5Molecular Classification and PrognosticSignatures of Breast Tumors

Luciane R. Cavalli and Iglenir J. Cavalli

5.1 Introduction

Breast cancer is a complex and heterogeneous disease wheretumors of the same apparent prognostic type can differwidely in their responsiveness to therapy and survival rates.Traditionally, the classification of breast cancer is per-formed on the basis of clinical–histopathological parame-ters, such as age, tumor size, histological grade, lymph nodestatus, and analysis of estrogen receptor (ER), progesteronereceptor (PR), and human epidermal growth factor receptor2 (HER2) expression. The evaluation of these combinedfactors has been widely used in clinical practice and formedthe basis to classify patients into various risk categories suchas the St. Gallen criteria [1] and the Nottingham PrognosticIndex [2]. However the markedly extensive breast cancerheterogeneity combined with the lack of reliable predictivefactors among these categories limits their ability todistinguish subtle phenotypic differences that may presentrelevant therapeutic implications.

In the past decade, with the development of high-throughput microarray platforms, genome-wide-basedmethods have been widely employed and a molecularclassification of breast cancer has emerged. Gene expres-sion profiling studies have showed that expression patternanalysis can refine the classification of breast tumors intodifferent subtypes, known as ‘‘intrinsic’’ subtypes, andrepresented a significant improvement over the traditionalmethods of tumor classification [3, 4]. In addition, severalprognostic gene signatures to predict clinical outcome and

customize therapy have originated from these studies (forreviews, see [5–9].

In this chapter we will discuss some of these geneexpression signatures and their emerging roles in providingnew insights into breast cancer classification and inassessing the patient’s prognosis and defining therapy.

5.2 Molecular Classification: The GeneExpression ‘‘Intrinsic’’ Subtypes

Genome-wide studies, using microarray-based methods,have allowed the analysis of the DNA copy number changesor gene expression of thousands of genes in a singleexperiment in a given tumor sample [10–12]. These meth-ods revealed the complexity of the notable breast cancerheterogeneity at the molecular level [13–15] as clearlydemonstrated by the large variation in the gene expressionpatterns.

The pioneer study described by Perou et al. [3], based ongene expression analysis, set the basis for the currentmolecular classification of breast tumors known as the‘‘intrinsic’’ subtypes. These authors performed comple-mentary DNA microarray analysis in a set of normal andmalignant human breast tissues from 42 individuals. Withuse of a hierarchical clustering method, the samples wereclustered into four molecular subtypes according to differ-ences in their gene expression profiles (of 1,753 genes):luminal, normal breast-like, HER2, and basal-like. In a verysimplistic description, luminal tumors were characterizedby high expression of hormone receptors and associatedgenes; normal breast-like cancers were defined by poorlycharacterized tumors; HER2 subtypes exhibited highexpression of HER2 and other genes located in the 17qamplicon and low expression of ER and associated genes;and basal tumors exhibited high expression of basalepithelial genes, basal cytokeratins, and epidermalgrowth factor receptor (EFGR), and low expression ofER and associated genes. The morphological and

L. R. Cavalli (&)Lombardi Comprehensive Cancer Center,Georgetown University Medical Center, Washington, USAe-mail: lrc@georgetown.edu

I. J. CavalliGenetic Department, Federal University of Parana,Curitiba, Brazile-mail: cavalli@ufpr.br

C. Urban and M. Rietjens (eds.), Oncoplastic and Reconstructive Breast Surgery,DOI: 10.1007/978-88-470-2652-0_5, � Springer-Verlag Italia 2013

55

immunohistochemical features of basal-like cancers weresimilar to those described for tumors arising in BRCA1germ-line mutation carriers [16–19].

