analysis of mucosal melanoma whole-genome landscapes ... · analysis of mucosal melanoma...

Precision Medicine and Imaging

Analysis of Mucosal Melanoma Whole-GenomeLandscapes Reveals Clinically Relevant GenomicAberrationsRong Zhou1,2,3, Chaoji Shi2,Wenjie Tao1,2,3, Jiang Li4, Jing Wu1,2,3, Yong Han1,2,3,Guizhu Yang3, Ziyue Gu1,2,3, Shengming Xu1,2,3, Yujue Wang1,2,3, Lizhen Wang4,YananWang1, Guoyu Zhou1, Chenping Zhang1,2,3, Zhiyuan Zhang1,2,3, and Shuyang Sun1,2,3

Abstract

Purpose: Unlike advances in the genomics-driven precisiontreatment of cutaneous melanomas, the current poor under-standing of the molecular basis of mucosal melanomas (MM)has hindered such progress forMMpatients. Thus, we sought tocharacterize the genomic landscape of MM to identify genomicalterations with prognostic and/or therapeutic implications.

Experimental Design: Whole-genome sequencing (WGS)was performed on 65MM samples, including 63 paired tumorblood samples and 2 matched lymph node metastases, with afurther droplet digital PCR–based validation study of anindependent MM cohort (n¼ 80). Guided by these molecularinsights, the FDA-approved CDK4/6 inhibitor palbociclib wastested in an MM patient-derived xenograft (PDX) trial.

Results: Besides the identification of well-recognized drivermutations of BRAF (3.1%), RAS family (6.2%), NF1 (7.8%),and KIT (23.1%) in MMs, our study also found that (i)

mutations and amplifications in the transmembrane nucleo-porin gene POM121 (30.8%) defined a patient subgroup withhigher tumor proliferation rates; (ii) enrichment of structuralvariations between chromosomes 5 and 12 defined a patientsubgroup with significantly worse clinical outcomes; (iii) over50% of the MM patients harbored recurrent focal amplifica-tion of several oncogenes (CDK4, MDM2, and AGAP2) at12q13-15, and this co-occurred significantly with amplifica-tion of TERT at 5p15, which was verified in the validationcohort; (iv) the PDX trial demonstrated robust antitumoreffects of palbociclib in MMs harboring CDK4 amplification.

Conclusions: Our largest-to-date cohort WGS analysis ofMMs defines the genomic landscape of this deadly cancer atunprecedented resolution and identifies genomic aberrationsthat could facilitate the delivery of precision cancer treatments.

See related commentary by Shoushtari, p. 3473

IntroductionMelanomas are tumors that originate from melanocytes with

varying anatomic distribution, clinical features, and biologicalbehaviors (1, 2). Mucosal melanomas (MM) are one of the

deadliest subtypes of melanoma; as most MMs metastasizeand/or recur after resection (3, 4). MM has significantly worseprognosis compared with other melanoma subtypes, with 5-yearsurvival rates ranging from only 20% to 25% (5–7). It is alsonotable that MMs occur more frequently among Asian popula-tions than among Caucasian populations (8, 9).

In contrast to cutaneous melanoma (CM), for which ultravioletradiation that causes a predominant C > T nucleotide transitionsignature has been established as the major risk factor, the molec-ular pathogenesis of MM remains elusive (10). CM is the bestgenomically characterized type ofmelanoma, and the treatment ofCM has benefited enormously from significant clinical break-throughs in the last decade that have revolutionized its molecularclassificationand targeted therapy(11).Recent TheCancerGenomeAtlas (TCGA) research has advanced our understanding of CM bydefining four molecular subtypes of CMs based on the presence ofspecific driver mutations—BRAF-mutant CM, RAS-mutant CM,NF1-mutant CM, and triple wild-type CM—and there are nowFDA-approved molecular-subtype–specific inhibitor drugs, forexample, the BRAF V600E/V600K mutation as an indicator forresponsiveness to vemurafenib treatment (12–14). ComparedwithCMs with multiple definite driver oncogenes, the genomic under-lying of MMs has not been fully characterized.

Several studies have utilized array-based comparative genomichybridization or whole-exome sequencing (WES) and targetedsequencing to investigate the mutational spectra of MM (15–18).Furney and colleagues (2013) conducted the first whole-genomesequencing (WGS) analysis of 5MM samples (16).More recently,

1Department of Oral and Maxillofacial-Head Neck Oncology, Shanghai NinthPeople's Hospital, College of Stomatology, Shanghai Jiao Tong University Schoolof Medicine, Shanghai, P.R. China. 2National Clinical Research Center for OralDiseases, Shanghai, P.R. China. 3Shanghai Key Laboratory of Stomatology andShanghai Research Institute of Stomatology, Shanghai, P.R. China. 4Department ofOral Pathology, Shanghai Ninth People's Hospital, College of Stomatology,Shanghai Jiao Tong University School of Medicine, Shanghai, P.R. China.

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

R. Zhou, C. Shi, W. Tao, and J. Li contributed equally to this article.

Z. Zhang and S. Sun jointly supervised this work.

Corresponding Authors: Shuyang Sun, Ninth People's Hospital, College ofStomatology, Shanghai Jiao Tong University School of Medicine, Number639, Zhi-Zao-Ju Road, Shanghai 200011, China. Phone: 86-13-651629869;Fax: 86-21-63136856; E-mail: [email protected]; and Zhiyuan Zhang,Department of Oral and Maxillofacial-Head Neck Oncology, Shanghai NinthPeople's Hospital, College of Stomatology, Shanghai Jiao Tong UniversitySchool of Medicine, Number 639, Zhi-Zao-Ju Road, Shanghai, China. Phone:86-21- 3845-2223; Fax: 86-21-63135412; E-mail: [email protected]

Clin Cancer Res 2019;25:3548–60

doi: 10.1158/1078-0432.CCR-18-3442

�2019 American Association for Cancer Research.

