biostudies-literatureYuan Qthe Haiyan Science Foundationthe China Primary Health Care Foundationthe Wu Jie Ping Medical Foundationthe Intra-Hospital Project of 900TH Hospital of The Joint Logistics Support ForceChina Health & Medical Development Foundation71https://www.ebi.ac.uk/biostudies/studies/S-EPMC12802299biostudies-literatureUnknown24(1)<h4>Background</h4>Breast cancer heterogeneity complicates prognosis and treatment. Metabolic reprogramming, particularly lysine beta-hydroxybutyrylation (Kbhb) driven by ketone bodies, influences the tumor microenvironment. However, the impact of Kbhb on specific breast cancer subpopulations remains unclear. This study aims to identify Kbhb-affected tumor cell subsets and evaluate their prognostic potential.<h4>Methods</h4>We integrated multi-omics data from TCGA, GEO, single-cell RNA sequencing, and spatial transcriptomics. After identifying breast cancer subpopulations influenced by Kbhb-associated genes, we validated the functional role of key genes via molecular experiments. A machine learning-based prognostic model was developed using 101 algorithm combinations.<h4>Results</h4>We ideJournal of translational medicineMachine learning-based identification of kbhb-affected tumor cell subsets as prognostic and therapeutic targets in breast cancer.PMC12802299No. 2023QN08No. cphcf-2023-017No. JJZD2021-02No. chmdf2025-xrkt04-03No. 320.6750.18215Ni LYuan QSha YYe RDeng LHan JYu HfalseMachine learning-based identification of kbhb-affected tumor cell subsets as prognostic and therapeutic targets in breast cancer.<h4>Background</h4>Breast cancer heterogeneity complicates prognosis and treatment. Metabolic reprogramming, particularly lysine beta-hydroxybutyrylation (Kbhb) driven by ketone bodies, influences the tumor microenvironment. However, the impact of Kbhb on specific breast cancer subpopulations remains unclear. This study aims to identify Kbhb-affected tumor cell subsets and evaluate their prognostic potential.<h4>Methods</h4>We integrated multi-omics data from TCGA, GEO, single-cell RNA sequencing, and spatial transcriptomics. After identifying breast cancer subpopulations influenced by Kbhb-associated genes, we validated the functional role of key genes via molecular experiments. A machine learning-based prognostic model was developed using 101 algorithm combinations.<h4>Results</h4>We ide2025-01-01T00:00:00Z2025 Dec2026-06-11T04:58:16.197Z2026-06-11T03:08:24.304ZS-EPMC128022994138208410.1186/s12967-025-07555-3