198). BRAF V600E and other mutations in the MAPK pathwayare very early events in melanoma development substantiallyenriched in benign lesions. Mutations in other common drivergenes are found only in intermediate or later stages of diseasesuch as CDKN2A loss, TERT promotermutations, or the SWI/SNFchromatin modifiers ARID1A, ARID2, or SMARCA4. In the BRAFV600E zebrafish model of melanoma, deletion of p53 promotesthe nevus-to-melanoma transformation, but melanomas remainsurprisingly infrequent considering that all of the cells bear boththe oncogene and tumor suppressor loss (199) – a feature thatreplicates the phenomenon of "field defect" in human tumors.Studies in BRAF V600E/p53-null zebrafish now suggests thatinitiation of malignant transformation within such a "cancerizedfield" requires fundamental epigenetic reprogramming of thesepremalignant cells into an embryonic state via transcriptionfactor-mediated reactivation of genes typically expressed onlyin neural crest progenitor cells (197). This reprogramminginvolves binding of multiple transcription factors and generationof "superenhancer" regions. Engineered models and epigeneticmechanistic work suggest key roles of p15 loss and autophagy(overcoming senescence) in promoting BRAF V600E-mutanttransformation to melanoma (200). Deletion of Atg7 inhibitstumorigenesis, likely via a mitochondrial mechanism (201).

Similarly, mouse model research demonstrated that basal cellcarcinomas, known to be driven by oncogenic signaling in thehedgehog pathway, only originate from stem cells located in very

The Precancer Atlas




specific areas of the murine epidermis, which are reprogrammedback into amore progenitor-like state before progressing to cancerpossibly involving EMT (202, 203). In the pancreas, the tran-scription factor KLF4 is a ductal fate determinant, inducingcellular identity change to a duct-like lineage and initiatingacinar-cell reprogramming during early premalignancy (204). InKras GEMM, Klf4 deletion dramatically reduced PanIN number,while Klf4 overexpression did the opposite. Acinar cell repro-gramming can also involveNotch, YAP, TAZ, and c-MYC. Geneticablation of Smoothened in stromal fibroblasts in a Kras GEMMincreased the early premalignant acinar-to-ductal metaplasia andPanINs (205). Mutant Kras cooperates with impaired JNK signal-ing and induces mitochondrial oxidative stress in acinar cellsto accelerate PanIN development. Like the zebrafish melanomamodel, these experiments provide further evidence that the ear-liest stages of tumorigenesis are characterized by reprogrammingto a more embryonic cell state. Such data suggest that tumor-initiating cells can be identified– andpotentially targeted for earlydestruction – through their ability to reactivate an "embryonic"epigenetic state, highlighting one of the PCA's key missions:probing premalignant cells and model systems to better under-stand when epigenomic changes arise and how stable they areover time.

The Power of Immunology andBiochemistryImmune oncology

The integration of multiple omics analysis platforms withimmune-informatics analysis can be the foundation of a moreeffective framework for precision prevention. There is now awealth of evidence from both animal models and cancer patientsof how the immune system can survey and recognize peptidesencoded by certain genetic mutations when such peptidesare presented on the surface of the cancer cell bound to MHC-Class I andClass IImolecules. Immunogenic neoantigens, includ-ing oncogenic drivers, may also be targets of immunosurveillance(206, 207). For example, T-cells specific to mutated RAS peptideshave been found in cancer patients and may be a viable targetfor immune approaches to treatment and even prevention. Proof-of-principle experiments of vaccine targeting mutant Kras (withTreg depletion) in a pancreasmousemodel induced CD8þ T-cellsspecific for the Kras mutation and showed preventive efficacy inthe early PanIN setting (207). In addition to KRAS and otherpredicted mutations in known oncogenes (e.g., PI3K, b-catenin,and Myc), cancer cells and their precursors can harbor tens tohundreds of randommutations throughout their genome.GEMMstudies have identified mechanisms beginning with these geneticdrivers and other somatic alterations, which progressively recruitinflammatory/immunosuppressive cells and induce changes innormal cells to create and interact with the premalignant tumormicroenvironment (TME) to promote oncogenesis and immuneevasion (see Krasmap above in Big Genomics). This complexity ishighlighted by some preclinical data, surprisingly suggesting thatimmunogenicity of premalignant lesions can cause early immunesuppression/tolerance (206). These studies are currently limitedin humans, however, to only a few lesion types and patients. Therole of tumor suppressors (e.g., p53, ARF, Rb, PTEN) in immunityis strongly linked to maintenance of genomic integrity. p53 canmodulate innate and adaptive immunity, including macrophagefunction and production of certain cytokines, chemokines, and

ICAM1. p53 can also influence various immune checkpoints, e.g.,DD1a is a direct transcriptional target of p53, while p53 regulatesPD-L1 via miR34, which directly binds to the 30 UTR of the geneencoding PD-L1 (208).

Vaccine-based approaches hold particular promise sincethey are a form of precision prevention with few side effects.Viral vaccines (e.g., to HPV) given before exposure can providelong-term protection from cancer development after only oneor two treatments (140). HPV vaccines have modest activity,however, in treating chronic viral infections and related pre-cancers, and far less activity in treating established cancers.Therapeutic vaccine studies targeting viral E6/E7 oncogenicdrivers in CIN2/3, including results from single-cell T-cellreceptor (TCR) sequencing, suggest that inducing efficienttrafficking of functional effector T-cells to the epithelial diseasesite is critical to eliminate both CIN and virus (209). HPVinduces APOBEC3B (which mutates chromosomal DNA) andtumor-associated stromal fibroblasts (see APOBEC above). Themechanisms of viral immune evasion vary by pathogen (sevenviruses have been linked with human neoplasia) but arestrikingly similar to those used by non-viral neoplasias. HPVexamples of immune evasion include: E6 inactivates p53,which induces PD-L1 (as above) and cervical Tregs, and inte-grates into/disrupts the PD-L1 30 UTR enhancing PD-L1 expres-sion (210) and certain HLA genes have been linked to infectionand CIN transformation, and immune evasion (209, 210).Increased diversity/dysbiosis of vaginal microbiota combinedwith reduced abundance of Lactobacillus spp. is involved in HPVacquisition and persistence in the evolution of cervical pre-cancer and cancer (211). These provocative data suggesting thatvaginal microbiota may influence the host's innate immuneresponse, susceptibility to infection and neoplasia, will requirefuture longitudinal, multi-omic studies (212) as proposed inthe PCA to prove causality.

Evidence for immune surveillance has been reported inhealthy people and associated with lowered lifetime cancerrisk. Childhood febrile viral infections have been associatedwith reduced cancer risk, consistent with an influenza mousemodel in which the virus infection elicited protective antibo-dies and T-cells specific for host and some tumor-associatedantigens (213). These data suggest that infection-inducedimmunity and immune memory could provide long-termimmune surveillance of cancer, important properties for vac-cine targets. T-cells are likely the main effector cells in prevent-ing most forms of cancer. The immune system has the ability torecognize precancers and generate immune responses to poten-tially intercept and prevent cancer in the elimination phase ofimmunoediting (58, 62, 214). Precancers that are not elimi-nated proceed to the equilibrium phase in which the immunesystem holds the lesion in check and avoiding immune elim-ination is a hallmark of cancer (6). We must learn how to bothstrengthen T-cell immunity – either through immunization,drugs, or engineering – and concurrently overcome a dynamichostile tumor microenvironment that prevents T-cell activationand infiltration into early neoplasia. The latter involves mul-tiple factors, for example, intricate signaling networks, meta-bolic reprogramming of the microenvironment by the highutilization of extracellular glucose and glutamine results inextracellular lactate, which attenuates dendritic and T-cell acti-vation, stimulates macrophage polarization to an M2 state,induces VEGF secretion by stromal cells, and activates NFkB.

Perspective




The microenvironment can in turn have profound effects on themetabolism of neoplastic cells (83). Emerging data suggest thatmicroenvironment barriers develop early in precursor lesionsbut are likely qualitatively different from more establishedcancer-associated barriers. The progressive accumulation ofsomatic changes that leads to neoplasia also co-opts neighbor-ing vascular, neuronal, and other normal cells to support/promote oncogenesis by subverting the immune system toescape detection and elimination.

Remarkable new data revealed that high-level arm- andwhole-chromosome-SCNAs drive immune evasion (215). This unanti-cipated effect is in striking contrast mutational burden effects onimmunity, and can override immune response even in highmutational/neoantigen burden settings (e.g., MSI-H/MMR-defi-cient tumors; refs. 9, 10), revealing an increasingly intricateinterplay between SCNA levels, gene alterations, and immunity.Critical to vaccine development, therefore, is the identification ofpotent immune enhancers/adjuvants (e.g., metformin, toll-likereceptors [TLRs], STING, stromal inhibitors) that can specificallytarget one or more innate pathways and alter the developinginflammation that promotes immune suppression. For example,cancer vaccines can increase tumor infiltrating CD8þ T-cells,but these cells produce interferon-g , leading to upregulation ofPD-L1 and other immunosuppressive pathways. Furthermore,experience with therapeutic cancer vaccines shows that targetinga single antigen or a single mutated peptide invariably leads tooutgrowth of cancer cells that have lost that mutation (5). Thismay happen in the precancer setting as well, requiring a vaccinethat elicits a polyclonal and polyspecific immune response, andmonitored by T-cell receptor sequencing to look at clonalityand clone expansion, liquid biopsy detection of low levels ofspecific mutations or mutational load, SCNAs and imaging ofthe microenvironment, immune response (216, 217), and high-grade precancer (e.g., PanIN-3; ref. 218).

In a clinical feasibility trial of advanced adenoma patients, lackof immune response to a MUC1 cancer vaccine correlated withincreased levels of circulating MDSCs responsible for inhibitingadaptive immunity (219), suggesting that these may be usefulbiomarkers to identify individuals unlikely to benefit from pre-ventive cancer vaccines. As above, research into drugs that couldhelp overcome such immune resistancewill be critical.Metforminhas many key properties in this context, enhancing T-cell immu-nity and immune memory, and influencing the microbiome, byaffecting mitochondrial biology and RANK-L (see above; refs. 29,220–222). Furthermore, prospective cohort data suggest thataspirin prevention of CRC is related to its effects on T-cellimmunity (223). Large study of adenomas reported a highlyinflammatory microenvironment (224), which varied by histol-ogy and location (225). Two NGS reports of inflammatory boweldisease (IBD)-associated CRC suggested that, compared to theirsporadic counterparts, IBD-associated CRCs have a distinct muta-tional profile associated with cell-to-cell signaling, cell adhesion,and epigenetic regulators/chromatin modifiers, all linked to IBDinflammatory mediators (226, 227). IDH1 mutation (extremelyrare in sporadic CRC) was found only in Crohn's-associated CRC.As a precursor to CRC, ongoing IBD microbiome studies willcontinue to inform the biology of cancer development as shownby recent findings of immune-protozoa-microbiota interactionsin colitis and CRC (228).

Every human body contains �40 trillion microbes (micro-biota), which have exponentially more genes (the microbiome)

than do human cells; 99% of microbiota reside in the gut. Theroles of colonizing viruses, fungi, and parasites are reviewedelsewhere (228, 229). Insights from ongoing cancer research areelucidating the interplay and crosstalk between microbiota,innate immunity (myeloid and lymphoid), genetics, environ-mental exposures, diet, drugs and lifestyle, which centers on themetabolitesgenerated from host and multibiome activitiesand interactions (109, 110). Gut microbiota influence theshape and quality of the immune system, the immune systemguides the composition and localization of the microbiota, andboth can influence oncogenesis. Transcriptional reprogram-ming through epigenetic modifications is a prominent mech-anism by which microbiota influence innate immunity. Con-flicting clinical results of high-fiber diets have not controlled formicrobiota, which ferment fiber into butyrate and other shortchain fatty acids (SCFAs) that have energetic (via b-oxidation inthe mitochondria) and epigenetic functions in colonocytes,histone acetylation, and tumor suppressor effects. The micro-biota-epigenetic crosstalk can be illustrated when histone dea-cetylase 3 (HDAC3) is specifically deleted from intestinal cells:gene expression is massively altered and the integrity of theepithelial barrier is lost. Microbiota undergo rhythmic oscilla-tions in composition and function and induce TLR signaling inintestinal epithelial cells to drive hormone production andmetabolic activity through a coordinated circadian clock(110). Intestinal barrier function (and bacterial translocation)is also regulated by GWAS-identified laminin nuclear andmtDNA variants (119, 120) and inflammatory cytokines, suchas IL-1b and IL-18 (230), autophagy (96), p53 loss, andcarbohydrates (which affect gut mucous layer and microbiotaspatial organization; ref. 231). A mouse model of impairedintestinal barrier function, where immune cells are exposed tothe microbial product lipopolysaccharide, favors intestinaltumorigenesis through the action of interleukin IL-23/IL-17.Low-grade gut inflammation due to microbiota weakens epi-thelial tight junctions and may cause cancer risk factors –

obesity and Type 2 diabetes (232).Intricate community structures, such as matrix-enclosed poly-

microbial biofilms, can protect luminal microbiota from hostfactors and antibiotics, and are immunogenic (233). Newmetab-olite imaging techniques, such as nanostructure imaging massspectrometry, have identified polyamine metabolites that canenhance the activity of SLC3A2, which imports nitric oxide andcan induce biofilm formation. Themetabolome reflects both hostand microbial activities. New tools are needed to assign strainspecificity and assemble individual genomes from hybrid captureand single-cell approaches to isolate and sequence rare speciesand single microbial cells (110, 234). Gut microbiota and othermany factors can intrinsically affect the epithelial/mucus barrier(from germline to diet to metabolite, etc.), including a protectiverole against CRC with barrier maintenance, largely through pat-tern recognition receptors (e.g., TLRs and NOD-like receptors),mucin glycan composition, and production of protective meta-bolites, such as SCFAs (e.g., butyrate can suppress colon tumor-igenesis, mediated by Gpr109a and discussed earlier). Nod2loss (a mouse model of innate immune deficiency) disrupts thegut microbial balance (dysbiosis), induces IL-6, and gives riseto colitis-associated carcinogenesis inmice (110). Thymic stromallymphopoietin (TSLP) is a cytokine expressed mainly by epi-thelial cells at barrier surfaces (skin, gut, and lung). Extensivesequencing and computational tools were used to study skin

The Precancer Atlas




metabolites and microbiota, producing a molecular map of theskin surface, identifying chemical drivers of skin cancer (235).Short-course calcipotriol, a topical TSLP-specific inducer FDAapproved for psoriasis, durably suppressed skin cancer develop-ment in GEMMs consistent with an immune memory responseand markedly reduced actinic keratosis (mediated by T-cell adap-tive immunity) in a randomized clinical trial (236).

A surprising source of exogenously DNA damage double-stranded breaks come from microbiota such as H. pylori via theNER pathway, which cause genomic instability (4-fold increase inmutation frequency inmice) of gastric nuclear andmitochondrialDNA, intraepithelial neoplasia and adenocarcinoma (237), andMycobacterium tuberculosis can inhibit T-cell activity. This immu-nosuppressive effect may be similar to the potential immuno-suppressive effect of F. nucleatum (and its virulence factor FadA,which modulated E-cadherin/b-catenin signaling and increasescolonic permeability) in mice and recently validated clinically inCRC. F. nucleatum protein Fap2 can mediate F. nucleatum attach-ment to and invasion of adenomas and CRC and immuneevasion. Mucosal microbial communities show distinct altera-tions across stages of colorectal carcinogenesis and seem moreinvolved in the conventional chromosomal instability pathwayvs. serrated precursors. F. nucleatum levels have also been associ-ated with MSI and colonic tumorigenesis (238). Correlations ofbacterial taxa indicate early signs of dysbiosis in adenoma, and co-exclusive relationships are subsequentlymore common in cancer.Microbiota influences lesion localization with proximal (right-sided) colon tumors much more likely associated with biofilm-producing bacteria than distal (left–sided) tumors. Emerging datasuggest a link between ETBF, IBD, and CRC. ETBF can trigger IL-17-dependent colon tumorigenesis characterized by immuneinfiltrate and myeloid signature (239). Depletion of Tregs in aGEMM enhanced colitis but suppressed tumorigenesis associatedwith shifting mucosal cytokine profile from IL-17 to interferon-g .Impaired epithelial barrier function, induced by alarmins, recruitand activate Tregs. It has been shown that gut microbes andmetabolites modulate whole host immune and hormonal factorsinfluencing the fate of distant precancers (e.g., breast), possibly byinteracting with broader systemic microbial-immune networks.

Leveraging the recently launched US National MicrobiomeInitiative could help identify potential microbiota-related pre-vention factors including lifestyle (108, 232, 240), antibiotics,diet, and microbial reprogramming (241, 242). Diets rich inwhole grains and fiber are associated with a lower risk forF. nucleatum-positive (but not -negative) CRC, supporting apotential role for intestinal microbiota in regulating host immu-nity mediating the association between diet and colorectal neo-plasia (243). High-protein diet can reduce beneficial microbiotaand metabolites, downregulating immune protection (110).High-fat diet was found to induce intestinal progenitor cells toadopt amore stemcell-like fate, increasing tumor incidence. Theseeffects were not the result of obesity but were caused by certainfatty acids in the diet (244). In contrast, calorie restriction has theopposite effect, associated with reduced tumor initiation. Short-termdiet changes in rural Africans and African Americans resultedin large changes in bacterial species, metabolites and cancer risk(241). Gut microbiota-induced metabolites and componentswere recently shown to promote obesity-linked immune escapein hepatic tumorigenesis (245). Finally, bacterial composition inBarrett’s esophagus is dynamic and associated with genomicinstability (246).

Analyses of NGS genomic data are critical to develop vaccinesthat target specific epitopes derived from mutations, copy num-ber alterations, or other variants common to precancers. How-ever, this direct strategy is especially challenging given thelarge number of alterations, low penetrance of driver muta-tions, so-called "long tail" problem (low frequency mutations;ref. 247), and corresponding mutant peptides, which do notlead to effective antigen presentation and response. Mass spec-trometry-based analysis and immunogenic assays in mice (248),coupled with precursor NGS genomic data, will help selectbetter precancer vaccine targets. Computational methodologiesusing existing resources and databases that catalog potentialantigens (249) and machine-learning classification approachesto predict peptide binding affinity to HLA I and II have also beendeveloped (250, 251). Computational analyses of neoantigen-epitope prediction algorithms have shown that only a very smallproportion of predicted neo-epitopes are actually presented onMHC class I as targets of endogenous T-cell responses (10, 252,253). Using the NGS genomic data from precancers coulduse two strategies to nominate candidate neoantigens: 1) muta-tion-calling algorithms to identify frequently occurring antigensand 2) for the low frequency events, utilize functional mapsdescribed above to identify complementary antigens that asso-ciate with oncogenic states (168). These filtered lists of neo-antigens could predict/prioritize T-cell neoepitope candidates/vaccine targets in silico using algorithms and analytic pipelinesbased on stabilized peptide p–MHC-I binding affinity (252,254), although their utility to predict MHC class II antigens,gene fusions, splicing variants, and posttranslational modifica-tions is limited, since they rely on whole-exome sequencing(which is best for point mutations and small insertions/dele-tions). Novel approaches using T-cells from healthy donors maybroaden neoantigen-specific immune responses (255). Leverag-ing the PCA to develop high-throughput approaches andimproved predictive algorithms to identify (and quantify)immunogenicity of the precancer antigenic repertoire will becritical to identifying potential immunosurveillance and vaccinetargets (256–258).

As above, the MHC/HLA complex (located on 6p21) iscritical to immune oncology and vaccine development. HLAloci are highly polymorphic and implicated in cancer riskby multiple studies in a variety of tumor types, including viasearch of the NHGRI GWAS catalog (259). Highlighting theimportance of biochemistry in this context, a recent analysisfound somatic mutations that disrupt b-2 microglobulin(a component of class I MHC located on chromosome 15)protein-protein interactions, with a striking enrichment formutations at protein interfaces involving b-2 microglobulin'sbinding partners (260). It has been shown that disruption ofb-2 microglobulin can minimize immunogenicity of humanembryonic stem cells (261). Such mechanisms may be employ-ed by precancers and cancers to escape immune surveillance(262, 263). In human Lynch syndrome-associated CRC, b-2microglobulin mutations and accordingly HLA class I loss ordownregulation is frequent (up to 40%); most likely resultingfrom an active immune selection/editing process (264). FOXP3-positive T-cell infiltration was significantly lower in normalmucosa adjacent to mutant (mt)-b-2 microglobulin comparedto WT-b-2 microglobulin tumors, suggesting that in the absenceof Tregs, the outgrowth of less immunogenic mt-b-2 microglo-bulin tumor cells is favored (see above).