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the largest-to-date WGS study (n ¼ 183, published in 2017) ofvarious melanoma subtypes included 8 MMs (19). In general,these studies found that MMs lack common molecular driversknown for CMand also lack UV-light relatedmutation signatures.MMs have lower overall mutational burdens than CMs. It isnotable that detailed profiling of the genomic landscape, espe-cially the characterization of large-scale genomic rearrangementssuch as structural variations (SV; deletions, duplications, inver-sions, translocations, etc.), has been limited in these small-cohortstudies. Except for the well-recognized BRAF-activating mutationin all melanoma subtypes, the only gene that has been associatedwith the targeted treatment of MM patients is KIT (20–22).Imatinib is currently the only targeted drug for KIT-mutant mel-anomas recommended in Clinical Practice Guidelines of theNational Comprehensive Cancer Network. Although imatinibsometimes conferred early disease control, the cancers of mostpatients ultimately progressed (23). Thus, patients diagnosedwith this particularly deadly form ofmelanoma have not yet fullybenefited from genomics-era advances in precision oncology.

Here, seeking to further characterize themolecular pathogenesisof this deadly subtypeofmelanoma,wedescribe the largest-to-dateMM cohort (n ¼ 65) that has been used for genomic landscapeprofiling, with validation of the recurrent genomic pattern in anindependent MM cohort (n ¼ 80). Guided by the molecularinsights, a patient-derived xenograft (PDX) trial is conducted toevaluate the therapeutic efficacy of the selected targeted agent in apopulation-based PDX cohort. Together, these data providedinsights into the recurrent genomic aberrations associated withclinical relevance and demonstrates how these insights couldinform triage of patients for effective precision cancer treatments.

Materials and MethodsTumor samples

Eligible patients had a diagnosis of either primary or recurrentMM, and none of the patients was treated by chemotherapy or

radiotherapy before the operation. Tumor samples were collectedfrom gingiva (n ¼ 28), hard palate (n ¼ 13), multisites (n ¼ 11;hard palate/lip and gingiva), and other site (n¼ 13). Fresh-frozentumor samples and blood samples were mainly obtained fromNinth People's Hospital in Shanghai with written informedconsent from each patient and research ethics board approval inaccordance with the Declaration of Helsinki. After being checkedby the two different pathologists (J. Li and L. Wang), the tumortissues or regional lymph nodes were immediately frozen inliquid nitrogen and stored at �80�C. The validation cohortincluded 80 archived formalin-fixed paraffin-embedded (FFPE)MM clinical samples (diagnosed between 2004 and 2013), col-lected from gingiva (n¼ 36), hard palate (n¼ 29), multisites (n¼5; hard palate and gingiva, lip/gingiva and buccal), and other site(n ¼ 10). Detailed clinicopathologic information for patients inthe WGS and validation cohort is provided in SupplementaryTable S1.

WGS processingWGSwas performed on Illumina HiSeq X10 instruments at the

WuXi NextCode (https://www.wuxinextcode.com) facility inShanghai with 150 base pair (bp) pair-end libraries. The averagedepth was 69 � in the tumor samples and 35 � in the normalsamples. Sequence data were aligned to the hg19 (GRCh37)genome with BWA (v0.7.12-r1044); this generated a sorted levelbinary file (BAM). Mark duplication was performed with Sention(ref. 24; version201611.02) on eachBAMfile. The readswere thenrealigned to the hg19 (GRCh37) genome with Sention to betteridentify the InDel mutations.

Single-nucleotide variant calling and Sanger sequencingAll somatic mutations were detected with each of the paired

tumor–normal samples using Sention with the TNhaplotyperalgorithm. All high-confident variants were annotated withANNOVAR (ref. 25; hg19, v1.2) for consequence prediction andvariant effect prediction. Two methods, MutSigCV (ref. 26; v1.4)and OncodriveFML (27; ref. v2.0.2), were used to identify signif-icant mutated genes among all high-confident variants, with athreshold of q < 0.1. Sanger sequencing was conducted as previ-ously reported (19), the PCR products were sequenced on an ABI-3500Dx Genetic Analyzer (Applied Biosystems) and data wereanalyzed with Sequence analysis (v5.4) using hg19 (GRCh37)genome as reference.

Copy-number variant detectionAll somatic copy-number variant (CNV) determining was

carried out with CNV kit (ref. 28; v0.8.3). Whole genome wassplit into bins with window size of 5k bp against eachchromosome and the log2 ratio was estimated for each bin.Several bins would join together to a larger segment with asignificance threshold of 1 � 10�6 and the copy number ofsegment would be estimated. Genes with copy number at leastthree were defined as gain and no more than one were definedas loss.

SV detectionSVs were identified using Manta (ref. 29; v1.1.1) software,

which identified all of the structural variants based on split readsand spanning paired reads, and classified them into five kinds:translocation breakend (BND), deletion (DEL), tandem duplica-tion (DUP), insertion (INS), and inversion (INV). Depending on

Translational Relevance

Mucosal melanoma (MM) is one of the deadliest subtypesof melanoma, and it occurs more frequently among Asiansthan among Caucasians. The lack of understanding about themolecular pathogenesis of MMs has hindered genomics-eraprecision medicine advances that could help patients withthis disease. Here, in the largest-to-date cohort whole-genomesequencing (WGS) analysis of MMs, we confirmed pre-viously characterized genomic aberrations and highlightedthe prognostic and therapeutic significance of recurrent geno-mic aberrations such as POM121 mutation/amplificationand large-scale genomic rearrangements between chromo-somes 5 and 12. Additionally, the patient-derived xenografttrial demonstrated robust antitumor effects of the FDA-approved CDK4/6 inhibitor palbociclib in MMs harboringCDK4 amplification. To our knowledge, this is the first cohortof xenograft models in which interpatient genetic hetero-geneity was represented and has been used for targeted drugevaluation in MM. Thus, our study demonstrates how thegenomic insights of MMs can inform patient stratification andprecision cancer treatments.

