multiregional sequencing reveals genomic alterations and ... · primary malignant melanoma of the...

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Multiregional sequencing reveals genomic alterations and clonal dynamics in primary malignant 1

melanoma of the esophagus 2

Running title: Genetic evolution of PMME 3

Jingjing Li1*, Shi Yan2*, Zhen Liu1*, Yong Zhou2, Yaqi Pan1, WenQin Yuan1, Mengfei Liu1, Qin Tan1, Geng 4

Tian3, Bin Dong4, Hong Cai1, Nan Wu2, Yang Ke1. 5

1 Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), 6

Laboratory of Genetics, Peking University Cancer Hospital & Institute, Beijing, China. 7

2 Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), 8

Department of Thoracic Surgery II, Peking University Cancer Hospital & Institute, Beijing, China. 9

3 Geneis Co. Ltd., Beijing, China. 10

4 Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Central 11

Lab, Peking University Cancer Hospital & Institute, Beijing, China. 12

Correspondence and requests for materials should be addressed to Nan Wu, MD, Department of 13

Thoracic Surgery II, Peking University Cancer Hospital & Institute, Fucheng road 52, Haidian District, 14

Beijing, 100146, China. E-mail: [email protected]; Yang Ke, Professor, Laboratory of Genetics, 15

Peking University Cancer Hospital & Institute, Fucheng road 52, Haidian District, Beijing, 100146, 16

China. E-mail: [email protected]. 17

* These authors contribute equally to this work. 18

Key words: primary malignant melanoma of the esophagus, multiregional sequencing, tumor 19

evolution 20

Abbreviations: 21

BAF, B allele frequency 22

CCF, cancer cell fraction 23

ESCC, esophageal squamous cell carcinoma 24

FFPE , paraffin-embedded 25

GI, gastrointestinal 26

IHC, immunohistochemistry 27

ITH, intra-tumor heterogeneity 28

LRR, Log R ratio 29

OG, oncogene 30

Research. on January 28, 2020. © 2017 American Association for Cancercancerres.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on September 29, 2017; DOI: 10.1158/0008-5472.CAN-17-0938

mailto:[email protected]

http://cancerres.aacrjournals.org/

2

PCM , primary cutaneous melanoma 31

PMM, primary mucosal melanoma 32

PMME, primary malignant melanoma of the esophagus 33

SCNAs, somatic copy number alterations 34

SNVs, somatic nucleotide variants 35

TSG, tumor suppressor gene 36

VAF, variant allele frequency 37

38

Grant support: 39

This work was supported by the UMHS-PUHSC Joint Institute for Translational and Clinical Research 40

(grant number BMU20140483) (Y.Ke), Beijing Municipal Science and Technology Commission [grant 41

number Z141100002114046] (Y.Ke), and the Charity Project of National Ministry of Health [grant 42

number 201202014] (Y.Ke). 43

44

45




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Abstract 46

Primary malignant melanoma of the esophagus (PMME) is a rare and aggressive disease with high 47

tendency of metastasis. To characterize the genetic basis and intra-tumor heterogeneity of PMME, we 48

performed multiregion exome sequencing and whole genome SNP array genotyping of 12 samples 49

obtained from a PMME patient. High intra-tumor heterogeneity was observed in both somatic 50

mutation and copy number alteration levels. Nine geographically separate samples including two 51

normal samples were clonally related and followed a branched evolution model. Most putative 52

oncogenic drivers such as BRAF and KRAS mutations as well as CDKN2A biallelic inactivation were 53

observed in trunk clones, whereas clinically actionable mutations such as PIK3CA and JAK1 mutations 54

were detected in branch clones. Ancestor tumor clones evolved into three subclonal clades: clade1 55

fostered metastatic subclones that carried metastatic features of PIK3CA and ARHGAP26 point 56

mutations as well as chr13 arm-level deletion, clade2 owned branch-specific JAK1 mutations and PTEN 57

deletion, and clade3 was found in two vertical distribution samples below the primary tumor area, 58

highlighting the fact that it is possible for PMME to disseminate by the submucosal longitudinal 59

lymphatic route at an early stage of metastasis. These findings facilitate interpretation of the genetic 60

essence of this rare melanoma subtype as well as the pattern of cancer evolution, thus reinforcing the 61

therapeutic challenges associated with PMME. 62

Introduction 63

Mucosal melanoma is most often the result of metastases from primary cutaneous melanoma (PCM), 64

whereas primary mucosal melanoma (PMM) is an exceedingly rare disease that behaves more 65

aggressively and has a poorer prognosis(1). The molecular and pathological characteristics of 66

cutaneous melanoma have been well studied, and more than one thousand PCM exomes have been 67




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sequenced(2,3). Key cellular pathways, such as CDKN2A/CDK4/CCND1/RB1, MAPK and PI3k/AKT, and 68

significant genes, such as BRAF, NRAS, TERT, TP53, NF1, and RB1, are considered to play critical roles in 69

PCM tumorigenesis(4-7). Recently, two studies with very limited sample sizes have claimed that 70

distinct mechanisms drive PMM and PCM(8,9). Moreover, melanoma subtypes affecting different 71

body regions exhibit different genetic features, even those of the same histological type(2,10,11). 72

Despite these findings, there is a paucity of data elucidating the etiopathogenesis and predictive 73

factors, as well as the effectiveness of therapeutic options, for these diseases. 74

Primary malignant melanoma of the esophagus (PMME) is a rare gastrointestinal (GI) mucosal 75

melanoma, representing 0.1-0.2% of all esophageal malignancies, with only 339 cases reported by 76