Perspective




Biochemistry: understanding the molecular basis of neoplasiaTCGA and related studies have demonstrated that a large

number of genetic and epigenetic factors, such as chromatinmodifiers and remodelers, are highly mutated in a large numberof solid tumors and in hematologic malignancies. Recurrentmutations in genes that encode regulators of chromatin structureand function highlight the central role that aberrant epigeneticregulation plays in the pathogenesis of these neoplasms. Deci-phering the molecular mechanisms for how alterations in epige-netic modifiers, specifically histone and DNA methylases anddemethylases, drive hematopoietic transformation could provideavenues for developing novel targeted epigenetic prevention forhematologic neoplasia and could also inform future research insolid tumors. Many such protein complexes – including the MLLfamily and polycomb components PRC1 and PRC2, which con-tain EZH2, ASXL1, and BAP1 (265), and the SWI/SNF (266) –

contain genes that are frequently mutated in human cancers butwere initially identified in simple model systems, such as Dro-sophila and yeast, emphasizing the importance of model organ-isms in any large-scale efforts in cancer prevention.While genomicdeletions and nonsense, frameshift, and splice sitemutations thatintroduce a premature stop codon or alter protein structure can beobvious loss-of-function events, missense mutations can be hardto classify unless they alter enzymatic function or disrupt protein–protein interfaces.

A large number of hematologic malignancies harbor trans-locations of the N-terminal region of MLL1 to diverse fusionpartners that share very little sequence or functional similarity.To understand how these diverse MLL translocations resultin leukemogenesis, biochemical and enzymological studieswere essential. First, MLL and its yeast homolog SET1 havebeen shown to be present in COMPASS (Complex of ProteinsAssociated with Set1), catalyzes methylation at histone H3K4(265, 267), although our understanding of the function of thisimportant enzyme is continuing to evolve (268). COMPASSdysregulation of gene expression can give rise to various can-cers (267). Second, AFF4, itself a fusion partner of MLL inleukemia, has been found to be a common factor among allpurified MLL translocations (269). Third, ELL, one of the fre-quent translocation partners of MLL in leukemia, has beenfound to function as an RNA Pol II elongation factor thatincreased the catalytic rate of transcription elongation by RNAPol II by suppressing transient pausing (270). Finally, it hasbeen shown that many MLL translocation partners are foundin association with ELL and the positive transcription elonga-tion factor (P-TEFb), within the Super Elongation Complex(SEC; refs. 265, 270, 271). The translocation of MLL into SECis involved in the misrecruitment of SEC to MLL target genes,perturbing transcription elongation checkpoints at these lociand resulting in leukemia (271). MLL-induced leukemogen-esis highlights the role of deregulated histone methylation intumorigenesis (272).

Another example of the importance of biochemistry is deci-phering the molecular role of an observed genetic link ofEZH2 in cancer. EZH2 encodes the catalytic subunit of PRC2,which is responsible for methylating lysine 27 of histone3 (H3K27). Trimethylation at this site is associated with closedchromatin and silencing of neighboring gene expression. Inneoplasia, EZH2 can influence T-cell biology (273) and functionas either an oncogene or a tumor suppressor gene depending onthe cellular context; for example, EZH is sufficient to transform

lung cells in transgenic mousemodels overexpressing EZH (274),and loss-of-function EZH2 mutations occur in MDS and chronicmyelomonocytic leukemia (CMML; ref. 275). In germinal centerdiffuse large B-cell lymphomas, recurrentmutations essentially ofonly one codon (Y641) create a protein with reduced affinity forunmethylated H3K27 but highly increased affinity for mono-methylated H3K27, resulting in higher levels of H3K27 trimethy-lation overall. In contrast, pre-AML syndromes like MDS andCMML do not develop Y641 mutations but instead recurrentlydevelop nonsense, frameshift, and other loss-of-function muta-tions in EZH2 resulting in low levels of H3K27 trimethylation(276). Ezh2 loss synergizes with JAK2-V617F in hematopoieticcells to contribute to the development and progression of MPN.The MPN phenotype induced by JAK2-V617F was accentuated inJak2-V617F;Ezh2(-/-) mice, resulting in expansion of the stem celland progenitor cell compartments and severe disease progression,including more advanced myelofibrosis and reduced survival(277). These results, which support tumor suppressor functionof EZH2 in patients with MPN, have important clinical implica-tions for EZH2 inhibitor development in this setting. It is possiblethat EZH2 inhibition will mimic malignancy-associated, loss-of-function EZH2 mutations in normal myeloid cells leading todysregulated growth or differentiation in these cells, highlightingthe need for future context-dependent studies.

SWI/SNF is also a critical regulator of nucleosome remodelingconserved from yeast to humans. Biochemical investigationcombined with bioinformatic assessments have demonstratedwidespread genomic alterations that occur across the membersof the complex in 19.6% of all human tumors reported in 44studies (278). In liver, genetic suppression of SWI/SNF complexmember ARID1B was shown to overcome oncogene-inducedsenescence and lead to liver neoplastic progression (279). Thefinding that ARID1A deficiency disrupts SWI/SNF-mediatedcontrol of enhancers (including H3K27 reduction) provides amechanism by which ARID1A mutations/deletions may pro-mote colorectal and mammary tumorigenesis (280, 281). Whilethese studies suggest an emerging role for SWI/SNF in cancerdevelopment, further delineation of the role of SWI/SNF com-plexes in precancers will help drive preventive efforts. Further-more, prior studies demonstrate antagonistic relationshipbetween the SWI/SNF and PRC2 complex in mediating onco-genic transformation (265, 267).

A transformative example of biochemistry's importancein premalignant biology involves the discovery of recurrentmutations in IDH1 and IDH2 in glioblastoma, AML, and theirprecursor cells. Such mutations were found through broadsequencing efforts (282) although their role at the molecularlevel was not clear until the advent of modern metabolomicsprofiling (283), which found that mutant IDH enzymes con-vert the normal intracellular metabolite alpha-ketoglutarateinto 2-hydroxyglutarate. A competitive inhibitor of a largeclass of dioxygenase enzymes that utilizes alpha-ketoglutarate,2-hydroxyglutarate accumulates to very high levels in IDH-mu-tated cancers, potently inhibiting many important intracellulardioxygenases, including the TET family, prolyl hydroxylases,and several histone demethylases (284–286). Thus, biochem-istry and metabolomics have illustrated how 2-hydroxygluta-rate contributes to carcinogenesis in a hitherto unprecedentedway by acting as a novel "oncometabolite" generated by soma-tic IDH1/IDH2 mutations that can potentially serve as vaccinetargets for both cancer prevention (287).

The Precancer Atlas




Biochemical approaches have also focused on the signifi-cance of metabolism and its link to epigenetic factors, suchas the TET family in the regulation of cell-lineage specifica-tion and the development of cancer. These discoveries areonly a few examples among a large number of biochemicalapproaches in neoplasia and are a testimony to the power ofbiochemistry in understanding neoplasia and the design ofits targeted prevention, for example, by highlighting theimportance of epigenetic regulation. High information contentmass spectrometry to profile global histone modifications inhuman cancers (113), when combined with the DNA-sequenc-ing data, can be used to identify novel variants that can driveepigenetic changes that can lead to oncogenic transformation.Chromatin-immunoprecipitation technology combined withNGS sequencing (ChIP-seq) can provide systematic informa-tion regarding the architecture of the chromatin cell states ofcancers. New technological advances have demonstrated thatChIP-seq can be carried out in human tissues (289). Interest-ingly, examination of the chromatin landscape was able tofully distinguish the normal vs. cancers. These results suggestthe possibility of gaining additional insights into precancers bysystematic assessment of chromatin states using key histoneacetylation and methylation patterns, super-enhancers, aswell as TET, SWI/SNF, and PRC2 all of which are critical forchromatin regulation (289).

It is essential that the PCA incorporate detailed biochemicaland enzymological studies on purified protein complexesto decipher the precise, context-dependent function of chroma-tin and other epigenetic modifiers and somatic mutationsin precancer development and progression (268). This will alsoallow the profiles to be cross-referenced with the landscapesin primary tumors, as well as of the corresponding transcrip-tomic data to identify critical epigenetic changes that are nec-essary formalignant transformation. The intricate roles of EZH2,PRC2 and SWI/SNF in chromatin regulation in normal devel-opment and neoplasia require further elucidation especiallyin precancers. Finally, metabolic alterations in neoplasia con-tinue to uncover novel connections between nutrient utilizationand oncogenic state (83), critical to precancer progression.

Single-Cell AnalysesThe natural history of precancers is heavily influenced by

the multi-omic heterogeneity (229, 290; also see Big Genomicssection) of neoplastic cells, multibiome, and tissue microenvi-ronment. Single-cell RNA- or DNA-sequencing technologiescan be specifically leveraged to unravel the elaborate cellularrelationships within these lesions and stem cell identity thatcannot be addressed by assaying bulk tissue (291, 292). In thecase of mRNA profiles, downstream analyses can characterizeknown populations and novel subpopulations of cells andassess how these populations change in abundance as diseaseprogresses or regresses. These data also can be used to moreaccurately infer important disease-associated gene regulatoryand immune cell networks (293), because the gene expressionvariability has not been averaged across all sampled cells as inbulk tissue. In addition, single-cell sequencing can reveal andmonitor lesion heterogeneity in somatic alterations and com-plex clonal dynamics among epithelial cells sampled at differentgeographic locations and over time to complement existingmulti-region bulk sequencing approaches (294). These data

will provide a high-resolution picture of cell types present inprecancers and their surrounding microenvironment and thetranscriptional programs active within each cell type that drivedisease progression.

Several technical limitations need to be overcome, however,to realize the full potential of single-cell sequencing of precan-cers. These lesions are relatively small and frequently onlydiagnosed in formalin-fixed, paraffin-embedded (FFPE) tissuespreviously precluding comprehensive genome-sequencing stud-ies using current methods (295). Furthermore, informationregarding the location of neoplastic cells with particular muta-tions within a given lesion is especially important for earlylesions, as this often defines the boundary between preinvasiveand invasive neoplasia. Therefore, the development and appli-cation of methods that allow assessing the genetic and pheno-typic features in situ using intact FFPE tissue samples is especiallycritical for the improved understanding of preinvasive lesions.Several technologies enable copy number alteration and geneexpression analyses at the single-cell level from FFPE slides.These include FISH and immuno-FISH (combination of FISHwith immunofluorescence; refs. 296, 297), mRNA in situ hybrid-ization, in situ PCR, and STAR-FISH (298–300). The applicationof immuno-FISH for the analysis of cellular phenotypic hetero-geneity and genetic features revealed extensive intratumor diver-sity in DCIS and clear expansion of minor subclones in DCIS todominant clones in invasive ductal carcinoma (297). A short-coming of these methods is the limited set of markers that canbe assessed on a single slide and the need for a priori knowledgeof the changes to be analyzed.

These methods are beginning to be applied to precancers,including DCIS, with massively parallel single-cell sequencingfor copy number analysis. This proof-of-principle analysis estab-lished technical feasibility and demonstrated intra-lesion geneticheterogeneity at DCIS, suggesting complex and distinct evolu-tionary processes involved in early DCIS to subclonal selection ininvasive disease. Multicolor FISH to evaluate clonal evolution atsingle-cell resolution in Barrett's esophagus found extensivegenetic diversity in progressors (301). A whole-exome single-cellsequencingmethodwas developed to assess genetic heterogeneityand tested on a premalignant JAK2-negative MPN (essentialthrombocythemia) patient (302). Such profiling of a differentMPNmyelofibrosis revealed substantial heterogeneity in cytokineproduction (303). Single-cell genomic research of childhoodALL provided a high-resolution view of the preleukemic sequenceof events leading to ALL, with early ETV6-RUNX1 translocationsin hematopoietic precursors to later APOBEC-mediated transfor-mation to leukemia (304). Somaticmutation loads in establishedsingle-cell clonal lineages provide information about lifetimeexposures and intrinsic factors (164). Importantly, however,current single-cell sequencing approaches have important tech-nological limitations, especially in epithelial precancers. First, themethods available are labor and cost intensive. Second, it iscurrently not possible to obtain accurate detailed copy numberand mutational data from the same cell, given that some whole-genome amplification methods yield templates optimal for copynumber analysis, whereas others are optimal for mutation pro-filing. Therefore, efforts are required for the development of lesslabor-intensive and more cost-effective methods for sequencingapproaches and clonal lineage tracing, which are essential for adetailed analysis of the evolutionary paths of in situ disease and itsprogression to invasive cancer. Two more technologies, FISSEQ

Perspective




(fluorescent in situ sequencing; ref. 292) and "spatial transcrip-tomics" (305), allow for complete transcriptome analysis of singlecells in intact tissue sections. Recently, a highly sensitive andquantitative single-cell RNA-seq assay to detect transcriptionalvariation and subtle differences in gene expression betweenrelated cells or cell states (306) has been developed. Thesetechniques will help elucidate chromatin maps/signatures andepigenetic heterogeneity in neoplasia (307) and the multibiome(229, 308), including imaging of host–microbiota interchanges(309). Leveraging Human Cell Atlas advances, including novelsingle-cell technology, will be critical.

Cost reduction and advances in cell sequencing (and cfDNAtechnology) could theoretically allow temporal monitoring ofblood and epithelial premalignancies on a population scalewithin the PCA (310–312). Periodic single-cell DNA sequencingof multiple cells from an individual will be invaluable for can-cer prevention as it will allow one to assess the overall baselineaccumulation of somatic mutations over time in a person, tosurvey andmonitor multiple different endogenous processes andexogenous exposures through the use of mutational signatures,and to reveal the existence of progenitor cells, premalignantclones, and clonal evolution over time (313–315). The unprec-edented resolution of sequencing single cells comes with a heftycomputational and data price. Monitoring even a single individ-ual will require multiple sequencing of one's genome every yearresulting in several terabytes of data per person. As such, popu-lation-scale examinations will generate millions of whole-genome sequences resulting in exabyte scale data (>1018 bytes)requiring next generation of computational infrastructure (316)and novel computational frameworks (e.g., to take into accounttheir relatively low signal resolution when compared with tradi-tional bulk tissue sequencing). Challenges for whole-genomeanalyses with single-cell resolution will be highly amplified withmulti-omic sequencing (317). More than ever, the rate-limitingstep will be data analysis.

Liquid Biopsies for Early Detection andIntervention

By virtue of the clonal nature of tumor cells, somatic changesare present inmany copies that are continuously released and canbe detected in the blood as cell-free (cf) circulating tumor DNA(318). In cancer patients, alterations in cfDNA can be detectedusing sequencing and bioinformatic approaches, although suchalterations can be difficult to detect as they often represent aminute fraction (<1%) of cfDNA. A variety of both targeted andwhole-genome approaches have been developed to detectsuch alterations in cfDNA (319, 320). These have been used forearly detection of recurrence in colorectal cancer, pancreaticcancer, neuroblastoma, hematopoietic malignancies, and others

)321–323 ). Importantly, cfDNA detection of pancreatic cancerrecurrence appears to precede radiographic detection of recur-rence by over six months in some cases, providing a largerwindow for potential intervention in this challenging disease(322). Ultra-deep NGS identified somatic mutations in cfDNAfrom uterine lavage in patients with stage IA and in �50% ofnormalwomen, age-related (321). A newphylogeneticmultiplex-PCR NGS platform approach to ctDNA profiling provides suffi-cient sensitivity to both identify lung cancer patients destined torelapse within a year of subclonal detection. Of importance toearly detection research, cfDNA was recently found in plasma in

patients with premalignant lung and bladder disease (324, 325).Differentially methylated loci in multiple HPV and host genesdetected byNGS in urine cfDNA could lead to precision screeningin cervical premalignancy (326). Somatic mutations in cfDNAamong individuals without any precancer diagnosis, however,pose evenmore serious challenges for the development of ctDNAscreening tests (327).

Achieving acceptable levels of sensitivity and specificity forearly cancer detection will require further technical advancesto identify possible combinations of cancer-specific mutationsand define potential quantitative thresholds to avoid overdiag-nosis. Enrichment steps can be based on biological properties (e.g., surface expression markers) or physics (e.g., size, density,deformability). Based on findings to date, it can already beenvisaged that DNA sequencing needs to be broad, to encompassconsiderable tumor heterogeneity, and deep, to detect minuteamounts of ctDNA fragments in themilieuof extensive geneticallynormal cfDNA. Nonmalignant conditions that can lead to thedeath of normal cells may also lead to a further dilution of ctDNAmolecules and hamper quantitative evaluations. Very sensitivetechnologies that allow the detection of less than 0.1% of ctDNAin blood plasma (e.g., digital droplet PCR or cancer personalizedprofiling [CAPP] by deep sequencing methods) have been devel-oped and applied to cfDNA analyses in patients with variousforms of cancer (328), but the key biological limitation might bethenumber of genomeequivalents present in blood samples fromearly-stage cancer patients.

Much work remains to be done in improving methodologiesfor detectionof circulating tumorDNA. In addition to theneed forhigher sensitivity, the specificity of cfDNA measurements alsofaces serious challenges (329). Several emerging reports haveshown that cancer-associated mutations are not restricted tocancer patients. Very low levels of TP53-mutated cfDNA wereobserved inplasmaofmatchednon-cancer controls in lung cancerearly detection research (327) and in the peritoneal fluid andperipheral blood of women with benign ovarian lesions (319).Likewise, a potential confounding issue is the detection of clonalalterations that arise in blood cells of healthy individuals thatmaybe associated with aging and clonal hematopoiesis (see below).Distinguishing between alterations in genes associatedwithMDS/AML versus solid tumors may be one way to overcome this issue.Additionally, even when molecular alterations are identified,determining the tissue of origin of the incipient neoplastic lesioncan be extremely challenging. Combining sequencing of cfDNAwith epigenetics markers (330, 331), mutational signatures,imaging andmathematical modeling can be used for pinpointingthe most likely tissue in which the clone originated. Even greaterissues challenge the promise of ctDNA analysis for early cancerdetection. Genomic alterations, such as those in the BRAF, RAS,EGFR, HER2, FGFR3, PIK3CA, TP53, CDKN2A, and NF1/2 genes,all considered hallmark drivers of specific cancers, can also beidentified in benign and premalignant conditions, occasionally atfrequencies higher than in their malignant counterparts.

Analysis of other blood/fluid components, such as exo-somes, platelets (332), urine, peritoneal fluid, and circulatingtumor cells (CTCs), may help increase the sensitivity of detec-tion (318, 324–326). CTCs are released early during tumordevelopment (318) and have been found in patients with smallprimary tumors. Thus, detection of CTCs might be an alterna-tive approach to early cancer identification. Circulating tumorcells have been detected in 3% of patients with chronic

The Precancer Atlas




obstructive pulmonary disease (COPD) who have an elevatedrisk of developing lung cancer 1–4 years before annual CT-screening detected lung nodules (333), possibly complement-ing a CLIA-approved bronchial airway genomic classifier (FDALaboratory Developed Test [LDT]) validated for lung cancerdetection (334), but were not detected in control individuals(both smokers and nonsmokers) with normal lung function. Theother FDA-approved omic stool DNA test is for CRC screening(111). This approach was recently extended into the less invasive,more accessible nasal epithelium where gene-expression altera-tions were associated with lung cancer detection (335). Technicaladvances have established the feasibility of detecting and NGSof CTCs collected from blood at the very early steps of tumorinvasion (336).