Identifying Clinically Relevant Genomic Aberrations in MMs

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the structural variant type and the copy-number status in break-points (30), all variants were further classified into eight groups:deletions, duplications, tandem duplications, fold-back inver-sions, amplified inversions, inversions, intrachromosomal, orinterchromosomal translocations.

Commonly mutated genes and pathwaysA manually curated list of commonly mutated tumor suppres-

sor genes and oncogenes was created and analyzed. The frequencyof SVs, CNVs, and single-nucleotide variants (SNV) were calcu-lated for each gene. All geneswere overlaid onto pathways definedby the Kyoto Encyclopedia of Genes and Genomes (KEGG) andGene Ontology (GO) gene sets from MSigDB v6.0 (http://software.broadinstitute.org/gsea/msigdb).

Detection of breakpoint clusteringChromosomes containing highly significant clustering distribu-

tions of breakpoints were identified as recently described (31) witha stringent threshold of P < 0.00001. Similarly, chromosomes withhigh numbers of translocations were identified with a minimumthreshold of 10 translocation breakpoints per chromosome (32).Chromosomes that contained all these characters were categorizedas clustered interchromosomal translocation. Chromothripsiswas detected using Shatterproof (ref. 33; v0.14) with the defaultsettings. Chromosomes with a maximum final score above 0.517were considered positive (34). Breakage–fusion–bridge (BFB) wasdetected based on the evidence of fold-back inversions andtelomere loss and inversions as previously reported (35).

IHCIHC was performed on FFPE tissue sections of tumor samples

and PDX xenografts. Briefly, 4-mm-thick sections were cut andprocessed for IHC detection using antibodies against Ki67 (dilut-ed 1: 100, #M7240, Dako) and CDK4 (diluted 1: 200, #108357,Abcam). Slides were developed with 3-amino-9-ethylcarbazole(AEC, #K3464, Dako) peroxidase reaction and counterstainedwith Mayer's hematoxylin. CDK4 expression evaluation of thestaining reaction was performed in accordance with the Immu-noReactive Score system. Tumor slices scoring at least 4 points inour study were classified CDK4 positive.

Fluorescence in situ hybridizationCDK4 and TERT amplification tests were performed on FFPE

tissue sections using commercial probes (ZytoLight SPECCDK4/CEN12 Dual Color Probe and TERT/CEN5 Dual ColorProbe, ZytoVision GmbH). The colocalization status of CDK4and TERTwas examined by commercial custom probes (EmpireGenomics). All fluorescence in situ hybridization (FISH) exper-iment procedures were performed according to the manufac-turer's instructions. The signal number of CDK4, CEN12, TERT,and CEN5 was scored by counting a minimum of 100 non-overlapping nuclei per slide. The related ratio and the averagecopy number of CDK4 and TERT were then calculated. Ampli-fication was defined by examining first the CDK4/CEN12 ratiofollowed by the average CDK4 copy number. Nonamplificationwas defined as a CDK4/CEN12 ratio <2.5 with an average CDK4copy number <5.0 signals per nucleus, whereas amplificationwas defined as a CDK4/CEN12 ratio <2.5 with an average CDK4copy number �5.0 signals per nucleus or a ratio �2.5 or anuncountable sample due to clustering of green signals.

Laser capture microdissection and droplet digital PCRThe FFPE tumor tissues were cut into at least six sections

(8 mm thickness) and mounted on PEN Membrane Glass Slides(Applied Biosystems). Sections were stained with hematoxylinand eosin to distinguish normal or nonlesional mucosa frommelanoma. Genomic DNA was isolated from collected speci-mens using a QIAamp DNA FFPE Tissue Kit (#56404, Qiagen).Droplet digital PCR (ddPCR) was performed on a QX200ddPCR system (Bio-Rad). RPP30 was used as the reference geneand its copy number. In brief, 10 ng of genomic DNA isolatedfrom microdissected FFPE samples or xenograft samples wasadded into each well. After PCR amplification, droplets weresequentially counted for CDK4 or TERT or AGAP2 or MDM2(FAM-labeled) or RPP30 (VIC-labeled). Data analysis was per-formed using QuantaSoft software version 1.6.6 (Bio-Rad). Toset up a threshold to distinguish samples with amplified targetgenes, Target/Reference ratio in melanoma and in nonlesionalmucosa tissues adjacent to MMs was calculated.

PDX trialPDX model was established as we previously reported (36),

and xenograft from established PDX model was trimmed into20–30 mm3 fragments for subcutaneous implantation in nudemice (Shanghai SLAC Laboratory Animal Co.). Xenograft-bearingmice with an average tumor volume 150 to 250 mm3 wererandomized into the control arm and the treatment arm on thebasis of tumor size, tumor growth rate, and mouse bodyweightand were treated with vehicle (sodium lactate buffer, 50 mmol/L,pH 4.0, orally, daily) or palbociclib (Pfizer, orally, daily) at a doseof 120 mg/kg, 90 mg/kg, or 60 mg/kg in PDX models in a 28-dayor a 56-day long-term treatment schedule. Tumor size andbodyweight measurements for mice were taken twice weeklyusing, respectively, a digital caliper and electronic scale. Thepercentage of tumor growth inhibition (TGI) was defined as100 � [1 � (TVf_treated�TVi_treated)/(TVf_control� TVi_control)],where TVf is the average tumor volume at the end of study andTVi is the average tumor volume at the initiation of treatment.

For the PDX trial, each PDX model xenograft was transplantedin three mice, and the first mouse to reach 150 to 250 mm3 wasassigned to the treatment group, the second to the vehicle group,and the third mouse was excluded, utilizing the one mouse perpatient per treatment group setup described previously (37, 38).Treatment responsewas assessed bymonitoring changes in tumorvolume of the treatedmouse and comparing to the tumor volumeof the vehicle-treated mouse (treated/control %) using the fol-lowing formulas: T/C (%) ¼ (TVf_treated�TVi_treated)/(TVf_control�TVi_control)]. The drug response criteria were as follows: progres-sion if T/C >50%, suppression if T/C ¼ 50–0%, and regression ifT/C <0%. Animal care and experiments were performed under theapproval and supervision of the Institutional Animal Care andUse Committee (IACUC) of the Shanghai Jiao Tong UniversitySchool of Medicine.

