Literature DB >> 27270314

Whole-exome sequencing to identify somatic mutations in peritoneal metastatic gastric adenocarcinoma: A preliminary study.

Hao Liu1, Fengping Li1, Yu Zhu1, Tingting Li1, Haipeng Huang1, Tian Lin1, Yanfeng Hu1, Xiaolong Qi1, Jiang Yu1, Guoxin Li1.   

Abstract

Peritoneal metastasis occurs in more than half of patients with unresectable or recurrent gastric cancer and is associated with the worst prognosis. The associated genomic events and pathogenesis remain ambiguous. The aim of the present study was to characterize the mutation spectrum of gastric cancer with peritoneal metastasis and provide a basis for the identification of new biomarkers and treatment targets. Matched pairs of normal gastric mucosa and peritoneal tissue and matched pairs of primary tumor and peritoneal metastasis were collected from one patient for whole-exome sequencing (WES); Sanger sequencing was employed to confirm the somatic mutations. G>A and C>T mutations were the two most frequent transversions among the somatic mutations. We confirmed 48somatic mutations in the primary site and 49 in the peritoneal site. Additionally, 25 non-synonymous somatic variations (single-nucleotide variants, SNVs) and 2 somatic insertions/deletions (INDELs) were confirmed in the primary tumor, and 30 SNVs and 5 INDELs were verified in the peritoneal metastasis. Approximately 59% of the somatic mutations were shared between the primary and metastatic site. Five genes (TP53, BAI1, THSD1, ARID2, and KIAA2022) verified in our study were also mutated at a frequency greater than 5%in the COSMIC database. We also identified 9genes (ERBB4, ZNF721, NT5E, PDE10A, CA1, NUMB, NBN, ZFYVE16, and NCAM1) that were only mutated in metastasis and are expected to become treatment targets. In conclusion, we observed that the majority of the somatic mutations in the primary site persisted in metastasis, whereas several single-nucleotide polymorphisms occurred de novo at the second site.

Entities:  

Keywords:  Sanger sequencing; gastric cancer; peritoneal metastasis; somatic mutation; whole-exome sequencing (WES)

Mesh:

Year:  2016        PMID: 27270314      PMCID: PMC5190066          DOI: 10.18632/oncotarget.9707

Source DB:  PubMed          Journal:  Oncotarget        ISSN: 1949-2553


INTRODUCTION

Gastric cancer is the fifth most commonly diagnosed cancer and the third leading cause of cancer mortality worldwide [1-3]. Although a steady decline in cancer incidence and mortality have been observed in recent years, an estimated 951,600 new gastric cancer cases and 723,100 deaths were reported in 2012. Approximately 40% of gastric cancer cases occur in China, and many are diagnosed at an advanced stage with a tendency toward metastasis and recurrence [4]. Peritoneal carcinoma occurs in both the advanced and early stages of gastric cancer and is the most common type of metastasis and recurrence [5-7]. The median survival of patients with peritoneal metastasis is less than 6 months due to the development of resistance to therapy [8-11]. Peritoneal metastasis accounts for 20.0–53.5% of recurrences after radical resection for gastric cancer [12]. Elucidating the molecular mechanism driving peritoneal metastasis of gastric adenocarcinoma is thus critical. Next-generation sequencing has emerged as a powerful tool to identify potential oncogene targets for personal therapeutic intervention as part of precision medicine and has revolutionized cancer research [13, 14]. Whole-genome sequencing provides a relatively unbiased review of the genome but is costly and produces large datasets, which present a heavy computational burden. Thus, many researchers and clinicians choose whole-exome sequencing (WES) for personal management [15]. WES directly sequences all exonic regions, which account for only 1% of the whole genome, to accurately depict the relationship between mutations and phenotypes. Furthermore, WES can achieve higher sequencing depth at a lower cost than whole-genome sequencing [16, 17]. In the era of precision medicine, WES is approved to facilitate the identification of candidate predictive biomarkers of response in metastatic cancer harboring biologically informative alterations [18]. Gastric adenocarcinoma is the most common type of gastric cancer. Once peritoneal metastasis is observed, surgery is no longer preferred as the therapeutic strategy, leading to difficulty in collecting matched primary and metastatic tumor specimens and a lack of relevant reports. Xia and colleagues recently suggested that non-curative dissection of peritoneal metastasis in selected gastric cancer patients significantly prolongs survival [19, 20]. Accordingly, we collected matched specimens for WES after non-curative dissection [21]. The genomic events during gastric cancer dissemination to the peritoneum are unknown. In our study, we aimed to reveal the mutation spectrum of peritoneal metastatic gastric adenocarcinoma by WES. Normal gastric mucosa, primary cancer, normal peritoneum and peritoneal metastasis tissues were collected from one patient.

