chromosomal instability in cell-free dna as a ......personalized medicine and imaging chromosomal...

Personalized Medicine and Imaging

Chromosomal Instability in Cell-Free DNA as aHighlySpecificBiomarker forDetectionofOvarianCancer in Women with Adnexal MassesAdriaan Vanderstichele1,2, Pieter Busschaert1,2, Dominiek Smeets3,4,Chiara Landolfo1, Els Van Nieuwenhuysen1,2, Karin Leunen1,2, Patrick Neven1,2,Fr�ed�eric Amant1,2,5, Sven Mahner6,7, Elena Ioana Braicu8, Robert Zeilinger9,An Coosemans1,2, Dirk Timmerman1, Diether Lambrechts3,4, and Ignace Vergote1,2

Abstract

Purpose: Chromosomal instability is a hallmark of ovariancancer. Here, we explore copy-number alteration (CNA) profilingin cell-free DNA as a potential biomarker to detect malignancy inpatients presenting with an adnexal mass.

Experimental Design: We prospectively enrolled 68 patientswith an adnexal mass, of which 57 were diagnosed with invasiveor borderline carcinoma and 11 with benign disease. Cell-freeDNA was extracted from plasma and analyzed by low-coveragewhole-genome sequencing.

Results: Patterns of chromosomal instability were detectable incell-free DNA using 44 healthy individuals as a reference. Profileswere representative of those observed in matching tumor tissueand contained CNAs enriched in two large datasets of high-gradeserous ovarian cancer (HGSOC). Quantitative measures of chro-mosomal instability, referred to as genome-wide z-scores, were

significantly higher in patients with ovarian carcinoma than inhealthy individuals or patientswithbenigndisease. Cell-freeDNAtesting improved malignancy detection (AUC 0.89) over serumCA-125 (AUC 0.78) or the risk of malignancy index (RMI, AUC0.81). AUC values of cell-free DNA testing even further increasedfor HGSOC patients specifically (AUC 0.94). At a specificity of99.6%, a theoretical threshold required for ovarian cancer screen-ing, sensitivity of cell-free DNA testing was 2- to 5-fold highercompared with CA-125 and RMI testing.

Conclusions: This is the first study evaluating the poten-tial of cell-free DNA for the diagnosis of primary ovariancancer using chromosomal instability as a read-out. Wepresent a promising method to increase specificity of pre-surgical predictionofmalignancy in patientswith adnexalmasses.Clin Cancer Res; 23(9); 2223–31. �2016 AACR.

IntroductionOvarian cancer is thefifthmost common cause of female cancer

mortality and remains the leading cause of gynecological cancermortality in developed countries (1). Peritoneal spread oftenprecedes the onset of symptoms, which explains the high per-

centage of patients presenting with advanced-stage disease atprimary diagnosis. Despite the introduction of improved surgicaltechniques, chemotherapy regimens, and targeted therapies, over-all survival rates for these patients have not improved significantlysince the introduction of platinum-based chemotherapy (5-yearoverall survival rate of ca. 30%; ref. 2). Multiple efforts have beenmade to evaluate early screening methods based on serum CA-125 concentrations and/or transvaginal ultrasound (3, 4). Untilnow, these methods did not meet the standards required toadvocate population-based screening. Indeed, the recent UKC-TOCS trial failed to demonstrate a mortality reduction withultrasound and/or CA-125-based screening for ovarian cancer(4), illustrating the urgent need for additional cancer-specificdiagnostic biomarkers (5).

Due to rapid developments in the field of noninvasiveprenatal testing (NIPT), the analysis of tumor-specific copy-number alterations (CNA) in cell-free DNA has gained momen-tum as a potential cancer screening tool. Indeed, we and othersreported that occult maternal cancers can be discovered byNIPT testing (6, 7), leading to the diagnosis of a presymptom-atic advanced-stage ovarian cancer in a 41-year-old patient at15 weeks of gestation. As chromosomal instability is an impor-tant hallmark of cancer (8), it is indeed expected that NIPTtesting, which is designed to detect specific fetal chromosomalanomalies (aneuploidy), is also able to reveal tumor-specificpatterns of chromosomal instability in the plasma from cancerpatients (9).

