# 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.

## Key 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)