RESULTS

Identification of single-nucleotide variants (SNVs) and insertions/deletions (INDELs) in primary and secondary tumor sites

We identified 46,609 SNVs and 48,215 SNVs in the primary gastric cancer and peritoneal metastasis, respectively; approximately 89% of the SNVs had been detected by the 1000 Genomes Project. Additionally, 4,506 INDELs and 4,643 INDELs were identified in the primary gastric cancer and peritoneal metastasis, respectively, of which 43% had been identified by the 1000 Genomes Project. Even the normal gastric mucosa and peritoneum had many SNVs and INDELs. Most of the INDELs were less than five bases in length; small INDELs represent previous in-frame shift mutations (Figure 1).
Figure 1

Distribution of the lengths of all INDELs in the on-target regions

A length >0 indicates an insertion mutation; otherwise, the length represents a deletion mutation.

Distribution of the lengths of all INDELs in the on-target regions

A length >0 indicates an insertion mutation; otherwise, the length represents a deletion mutation.

Identification of somatic variations from primary gastric cancer and peritoneal metastasis

By comparing the normal gastric mucosa and peritoneal tissue, we identified 48 non-synonymous somatic mutations in the primary tumor and 49 non-synonymous somatic mutations in the peritoneal metastasis after filtering, including7 somatic INDELs in the primary gastric cancer and 11 somatic INDELs in the secondary carcinoma. In the primary gastric adenocarcinoma, most (gastric adenocarcinoma vs. peritoneal nodules: 39%vs.40%, respectively) of the on-target somatic mutations were in the exonic region, and most (gastric adenocarcinoma vs. peritoneal nodules: 20% vs. 20%%, respectively) were synonymous somatic mutations. The primary gastric cancer and peritoneal metastasis exhibited similar mutation spectra. We observed that G: C>A: T was the most frequent transversion in somatic mutations (Figure 2). The transversion of C: G>T: A was also enriched in the somatic mutations, consistent with a report by Chen et al. [14].
Figure 2

Mutation spectrum of non-synonymous variations in gastric cancer

The blue bar represents somatic mutations in primary gastric cancer, and the red bar indicates somatic non-synonymous mutations identified in peritoneal metastasis.

Mutation spectrum of non-synonymous variations in gastric cancer

The blue bar represents somatic mutations in primary gastric cancer, and the red bar indicates somatic non-synonymous mutations identified in peritoneal metastasis.

Confirmation of somatic non-synonymous mutations

Twenty-five non-synonymous somatic SNVs and 2 somatic INDELs were confirmed in the primary tumor (Table 1), and thirty non-synonymous SNVs and five INDELs were verified in the peritoneal metastasis (Table 2) (Figure 3). Approximately 59% of the somatic mutations were shared between the primary and metastatic sites (Figure 4). The 22 mutated genes in common were IGFN1, NRXN1, CHL1, OR2W1, BAI1, RAG1, OR5T1, CPSF7, ARID2, THSD1, VWA3A, ZC2HC1C, C15orf57, TP53, ENOSF1, NDC80, MIER2, POLRMT, TTC3, KIAA2022, DNAJC3, and E2F7. Wealso identified nine genes (ERBB4, ZNF721, NT5E, PDE10A, CA1, NUMB, NBN, ZFYVE16, and NCAM1) that were only mutated in metastasis. Searching the KEGG PATHWAY database revealed that two genes (TP53 and BAI) that are important members of theTP53 pathway were simultaneously mutated in the gastric cancer and peritoneal metastasis. Both tumor sites also harbored two somatic non-synonymous mutations in the TP53 gene.
Table 1

