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Background <p>Gastric cancer (GC) remains a lethal malignancy with high heterogeneity and poor prognosis. Crotonylation, a key post-translational modification, contributes significantly to oncogenic processes and immune system interactions; however, its prognostic significance in gastric cancer is not fully understood.</p> Methods <p>We integrated single-cell RNA sequencing and bulk transcriptomics to evaluate cell-specific crotonylation activity and utilized WGCNA to identify core crotonylation-related gene modules. A machine learning-derived crotonylation-related prognostic signature (CRGS) was established and validated across independent cohorts. Functional enrichment, immune infiltration, and immunotherapy response analyses were conducted. Furthermore, the expression and oncogenic roles of a key risk gene, TIMP1, were experimentally validated using qRT-PCR, colony formation, and Transwell migration/invasion assays.</p> Results <p>Single-cell analysis revealed significantly elevated crotonylation activity in epithelial cells. The machine learning-derived CRGS successfully stratified patients into distinct risk groups, with high-risk patients showing a severe survival disadvantage. The nomogram integrating the CRGS and clinical factors demonstrated robust prognostic accuracy. Functional analysis indicated that high-risk patients were enriched in tumor-promoting pathways, while low-risk patients exhibited enhanced immune infiltration and metabolic homeostasis. The low-risk group also exhibited elevated tumor mutational burden, stronger cancer-immunity cycle activity, and better predicted response to immune checkpoint inhibitors. Experimental validation confirmed that TIMP1 was heavily upregulated in GC cell lines. Silencing TIMP1 significantly suppressed GC cell proliferation, colony formation, migration, and invasion.</p> Conclusions <p>Our study establishes a reliable, clinically translatable CRGS for risk stratification and immunotherapy prediction, while identifying TIMP1 as a potential therapeutic target and a key oncogenic factor in vitro in GC.</p>

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Characterization of the crotonylation landscape in gastric cancer: a machine learning-derived prognostic signature and the oncogenic role of TIMP1

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月28日

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  • Ji Gao,
  • Yuefeng Zhang,
  • Min Zhou,
  • Xiaoli Tian

摘要

Background

Gastric cancer (GC) remains a lethal malignancy with high heterogeneity and poor prognosis. Crotonylation, a key post-translational modification, contributes significantly to oncogenic processes and immune system interactions; however, its prognostic significance in gastric cancer is not fully understood.

Methods

We integrated single-cell RNA sequencing and bulk transcriptomics to evaluate cell-specific crotonylation activity and utilized WGCNA to identify core crotonylation-related gene modules. A machine learning-derived crotonylation-related prognostic signature (CRGS) was established and validated across independent cohorts. Functional enrichment, immune infiltration, and immunotherapy response analyses were conducted. Furthermore, the expression and oncogenic roles of a key risk gene, TIMP1, were experimentally validated using qRT-PCR, colony formation, and Transwell migration/invasion assays.

Results

Single-cell analysis revealed significantly elevated crotonylation activity in epithelial cells. The machine learning-derived CRGS successfully stratified patients into distinct risk groups, with high-risk patients showing a severe survival disadvantage. The nomogram integrating the CRGS and clinical factors demonstrated robust prognostic accuracy. Functional analysis indicated that high-risk patients were enriched in tumor-promoting pathways, while low-risk patients exhibited enhanced immune infiltration and metabolic homeostasis. The low-risk group also exhibited elevated tumor mutational burden, stronger cancer-immunity cycle activity, and better predicted response to immune checkpoint inhibitors. Experimental validation confirmed that TIMP1 was heavily upregulated in GC cell lines. Silencing TIMP1 significantly suppressed GC cell proliferation, colony formation, migration, and invasion.

Conclusions

Our study establishes a reliable, clinically translatable CRGS for risk stratification and immunotherapy prediction, while identifying TIMP1 as a potential therapeutic target and a key oncogenic factor in vitro in GC.