Western blottingFreshly frozen xenograft tissuewas lysedusing 1%SDS solution

(Beyotime), containing 1%phosphatase and proteinase inhibitorcocktail (Bimake). Approximately 200mg of xenograft tissue washomogenized and lysed using 0.5 mL of lysis buffer. The proteinconcentration of individual samples was determined with BCAProtein Assay Kit (Beyotime). An equal quantity of protein wasseparated by 10% SDS-PAGE and transferred onto a transfer

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membrane (Millipore) and was blocked for 1 hour with 5%nonfat dry milk followed by incubation with primary and sec-ondary antibodies. The antibodies against the following proteinswere used: Rb (#ab24, Abcam), GAPDH (#2118, CST), andphospho-Rb (S807/811, #8516, CST). The chemiluminescencesignal was developed with ECL-plus reagent (Beyotime) anddetected by autoradiography.

Data depositionThe raw sequence data have been deposited in the Genome

Sequence Archive in BIG Data Center, Beijing Institute of Geno-mics (BIG), Chinese Academy of Sciences, under accession num-ber HRA000004. The Web link for these publicly available data(with controlled access on reasonable request) is http://bigd.big.ac.cn/gsa-human/s/sdtAbxY4.

ResultsClinical samples and genomic landscape of MMs

Patients eligible for this study had a diagnosis of either primaryor recurrent MM, and none of the patients were treated withchemotherapy or radiotherapy before operation. The fresh-frozenMM specimens and matched blood samples were mainlyobtained from the Ninth People's Hospital in Shanghai between2014 and 2017 (Supplementary Table S1). We performed high-depthWGSon a total of 65 samples (including 63matched tumorand blood samples and two lymph node metastases). Analysis ofSNVs across all tumors revealed a low overall mutation burden,with a median of 4.53 mutations per megabase (range, 0.26–34.56 mutations per megabase; Fig. 1A, all the coding SNVs andInDels are provided in Supplementary Table S1). In contrast, wedetected a total of 60,129 somatic SVs and 225,665 CNVs amongall tumors which were highly variable across each individual(Fig. 1B and C), with an average of 925 SVs and 3,472 CNVs perindividual (range, 20–4,302 and 132–15,221, respectively).

Wenext usedMutSigCVandOncodriveFML (q<0.1) to identifysignificantly mutated genes, and sorted MMs based on the well-characterized driver genes (BRAF V600/K601, RAS family, andNF1 loss-of-functionmutations) for CM (Fig. 1D; SupplementaryTable S2). We found that only 10 of 65MMs featured any of thesemutations, and the only widely recognized oncogene mutationimplicated in MMs, KIT, was observed in 23.1% (15 of the 65)MM samples (Fig. 1D). Additionally, an exploratory KEGG path-way analysis revealed that, relative to SNVs, genes affected by SVsand CNVs appear to contribute more prominently to the overallgenetic aberration frequency of the genes within the dysregulatedpathways in MMs; for instance, 72% and 60% MM samples hadone or more genetic aberrations in genes within the cell-cyclepathway and MAPK pathway, and SVs/CNVs accounted for thevast majority of these genetic aberrations (70% of 72% and 54%of 60%, respectively; Supplementary Table S3; SupplementaryFig. S1). Thus, in contrast toCM(detailed comparisonprovided inSupplementary Table S3), which has one of the highest somaticmutation rates anddrivenby SNVs indriver genes (16, 19, 39), theoverall genomic landscape of MM indicates the biological signif-icance of large-scale genomic rearrangements (SVs and CNVs) inthe majority of the MM cases.

Recurrent POM121 mutations with clinical relevance for MMsOne gene that did appear to be especially relevant was

POM121—encoding a transmembrane nucleoporin—which was

mutated in 15.4%(10of the 65)of theMMsandwas theonly geneother than KIT supported in both our MutSigCV and Oncodri-veFML analyses of our genomic data. We found 6 previouslyunidentified somaticmutations in POM121 in these 10MMs, and4 of these mutations, including two identical insertions, werevalidated by Sanger sequencing in 5MMs (Fig. 2A; SupplementaryFig. S2). Notably, 1 of these 10 MMs also featured POM121amplification; a total of 11 of the 65MMs POM121 amplification(Supplementary Fig. S3). We then evaluated the clinical relevanceof the recurrent genomic alterations in POM121 and found thatpatients with POM121 mutation (rather than amplification)tended to have worse clinical outcomes (median overall survival9.0 vs. 25.0months, log-rank P¼ 0.098; Fig. 2B). Consistent withits pathophysiologic functions observed in prostate cancer, wefound that MMs with POM121 mutation or amplification hadsignificantly higher tumor proliferation rates than MMs withoutPOM121 alteration; measured as Ki67 expression index (fractionof Ki67-positive tumor cells >20%; 17/20 samples, 90.5% vs.22/43 samples; 64.8%, P ¼ 0.012, Fisher exact test; Fig. 2C).Representative antibody staining for Ki67 is shown in Fig. 2D.