2016 (12-14). It is reported that PMME has a tendency for vertical growth within the esophageal 77

wall(15). Melanosis is another important feature favoring PMME over a metastatic melanoma to the 78

esophagus(15). However, the molecular background of PMME is largely unknown because of its rarity. 79

Recent reports have included only small series or case studies with analyses of a single or few 80

molecular aberrations. The BRAF, NRAS, KRAS, and c-Kit genes have been reported to be the most 81

commonly altered genes in PMME(16,17). Although evidence indicates that GI (gastrointestinal) 82

mucosal melanoma arises primarily at certain areas within the GI system, it is still difficult to 83

distinguish PMM from metastatic melanoma in the GI tract that may be derived from an unknown or 84

regressed cutaneous primary tumor. Tumorigenesis and metastatic mechanisms, as well as other 85

clinical performance of PMME are lack of scientific interpretation due to the vacancy of studies. 86

Here, we applied exome sequencing and chromosomal aberration analysis to study multiple spatially 87

separated resected samples from a PMME patient, including samples of the primary tumor, metastatic 88

lymph nodes, normal esophageal mucosal tissues, and non-neoplastic melanosis lesion. The presence 89




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of a precursor lesion or melanosis could be a marker for GI mucosal melanoma(18); however, this 90

notion is still under debate, and more evidence is needed. In general, this PMME exhibited distinct 91

genetic features, with both similarities to and differences from those of cutaneous melanoma. 92

Significant driver genes in PCM, such as BRAF and CDKN2A, were determined to be potential driver 93

genes in this PMME, whereas infrequently altered genes in PCM, such as KRAS, also played a role in 94

PMME tumorigenesis. By characterizing the genetic basis and intra-tumor heterogeneity (ITH), we 95

found that the genome of this PMME fit a branching evolution model, as ancestor clones evolved 96

along different trajectories and diversified into primary tumor subclones and early and late metastatic 97

subclones. Interestingly, the mutational signature switched from a C>T to a C>A transition with tumor 98

progression, indicating that different inducers promoted each trunk and branch mutation during the 99

mutational processes. 100

Comprehensively resolving the genetic architecture and temporal dynamics of the mutagenic 101

processes in PMME could help us better understand the genetic basis of this rare malignancy. With 102

more PMME cancer genomes being deciphered, advanced diagnostics and therapeutics could be 103

developed in the near future. 104

Material and Methods 105

Patient and samples 106

A 59-year-old Chinese female was admitted to the Thorax Surgical II Department of Beijing Cancer 107

Hospital in October 2013 with a 3-month history of dysphagia. Physical examination and CT scan 108

showed no evidence of skin melanoma lesions. Esophagogastroduodenoscopy revealed a 3.0 × 2.5-cm 109

polypoidal tumor with black pigmentation; 3 cm below the bottom edge of the main tumor, a flat, 0.5 110

× 1.0-cm mucosal melanosis lesion was observed. The patient did not receive any treatment before 111




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surgery. The patient was informed and signed an informed consent form before surgery. This study 112

was approved by the Medical Ethics Committee of Peking University Cancer Hospital (#2013KT31) and 113

conducted in accordance with the Declaration of Helsinki. 114

The resected esophageal specimen was photographed and marked with a vertical ruler. Then, spatially 115

separated samples, including four primary tumor samples (T1-T4), five normal mucosal samples 116

(N1-N5), and one mucosal melanosis sample (ME1), were collected discretely. Lymph node samples 117

(LN1-LN4) were isolated from surgical specimen tissue blocks, and a peripheral blood sample was 118

acquired after surgery (Figure 1A&Figure S1). Each tumor and normal mucosal sample (10-20 mg) was 119

cut into thirds; one piece was used for pathological analysis, the second was used for genomic DNA 120

extraction, and the third was kept in a storage solution (RNAlater, Thermo Fisher Scientific) as an 121

extra piece. Experienced local pathologists performed a histopathological review of all primary tumors, 122

including immunohistochemistry (IHC) for detection of HMB-45, Melan-A, and S-100 protein 123

expressions (Supplementary Figure S2). The ME1 sample had a jelly-like texture, which may have led 124

to its failure in the formalin-fixed, paraffin-embedded (FFPE) process; thus, no further pathological 125

examination was performed on this sample. Genomic DNA was isolated using a DNeasy Blood and 126

Tissue Kit (QIAGEN) or a QIAamp DNA FFPE Tissue Kit (QIAGEN). 127

Multiregion exome sequencing 128

Exome capture was performed using 3-6 μg of genomic DNA per sample with an Agilent SureSelect 129

Human All Exon V4 Kit according to the manufacturer’s instructions. Briefly, genomic DNA was 130

fragmented with an ultrasonicator (Covaris) to obtain fragments that were primarily between 250 and 131

300 bp in length. These fragments were amplified using an NEBNext Ultra DNA Library Prep Kit (NEB) 132

and then hybridized with an Illumina TruSeq Capture Kit for enrichment. Each captured library was 133




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loaded onto an Illumina HiSeq2000 platform, and paired-end sequencing was performed to the 134

desired median sequencing depth (>200×). Raw image files were processed using HCS1.4.8 for base 135

calling with the default parameters. 136

The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive 137

in BIG Data Center, Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, under accession 138

number CRA000346, that are publicly accessible at http://bigd.big.ac.cn/gsa. 139

Somatic mutation calling 140

The sequencing reads were aligned to a human reference genome (hg19) using BWA(19). Mutect 141