1Department of Gynaecology and Obstetrics, University Hospitals Leuven,Leuven, Belgium. 2Division of Gynaecological Oncology, Leuven Cancer Insti-tute, KU Leuven, Leuven, Belgium. 3Vesalius Research Center, VIB, Leuven,Belgium. 4Laboratory for Translational Genetics, Department of Oncology, KULeuven, Leuven, Belgium. 5Center for Gynecologic Oncology Amsterdam(CGOA), Netherlands Cancer Institute (NKI), Amsterdam, the Netherlands.6Department of Gynecology and Gynecologic Oncology, Hamburg-EppendorfUniversity Medical Center, University Cancer Center Hamburg-Eppendorf(UCCH), Hamburg, Germany. 7Department of Gynecology and Obstetrics,University of Munich – LMU, Munich, Germany. 8Department of Gynecology,Campus Virchow-Klinikum, Charit�e University Hospital, European CompetenceCenter for Ovarian Cancer, Berlin, Germany. 9Department of Obstetrics andGynecology, Molecular Oncology Group, Comprehensive Cancer Center, Gyne-cologic Cancer Unit, Medical University of Vienna, Vienna, Austria.

Note: Supplementary data for this article are available at Clinical CancerResearch Online (http://clincancerres.aacrjournals.org/).

Corresponding Author: Diether Lambrechts, University of Leuven, Herestraat49, Box 912, 3000 Leuven, Belgium. Phone: 32 16 37 32 09; Fax: 32 16 37 25 85;E-mail: [email protected]

doi: 10.1158/1078-0432.CCR-16-1078

�2016 American Association for Cancer Research.

ClinicalCancerResearch

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on June 11, 2020. © 2017 American Association for Cancer Research. clincancerres.aacrjournals.org Downloaded from

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Elaborating on these findings, we here intend to studywhether low-coverage whole-genome sequencing can be usedin patients presenting with adnexal masses, as a tool to selectwhich patients should undergo surgery. With 5% to 10% ofwomen undergoing surgery for a suspected ovarian neoplasmin the course of their life, adnexal uterine masses represent afrequent medical problem (10). The accurate detection ofmalignancy in these patients is of paramount importance toselect patients for adequate surgery (in case of suspected malig-nancy), continued surveillance (if the suspicion of malignancyis low), or expectant management (in case of a benign adnexalmass). Many efforts have been made to assist in the decisionprocess and to improve the management of these patients,by implementing mathematical models consisting of clinicaldata, such as ultrasound imaging, and serum biomarkers, suchas CA-125 (cancer antigen 125) and HE-4 (human epididymisprotein 4; refs. 11, 12). Nevertheless, current models still lackspecificity (13), and in order to decrease the number of unnec-essary surgical interventions and to improve patient selectionfor tertiary oncological referral, it is thus imperative to developimproved screening models.

Here, we propose to implement cell-free DNA testing in thepreoperative evaluation of patients presenting with an adnexalmass. We developed and validated a whole-genome sequencingmethod and analysis pipeline to detect ovarian cancer–specificpatterns of chromosomal instability in cell-free DNA and com-pared its specificity for predicting malignancy in patients with anadnexalmass to othermodalities, such as ultrasound imaging andserum CA-125.

Materials and MethodsPatients and clinical data

Wecollectedpretreatment blood samples frompatientswith anadnexal mass suspicious for malignancy, referred to the depart-ment of gynecological oncology and the department of gyneco-logical ultrasound of the University Hospitals Leuven (Leuven,Belgium). All samples were collected between September 2014and October 2015. Blood samples were also obtained from a

cohort of healthy female individuals. The ethical committee of theUniversity Hospitals Leuven approved this study (S/55904), andall includedpatients gavewritten informed consent.Wemeasuredpretreatment serum CA-125 levels and calculated the risk ofmalignancy index (RMI; ref. 14), using data from a preoperativetransvaginal ultrasound.

Cell-free DNA extraction and whole-genome low-coveragesequencing

Plasma was extracted through a two-step centrifugation proce-dure, andDNAwas extractedusing theQIAampcirculatingnucleicacid Kit (Qiagen). DNA sequencing libraries were prepared usingthe KAPA DNA Library Preparation Kit (KAPA Biosystems).Whole-genome sequencing was performed on a HiSeq2500 (Illu-mina) using a V4 flowcell generating 1 � 50 bp reads.

