Gastric carcinoma (GC) is a high heterogeneity and malignant tumor originating from the stomach. This particular cancer ranks as the fifth most frequently diagnosed form of cancer and claims the position of the third highest cause of cancer-related deaths worldwide in 2020 [1]. The incidence rate and mortality of gastric cancer in China account for 43.9% and 48.5% of the world, respectively, and the 5-year overall survival rate is only 27.4% at present [2]. Patients with GC had a poor prognosis due to ineffective therapies and multiple resistance [3].

Genomics with next-generation sequencing has been used to identify diagnostic and prognostic markers and new therapeutic targets for GC. Several studies performed whole-exome sequencing (WES) on 690 Japanese cases [4], [5], 55 Korean cases [6], 15 Caucasian cases, 33 Vietnamese cases [7], 78 Chinese [8], and 442 multiancestry cases [9]. The cancer genome atlas (TCGA) and the Asian cancer research group used WES and whole-genome sequencing (WGS) on multiancestry cases and classify GC into four molecular subtypes, including Epstein-Barr virus, microsatellite instability (MSI), genomically stable, and chromosomal instability [9], [10]. The study by Totoki et al., including 603 Japanese cases, 442 multiancestry cases from TCGA, and 318 case from East Asian cohorts described the molecular landscape across various ancestries and identified 77 significantly mutated genes (e.g., ARHGAP5 and TRIM49C) [4]. Kakiuchi et al., Liu et al., Park et al., and Chen et al. performed WES on Chinese, Korean, and Vietnamese cases and provides potential therapies and prognosis markers [5], [6], [7], [8], [11]. Especially for the worst prognosis subtype of diffuse-type gastric cancer, Kakiuchi et al. identified a potential therapeutic target [5]. Chen et al. found two distinct GC subtypes with either high-clonality or low-clonality in Chinese cases [8]. In addition, an increasing number of studies have shown that genome alteration detected through WES and WGS plays a key role in predicting the response of targeted therapy and immunotherapy. Patients harboring TP53, LRP1B, FAT4, and RNF43 mutations are mainly manifested as immune rejection [12], [13], [14]. ARID1A mutation is a biomarker for immune checkpoint blockade therapy [15] and is associated with increased immune activity in GC [16]. Mutations in the PI3K-AKT-mTOR pathway can affect immune cell infiltration in mismatch repair-deficient (dMMR)/microsatellite instability-high (MSI-H) gastric adenocarcinoma [17]. As a pan-cancer marker, alterations in PARP1 are significantly associated with higher immune infiltration in various tumors, including CD8+ T cells in gastric cancer [18]. Tumor mutation burden (TMB) and MSI have been recommended by the NCCN Gastric Cancer Guidelines (2022) as biomarkers for predicting the efficacy of immunotherapy. PIK3CA, KRAS, and ARID1A mutations are associated with MSI status [19], [20], [21], [22]. The link between TP53, MUC4, MUC16, TTN, and TMB is strongly supported by Li et al. and Yang et al. [23], [24]. However, given GC's high heterogeneity and complexity, the studies on immuno-related gene mutations in GC are insufficient.

Moreover, early clonal events can be identified as promising therapeutic targets for tumorigenesis, providing clues to etiology and cell-intrinsic mechanisms. The pathogenesis of GC is highly complex, encompassing factors that regulate apoptosis, the modules of HER2 expression, cell cycle regulators, factors that influence cell membrane properties, multidrug resistance proteins, and MSI [25]. The poorly defined, undetectable, or difficult-to-biopsy premalignant lesions have made the genetic progression of GC remain speculative [26]. A few studies described somatic mutations occurring in the early stage of GC. Only Yoshida et al. and Sahgal et al. found that mutations of TP53, APC, and CTNNB1 and amplification of ERBB2 were found frequently in early GC [27], [28]. Therefore, further research is warranted to investigate the early somatic mutations in GC.

We performed WES on the tumor and matched normal samples collected from 40 patients with GC to explore the order of genetic events and the immuno-related genes.