In subsequent larger studies from the same group, it wasdemonstrated that the luminal subtype could be furtherdivided into at least two subgroups (luminal A and luminalB) [4, 20, 21], each with different gene expression profilesand different prognosis (Fig. 5.1). Luminal A tumorsexhibited high levels of expression of ER-activated genesand low proliferation rates and were associated with a goodprognosis, whereas luminal B tumors were more often ofhigher histological grade and exhibited higher proliferationrates and a worse prognosis. This initial molecular taxon-omy has been validated in several other studies, which alsoidentified a few less defined subtypes, including the inter-feron-rich, molecular apocrine, and claudin-low tumors[20–28]. The complete molecular characterization of theseless defined subtypes has not been performed and theclinical implications have not been fully identified and/orare not known.

The five major molecular subtypes identified in thesestudies differ not only in regard to their pattern of geneexpression and clinical features but also in regard to theresponse to treatment and clinical outcome [5, 6, 20, 29,30]. Patients with luminal tumors respond well to endocrinetherapy; however, luminal A and luminal B tumors responddifferently to the type of endocrine agent used (tamoxifen oraromatase inhibitors) and also exhibit a variable response tochemotherapy [31–34]. Patients with luminal A tumorspresent with an overall good prognosis with a 5 year sur-vival rate of approximately 90 %. Patients with HER2-amplified tumors respond to trastuzumab antibody mono-clonal therapy and to anthracycline-based chemotherapy;however, they generally have a poor prognosis and their5 year survival rate can be as low as 20 % [35, 36]. Finally,patients with the basal-like tumor subtype have no responseto endocrine therapy or trastuzumab therapy; however, they

can be sensitive to platinum-based chemotherapy andpoly(ADP-ribose) polymerase 1 inhibitors [37–39]. Thesetumors are especially common in African-American womenand generally also have poor prognosis [40–42]. Interest-ingly, in the neoadjuvant setting, the intrinsic subtypes havealso been found to exhibit different responses to treatment.The pathological complete response rates to standard che-motherapy based on anthracycline and taxane was approx-imately 7 % for the luminal A subtype, 17 % for theluminal B subtype, 36 % for the HER2-positive subtype,and 43 % for the basal-like subtype [32].

To study the utility of these subtypes in breast tumorclassification, a total of 189 breast tumors across 1,906‘‘intrinsic’’ genes were analyzed by Parker et al. [32]. Theyidentified a set of 50 genes that were further validated andcompared for reproducibility of classification across dif-ferent prediction methods and different patient cohorts. Thisanalysis profiled by quantitative real-time PCR a total of122 breast cancers from the 189 individuals into the‘‘intrinsic’’ subtypes luminal A, luminal B, HER2-positive,basal-like, and normal-like. Owing to its high reproduc-ibility, a standardized method of classification was devel-oped, the Prediction Analysis of Microarray 50 (PAM50)Breast Cancer Intrinsic Classifier test, which is currentlycommercially available (ARUP Laboratories, Salt LakeCity, UT, USA). The PAM50 assay offers the measurementof the expression level of 55 genes (50 classifier genes andfive housekeepers) and is recommended for all patientsdiagnosed with invasive breast cancer, regardless of tumorstage or ER status.

The gene expression intrinsic subtypes were discussed forconsideration at the last St. Gallen International BreastCancer Conference [42]. A simplified clinicopathologicalclassification that defines subtypes on the basis of theimmunohistochemical analysis of ER, PR, and HER2 statusand Ki-67 labeling index (Ki-67 is a cell proliferation mar-ker), similar to what was proposed by Cheang et al. [31], was

Fig. 5.1 Breast cancer classification into five molecular subtypes.Hierarchical clustering of 115 tumor tissues and seven nonmalignanttissues using the ‘‘intrinsic’’ gene set. Experimental dendrogram

showing the clustering of the tumors into five subgroups. Branchescorresponding to tumors with low correlation to any subtype are shownin gray. (From Sorlie et al. [20])

56 L. R. Cavalli and I. J. Cavalli

endorsed (Table 5.1). The breast cancer subtypes defined bythis classification are similar but not identical to the fiveintrinsic subtypes and represent a convenient approximationthat can be used in considerably less expensive and lesscomplex assays. In general, the therapy recommendationsfor this classification follow the ‘‘intrinsic’’ subtype classi-fication: luminal A tumor patients generally require onlyendocrine therapy, considering that they are mostly lessresponsive to chemotherapy; luminal B patients, in additionto endocrine therapy, should receive chemotherapy (bothanthracycline-based and taxane-based); patients with HER2-positive tumors should receive chemotherapy and 1 year oftreatment with trastuzumab; and patients with triple-nega-tive tumors should be treated with chemotherapy (alsoanthracycline-based and taxane-based in addition to analkylating agent, typically cyclophosphamide).

