Comprehensive analysis of T-cell regulatory factors and tumor immune microenvironment in stomach adenocarcinoma

Abstract

Background Gastric cancer (GC) is one of the most prevalent malignant tumors worldwide and is associated with high morbidity and mortality rates. However, the specific biomarkers used to predict the postoperative prognosis of patients with gastric cancer remain unknown. Recent research has shown that the tumor microenvironment (TME) has an increasingly positive effect on anti-tumor activity. This study aims to build signatures to study the effect of certain genes on gastric cancer. Methods Expression profiles of 37 T cell-related genes and their TME characteristics were comprehensively analyzed. A risk signature was constructed and validated based on the screened T cell-related genes, and the roles of hub genes in GC were experimentally validated. Results A novel T cell-related gene signature was constructed based on CD5, ABCA8, SERPINE2, ESM1, SERPINA5, and NMU. The high-risk group indicated lower overall survival (OS), poorer immune efficacy, and higher drug resistance, with SERPINE2 promoting GC cell proliferation, according to experiments. SERPINE2 and CXCL12 were significantly correlated, indicating poor OS via the Youjiang cohort. Conclusions This study identified T cell-related genes in patients with stomach adenocarcinoma (STAD) for prognosis estimation and proposed potential immunotherapeutic targets for STAD.

Predictive Factors of Immunotherapy in Gastric Cancer: A 2024 Update

“…With SERPINE2 boosting GC cell proliferation, the high-risk group exhibited decreased overall survival (OS), decreased immunological efficacy, and increased treatment resistance. These T-cell-related genes have been suggested as prospective targets for immunotherapy in patients with STAD and can aid in prognosis estimation [ 41 ].…”

“…--STK40 is the most important gene linked to senescence that influences the development of GC [27] -CS might represent the therapeutic impact of immunotherapy [28] -MFAP2+ CAFs create an immune-evading TME with immune effector cells that are debilitated [29] the immunotherapy characteristics of the TME were strongly correlated with two genes (MSH4 and RPL22L1) and four methylation probes (EPM2AIP1|MLH1:cg27331401, LNP1:cg05428436, and TSC22D2:cg15048832) [30] a lncRNA signature model associated with DNA methylation regulators is a novel method for predicting the treatment response and stratification of patients with GC [31] -N6-methyladenosine (m6A) regulator-mediated genes in the glycolytic pathway predict the prognosis and immunotherapy response of GC patients [32] the adenosine pathway-based signature is a potentially useful risk stratification tool that might inform personalized prognostication and immunotherapy for GC patients [33] the TIDE score and the IPS indicate that decreased immunotherapy benefit is associated with elevated expression of CHSY3 [34] -FIRGs have significant therapeutic and predictive potential for GC and have a role in the onset and progression of the disease [35] -TGF-beta, TP53, and NRF2 pathways dominated the high-risk group, whereas the LRTK-RAS and WNT pathways represented the low-risk group [36] the Anoikis-related lncRNA genes predictive model has been shown to have high predictive accuracy and may be used as a guide for prognostic evaluation and clinical treatment of patients with STAD [37] five methylation-related genes, namely, CHAF1A, CPNE8, PHLDA3, SPARC, and EHF were found to potentially be significant for patient prognosis [38] -Hedgehog signaling, a highly conserved system that controls cell division and growth, is crucial in the development of STAD [39] -SPP1 has been identified as a stand-alone predictor of STAD prognosis and may control the disease course [40] the T-cell-related genes CD5, ABCA8, SERPINE2, ESM1, SERPINA5, and NMU have been suggested as prospective targets for immunotherapy in patients with STAD and can aid in prognosis estimation [41] -ICB treatment for EBVaGC may be better guided by the identification of SMARCA4, TMB, and CTLA-4 mutations as possible predictive markers of ICB success [42] Table 3. Major developments in immunological predictive factors research.…”

“…These T-cell-related genes have been suggested as prospective targets for immunotherapy in patients with STAD and can aid in prognosis estimation [41].…”