(v1.16) was employed for somatic mutation calling. The following filtering criteria were applied to the 142

mutation profiles produced with Mutect to obtain highly probable somatic nucleotide variants (SNVs): 143

(i) only SNVs marked with a ‘keep’ status were considered; (ii) minimum depths of 10× and 14× were 144

required for the normal and tumor samples, respectively; and (iii) a minimum of four reads was 145

required to support the mutant allele. Small indels were identified using Pindel version 0.2.4(20) in 146

paired tumor-normal mode. Highly probable indels were identified using an in-house pipeline as 147

follows: i) all identified indels were required to have a minimum coverage of 20 reads in both the 148

tumor and normal samples; and ii) a minimum of 5 independent reads was required to support the 149

indel event in the tumor sample, with no evidence of such an event in the paired normal sample. The 150

qualified variants were annotated with oncotator(21). 151

Variant classification 152

To identify possible driver events, we classified the altered genes in this PMME according to reports in 153

the literature, as well as databases. Mutated genes were classified into one of six tiers: 1) Tier A: 154

cutaneous melanoma-related gene(2); 2) Tier B: probability score for oncogene (OG) or tumor 155



http://bigd.big.ac.cn/gsa


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suppressor gene (TSG) > 0.75, as indicated by TUSON Explore (22); 3) Tier C: suggested TSG or OG by 156

Vogelstein et al(23); 4) Tier D: suggested significant cancer gene by Lawrence et al(24); 5) Tier E: 157

cancer-related gene in the Cancer Gene census catalog (http://cancer.sanger.ac.uk/census); and 6) Tier 158

F: recurrent gene mutation in mucosal melanoma(8). SIFT(25), PolyPhen-2(26), and 159

MutationAssessor(27) were used to predict the potential biological function changes of each missense 160

mutation. If any mutation received a rating of "Damaging" in SIFT, "Damage"/"Possible Damage" in 161

Polyphen-2, or "Medium"/"High" in MutationAssessor, it was considered to have a high functional 162

impact (HiFI). Nonsense and frameshift mutations, as well as splicing mutations, were also regarded as 163

HiFI alterations. Non-HiFI mutations were not considered to contribute to PMME tumorigenesis or 164

invasion. 165

Copy number alteration 166

Whole-genome SNP array for each samples was performed on Illumina Human OmniZhongHua 167

BeadChips (Illumina, San Diego, CA, USA). Raw intensity values were processed to obtain a normalized 168

B allele frequency (BAF) and a Log R ratio (LRR) for each probe using the Genome Studio Software 169

V2011.1. LRR values were segmented by the ASCAT algorithm(28). Tumor and matched normal 170

samples were used in pairs to obtain somatic alterations. 171

Inferring cancer cell fraction and clonal status 172

Somatic copy number alterations (SCNAs) were predicted with ADTEx(29) using both depth of 173

coverage ratios and B allele frequencies (BAFs) calculated from the WES data. Briefly, ADTEx consists 174

of two hidden Markov models (HMMs) to predict SCNAs and genotypes in WES data. One HMM is 175

used to predict CNAs, which, in combination with BAFs, can be used to estimate tumor ploidy and 176

predict absolute copy numbers. The second HMM is used to predict the zygosity or genotype of each 177




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CNA segment. In this study, ADTEx v2.0 was run with the BAM and BAF inputs using the default 178

parameters. 179

ABSOLUTE (v1.0) was used to predict the tumor content, ploidy, and absolute copy number based on 180

the copy number profile and somatic SNVs for each tumor. The cancer cell fraction (CCF) of each 181

mutation was subsequently estimated according to the mutant VAFs after adjustment for the tumor 182

purities and local absolute copy number. Private, branch, trunk mutations were determined by the 183

extent of shared mutations among the different samples. 184

Phylogenetic tree construction 185

In principle, a phylogenetic tree was generated according to the numbers of shared mutations among 186

the samples. Of the sequenced samples, three were considered to be normal tissue samples (N1, N5, 187

and LN4) with few mutations, and another three (LN3, ME1, and N3) had a low tumor content (35%, 188

15%, and 17%, respectively). The four primary tumor samples (T1-T4) possessed a high tumor content 189

of over 80%, whereas the other two lymph node samples (LN1 and LN2) had a tumor cell proportion 190

of >50%. Utilizing low-tumor-content samples can introduce bias into the phylogenetic tree. Therefore, 191

we selected SNVs from six high-tumor-content samples to create the topological structure that 192

reflected the main evolutionary trajectory of this tumor. Then, we added the remaining samples to the 193

prototype tree according to the numbers of SNVs they shared with the existing taxon. Because ME1 194

and N3 had a relatively low tumor content, we were not able to estimate the precise divergence time 195

when they derived from the founding clone; thus, we suggested that they should be located at the 196

beginning of the trunk of the tree (Figure 1B). During tree construction, we also considered tumor 197

content, copy number changes, and intermixed clones that might have led to the misinterpretation 198

of our findings. By calculating branch/trunk lengths inferred from the mutation counts, the final trees 199




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were drawn manually. 200

201

Results 202

Mutation profiles of primary mucosal melanoma 203

Whole exon-capture multiregion sequencing (WES) was performed on DNA from 12 samples derived 204

from esophagectomy specimens, including four samples obtained from primary tumor dissection 205

(T1-T4), three normal mucosal samples (N1, N3, and N5), one melanosis sample (ME1), and four 206

metastatic lymph node samples (LN1-LN4). Germline control DNA was extracted from the peripheral blood. 207

From 13 sequenced samples, high-coverage sequencing (mean, 200×) data were obtained. Overall, 208