The St. Gallen panel [42] did not endorse the measure-ment of cytokeratin 5/6 or epidermal growth factor receptorfor the determination of basal-like tumors for clinicaldecision making. In the future, this formal subtyping is verylikely to be refined and expanded to include the measure-ment of novel tumor markers; presently, however, the St.Gallen consensus recommends the classification of breastcancer subtypes and the guide to therapeutic decisions to bebased only on the four clinicopathological markers descri-bed above.

Although gene expression profiling has greatly contrib-uted to the determination of breast cancer subtypes and theirassociated differential prognosis, presently this defined‘‘intrinsic’’ molecular classification is not routinely used inclinical practice to classify the patient’s breast tumor sub-type, and no new target therapies have yet resulted for thesesubtypes [43–45]. Several technical challenges limit its use

in clinical practice, including not only the prohibitive costsof the equipment and reagents for the expression assays andthe lack of suitable technical personnel to conduct thecomplex informatics data analysis, but mainly the lack ofreproducibilty and uniformity among laboratories in rela-tion to the selection of the ‘‘intrinsic’’ genes to be used. Thislatter limitation can be easily perceived by the existence ofmultiple versions of molecular classification systemsdeveloped or under development. In addition, most geneexpression microarray analyses were performed by inde-pendent investigators using different methods and applied todifferent patient populations. Another important variabilitywas the cellular composition of the tissue samples (stroma,tumor, and normal cells) in these studies [46, 47]. Cleatoret al. [46], in evaluating the cellular composition of theclassified samples, demonstrated that the percentage ofinvasive cancer cells within a sample influenced theexpression profile; at least 10 % of the genes (144 genes)were found to correlate with cellular composition.

Other challenges include biological inherent facts, suchas that the subtypes assigned by microarrays do not alwayscorrespond to the same subtype defined by the routineimmunohistochemical (IHC) staining that is used in stan-dard clinical assays [32, 48, 49]. In the retrospective anal-ysis by de Ronde et al. [48], 195 stage II and stage III breasttumors from patients that received neoadjuvant treatmentwere classified by both IHC and messenger RNA expressionanalysis on then basis of the molecular classification. TheIHC and molecular subtypes showed high concordance withthe exception of the HER2 group, where 60 % of the HER2-positive tumors were not classified as the HER2 molecularsubtype. In addition, for the ER-positive tumors, neither thePR status nor the endocrine responsiveness index (all the

Table 5.1 Intrinsic and immunohistochemical (IHC) subtypes and type of treatment recommended (St.Gallen’s conference, 2011)

Intrinsic subtype IHC subtype Definition Type of treatment

Luminal A Luminal A HER2 positiveKi-67 low

Endocrine therapy alone

Luminal B Luminal B (HER2 negative) HER2 negativeER positivePR positiveKi-67 high

Endocrine therapy with or without cytotoxic therapy

Luminal B (HER2 positive) HER2 positiveER positivePR positive

Cytotoxic therapy plus anti-HER2 therapy plus hormonal therapy

HER2 overexpression HER2 positive HER2 positiveER negativePR negative

Cytotoxic therapy plus anti-HER2 therapy

Basal-like Triple negative HER2 negativeER negativePR negative

Cytotoxic therapy

Modified from Goldrisch et al. [42] and Perou et al. [3]ER estrogen receptor, PR progesterone receptor, HER2 human epidermal growth factor receptor 2, ki-67 antigen ki-67- protein marker for cellproliferation

5 Molecular Classification and Prognostic Signatures of Breast Tumors 57

tumors showed similar degrees of response to chemother-apy) accurately distinguished the tumors into the luminal Aand luminal B subtypes. In fact, several studies have sug-gested that these ER-positive subtypes may not be com-pletely separate entities [50–52].