Bio-informatics pipelineRaw sequencing reads were mapped to the human reference

genome Hg19 using BWA v0.7.1 (15). Duplicate and low-qualityreads were removed by Picard Tools v1.11 and Samtools v0.1.18,respectively (16). The QDNAseq package v.1.0.5 was used tocreate bins of 1,000 kb along the genome (17). Distributions ofbin counts for plasma samples were shifted and rescaled based ondistributions for healthy individuals to correct for the total num-ber of reads. Furthermore, bin values were smoothed by takingmoving window averages based on windows of 50 Mb (i.e., 50adjacent bins), which move in steps of 1,000 kb (i.e., 1 bin). Wecalculated z-scores for these windows, i.e., the number of SDs thata given window deviates from the population mean. A detaileddescription of the pipeline can be found in SupplementaryMethods.

Tumor tissue correlationMatching fresh-frozen tumor specimens were collected at

baseline (staging laparoscopy or debulking surgery). DNA wasextracted after macrodissection, and sequencing libraries weregenerated in a similar way as for plasma DNA. Bioinformaticprocessing comprised the use of the QDNAseq package (17)and the ASCAT algorithm (18).

Genome-wide z-scoreFor each sample i, we calculated the sum of squares Si of

window z-values. To quantify chromosomal instability, we cal-culated the genome-wide z-score (19) as the Si normalized basedon the healthy individuals (HI):

zi ¼ Si � SHI

SD SHIð Þ

Statistical analysisROC curves were constructed, and the corresponding AUC

values were calculated using the "ROCR" package in R (20).Sensitivities and specificities were calculated using the "caret"package (21). All data were processed in R version 3.1.3.

ResultsAssessing chromosomal instability in cell-free DNA

Weobtained plasmaDNA samples from 68 patients presentingwith an adnexalmass prior to undergoing surgery or receiving anytreatment, as well as from 44 healthy female individuals. Clinical

Translational Relevance

With a 5% to 10% lifetime risk for women to undergosurgery for a suspected ovarian malignancy, the accuratedetection of malignancy in women presenting with adnexalmasses is important to select them for adequate surgery,increased surveillance, or expectant management. However,current detection methods lack sufficient specificity. Sequenc-ing studies have shown that chromosomal instability is inher-ent to ovarian tumors. Here, we develop a novel method thatuses chromosomal instability detected by whole-genomesequencing on cell-free DNA, which can be noninvasivelyobtained from plasma. We show that our proposed methodoutperforms current detection methods based on serum CA-125 testing and ultrasound imaging to predict ovarian malig-nancy. Our findings can easily translate into clinical practice,because its analytical protocols are very similar to thoseapplied for noninvasive prenatal testing (NIPT) in pregnantwomen, which is broadly adopted in routine clinical practice.

Vanderstichele et al.

Clin Cancer Res; 23(9) May 1, 2017 Clinical Cancer Research2224




characteristics for all 112 included samples are summarizedin Table 1 (detailed characteristics in Supplementary Table S4).Briefly, 54 patients were diagnosed with invasive carcinoma, 3with borderline carcinoma and 11 with a benign mass. Whole-genome short-read sequencing was performed on all cell-freeDNA samples with a median of 7.6 � 106 sequencing reads persample, corresponding to a median read depth of 0.12� (inter-quartile range, IQR, 0.08–0.16�, Supplementary Table S1).

For each healthy individual, we counted the number of readsper 1 Mb bin. To reduce noise across these bins, we used asliding window approach and calculated for each window of50 Mb a z-score using the remaining healthy individuals as areference. Relative to the observed distribution of z-scores inthe healthy individuals, absolute z-scores higher than 3 wereconsidered indicative of regions with a significant chromosom-al gain or loss (19). Overall, 0.3% of all windows in healthyindividuals exhibited z-scores >3, whereas in cell-free DNAsamples from patients with an invasive tumor (n ¼ 54),14% of windows exhibited a z-score >3. The heatmapin Fig. 1 shows the genome-wide distribution of over- andunderrepresented 50 Mb windows (z-score >3) obtained for allsamples: all genomic regions that are overrepresented and thusindicative of somatic amplifications are shown in red, whereas

genomic regions that are underrepresented and thus indicativeof somatic deletions are shown in blue. Visual inspection showsthat a large degree of chromosomal instability is detectablein patients with an invasive carcinoma, especially in the 45samples of the HGSOC subtype. On the other hand, patientswith borderline carcinoma (n ¼ 3) or a benign ovarian mass(n ¼ 11) demonstrate a stable chromosomal pattern compa-rable to the profiles obtained from healthy individuals.