Focusing on population groups at an elevated risk of develop-ing cancer (e.g., COPD patients or individuals with inherit-ed cancer susceptibility) is a good strategy to speed up the processof testing and validation of emerging approaches and technolo-gies before considering large population-based screening effortsas indicated above. CTCs have been detected in �10% of CRCprecancers (adenomas) possibly stimulated by cytokine-drivenepithelial migration. Enormous resources are required to identifygenomic aberrations specific and sensitive enough to detectadvanced precancers and early malignant lesions in large cohorts.Finally, verification of the findings of approaches involving liquidbiopsy will call for acquisition of information on the putativelocation of the occult lesion to select the appropriate imagingmodalities or other diagnostic means prior to planning appro-priate therapies. In this context, tissue-specific multiplex tran-scriptome profiling of single CTCs (337) might be a promisingapproach. With these approaches, it is possible to imagine a timewhen individuals at high risk of developing cancer due to eithergenetic or environmental risk factors could be serially monitoredusing a blood-based test. A potential advantage of this approachwould be the relative ease of compliance compared with othermore invasive screening technologies. Ultimately, the specificmethodology would be determined by practical considerationssuch as cost, sensitivity, specificity, and robustness of the assays,but these approaches may forever change screening for cancersthat are currently incurable unless diagnosed at an early stage.

Longitudinal Analysis of PremalignanciesIt is likely that synchronous precancer/cancer pair studies

will not always accurately reflect the temporal clonal evolutionunderlying neoplastic transformation, i.e., genetic alterationsfound in precancer adjacent to cancer are not comparable tothose found in precancer in a patient who never progressed(as well shown in Barrett's esophagus). To fully appreciate suchmechanisms, systematic spatial and temporal sampling of neo-plastic cells will be essential. To date, such analyses of epithelialpremalignancies, with the exception of Barrett's esophagus, havebeen extremely limited, with reports of a relatively small numberof patients with lung squamous and adenocarcinoma prema-lignancy/field defect followed longitudinally (111, 338, 339).Whole transcriptome and genome analysis of preinvasive andearly invasive squamous lung carcinoma in a small number ofpatients have identified molecular alterations in both epithelialcell signaling pathways and immune cell pathways that associatewith progression of these precancers over time. Several cross-sectional studies, however, of lung squamous carcinogenesis have

been reported. Abnormal upregulation of chemokine genes suchas CXCL1, CXCL8, CXCL9 or CXCL10 is frequently detected inpreinvasive lung lesions. Other differentially expressed genesinclude SOX2, CEACAM5, SLC2A1, RNF20, SSBP2, RASGRP3,and PTTG1, which is a known proto-oncogene. Differential geneexpression was modest between low- and high-grade precancers,but substantial changes occurred between preinvasive and inva-sive squamous cell carcinoma samples (analogous to the patternin Barrett's). The majority of the differentially expressed pre-cancer genes, however, were shared with those in early invasivelesions. Pathway analysis showed that these shared genes areassociated with DNA damage response, DNA/RNA metabolism,and inflammation. PI3K/AKT signaling was an early event dur-ing squamous carcinogenesis (338, 340). Homozygous inacti-vation of Keap1 or Trp53 promoted airway basal stem cellself-renewal, suggesting expansion of mutant stem cell clones.Deletion of Trp53 and Keap1 in these stem cells recapitulated thehuman setting (341).

Genomic instability and driver genes promote clonal evo-lution/diversity as illustrated below (150, 342). Surprisingrelationships between SCNA types and levels, mutation bur-den, cell cycle markers, and immunity (215) have majorimplications on malignant transformation. Large longitudinalstudies of Barrett's esophagus established SCNAs as essentialoncogenic drivers. Non-progressors largely maintained stablegenomes, in contrast to patients with high levels of SCNAs,genome doubling, genetic diversity, and chromosomal insta-bility/catastrophe associated with rapid (<2 years) progressionto esophageal cancer (343). Another Barrett's esophagus reportof clonal evolution at single-cell resolution using multicolorFISH found that baseline genetic diversity predicts progression(to cancer) and remains in stable dynamic equilibrium overtime, suggesting that clonal make up and evolutionary trajec-tory of the lesion is predetermined from the outset (301).Clonal expansions were rare, often involving p16. Importantly,this Barrett's work has established the feasibility and model oflongitudinal study in epithelial premalignancy. Focusing onpremalignancies of the blood has several advantages, includingthe ease of repeatedly acquiring neoplastic cells to interrogateclonal evolution, discoveries that inform single-cell sequencingstudies in epithelial neoplasia. Study of MPNs provides theonly direct data that somatic mutation order (JAK2 and TET2)can greatly influence disease features (183). The overall malig-nant transformation rate for clonal hematopoiesis, monoclo-nal B-cell lymphocytosis (MBL), and monoclonal gammopa-thy of undetermined significance (MGUS) is about 1–2% peryear, but individual risk is highly variable. Comprehensivesingle-cell and cfDNA omics research will play a key role indissecting disease pathogenesis. We now have the ability tomonitor hundreds of individual cells, thus overcoming bulk-cell/tissue limitations and allowing precise analyses of intra-clonal and microenvironment architecture and crosstalk in theprocess and timing of transformation.

The unexpectedly high prevalence of clonal hematopoiesiswas recently characterized (344, 345) by NGS identification ofsomaticmutations in genes (mutant clones ofmostly single drivermutations), similar to the mutational spectrum seen in MDS(notably DNMT3A, TET2, and ASXL1), and is age-related in thegeneral population and associated with increased risk of MPN,MDS, and AML (346, 347). In one study using ultra sensitive NGStechniques, tiny hematopoietic clones defined by somatic

Perspective




mutations could be identified in as many as 95% of women intheir 50s, arguing that potentially premalignant clones are ubiq-uitous (348). Although the mechanism is unclear, most peoplewith more macroscopic clonal hematopoiesis of indeterminatepotential (CHIP) can stably harbor small hematopoietic clonesfor long periods of time. These clones must have initially expand-ed to the point of being detectable but then were held in check(347). One possibility is that the somatically mutated clonesare able to persist in a finite number of pseudo-niches notavailable to normal stem cells. Once these pseudo-niches arefilled, the clone cannot expand further until additionalmutationsare acquired or the microenvironment is altered to create addi-tional areas hospitable to these cells. This phenomena has beenobserved in some other sites (e.g., eyelid, skin, BRAF-mutantmoles; see above), where clones only grow so much before theybecome stable, until epigenetic reprogramming or some otherevent promotes transformation (see epigenetic section).

Recent studies have demonstrated how cells with a wide rangeof somatic mutations typical of myeloid malignancies (e.g., inU2AF1, SF3B1, SRSF2, ASXL1, or TET2) can induce inflammatoryconditions and innate immune responses that then favor thegrowth of these mutant cells. Whether adaptive immune surveil-lance plays a role in limiting the expansionof premalignant clonesis unclear. T-cell-mediated autoimmunity is well documented insome forms ofMDS suggesting that interactions with the adaptiveimmune system likely play a role clonal evolution. It appears thatthe aging bone marrow microenvironment promotes outgrowthof clones (e.g., driven bymutations in splicing factor genes SF3B1,SRSF2) and is associated with innate and adaptive immuneattrition. Murine findings suggest that aberrant splicing may alsoproduce neoantigens capable of eliciting an immune responsethat would need to be suppressed or evaded for progression tooccur. Drugs targeting the inflammasome and innate immuneresponses implicated in remodeling of the microenvironmentare potential preventive approaches under investigation. Thestrong age dependency for clonal hematopoiesis occurs in thecontext of age-related changes in the bone marrow microenvi-ronment and in normal HSCs with accumulation of DNAdamage, myeloid skewing, altered DNA methylation patterns,and relative quiescence. The same genetic and epigeneticchanges that drive oncogenesis may be selected for in thiscontext and are not necessarily inevitable consequences ofaging (349). Novel models using human disease-derived iPSCsand CRISPR/Cas9 editing tools have been used to map (andreverse) the evolution of the full spectrum of myeloid neoplasiafrom CHIP to MDS to AML (350). These models can be usedto test compounds that might have stage specific effects capableof altering the fitness or preventing the evolution of premalig-nant clones.

Chronic infection with persistent inflammation depleteshematopoietic stem and progenitor cells through primarilythrough replication stress-induced terminal differentiation medi-ated by the transcription factor BATF2. Using a murine model ofM. avium infection, inflammatory stimulation was a greater con-tributor to pancytopenia than myelofibrosis. Further study ofthese effects will provide mechanistic insight into diseases ofprogenitor and stem cell attrition/malfunction such as clonalhematopoiesis, MDS, and aplastic anemia (351). Aplastic anemiais a slightly different scenario, with two distinct processes occur-ring – immune-mediated destruction of hematopoietic cells and aconstant stimulus for the regeneration of these cells. Two kinds of

clonal hematopoietic cells may be selected for in that environ-ment – those that can evade the immune system (reverting to amore normal stem cell state) and those that acquire mutationspromoting clonal expansion. Clonal hematopoiesis is highlyprevalent among patients with aplastic anemia, in which twobroad types of genetic alterations are identified: (1) age-relatedmutations and CNAs commonly seen in myeloid malignancies(e.g.,DNMT3A, RUNX1, ASXL1) and (2) those not age related andhighly specific to aplastic anemia – PIGA and BCOR/BCORL1mutations and uniparental disomy (UPD) in 6p (6pUPD) iden-tified SNP array karyotyping, which in contrast to the first type,is associated with stable or decreasing clone size over time andmuch lower rates progression to MDS/AML (352). 6pUPD func-tionally results in deletion of half of the class I HLA locus, pro-viding amechanism for evasion of an immune response. Outsideof this context, this eventwould not be predicted to confer a clonaladvantage. In aplastic anemia, this form of immune evasionwould allow stemcells to function as theymightwere the immuneresponse not present. Clones with driver mutations in MDS-related genes, on the other hand, may gain proliferative orniche-independent growth capabilities that are more oncogenic.This is borne out by observations that 6pUPD ismore common inchildren with aplastic anemia, an age group where CHIP muta-tions are rare and that 6pUPD is exceedingly rare in elderly MDSand AML. This suggests that 6pUPD is not an oncogenic event butonly allows stem cells to persist in autoimmunity.

Nearly 40%of individuals with unexplained cytopenias harbordetectable mutations, many with clones having more than onedriver mutation and higher risk of transformation to MDS/AMLand all-causemortality (353). Cooperatingmutations also can beidentified during periods of clonally skewed hematopoiesis insporadic and hereditary settings that precede myeloid transfor-mation. DNMT3A haploinsufficiency transformed FLT-mutantmyeloproliferative disease into AML in mouse model (354). Thefrequent co-occurrence of germline GATA2 and somatic ASXL1events (355) and germline SNPs associated with somatic muta-tions of JAK2 have uncovered several targetable cooperativemutations (356) driving premalignant progression (357). Exam-ples of hereditarymutated transcription factors that predispose tohematologic neoplasia include mutations in CEBPA, RUNX1,ETV6, and PAX5 (287, 357). A recent GWAS identified germlinevariants that predispose toboth JAK2V617F clonal hematopoiesisand MPN (356). Four genes (JAK2, SH2B3, CHEK2, and TET2)altered in both inherited and somatic settings, contribute toV617F clonal hematopoeisis and/or MPN development. Thisidentification of a predisposition allele associated with TET2 isintriguing since somaticTET2mutations are common early eventsinmyeloid precursors, including clonal hematopoiesis andMPN,and can be identified in HSCs, either preceding or following theacquisition of V617F, with the mutational order of these twogenes influencing the clinical and biologic behavior of theseneoplasms.

MBL is an asymptomatic expansion of clonal B-cells in theperipheral blood present in roughly 4% of all U.S. individualsover the age of 40 years (358). Genetic predisposition to MBL issuggested by the finding that the incidence ofMBL is 3-fold higherfor individuals within familial chronic lymphocytic leukemia(CLL) kindreds (defined as families with at least two first-degreerelatives with CLL). A large GWAS of CLL andMBL families foundsignificant germline variant associations in two out of eightregions tested (359). NGS has shown that most mutations and

The Precancer Atlas




intraclonal heterogeneity found inCLL are already present inMBLyears before progression (360, 361). Furthermore, longitudinalMBL studies, including those from patients who progressed toCLL, have begun to elucidate the sequence, timing, and impact ofsubclonal expansion and T-cell exhaustion on malignant trans-formation (362–364). Risks of serious bacterial infections inindividuals with MBL are similar to those with CLL (365–367)and linked toMBL transformation (368, 369) and solid tumor riskis 3–4-fold higher in MBL and CLL (versus healthy controls), allthought to be due to defects in immune surveillance (366, 367).Antibody responses to primary and secondary antigen challengesare typically inefficient among patients with early-stage CLL.Preliminary data have shown that immunologic T-cell synapseis defective in individuals with MBL as well (358). Efforts togenerate efficient vaccine responseswill, therefore, be challenging.Enhancement of cytolytic T-cell function in MBL via vaccinetherapy should be a long-term challenge since graft-versus-leu-kemia is highly effective in eradicating leukemic B-cells. Bothin vitro and in vivodata suggest that lenalidomide can repair defectsin the T-cell immune synapse and reduce Tregs in CLL patients(370, 371), an approach currently being tested clinically inMBL. Of note, mouse model data suggest that age and inflam-matory status of the host microenvironment promotes selectionfor adaptive oncogenic events in B-cell progenitors (372), anal-ogous to clonal hematopoiesis. Relatedwork involves ahereditarysyndrome of susceptibility to pre–B-cell neoplasia caused byinherited mutations of PAX5. Mechanistic data indicated thatinherited susceptibility and aberrant immune responses to post-natal infections drives B-cell clonal evolution of premalignant B-cells and transformation to leukemia and lymphoma, by showingthat pre-B-ALLwas initiated in Pax5heterozygousmice onlywhenexposed to common infections (373).

The basis of MGUS as a precursor state is striking similar toother, recently characterized precursors of hematologic malignan-cies (e.g., clonal hematopoiesis and MBL; ref. 374). Studies ofMGUS have provided some of the best evidence that the immunesystem has the capacity to recognize precursor states. Search forshared targets of immune response led to the finding that T-cellsagainst stem cell antigens (such as SOX2) are particularly enrichedin MGUS (versus MM). Prospective data demonstrate that base-line SOX2 T-cell immunity correlates with risk of transformation(214). Loss of T, NK and NKT cells (possibly due to Tregs, MDSCs,suppressive cytokines) have been associated with progression toMM. Prevention strategies include boosting pre-existing T-cellimmunity, for example, with SOX2 vaccines and immune-mod-ulatory drugs. Much of the genomic instability and somatichypermutation events in MGUS are thought to originate/occurin the germinal center where IgH translocations involving AIDinduced by tumor-dendritic cell cross-talk appear to be earlyevents in myelomagenesis. Immunoglobulin IGHV genes carryimprints of clonal tumor history. Deep sequencing of the Ig locusindicate ongoing somatic hypermutation in a subset of neoplasticcells, suggesting neoplastic transformation is initiated in a germi-nal center B-cell. These data parallel IGHV clonal sequences insome MGUS with ongoing somatic hypermutation imprints.Since MGUS precedes MM, these data suggest origins of MGUSand MM with IGHV gene mutational intraclonal variation fromthe same germinal center B-cell (375). Whole-epigenome NGSwith extensive and unbiased analysis of the DNA methylome,including promoters, gene bodies, and intergenic regions innormal plasma cells, MGUS, and MM patient samples, identified

DNA methylation of B-cell-specific enhancers, a new phenome-non in MM pathogenesis (376). This pattern may reveal newpotential insights in the biology of the disease, representing ade novo epigenetic reprogramming or reflecting an epigeneticimprint of initial premalignant phases of the disease in progenitorcells. MGUSwas less heterogeneous thanMMbut shared a similarhypermethylation signature. In contrast, hypomethylation inMMwas much more extensive and heterogeneous than in MGUS,suggesting that it may be involved in transformation. Genomicstudies, including small NGS reports have highlighted that MGUSis a genetically advanced lesion (with many of the genetic changesfound in MM cells) with intraclonal heterogeneity in longitudinalstudies (377). The mutational landscape reflects the biologiccontinuum of plasma cell dyscrasias from a low-complexitymutational pattern in MGUS and immunoglobulin light-chainamyloidosis to a high-complexity pattern in MM (378). Genomicstudy of light-chain amyloidosis did not find a unifying mutation(by whole-exome sequencing), had similar CNA profiles asMM, but surprisingly the transcriptome is very similar to normalplasma cells (379).

Strikingly similar to clonal hematopoiesis andMBL, MGUS cellsdemonstrate clinical dormancy despite these extensive genomicalterations. Interestingly, new humanized models developed togrow precursor cells in vivo indicate that MGUS cells have the capa-city for progressive growth, clearly indicating that the clinical stabi-lity/dormancy of these cells is in part mediated by features extrinsicto tumor cells, such as the non-cellular matrix and immune, bone,endothelial, stromal, and other cells in the bone marrow niche(shared with hematopoietic stem cells) where signals derived fromosteoblasts may be important for mediating dormancy of MGUScells (377). These humanized models to grow premalignant cellsin vivo should greatly advance the study of clonal evolution andmalignant transformation in this setting (380). Inherited geneticvariation in specific SNPs increases MGUS predisposition and riskof transforming to MM (381). Loci identified also points to a rolefor chronic antigen-driven stimulation in driving clonal originsand evolution in MM and other B-cell tumors. The risk of MM isincreased >30-fold in the inherited glucosphingolipid storage dis-order Gaucher disease (GD), characterized by germline GBAmuta-tions, due in part to lysolipid-induced chronic inflammation andgenomic instability shown topromote thedevelopment of gammo-pathy inmice andpatients. Lysolipid substrate reduction (especiallygiven early) in Gba1-deficient mice decreased the risk of gammo-pathies (382, 383). This led to the recent discovery that in nearly25% of all cases of MGUS/MM, the underlying clone may bedriven by lipid antigens such as inflammation-associated bioactivelipids,whichhas importantprevention implications (382).Anotherhigh-risk group are blacks. Studies of GD and African cohorts(in Ghana) have an increased incidence of polyclonal gammopa-thies (377), suggesting thatpolyclonalB-cell activationmaybea lessgenetically complex pre-MGUS phase.

SummaryWhile a number of interventions are already FDA approved

for cancer prevention (detailed in ref. 384), this is only thetip of the iceberg. New precision prevention approaches willbe needed, with novel agents and combinations (11, 43, 385),trial designs (e.g., involving molecular/immune risk selection;refs. 386–388), surrogate (e.g., PI3K signature; ref. 389),and predictive markers (e.g., somatic mutations and germline

Perspective




variants of PIK3CA, BRAF, and HLA class I antigen expression inaspirin efficacy in CRC; promising leads are being evaluatedprospectively; refs. 389–391). Emerging studies/models ofprogenitors and mutational processes linking cell lineage toclonal evolution include: iPSCs and CRISPR/Cas9 editing tomap the evolution of myeloid neoplasia; and cell-fate dynam-ics, reprogramming, and lineage-specific regulation to progen-itor cells, potentially at the single-cell level, that can be iden-tified and targeted for early destruction (124, 314, 350). Forexample, elegant studies of luminal progenitor biologyand RANK signaling initiated a transformative prevention trialin BRCA1 carriers. Recent in-depth mechanistic work involvingfarnesoid X nuclear receptor ligand (392) adds further biolog-ical plausibility to the first real signal of clinical benefit inNASH (393). As documented in this Perspective, Barrett'sesophagus is the most developed model for the PCA indicatingfeasibility and major discovery, including: germline (rare muta-tions and GWAS; refs. 116–118), mitochondrial (161), biggenomics (153–155), epigenetics/transcriptomics (156), bio-chemical (163), immune (157), microbiome (246), single-cell(301), and longitudinal (383) studies and molecular monitor-ing to avoid overdiagnosis (394).

