What question did this study set out to answer?

The aim is to develop a mitotic catastrophe-related gene signature that predicts prognosis and therapeutic responses in lung adenocarcinoma.

May 20, 2026BMC Medical Genomics0 citationsOpen Access

Mitotic catastrophe–related six-gene signature predicts prognosis, tumor immune landscape, and therapeutic response in lung adenocarcinoma

MLMinghao Luo GZGuoqing Zhu ZWZhong Weiquan

Key Points

The aim is to develop a mitotic catastrophe-related gene signature that predicts prognosis and therapeutic responses in lung adenocarcinoma.
Utilized datasets from TCGA and GEO databases to identify differentially expressed MCRGs.
Constructed a six-gene RiskScore model using LASSO-Cox and multivariate Cox regression analyses.
Analyzed immune microenvironment and drug sensitivity through ESTIMATE, MCPcounter, and TIDE.
Identified 2,290 upregulated and 1,959 downregulated genes with 266 overlapping MCRGs.
Developed a six-gene model that effectively stratified overall survival (OS) and disease-specific survival (DSS) in TCGA and validated in GSE31210.
High-risk tumors showed lower immune scores and impaired immune checkpoint inhibition response, correlating with various drug IC50 values.

Abstract

Lung adenocarcinoma (LUAD) exhibits significant molecular and immune heterogeneity, limiting the prognostic and therapeutic value of single biomarkers. Mitotic catastrophe (MC) is a key biological axis, but externally validated MC-related gene (MCRG) signatures integrating immune and pharmacologic annotations remain lacking. We obtained datasets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed genes overlapping with mitotic catastrophe–related genes (MCRGs) were screened. GSVA-derived MCRG scores guided WGCNA to identify associated modules; after KEGG/GO-BP enrichment and mutation analysis, a six-gene RiskScore model was constructed via LASSO-Cox and multivariate Cox regression. Immune microenvironment was analyzed by ESTIMATE and MCPcounter; ICI responsiveness by TIDE; drug sensitivity by pRRophetic. Wet-lab validation included qPCR, CCK-8, and siRNA-mediated GNPNAT1 knockdown assays. A total of 2,290 upregulated and 1,959 downregulated genes were identified, with 266 overlapping MCRGs. The turquoise module showed the highest correlation with MCRG scores, and 940 overlapping genes were enriched in pathways like p53 signaling. The six-gene model (GNPNAT1, etc.) effectively stratified OS, PFI, and DSS in TCGA and was validated in GSE31210. High-risk tumors had lower immune scores, depleted key immune lineages, poor ICI response, and correlated with various drug IC50 values. Wet-lab assays confirmed abnormal expression of target genes in LUAD cells, and GNPNAT1 silencing inhibited proliferation, migration, and invasion. The MC-related molecular axis integrates tumor proliferation-metabolism-immunity networks, providing actionable guidance for perioperative and translational therapeutic stratification. We proposed an MC-anchored six-gene signature integrating prognostic, immune, and therapeutic dimensions in LUAD. This exploratory study has biological plausibility, but prospective multi-center studies are required before clinical application.

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