SV pattern identified in MMsOur WGS data from the MMs allowed us to comprehensively

catalog large-scale structural rearrangements that are not detect-able using exome sequencing data and array-based comparativegenomic hybridization. We found that interchromosomal trans-locations constitute more than half of all the SVs (54.1%, 32,560of 60,129). Notably, interchromosomal translocations (17%)and intrachromosomal translocations (27%) between or withinchromosome (chr) 5 and chr12 accounted for 44% of all thedetected SVs (Supplementary Fig. S4A and S4B). Clusters of break-points, which indicate complex genomic rearrangements, werefound to be abundant across the chromosomes of most MMsamples, and a recurrent pattern of clustered interchromosomaltranslocations between chr5 and chr12was alsoobserved (Fig. 3A).This pattern of SVs was similar to a phenomenon initially reportedfor ovarian cancer wherein a large number of interchromosomaltranslocations occurred for chromosomes that have a high numberof clustered breakpoints (32). Both chr5 and chr12 are verystrongly enriched for this clustered interchromosomal transloca-tion SV trend (Fig. 3A). Additionally, manual review of the circosplots as well as visual inspection using the Integrative GenomeViewer and Sanger sequencing further validated these observedSVs between chr5 and chr12 in two representative MM samples(MM023 and MM065; Supplementary Fig. S5).

Our finding that MMs feature a highly rearranged genomicprofile suggested that there may be genetic mechanisms that caninduce complex genomic rearrangements that could be drivingthe oncogenic process for this disease. Pursuing this idea, weexamined the distribution in MMs of various known oncogenicgenetic events (e.g., BFB and chromothripsis; SupplementaryFigs. S4C and S6; Supplementary Table S4). We observedthat the distribution of BFBs was significantly correlated withthe distribution of clustered interchromosomal translocations(Kendall t ¼ 0.270, P ¼ 0.032; Fig. 3B).

Prognosis of MM subgroups with recurrent SV patternThe aforementioned WGS study of multiple melanoma sub-

types alsodetectedBFBs in17.8%(32of178)melanoma samples,whereas the possible clinical significance of BFBs was not dis-cussed (19). We here evaluated the prognostic significance the





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observed clustered interchromosomal translocations and foundthat patients with clustered interchromosomal translocationsbetween chr5 and chr12 showed significantly worse clinicaloutcomes (median overall survival 9.0 vs. 28.0 months, log-rankP ¼ 0.047; Fig. 3C). In light of our speculations about theunderlying oncogenic genetic events, it is notable that BFBs,but not chromothripsis, were tightly associated with worseprognosis (median overall survival 9.0 vs. 34.0 months, log-rank

P ¼ 6.9 � 10�4; Fig. 3D). No correlation was detected betweenPOM121 mutation and clustered interchromosomal transloca-tions between chr5 and chr12 (Kendall correlation analysis; datanot shown).

Note that for two of the patients in MM cohort, we alsosequenced matched lymph node metastases, and the same SV-and CNV-driven genomic profile was also observed in the metas-tases, showing strong concordance with the primary tumor

Figure 1.

Genomic profiles of MM. Each column represents an individual tumor that underwent WGS; MMs were grouped into two groups based on the classification of CMproposed by the TCGA: BRAFmutated or RASmutated,NF1mutated, triple wild type. A–C, The top panel shows the mutation burden of each tumor, whereas themiddle and bottom show, respectively, the number of CNVs and SVs. Gain (�3 copies) is represented in orange; loss (�1 copy) is represented in green. D,Published melanoma driver genes and significantly mutated genes (bold font) identified by MutSigCV (marked with an asterisk) or OncodriveFML (marked withan octothorpe) in MMs. E, Clinical covariates including sex, age, risk factors (drinking and smoking), and tumor sites.

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(Supplementary Fig. S7; Supplementary Table S5). Perhaps futurework should compare differences in BFBs and/or other differencesbetween CM andMM to help deepen our scientific understandingof how these types of oncogenic genetic events influence metas-tasis and morbidity.

CNV landscape and recurrently amplified genes in MMsPrevious studies have examined the CNV features of MMs by

using array-based comparative genomic hybridization and WESbased on relatively small samples sizes (<20 samples; refs. 15, 17,40). OurWGS data from a relatively large patient cohort provided

Figure 2.

Recurrent POM121mutations identified in MMs. A,Map of POM121 functional domains and the sites of amino acid changes found byWGS. B, Patients with POM121mutation tend to have worse prognosis. C, Ki67 expression of patients according to the mutational status of POM121. The P value was calculated by the Fisherexact test.D, Representative images of different staining levels of Ki67 expression in MMs. Scale bars, 100 mm; H&E, hematoxylin and eosin.






the first opportunity to robustly assess the genome-wide CNVlandscape of MM. In accordance with the aforementionedreports (17, 40), we found that amplification of the 12q13–15locus—which contains the well-recognized oncogene CDK4—inmore than 50% of MMs (33 of 65 samples), making it the mostcommonly altered genomic region among all the MMs we exam-ined (i.e., this was the region with the highest median of log ratioof read depth value; Fig. 4A; Supplementary Fig. S3).

GISTIC analysis was performed to define a more detailed CNVprofile ofMMby determining regions of significant recurrent gainand loss. We identified recurrent CNVs in regions with well-recognized cancer driver genes, including gain of 1p12(NOTCH2), 4q12 (KIT), 5p15 (TERT), 11q13 (CCND1), and12q13–15 (CDK4, MDM2, and AGAP2) chromosomal regions,

and loss of the 9p21 (CDKN2A/B) and 17q15 (TP53) chromo-somal regions among theMMs (Fig. 4B; Supplementary Table S6).Other melanoma-associated driver genes such as MET, BRAF,PDGFRA, and KRAS were also found to be recurrently amplifiedamong the MMs (Supplementary Fig. S3).

Correlation between the SV and CNV patternsOf particular note, amplification of 12q13–15 (containing

CDK4) and 5p15 (containing TERT), which were highly signifi-cantly co-associated (Kendall t ¼ 0.608, P ¼ 1.15 � 10�6), wasfound to be the most significant regions of amplification (Q ¼1.10 � 10�34 and 5.59 � 10�21, respectively; GISTICanalysis; Fig. 4B). Validation of CDK4 and TERT copy-numberalteration by FISH supported that the MM patients did indeed

Figure 3.