Developing cancer vaccines as potent as polio, diphtheria,and rubella vaccines would protect future generations fromdeveloping cancer. In cervical cancer, prophylactic vaccinationagainst HPV can virtually eliminate the disease (395), althoughimmune evasion is an issue in CIN2/3 (396). The developmentof cancer vaccines to stimulate T-cells (with strong adjuvants)to recognize precancer antigens as foreign may prevent cancereven at the premalignant stage (264). The communicationbetween the immune system and neoplasia reflects a funda-mental principle of oncogenesis in which tumors orchestratean intricate signaling network involving different immunecells and metabolic pathways to induce immune tolerance.This increasingly complex interplay involves an elaboratemicroenvironment (Fig. 1; refs. 215, 397); autophagy, aging,mitochondrial dynamics, metabolic activation, epigeneticreprogramming, and HSC fate (83, 96, 372, 398); and intricatesystemic microbial landscape (109, 110). Repurposing provenpreventive agents such as tamoxifen is supported by strikingoff-target innate and adaptive immune effects (30, 399). Arigorous, integrated approach recently confirmed the wide-spread genetic regulation of immune and inflammatory path-ways, extending experiments to primary human cells in disease-relevant contexts to unravel the cell- and context-specific reg-ulatory effects of intricate disease variants (400). Finally, sys-tematic, genome-wide transcriptional and epigenetic studieshave begun to uncover the role of heterogeneity and variabilityacross multiple immune cell types (401).

Age-related CHIP, now established by NGS, was found in 10%of over 40,000 healthy people >65 years (e.g., 344, 345, 347).Several ultra-deep NGS studies emerging over the past year areredefining the premalignant landscape finding minute somaticmutation-driven clones in normal tissue, including blood cells([micro-CHIP] in 95% of 50–60 year old women), eyelid skin(32%of234biopsies from fourmiddle-agedhealthypeople), andage-related peritoneal (100% in 20 women) and uterine (49% in95 women) lavage fluid (126, 321, 348, 402). These clones seemto expand to the point of being detectable but then held in checkuntil an epigenetic, immune (equilibrium phase), or other trans-forming event (264, 347, 403). Diet, lifestyle, environmental,

metabolomic factors, and the human genome and multibiome(including viruses and protozoa), which share an intricate setof interdependencies (109, 110, 228, 229, 232–234, 404), haveimportant implications for prevention strategies through target-ing immune cells and microbiota mechanistically rooted ingnotobiotic mouse models. Probing germline (rare mutationsand common variants)-somatic interactions is leading to novelprevention targets and approaches. Single-cell tools are beginningto reveal immense heterogeneity of DCIS and Barrett's esophagus.A major challenge is to develop single-cell technology to studyspatial proximity and temporal dynamics between cells, integrat-ing individual cellular states into models of functioning tissues,including interactions of precancer and immune cells and othercomponents of the microenvironment, which will revolutionizeour fundamental understanding of neoplasia biology (405).

In BRCA1/2-mutation carriers, high-grade serous ovarian car-cinoma (most common and severe subtype) originates fromfallopian tubes rather than the ovaries. This shift in understandinghighlights the remarkable prospect of practice-changing preven-tion advances, however, the scarcity of clinically annotated pre-cancers to interrogate limits essential biologic insight needed todrive novel interception strategies (127). This is one of manyexamples where a national PCA effort could transform a devas-tating disease. Based on recent recommendations from the NCIBlue Ribbon Panel associated with the Cancer Moonshot initia-tive, the NCI has assembled a precancer think tank to develop anational roadmap for these types of studies. Establishing a PCAthat integrates multi-omics and immunity (Fig. 1) will be criticalto better dissect and disrupt clonal evolution/diversity and theimmunosuppressive microenvironment to identify targets/mechanisms and immunogenic antigens, including the designof vaccines, to detect, prevent, and reject precancers.

As indicated in this Perspective, the complexities and challengesof this project are daunting, but the disruptive tools to makethe PCA feasible are coming on line and the potential publichealth benefits of preventing cancer are immeasurable. To accel-erate the prevention of cancer, this field needs a large-scale,longitudinal effort, leveragingmajor initiatives and infrastructure,diverse disciplines, technologies, and models (164, 350, 380,406–412) to develop a multi-omics and immunity PCA. Thisunified Atlas will provide a vast national resource for discovery tointerrogate, target, and intercept events that drive oncogenesis.

In summary, to fully achieve cancer prevention, we mustbuild teams with multiple areas of expertise from the NIH,academia, Food and Drug Administration, private founda-tions, philanthropic partners, and industry. The best analogyof assembling such a multidisciplinary team is the ManhattanProject—one goal, multiple experts.

Disclosure of Potential Conflicts of InterestA.E. Spira reports receiving a commercial research grant from Janssen

Pharmaceuticals and is a consultant/advisory board member for JanssenPharmaceuticals and Veracyte Inc. M.B. Yurgelun reports receiving a com-mercial research grant from Myriad Genetic Laboratories, Inc. R. Bejar is aconsultant/advisory board member for Genoptix, Celgene, FoundationMedicine, and Alexion. J.E. Garber reports receiving other commercialresearch support from Novartis and Ambry Genetics and is a consultant/advisory board member for Biogen, Novartis, and GTx. V.E. Velculescu hasownership interest (including patents) in Personal Genome Diagnostics andis a consultant/advisory board member for Personal Genome Diagnostics.M.L. Disis reports receiving a commercial research grant from VentiRx,Celgene, Jannsen, Seattle Genetics, and EMD Sorono and has ownership

The Precancer Atlas




interest (including patents) in VentiRx and Epithany. No potential conflictsof interest were disclosed by the other authors.

Authors' ContributionsConception and design: A.E. Spira, M.B. Yurgelun, R. Bejar, E. Vilar, T.R.Rebbeck, V.E. Velculescu, S.M. LippmanAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): S.M. LippmanAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis):M.B. Yurgelun, T.R. Rebbeck,D.Wallace, S.M. LippmanWriting, review, and/or revision of the manuscript: A.E. Spira, M.B. Yurgelun,L. Alexandrov, A. Rao, R. Bejar, K. Polyak, M. Giannakis, A. Shilatifard, O.J. Finn,M. Dhodapkar, N.E. Kay, E. Braggio, E. Vilar, S.A. Mazzilli, T.R. Rebbeck,J.E. Garber, V.E. Velculescu, M.L. Disis, D. Wallace, S.M. LippmanStudy supervision: S.M. Lippman

AcknowledgmentsThe authors thank Jennifer Beane, PhD, for her input on the single-cell

sequencing section and Leona Flores, PhD, for editorial assistance with thisarticle.

Grant SupportA.E. Spirawas supported byNIH/NCI 1U01CA214182 and5U01CA196408.

S.M. Lippman was supported for this work by NCIP30-CA023100-29. ASand SML co-chair the PremalignanT Cancer Genome Atlas (PreTCGA) Demon-stration Project, NCI BRP.

Received August 24, 2016; revised January 20, 2017; accepted January 20,2017; published online April 3, 2017.

References1. HudsonKL, Collins FS. The 21st Century Cures Act - A View from theNIH.

N Engl J Med 2017;376:111–13.2. Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA Jr, Kinzler

KW. Cancer genome landscapes. Science 2013;339:1546–58.3. Borras E, San Lucas FA, Chang K, Zhou R, Masand G, Fowler J, et al.

Genomic landscape of colorectal mucosa and adenomas. Cancer Prev Res2016;9:417–27.

4. Blackburn EH. Cancer interception. Cancer Prev Res 2011;4:787–92.5. Spira A, Disis ML, Schiller JT, Vilar E, Rebbeck TR, Bejar R, et al. Leveraging

premalignant biology for immune-based cancer prevention. Proc NatlAcad Sci U S A 2016;113:10750–8.

6. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell2011;144:646–74.

7. Rahman N. Realizing the promise of cancer predisposition genes. Nature2014;505:302–8.

8. ToC, KimEH, RoyceDB,WilliamsCR,Collins RM, Risingsong R, et al. ThePARP inhibitors, veliparib and olaparib, are effective chemopreventiveagents for delaying mammary tumor development in BRCA1-deficientmice. Cancer Prev Res 2014;7:698–707.

9. Dudley JC, Lin MT, Le DT, Eshleman JR. Microsatellite instability as abiomarker for PD-1 blockade. Clin Cancer Res 2016;22:813–20.

10. Le DT, Uram JN,WangH, Bartlett BR, KemberlingH, Eyring AD, et al. PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med2015;372:2509–20.

11. Samadder NJ, Neklason DW, Boucher KM, Byrne KR, Kanth P, SamowitzW, et al. Effect of sulindac and erlotinib vs placebo on duodenal neoplasiain familial adenomatous polyposis: a randomized clinical trial. JAMA2016;315:1266–75.

12. TungN, LinNU,Kidd J, AllenBA, SinghN,WenstrupRJ, et al. Frequency ofgermlinemutations in 25 cancer susceptibility genes in a sequential seriesof patients with breast cancer. J Clin Oncol 2016;34:1460–8.

13. Yurgelun MB, Kulke MH, Fuchs CS, Allen BA, Uno H, Hornick JL, et al.Cancer susceptibility gene mutations in individuals with colorectal can-cer. J Clin Oncol 2017 Jan 30:[Epub ahead of print].

14. Zhang J, Walsh MF, Wu G, Edmonson MN, Gruber TA, Easton J, et al.Germline mutations in predisposition genes in pediatric cancer. N Engl JMed 2015;373:2336–46.

15. Joost P, Therkildsen C, Dominguez-Valentin M, J€onsson M, Nilbert M.Urinary tract cancer in lynch syndrome; increased risk in carriers of MSH2mutations. Urology 2015;86:1212–7.

16. Schaefer MH, Serrano L. Cell type-specific properties and environmentshape tissue specificity of cancer genes. Sci Rep 2016;6:20707.

17. Sedic M, Skibinski A, Brown N, Gallardo M, Mulligan P, Martinez P, et al.Haploinsufficiency for BRCA1 leads to cell-type-specific genomic insta-bility and premature senescence. Nat Commun 2015;6:7505.

18. Benitez-Buelga C, Vaclova T, Ferreira S, Urioste M, Inglada-Perez L,Soberon N, et al. Molecular insights into the OGG1 gene, a cancer riskmodifier in BRCA1 and BRCA2 mutations carriers. Oncotarget 2016;7:25815–25.

19. Uziel O, Yerushalmi R, Zuriano L, Naser S, Beery E, Nordenberg J, et al.BRCA1/2 mutations perturb telomere biology: characterization of struc-

tural and functional abnormalities in vitro and in vivo. Oncotarget2016;7:2433–54.

20. WidschwendterM, Rosenthal AN, Philpott S, Rizzuto I, Fraser L, HaywardJ, et al. The sex hormone system in carriers of BRCA1/2 mutations: a case-control study. Lancet Oncol 2013;14:1226–32.

21. Pathania S, Bade S, LeGuillouM, Burke K, Reed R, Bowman-Colin C, et al.BRCA1 haploinsufficiency for replication stress suppression in primarycells. Nat Commun 2014;5:5496.

22. Savage KI, Matchett KB, Barros EM, Cooper KM, Irwin GW, Gorski JJ, et al.BRCA1 deficiency exacerbates estrogen-induced DNA damage and geno-mic instability. Cancer Res 2014;74:2773–84.

23. Nikkila J, Parplys AC, Pylkas K, Bose M, Huo Y, Borgmann K, et al.Heterozygous mutations in PALB2 cause DNA replication and damageresponse defects. Nat Commun 2013;4:2578.

24. Communal L, Vilasco M, Hugon-Rodin J, Courtin A, Mourra N, LahlouN, et al. Proliferation and ovarian hormone signaling are impaired innormal breast tissues from women with BRCA1 mutations: benefit of aprogesterone receptor modulator treatment as a breast cancer preven-tive strategy in women with inherited BRCA1 mutations. Oncotarget2016;7:45317–30.

25. Gorrini C, Gang BP, Bassi C, Wakeham A, Baniasadi SP, Hao Z,et al. Estrogen controls the survival of BRCA1-deficient cells via aPI3K-NRF2-regulated pathway. Proc Natl Acad Sci U S A 2014;111:4472–7.

26. Harte MT, O'Brien GJ, Ryan NM, Gorski JJ, Savage KI, Crawford NT,et al. BRD7, a subunit of SWI/SNF complexes, binds directly to BRCA1and regulates BRCA1-dependent transcription. Cancer Res 2010;70:2538–47.

27. Eakin CM, Maccoss MJ, Finney GL, Klevit RE. Estrogen receptor alpha is aputative substrate for the BRCA1ubiquitin ligase. ProcNatl Acad Sci U S A2007;104:5794–9.

28. Day FR, Ruth KS, Thompson DJ, Lunetta KL, Pervjakova N, Chasman DI,et al. Large-scale genomic analyses link reproductive aging to hypotha-lamic signaling, breast cancer susceptibility and BRCA1-mediated DNArepair. Nat Genet 201547:1294–303.

29. Cuyas E, Fernandez-Arroyo S, Alarcon T, Lupu R, Joven J, Menendez JA.Germline BRCA1 mutation reprograms breast epithelial cell metabo-lism towards mitochondrial-dependent biosynthesis: evidence formetformin-based "starvation" strategies in BRCA1 carriers. Oncotarget2016;7:52974–92.

30. Svoronos N, Perales-Puchalt A, Allegrezza MJ, Rutkowski MR, Payne KK,Tesone AJ, et al. Tumor cell-independent estrogen signaling drives diseaseprogression through mobilization of myeloid-derived suppressor cells.Cancer Discov 2017;7:72–85.

31. Visvanathan K,Hurley P, Bantug E, Brown P, Col NF, Cuzick J, et al. Use ofpharmacologic interventions for breast cancer risk reduction: AmericanSociety of Clinical Oncology clinical practice guideline. J Clin Oncol2013;31:2942–62.

32. Xu L, Zhao Y, Chen Z, Wang Y, Chen L, Wang S. Tamoxifen and risk ofcontralateral breast cancer among women with inherited mutations inBRCA1 and BRCA2: a meta-analysis. Breast Cancer 2015;22:327–34.

Perspective




33. Alothman SJ, Wang W, Goerlitz DS, Islam M, Zhong X, Kishore A, et al.Responsiveness of Brca1 and Trp53 deficiency induced mammary pre-neoplasia to selective estrogen modulators versus an aromatase inhibitorin Mus musculus. Cancer Prev Res in press.

34. Jeong JH, Jo A, Park P, Lee H, Lee HO. Brca2 deficiency leads to T cell lossand immune dysfunction. Mol Cells 2015;38:251–8.

35. Dabydeen SA, Kang K, Diaz-Cruz ES, Alamri A, Axelrod ML, Bouker KB,et al. Comparison of tamoxifen and letrozole response in mammarypreneoplasia of ER and aromatase overexpressing mice definesan immune-associated gene signature linked to tamoxifen resistance.Carcinogenesis 2015;36:122–32.

36. Nolan E, Vaillant F, BranstetterD, Pal B,GinerG,Whitehead L, et al. RANKligand as a potential target for breast cancer prevention in BRCA1-mutation carriers. Nat Med 2016;22:933–9.

37. Sigl V, Owusu-Boaitey K, Joshi PA, Kavirayani A,Wirnsberger G, Novatch-kova M, et al. RANKL/RANK control Brca1 mutation-driven mammarytumors. Cell Res 2016;26:761–74.

38. Gross K, Wronski A, Skibinski A, Phillips S, Kuperwasser C. Cell fatedecisions during breast cancer development. J Dev Biol 2016;4:4.

39. Sau A, Lau R, CabritaMA,Nolan E, Crooks PA, Visvader JE, et al. Persistentactivation ofNF-kappaB inBRCA1-deficientmammary progenitors drivesaberrant proliferation and accumulation of DNA damage. Cell Stem Cell2016;19:52–65.

40. Phillips S, Prat A, Sedic M, Proia T, Wronski A, Mazumdar S, et al. Cell-state transitions regulated by SLUG are critical for tissue regeneration andtumor initiation. Stem Cell Rep 2014;2:633–47.

41. Melchor L, Molyneux G, Mackay A, Magnay FA, Atienza M, Kendrick H,et al. Identification of cellular and genetic drivers of breast cancer het-erogeneity in genetically engineered mouse tumour models. J Pathol2014;233:124–37.

42. Palafox M, Ferrer I, Pellegrini P, Vila S, Hernandez-Ortega S, Urruticoe-chea A, et al. RANK induces epithelial-mesenchymal transition andstemness in human mammary epithelial cells and promotes tumorigen-esis and metastasis. Cancer Res 2012;72:2879–88.

43. Nolan E, Lindeman GJ, Visvader JE. Out-RANKing BRCA1 in mutationcarriers. Cancer Res 2017;77:595–600.

44. Galluzzi L, Buque A, Kroemer G. Prevention of breast cancer by RANKL/RANK blockade. Cell Res 2016;26:751–2.

45. WidschwendterM, BurnellM, Fraser L, Rosenthal AN, Philpott S, ReiselD,et al. Osteoprotegerin (OPG), The Endogenous Inhibitor of ReceptorActivator of NF-kappaB Ligand (RANKL), is Dysregulated in BRCAMuta-tion Carriers. EBioMedicine 2015;2:1331–9.

46. Shu CA, Pike MC, Jotwani AR, Friebel TM, Soslow RA, Levine DA,et al. Uterine cancer after risk-reducing salpingo-oophorectomywithout hysterectomy in women with BRCA mutations. JAMA Oncol2016;2:1434–40.

47. Kotsopoulos J, Huzarski T, Gronwald J, Singer CF, Moller P, Lynch HT,et al. Bilateral oophorectomy and breast cancer risk in BRCA1 and BRCA2mutation carriers. J Natl Cancer Inst 2017;109.

48. Kais Z, Rondinelli B, Holmes A, O'Leary C, Kozono D, D'Andrea AD,et al. FANCD2 maintains fork stability in BRCA1/2-deficient tumorsand promotes alternative end-joining DNA repair. Cell Rep 2016;15:2488–99.

49. Longerich S, Li J, Xiong Y, Sung P, Kupfer GM. Stress and DNA repairbiology of the Fanconi anemia pathway. Blood 2014;124:2812–9.

50. Sumpter R Jr, Sirasanagandla S, Fernandez AF, Wei Y, Dong X, Franco L,et al. Fanconi anemia proteins function inmitophagy and immunity. Cell2016;165:867–81.

51. Belcheva A, Irrazabal T, Robertson SJ, Streutker C, Maughan H, Rubino S,et al. Gut microbial metabolism drives transformation ofMSH2-deficientcolon epithelial cells. Cell 2014;158:288–99.

52. Montrose DC, Zhou XK, McNally EM, Sue E, Yantiss RK, Gross SS, et al.Celecoxib alters the intestinal microbiota andmetabolome in associationwith reducing polyp burden. Cancer Prev Res 2016;9:721–31.

53. Kostic AD, Chun E, Robertson L, Glickman JN, Gallini CA, Michaud M,et al. Fusobacterium nucleatum potentiates intestinal tumorigenesis andmodulates the tumor-immune microenvironment. Cell Host Microbe2013;14:207–15.

54. Housseau F, Wu S, Wick EC, Fan H, Wu X, Llosa NJ, et al. Redundantinnate and adaptive sources of IL17 production drive colon tumorigen-esis. Cancer Res 2016;76:2115–24.

55. L�evy J, Cacheux W, Bara MA, L'Hermitte A, Lepage P, Fraudeau M, et al.Intestinal inhibition of Atg7 prevents tumour initiation through a micro-biome-influenced immune response and suppresses tumour growth. NatCell Biol 2015;17:1062–73.

56. VasenH, Ibrahim I, PonceCG, Slater EP,Matthai E, CarratoA, et al. Benefitof surveillance for pancreatic cancer in high-risk individuals: outcome oflong-term prospective follow-up studies from three European ExpertCenters. J Clin Oncol 2016;34:2010–9.

57. Salo-Mullen EE, O'Reilly EM, Kelsen DP, Ashraf AM, Lowery MA, Yu KH,et al. Identification of germline genetic mutations in patients withpancreatic cancer. Cancer 2015;121:4382–8.

58. Beatty PL, van der Geest R, Hashash JG, Kimura T, Gutkin D, Brand RE,et al. Immunobiology and immunosurveillance in patients with intra-ductal papillary mucinous neoplasms (IPMNs), premalignant precursorsof pancreatic adenocarcinomas. Cancer Immunol Immunother 2016;65:771–8.

59. Alsop K, Fereday S, Meldrum C, deFazio A, Emmanuel C, George J,et al. BRCA mutation frequency and patterns of treatment responsein BRCA mutation-positive women with ovarian cancer: a reportfrom the Australian Ovarian Cancer Study Group. J Clin Oncol 2012;30:2654–63.

