SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses

TL;DR

This study identifies SUMOylation-related genes that define prognostic subtypes in stomach cancer, using machine learning and single-cell analysis to improve risk stratification and treatment strategies.

Contribution

The study introduces a SUMOylation Risk Score model and identifies novel SUMOylation-related genes with prognostic and immunological significance in stomach adenocarcinoma.

Findings

Two molecular subtypes with distinct survival and immune profiles were identified based on SUMOylation patterns.

The SRS model achieved high accuracy (AUC: 0.97) in predicting patient risk and correlating with tumor stage and immune suppression.

L3MBTL2 and VHL were validated as key genes influencing cancer cell proliferation and invasion.

Abstract

Stomach adenocarcinoma (STAD) exhibits high molecular heterogeneity and poor prognosis, necessitating robust biomarkers for risk stratification. While SUMOylation, a post-translational modification, regulates tumor progression, its prognostic and immunological roles in STAD remain underexplored.

Prognostic SUMOylation-related genes (SRGs) were screened via univariate Cox regression, and patients were stratified into molecular subtypes using unsupervised consensus clustering. A SUMOylation Risk Score (SRS) model was developed using 69 machine learning models across 10 algorithms, with performance evaluated by C-index and AUC. Immune infiltration, pathway enrichment identified key SRGs, and in vitro functional assays were validated.

Two molecular subtypes (A/B) with distinct SUMOylation patterns, survival outcomes (log-rank p < 0.001), and immune microenvironments were identified. The random survival forest (RSF)-based SRS model (AUC: 0.97) stratified patients into high-/low-risk groups, where high-risk patients exhibited advanced tumor stages, immune suppression, and elevated TIDE scores (p < 0.001). Functional enrichment linked low-risk groups to genome stability pathways (DNA repair, cell cycle control). In vitro validation confirmed that L3MBTL2 and VHL knockdown promoted proliferation, migration, and invasion in AGS cells (p < 0.05).

This study establishes SRGs as independent prognostic indicators and defines SUMOylation-driven subtypes with distinct immune and molecular features. The SRS model and functional validation of L3MBTL2/VHL provide actionable insights for personalized STAD management and immunotherapy targeting. (214 words)

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