Once these and others critical challenges are overcomeand a universally accepted signature for identifying breastcancer subtypes is established, assays that can maintain asimilar level of analytical reproducibility and clinical utilitycan be developed and implemented for the molecularclassification of a patient’s breast tumor. However suchassays should not be expected, at least not soon, to replacethe traditional breast cancer classification systems.

5.3 Prognostic Gene Expression Signatures

In the daily management of breast cancer, the selection ofthe most appropriate adjuvant treatment for an individualpatient remains a challenge, despite the excellent assistanceof the established therapy guidelines such as those of the St.Gallen consensus [1, 42], the National Institutes of Health[53], and Adjuvant! Online (http://www.adjuvantonline.

com). The ability to identify breast cancer patients witheither a very high or a very low risk of recurrence, whowould need adjuvant systemic therapy, from those whocould be spared such type of treatment is critical. The powerof making this distinction at the time of diagnosis, from theanalysis of the patient’s primary tumor, would substantiallyimprove breast cancer survival.

Several multigene signatures that predict outcome andresponse to therapy in breast cancer have been developedthrough the data obtained from gene expression profiling(for reviews, see [5–9] (Table 5.2). In these studies, majorprognostic factors, such as lymph node status and ER status,were addressed and have allowed subgroups of tumors witha very distinct clinical outcome that could not be predictedby conventional prognostic factors to be distinguished in theanalysis of the patient’s primary tumors. The main objectivein most of these studies was to predict which patients wouldbenefit from a more aggressive treatment and which patientswould be unlikely to respond and therefore for whom therewould not be a significant survival benefit.

Vant’veer et al. [54], some of the pioneers of thesestudies, proposed a prognostic gene signature to identify agroup of good prognosis patients with minimal risk of

Table 5.2 Commonest prognostic gene expression breast cancer signatures commercially available

Geneexpressionsignatures

Patientpopulation

Prediction Number of genes Material Assay Company

OncotypeDx

ER positive/negativeLN negativeTamoxifentreated

Risk ofrecurrence

21 genes FFPE RT-PCR Genomic Health (Redwood City,CA, USA)

MammaPrint ER positive/negativeLN negativeTumorsize \ 5 cmAge \ 61 years

Risk ofdistantmetastasis

70 genes Frozen Microarray Agendia (Huntington Beach, CA,USA, and Amsterdam, TheNetherlands)

PAM50 LN negativeER positive/negativeNo systemictherapy

Risk ofrelapse

55 genes Frozen/FFPE

qRT-PCR/microarraya/nCounterb

ARUP Laboratories (Salt LakeCity, UT, USA): (qRT-PCRformat)Nanostring Technologies (Seattle,WA, USA): nCounter format

MapQuantDX

ER positive/negativeLN positive/negative

Moleculargrading

97 genes Frozen/FFPE

Microarray Ipsogen (New Haven, CT, USA,and Marseilles, France)

BreastCancerIndex

ER positiveLN negative

Risk of laterecurrenceResponse toendocrinetherapy

2 genes,HOXB13:IL17Rmolecular gradeindex

FFPE RT-PCR BioTheranostics (San Diego, CA,USA)

ER estrogen receptor, LN lymph node, FFPE formalin-fixed paraffin-embedded, RT-PCR real-time PCR, qRT-PCR quantitative real-time PCRa PAM50, marketed by Arup Laboratories as a breast cancer classifierb In development

