Aug 2026· Frontiers in Genetics· Vol 17· 0 citations· 43 references
Medicine
TL;DR
The integrated analyses identify an MG-associated prognostic framework and prioritize CCNA2 for further validation in LUAD, providing novel clinical actionable target for LUAD patients.
Abstract
Background Lung adenocarcinoma (LUAD) remains a leading cause of cancer mortality, with metabolic reprogramming, particularly dysregulated mitochondrial transport and glycolysis (MG), emerging as a hallmark of its progression. Despite the recognized importance of these pathways, an integrated, clinically actionable model that combines them for patient stratification and therapeutic targeting is lacking. Objective This study aims to decode integrated MG-associated molecular patterns in the progression of LUAD, providing novel clinical actionable target for LUAD patients. Methods GSVA and WGCNA were applied to an integrated GEO cohort to identify MG-associated genes. LASSO-Cox and multivariable Cox analyses were used to construct and validate a prognostic model and prioritize CCNA2 as a prognostic candidate. Single-cell, spatial, cell-based, drug-sensitivity, and xenograft analyses were used for validation. Results The MG-associated signature stratified overall survival, and CCNA2 was enriched in malignant cells. CCNA2 knockdown reduced A549 proliferation, wound closure, and invasion. GSCA analysis identified BHG712, IPA-3, and KIN001-260 as candidate compounds, and IPA-3 produced the largest reduction in xenograft tumor burden. Conclusion The integrated analyses identify an MG-associated prognostic framework and prioritize CCNA2 for further validation in LUAD.
Objective Lung adenocarcinoma (LUAD) is a highly aggressive malignancy originating from the bronchial epithelium or glandular tissues and represents the most rapidly increasing subtype of lung cancer worldwide. Its high incidence and mortality rates contribute to an overall unfavorable prognosis. Therapeutic options fo...
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