Chromosomal instability in cell-free DNA andmatching tumorbiopsies

To show that CNAs observed in cell-free DNA from cancerpatients were similar to those in the corresponding tumor, wegenerated copy-number estimates by whole-genome sequenc-ing of DNA (17) obtained from eight pretreatment HGSOCtumor biopsies. To visualize the similarity between the log2ratios from tumor tissue and z-scores in cell-free DNA samples,all values within a tumor sample were rank transformed, andranks were plotted using a color scale from blue (bins withlowest ranks) to red (bins with highest ranks), as shown inSupplementary Fig. S1. The median Spearman correlation coef-ficient between cell-free DNA and tumor DNA profiles was 0.51(IQR, 0.37–0.62; P < 0.01 for all samples), thus confirming thespecificity of the plasma profiles. We also included 4 patientsfor which multiple tissue biopsies from different tumor siteswere available (Supplementary Figs. S2 and S3). Although thenumber of biopsies assessed was small, prominent CNAsshared between the tumor biopsies were also detectable in thecell-free DNA.

In order to further demonstrate the specificity of the observedCNAs, we focused on the 45 cell-free DNA samples obtainedfrom patients diagnosed with high-grade serous ovarian cancer(HGSOC). We retrieved segmented copy-number data from160 HGSOC cases, previously characterized by SNP arrayprofiling of fresh-frozen tumoral tissue-derived DNA in thecontext of the OVCAD project (22), as well as from 565 HGSOCcases included in The Cancer Genome Atlas (TCGA) project(23). To visualize the similarity between copy-number profilesgenerated on cell-free DNA samples and those obtained fromtissue-derived DNA, we plotted the average profiles of CNAs forthe three cohorts (Fig. 2; Supplementary Methods). The twoupper plots depict the average copy-number profile for the twosets of HGSOC cases, whereas the lower plot depicts the averagez-scores value per window across 45 HGSOC cell-free DNAsamples. Spearman correlation coefficient between cell-free andtumor tissue samples was 0.67 for both cohorts, whereas thecorrelation between OVCAD and TCGA was 0.92 (P < 0.01 forall 3 comparisons).

Genome-wide z-scores as a quantitative measure ofchromosomal instability

Next, using a sum of squares approach to reflect the overalldeviation in z-scores across all windows, we constructed for eachcell-free sample a global measure of genomic instability (seeSupplementary Methods), hereafter referred to as the genome-wide z-score. The median genome-wide z-score of healthy indi-viduals was �0.1. There was no correlation (R2 ¼ 0.0034, P ¼0.70) between the genome-wide z-score and the age (or meno-pausal status) of the healthy individuals (Supplementary Fig. S6).For patients presenting with a benign adnexal mass, the median

Table 1. Clinical characteristics of the study population. The followingabbreviation was used: IQR, interquartile range

Patients with an adnexal mass (n ¼ 68)Healthyindividuals(n ¼ 44)

Benign mass(n ¼ 11)

Borderlinecarcinoma(n ¼ 3)

Invasivecarcinoma(n ¼ 54)

Age (in years)Median 48 58 44 63IQR 25–56 36–75 40–47 59–73

Adnexal histologyCystadenoma — 2 — —

Cystadenofibroma — 3 — —

Fibroma — 4 — —

Teratoma — 2 — —

Serous borderline — — 3 —

Low-grade serous — — — 5Mucinous — — — 2Endometrioid — — — 1Clear-cell — — — 1High-grade serous — — — 45