60. Saeterdal I, Bjorheim J, Lislerud K, Gjertsen MK, Bukholm IK, Olsen OC,et al. Frameshift-mutation-derived peptides as tumor-specific antigens ininherited and spontaneous colorectal cancer. Proc Natl Acad Sci U S A2001;98:13255–60.

61. Pakish JB, Zhang Q, Chen Z, Liang H, Chisholm G, Yuan Y, et al.Immune microenvironment in microsatellite instable endometrial can-cers: Hereditary or sporadic origin matters. Clin Cancer Res 2017 Mar 6:[Epub ahead of print].

62. Schwitalle Y, Kloor M, Eiermann S, LinnebacherM, Kienle P, Knaebel HP,et al. Immune response against frameshift-induced neopeptides inHNPCC patients and healthy HNPCC mutation carriers. Gastroenterol-ogy 2008;134:988–97.

63. Borras E, PandeM, Chang K, Cuddy A, Bannon SA,MorkME, et al. In Silicosystems biology analysis of variants of uncertain significance in Lynchsyndrome supports the prioritization of functional molecular validation.Cancer Prev Res in press.

64. Yurgelun MB, Chenevix-Trench G, Lippman SM. Translating germlinecancer risk into precision prevention. Cell 2017;168:566–70.

65. Ait OuakrimD, Dashti SG, Chau R, BuchananDD, ClendenningM, RostyC, et al. Aspirin, ibuprofen, and the risk of colorectal cancer in lynchsyndrome. J Natl Cancer Inst 2015;107:djv170.

66. Oxnard GR, Heng JC, Root EJ, Rainville IR, Sable-Hunt AL, Shane-CarsonKP, et al. Initial results of a prospective,multicenter trial to study inheritedlung cancer risk associated with germline EGFR T790M: INHERIT EGFR.J Clin Oncol 33, 2015 (suppl; abstr 1505).

67. Wu X, Wen CP, Ye Y, Tsai M, Wen C, Roth JA, et al. Personalized riskassessment in never, light, and heavy smokers in a prospective cohort inTaiwan. Sci Rep 2016;6:36482.

68. Lu C, Xie M, Wendl MC, Wang J, McLellan MD, Leiserson MD, et al.Patterns and functional implications of rare germline variants across 12cancer types. Nat Commun 2015;6:10086.

69. Campbell PJ. Somatic and germline genetics at the JAK2 locus. Nat Genet2009;41:385–6.

70. Liu W, He L, Ramirez J, Krishnaswamy S, Kanteti R, Wang YC, et al.Functional EGFR germline polymorphisms may confer risk forEGFR somatic mutations in non-small cell lung cancer, with apredominant effect on exon 19 microdeletions. Cancer Res 2011;71:2423–7.

71. Li Q, Seo JH, Stranger B, McKenna A, Pe'er I, Laframboise T, et al.Integrative eQTL-based analyses reveal the biology of breast cancer riskloci. Cell 2013;152:633–41.

72. Carter H,Marty R, HofreeM, Gross A, Jensen J, Fisch KM, et al. Interactionlandscape of inherited polymorphisms with somatic events in cancer.Cancer Discov 2017 Feb 10.

73. Puzone R, Pfeffer U. SNP variants at the MAP3K1/SETD9 locus 5q11.2associatewith somatic PIK3CAvariants inbreast cancers. Eur JHumGenet2017;25:384–87.

74. Jennis M, Kung CP, Basu S, Budina-Kolomets A, Leu JI, Khaku S, et al. AnAfrican-specific polymorphism in the TP53 gene impairs p53 tumorsuppressor function in a mouse model. Genes Dev 2016;30:918–30.

The Precancer Atlas




75. Kar SP, Beesley J, Amin Al Olama A, Michailidou K, Tyrer J, Kote-Jarai Z,et al. Genome-wide meta-analyses of breast, ovarian, and prostate cancerassociation studies identify multiple new susceptibility loci shared by atleast two cancer types. Cancer Discov 2016;6:1052–67.

76. Amos CI, Dennis J, Wang Z, Byun J, Schumacher FR, Gayther SA, et al. TheOncoArray Consortium: a network for understanding the genetic archi-tecture of common cancers. Cancer Epidemiol Biomarkers Prev 2017;26:126–35.

77. Walker LC, Marquart L, Pearson JF, Wiggins GA, O'Mara TA, Parsons MT,et al. Evaluation of copy-number variants as modifiers of breast andovarian cancer risk for BRCA1 pathogenic variant carriers. Eur J HumGenet 2017 Feb 1.

78. Couch FJ, Kuchenbaecker KB, Michailidou K, Mendoza-Fandino GA,Nord S, Lilyquist J, et al. Identification of four novel susceptibility locifor oestrogen receptor negative breast cancer. Nat Commun 2016;7:11375.

79. He Y, Gorkin DU, Dickel DE, Nery JR, Castanon RG, Lee AY, et al.Improved regulatory element prediction based on tissue-specificlocal epigenomic signatures. Proc Natl Acad Sci U S A 2017;114:E1633–40.

80. Middlebrooks CD, Banday AR, Matsuda K, Udquim KI, Onabajo OO,Paquin A, et al. Association of germline variants in the APOBEC3 regionwith cancer risk and enrichment with APOBEC-signature mutations intumors. Nat Genet 2016;48:1330–8.

81. Nik-Zainal S, Wedge DC, Alexandrov LB, Petljak M, Butler AP, Bolli N,et al. Association of a germline copy number polymorphism of APO-BEC3A and APOBEC3B with burden of putative APOBEC-dependentmutations in breast cancer. Nat Genet 2014;46:487–91.

82. Wallace DC. Mitochondrial DNA variation in human radiation anddisease. Cell 2015;163:33–8.

83. Pavlova NN, Thompson CB. The emerging hallmarks of cancer metab-olism. Cell Metab 2016;23:27–47.

84. Brandon M, Baldi P, Wallace DC. Mitochondrial mutations in cancer.Oncogene 2006;25:4647–62.

85. Arnold RS, Sun Q, Sun CQ, Richards JC, O'Hearn S, Osunkoya AO, et al.An inherited heteroplasmic mutation in mitochondrial gene COI in apatient with prostate cancer alters reactive oxygen, reactive nitrogen andproliferation. Biomed Res Int 2013;2013:239257.

86. Petros JA, Baumann AK, Ruiz-Pesini E, Amin MB, Sun CQ, Hall J, et al.mtDNA mutations increase tumorigenicity in prostate cancer. Proc NatlAcad Sci U S A 2005;102:719–24.

87. Canter JA, Kallianpur AR, Parl FF, Millikan RC. Mitochondrial DNAG10398A polymorphism and invasive breast cancer in African-Americanwomen. Cancer Res 2005;65:8028–33.

88. Permuth-Wey J, Chen YA, Tsai YY, Chen Z, Qu X, Lancaster JM, et al.Inherited variants in mitochondrial biogenesis genes may influenceepithelial ovarian cancer risk. Cancer Epidemiol Biomarkers Prev2011;20:1131–45.

89. Williams SB, Ye Y, Huang M, Chang DW, Kamat AM, Pu X, et al.Mitochondrial DNA content as risk factor for bladder cancer and itsassociation with mitochondrial DNA Polymorphisms. Cancer Prev Res2015;8:607–13.

90. Liu VW, Wang Y, Yang HJ, Tsang PC, Ng TY, Wong LC, et al.Mitochondrial DNA variant 16189T>C is associated with susceptibilityto endometrial cancer. Hum Mutat 2003;22:173–4.

91. Zhai K, Chang L, Zhang Q, Liu B, Wu Y. Mitochondrial C150Tpolymorphism increases the risk of cervical cancer and HPV infection.Mitochondrion 2011;11:559–63.

92. Zhai K, Chang L, Zhang Q, Liu B, Wu Y. Mitochondrial C150Tpolymorphism increases the risk of cervical cancer and HPV infection.Mitochondrion 2011;11:559–63.

93. Schroder T, Kucharczyk D, Bar F, Pagel R, Derer S, Jendrek ST, et al.Mitochondrial gene polymorphisms alter hepatic cellular energy metab-olism and aggravate diet-induced non-alcoholic steatohepatitis. MolMetab 2016;5:283–95.

94. Fan W, Waymire KG, Narula N, Li P, Rocher C, Coskun PE, et al. Amousemodel of mitochondrial disease reveals germline selection againstsevere mtDNA mutations. Science 2008;319:958–62.

95. Gasparre G, Iommarini L, Porcelli AM, Lang M, Ferri GG, Kurelac I, et al.An inherited mitochondrial DNA disruptive mutation shifts to homo-plasmy in oncocytic tumor cells. Hum Mutat 2009;30:391–6.

96. Zong WX, Rabinowitz JD, White E. Mitochondria and Cancer. Mol Cell2016;61:667–76.

97. Feeley KP, Bray AW, Westbrook DG, Johnson LW, KestersonRA, Ballinger SW, et al. Mitochondrial genetics regulate breastcancer tumorigenicity and metastatic potential. Cancer Res 2015;75:4429–36.

98. Schriner SE, Linford NJ, Martin GM, Treuting P, Ogburn CE, Emond M,et al. Extension of murine life span by overexpression of catalase targetedto mitochondria. Science 2005;308:1909–11.

99. Goh J, Enns L, Fatemie S, Hopkins H, Morton J, Pettan-Brewer C, et al.Mitochondrial targeted catalase suppresses invasive breast cancer inmice.BMC Cancer 2011;11:191.

100. Latorre-Pellicer A, Moreno-Loshuertos R, Lechuga-Vieco AV, Sanchez-Cabo F, Torroja C, Acin-Perez R, et al. Mitochondrial and nuclearDNA matching shapes metabolism and healthy ageing. Nature 2016;535:561–5.

101. Picard M, Zhang J, Hancock S, Derbeneva O, Golhar R, Golik P, et al.Progressive increase in mtDNA 3243A>G heteroplasmy causes abrupttranscriptional reprogramming. Proc Natl Acad Sci U S A 2014;111:E4033–42.

102. Wang PY, Li J, Walcott FL, Kang JG, Starost MF, Talagala SL, et al.Inhibitingmitochondrial respirationprevents cancer in amousemodel ofLi-Fraumeni syndrome. J Clin Invest 2017;127:132–136.

103. Dong LF, Kovarova J, Bajzikova M. Horizontal transfer of wholemitochondria restores tumorigenic potential in mitochondrial DNA-deficient cancer cells. eLife 2017;10.7554/eLife.22187.

104. Chen PL, Chen CF, Chen Y, Guo XE, Huang CK, Shew JY, et al.Mitochondrial genome instability resulting from SUV3 haploinsuffi-ciency leads to tumorigenesis and shortened lifespan. Oncogene 2013;32:1193–201.

105. Birsoy K, Possemato R, Lorbeer FK, Bayraktar EC, Thiru P, Yucel B, et al.Metabolic determinants of cancer cell sensitivity to glucose limitation andbiguanides. Nature 2014;508:108–12.

106. Dan Dunn J, Alvarez LA, Zhang X, Soldati T. Reactive oxygen speciesand mitochondria: A nexus of cellular homeostasis. Redox Biol 2015;6:472–85.

107. Blein S, Bardel C,Danjean V,McGuffog L,Healey S, Barrowdale D, et al.An original phylogenetic approach identified mitochondrial haplogroupT1a1 as inversely associated with breast cancer risk in BRCA2 mutationcarriers. Breast Cancer Res 2015;17:61.

108. Blein S, Barjhoux L; GENESIS investigators, Damiola F, Dondon MG,Eon-Marchais S, et al. Targeted sequencing of themitochondrial genomeof women at high risk of breast cancer without detectable mutations inBRCA1/2. PLoS One 2015;10:e0136192.

109. Garrett WS. Cancer and the microbiota. Science 2015;348:80–6.110. Thaiss CA, Zmora N, Levy M, Elinav E. The microbiome and innate

immunity. Nature 2016;535:65–74.111. Beane J, Campbell JD, Lel J, Vick J, Spira A. Genomic approaches to

accelerate cancer interception. Lancet Oncol in press.112. O'Connell MA, Mannion NM, Keegan LP. The epitranscriptome and

innate immunity. PLoS Genet 2015;11:e1005687.113. Rasmussen KD, Helin K. Role of TET enzymes in DNA methylation,

development, and cancer. Genes Dev 2016;30:733–50.114. Stahl M, Kohrman N, Gore SD, Kim TK, Zeidan AM, Prebet T.

Epigenetics in cancer: A hematological perspective. PLoS Genet 2016;12:e1006193.

115. Rebbeck TR, Sellers TA. The Fruits of the genomic revolution. CancerEpidemiol Biomarkers Prev in press.

116. Gharahkhani P, Fitzgerald RC, Vaughan TL, Palles C, Gockel I,Tomlinson I, et al. Genome-wide association studies in oesophagealadenocarcinoma and Barrett's oesophagus: a large-scale meta-analysis.Lancet Oncol 2016;17:1363–73.

117. Buas MF, He Q, Johnson LG, Onstad L, Levine DM, Thrift AP, et al.Germline variation in inflammation-related pathways and risk of Barrett'soesophagus and oesophageal adenocarcinoma. Gut 2016; [Epub aheadof print].

118. Fecteau RE, Kong J, Kresak A, Brock W, Song Y, Fujioka H, et al.Association between germline mutation in VSIG10L and familial barrettneoplasia. JAMA Oncol 2016;2:1333–9.

119. Peters U, Jiao S, Schumacher FR, Hutter CM, Aragaki AK, BaronJA, et al. Identification of genetic susceptibility loci for colorectal


Perspective



tumors in a genome-wide meta-analysis. Gastroenterology 2013;144:799–807.

120. Whiffin N, Hosking FJ, Farrington SM, Palles C, Dobbins SE, ZgagaL, et al. Identification of susceptibility loci for colorectal cancer in agenome-wide meta-analysis. Hum Mol Genet 2014;23:4729–37.

121. Petridis C, Brook MN, Shah V, Kohut K, Gorman P, Caneppele M, et al.Genetic predisposition to ductal carcinoma in situ of the breast. BreastCancer Res 2016;18:22.

122. Hollstein M, Alexandrov LB, Wild CP, Ardin M, Zavadil J. Base changesin tumour DNA have the power to reveal the causes and evolution ofcancer. Oncogene 2017;36:158–67.

123. Hoang ML, Kinde I, Tomasetti C, McMahon KW, Rosenquist TA,Grollman AP, et al. Genome-wide quantification of rare somatic muta-tions in normal human tissues using massively parallel sequencing. ProcNatl Acad Sci U S A 2016;113:9846–51.

124. Imielinski M, Guo G, Meyerson M. Insertions and deletions targetlineage-defining genes in human cancers. Cell 2017;168:460–472.

125. Forsberg LA, Rasi C, Pekar G, Davies H, Piotrowski A, Absher D, et al.Signatures of post-zygotic structural genetic aberrations in the cells ofhistologically normal breast tissue that can predispose to sporadic breastcancer. Genome Res 2015;25:1521–35.

126. Martincorena I, Roshan A, Gerstung M, Ellis P, Van Loo P, McLarenS, et al. Tumor evolution. High burden and pervasive positiveselection of somatic mutations in normal human skin. Science 2015;348:880–6.

127. Sherman ME, Drapkin RI, Horowitz NS, Crum CP, Friedman S, KwonJS, et al. Rationale for developing a specimen bank to study the patho-genesis of high-grade serous carcinoma: a review of the evidence. CancerPrev Res 2016;9:713–20.

128. Shi K, Carpenter MA, Banerjee S, Shaban NM, Kurahashi K, SalamangoDJ, et al. Structural basis for targeted DNA cytosine deamination andmutagenesis by APOBEC3A and APOBEC3B. Nat Struct Mol Biol2017;24:131–9.

129. Starrett GJ, Luengas EM, McCann JL, Ebrahimi D, Temiz NA, Love RP,et al. The DNA cytosine deaminase APOBEC3H haplotype I likely con-tributes to breast and lung cancer mutagenesis. Nat Commun 2016;7:12918.

130. Robles-Espinoza CD, Roberts ND, Chen S, Leacy FP, Alexandrov LB,Pornputtapong N, et al. Germline MC1R status influences somatic muta-tion burden in melanoma. Nat Commun 2016;7:12064.

131. Z�amborszky J, Szikriszt B,Gervai JZ, Pipek O, P�oti �A,Krzystanek M, et al.Loss of BRCA1 or BRCA2markedly increases the rate of base substitutionmutagenesis and has distinct effects on genomic deletions. Oncogene2017;36:746–55.

132. Agrawal N, Jiao Y, Bettegowda C, Hutfless SM, Wang Y, David S, et al.Comparative genomic analysis of esophageal adenocarcinoma and squa-mous cell carcinoma. Cancer Discov 2012;2:899–905.

133. Alexandrov LB, Nik-Zainal S, Siu HC, Leung SY, Stratton MR. Amutational signature in gastric cancer suggests therapeutic strategies.Nat Commun 2015;6:8683.

134. Connor AA, Denroche RE, Jang GH, Timms L, Kalimuthu SN, SelanderI, et al. Association of distinct mutational signatures with correlates ofIncreased Immune Activity in Pancreatic Ductal Adenocarcinoma. JAMAOncol 2016:[Epub ahead of print].

135. Secrier M, Li X, de Silva N, Eldridge MD, Contino G, Bornschein J,et al. Mutational signatures in esophageal adenocarcinoma defineetiologically distinct subgroups with therapeutic relevance. Nat Genet2016;48:1131–41.

136. Smid M, Rodriguez-Gonzalez FG, Sieuwerts AM, Salgado R, Prager-Vander Smissen WJ, Vlugt-Daane MV, et al. Breast cancer genome andtranscriptome integration implicates specific mutational signatures withimmune cell infiltration. Nat Commun 2016;7:12910.

137. Strickland KC, Howitt BE, Shukla SA, Rodig S, Ritterhouse LL, Liu JF,et al. Association andprognostic significance of BRCA1/2-mutation statuswith neoantigen load, number of tumor-infiltrating lymphocytes andexpression of PD-1/PD-L1 in high grade serous ovarian cancer. Onco-target 2016;7:13587–98.

138. Rashid M, Fischer A, Wilson CH, Tiffen J, Rust AG, Stevens P, et al.Adenoma development in familial adenomatous polyposis andMUTYH-associated polyposis: somatic landscape and driver genes. J Pathol2016;238:98–108.

139. Kim J, Mouw KW, Polak P, Braunstein LZ, Kamburov A, Tiao G, et al.Somatic ERCC2 mutations are associated with a distinct genomic signa-ture in urothelial tumors. Nat Genet 2016;48:600–6.

140. McCaskill-Stevens W, Pearson DC, Kramer BS, Ford LG, Lippman SM.Identifying and creating the next generation of community-basedcancer prevention studies: summary of a national cancer institute thinktank. Cancer Prev Res 2017;10:99–107.

141. Chen AC,Martin AJ, Choy B, Fernandez-Penas P, Dalziell RA,McKenzieCA, et al. A phase 3 randomized trial of nicotinamide for skin-cancerchemoprevention. N Engl J Med 2015;373:1618–26.

142. Alexandrov LB, Jones PH, Wedge DC, Sale JE, Campbell PJ, Nik-ZainalS, et al. Clock-like mutational processes in human somatic cells. NatGenet 2015;47:1402–7.

143. Podolskiy DI, Lobanov AV, Kryukov GV, Gladyshev VN. Analysis ofcancer genomes reveals basic features of human aging and its role incancer development. Nat Commun 2016;7:12157.

144. Alexandrov LB, Ju YS,Haase K, Van Loo P,Martincorena I, Nik-Zainal S,et al. Mutational signatures associated with tobacco smoking in humancancer. Science 2016;354:618–22.

145. Cooper CS, Eeles R, Wedge DC, Van Loo P, Gundem G, AlexandrovLB, et al. Analysis of the genetic phylogeny of multifocal prostatecancer identifies multiple independent clonal expansions in neoplas-tic and morphologically normal prostate tissue. Nat Genet 2015;47:367–72.

146. Kim SY, Jung SH, Kim MS, Baek IP, Lee SH, Kim TM, et al. Genomicdifferences between pure ductal carcinoma in situ and synchronousductal carcinoma in situ with invasive breast cancer. Oncotarget 2015;6:7597–607.