Somatic mutations identified by WES in primary gastric cancer

ChrPositionExonAllele changeAmino acid variationCertificationGenedb SNPPolyphen2 prediction
chr1475537380exon2A>GY35CYZC2HC1CBenign
chr1540846283exon4C>AA158SYC15orf57Damaging
chr1111957501exon1124bp del533_541delNOVGP1rs201350653
chr2179582678exon83A>GV7108ANTTNBenign
chr177574026exon6C>AG202VYTP53Damaging
chr177574027exon6C>AG202WYTP53Damaging
chr199057778exon3A>CS9890ANMUC16Probably damaging
chr1103481225exon10G>AP380LNCOL11A1Damaging
chr2212248608exon27T>CE1204GNERBB4Probably damaging
chr1710427078exon36C>GD1767HNMYH2Damaging
chr377684050exon24C>GR1264GYROBO2Benign
chrX73961529exon3C>GD955HYKIAA2022Damaging
chr1235926118exon22A>TI2052NYLYSTProbably damaging
chr1246242737exon13T>CF567LYARID2Damaging
chr330691871exon31bp insE125fsNTGFBR2
chr1352972327exon3G>TL21IYTHSD1Probably damaging
chr8143545787exon1C>AD76EYBAI1Damaging
chr3439979exon24C>GP1039RYCHL1Damaging
chr138185137exon15T>AK902MNEPHA10Damaging
chr250280649exon4C>AQ231HYNRXN1Damaging
chr1136595492exon2T>CI213TYRAG1Benign
chr1277449826exon31 bp insF60fsYE2F7
chr1136595553exon21 bp insS233fsNRAG1
chr2138494232exon12T>CL339PYTTC3Damaging
chr46304013exon8G>GG831CNWFS1Damaging
chr1114880776exon13C>AA903ENPDE3BDamaging
chr1523931941exon1G>CR142GNNDNProbably damaging
chr6165801813exon17A>CF596VNPDE10ADamaging
chr1201168763exon7C>TR147WYIGFN1
chr5178392069exon5G>TG222WNZNF454Damaging
chr2229885858exon418bp del744_749delNNEFHrs59890097
chr890958479exon131 bp insK653fsNNBN
chr1156043937exon1A>CS275RYOR5T1Benign
chr19620049exon12G>AA932VYPOLRMTDamaging
chr4437571exon3C>GA229PNZNF721Probably damaging
chr18697265exon3A>CL95RYENOSF1Damaging
chr114936758exon1C>AG46CYOR51G2Damaging
chr182577827exon4G>AD88NYNDC80Damaging
chr19308907exon11C>TG335SYMIER2Damaging
chrX142596888exon2T>GK61TNSPANXN3Benign
chr1396439336exon113 bp del429_429delYDNAJC3
chr1622111606exon4T>CL106SYVWA3ADamaging
chr629012638exon1C>TM105IYOR2W1Probably damaging
chr1688600174exon10G>AR603HNZFPM1Damaging
chr1473822447exon4G>AR5WNNUMBDamaging
chr886241943exon6T>AE215VNCA1Probably damaging
chr5134910301exon3C>TR94HYCXCL14rs139612389Damaging
chr1161179326exon8G>AR390CYCPSF7Damaging
Table 2

somatic mutations identified by WES in secondary cancer site

ChrPositionExonAllele changeAmino acid variationCertificationGenedb SNPPolyphen2 prediction
chr138185137exon15T>AK902MNEPHA10Damaging
chr1103481225exon10G>AP380LNCOL11A1Damaging
chr1201168763exon7C>TR147WYIGFN1
chr2237619910exon16A>TN496IYRYR2Benign
chr250280649exon4C>AQ231HYNRXN1Benign
chr2179582678exon83A>GV7108AYTTNBenign
chr3212248608exon27T>CE1204GYERBB4Probably damaging
chr3439979exon24C>GP1039RYCHL1Damaging
chr475786223exon5A>TF851INZNF717Damaging
chr4437571exon3C>GA229PYZNF721Probably damaging
chr66304013exon8G>TG831CNWFS1Damaging
chr629012638exon1C>TM105IYOR2W1Probably damaging
chr686199234exon6C>TT376MYNT5EProbably damaging
chr8165801813exon17A>CF596VYPDE10ADamaging
chr886241943exon6T>AE215VYCA1Probably damaging
chr11143545787exon1C>AD76EYBAI1Damaging
chr114936758exon1C>AG46CNOR51G2Damaging
chr1136595492exon2T>CI213TYRAG1Benign
chr1156043937exon1A>CS275RYOR5T1Benign
chr1261179326exon8G>AR390CYCPSF7Damaging
chr1346242737exon13T>CF567LYARID2Damaging
chr1452972327exon3G>TTHSD1YTHSD1Probably damaging
chr1473822447exon4G>AR5WYNUMBDamaging
chr1575537380exon2A>GY35CYZC2HC1CBenign
chr1640846283exon4C>AA158SYC15orf57Damaging
chr1622111606exon4T>CL106SYVWA3ADamaging
chr1788600174exon10G>AR603HNZFPM1Damaging
chr177574026exon6C>AG202VYTP53Damaging
chr177574027exon6C>AG202WYTP53Damaging
chr18697265exon3A>CL95RYENOSF1Damaging
chr192577827exon4G>AD88NYNDC80Damaging
chr19308907exon11C>TG335SYMIER2Damaging
chr19620049exon12G>AA932VYPOLRMTDamaging
chr219057778exon3A>CS9890ANMUC16Probably damaging
chr2238494232exon12T>CL339PYTTC3Damaging
chrX19119441exon1G>AG177RNTSSK2Damaging
chrX73961529exon7C>GD955HYKIAA2022Damaging
chr3142596888exon9T>GK61TYSPANXN3Benign
chr330691871exon31 bp insE125fsNTGFBR2
chr1277449826exon31 bp insF60fsYE2F7
chr1396439336exon113 bp del429_429delYDNAJC3
chr1136595553exon21 bp insS233fsNRAG1
chr890958479exon131bp insK653fsYNBN
chr6160211645exon13bp del9_10delNMRPL18rs58504486
chr579746372exon94 bp del1117_1118delYZFYVE16
chr1670954703exon4615bp del2521_2525delNHYDINrs67115747
chr9139992321exon51 bp delL221fsNMAN1B1
chr11112832362exon21 bp delT10fsYNCAM1
chr375787042exon54 bp insL578fsNZNF717
Figure 3

Non-synonymous somatic mutations discovered by WES

From outside to inside: the outer ring represents the chromosome number and section, the blue ring and letters indicate mutated genes with non-synonymous somatic variations and their chromosomal locations, and the gray ring shows genes with somatic INDEL mutations. Figure 3A and 3B summarize the confirmed non-synonymous somatic mutations in primary gastric adenocarcinoma and peritoneal metastasis, respectively.