58 L. R. Cavalli and I. J. Cavalli

development of distant metastasis within 5 years afterdiagnosis. The expression of 25,000 genes was analyzed inprimary breast tumors, and a set of 70 genes with differ-ential expression profiles separated the patients into twocategories, ‘‘poor’’ and ‘‘good’’ signature groups, on thebasis of their risk of developing distant metastasis. Amongthe genes that were upregulated in the poor signature groupwere genes involved in the cell cycle, angiogenesis, inva-sion and metastasis, and signal transduction, such asCCNE2, MCM6, MMP9, MP1, RAB6B, PK428, ESM1, andthe vascular endothelial growth factor receptor FLT1.Subsequent studies confirmed the reproducibility of theinitial 70-gene signature as a predictor of outcome inde-pendently of traditional clinical–histopathological prog-nostic markers [55–57]. This validation analysis led to thedevelopment of the commercial test MammaPrint devel-oped by Agendia (Amsterdam, The Netherlands). This testis approved by the Food and Drug Administration for use inpatients less than 61 years old, who are lymph-node-nega-tive, and who present with a tumor smaller than 5 cm insize. This signature is currently being evaluated in a largeclinical trial, MINDACT (Microarray In Node-Negativeand 1–3 Positive Lymph-Node Disease May Avoid Che-motherapy Trial), which is performed in breast cancerpatients with ER-positive, lymph-node-negative diseasewith long-term follow-up and known clinical outcome. Theprimary end point is to test its robustness and clinicalapplicability in identifying patients who could be spared theuse of chemotherapy without affecting the survival out-come. On the basis of an independent validation study [58],this trial now also includes patients with one to threepositive axillary lymph nodes.

The other prognostic signature also commerciallyavailable is the Oncotype DX breast cancer assay (GenomicHealth, Redwood City, CA, USA). This assay was devel-oped on the basis of the identification of 250 selected geneswith different expression profiles [59–61], initially tested inpatients from the National Surgical Adjuvant Breast andBowel Project (NSABP) B-20 clinical trial [62]. After sta-tistical analysis and clinical validation, 21 genes (16 cancer-related genes and five reference genes) were selected andtheir expression analysis was translated into a ‘‘recurrencescore’’ (RS), which was then used to assign the patients toone of three groups, on the basis of the risk of developingdistant metastasis: low risk (RS \ 18), intermediate risk(RS C 18 and RS \ 31), and high risk (RS C 31) [63]. Thisvalidation study was performed in lymph-node-negative,ER-positive breast cancer patients who were treated withtamoxifen in the large, multicenter NSABP B-14 trial [64].Subsequent studies have demonstrated its clinical utility asan independent prognostic parameter in ER-positive andlymph-node-positive patients who received adjuvant che-motherapy [65] and also in postmenopausal patients with

ER-positive tumors who were treated with aromataseinhibitors [66]. An ongoing large prospective clinical trial,TAILORX [Trial Assigning Individualized Options forTreatment (Rx)], is further testing the clinical utility ofOncotype DX with the primary end point of accessingwhether adjuvant chemotherapy plus hormonal therapyproduces a better outcome when compared with hormonaltherapy alone in patients who have a low or intermediatescore (RS between 11 and 25).

In contrast to MammaPrint, which is performed by amicroarray assay in frozen tumor tissue samples, OncotypeDX can be performed by real-time PCR in formalin-fixedparaffin-embedded samples, not requiring therefore thehighest-quality RNA material. The Oncotype DX prognos-tic test has been endorsed by the American Society ofClinical Oncology [67] for clinical use and was included inthe last National Comprehensive Cancer Network guide-lines (Breast Cancer version 1.201) and the St. GallenInternational Expert Consensus [42]. The recommendationfor its use is limited to newly diagnosed patients withlymph-node-negative, ER-positive breast cancer who weretreated with tamoxifen. The clinical utility and appropriateapplication recommendations for other multigene assays,such as MammaPrint, are under investigation.