386 nonsynonymous nucleotide substitutions and 134 indels (insertions and deletions) were detected 209

in at least one sample (Supplementary Table S1 and S2). Fifty single nucleotide variants (SNVs) were 210

randomly selected and validated in four primary tumor samples (T1-T4) by nucleotide mass spectrum 211

(Sequenom) The genotypes were successfully validated for 188 (94%) of the 200 (50 mutations per 212

sample) tested loci. Tumor purity of the primary tumor was estimated to be nearly 80% using 213

ABSOLUTE software according to the exome sequencing data (Table 1), indicating that our data were 214

sufficiently robust to detect subclonal mutations with low variant allele frequencies (VAFs). 215

To compare the differences in the mutation spectra between PMME and PCM, we acquired genomic 216

data for PCM from TCGA database (http://www.cbioportal.org/). A total of 281339 SNVs from 341 217

PCMs were used in this analysis. We also utilized WES data from 81 squamous esophageal carcinomas 218

(derived from unpublished data obtained in our laboratory) to compare similarities in mutational 219

signatures among ESCC, PCM, and PMME. As reported previously, the PCM genome exhibited a 220

specific predominance of C>T transitions at TpC dinucleotides, which were probably associated with 221




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exposure to ultraviolet light. The ESCC genome was characterized by a mutational process associated 222

with an APOBEC-mediated and aging signature; thus, the mutations tended to be C>T or C>G 223

alterations. In this PMME genome, we found that 46.1% (178/386) of the somatic mutations were C>A 224

transitions, 41% (73/178) of which occurred in the CpCpA tri-nucleotide context (Figure 2A-B). 225

However, no similar signature was identified in the COSMIC data, suggesting that the CpCpA signature 226

found in this PMME genome may be caused by an unknown mutational process that needs to be 227

further investigated. In summary, although these three types of tumors shared similar anatomical or 228

pathological characteristics, they underwent distinct mutational processes, indicating that different 229

molecular mechanisms drive the tumorigenesis and progression of each tumor type. 230

Regional ploidy profiling and chromosomal aberration detection 231

SCNAs were investigated in this PMME. At the arm level, we observed copy number loss of 1p, 3p, 4p, 232

11p, 11q, and 14q and copy number gain of 1q, 6p, 8p, and 8q (Figure 3A). To identify focal 233

amplifications or deletions in these samples, we applied GISITC to determine copy numbers for these 234

13 regional samples and found 23 amplification and 21 deletion peaks across the genome, some of 235

which were associated with potential oncogenic genes, such as EIF3E, KRAS, and SOX5 and the tumor 236

suppressor genes PTEN and CDKN2A. Interestingly, we observed characteristics of chromothripsis in 237

chromosome 3p in the primary tumor samples (T1-T4) and two metastasis lymph nodes (LN1 and LN2) 238

(Figure 3B). These observations were based on the following principals: 1) only one chromosome was 239

affected; 2) distinctive oscillation between two copy number states arose across the affected regions; 240

and 3) within the regions with ‘higher’ copy number states, retention of heterozygosity was observed. 241

Intra-tumor heterogeneity and spatial separation of subclones 242

To assess ITH, we examined 235 nonsynonymous point mutations from the primary tumor, including 243




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the T1-T4 regions, to determine the regional mutation distribution. Only 20% (47/235) of the 244

mutations were detectable across all four sampled tumor regions, whereas 54.5% (128/235) of the 245

mutations existed in a single region. Among all of the sequenced spatial samples, N1, N5, and LN4 246

were confirmed to be in the normal mucosal region due to their infrequent mutations, and N3 and 247

ME1 showed pre-tumor clonogenic potential because they both shared pathogenic mutations with 248

other samples of high tumor content, suggesting that they were clonally related. As the tumor content 249

was relatively low in these two samples, the number of SNVs was not as high as that in the primary 250

tumor regions. T1-T4 and LN1-LN3 were considered to be tumor regions, and we found an average of 251

136 mutations per sample, with the number of SNVs ranging from 98 to 188, in regions with a tumor 252

content of over 50% (Table 1). 253

To characterize the ITH and evolutionary trajectories in the PMEE genome, a phylogenetic tree was 254

constructed based on the extent of shared somatic mutations identified in each of the tumor 255

cell-infected regions (T1-T4, LN1-LN3, ME1, and N3), and this tree was used to determine the clonal 256

relatedness of the tumor subclones that co-existed in this PMME. The results showed that this PMME 257

tumor had a typical branched rather than linear tumor evolution. Subclones of the primary tumor and 258

other regions shared genetic mutations inherited from a common ancestor. Allopatric clones evolved 259

and followed distinct evolutionary trajectories. ME1 and N3 remained at the original phylogenetic 260

position and slowly developed alterations, whereas the T1-T4 sample region acquired the necessary 261

genetic alterations to form the primary tumor clone. The original tumor clone continued to progress 262

and diversified into two major branches: clade1 and clade2 (Figure 1B). Interestingly, we observed 263

that clade1 seemed to undergo a trunk mutation accumulation stage, during which time dozens of 264

mutations emerged in this branch, which then shaped the main clonal constituents in clade1 that 265




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evolved into new subclones with metastatic ability. Notably, we found that the tumor sample T4 266

shared mutations with both clades, suggesting that the subclones had originated from clade1 and 267

clade2 and that they had broken the spatial barriers of the solid tumor and intermixed in the T4 region. 268