Figure 4

Distribution of confirmed non-synonymous somatic mutations in primary gastric cancer and peritoneal metastasis

Non-synonymous somatic mutations discovered by WES

From outside to inside: the outer ring represents the chromosome number and section, the blue ring and letters indicate mutated genes with non-synonymous somatic variations and their chromosomal locations, and the gray ring shows genes with somatic INDEL mutations. Figure 3A and 3B summarize the confirmed non-synonymous somatic mutations in primary gastric adenocarcinoma and peritoneal metastasis, respectively.

Comparison with a public database

In the COSMIC database, the most common type of substitutional somatic mutation in gastric adenocarcinoma is the transversion of G: C> A: T, and the major INDELs are short(less than 5 bases), consistent with our observations of the gastric adenocarcinoma with peritoneal metastasis in the present study. Five genes (TP53, BAI1, THSD1, ARID2, and KIAA2022) verified in our study were also mutated at a frequency greater than 5%in gastric adenocarcinoma in the COSMIC database, but the amino acid changes F567L in ARID2, D76E in BAI1, L21I in THSD1, and D955H in KIAA2022 had not been reported previously in gastric cancer. In the COSMIC database, TP53 was mutated in 33.4% of gastric adenocarcinoma, and 2 point mutations in TP53 were identified in the present study. The ARID2 gene was mutated at a frequency of 5.3% in 514 gastric adenocarcinoma cases. In our study, the patient also had an ARID2 gene missense mutation in both the primary tumor and peritoneal metastasis. The mutation of BAI1 leads to the amino acid mutation L21T and exerts a damaging effect on its function. BAI1 was mutated in approximately 5% of gastric adenocarcinoma in the COSMIC database, and this angiogenesis inhibitor gene was even mutated as highly as 11% among the 295 samples reported in The Cancer Genome Atlas Research Network. THSD1, which is mutated in both the primary gastric cancer and peritoneal metastasis, has a mutation frequency of 5.4%(21/389) in gastric adenocarcinoma in the COSMIC database. KIAA2022 was mutated at a high frequency of 6.9% (27/389) as analyzed by the COSMIC database. In our study, we identified a missense somatic mutation in KIAA2022, and the consequent amino acid variationD955H would presumably exert a damaging effect in the protein (Figure 5).
Figure 5

Mutation distribution of the five genes in the COSMIC database

A, B, C, D, and E represent the genesTP53, BAI1, ARID2, THSD1and KIAA2022, respectively. The arrow indicates the site of the mutation identified in gastric adenocarcinoma and matched peritoneal metastasis.

Mutation distribution of the five genes in the COSMIC database

A, B, C, D, and E represent the genesTP53, BAI1, ARID2, THSD1and KIAA2022, respectively. The arrow indicates the site of the mutation identified in gastric adenocarcinoma and matched peritoneal metastasis.