FIGO stageIA — — 1 3IB — — 2 —

IC1 — — — 1IC2 — — — 1IC3 — — — 2IIB — — — 1IIIA1 — — — 3IIIA2 — — — 1IIIB — — — 8IIIC — — — 14IVB — — — 20

MenopausalPremenopausal 26 4 3 6Postmenopausal 18 7 — 48

CA-125 (in U/mL)Median — 29 17 310IQR — 21–68 15–2494 78–883

RMIMedian — 105 51 2076IQR — 74–348 45–7,482 592–7,052

Cell-Free DNA Testing in Women with Adnexal Masses

www.aacrjournals.org Clin Cancer Res; 23(9) May 1, 2017 2225




genome-wide z-score was �0.6, whereas for patients with bor-derline or invasive carcinoma, it increased to amedian value of 11(see Supplementary Table S2; Fig. 3). Genome-wide z-scoresfurther increased to 12.9 when only considering patients with aninvasive carcinoma. Indeed, borderline ovarian tumors are nottypically characterized by large-scale chromosomal instability,except when associated with a high-grade invasive tumor com-ponent (24). Furthermore, we observed a positive correlationbetween FIGO stage and the genome-wide z-score for HGSOCtumors (Fig. 3). Indeed, although numbers were limited, cell-freeDNA sequencing yielded genome-wide z-scores that were lowerfor lower-stage HGSOCs (median score of � 6.5 for 15 stage I/II/IIIA-B cases) compared with more advanced HGSOCs (medianscore of � 37 for 30 stage IIIC/IV cases). Median genome-wide z-scores for early-stage HGSOC tumors were still higher than thevalues observed in healthy individuals and patients with benignovarian disease (Fig. 3, Supplementary Table S2). In addition,elevated genome-wide z-scores were also observed for some of thenon-HGSOC cases tested, i.e., a low-grade serous carcinoma(LGSOC) tumor (OV1465, FIGO IIIB, score of 45.92) and a clearcell ovarian tumor (OV1529, FIGO IIIC, score of 1540.37).Indeed, it is known that ovarian clear cell carcinomas and otherrare ovarian cancer subtypes constitute a heterogeneous disease atthe genomic level, with only a subset of tumors displayinggenomic instability. Consequently, we failed to observe elevatedgenome-wide z-scores in 7 of 9 non-HGSOC cases (Supplemen-tary Table S2 and Supplementary Fig. S8).

We sequenced approximately 8 million reads per sample,corresponding to a median coverage of 0.12�. For 6 samples,over 40million sequencing readswere available and the influenceof sequencing coverage on the genome-wide z-scorewas evaluatedby selecting random subsets of sequencing reads, and plotting thegenome-wide z-score as a function of sequencing coverage. Wefailed to observe an increase in the genome-wide z-score from 5 to10 million sequencing reads onward (Supplementary Fig. S7),thereby supporting our approach of applying a low-coveragesequencing approach (� 0.10�).

Overall, these data suggest that genome-wide z-scores can beused to distinguish patients with an invasive carcinoma of high-grade serous histology from healthy individuals and patientswith a benign adnexal mass, and this independently from FIGOstage.

Performance of genome-wide z-score for prediction ofmalignancy

Next, by applying different thresholds of the genome-wide z-score to classify cell-free DNA samples either as cancer patients orhealthy individuals, and assessing the number of true-positivesand false-positives at that specific threshold, we generated ROCcurves. First, we assessed the AUC to discriminate patients withborderline and invasive carcinoma (n ¼ 57) from patients with abenign adnexal mass (n ¼ 11). This is relevant as the first set ofpatients is generally selected for surgery and the latter undergoesexpectant management. We also repeated this analysis for

Figure 1.

Heatmap of the chromosomal instability profiles of all 112 included samples. Genomic regions, estimated to be amplified and deleted based on window z-scorecalculation, are shown in red and blue respectively where red indicates z-scores larger than 3, light red z-scores between 2 and 3, blue indicates z-scores lowerthan -3, and light blue z-scores between -2 and -3. Profiles of the 44 healthy individuals are labeled in green and show a limited number of over- or underrepresentedwindow z-scores, as is the case for the 11 patients with benign ovarian disease and the 3 patients with borderline carcinoma shown underneath andrespectively labeled in blue andorange. On the lower half of the plot, all 54 patientswith invasive ovarian cancer are displayed. FIGO stages are annotated for all casesof borderline and invasive ovarian cancer. Non-HGSOC cases are labeled in red and HGSOC cases in dark red. The abnormal genomic representation of a majority ofinvasive ovarian cancers can be easily perceived from this heatmap, especially in the HGSOC group where a characteristic pattern of genomic gains andlosses is displayed.






HGSOC alone (n¼ 45). The obtained AUC values were 0.89 and0.94, for both scenarios, respectively (Fig. 4A).

We also explored whether assessing specific genomic regions,known to be recurrently amplified or deleted in HGSOC tumors,could improve assay performance for detection of HGSOC cases.We applied both a shrinkage algorithm or selected genomicregions enriched in the TCGA cohort, but could not observe animprovement in the detection of malignancy (SupplementaryFig. S5A and S5B).