We further divided T4 into T4a and T4b according to their respective subclones, and we then 269

compared the VAFs of the shared mutations between the spatial samples in clade1 and clade2. Our 270

results showed that nearly 20% and 60% of the tumor subclones of T4 came from clade1 and clade2, 271

respectively. Additionally, the VAFs of the mutations in T4a and T4b were lower than those of the 272

mutations in the other regions in each clade (Supplementary Figure S3A), which further highlights 273

the fact that T4 was derived from two progenitor. 274

At the copy number level, this PMME also exhibited ITH. Copy number loss of 1p, 3p, 11p, 11q, and 275

14q and gain of 1q, 8p, and 8q were ubiquitous and conserved across all tumor clones, and these 276

SCNAs were considered to have occurred as early evolutionary events (Figure 3A&3C). Focal 277

amplification of SOX5 and EIF3E, as well as homogenous deletion of CDKN2A were in the trunk clones. 278

Telomere-bounded 1q and 2q amplification, internal 4q deletion, neutral LOH of 7p, chr13 arm level 279

deletion and 12q gain were specific occurred in clade1; telomere-bounded 4q deletion, 7p 280

amplification, chr10 arm level deletion (Figure S3B), and chr18 arm level deletion were only identified 281

in clade2 (Figure 3A & Supplementary Figure S4A-C). Furthermore, we found that clade-specific SCNAs 282

intermixed in T4, such as deletions involving 4q, telomere-bounded amplification of 2q, chromosome 283

10 and 18 deletion, further confirming that T4 is intermixed clones from two different clades. For 284

example, 10q deletion involving PTEN (chr10q23.31) was detected in clade2 but absence in clade1, 285

whereas PTEN deletion of T4 showed a lower VAF (Supplementary Figure S3B). The phylogenetic 286

relationships between each of the spatial regions reflected by the SCNAs were highly consistent with 287




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the mutation tree. 288

Potential parallel evolution was observed in this PMME at copy number level although no evidence of 289

parallel evolution was found at the mutational level. A mirrored subclonal allelic imbalance was 290

observed in chromosome 4. If the maternal allele is gained or lost in a subclone in one region, yet the 291

paternal allele is gained or lost in a different subclone in another region, it will result in a mirrored 292

subclonal allelic imbalance profile(30). Different SCNAs of chr4 deletion which affected maternal allele 293

of chr4:82-143M and paternal allele of chr4:93M-telomere were observed in clade1 and clade2 294

respectively (Figure 4), suggesting parallel evolution in branched stage. Moreover, even inside the 295

independent clades, such chromosomal instability persisted. In clade1, 27% subclones of T1 296

obtained a privately chr4 arm-level deletion, which coexisted with the clade1 common chr4 aberration 297

(chr4:82-143M); in clade2, 46% tumor subclones of T2 shared clade specific chr4 loss (93M-telomere) 298

with T3 in paternal allele, whereas the remaining 54% subclones of T2 carried chr4:103M-telomere 299

loss in maternal allele (Figure 4). 300

301

Mutation spectra of truncal and branch mutations 302

To further explore the dynamics of the mutational processes shaping this PMME genome over time, 303

the temporal spectra of the somatic mutations in the different evolutionary stages were analyzed. The 304

PMME genome exhibited a significant increase in the proportion of C>A transversions in branch 305

mutations compared with trunk mutations (P = 0.006) (Figure 2B), which was accompanied by a 306

decrease in C>T transitions. The private mutations in ME1 and N3 presented with similar signatures as 307

the founder mutation (Figure 2B). 308

Identification of truncal and branch driver mutations 309




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To determine whether specific driver genes carried predominantly trunk or branch mutations, we 310

identified potential driver mutations according to the known cancer gene catalogs. A total of 22 311

altered genes were present in the catalogs, and each of them carried a single mutation, except CDH13 312

(Figure 4). Among the 26 potential driver mutations identified, 17 were predicted to be pathogenic by 313

SIFT/Polyphen2/MutationAssessor. Potential functional trunk mutations in BRAF, KRAS, DNAH7, and 314

CDH13 were detected in all of the primary tumor regions; therefore, these mutations were considered 315

to have occurred during the early stages of tumorigenesis. In addition, branch mutations in JAK, 316

ARHGEF4, and UMOD were observed. The JAK mutations belonged to clade2, and the mutations in the 317

other two genes were specific to clade1. Mutations in PIK3CA, GPRASP1, and ARHGAP26 occurred 318

exclusively in T1 and lymph node metastatic regions, whereas their cancer cell fraction (CCF) values 319

were increased in the metastatic regions, which suggested that the tumor cell populations that 320

harbored these mutations might have experienced subclonal expansion after exposure to the 321

metastatic lymph node environment. Activating mutations in TRPS1, MAPK3K13, AHNAK, DNAH3, 322

PCDHGA3, PRUNE2, and TAS1R2 were private and distributed throughout different spatial regions 323

(Figure 1B). However, their CCFs were much lower than those of the founding and branch mutations, 324

as they appeared to be intra-regional subclonal mutations (Figure 5). 325

Discussion 326

The genomic landscape of cutaneous melanoma has been well described through the use of 327

next-generation sequencing (NGS). New diagnostic and prognostic biomarkers, as well as therapeutic 328

approaches, are being developed based on known germline and somatic genetic alterations in PCM. 329

These advances will improve the treatment of PCM patients. However, the genetic nature of PMM 330

still has not been elucidated; thus, patients with PMM, which is an important subtype of melanoma, 331