147. Sakr RA, Schizas M, Carniello JV, Ng CK, Piscuoglio S, Giri D, et al.Targeted capture massively parallel sequencing analysis of LCIS andinvasive lobular cancer: Repertoire of somatic genetic alterations andclonal relationships. Mol Oncol 2016;10:360–70.

148. Hosoda W, Chianchiano P, Griffin JF, Pittman ME, Brosens LA, No€e M,et al. Genetic analyses of isolated high-grade pancreatic intraepithelialneoplasia (HG-PanIN) reveal paucity of alterations in TP53 and SMAD4. JPathol 2017 Feb 11:[Epub ahead of print].

149. Wood HM,Conway C,Daly C,Chalkley R, Berri S, Senguven B, et al. Theclonal relationships between pre-cancer and cancer revealed byultra-deepsequencing. J Pathol 2015;237:296–306.

150. Vogelstein B, Kinzler KW. The path to cancer –three strikes and you'reout. N Engl J Med 2015;373:1895–8.

151. Vinayanuwattikun C, Le Calvez-Kelm F, Abedi-Ardekani B, Zaridze D,Mukeria A, Voegele C, et al. Elucidating genomic characteristics of lungcancer progression from in situ to Invasive Adenocarcinoma. Sci Rep2016;6:31628.

152. Kass EM, Moynahan ME, Jasin M. When genome maintenance goesbadly awry. Mol Cell 2016;62:777–87.

153. Ross-Innes CS, Becq J,Warren A, Cheetham RK,Northen H,O'DonovanM, et al. Whole-genome sequencing provides new insights into the clonalarchitecture of Barrett's esophagus and esophageal adenocarcinoma.Nat Genet 2015;47:1038–46.

154. Stachler MD, Taylor-Weiner A, Peng S, McKenna A, Agoston AT, OdzeRD, et al. Paired exome analysis of Barrett's esophagus and adenocarci-noma. Nat Genet 2015;47:1047–55.

155. Weaver JM, Ross-Innes CS, Shannon N, Lynch AG, Forshew T, BarberaM, et al.Ordering ofmutations in preinvasive disease stages of esophagealcarcinogenesis. Nat Genet 2014;46:837–43.

156. Zeng J, Kelbauskas L, Rezaie A, Lee K, Ueberroth B, Gao W,et al. Transcriptional regulation by normal epithelium of prema-lignant to malignant progression in Barrett's esophagus. Sci Rep2016;6:35227.

157. Nadatani Y, Huo X, Zhang X, Yu C, Cheng E, Zhang Q, et al. NOD-like receptor protein 3 inflammasome priming and activation inBarrett's epithelial cells. Cell Mol Gastroenterol Hepatol 2016;2:439–53.

158. Ju YS, Alexandrov LB, Gerstung M, Martincorena I, Nik-Zainal S,Ramakrishna M, et al. Origins and functional consequences ofsomatic mitochondrial DNA mutations in human cancer. eLife 2014;3:e02935.

159. Stewart JB, Alaei-Mahabadi B, Sabarinathan R, Samuelsson T, GorodkinJ, Gustafsson CM, et al. SimultaneousDNA andRNAmapping of somatic


The Precancer Atlas



mitochondrial mutations across diverse human cancers. PLoS Genet2015;11:e1005333.

160. Reznik E, Wang Q, La K, Schultz N, Sander C. Mitochondrialrespiratory gene expression is suppressed in many cancers. eLife 2017;6:e21592.

161. Lee S, Han MJ, Lee KS, Back SC, Hwang D, Kim HY, et al. Frequentoccurrence of mitochondrial DNA mutations in Barrett's metaplasiawithout the presence of dysplasia. PLoS One 2012;7:e37571.

162. Nicholson AM, Graham TA, Simpson A, Humphries A, Burch N,Rodriguez-Justo M, et al. Barrett's metaplasia glands are clonal, containmultiple stem cells and share a common squamous progenitor. Gut2012;61:1380–9.

163. Huhta H, Helminen O, Palom€aki S, Kauppila JH, Saarnio J, LehenkariPP, et al. Intratumoral lactate metabolism in Barrett's esophagus andadenocarcinoma. Oncotarget 2017 Feb 11:[Epub ahead of print].

164. Saini N, Roberts SA, Klimczak LJ, Chan K, Grimm SA, Dai S, et al. Theimpact of environmental and endogenous damage on somatic mutationload in human skin fibroblasts. PLoS Genet 2016;12:e1006385.

165. Martelotto LG, Baslan T, Kendall J, Geyer FC, Burke KA, Spraggon L,et al. Whole-genome single-cell copy number profiling from formalin-fixed paraffin-embedded samples. Nat Med 2017;Feb 6:[Epub aheadof print].

166. Godec J, Tan Y, Liberzon A, Tamayo P, Bhattacharya S, Butte AJ,et al. Compendium of immune signatures Identifies conserved andspecies-specific biology in response to inflammation. Immunity 2016;44:194–206.

167. Subramanian A, Tamayo P, Mootha VK,Mukherjee S, Ebert BL, GilletteMA, et al. Gene set enrichment analysis: a knowledge-based approach forinterpreting genome-wide expression profiles. Proc Natl Acad Sci U S A2005;102:15545–50.

168. Kim JW,Botvinnik OB, Abudayyeh O, Birger C, Rosenbluh J, Shrestha Y,et al. Characterizing genomic alterations in cancer by complementaryfunctional associations. Nat Biotechnol 2016;34:539–46.

169. Ying H, Dey P, Yao W, Kimmelman AC, Draetta GF, Maitra A, et al.Genetics and biology of pancreatic ductal adenocarcinoma. Genes Dev2016;30:355–85.

170. Liou GY,Doppler H,Necela B, Edenfield B, Zhang L, Dawson DW, et al.Mutant KRAS-induced expression of ICAM-1 in pancreatic acinar cellscauses attraction of macrophages to expedite the formation of precan-cerous lesions. Cancer Discov 2015;5:52–63.

171. Pylayeva-Gupta Y, Das S, Handler JS, Hajdu CH, Coffre M, Koralov SB,et al. IL35-Producing B Cells promote the development of pancreaticneoplasia. Cancer Discov 2016;6:247–55.

172. W€ormann SM, Diakopoulos KN, Lesina M, Alg€ul H. The immunenetwork in pancreatic cancer development and progression. Oncogene2014;33:2956–67.

173. Krogan NJ, Lippman S, Agard DA, Ashworth A, Ideker T. The cancer cellmap initiative: defining the hallmark networks of cancer. Mol Cell2015;58:690–8.

174. Hu D, Shilatifard A. Epigenetics of hematopoiesis and hematologicalmalignancies. Genes Dev 2016;30:2021–41.

175. Teschendorff AE, Gao Y, Jones A, Ruebner M, Beckmann MW,Wachter DL, et al. DNA methylation outliers in normal breast tissueidentify field defects that are enriched in cancer. Nat Commun2016;7:10478.

176. Yoda Y, Takeshima H, Niwa T, Kim JG, Ando T, Kushima R, et al.Integrated analysis of cancer-related pathways affected by genetic andepigenetic alterations in gastric cancer. Gastric Cancer 2015;18:65–76.

177. Wali RK, Momi N, Dela Cruz M, Calderwood AH, Stypula-Cyrus Y,Almassalha L, et al. Higher order chromatinmodulator cohesin SA1 is anearly biomarker for colon carcinogenesis: race-specific implications.Cancer Prev Res 2016;9:844–854.

178. Yang Z, Wong A, Kuh D, Paul DS, Rakyan VK, Leslie RD, et al.Correlation of an epigenetic mitotic clock with cancer risk. Genome Biol2016;17:205.

179. Siegmund KD, Marjoram P, Woo YJ, Tavare S, Shibata D. Inferringclonal expansion and cancer stem cell dynamics from DNA methyl-ation patterns in colorectal cancers. Proc Natl Acad Sci U S A 2009;106:4828–33.

180. Busque L, Patel JP, Figueroa ME, Vasanthakumar A, Provost S,Hamilou Z, et al. Recurrent somatic TET2 mutations in normal

elderly individuals with clonal hematopoiesis. Nat Genet 2012;44:1179–81.

181. Lu C, Ward PS, Kapoor GS, Rohle D, Turcan S, Abdel-Wahab O, et al.IDHmutation impairs histonedemethylation and results in ablock to celldifferentiation. Nature 2012;483:474–8.

182. Kwok B, Hall JM, Witte JS, Xu Y, Reddy P, Lin K, et al. MDS-associated somatic mutations and clonal hematopoiesis are commonin idiopathic cytopenias of undetermined significance. Blood 2015;126:2355–61.

183. Ortmann CA, Kent DG,Nangalia J, Silber Y,Wedge DC,Grinfeld J, et al.Effect of mutation order on myeloproliferative neoplasms. N Engl J Med2015;372:601–12.

184. Quivoron C, Couronne L,Della Valle V, Lopez CK, Plo I,Wagner-BallonO, et al. TET2 inactivation results in pleiotropic hematopoietic abnor-malities in mouse and is a recurrent event during human lymphomagen-esis. Cancer Cell 2011;20:25–38.

185. Blaschke K, Ebata KT, Karimi MM, Zepeda-Martinez JA, Goyal P,Mahapatra S, et al. VitaminC induces Tet-dependentDNAdemethylationand a blastocyst-like state in ES cells. Nature 2013;500:222–6.

186. Zhang Q, Zhao K, Shen Q, Han Y, Gu Y, Li X, et al. Tet2 is required toresolve inflammation by recruiting Hdac2 to specifically repress IL-6.Nature 2015;525:389–93.

187. Yue X, Trifari S, Aijo T, Tsagaratou A, Pastor WA, Zepeda-Martinez JA,et al. Control of Foxp3 stability throughmodulation of TET activity. J ExpMed 2016;213:377–97.

188. Permuth JB, Reid B, Earp M, Chen YA, Monteiro AN, Chen Z, et al.Inherited variants affecting RNA editingmay contribute to ovarian cancersusceptibility: results from a large-scale collaboration. Oncotarget2016;7:72381–94.

189. Han L, Diao L, Yu S, Xu X, Li J, Zhang R, et al. The Genomic Landscapeand Clinical Relevance of A-to-I RNA editing in human cancers. CancerCell 2015;28:515–28.

190. Wulff BE, Nishikura K. Modulation of microRNA expression andfunction by ADARs. Curr Top Microbiol Immunol 2012;353:91–109.

191. Chen L, Li Y, Lin CH, Chan TH, Chow RK, Song Y, et al. Recoding RNAediting of AZIN1 predisposes to hepatocellular carcinoma. Nat Med2013;19:209–16.

192. Jiang Q, Crews LA, Barrett CL, Chun HJ, Court AC, Isquith JM, et al.ADAR1 promotes malignant progenitor reprogramming in chronic mye-loid leukemia. Proc Natl Acad Sci U S A 2013;110:1041–6.

193. Qi L, Chan TH, Tenen DG, Chen L. RNA editome imbalance inhepatocellular carcinoma. Cancer Res 2014;74:1301–6.

194. Chen Y, Wang H, Lin W, Shuai P. ADAR1 overexpression is associatedwith cervical cancer progression and angiogenesis. Diagn Pathol2017;12:12.

195. Song C, Sakurai M, Shiromoto Y, Nishikura K. Functions of the RNAediting enzyme ADAR1 and their relevance to human diseases. Genes(Basel) 2016;7.

196. ZipetoMA, JiangQ,Melese E, JamiesonCH. RNA rewriting, recoding, andrewiring in human disease. Trends Mol Med 2015;21:549–59.

197. Kaufman CK,Mosimann C, Fan ZP, Yang S, Thomas AJ, Ablain J, et al. Azebrafish melanoma model reveals emergence of neural crest identityduring melanoma initiation. Science 2016;351:aad2197.

198. Kato S, Lippman SM, Flaherty KT, Kurzrock R. The conundrum ofgenetic "Drivers" in benign conditions. J Natl Cancer Inst 2016;108:1–13.

199. Patton EE, Widlund HR, Kutok JL, Kopani KR, Amatruda JF, MurpheyRD, et al. BRAF mutations are sufficient to promote nevi formation andcooperate with p53 in the genesis of melanoma. Curr Biol 2005;15:249–54.

200. McNeal AS, Liu K, Nakhate V, Natale CA, Duperret EK, Capell BC, et al.CDKN2B loss promotes progression from benign melanocytic nevus tomelanoma. Cancer Discov 2015;5:1072–85.

201. Xie X, Koh JY, Price S,White E,Mehnert JM. Atg7Overcomes senescenceand promotes growth of BrafV600E-driven melanoma. Cancer Discov2015;5:410–23.

202. Sanchez-Danes A, Hannezo E, Larsimont JC, Liagre M, Youssef KK,Simons BD, et al. Defining the clonal dynamics leading to mouse skintumour initiation. Nature 2016;536:298–303.

203. Youssef KK, Lapouge G, Bouvree K, Rorive S, Brohee S, Appelstein O,et al. Adult interfollicular tumour-initiating cells are reprogrammed into


Perspective



an embryonic hair follicle progenitor-like fate during basal cell carcinomainitiation. Nat Cell Biol 2012;14:1282–94.

204. Wei D, Wang L, Yan Y, Jia Z, Gagea M, Li Z, et al. KLF4 is essential forinduction of cellular identity change and acinar-to-ductal reprogram-ming during early pancreatic carcinogenesis. Cancer Cell 2016;29:324–38.

205. Liu X, Pitarresi JR, Cuiti~no MC, Kladney RD, Woelke SA, SizemoreGM, et al. Genetic ablation of Smoothened in pancreatic fibro-blasts increases acinar-ductal metaplasia. Genes Dev 2016;30:1943–55.

206. Willimsky G1, Cz�eh M, Loddenkemper C, Gellermann J, Schmidt K,Wust P, et al. Immunogenicity of premalignant lesions is the primarycause of general cytotoxic T lymphocyte unresponsiveness. J Exp Med2008;205:1687–700.

207. Keenan BP, Saenger Y, Kafrouni MI, Leubner A, Lauer P, Maitra A, et al. AListeria vaccine and depletion of T-regulatory cells activate immunityagainst early stage pancreatic intraepithelial neoplasms and prolongsurvival of mice. Gastroenterology 2014;146:1784–94.

208. Mu~noz-Fontela C,Mandinova A, Aaronson SA, Lee SW. Emerging roles ofp53 and other tumour-suppressor genes in immune regulation. Nat RevImmunol 2016;16:741–750.

209. Maldonado L, Teague JE, Morrow MP, Jotova I, Wu TC, Wang C, et al.Intramuscular therapeutic vaccination targeting HPV16 induces T cellresponses that localize in mucosal lesions. Sci Transl Med 2014;6:221ra13.

210. Kataoka K, Shiraishi Y, Takeda Y, Sakata S, MatsumotoM, Nagano S, et al.Aberrant PD-L1 expression through 30-UTR disruption in multiple can-cers. Nature 2016;534:402–6.

211. Mitra A, MacIntyre DA, Marchesi JR, Lee YS, Bennett PR, Kyrgiou M. Thevaginal microbiota, human papillomavirus infection and cervical intrae-pithelial neoplasia: what do we know and where are we going next?Microbiome 2016;4:58.

212. Tuna M, Amos CI. Next generation sequencing and its applications inHPV-associated cancers. Oncotarget 2017;8:8877–89.

213. Iheagwara UK, Beatty PL, Van PT, Ross TM, Minden JS, Finn OJ.Influenza virus infection elicits protective antibodies and T cellsspecific for host cell antigens also expressed as tumor-associatedantigens: a new view of cancer immunosurveillance. Cancer ImmunolRes 2014;2:263–73.

214. Dhodapkar MV, Sexton R, Das R, Dhodapkar KM, Zhang L, Sundaram R,et al. Prospective analysis of antigen-specific immunity, stem-cell anti-gens, and immune checkpoints in monoclonal gammopathy. Blood2015;126:2475–8.

215. Davoli T, Uno H, Wooten EC, Elledge SJ. Tumor aneuploidy correlateswith markers of immune evasion and with reduced response to immu-notherapy. Science 2017;355:eaaf8399.

216. Rashidian M, Keliher EJ, Bilate AM, Duarte JN, Wojtkiewicz GR, JacobsenJT, et al. Noninvasive imaging of immune responses. Proc Natl Acad SciU S A 2015;112:6146–51.

217. Cuccarese MF, Dubach JM, Pfirschke C, Engblom C, Garris C, Miller MA,et al. Heterogeneity of macrophage infiltration and therapeutic responsein lung carcinoma revealed by 3D organ imaging. Nat Commun2017;8:14293.

218. Serrao EM,KettunenMI, Rodrigues TB,Dzien P,Wright AJ, GopinathanA,et al. MRI with hyperpolarised [1-13C]pyruvate detects advanced pan-creatic preneoplasia prior to invasive disease in a mouse model. Gut2016;65:465–75.

219. Kimura T, McKolanis JR, Dzubinski LA, Islam K, Potter DM, SalazarAM, et al. MUC1 vaccine for individuals with advanced adenoma ofthe colon: a cancer immunoprevention feasibility study. Cancer PrevRes 2013;6:18–26.

220. Eikawa S,Nishida M,Mizukami S, Yamazaki C,Nakayama E,Udono H.Immune-mediated antitumor effect by type 2 diabetes drug, metformin.Proc Natl Acad Sci U S A 2015;112:1809–14.

221. Incio J, Suboj P, Chin SM, Vardam-Kaur T, Liu H, Hato T, et al.Metformin reduces desmoplasia in pancreatic cancer by reprogrammingstellate cells and tumor-associated macrophages. PLoS One 2015;10:e0141392.

222. Cuyas E, Fernandez-Arroyo S, Joven J, Menendez JA. Metformin targetshistone acetylation in cancer-prone epithelial cells. Cell Cycle 2016;15:3355–61.

223. Cao Y,Nishihara R,Qian ZR, Song M,Mima K, Inamura K, et al. Regularaspirin use associates with lower risk of colorectal cancers with lownumbers of Tumor-Infiltrating Lymphocytes. Gastroenterology 2016;151:879–92.

224. McLean MH,Murray GI, Stewart KN, Norrie G,Mayer C, Hold GL, et al.The inflammatory microenvironment in colorectal neoplasia. PLoS One2011;6:e15366.

225. Peters BA, Dominianni C, Shapiro JA, Church TR, Wu J, Miller G, et al.The gut microbiota in conventional and serrated precursors of colorectalcancer. Microbiome 2016;4:69.

226. Robles AI, Traverso G, Zhang M, Roberts NJ, Khan MA, Joseph C,et al. Whole-exome sequencing analyses of inflammatory boweldisease-associated colorectal cancers. Gastroenterology 2016;150:931–43.

227. Yaeger R, Shah MA, Miller VA, Kelsen JR, Wang K, Heins ZJ, et al.Genomic alterations observed in colitis-associated cancers are distinctfrom those found in sporadic colorectal cancers and vary by type ofinflammatory bowel disease. Gastroenterology 2016;151:278–87.

228. Chudnovskiy A, Mortha A, Kana V, Kennard A, Ramirez JD, Rahman A,et al. Host-protozoan interactions protect from mucosal infectionsthrough activation of the inflammasome. Cell 2016;167:444–56.

229. Filyk HA, Osborne LC. The multibiome: the intestinal ecosystem's influ-ence on immune homeostasis, health, and disease. EBioMedicine 2016;13:46–54.

230. Nowarski R, Jackson R,Gagliani N, de ZoeteMR, PalmNW, BailisW, et al.Epithelial IL-18 equilibrium controls barrier function in colitis. Cell2015;163:1444–56.

231. Earle KA, Billings G, Sigal M, Lichtman JS, Hansson GC, Elias JE, et al.Quantitative imaging of gut microbiota spatial organization. Cell HostMicrobe 2015;18:478–88.

232. Komaroff AL. The microbiome and risk for obesity and diabetes. JAMA2017;317:355–6.

233. Johnson CH, Spilker ME, Goetz L, Peterson SN, Siuzdak G. Metaboliteand microbiome interplay in cancer immunotherapy. Cancer Res 2016;76:6146–52.

234. Rooks MG, Garrett WS. Gut microbiota, metabolites and host immunity.Nat Rev Immunol 2016;16:341–52.

235. Bouslimani A, Porto C, Rath CM, Wang M, Guo Y, Gonzalez A, et al.Molecular cartography of the human skin surface in 3D. Proc Natl AcadSci U S A 2015;112:E2120–9.