Clustering of structural variants on chr5 and chr12 is associated with poor prognosis. Each column represents an individual tumor that underwent WGS.A, Annotation of chromosomes with clustered breakpoint regions (blue), high density of breakpoints (orange), both previous conditions (red), or clusteredinterchromosomal translocations (purple) from all the MMs. B, Distribution of defined structural rearrangement indicating oncogenic genetic events, includingBFB and chromothripsis among MMs on chr5 and chr12. C, Patients with clustered interchromosomal translocation (CTX) on both chr5 and chr12 had worseprognosis when compared with the remaining patients without this genomic pattern. The number of patients (n) per group is indicated. D, Patients with BFBshowed significantly worse prognosis compared with patients without this genetic event. The number of patients (n) per group is indicated.

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Figure 4.

Genomic landscape of CNV and significant regions of recurrent copy-number alteration in MMs. A, The landscape of CNV in MMs. The orange line and the redblock indicate copy-number gain, and the green line and blue block indicate copy-number loss. B, GISTIC analysis was performed to determine significant regionsof recurrent CNVs, and significant oncogenes in these regions were labeled. C, FISH analysis of the copy-number alteration of CDK4 (top) and TERT (bottom)amplification in representative MM samples with CDK4 or TERT amplification. Scale bars, 5 mm. D, Concordance analysis of CDK4 status defined by CNV detectionfrom theWGS data or by FISH analysis in 35 MM samples with enough tumor samples. The twomethods showed a high degree of agreement (McNemar testP¼ 1.000, k¼ 0.828, P¼ 9.226� 10�7).






exhibit amplification (Fig. 4C; Supplementary Fig. S8A). Highlevels of concordance were observed between FISH analysisand WGS result when defining the copy number of CDK4 in35 of the 65 samples (McNemar test P ¼ 1.000, k ¼ 0.828, P ¼9.226 � 10�7; Fig. 4D). Additionally, IHC with an antibodyagainst CDK4 further demonstrated apparently increased accu-mulation of CDK4 significantly correlated with the amplificationofCDK4 in these 35 samples (McNemar test P¼ 0.375, k¼ 0.708,P ¼ 2.100 � 10�5; Supplementary Fig. S8B–S8D).

Notably, we observed a striking similarity between the SV andCNV patterns: both of the amplified 12q13–15 and 5p15 regionsdemonstrated a significantly high number of interchromosomaltranslocations between chr5 and chr12 (P ¼ 5.561 � 10�10 and7.780� 10�10, respectively, Wilcoxonmatched-pairs signed ranktest; Supplementary Table S4), and patients with concurrentamplifications of 12q13–15 and 5p15 were overrepresentedamong the patients with poor prognosis (from Fig. 3C). FISHanalysis also validated the colocalization and amplification ofCDK4 and TERT from chr5 and chr12 in representative samples(Supplementary Fig. S9). It is notable that this situation in MMappears to fit with an intriguing previously proposed idea, whichholds that some oncogenic genetic events such as BFB can bothdrive interchromosome translocation between chromosomes andsimultaneously increase gene copy numbers on the translocatedchromosomal segments (32, 35).

Characterization of the identified genomic pattern in anindependent MM cohort

To further support this genomic pattern observed betweenchr5p15 and chr12q13–15 and validate the detected amplifiedgenes within these two regions, we retrospectively collected avalidation cohort of 80 MM FFPE samples and used laser capturemicrodissection to differentially sample MM versus nonlesionalmucosa tissues (Fig. 5A).We used PCRprobes targeting TERT, as aproxy covering 5p15, and used probes targeting CDK4, MDM2,and AGAP2 as proxies covering 12q13–15. An averaged copy-number ratio for these target genes was calculated for each ofthese genes relative to the reference geneRPP30, and a cutoff valueof >3 standard deviations above the mean (compared with thePCR data from the nonlesional mucosa samples) was used todefine samples as positive for the amplification of a given targetgene in an MM.

Consistent with the genomic features we demonstrated in theWGS MM cohort, amplifications of TERT, CDK4, MDM2, andAGAP2 were found, respectively, in 65% (52 of 80), 78.75%(63 of 80), 50% (40 of 80), and 48.75% (39 of 80) of themelanoma tissue samples (Fig. 5B–F). Additionally, concurrentamplifications of TERT with one of these three genes (CDK4,MDM2, and AGAP2) located on chr12 were found in 55%(44 of 80), 38.75% (31 of 80), and 40% (32 of 80) of samples,respectively. Spearman correlation analysis indicated that thecopy numbers of TERT that were significantly correlated withthe copy numbers of each of the three genes located on chr12(r ¼ 0.380, P ¼ 0.001 for TERT and CDK4; r ¼ 0.339, P ¼ 0.002for TERT and MDM2; r ¼ 0.477, P ¼ 8.00 � 10�6 for TERT andAGAP2). Thus, this follow-up analysis of an independentMM cohort showing nonrandomly amplified oncogenes locat-ed on chr5p15 and chr12q13–15 apparently recapitulatedthe MM genomic features initially identified in our WGS-data–based discovery, suggesting potential functional relevanceof these coamplified oncogenes.

Evaluation of palbociclib in a population-based PDX trialOf these coamplified oncogenes, CDK4 is the most well-rec-

ognized therapeutic target, and we selected palbociclib, the firstFDA-approved anti-CDK4/CDK6 inhibitor, for evaluation. Apilotexperiment exploring the therapeutic efficacy of palbociclib inPDX-MM011 (a CDK4-amplified model; Supplementary Fig.S10A) demonstrated dose-dependent TGI effects after 4 weeksof treatment, with TGI percentages ranging from 46.02% at adose of 60mg/kg to 76.08% at a dose of 90mg/kg (Fig. 6A and B).Palbociclib administered at a 120 mg/kg dose was not welltolerated by the mice (bodyweight loss >15%). Palbociclib pro-vided well-tolerated and sustained tumor suppression (TGI ¼60.31% at the dose of 60 mg/kg, TGI ¼ 87.05% at the dose of90 mg/kg) throughout the 8 weeks of drug administration of thepilot experiment (Fig. 6A and B).

