Molecular subtype of gastric cancer based on apoptosis-related genes reveals differential immune microenvironment and intratumoral microorganisms distribution.

Abstract

Background: Gastric cancer (GC) is known for its high heterogeneity, presenting challenges in current clinical treatment strategies. Accurate subtyping and in-depth analysis of the molecular heterogeneity of GC at the molecular level are still not fully understood.

Methods: This study categorized GC into two subtypes based on apoptosis-related genes (ARGs) and investigated differences in tumor immune microenvironment, intratumoral microorganisms distribution, gene expression, and signaling pathways. Key prognostic genes related to apoptosis in GC were identified through random survival forest analysis, and their specific signaling mechanisms were explored. Expression levels of key genes were validated through PCR in paired GC tissues and cancer cell lines. Moreover, biological functions of these key genes were verified in vitro experiments.

Results: A consistent clustering of GC was conducted using 161 apoptosis-related genes (ARGs), resulting in the identification of two subtypes, C1 and C2. Subsequently, significant differences were found in the tumor immune microenvironment, intratumoral microorganisms, gene expression, signaling pathways, and protein interaction networks between the two subtypes. GPX3, PLAT, and CAV1 were identified as key prognostic genes related to apoptosis in GC, with a focus on their impact on disease progression-related pathways. Furthermore, PCR assays validated that these three key genes exhibited significantly low expression levels in both GC cell lines and tissues. Finally, knocking down key genes expression significantly promoted cell proliferation, colony formation and invasion of GC.

Conclusions: Our study conducted a comprehensive analysis of the molecular characteristics of ARGs in GC, revealed their association with the tumor immune microenvironment and intratumoral microorganisms. These findings provide new ideas for the molecular classification of GC.