DISCUSSION

We performed WES to uncover the somatic mutation landscape of gastric adenocarcinoma with peritoneal metastasis. The mechanism of the peritoneal dissemination of gastric adenocarcinoma remains unknown, and there is no standard therapeutic method, resulting in poor survival [22]. Targeted gene analysis has identified TNF-alpha and EpCAM expression as facilitating peritoneal metastasis, whereas IL-1B might not correlate with the process of metastasis [23, 24]. Catumaxomab, an anti-EpCAM monoclonal antibody, coupled with intraperitoneally administered paclitaxel are recommended to effectively relieve gastric cancer-derived peritoneal metastasis [25]. Zhang et al. recently identified 27 somatic mutated genes and infusion of GPX4 and MPND in the19q13.3-13.4 region by whole-genome and -transcriptome sequencing of one patient [4]. The different mutation events in the present study may be attributable to the different pathological characteristics of the selected specimen. However, we cannot neglect the errors resulting from the small number of specimens in these two studies. Lim et al revealed significant enrichment of mutations in the Rho-ROCK signaling pathway by WES of gastric cancer and matched malignant ascites [21]. The discrepancies between Lim's findings and our results may be due in part to the diversity in sample selection. Genomic alterations also accumulate during the process of metastasis. The heterogeneity of gastric cancer, as revealed by Bass AJ e al., may also underlie the differences between our results and those of other studies [26]. We confirmed 20 somatic SNVs and 2 INDELs in one gastric adenocarcinoma by WES. After searching the KEGG public database, we identified two genes in the p53 pathway. The spontaneous mutation of p53 and BAI1 might play a vital role in the development of peritoneal metastasis of gastric adenocarcinoma. Five genes (TP53, BAI1, ARID2, THSD1, and KIAA2022) mutated in primary cancer and nine genes (ERBB4, ZNF721, NT5E, PDE10A, CA1, NUMB, NBN, ZFYVE16, NCAM1) mutated in peritoneal metastasis may be targets for the effective treatment of peritoneal metastatic gastric adenocarcinoma. Somatic mutations of BAI1 and its family members BAI2 and BAI3, which encode brain-specific angiogenesis inhibitors, have been identified in several cancers, including breast cancer, lung cancer, and ovarian cancer. Only BAI1 is transcriptionally regulated by p53 [27]. BAI1 is reported to be expressed in gastric epithelia during Helicobacter pylori infection and mediates the engulfment of apoptotic gastric epithelial cells [28]. BAI1 is also decreased in gastric cancer in patients with distant metastasis and poor prognosis [29]. Therefore, the role of BAI1 in metastatic gastric adenocarcinoma merits further study. ARID2 is a subunit of the PBAF chromatin-remodeling complex and has been reported to be mutated in melanoma (7%) and colorectal cancer (13%). ARID2 has been suggested to be tumor suppressive in hepatocellular carcinoma, with a mutation rate of 6.5%. ARID2 is mutated in 13% of colorectal cancer patients with microsatellite instability [30]. ARID2is also mutated in 18.2% of hepatocellular carcinoma cases, leading to inactivation of the coding protein [31]. Furthermore, the expression of ARID2 and its family members is lost during gastric cancer progression, but the effect of ARID2 on tumor progression is weaker than that of ARID1A [32]. In our study, ARID2 was synonymously mutated in exon13 and putatively disrupted the protein's function. THSD1 is located in the chromosome 13q region that is frequently lost in esophageal cancer, accelerating cancer formation [33]. In the COSMIC database, THSD1 was mutated in 5.4% (21/389) of gastric adenocarcinoma. In colorectal cancer, THSD1 is down-regulated and methylated in the promoter region [34], but the expression of THSD1 in gastric cancer with peritoneal metastasis and its role in turmorigenesis are not yet known. The THSD1 mutation in exon3 observed in this study results in the amino acid change L21T, likely exerts a damaging effect on the protein's function. KIAA2022 is a G-protein-coupled purinergic receptor gene located in the pseudoautosomal region of the X chromosome. For gastric adenocarcinoma, theKIAA2022 gene is mutated at a high frequency of 6.9% (27/389) in the COSMIC database. ZC2HC1C and C15orf57 were mutated in both the primary gastric cancer tissue and peritoneal metastasis and identified in gastric cancer for the first time. The mutation inZC2HC1C was an A>G substitution in exon 2, leading to a putatively benign effect, whereas the C15orf57 somatic mutation likely exerted a damaging effect on the protein. Nine genes were mutated in the peritoneal metastasis: ERBB4, ZNF721, NT5E, PDE10A, CA1, NUMB, NBN, ZFYVE16, and NCAMI. The acquisition of somatic mutations in these genes after metastasis, may drive phenotypic changes in cancer cells and the metastasis of gastric adenocarcinoma. As a member of the EGFR family, ERBB4 is frequently activated in brain metastases and metastatic colorectal cancer [35, 36]. In breast cancer, ERBB4plays an important role in the survival of ERBB2+ cells after they acquire resistance to lapatinib and trastuzumab [37]. The druggable gene ERBB4 was also reported to be mutated in malignant ascites of patients with gastric cancer [21]. We identified a somatic mutation in ERBB4 that may exert a damaging effect. Whether ERBB4 is indispensable for facilitating the peritoneal metastasis of gastric adenocarcinoma requires further investigation. The NUMB protein participates in the control of asymmetric division, ubiquitination of transcriptional factor p53, and endocytosis of the Notch receptor, and NUMB mutation leads to several types of cancer [38, 39]. We will further investigate the role of NUMB in peritoneal metastatic gastric cancer in a future study. The effects of somatic mutations in genes encoding zinc finger proteins (ZNF721 and ZFYVE16), a purine and pyrimidine metabolism protein (NT5E), carbonic anhydrase(CA1), and cyclic nucleotide phosphodiesterase(PDE10A)on the progress of gastric cancer requires further study. NCAM1, also known as cell adhesion molecular CD56, plays an important role in immune surveillance for the expansion of T cells, andNCAM1 over-expression in Ewing sarcoma indicates poor prognosis [40]. An insertion mutation was validated in the DNA repair gene NBN, which is altered in high-risk breast cancer [41]. Zhou et al. reported that polymorphic NBN tended to improve chemotherapeutic outcomes in gastric cancer. Because DNA repair capacity is attenuated during the evolution of cancer, more phenotypic changes tend to accelerate the formation of metastasis. In summary, we performed WES of a gastric adenocarcinoma with peritoneal metastasis. Five genes (TP53, BAI1, THSD1, ARID2, and KIAA2022) identified as frequently mutated in the COSMIC database may drive gastric adenocarcinoma dissemination to the peritoneum. The effect of the two novel somatic mutated genes (ZC2HC1C and C15orf57) in gastric cancer requires further investigation. Nine genes (ERBB4, ZNF721, NT5E, PDE10A, CA1, NUMB, NBN, ZFYVE16, and NCAMI) mutated in peritoneal metastasis are potential molecular targets for the treatment of metastatic gastric cancer. The major limitations of our study are the small sample size and single sequencing platform.