Genome-wide z-score compared with CA-125 and RMI asdiagnostic biomarkers

Patients presenting with an adnexal mass underwent preoper-ative transvaginal ultrasound scanning (n ¼ 60, 8 patients withmissing data), as well as serum CA-125 testing (n ¼ 67, 1 patientwithmissing data). Using these ultrasound data and preoperativeCA-125 values, we calculated the RMI values for each patient (seeSupplementaryMethods). BothCA-125 andRMIvalueswere thenused to construct ROC curves, as described for the genome-wide z-score. When considering patients with borderline and invasivecarcinoma relative to patients with a benign adnexal mass, the

preoperative CA-125 value exhibited an AUC of 0.78 (Fig. 4B).The RMI score, based on combined CA-125 and ultrasound data,had a slightly better AUCof 0.81 (Fig. 4C).Whenonly consideringpatients with HGSOC (n ¼ 45) and discriminating those frompatients with a benign adnexal mass (n¼ 11), the AUC increasedto 0.82 for CA-125 (Fig. 4B) and to 0.85 for RMI testing (Fig. 4C).Thus, AUC values obtained using genome-wide z-scores in cell-free DNA were higher than those obtained by ultrasound or CA-125 testing.

Interestingly, integrating the genome-wide z-score with RMIvalues in a logistic regression model also improved the per-formance of RMI testing: AUC 0.87 for the combined modelversus AUC 0.81 for RMI alone (benign vs. borderline andinvasive carcinoma), and AUC 0.92 for the combined modelversus AUC 0.85 for RMI alone (benign vs. HGSOC, seeSupplementary Fig. S9).

Next, we compared the sensitivity and specificity of eachbiomarker (Supplementary Table S3). Using the establishedcut-off of 35 U/mL, serum CA-125 yielded 86% sensitivity and64% specificity to detect malignancy (borderline or invasivecarcinoma), whereas RMI showed 80% sensitivity and 64%

Figure 2.

Correlation of plasma profiles with tissue-derived profiles in HGSOC cases. The two upper plots show the average copy number for each bin, calculated fromsegmented copy-number data of 565 HGSOC cases from the TCGA project (23) and 160 HGSOC cases from the OVCAD project (22). All values were centered by themedian value. The lower plot depicts the average of z-scores per bin across 45 HGSOC plasma samples. The Spearman correlation coefficients of the plasmasamples in comparison with the TCGA and OVCAD cohort were 0.78 and 0.77, respectively (P values < 0.01). The correlation between the TCGA and OVCAD cohortwas 0.92 (P value < 0.01).






specificity using the established cut-off of 200 (14). The optimalcut-off for the genome-wide z-score in our dataset, according toROC analysis, was 0.71. This corresponds to 74% sensitivity and91% specificity to detect malignancy (borderline and invasiveovarian carcinoma).

Furthermore, we calculated sensitivities for the threemodalitiesat a fixed "ideal" specificity of 99.6% (25). At this specificity, thecorresponding sensitivity of the genome-wide z-score to distin-guish benign tumors from malignant tumors was 67%. Whenonly considering HGSOC cases, the sensitivity increased toward78%. For serumCA-125 andRMI, sensitivities at 99.6% specificitywere only 13%and37% formalignant tumors, and11%and42%for HGSOC cases, respectively. Notably, a specificity of 99.6%corresponds to a genome-wide z-score cut-off of 1.48 for detectionof malignancy and HGSOC in our patient cohort. The theoreticalprobability of observing a genome-wide z-score higher than thiscut-off was 7.3% among healthy individuals (see SupplementaryFig. S4).

DiscussionThis study is the first to evaluate chromosomal instability in

cell-free DNA as a potential marker to discriminate patients withan adnexal mass caused by an invasive carcinoma from patientspresenting with an adnexal mass that is benign. Indeed, byapplying whole-genome sequencing at low coverage, we demon-strate that it is feasible to detect copy-number changes in cell-freeDNA. Particularly, the somatic copy-number alterations (SCNA)in cell-free DNA correlate well with those observed in tumorbiopsies. We also develop a genome-wide z-score to quantifychromosomal instability in cell-free DNA and show how this

score at a given threshold can be used to predict presence ofchromosomal instable tumors in cell-freeDNA.When comparinggenome-wide z-scores to serum CA-125measurements and ultra-sound (RMI), chromosomal instability in cell-free DNA clearlyoutperformed CA-125 and RMI. Moreover, our method increasesspecificity to detectmalignancy, whilemaintaining a sensitivity ofapproximately 70%. Although RMI is well established, its short-comings have been well documented (11, 26). Indeed, serumCA-125 levels can be normal in borderline and early stage invasiveovarian cancer, while often increased in benign tumors or con-ditions such as endometriosis, fibroids, pregnancy, and infection,ultimately generating a low specificity. Our data now suggest thatassessing chromosomal instability in cell-free DNA may serve asan important addition to the currently usedmathematicalmodelsand scoring systems for the detection of ovarian cancer in patientswith adnexal masses (11), especially because it may increasespecificity in combination with established methods (27). Pre-liminary data indeed show that the performance of RMI testingimproves when combined with cell-free DNA analysis (Supple-mentary Fig. S9).