Next, to evaluate the therapeutic efficacy of palbociclibacross a genetically heterogeneous MM population, we con-ducted a PDX trial with 24 PDXmodels established from 24MMpatients using one mouse per patient per treatment group(1 � 1 � 1) treatment format (37). ddPCR was applied tocharacterize the CDK4 and TERT copy numbers of each model:14 of the models featured CDK4 amplification, 13 of themodels featured TERT amplification, and concurrent amplifi-cation of CDK4 and TERT was observed in 9 models (Supple-mentary Fig. S10B). We used a palbociclib dose of 90 mg/kgfor a total of 8 weeks, and the drug response was defined asprogression, suppression, and regression. Among this MMPDX cohort, 37.5% (9/24) of the models, including 2 modelsdefined as regression and 7 models defined as suppression,demonstrated robust and sustained responses (Fig. 6C). Ofnote, 8 of these 9 models featured CDK4 amplification, whereasamong the 15 models that had drug responses defined asprogression, only 6 featured CDK4 amplification. Furthermore,a significant difference was observed in the probability ofprogression-free survival (PFS or tumor doubling time, definedas time until tumor volume reaches 200% of the baseline foreach of the PDX models) between groups annotated with orwithout CDK4 amplification (Fig. 6D; log-rank P ¼ 0.0012).

To further validate the therapeutic efficacy of palbociclibobserved in this population PDX trial, preserved tissuefrom PDX models with drug responses defined as regression(PDX-MM081), suppression (PDX-MM014), or progression(PDX-MM002) were used for additional palbociclib efficacyvalidation with relatively large sample sizes in each treatmentarm (n ¼ 7–12 mice per treatment group). Treatment with a90 mg/kg palbociclib dose for 4 weeks caused significanttumor inhibitions in PDX-MM081 (TGI ¼ 104.37 %) andPDX-MM014 (TGI¼ 62.21%); palbociclib caused no significanteffect in PDX-002 (TGI ¼ 18.34%; Fig. 6E–G). Western blotanalysis revealed decreased Rb phosphorylation in the xeno-grafts treated with palbociclib when compared with samplestreated with vehicle control in PDXmodels that were responsiveto the treatment (Supplementary Fig. S10C). Thus, our researchusing a genetically annotated PDX cohort representing molec-ularly defined MM patient subgroups illustrated the potenttherapeutic efficacy of palbociclib. Genotype and drug responsecorrelation analysis (indicated by the PFS comparison betweencases with or without CDK4 amplification), as well as thefollow-up study using large sample size treatment arms, furtherdemonstrate that MMs harboring CDK4 amplification are morelikely to benefit from palbociclib treatment.

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DiscussionThe present study illustrates the power of how a large patient

cohort collected mainly from one anatomic site/oral cavity—canbe examined with modern genomics analyses that yielded scien-tific insights about the molecular pathogenesis of the disease inquestion and suggest candidate strategies for precision therapieswhich have a high probability of success. It bears mention that,owing to the location and morphology of most MMs (whichexhibited a restrictedflat lesionwithin themucosal lining) and thedanger of causing functional impairment of the affected organ,the collection of fresh tumor tissue that meets the quality andquantity needed for WGS is quite difficult and extremely time-

consuming. In addition to the profound differences in the geno-mic feature of MM that we depicted when compared with CM,note that our unprecedentedly high-resolution analysis of thegenomic landscape of MM also revealed particular significantlymutated gene, as well as the unique SVs and correlated CNVsprofiles with prognostic and therapeutic relevance.

Specifically, we identified recurrent mutations of POM121 (n¼10), a previously unappreciated gene in melanoma, was the onlysignificantly mutated gene in MM other than KIT supported byboth ourMutSigCV andOncodriveFML analysismethods. Duringthe preparation of this article, Rodriguez-Bravo and colleaguesfirst reported an oncogenic role for POM121 in enhancing inprostate cancer tumor aggressiveness through interaction with

Figure 5.

Characterization of the genomic pattern using ddPCR in an independent MM cohort.A, Representative images of laser capture microdissection for isolating (MMor nonlesional adjacent mucosa tissue) fromMM samples under direct microscopic visualization. B–E, Copy numbers of TERT (located on 5p15) in CDK4, MDM2,and AGAP2 (located on 12q13–15) in MMs assessed by ddPCR. The number of melanoma tumor tissue samples (n) per group is indicated. F, Graph summarizingthe results from B–E.






importin b to promote the nuclear import of MYC, E2F1, AR, andGATA2 (41). Furthermore, they demonstrated that targeting aPOM121–importin b axis using the importin b inhibitor impo-tazole decreases the growth of patient-derived prostate cancerxenografts. Our results contribute to the emerging evidence aboutthe oncogenic role of POM121, as we found that patients withPOM121 mutations tend to have worse prognosis and we

observed that MMs with either POM121 mutation or POM121amplification had significantly higher tumor proliferation rates.Clearly, further research will be necessary to determine the patho-mechanistic role of POM121.

Considering that about 98% of the human genome is noncod-ing DNA and that somatic mutations in noncoding regulatoryregions are known to be major drivers of carcinogenesis (42). For

Figure 6.

Evaluation of therapeutic efficacy ofthe FDA-approved CDK4/6 inhibitorpalbociclib in a genetically annotatedPDX trial. A, Therapeutic efficacyof palbociclib in CDK4-amplifiedPDX-MM011 in an 8-week long-termtreatment schedule. The sample size(n) per group is indicated. B, Threegroups of mice from each of thetreatment arms after administrationof palbociclib at a dose of 60mg/kgor 90mg/kg and the control arm,n¼ 8 for each arm. C,Waterfall plotrevealing the target-dependent drugresponse in PDXmodels harboringamplification of CDK4 and/or TERT.Dotted lines separate differentcategories of drug response:progression, suppression, andregression. PDXs harboringamplification of CDK4, TERT, or bothare marked in red, blue, or orange.D, Kaplan–Meier PFS curve withpalbociclib treatment in MM PDXmodels, stratified by the geneticannotation of CDK4 amplification.E–G, Therapeutic efficiency ofpalbociclib in selected PDXmodelsfrom each response group:PDX-MM081 (regression group),PDX-MM014 (suppression group), andPDX-MM002 (progression group) at adose of 90 mg/kg for 4 weeks. TGIand the sample size (n) per group areindicated. d, day; p.o., orally; QD,every day;W, weeks.