16

may not benefit from the advances facilitated by the new technologies. Therefore, sequencing efforts 332

must be continued, and particular attention should be paid to rare melanoma subtypes to 333

comprehensively characterize the somatic mutational landscape of melanoma. In this study, we 334

sequenced a rare primary esophageal melanoma using a multiregion exome sequencing strategy to 335

characterize the genetic profile, ITH, and clonal evolution of this PMME. 336

Our data revealed that the four primary tumor samples harbored a total of 110 coding region nsSNVs, 337

whereas each tumor site carried an average of 55 nsSNVs (T1: 67, T2: 48, T3: 38, and T4: 67). The real 338

mutational burden was underestimated by one-fold when only one tumor sample was sequenced, 339

which suggests that high ITH existed in this PMME genome. The high somatic mutational burden in 340

melanoma has been previously linked to favorable outcomes in immune-based therapeutic 341

approaches(31); thus, it is necessary to consider the influence of ITH in the PMME genome when 342

evaluating mutational burden, particularly in clinical practice. 343

To better interpret the genomic ITH and tumor evolutionary history in this PMME, we selected 23 344

important mutations from among all of the altered genes as representative genetic evolutionary 345

events. The candidate driver genes for mucosal melanoma are currently unclear; thus, we employed 346

pan-cancer and cutaneous melanoma catalogs, as well as data from nine reported mucosal melanoma 347

genomes, to predict putative driver genes. Genomic ITH of this PMME was observed for both somatic 348

mutations and chromosomal imbalances. Among the 22 selected putative driver mutations, only four 349

were clonal events; the other mutations, including a canonical hotspot mutation, PIK3CAE545A, were 350

restricted to tumor subclones.In copy number level, ITH was also significant. Some SCNVs involving 351

important cancer genes such as homogeneous deletion of CDKN2A, and high level amplification of 352

KRAS and SOX5 (Figure 3C) were ubiquitous across the clade 1 and clade2.Each evolution braches had 353




17

its own specific SCNAs, such as PTEN focal deletion that was exclusively occurred in clade2 and chr13 354

arm-level deletion that only apperaed in clade1.The ITH status could have important implications for 355

targeted therapeutic strategies. Strikingly, we found that mutations in genes involved in the 356

PI3K-AKT-mTOR pathway, such as PIK3CA, tended to be present in subclones, and some reports have 357

suggested that PIK3CA mutations often lead to subclonal expansion, whereas mutations in genes 358

associated with RAS-MEK or cyclin-dependent kinase often result in founding clones. These results are 359

consistent with previous research(32). Therefore, our findings suggest that the current methods 360

utilized to identify cancer genes are likely biased to detect clonal drivers that occur at a higher 361

frequency in single samples; thus, it is necessary to use a more efficient strategy to obtain a full list of 362

clinically actionable genes, such as collecting spatial samples from the same individual and pooling 363

DNA for further analysis. 364

A phylogenetic tree was constructed for this PMME by analyzing the genetic variants identified in 365

tissues from each of the geographically separated regions. A branching evolution model was proposed, 366

as two of the tumor clades exhibited subclonal differentiation. Genetic diversity was greater in the T4 367

region than at the other sites; it seemed that T4 comprised two distinct subclones (T4a and T4b), 368

which belonged to clade1 and clade2, respectively. By comparison of VAFs of T4 mutations and 369

SCNAs with other primary tumor samples, it was very obviously that branch specific mutations or 370

SCNAs showed lower VAF value in T4 than others (Supplementary Figure S3A-B). These results 371

indicated that the subclones of clade1 and clade2 converged in T4 but that competitive subclones 372

with selective advantages had not yet adapted in that region. Recently, a common parallel evolution 373

pattern that involved chromosome 4 instability was suggested by Jamal‑Hanjani et al. in lung 374

cancer(30). In this study, we also observed chromosome 4 instability which performed diverse forms 375




18

in evolution branches (Figure 4). Ongoing dynamic chromosomal instability were associated with 376

intratumor heterogeneity and resulted in parallel evolution of driver somatic copy-number alterations, 377

which may possibly associated with poor survival in cancer patients(30). 378

Early (truncal) mutations likely occur either before or during tumor initiation or during early 379

development, whereas late (branch) mutations reflect mutational processes that shape the genome 380

during tumor maintenance and progression(33). By focusing on putative driver events, we found that 381

critical trunk mutations tended to be clonal, whereas branch mutations tended to be present in 382

subclones (Figure 4 & Supplementary Figure S5). Among the four trunk mutations, BRAF and KRAS, 383

particularly BRAF, are notorious cancer-promoting mutations in various cancers, and they account for 384

25% of melanoma cases in the Chinese population(34). We did not observe a hot spot mutation in 385

BRAFV600E in this case, but another pathogenic mutation, BRAFH574Q, was detected, which may also play 386

a significant role in tumorigenesis. KRAS gene mutations are rarely observed in cutaneous melanoma. 387

However, the hot spot mutation KRASK12S has been reported in one PMME(17). Notably, trunk 388

mutations in CDH13 and DNAH7 exhibited similar evolutionary patterns as those in BRAF and KRAS, 389

indicating that they might also function during tumor initiation. CDH13 encodes a member of the 390

cadherin superfamily, and it is hypermethylated in many types of cancers(35-37). DNAH7 is a 391

component of the inner dynein arm of ciliary axonemes and drives the sliding of microtubules, which 392

is associated with papillary craniopharyngioma(38). Thus, we suggest that CDH13 and DNAH7 might 393

also be critical during initial tumorigenesis and that more attention should be paid to these genes. 394