MATERIALS AND METHODS

Clinicopathology of the patient

The 60-year-old male patient was diagnosed with gastric cancer with peritoneal metastasis by computed tomography (CT) and gastroscope inspection at Nanfang Hospital of Southern Medical University in 2014. The patient had not received preoperative chemotherapy or radiotherapy; he underwent palliative total gastrectomy and D2-NO.10 lymphadenectomy followed by the construction of Roux-en-Y esophagojejunostomy. After surgery, the specimens were subjected to further pathological testing, which revealed poorly differentiated primary gastric adenocarcinoma located in the cardia of the stomach of Borrmann III type with a maximum diameter of 5 cm. Furthermore, the gastric tumor was of the mixed type in Lauren classification and had invaded to the submucosa. Lymphatic metastasis was also confirmed (8/63). Thus, the patient had advanced gastric cancer with a dismal prognosis. Sample collection and sequencing analysis were approved by the ethics committee of Southern Medical University, and the patient provided written informed consent.

Sample collection and DNA extraction

We harvested matched gastric cancer tissue and adjacent normal gastric mucosa, peritoneal metastasis and adjacent normal peritoneal tissue from one patient by laparoscopy. The DNeasy Blood & Tissue Kit (Qiagen, Germany) was used according to the manufacturer's instructions to extract and purify DNA from the harvested tissues. The concentration and quality of the DNA were determined using a NanoDrop ND-1000 spectrophotometer. Finally, 0.8%agarose gel electrophoresis was performed to confirm the quality of the DNA. Four DNA samples passed all of the strict quality supervision tests and were available for WES.

Whole-exome capture

We selected IlluminaHiSeq 2500in a paired end 2×100nt multiplex procedure to capture all exons of the samples. First, we constructed a DNA library by fragmenting the genomic DNA. Second, we utilized a Qubit® 2.0 Fluorometer to determine the concentration of the library, and the Agilent 2100 system was used to investigate the library's quality. Next, we utilized the Illumina PE Flow Cell v3 – HS system to sequence randomized DNA fragments. All sequencing processes were controlled by data collection software according to the HiSeq 2500 User Guide.

Analysis of raw sequencing data

We aligned the paired-end reads to the reference human genome (hg19) using the third-party software BWA (Burrows–Wheeler Alignment, version5.9) with default parameters for the deletion of possible PCR repeats by samtools rmdup. The average mapping ratio was as high as 96%. The Flagstat tool was utilized to assess the mapping information. Next, we analyzed the distribution of each sample's reads in the target region and the enrichment of reads in the genome. The average sequencing depth in the exome region of the case was approximately 100×; under these conditions, at least 90% of the exome region was covered by 10 or more reads, and the coverage of the target region was approximately 80%(Supplementary Figure S1). SNVs (single nucleotide variations) and INDELs (insert and deletion mutations) were then processed using the GATK UnifiedGenotyper (GenomeAnalysisTK-3.1-1). Finally, we annotated the mutations using ANNOVAR software.

Identification of somatic SNV and INDEL mutations

We applied MuTect to the WES data to detect somatic point and INDEL mutations. Normal gastric mucosa tissue and peritoneum tissue were used as references for somatic mutations of the primary and secondary tumors, respectively. Low-quality reads were first removed, bam was performed for alignment by GATK INDEL and SNV realigner after eliminating possible duplicates, and MuTect was then used to identify somatic SNVs. All somatic SNVs were annotated by ANNOVAR, which annotates by gene symbol, chromosome position, reference bases and observed bases, and mutation type. By filtering false positives, confident somatic SNVs were obtained (Figure 6).
Figure 6

Pipeline of somatic mutation analysis from raw sequencing data

Low-quality reads were removed, and bam was performed for alignment using GATK INDEL and SNV realigner after eliminating possible duplicates. MuTectwas used to identify somatic SNVs, and all somatic SNVs were annotated by ANNOVAR. By filtering false positives, confident somatic SNVs were obtained.

Pipeline of somatic mutation analysis from raw sequencing data

Low-quality reads were removed, and bam was performed for alignment using GATK INDEL and SNV realigner after eliminating possible duplicates. MuTectwas used to identify somatic SNVs, and all somatic SNVs were annotated by ANNOVAR. By filtering false positives, confident somatic SNVs were obtained.