236. Cunningham TJ, Tabacchi M, Eliane JP, Tuchayi SM, Manivasagam S,Mirzaalian H, et al. Randomized trial of calcipotriol combined with 5-fluorouracil for skin cancer precursor immunotherapy. J Clin Invest2017;127:106–16.

237. Koeppel M, Garcia-Alcalde F, Glowinski F, Schlaermann P, Meyer TF.Helicobacter pylori infection causes characteristic DNA damage patternsin human cells. Cell Rep 2015;11:1703–13.

238. Lennard KS, Goosen RW, Blackburn JM. Bacterially-associated tran-scriptional remodelling in a distinct genomic subtype of colorectalcancer provides a plausible molecular basis for disease development.PLoS One 2016;11:e0166282.

239. Thiele Orberg E, Fan H, Tam AJ, Dejea CM, Destefano Shields CE,Wu S, et al. The myeloid immune signature of enterotoxigenicBacteroides fragilis-induced murine colon tumorigenesis. MucosalImmunol 2016;10:421–33.

240. Bressa C, Bailen-Andrino M, Perez-Santiago J, Gonzalez-Soltero R, PerezM, Montalvo-Lominchar MG, et al. Differences in gut microbiota profilebetween women with active lifestyle and sedentary women. PLoS One2017;12:e0171352.

241. O'Keefe SJ, Li JV, Lahti L, Ou J, Carbonero F, Mohammed K, et al. Fat,fibre and cancer risk in African Americans and rural Africans. Nat Com-mun 2015;6:6342.

242. Grigg JB, Sonnenberg GF. Host-Microbiota interactions shapelocal and systemic inflammatory diseases. J Immunol 2017;198:564–71.

243. Mehta RS, Nishihara R, Cao Y, Song M, Mima K, Qian ZR, et al.Association of dietary patterns with risk of colorectal cancer subtypesclassified by fusobacterium nucleatum in tumor tissue. JAMA Oncol2017 Jan 26:[Epub ahead of print].

244. Beyaz S, Mana MD, Roper J, Kedrin D, Saadatpour A, Hong SJ, et al.High-fat diet enhances stemness and tumorigenicity of intestinal pro-genitors. Nature 2016;531:53–8.


The Precancer Atlas



245. Loo TM, Kamachi F, Watanabe Y, Yoshimoto S, Kanda H, Arai Y, et al.Gut Microbiota Promotes Obesity-Associated Liver Cancer throughPGE2-Mediated Suppression of Antitumor Immunity. Cancer Discov2017;Feb 15:[Epub ahead of print].

246. Gall A, Fero J, McCoy C, Claywell BC, Sanchez CA, Blount PL, et al.Bacterial composition of the human upper gastrointestinal tract micro-biome is dynamic and associated with genomic instability in a Barrett'sesophagus cohort. PLoS One 2015;10:e0129055.

247. Garraway LA, Lander ES. Lessons from the cancer genome. Cell 2013;153:17–37.

248. Bassani-Sternberg M, Braunlein E, Klar R, Engleitner T, Sinitcyn P,Audehm S, et al. Direct identification of clinically relevant neoepitopespresented on native human melanoma tissue by mass spectrometry.Nat Commun 2016;7:13404.

249. Olsen L, Johan Kudahl U, Winther O, Brusic V. Literature classificationfor semi-automated updating of biological knowledgebases. BMC Geno-mics 2013;14:S14.

250. Backert L, Kohlbacher O. Immunoinformatics and epitope prediction inthe age of genomic medicine. Genome Med 2015;7:119.

251. Larsen MV, Lundegaard C, Lamberth K, Buus S, Lund O, Nielsen M.Large-scale validation of methods for cytotoxic T-lymphocyte epitopeprediction. BMC Bioinformatics 2007;8:424.

252. Gubin MM, Artyomov MN, Mardis ER, Schreiber RD. Tumor neoanti-gens: building a framework for personalized cancer immunotherapy.J Clin Invest 2015;125:3413–21.

253. Rajasagi M, Shukla SA, Fritsch EF, Keskin DB, DeLuca D, Carmona E,et al. Systematic identification of personal tumor-specific neoantigens inchronic lymphocytic leukemia. Blood 2014;124:453–62.

254. Gubin MM, Zhang X, Schuster H, Caron E, Ward JP, Noguchi T, et al.Checkpoint blockade cancer immunotherapy targets tumour-specificmutant antigens. Nature 2014;515:577–81.

255. Stronen E, Toebes M, Kelderman S, van Buuren MM, Yang W, van RooijN, et al. Targetingof cancer neoantigenswithdonor-derived T cell receptorrepertoires. Science 2016;352:1337–41.

256. Duan F, Duitama J, Al Seesi S, Ayres CM, Corcelli SA, Pawashe AP, et al.Genomic and bioinformatic profiling of mutational neoepitopes revealsnew rules to predict anticancer immunogenicity. J Exp Med 2014;211:2231–48.

257. Srivastava PK. Neoepitopes of cancers: Looking back, looking ahead.Cancer Immunol Res 2015;3:969–77.

258. Zhang X, Sharma PK, Peter Goedegebuure S, Gillanders WE. Person-alized cancer vaccines: Targeting the cancer mutanome. Vaccine 2017;35:1094–100.

259. Welter D,MacArthur J,Morales J, Burdett T, Hall P, Junkins H, et al. TheNHGRI GWAS Catalog, a curated resource of SNP-trait associations.Nucleic Acids Res 2014;42:D1001–6.

260. Engin HB, Kreisberg JF, Carter H. Structure-based analysis reveals cancermissense mutations target protein interaction interfaces. PLoS One2016;11:e0152929.

261. Wang D, Quan Y, Yan Q, Morales JE, Wetsel RA. Targeted disruption ofthe beta2-microglobulin gene minimizes the immunogenicity of humanembryonic stem cells. Stem Cells Transl Med 2015;4:1234–45.

262. Echterdiek F, Janikovits J, Staffa L, Muller M, Lahrmann B,Fruhschutz M, et al. Low density of FOXP3-positive T cells innormal colonic mucosa is related to the presence of beta2-micro-globulin mutations in Lynch syndrome-associated colorectal can-cer. Oncoimmunology 2016;5:e1075692.

263. Zaretsky JM, Garcia-Diaz A, Shin DS, Escuin-Ordinas H, Hugo W, Hu-Lieskovan S, et al. Mutations associated with acquired resistance to PD-1blockade in melanoma. N Engl J Med 2016;375:819–29.

264. Yarchoan M, Johnson BA 3rd, Lutz ER, Laheru DA, Jaffee EM. Targetingneoantigens to augment antitumour immunity. Nat Rev Cancer 2017 Feb24:[Epub ahead of print].

265. Piunti A, Shilatifard A. Epigenetic balance of gene expression byPolycomb and COMPASS families. Science 2016;352:aad9780.

266. Lin C,Garruss AS, Luo Z,Guo F, Shilatifard A. The RNAPol II elongationfactor Ell3 marks enhancers in ES cells and primes future gene activation.Cell 2013;152:144–56.

267. Shilatifard A. The COMPASS family of histone H3K4 methylases:mechanisms of regulation in development and disease pathogenesis.Annu Rev Biochem 2012;81:65–95.

268. Hu D, Gao X, Cao K, Morgan MA, Mas G, Smith ER, et al. Notall H3K4 methylations are created equal: Mll2/COMPASS depen-dency in primordial germ cell specification. Mol Cell 2017;65:460–75.

269. Smith E, Lin C, Shilatifard A. The super elongation complex (SEC) andMLL in development and disease. Genes Dev 2011;25:661–72.

270. Lin C, Smith ER, Takahashi H, Lai KC, Martin-Brown S, Florens L, et al.AFF4, a component of the ELL/P-TEFb elongation complex and a sharedsubunit of MLL chimeras, can link transcription elongation to leukemia.Mol Cell 2010;37:429–37.

271. Mohan M, Lin C, Guest E, Shilatifard A. Licensed to elongate: amolecular mechanism for MLL-based leukaemogenesis. Nat Rev Cancer2010;10:721–8

272. Zhu L, Li Q, Wong SH, Huang M, Klein BJ, Shen J, et al. ASH1L linkshistone H3 Lysine 36 Dimethylation to MLL Leukemia. Cancer Discov2016;6:770–83.

273. Christofides A, Karantanos T, Bardhan K, Boussiotis VA. Epigeneticregulation of cancer biology and anti-tumor immunity by EZH2. Onco-target 2016;7:85624–40.

274. Zhang H,Qi J, Reyes JM, Li L, Rao PK, Li F, et al.OncogenicDeregulationof EZH2 as an opportunity for targeted therapy in lung cancer. CancerDiscov 2016;6:1006–21.

275. Kim KH, Roberts CW. Targeting EZH2 in cancer. Nat Med 2016;22:128–34.

276. Lund K, Adams PD, Copland M. EZH2 in normal and malignanthematopoiesis. Leukemia 2014;28:44–9.

277. Shimizu T, Kubovcakova L, Nienhold R, Zmajkovic J, Meyer SC, Hao-Shen H, et al. Loss of Ezh2 synergizes with JAK2-V617F in initiatingmyeloproliferative neoplasms and promoting myelofibrosis. J Exp Med2016;213:1479–96.

278. Kadoch C, Hargreaves DC, Hodges C, Elias L, Ho L, Ranish J, et al.Proteomic and bioinformatic analysis of mammalian SWI/SNF com-plexes identifies extensive roles in human malignancy. Nat Genet 2013;45:592–601.

279. Tordella L, Khan S, Hohmeyer A, Banito A, Klotz S, Raguz S, et al. SWI/SNF regulates a transcriptional program that induces senescence toprevent liver cancer. Genes Dev 2016;30:2187–98.

280. Mathur R, Alver BH, San Roman AK, Wilson BG, Wang X, Agoston AT,et al. ARID1A loss impairs enhancer-mediated gene regulation and drivescolon cancer in mice. Nat Genet 2017;49:296–302.

281. Kartha N, Shen L, Maskin C, Wallace M, Schimenti JC. The chromatinremodeling component arid1a is a suppressor of spontaneousmammarytumors in mice. Genetics 2016;203:1601–11.

282. Parsons DW, Jones S, Zhang X, Lin JC, Leary RJ, Angenendt P, et al. Anintegrated genomic analysis of human glioblastomamultiforme. Science2008;321:1807–12.

283. Dang L, White DW, Gross S, Bennett BD, Bittinger MA, Driggers EM,et al. Cancer-associated IDH1 mutations produce 2-hydroxyglutarate.Nature 2009;462:739–44.

284. Koivunen P, Lee S, Duncan CG, Lopez G, Lu G, Ramkissoon S, et al.Transformation by the (R)-enantiomer of 2-hydroxyglutarate linked toEGLN activation. Nature 2012;483:484–8.

285. Losman JA, Kaelin WG Jr. What a difference a hydroxyl makes:mutant IDH, (R)-2-hydroxyglutarate, and cancer. Genes Dev 2013;27:836–52.

286. Xu W, Yang H, Liu Y, Yang Y,Wang P, Kim SH, et al. Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of alpha-ketoglutarate-depen-dent dioxygenases. Cancer Cell 2011;19:17–30.

287. Koeffler HP, Leong G. Preleukemia: one name, many meanings.Leukemia 2017;31:534–42.

288. Schuyler RP,Merkel A, Raineri E, Altucci L, Vellenga E,Martens JH, et al.Distinct trends ofDNAmethylation patterning in the Innate andAdaptiveImmune Systems. Cell Rep 2016;17:2101–11.

289. Dimitrova E, Turberfield AH, Klose RJ. Histone demethylases inchromatin biology and beyond. EMBO Rep 2015;16:1620–39.

290. Mazor T, Pankov A, Song JS, Costello JF. Intratumoral Heterogeneity ofthe Epigenome. Cancer Cell 2016;29:440–51.

291. Gr€un D, Muraro MJ, Boisset JC, Wiebrands K, Lyubimova A,Dharmadhikari G, et al. De novo prediction of stem cell identi-ty using single-cell transcriptome data. Cell Stem Cell 2016;19:266–77.


Perspective



292. Stegle O, Teichmann SA, Marioni JC. Computational and analyti-cal challenges in single-cell transcriptomics. Nat Rev Genet 2015;16:133–45.

293. Mahata B, Zhang X, Kolodziejczyk AA, Proserpio V, Haim-Vilmovsky L,Taylor AE, et al. Single-cell RNA sequencing reveals T helper cellssynthesizing steroids de novo to contribute to immune homeostasis.Cell Rep 2014;7:1130–42.

294. Gerlinger M,Rowan AJ,Horswell S, Larkin J, Endesfelder D,Gronroos E,et al. Intratumor heterogeneity and branched evolution revealed bymultiregion sequencing. N Engl J Med 2012;366:883–92.

295. Navin NE. Cancer genomics: one cell at a time. Genome Biol 2014;15:452.

296. Almendro V, Kim HJ, Cheng YK, Gonen M, Itzkovitz S, Argani P, et al.Genetic and phenotypic diversity in breast tumor metastases. Cancer Res2014;74:1338–48.

297. Park SY, Gonen M, Kim HJ, Michor F, Polyak K. Cellular and geneticdiversity in the progression of in situ human breast carcinomas to aninvasive phenotype. J Clin Invest 2010;120:636–44.

298. Grundberg I, Kiflemariam S,Mignardi M, Imgenberg-Kreuz J, Edlund K,Micke P, et al. In situ mutation detection and visualization of intratumorheterogeneity for cancer research and diagnostics. Oncotarget 2013;4:2407–18.

299. Ikeda S, Takabe K, Inagaki M, Funakoshi N, Suzuki K. Detection of genepoint mutation in paraffin sections using in situ loop-mediated isother-mal amplification. Pathol Int 2007;57:594–9.

300. Janiszewska M, Liu L, Almendro V, Kuang Y, Paweletz C, Sakr RA, et al.In situ single-cell analysis identifies heterogeneity for PIK3CA mutationand HER2 amplification in HER2-positive breast cancer. Nat Genet2015;47:1212–9.

301. Martinez P, Timmer MR, Lau CT, Calpe S, Sancho-Serra MdelC, Straub D, et al. Dynamic clonal equilibrium and predeter-mined cancer risk in Barrett's oesophagus. Nat Commun 2016;7:12158.

302. Hou Y, Song L, Zhu P, Zhang B, Tao Y, Xu X, et al. Single-cell exomesequencing and monoclonal evolution of a JAK2-negative myeloprolif-erative neoplasm. Cell 2012;148:873–85.

303. Kleppe M, Kwak M,Koppikar P, Riester M, Keller M, Bastian L, et al. JAK-STAT pathway activation in malignant and nonmalignant cells contri-butes to MPN pathogenesis and therapeutic response. Cancer Discov2015;5:316–31.

304. Gawad C, Koh W, Quake SR. Dissecting the clonal origins of childhoodacute lymphoblastic leukemia by single-cell genomics. Proc Natl Acad SciU S A 2014;111:17947–52.

305. Stahl PL, Salmen F, Vickovic S, Lundmark A, Navarro JF, Magnusson J,et al. Visualization and analysis of gene expression in tissue sections byspatial transcriptomics. Science 2016;353:78–82.

306. Sheng K, Cao W, Niu Y, Deng Q, Zong C. Effective detection of variationin single-cell transcriptomes using MATQ-seq. Nat Methods 2017;14:267–270.

307. Rotem A, Ram O, Shoresh N, Sperling RA, Goren A, Weitz DA, et al.Single-cell ChIP-seq reveals cell subpopulations defined by chromatinstate. Nat Biotechnol 2015;33:1165–72.

308. Cleary B, Brito IL, Huang K, Gevers D, Shea T, Young S, et al. Detectionof low-abundance bacterial strains in metagenomic datasets by eigen-genome partitioning. Nat Biotechnol 2015;33:1053–60.

309. Geva-Zatorsky N, Alvarez D, Hudak JE, Reading NC, Erturk-HasdemirD, Dasgupta S, et al. In vivo imaging and tracking of host-microbiotainteractions via metabolic labeling of gut anaerobic bacteria. Nat Med2015;21:1091–100.

310. Diaz LA Jr., Bardelli A. Liquid biopsies: genotyping circulating tumorDNA. J Clin Oncol 2014;32:579–86.

311. Grun D, van Oudenaarden A. Design and analysis of single-cellsequencing experiments. Cell 2015;163:799–810.

312. Macaulay IC, Voet T. Single cell genomics: advances and future perspec-tives. PLoS Genet 2014;10:e1004126.

313. Chen X, Love JC, Navin NE, Pachter L, Stubbington MJ, Svensson V,et al. Single-cell analysis at the threshold. Nat Biotechnol 2016;34:1111–18.

314. Nestorowa S, Hamey FK, Pijuan Sala B, Diamanti E, Shepherd M,Laurenti E, et al. A single-cell resolution map of mouse hematopoieticstem and progenitor cell differentiation. Blood 2016;128:e20–31.

315. Pestrin M, Salvianti F, Galardi F, De Luca F, Turner N, Malorni L, et al.Heterogeneity of PIK3CA mutational status at the single cell level incirculating tumor cells frommetastatic breast cancer patients. Mol Oncol2015;9:749–57.

316. Stephens ZD, Lee SY, Faghri F, Campbell RH, Zhai C, Efron MJ, et al. Bigdata: Astronomical or Genomical? PLoS Biol 2015;13:e1002195.

317. Bock C, Farlik M, Sheffield NC.Multi-Omics of single cells: strategies andapplications. Trends Biotechnol 2016;34:605–8.

318. Haber DA, Velculescu VE. Blood-based analyses of cancer: circu-lating tumor cells and circulating tumor DNA. Cancer Discov 2014;4:650–61.

319. Forshew T, Murtaza M, Parkinson C, Gale D, Tsui DW, Kaper F, et al.Noninvasive identification and monitoring of cancer mutations by tar-geted deep sequencing of plasma DNA. Sci Transl Med 2012;4:136ra68.

320. Leary RJ, Sausen M, Kinde I, Papadopoulos N,Carpten JD,Craig D, et al.Detectionof chromosomal alterations in the circulationof cancer patientswith whole-genome sequencing. Sci Transl Med 2012;4:162ra54.

321. Nair N, Camacho-Vanegas O, Rykunov D, Dashkoff M, Camacho SC,Schumacher CA, et al. Genomic analysis of uterine lavage fluid detectsearly endometrial cancers and reveals a prevalent landscape of drivermutations in women without histopathologic evidence of cancer: aprospective cross-sectional study. PLoS Med 2016;13:e1002206.

322. Sausen M, Phallen J, Adleff V, Jones S, Leary RJ, Barrett MT, et al. Clinicalimplications of genomic alterations in the tumour and circulation ofpancreatic cancer patients. Nat Commun 2015;6:7686.

323. Tie J, Wang Y, Tomasetti C, Li L, Springer S, Kinde I, et al. Circulatingtumor DNA analysis detects minimal residual disease and predictsrecurrence in patients with stage II colon cancer. Sci Transl Med 2016;8:346ra92.

324. Birkenkamp-Demtroder K,Nordentoft I, Christensen E,Hoyer S, ReinertT, Vang S, et al. Genomic alterations in liquid biopsies from patients withbladder cancer. Eur Urol 2016;70:75–82.

325. Izumchenko E, Chang X, Brait M, Fertig E, Kagohara LT, Bedi A, et al.Targeted sequencing reveals clonal genetic changes in the progression ofearly lung neoplasms and paired circulating DNA. Nat Commun2015;6:8258.

326. Guerrero-Preston R, Valle BL, Jedlicka A, Turaga N, Folawiyo O, Pirini F,et al. Molecular triage of premalignant lesions in liquid-based cervicalcytology and circulating cell-free dna from urine, using a panel ofmethylated human papilloma virus and host genes. Cancer Prev Res2016;9:915–24.

327. Fernandez-Cuesta L, Perdomo S, Avogbe PH, Leblay N, DelhommeTM, Gaborieau V, et al. Identification of Circulating Tumor DNA forthe Early Detection of Small-cell Lung Cancer. EBioMedicine 2016;10:117–23.