It should be noted, however, that themajority of study patientswere recruited through our tertiary center for gynecological oncol-ogy. Our sample set is therefore enriched for patients withmalignancy, whereas in routine clinical practice the majority ofpatients with adnexal masses are characterized by benign disease.It is therefore important to independently confirm our observa-tions in prospective studies. In this context, the InternationalOvarian Tumor Analysis Group, IOTA (28), has initiated a pro-spective study to formally explore the integration of cell-free DNAtesting in their IOTA prediction models (amendment to IOTA-5study, NCT01698632).

Figure 3.

Distribution of genome-wide z-scores according to FIGO stage and histology. Genome-wide z-score distributions are shown for 44 healthy individuals ("Healthy"), 11patients with benign ovarian disease ("Benign"), 3 patients with borderline ovarian carcinoma ("BOT"), and 54 patients with invasive ovarian carcinoma ("Invasive").The group of patients with an invasive cancer was divided according to FIGO stage: 8 patients with FIGO stage I–II disease, 12 patients with FIGO stage IIIA-B disease, 14 patientswith FIGO stage IIIC disease, and 20 patients with FIGO stage IV disease. Filled dots represent HGSOC cases, whereas unfilled dots representnon-HGSOC cases. A positive correlation between FIGO stage and the genome-wide z-score for HGSOC tumors was observed. Elevated genome-wide z-scores,compared with the benign cases, were also observed for some of the non-HGSOC cases. Further descriptive statistics are detailed in Supplementary Table S2,and information on individual samples is shown in Supplementary Table S4.






Figure 4.

ROC analyses for genome-wide z-score calculation, CA-125, and RMI testing. AUC values were calculated, validated cut-offs for RMI and CA-125 were annotated onthe respective plots (35 U/mL for CA-125 and 200 for RMI).A, Performance of genome-wide z-score calculation to discriminate patients with benign ovarian disease(n¼ 11) from patients with borderline and invasive carcinoma (n¼ 57, left plot) and patients with HGSOC specifically (n¼ 45, right plot). AUC values were 0.89 and0.94, respectively. B, Performance of CA-125 testing to discriminate patients with benign ovarian disease (n ¼ 11) from patients with borderline and invasivecarcinoma (n¼ 56, left plot) and patients with HGSOC specifically (n¼ 44, right plot). AUC valueswere 0.78 and 0.82, respectively. C, Performance of RMI testing todiscriminate patients with benign ovarian disease (n ¼ 11) from patients with borderline and invasive carcinoma (n ¼ 49, left plot) and patients with HGSOCspecifically (n ¼ 38, right plot). AUC values were 0.81 and 0.85, respectively.






A particular strength of assessing chromosomal instability atthe whole-genome level is that this unbiased approach cansuccessfully be applied to themajority of ovarian tumors withoutprior knowledge about the tumor's genetic architecture. A previ-ous report (29) already successfully assessed tumor-specificmuta-tions in circulating tumor DNA collected from HGSOC patients,but the approach required prior genetic characterization of thetumor using whole-exome sequencing. Except for TP53 muta-tions, HGSOC tumors do not frequently carry oncogenic drivermutations. In contrast, HGSOC tumors are almost always char-acterized by a high degree of chromosomal instability (23, 30).Furthermore, because performing low-coverage whole-genomesequencing to detect chromosomal instability is less complicatedcompared with first characterizing and then detecting tumor-specific mutations in cell-free DNA, our proposed method mightbe much more straightforward to apply in a routine diagnosticsetting. Likewise, assessing chromosomal instability in cell-freeDNA could also detect tubal carcinoma, which is a type of ovariancancer that is challenging to detect by ultrasound, and usually ischaracterized by TP53 mutations and chromosomal instabilityarising due to BRCA1/2 deficiency (31). On the other hand, alimited number of cases in our study did not have an increasedgenome-wide z-score,whichprobably is due to a tumor fraction inplasma that is below the limit of detection of our low coverageapproach (32). In addition, some tumors lacking chromosomalinstability will not be detected. This is the case for a number ofnon-HGSOC tumors, which are chromosomal stable types ofovarian cancer (i.e., "type 1" tumors, such as low-grade serousor mucinous ovarian cancer). These could be detectable bycomplementing our method of assessing chromosomal instabil-ity in cell-free DNAwith a targeted sequencing panel for recurrentsomatic mutations such as KRAS and PIK3CA, which are charac-teristic for these tumor types (33).

