ArticleJournal of thoracic disease2026
Integrated hypoxia and metabolic gene signature to predict clinical outcomes and therapeutic vulnerabilities in lung adenocarcinoma.
Article in Journal of thoracic disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Background: Immune checkpoint inhibitors (ICIs) have transformed the therapeutic landscape of advanced non-small cell lung cancer (NSCLC), yet ~50% of lung adenocarcinoma (LUAD) patients exhibit primary or acquired resistance, underscoring the urgent need for predictive biomarkers. Hypoxia and metabolic reprogramming (HMR) are intertwined oncogenic hallmarks that reshape the tumor microenvironment (TME) and drive immune evasion, representing promising targets for signature development. Herein, we constructed an integrated HMR gene signature to predict clinical outcomes and therapeutic vulnerabilities in LUAD. Methods: Transcriptomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed. Hypoxia and energy metabolism pathways were scored via single-sample gene set enrichment analysis (ssGSEA), and subtypes were stratified. A 9-gene prognostic model was constructed using least absolute shrinkage and selection operator (LASSO) regression and validated across cohorts. Single-cell RNA (scRNA) data and in-house experimental validation explored associations between gene expression, immune microenvironment, and treatment outcomes. Results: We developed a 9-gene HMR signature ( Conclusions: Overall, our integrated HMR signature exhibits robust prognostic and predictive value, unravels TME-driven ICI resistance mechanisms, and identifies subtype-specific therapeutic vulnerabilities. This tool has potential for clinical application, as it links HMR to clinical outcomes and provides novel insights to guide precision treatment strategies for LUAD patients.
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