328. Newman AM, Lovejoy AF, Klass DM, Kurtz DM, Chabon JJ, Scherer F,et al. Integrated digital error suppression for improved detection ofcirculating tumor DNA. Nat Biotechnol 2016;34:547–55.

329. Cheng F, Su L, Qian C. Circulating tumor DNA: a promising biomarkerin the liquid biopsy of cancer. Oncotarget 2016;7:48832–41.

330. Warton K, Samimi G. Methylation of cell-free circulating DNA in thediagnosis of cancer. Front Mol Biosci 2015;2:13.

331. Wen L, Li J, Guo H, Liu X, Zheng S, Zhang D, et al. Genome-scaledetection of hypermethylated CpG islands in circulating cell-free DNA ofhepatocellular carcinoma patients. Cell Res 2015;25:1250–64.

332. Best MG, Sol N, Kooi I, Tannous J, Westerman BA, Rustenburg F, et al.RNA-Seq of tumor-educated platelets enables blood-based pan-cancer,multiclass, and molecular pathway cancer diagnostics. Cancer Cell2015;28:666–76.

333. Ilie M, Hofman V, Long-Mira E, Selva E, Vignaud JM, Padovani B,et al. "Sentinel" circulating tumor cells allow early diagnosis oflung cancer in patients with chronic obstructive pulmonary disease.PLoS One 2014;9:e111597.

334. Silvestri GA, Vachani A,Whitney D, Elashoff M, Porta Smith K, FergusonJS, et al. A bronchial genomic classifier for the diagnostic evaluation oflung cancer. N Engl J Med 2015;373:243–51.

335. Perez-Rogers JF, Gerrein J, Anderlind C, Liu G, Zhang S, Alekseyev Y,et al. Shared gene expression alterations in nasal and bronchial epithe-lium for lung cancer detection. J Natl Cancer Inst 2017 in press.

336. Pantel K. Blood-based analysis of circulating cell-free DNA and tumorcells for early cancer detection. PLoS Med 2016;13:e1002205.


The Precancer Atlas



337. Gorges TM, Kuske A, Rock K, Mauermann O, Muller V, Peine S, et al.Accession of tumor heterogeneity by multiplex transcriptome profilingof single circulating tumor cells. Clin Chem 2016;62:1504–15.

338. Tsay JC, Li Z, Yie TA, Wu F, Segal L, Greenberg AK, et al. Molecularcharacterization of the peripheral airway field of cancerization in lungadenocarcinoma. PLoS One 2015;10:e0118132.

339. Pipinikas CP, Kiropoulos TS, Teixeira VH, Brown JM, Varanou A, FalzonM, et al. Cell migration leads to spatially distinct but clonally relatedairway cancer precursors. Thorax 2014;69:548–57.

340. Koper A, Zeef LA, Joseph L, Kerr K, Gosney J, Lindsay MA, et al. Wholetranscriptome analysis of pre-invasive and invasive early squamouslung carcinoma in archival laser microdissected samples. Respir Res2017;18:12.

341. Jeong Y, Hoang NT, Lovejoy A, Stehr H, Newman AM, Gentles AJ, et al.Role of KEAP1/NRF2 and TP53 mutations in lung squamous cellcarcinoma development and radiation resistance. Cancer Discov 2017;7:86–101.

342. Fitzgerald DM, Hastings PJ, Rosenberg SM. Stress-induced mutagenesis:implications in cancer and drug resistance. Ann Rev Cancer Biol2017;1:6.1–6.22.

343. Li X, Paulson TG, Galipeau PC, Sanchez CA, Liu K, Kuhner MK, et al.Assessment of esophageal adenocarcinoma risk using somatic chromo-some alterations in longitudinal samples in Barrett's esophagus. CancerPrev Res 2015;8:845–56.

344. Jaiswal S, Fontanillas P, Flannick J, Manning A, Grauman PV, Mar BG,et al. Age-related clonal hematopoiesis associatedwith adverse outcomes.N Engl J Med 2014;371:2488–98.

345. Xie M, Lu C, Wang J, McLellan MD, Johnson KJ, Wendl MC, et al. Age-related mutations associated with clonal hematopoietic expansion andmalignancies. Nat Med 2014;20:1472–8.

346. Bejar R, Stevenson K, Abdel-WahabO,Galili N, Nilsson B,Garcia-ManeroG, et al. Clinical effect of point mutations in myelodysplastic syndromes.N Engl J Med 2011;364:2496–506.

347. Steensma DP, Bejar R, Jaiswal S, Lindsley RC, Sekeres MA, Hasserjian RP,et al. Clonal hematopoiesis of indeterminate potential and its distinctionfrom myelodysplastic syndromes. Blood 2015;126:9–16.

348. Young AL, Challen GA, Birmann BM,Druley TE. Clonal haematopoiesisharbouring AML-associated mutations is ubiquitous in healthy adults.Nat Commun 2016;7:12484.

349. Park CY (ed.). Hematopoiesis in Aging. Semin Hematol 2016;54;1–56.350. Kotini AG, Chang CJ, Chow A, Yuan H, Ho TC, Wang T, et al. Stage-

specific human induced pluripotent stem cells map the progression ofmyeloid transformation to transplantable leukemia. Cell Stem Cell2017;20:315–28.

351. Matatall KA, Jeong M, Chen S, Sun D, Chen F, Mo Q, et al. Chronicinfection depletes hematopoietic stem cells through stress-induced ter-minal differentiation. Cell Rep 2016;17:2584–95.

352. Ogawa S. Clonal hematopoiesis in acquired aplastic anemia. Blood2016;128:337–47.

353. Cargo CA, Rowbotham N, Evans PA, Barrans SL, Bowen DT, Crouch S,et al. Targeted sequencing identifies patients with preclinical MDS at highrisk of disease progression. Blood 2015;126:2362–5.

354. Meyer SE, Qin T, Muench DE, Masuda K, Venkatasubramanian M, OrrE, et al. DNMT3A Haploinsufficiency Transforms FLT3ITD myeloprolif-erative disease into a rapid, spontaneous, and fully penetrant acutemyeloid leukemia. Cancer Discov 2016;6:501–15.

355. Lubking A, Vosberg S, Konstandin NP, Dufour A, Graf A, Krebs S, et al.Young woman with mild bone marrow dysplasia, GATA2 and ASXL1mutation treated with allogeneic hematopoietic stem cell transplanta-tion. Leuk Res Rep 2015;4:72–5.

356. Hinds DA, Barnholt KE, Mesa RA, Kiefer AK, Do CB, Eriksson N, et al.Germ line variants predispose to both JAK2 V617F clonal hematopoiesisand myeloproliferative neoplasms. Blood 2016;128:1121–8.

357. Churpek JE, Pyrtel K, Kanchi KL, Shao J, Koboldt D, Miller CA, et al.Genomic analysis of germ line and somatic variants in familial myelo-dysplasia/acute myeloid leukemia. Blood 2015;126:2484–90.

358. Parikh SA, Kay NE, Shanafelt TD. Monoclonal B-cell lymphocytosis:update ondiagnosis, clinical outcome, and counseling. ClinAdvHematolOncol 2013;11:720–9.

359. Slager SL, Rabe KG, Achenbach SJ, Vachon CM, Goldin LR,Strom SS, et al. Genome-wide association study identifies a novel

susceptibility locus at 6p21.3 among familial CLL. Blood 2011;117:1911–6.

360. Ojha J, Secreto C, Rabe K, Ayres-Silva J, Tschumper R, Dyke DV, et al.Monoclonal B-cell lymphocytosis is characterized by mutations in CLLputative driver genes and clonal heterogeneity many years before diseaseprogression. Leukemia 2014;28:2395–8.

361. Puente XS, Bea S, Valdes-Mas R, Villamor N, Gutierrez-Abril J, Martin-Subero JI, et al. Non-coding recurrent mutations in chronic lymphocyticleukaemia. Nature 2015;526:519–24.

362. Barrio S, Shanafelt TD,Ojha J, Chaffee KG, Secreto C, Kortum KM, et al.Genomic characterization of high-count MBL cases indicates that earlydetection of driver mutations and subclonal expansion are predictors ofadverse clinical outcome. Leukemia 2017;31:170–76.

363. Goldin LR, Lanasa MC, Slager SL, Cerhan JR, Vachon CM, StromSS, et al. Common occurrence of monoclonal B-cell lymphocytosisamong members of high-risk CLL families. Br J Haematol 2010;151:152–8.

364. Oddsson A, Kristinsson SY, Helgason H, Gudbjartsson DF, MassonG, Sigurdsson A, et al. The germline sequence variant rs2736100_C inTERT associates with myeloproliferative neoplasms. Leukemia 2014;28:1371–4.

365. Landau DA, Tausch E, Taylor-Weiner AN, Stewart C, Reiter JG, Bahlo J,et al. Mutations driving CLL and their evolution in progression andrelapse. Nature 2015;526:525–30.

366. Moreira J, Rabe KG, Cerhan JR, Kay NE, Wilson JW, Call TG, et al.Infectious complications among individuals with clinical monoclonal B-cell lymphocytosis (MBL): a cohort study of newly diagnosed casescompared to controls. Leukemia 2013;27:136–41.

367. Solomon BM, Chaffee KG,Moreira J, Schwager SM, Cerhan JR, Call TG,et al. Risk of non-hematologic cancer in individuals with high-countmonoclonal B-cell lymphocytosis. Leukemia 2016;30:331–6.

368. Anderson LA, Landgren O, Engels EA. Common community acquiredinfections and subsequent risk of chronic lymphocytic leukaemia. Br JHaematol 2009;147:444–9.

369. Slager SL. Genome-wide association analysis implicates dysregulation ofimmunity genes in chronic lymphocytic leukemia. Nat Commun 2017;141:14175.

370. Ramsay AG, Johnson AJ, Lee AM, Gorgun G, Le Dieu R, Blum W, et al.Chronic lymphocytic leukemia T cells show impaired immunologicalsynapse formation that can be reversed with an immunomodulatingdrug. J Clin Invest 2008;118:2427–37.

371. Shanafelt TD,Ramsay AG, Zent CS, Leis JF, Tun HW,Call TG, et al. Long-term repair of T-cell synapse activity in a phase II trial of chemoimmu-notherapy followed by lenalidomide consolidation in previously untreat-ed chronic lymphocytic leukemia (CLL). Blood 2013;121:4137–41.

372. Henry CJ, Casas-Selves M, Kim J, Zaberezhnyy V, Aghili L, DanielAE, et al. Aging-associated inflammation promotes selection for adap-tive oncogenic events in B cell progenitors. J Clin Invest 2015;125:4666–80.

373. Martin-Lorenzo A,Hauer J, Vicente-Duenas C,Auer F,Gonzalez-HerreroI, Garcia-Ramirez I, et al. Infection Exposure is a Causal Factor in B-cellPrecursor Acute Lymphoblastic Leukemia as a Result of Pax5-InheritedSusceptibility. Cancer Discov 2015;5:1328–43.

374. Ganapathi KA, Pittaluga S, Odejide OO, Freedman AS, Jaffe ES. Earlylymphoid lesions: conceptual, diagnostic and clinical challenges. Hae-matologica 2014;99:1421–32.

375. Cowan G, Weston-Bell NJ, Bryant D, Seckinger A, Hose D, Zojer N,et al. Massive parallel IGHV gene sequencing reveals a germinal centerpathway in origins of human multiple myeloma. Oncotarget 2015;6:13229–40.

376. Agirre X,CastellanoG, PascualM,Heath S, KulisM, Segura V, et al.Whole-epigenome analysis inmultiplemyeloma reveals DNAhypermethylationof B cell-specific enhancers. Genome Res 2015;25:478–87.

377. Dhodapkar MV. MGUS to myeloma: a mysterious gammopathy ofunderexplored significance. Blood 2016;128:2599–606.

378. Rossi A, Voigtlaender M, Janjetovic S, Thiele B, Alawi M, M€arz M, et al.Mutational landscape reflects the biological continuum of plasma celldyscrasias. Blood Cancer J 2017;7:e537.

379. Paiva B,Martinez-Lopez J, Corchete LA, Sanchez-VegaB, Rapado I, PuigN,et al. Phenotypic, transcriptomic, and genomic features of clonal plasmacells in light-chain amyloidosis. Blood 2016;127:3035–9.


Perspective



380. Das R, Strowig T, Verma R, Koduru S, Hafemann A, Hopf S, et al.Microenvironment-dependent growth of pre-neoplastic and malignantplasma cells in humanized mice. Nat Med 2016;22:1351–7.

381. Weinhold N, Johnson DC, Rawstron AC, Forsti A, Doughty C, Vijayak-rishnan J, et al. Inherited genetic susceptibility to monoclonal gammo-pathy of unknown significance. Blood 2014;123:2513–7.

382. Nair S, Branagan AR, Liu J, Boddupalli CS, Mistry PK, Dhodapkar MV.Clonal immunoglobulin against lysolipids in the origin of myeloma.N Engl J Med 2016;374:555–61.

383. Pavlova EV, Archer J, Wang S, Dekker N, Aerts JM, Karlsson S, et al.Inhibition of UDP-glucosylceramide synthase in mice prevents Gaucherdisease-associated B-cell malignancy. J Pathol 2015;235:113–24.

384. Kensler TW, Spira A, Garber JE, Szabo E, Lee JJ, Dong Z, et al. Trans-forming cancer prevention through precision medicine and immune-oncology. Cancer Prev Res 2016;9:2–10.

385. Sedic M, Kuperwasser C. BRCA1-hapoinsufficiency: unraveling themolecular and cellular basis for tissue-specific cancer. Cell Cycle 2016;15:621–7.

386. Bauman JE, Grandis J. Oral Cancer Chemoprevention–The End ofEPOC, the Beginning of an Epoch of Molecular Selection. JAMA Oncol2016;2:178–9.

387. WilliamWN Jr, Papadimitrakopoulou V, Lee JJ,Mao L, Cohen EE, LinHY,et al. Erlotinib and the Risk of Oral Cancer: The Erlotinib Prevention ofOral Cancer (EPOC) Randomized Clinical Trial. JAMA Oncol 2016;2:209–16.

388. William WN Jr, Uraoka N, Peng SA, Lee JJ, El-Naggar AK, Parra E, et al.Abstract 387: Immune profiling of oral pre-malignant lesions (OPLs):an Erlotinib Prevention of Oral Cancer (EPOC) study biobank analysis.J Clin Oncol/ASCO 2017.

389. Lam S,Mandrekar SJ,Gesthalter Y, Allen Ziegler KL, Seisler DK,MidthunDE, et al. A randomized phase IIb trial of myo-inositol in smokers withbronchial dysplasia. Cancer Prev Res 2016;9:906–14.

390. Zumwalt TJ,WodarzD, KomarovaNL, Toden S, Turner J, Cardenas J, et al.Aspirin-induced chemoprevention and response kinetics are enhanced byPIK3CA mutations in colorectal cancer cells. Cancer Prev Res 2017;10:208–18.

391. Drew DA, Cao Y, Chan AT. Aspirin and colorectal cancer: the promise ofprecision chemoprevention. Nat Rev Cancer 2016;16:173–86.

392. KettnerNM,VoicuH, FinegoldMJ, CoarfaC, Sreekumar A, Putluri N, et al.Circadian homeostasis of livermetabolism suppresses hepatocarcinogen-esis. Cancer Cell 2016;30:909–24.

393. Neuschwander-Tetri BA, Loomba R, Sanyal AJ, Lavine JE, Van NattaML, Abdelmalek MF, et al. Farnesoid X nuclear receptor ligand obeti-cholic acid for non-cirrhotic, non-alcoholic steatohepatitis (FLINT): amulticentre, randomised, placebo-controlled trial. Lancet 2015;385:956–65.

394. Ross-Innes CS, Chettouh H, Achilleos A, Galeano-Dalmau N, Debiram-Beecham I, MacRae S, et al. Risk stratification of Barrett's oesophagususing a non-endoscopic sampling method coupled with a biomarkerpanel: a cohort study. Lancet Gastroenterol Hepatol 2017;2:23–31.

395. Emmons KM, Colditz GA. Realizing the potential of cancer prevention -the role of implementation science. N Engl J Med 2017;376:986–90.

396. Westrich JA, Warren CJ, Pyeon D. Evasion of host immune defenses byhuman papillomavirus. Virus Res 2017;231:21–33.

397. Roh W, Chen PL, Reuben A, Spencer CN, Prieto PA, Miller JP, et al.Integrated molecular analysis of tumor biopsies on sequential CTLA-4and PD-1 blockade reveals markers of response and resistance. Sci TranslMed 2017;9:eaah3560.

398. Ho TT, Warr MR, Adelman ER, Lansinger OM, Flach J, Verovskaya EV,et al. Autophagy maintains the metabolism and function of young andold stem cells. Nature 2017;543:205–10.

399. Corriden R, Hollands A, Olson J, Derieux J, Lopez J, Chang JT, et al.Tamoxifen augments the innate immune function of neutrophilsthrough modulation of intracellular ceramide. Nat Commun 2015;6:8369.

400. Chen L, Ge B, Casale FP, Vasquez L, Kwan T, Garrido-Martin D, et al.Genetic drivers of epigenetic and transcriptional variation in humanimmune cells. Cell 2016;167:1398–414.

401. Ecker S, Chen L, Pancaldi V, Bagger FO, Fernandez JM, Carrillo de SantaPau E, et al. Genome-wide analysis of differential transcriptional andepigenetic variability across human immune cell types. Genome Biol2017;18:18.

402. Krimmel JD, Schmitt MW,Harrell MI, Agnew KJ, Kennedy SR, EmondMJ,et al. Ultra-deep sequencing detects ovarian cancer cells in peritonealfluidand reveals somatic TP53 mutations in noncancerous tissues. Proc NatlAcad Sci U S A 2016;113:6005–10.

403. Abbosh C, Venkatesan S, Janes SM, Fitzgerald RC, Swanton C.Evolutionary dynamics in pre-invasive neoplasia. Curr Opin Syst Biol2017 Feb 16:[Epub ahead of print].

404. Pettapiece-Phillips R, Kotlyar M, Chehade R, Salmena L, Narod SA,Akbari M, et al. Uninterrupted sedentary behavior downregulates BRCA1gene expression. Cancer Prev Res 2016;9:83–8.

405. Tanay A, Regev A. Scaling single-cell genomics from phenomenology tomechanism. Nature 2017;541:331–8.

406. Drost J, van Jaarsveld RH, Ponsioen B, Zimberlin C, van Boxtel R, BuijsA, et al. Sequential cancer mutations in cultured human intestinal stemcells. Nature 2015;521:43–7.

407. Keysselt K, Kreutzmann T, Rother K, Kerner C, Krohn K, Przybilla J, et al.Different in vivo and in vitro transformation of intestinal stem cellsin mismatch repair deficiency. Oncogene 2016 Dec 12:[Epub aheadof print].

408. Zhang Z, Christin JR, Wang C, Ge K, Oktay MH, GuoW. Mammary-stem-cell-based somatic mousemodels reveal breast cancer drivers causing cellfate dysregulation. Cell Rep 2016;16:3146–56.

409. GundryMC, Brunetti L, Lin A,Mayle AE, Kitano A,Wagner D, et al. Highlyefficient genome editing ofmurine and human hematopoietic progenitorcells by CRISPR/Cas9. Cell Rep 2016;17:1453–61.

410. Papapetrou EP. Patient-derived induced pluripotent stem cellsin cancer research and precision oncology. Nat Med 2016;22:1392–401.

411. Zumwalde NA, Haag JD, Sharma D, Mirrielees JA, Wilke LG, GouldMN, et al. Analysis of immune cells from human mammary ductalepithelial organoids reveals Vdelta2þ T cells that efficiently targetbreast carcinoma cells in the presence of bisphosphonate. Cancer PrevRes 2016;9:305–16.

412. Yamamoto Y, Wang X, Bertrand D, Kern F, Zhang T, Duleba M, et al.Mutational spectrumof Barrett's stem cells suggests paths to initiation of aprecancerous lesion. Nat Commun 2016;7:10380.


The Precancer Atlas



2017;77:1510-1541. Cancer Res Avrum Spira, Matthew B. Yurgelun, Ludmil Alexandrov, et al. Precancer Atlas to Drive Precision Prevention Trials

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