Another intriguing point is that, until now, detection of chro-mosomal instability in cell-free DNA has mainly been evaluatedin metastatic cancer patients, in which plasma typically containsa relatively high fraction of tumor-derived cell-free DNA (19, 34,35). Few other studies have assessed the feasibility of usingchromosomal instability for the early detection of cancer. Xiaand colleagues (36) already examined plasma-derived cell-freeDNA collected from 8 early-stage lung cancer patients versus 8healthy individuals, and demonstrated subtle but detectabledifferences in chromosomal instability. In addition, Sch€utz andcolleagues (37) analyzed a large dataset consisting of 204 patientswith prostate cancer versus 207 healthy individuals, and assessed alimited number of chromosomal regions for instability in cell-freeDNA. They reported a similar AUCof 0.92 todiscriminate patientsfrom healthy individuals. Our data elaborate on these findings,and our AUC value of 0.94 for HGSOC detection shows that ourapproach of assessing chromosomal instability in cell-free DNA isequally effective for patients with primary diagnosed (high-gradeserous) ovarian cancer. Judging from thesefirst positive results, we

believe that, at least from a technical point-of-view, cell-free DNAtesting for chromosomal instability could quickly be implemen-ted into clinical practice. Indeed, our analytical protocols are verysimilar to those applied forNIPT,which already iswidely adoptedin routine clinical practice in most developed countries.

In conclusion, our proposed methodology provides distinctadvantages to discriminate malignancy from a benign lesion inpatients presenting with an adnexal mass. This can form the basisof a larger validation study in which results from cell-free DNAtesting can be integrated into improved ultrasound-driven pre-diction models.

Disclosure of Potential Conflicts of InterestE.I. Braicu is a consultant/advisory board member for Glycotope and

Fujirebio. D. Lambrechts reports receiving commercial research support fromMultiplicom NV. No potential conflicts of interest were disclosed by the otherauthors.

Authors' ContributionsConception and design: A. Vanderstichele, D. Timmerman, D. Lambrechts,I. VergoteDevelopmentofmethodology:A. Vanderstichele, C. Landolfo,D. Timmerman,D. Lambrechts, I. VergoteAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): A. Vanderstichele, D. Smeets, C. Landolfo, K. Leunen,F. Amant, S. Mahner, E.I. Braicu, R. Zeilinger, A. Coosemans, D. Timmerman,D. Lambrechts, I. VergoteAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): A. Vanderstichele, P. Busschaert, D. Smeets, C. Land-olfo, D. Lambrechts, I. VergoteWriting, review, and/or revision of the manuscript: A. Vanderstichele,D. Smeets, C. Landolfo, E. Van Nieuwenhuysen, P. Neven, F. Amant, S. Mahner,E.I. Braicu, R. Zeilinger, A. Coosemans, D. Timmerman, D. Lambrechts,I. VergoteAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): A. Vanderstichele, D. Smeets, F. Amant,S. Mahner, D. TimmermanStudy supervision:A. Vanderstichele, D. Timmerman,D. Lambrechts, I. Vergote

AcknowledgmentsWe thankAnnick VandenBroeck,GilianPeuteman, Thomas VanBrussel, Evy

Vanderheyden, and Ana€�s VanHoylandt for their technical and logistic support.

Grant SupportThis work was supported by the Belgian Cancer Plan Action 29 of the

Ministry of Health of Belgium (grant number KPC-29-054), by theVriendtjes tegen Kanker fund (grant number EVO-FOVTK1-O2010), and byThe Flemish League against Cancer (grant number EVO-ZKD0344). F. Amantand D. Timmerman are Senior Clinical researchers for the Research Fund-Flanders (FWO-V). A. Coosemans is a postdoctoral researcher for theResearch Fund-Flanders (FWO-V).

The costs of publication of this articlewere defrayed inpart by the payment ofpage charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received April 28, 2016; revised September 21, 2016; accepted October 10,2016; published OnlineFirst November 14, 2016.

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2017;23:2223-2231. Published OnlineFirst November 14, 2016.Clin Cancer Res Adriaan Vanderstichele, Pieter Busschaert, Dominiek Smeets, et al. MassesBiomarker for Detection of Ovarian Cancer in Women with Adnexal Chromosomal Instability in Cell-Free DNA as a Highly Specific

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