The PAM50 multigene gene-expression-based assay,described above as an ‘‘intrinsic’’ subtype classificationassay, is also used to predict prognosis. This assay canpredict relapse-free survival, based on a risk of relapse(ROR) score, for patients with lymph-node-negative tumorswho were not treated with adjuvant systemic therapy [32].The prediction value of the ROR was evaluated in anindependent set of 786 patients with ER-positive tumorswho were treated only with tamoxifen [33]. For both lymph-node-negative and lymph-node-positive patients, the RORtogether with tumor size outperformed standard clinico-pathological variables, such as Ki-67, PR, and histologicalgrade. For the lymph-node-negative patients the PAM50ROR identified a group with more than 95 % 10 year sur-vival who had not been submitted to chemotherapy.

Several other prognostic signatures were developed,including ones that take into consideration the patient’stumor grade, such as MapQuant Dx (Ipsogen, Marseille,France), a microarray-based assay originally based on 97differentially expressed genes, which was validated asstrongly associated with risk of recurrence among patientswith grade 2 tumors [68, 69], and the Theros Breast CancerIndex (BCI BioTheranostics, San Diego, CA, USA), whichis based on a quantitative real-time PCR assay and providesan assessment of the likelihood of distant recurrence inpatients diagnosed with ER-positive and lymph-node-nega-tive breast cancer. It uses a combination of indices (HOX-B13:IL17BR two-gene ratio) and a proliferation-relatedfive-gene molecular grade index, which discriminates grade

5 Molecular Classification and Prognostic Signatures of Breast Tumors 59

1 from grade 3 breast tumors [70, 71]. Several other prog-nostic signatures that predict clinical outcome were devel-oped on the basis of cancer cell characteristics andprocesses, including wound healing, hypoxia, stem cells, andstroma–fibroblast interactions [72–77].

Although the importance of the gene expression signa-ture of breast tumors has been well established and may be amore accurate prognostic marker than other well-estab-lished clinical–histopathological criteria, one cannot assumethat all the genes present in these gene expression signaturepanels are equally important or have an independent role inbreast cancer pathogenesis and recurrence. Successfulenrichment, reliable identification, and molecular profilingof pure epithelial tumor cells are still key issues to beaddressed [78, 79].

Interestingly, although there is very little overlap amongthese signatures in relation to the gene composition, most ofthem are related to proliferation and ER-signaling cellularprocesses [52, 80, 81]. It is no coincidence that the pre-diction power of most of these signatures is more robust andindicated for ER-positive tumors/luminal subtype and lessfor the ER-negative subtypes [81], hence the specific clin-ical indication of most of these prognostic gene-expression-based assays for patients with ER-positive, lymph-node-negative disease for whom it is safer to recommend atreatment based only on hormonal therapy. Recent studieshave provided evidence that other genes related to cellularprocesses, including the expression of immune-responsegenes, have the potential to predict survival, especiallywithin the HER2-positive and basal-like subtypes of tumors[82–86].

5.4 Conclusions

The rapid advances in the DNA microarray technology andthe ability of performing large-scale validations haveallowed the development of gene expression signatures thatcan be used to identify breast cancer molecular subtypes andpredict response to therapy and clinical outcome. It is withoutquestion that the continued improvement of molecular tumorprofiling in gene-expression-based assays and the develop-ment of next-generation technologies, such as large-scalesequencing, will lead to successful application of these andnewly developed gene signatures in the clinical setting.These efforts will certainly be reflected in the stratification ofbreast cancer disease into a newly refined taxonomy, allow-ing for the understanding of the genetic diversity in the dif-ferent breast cancer subtypes. In addition, considering thatthe success of a treatment largely depends on the ability tomatch a particular tumor phenotype to a specific tumorgenomic target, these new technologies will provide the

identification of new therapeutically targetable markers,leading to the development of novel diagnostic tests to guidethe most appropriate and individualized cancer therapy.Finally, considering the current dissemination of the ge-nomically based testing and treatment strategies for cancer, itis imperative to address the use of these tests on the impact ofthe therapeutic decision making and the patient’s healthoutcome, taking into consideration the social and economicvariants of specific breast cancer patient populations.

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