However, more biological evidence is needed. 395

From the phylogenetic topology, we were also able to infer the possible evolutionary trajectories of 396

the tumor metastases. Among the four tested lymph nodes, three were found to be infiltrated by 397




19

metastatic tumor cells. All of the metastatic tumor subclones were nested in clade1, and T1 was their 398

most recent common ancestor. Metastatic subclones containing pathogenic mutations in ARHGAP26 399

and PIK3CA, as well as Chr13 arm-level deletion experienced subclonal expansion in metastatic 400

environments (Supplementary Figure S6). The subclone that carried ARHGEF4 and UMOD gene 401

mutations was detected in T1, T4, LN1, and LN2, and it maintained subclonal dominance in LN1 and 402

LN2. We employed TCGA data to test whether above PMME metastatic molecular changes are also 403

metastatic features in other melanoma (supplementary file, Table S3& Figure S7). It is noticeable that 404

chr13 arm-level deletion is significantly occurred in metastasis TCGA samples (Figure S7), which 405

suggested that this chromosome aberration could be a common metastatic marker in melanoma 406

regardless the sample type. The microenvironment in the lymph nodes might have facilitated positive 407

selection for metastatic tumor cells with such mutations, providing them with growth advantages. 408

Spatially separated lymph nodes had similar subclones and belonged to the same monophyletic group, 409

although most VAFs in the LN3 region were very low. Our results highlight the fact that spatially 410

segregated metastatic subclones can follow very similar evolutionary trajectories. 411

Another interesting finding was that two of the “normal” mucosal samples were related with the 412

primary tumor clone and may derived in the very early stage of tumorigenesis. ME1 and N3 shared a 413

certain number of SNVs with the primary tumors. A total of 41.3% of the SNVs (19/46) in N3 were 414

shared with the tumor clones, and 36.2% (29/80) of those in ME1 were also present in the primary 415

tumor (Supplementary Figure S8). Nevertheless, no significant gene mutations were identified in ME1 416

or N3. Intensive SCNA analysis could further confirm this relationships. Since ME1 (CCF=11%) and N3 417

(CCF=7%) had extremely low tumor cell content, only SCNAs with BAF> 0.535 based on ASCAT 418

algorithm (Figure S9) could be detected. Two chromosome aberrations which located in chr7q and 419




20

chr8 (Figure 3A) were identified in ME1, and chr8 amplification could also be observed in N3. Chr7q 420

and Chr8q amplification were trunk SCNAs and across both clade1 and clade2 samples, which 421

indicated that N3 and ME1 had a common ancestor with the primary tumor. Moreover, chr15 422

(60M-telomere) LOH was absence in ME1 or N3, which was another ubiquitous SCNA and with a high 423

detection threshold (BAF> 0.535). These results indicated that ME1 and N3 diverged from other tumor 424

samples in very early stage. It is reported that PMME has a tendency for vertical growth within the 425

esophageal wall, and has a tendency to disseminate by the submucosal lymphatic route(15). In this 426

case, ME1, N3 and the primary tumor distributed vertically along the esophageal wall (Supplementary 427

Figure S1), so it was most probably that early metastatic clade3 (ME1 and N3) was formed by 428

dissemination through the submucosal lymphatic route. Findings of this study illustrated the 429

mechanisms of early intramural metastasis, which might be a common cause for bad survival in cancer 430

patients(30). This finding prompt the clinicians pay more attention to improve the surgical strategy of 431

PMME to decrease the risk of recurrence or metastasis. Technically, it also warned that using “normal” 432

tissues as germline control is risky for missing some important molecular aberrations. 433

In this PMME, we observed significant shifts in the mutational signatures during different tumor 434

progression stages. The decreased proportion of C>T mutations was accompanied by an increase in 435

C>A mutations over time. In skin melanoma, C>T is the predominant nucleotide base substitution that 436

may be caused by the misrepair of ultraviolet-induced covalent bonds between adjacent 437

pyrimidines(39). C>T mutations may also be caused by another inductive event, such as the 438

spontaneous deamination of 5-methyl-cytosine, which predominantly occurs at NpCpG 439

trinucleotides(40). We observed a relatively high proportion of C>T transitions at CpG sites in the 440

trunk of the phylogenetic tree; however, within the branches, C>A changes became the most common 441




21

alteration (Table 1 and Figure 2B). Some studies have suggested that smoking may be a risk factor for 442

C>A substitutions(24,41). However, this patient was not a smoker, so it is unlikely that tobacco caused 443

damage to the genomic DNA. We presume that specific processes promoted the generation of genetic 444

diversity in this PMME and that the spontaneous deamination mutational process might have played 445

an important role in founding clone formation; subsequently, some unknown mutational processes 446

resulted in C>A alterations and eventually promoted subsequent subclonal expansions. Patterns of 447

mutation spectrum could also confirmed our presumption that metastatic event of ME1 and N3 448

started at early stage, because the mutation spectrum of ME1 and N3 were as similar as the founding 449

clone. 450

As in any case study, the present study has notable limitations. It involves only one patient, and thus 451

further studies are needed to determine whether the principles discovered here apply to other 452

patients. Despite such limitations, this case provides evidence for tumor evolution models and tumor 453

cell disseminate route in molecular level, which to our knowledge has not yet been demonstrated in 454

patients with PMME. 455

In conclusion, by sequencing multiregional samples obtained from a PMME patient, we determined 456

the evolutionary history of this tumor. The presence of ITH and regionally separated driver events, in 457

addition to the relentless and dynamic nature of genomic instability processes, were observed in this 458

case. These findings could help us better understand the processes of PMME tumorigenesis, 459

maintenance, and metastasis. Although large-scale sequencing efforts must be continued for mucosal 460

melanoma and PMME to comprehensively characterize their genomic landscapes, our results have 461

highlighted the importance of viewing tumor development as a dynamic evolutionary process. We 462

have revealed valuable genetic information that contributes to the understanding of the biological 463




