ArticleJournal of translational medicine2024
Architecting the metabolic reprogramming survival risk framework in LUAD through single-cell landscape analysis: three-stage ensemble learning with genetic algorithm optimization.
Article in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 19 citations in OpenAlex.
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- A machine learning-derived biological age model for liver grafts provides a superior assessment of aging compared to chronological age in transplantation.Scientific reports · 2026Article
- A Single-Cell Transcriptomic Atlas Elucidates a Microglial Gene Signature Linking Ferroptosis to Mitochondrial Dysfunction in Epilepsy.Journal of inflammation research · 2026Article
- Multi-omics comprehensive analysis identified KIF22 and KRAS as highly synthetic lethal pairs for triple-negative breast cancer.Frontiers in oncology · 2026Article
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- Targeting SPATS2 in lung adenocarcinoma: implications for prognosis and immune-based therapy.Discover oncology · 2025Article
- Integrative analysis based on CRISPR screen identifies apilimod as a potential therapeutic agent for cisplatin-induced acute kidney injury treatment.Science China. Life sciences · 2025Article
- Multi-omics dissection of fatty acid metabolism heterogeneity identifies PRDX1 as a prognostic marker in bladder cancer.Frontiers in immunology · 2025Article
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- Malignant epithelial cell marker-driven risk signature enables precise stratification in esophageal cancer.Frontiers in immunology · 2025Article
- Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC.Frontiers in immunology · 2025Article
- Toward precision oncology in LUAD: a prognostic model using single-cell sequencing and WGCNA based on a disulfidptosis relative gene signature.Frontiers in immunology · 2025Article
- An ensemble model for predicting dyslipidemia using 3-years continuous physical examination data.Frontiers in physiology · 2024Article
- Cancer metabolic reprogramming and precision medicine-current perspective.Frontiers in pharmacology · 2024Review
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Recent studies have increasingly revealed the connection between metabolic reprogramming and tumor progression. However, the specific impact of metabolic reprogramming on inter-patient heterogeneity and prognosis in lung adenocarcinoma (LUAD) still requires further exploration. Here, we introduced a cellular hierarchy framework according to a malignant and metabolic gene set, named malignant & metabolism reprogramming (MMR), to reanalyze 178,739 single-cell reference profiles. Furthermore, we proposed a three-stage ensemble learning pipeline, aided by genetic algorithm (GA), for survival prediction across 9 LUAD cohorts (n = 2066). Throughout the pipeline of developing the three stage-MMR (3 S-MMR) score, double training sets were implemented to avoid over-fitting; the gene-pairing method was utilized to remove batch effect; GA was harnessed to pinpoint the optimal basic learner combination. The novel 3 S-MMR score reflects various aspects of LUAD biology, provides new insights into precision medicine for patients, and may serve as a generalizable predictor of prognosis and immunotherapy response. To facilitate the clinical adoption of the 3 S-MMR score, we developed an easy-to-use web tool for risk scoring as well as therapy stratification in LUAD patients. In summary, we have proposed and validated an ensemble learning model pipeline within the framework of metabolic reprogramming, offering potential insights for LUAD treatment and an effective approach for developing prognostic models for other diseases.
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