Confirmation of non-synonymous somatic mutations

We exploited the Verity 96-well PCRamplifier(ABI, USA) to perform PCR by adding special primers, followed by conventional PCR-based Sanger sequencing using the ABI3730XL(ABI, USA) sequencer, the gold standard of sequencing systems. Next, we compared the results with the next-generation sequencing data to confirm the non-synonymous somatic mutations. COSMIC V76 is the latest version of the database of the catalog of somatic mutations in cancer. The database includes 1, 192,776 tumor samples for sequencing and25, 133whole-genome sequencing projects that have identified 3,942,175 coding mutations. Most of the data have been imported from the TCGA and ICGC databases. We compared our somatic mutations with the COSMIC database to identify driver genes of gastric cancer with peritoneal metastasis.
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Authors:  Jodi M Saunus; Michael C J Quinn; Ann-Marie Patch; John V Pearson; Peter J Bailey; Katia Nones; Amy E McCart Reed; David Miller; Peter J Wilson; Fares Al-Ejeh; Mythily Mariasegaram; Queenie Lau; Teresa Withers; Rosalind L Jeffree; Lynne E Reid; Leonard Da Silva; Admire Matsika; Colleen M Niland; Margaret C Cummings; Timothy J C Bruxner; Angelika N Christ; Ivon Harliwong; Senel Idrisoglu; Suzanne Manning; Craig Nourse; Ehsan Nourbakhsh; Shivangi Wani; Matthew J Anderson; J Lynn Fink; Oliver Holmes; Stephen Kazakoff; Conrad Leonard; Felicity Newell; Darrin Taylor; Nick Waddell; Scott Wood; Qinying Xu; Karin S Kassahn; Vairavan Narayanan; Nur Aishah Taib; Soo-Hwang Teo; Yock Ping Chow; Parmjit S Jat; Sebastian Brandner; Adrienne M Flanagan; Kum Kum Khanna; Georgia Chenevix-Trench; Sean M Grimmond; Peter T Simpson; Nicola Waddell; Sunil R Lakhani
Journal:  J Pathol       Date:  2015-08-19       Impact factor: 7.996

4.  Effect of expressions of tumor necrosis factor α and interleukin 1B on peritoneal metastasis of gastric cancer.

Authors:  Lin Guo; Jin-Lei Ou; Tong Zhang; Liang Ma; Long-Fei Qu
Journal:  Tumour Biol       Date:  2015-06-12

5.  Who will benefit from noncurative resection in patients with gastric cancer with single peritoneal metastasis?

Authors:  Xiang Xia; Chen Li; Min Yan; Bingya Liu; Xuexin Yao; Zhenggang Zhu
Journal:  Am Surg       Date:  2014-02       Impact factor: 0.688

6.  Inactivating mutations of the chromatin remodeling gene ARID2 in hepatocellular carcinoma.

Authors:  Meng Li; Hong Zhao; Xiaosong Zhang; Laura D Wood; Robert A Anders; Michael A Choti; Timothy M Pawlik; Hubert D Daniel; Rajesh Kannangai; G Johan A Offerhaus; Victor E Velculescu; Linfang Wang; Shibin Zhou; Bert Vogelstein; Ralph H Hruban; Nick Papadopoulos; Jianqiang Cai; Michael S Torbenson; Kenneth W Kinzler
Journal:  Nat Genet       Date:  2011-08-07       Impact factor: 38.330

Review 7.  Genetics and Molecular Pathogenesis of Gastric Adenocarcinoma.

Authors:  Patrick Tan; Khay-Guan Yeoh
Journal:  Gastroenterology       Date:  2015-06-12       Impact factor: 22.682

8.  Diverse somatic mutation patterns and pathway alterations in human cancers.

Authors:  Zhengyan Kan; Bijay S Jaiswal; Jeremy Stinson; Vasantharajan Janakiraman; Deepali Bhatt; Howard M Stern; Peng Yue; Peter M Haverty; Richard Bourgon; Jianbiao Zheng; Martin Moorhead; Subhra Chaudhuri; Lynn P Tomsho; Brock A Peters; Kanan Pujara; Shaun Cordes; David P Davis; Victoria E H Carlton; Wenlin Yuan; Li Li; Weiru Wang; Charles Eigenbrot; Joshua S Kaminker; David A Eberhard; Paul Waring; Stephan C Schuster; Zora Modrusan; Zemin Zhang; David Stokoe; Frederic J de Sauvage; Malek Faham; Somasekar Seshagiri
Journal:  Nature       Date:  2010-07-28       Impact factor: 49.962

Review 9.  Effective therapy for peritoneal dissemination in gastric cancer.

Authors:  Yutaka Yonemura; Etsurou Bandou; Kazuo Kinoshita; Taiichi Kawamura; Shigeru Takahashi; Yoshio Endou; Takuma Sasaki
Journal:  Surg Oncol Clin N Am       Date:  2003-07       Impact factor: 3.495

10.  Factors associated with peritoneal metastasis in non-serosa-invasive gastric cancer: a retrospective study of a prospectively-collected database.