22

mechanism of PMME and that also provides insights that may facilitate the development of 464

biomarkers and therapeutic strategies. 465

466

Acknowledgement: 467

The authors thank the patient and her family to participate this study. 468

469

470

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574




25

Table 1. Summary of the exome sequencing information for a multiregion-sequenced PMME. 575

Region Origin Tumor purity

SNVs nsSNVs Subclonal

mutations* C>T

transitions CG>TG

alterations C>A

transitions CC>AA

alterations Chromothripsis

T1 Primary tumor 0.85 149 122 0.61 0.36 0.52 0.40 0.47 3p T2 Primary tumor 0.77 136 108 0.56 0.32 0.57 0.38 0.41 3p T3 Primary tumor 0.79 98 79 0.41 0.38 0.59 0.30 0.34 3p T4 Primary tumor 0.77 188 150 0.69 0.28 0.55 0.49 0.43 3p

LN1 Lymph node 0.52 140 116 NA 0.38 0.53 0.35 0.49 3p

LN2 Lymph node 0.59 138 114 NA 0.38 0.53 0.36 0.48 3p

LN3 Lymph node 0.36 104 85 NA 0.39 0.54 0.30 0.48 NA

LN4 Lymph node NA 5 5 NA 0.40 0.50 0.60 0.33 NA

ME1 Mucosal

melanosis 0.11 70 54 NA 0.47 0.61

0.23 0.31 NA

N1 Normal mucosa 0.07 7 6 NA 0.57 0.50 0.00 0.00 NA

N3 Normal mucosa NA 30 27 NA 0.47 0.57 0.23 0.43 NA

N5 Normal mucosa NA 4 3 NA 0.33 0.00 0.25 0.00 NA

* Percentage of subclonal mutations in each sample. 576 nsSNV: nonsynonymous single nucleotide variant. 577 NA: Data not available. 578




26

Figure legends 579

Figure 1. Geographical sampling approach and evolution tree of PMME. (A) Geographic distribution 580

of multiregional samples obtained from the dissection of esophagectomy and metastasectomy PMME 581

specimens. (B) Phylogenetic trees were generated by the clustering of somatic mutations identified in 582

multiregional PMME samples. Relative branch lengths were determined by the proportion of 583

mutations in each branch. The most recent common ancestor of ME1 and N3 could not be inferred 584

precisely due to their low tumor content; therefore, they were placed at the distal end of the trunk. 585

T4a and T4b were parallel subclones in the T4 region. Chr4del* and chr4del# represents branch-specific 586

deletions Chr4: (82-143M) deletion and chr4: (93M to telomere) deletion in clade1 and clade2., 587

respectively. 588

589

Figure 2. Mutation spectrum of PMME. (A) Mutation spectrum for nsSNVs in 81 ESCC, 341 PCM, and 1 590

PMME sample. The numbers of SNVs and indels in spatial PMME samples were determined. (B) 591

Temporal and spatial dissection of the mutation spectrum in PMME samples. The proportion of C>A 592

transitions increased with tumor progression, accompanied by a decrease in C>T substitutions. Gray 593

indicates insufficient mutations for analysis. 594

595

Figure 3. Copy number alterations in PMME. (A) BAF (B allele frequencies) profile across the genome 596

of PMME. Chr13 arm level deletion is metastatic specific which only occurred in clade1 (Green 597

rectangle). SCNAr. (B) Chromothripsis was observed in chromosome 3. (C) High-level focal 598

amplification was detected in chromosome 12. The SOX5 and KRAS genes are located in this amplified 599

region. 600

Figure 4. Diverse evolutionary patterns within chromosome 4. Copy number analyses reveal diverse 601

evolutionary patterns within chromosome 4 during tumor progression. Blue rectangle represents 602

branch-specific deletion Chr4: 82-143M deletion in clade1 and Chr4: 93M to telomere deletion in 603

clade2; gray and green rectangle represent chr4:93M-telomere loss and chr4:103M-telomere loss, 604

which account for 46% and 54% tumor cells of T2 respectively. 605

Figure 5. Heatmap showing the CCF of putative driver genes in each spatial region in PMME. 606




27

Putative driver genes were classified into six tiers. CM: cutaneous melanoma-related genes; PMM: 607

recurrent gene mutation in mucosal melanoma. TUSON: suggested cancer gene by TUSON Explore; Vo: 608

suggested cancer gene by Vogelstein et al; Lau: suggested significant cancer gene by Lawrence et al; 609

and Consensus: cancer-related gene in the Cancer Gene census catalog. Genes marked with an 610

asterisk indicate that the mutation in the gene was predicted to be benign with SIFT, PolyPhen-2, or 611

MutationAssessor. For each region, red or yellow indicates the presence of mutations, whereas blue 612

indicates the absence of mutations. The values in the squares are the CCF (red) or VAF (yellow) for 613

each specific SNV. The VAF was used instead of the CCF when the CCF could not be estimated due to 614

low tumor purity or conflict with the SCNA data. 615

616

617




Published OnlineFirst September 29, 2017.Cancer Res Jingjing Li, Shi Yan, Zhen Liu, et al. esophagusclonal dynamics in primary malignant melanoma of the Multiregional sequencing reveals genomic alterations and

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