The epigenetic modifier lysine methyltransferase 2C is frequently mutated in gastric remnant carcinoma.

Gastric remnant carcinoma (GRC), which occurs in the stomach after partial gastrectomy, is a rare and aggressive form of gastric adenocarcinoma (GAC). Comprehensive profiling of genomic mutations in GRC could provide the basis for elucidating the origin and characteristics of this cancer. Herein, whole-exome sequencing (WES) was performed on 36 matched tumor-normal samples from patients with GRC and identified recurrent mutations in epigenetic modifiers, notably KMT2C, ARID1A, NSD1, and KMT2D, in 61.11% of cases. Mutational signature analysis revealed a low frequency of microsatellite instability (MSI) in GRC, which was further identified by MSIsensor, MSI-polymerase chain reaction, and immunohistochemistry analysis. Comparative analysis demonstrated that GRC had a distinct mutation spectrum compared to that of GAC in The Cancer Genome Atlas samples, with a significantly higher mutation rate of KMT2C. Targeted deep sequencing (Target-seq) of an additional 25 paired tumor-normal samples verified the high mutation frequency (48%) of KMT2C in GRC. KMT2C mutations correlated with poor overall survival in both WES and Target-seq cohorts and were independent prognosticators in GRC. In addition, KMT2C mutations were positively correlated with favorable outcomes in immune checkpoint inhibitor-treated pan-cancer patients and associated with higher intratumoral CD3+ , CD8+ tumor-infiltrating lymphocyte counts, and PD-L1 expression in GRC samples (p = 0.018, 0.092, 0.047, 0.010, and 0.034, respectively). Our dataset provides a platform for information and knowledge mining of the genomic characteristics of GRC and helps to frame new therapeutic approaches for this disease.

A 3-MicroRNA Signature Identified From Serum Predicts Clinical Outcome of the Locally Advanced Gastric Cancer.

Background: Current staging systems are inadequate for evaluating the prognosis of patients with locally advanced gastric cancer (LAGC, stages II-III). Therefore, we developed a serum microRNA (miRNA) signature to facilitate individualized management of these patients. Methods: Using microarray analysis, we analyzed 12 serum specimens based on different prognoses (good survival group, n = 7; poor survival group, n = 5). We identified and confirmed differential expression of these miRNAs using quantitative reverse transcription PCR (qRT-PCR) of serum from 51 patients with LAGC. A three miRNA-based classifier was established as a training set by Cox proportional hazard regression and risk-score analysis. We validated the prognostic accuracy of this model in an internal validation cohort (Sun Yat-Sen University Cancer Center, SYSUCC validation cohort, n = 50) and an external independent cohort (Beijing Cancer Hospital, BJCH cohort, n = 67). Results: Three miRNAs were found to be associated with survival of LAGC (P < 0.001 for miR-132, P = 0.011 for miR-548a-3p, and P < 0.001 for miR-1826). A three-miRNA signature was developed for the training set, and a significant difference was found between the survival of low- and high-risk score patients (P < 0.01). The combination of the miRNA signature and tumor-node-metastasis (TNM) stage exhibited superior discrimination. Consistent results were obtained by further validation of the internal set and the BJCH set, which confirmed the predictive value of the model. Conclusions: We built an easy-to-use prognostic signature using three serum miRNAs as markers. Our miRNA signature may improve postoperative risk stratification and serve as a complement to the TNM staging system.

Identification of the distinct genomic features in gastroesophageal junction adenocarcinoma and its Siewert subtypes.

Rates of gastroesophageal junction adenocarcinomas (GEJAs) have shown an alarming increase; however, the genetic background of GEJA and its Siewert classification have yet to be uncovered. Here, 60 paired tumor and normal DNA samples from GEJA patients were analyzed by whole-exome sequencing. Among them, 13 were Siewert type I, 14 were type II, and 33 were type III. A predominance of C/G>T/A substitutions was discovered in GEJA, followed by C/G>A/T substitutions. Notably, Siewert type I and type II/III display distinct sets of driver genes, mutational spectrum, and recurrently disrupted pathways. Siewert type I showed similarity to esophageal adenocarcinomas (EACs) and the chromosomal instability subtype of stomach adenocarcinomas, while Siewert type II/III showed similarity to the genomic stable subtype of stomach adenocarcinoma. We also found that mutation of FBXW7, a driver gene of GEJA, was enriched in Siewert type I. Our data identify differences between GEJA and stomach/EACs at the genomic level and provide evidence for differential treatment based on Siewert classification of GEJA. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.