Authors:  Baojun Huang; Zhe Sun; Zhenning Wang; Chong Lu; Chengzhong Xing; Bo Zhao; Huimian Xu
Journal:  BMC Cancer       Date:  2013-02-04       Impact factor: 4.430

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  11 in total

1.  Multi-omic profiling of peritoneal metastases in gastric cancer identifies molecular subtypes and therapeutic vulnerabilities.

Authors:  Yosuke Tanaka; Fumiko Chiwaki; Shinya Kojima; Masahito Kawazu; Masayuki Komatsu; Toshihide Ueno; Satoshi Inoue; Shigeki Sekine; Keisuke Matsusaki; Hiromichi Matsushita; Narikazu Boku; Yae Kanai; Yasushi Yatabe; Hiroki Sasaki; Hiroyuki Mano
Journal:  Nat Cancer       Date:  2021-08-16

2.  Copy number profiles of paired primary and metastatic colorectal cancers.

Authors:  Futoshi Kawamata; Ann-Marie Patch; Katia Nones; Catherine Bond; Diane McKeone; Sally-Ann Pearson; Shigenori Homma; Cheng Liu; Lochlan Fennell; Troy Dumenil; Gunter Hartel; Nozomi Kobayasi; Hideki Yokoo; Moto Fukai; Hiroshi Nishihara; Toshiya Kamiyama; Matthew E Burge; Christos S Karapetis; Akinobu Taketomi; Barbara Leggett; Nicola Waddell; Vicki Whitehall
Journal:  Oncotarget       Date:  2017-12-15

Review 3.  A unified model of the hierarchical and stochastic theories of gastric cancer.

Authors:  Yanjing Song; Yao Wang; Chuan Tong; Hongqing Xi; Xudong Zhao; Yi Wang; Lin Chen
Journal:  Br J Cancer       Date:  2017-03-16       Impact factor: 7.640

4.  A novel mutation in nuclear prelamin a recognition factor-like causes diffuse pulmonary arteriovenous malformations.

Authors:  Hong-Zhou Liu; Chun-Xian Du; Jing Luo; Xue-Ping Qiu; Zu-Hua Li; Qi-Yong Lou; Zhan Yin; Fang Zheng
Journal:  Oncotarget       Date:  2017-01-10

5.  Somatic mutations and increased lymphangiogenesis observed in a rare case of intramucosal gastric carcinoma with lymph node metastasis.

Authors:  Naoki Ikari; Shota Aoyama; Akiyoshi Seshimo; Yuji Suehiro; Tomoko Motohashi; Shohei Mitani; Sawako Yoshina; Etsuko Tanji; Akiko Serizawa; Takuji Yamada; Kiyoaki Taniguchi; Masakazu Yamamoto; Toru Furukawa
Journal:  Oncotarget       Date:  2018-01-22

6.  The HER4-YAP1 axis promotes trastuzumab resistance in HER2-positive gastric cancer by inducing epithelial and mesenchymal transition.

Authors:  Jiaolong Shi; Fengping Li; Xingxing Yao; Tingyu Mou; Zhijun Xu; Zheng Han; Siyu Chen; Wende Li; Jiang Yu; Xiaolong Qi; Hao Liu; Guoxin Li
Journal:  Oncogene       Date:  2018-03-14       Impact factor: 9.867

7.  S100A4-MYH9 Axis Promote Migration and Invasion of Gastric Cancer Cells by Inducing TGF-β-Mediated Epithelial-Mesenchymal Transition.

Authors:  Fengping Li; Jiaolong Shi; Zhijun Xu; Xingxing Yao; Tingyu Mou; Jiang Yu; Hao Liu; Guoxin Li
Journal:  J Cancer       Date:  2018-10-05       Impact factor: 4.207

8.  NT5E is associated with unfavorable prognosis and regulates cell proliferation and motility in gastric cancer.

Authors:  Sifeng Hu; Fanmei Meng; Xiankun Yin; Changling Cao; Guangyong Zhang
Journal:  Biosci Rep       Date:  2019-05-17       Impact factor: 3.840

9.  Comprehensive Analysis of CDC27 Related to Peritoneal Metastasis by Whole Exome Sequencing in Gastric Cancer.

Authors:  Riping Wu; Qiaolian Li; Fan Wu; Chunmei Shi; Qiang Chen
Journal:  Onco Targets Ther       Date:  2020-04-21       Impact factor: 4.147

10.  Bcl2l10 induces metabolic alterations in ovarian cancer cells by regulating the TCA cycle enzymes SDHD and IDH1.

Authors:  Su-Yeon Lee; Jinie Kwon; Kyung-Ah Lee
Journal:  Oncol Rep       Date:  2021-03-02       Impact factor: 3.906

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