Zhou et al.





example, mutation in the TERT promoter that drives TERT over-expression occurs as an early tumorigenic event in >70% ofCMs (43). Of note, we here detected 10 mutations (includingtwohighly recurrent hotspotmutation sites in theTERTpromoter:C228T and C250T) in 9 tumor samples (9 of 65, 13.8%) andfurther verified with targeted Sanger sequencing of the TERTpromoter region in all 65 tumor samples (Supplementary TableS2). Telomere length estimation analysis using qMotif tool wasalso conducted (19), whereas the telomere length was not corre-lated with other driver genetic lesions, including TERT promotermutation,TERT amplification,ATRX loss, TP53 loss,CDK4 ampli-fication, POM121mutation/amplification, KITmutation, and chr5–12 clustered CTX (Mann–Whitney U test; data not shown).Additionally, we identified some candidate driver loci with sig-nificantly mutated sequences in noncoding regions and illustrat-ed the mutation signature of MM as previously reported (19, 44),which could direct future hypothesis-driven research about thebiological basis of this deadly melanoma (Supplementary Figs.S11 and S12; Supplementary Table S2).

Previous studies have reported that melanomas that arise fromsun-protected tissues (e.g., MM, acral melanoma) have similargenomic features toMM, including a high frequency of CNVs andSVs (16, 19).OurWGS results further identifiedoncogenic geneticevents resembling BFB in 24 of 65 MM samples, which arepotentially involved in the recurrent localized genomic rearrange-ments between these amplified regions of chr5 and/or chr12. Inacral melanomas, enriched clustered breakpoints indicative oflocalized genomic rearrangements were found to be moreenriched in chr11, chr5, and chr17, whereas no such recurrentpattern was observed in CM (with significantly less SVs) or MM(possibly owing to the small sample size included in the study orowing to racial disparities; ref. 19). Thus, our characterization ofthe recurrent oncogenic pattern ofMMsupports thatMM is rightlyconceptualized as a subtype of melanoma distinct from CM anddistinct from acral melanomas.

More recently, Ablain and colleagues used a zebrafishmodelingapproach and confirmed that SPRED1 loss (which was alsoobserved in 24.6% samples in this study; Supplementary Fig.S3), especially in tumors driven by KIT mutation, is a driveralteration in MM (18). The MM zebrafish models, which canmodel different genotype combinations, significantly furtheredour understanding of themechanismsofMMdevelopment. In thepresent study, after our data-driven target definition and selectionof palbociclib, a population-based PDX trialwas conducted to testthe efficacy of this FDA-approved CDK4/6 inhibitor. To ourknowledge, this is the first cohort of MM PDX models in which

interpatient genetic heterogeneity was represented and has beenused for targeted drug evaluation. Our work offers a demonstra-tionof how truly genome-scale precisionmedicine (here, at the SVlevel) can successfully inform therapeutic strategies, at least at thepreclinical PDX model drug evaluation stage. We anticipate thelaunch of a novel genotype-driven precision clinical trial ofpalbociclib in MM in the very near future, and are also exploringthe use of importin b inhibitors in treating MM.

Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.

Authors' ContributionsConception and design: R. Zhou, Z. Zhang, S. SunDevelopment of methodology: J. Li, L. Wang, Z. Zhang, S. SunAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): Y. Han, G. Yang, Z. Gu, S. Xu, Y. Wang, L. Wang,Y. Wang, G. ZhouAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): R. Zhou, W. Tao, J. Li, J. WuWriting, review, and/or revision of the manuscript: R. Zhou, C. Shi, W. Tao,J. Wu, C. Zhang, Z. Zhang, S. SunAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): C. Shi, W. Tao, J. Li, J. Wu, Z. Zhang, S. SunStudy supervision: C. Zhang, Z. Zhang, S. Sun

AcknowledgmentsThe authors greatly thank Dr. Hao Chen and Jiaochun Shi (from WuXi

NextCode, WuXi AppTec, Shanghai, China), and Dr. Feng Zhang (from FudanUniversity) for assistance with bioinformatics analyses. The authors greatlythank Dr. Bosong Wang (from Shanghai Jiao Tong University School ofMedicine) and Dr. Yibiao Zhou (from Fudan University) for statistical analysis.The authors thank Shiqiang Wang (from the animal lab of Shanghai NinthPeople's Hospital of Shanghai Jiao Tong University School of Medicine) andZhongbiao Xiao (from the animal lab of Shanghai Jiao Tong University Schoolof Medicine) for animal studies. The authors greatly thank the GenomeSequence Archive (GSA) team of BIG Data Center for their help in dataarchiving. This work was funded by the National Key Research and Develop-ment Program of China (2017YFC0908500) and by grants from the NationalNatural Science Foundation of China (81572656 and 81202131), the ChinaPostdoctoral Science Foundation (2013M531191), the Shanghai PostdoctoralSustentation Fund, China (13R21415100), and the Shanghai Summit andPlateau Disciplines.

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 October 19, 2018; revised January 11, 2019; accepted February 14,2019; published first February 19, 2019.

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2019;25:3548-3560. Published OnlineFirst February 19, 2019.Clin Cancer Res Rong Zhou, Chaoji Shi, Wenjie Tao, et al. Reveals Clinically Relevant Genomic AberrationsAnalysis of Mucosal Melanoma Whole-Genome Landscapes

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