Cross-cohort integrative multi-omics analysis of cancer essential gene ATP6V0B to dissect functional characteristics and clinical implications in breast cancer
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Breast cancer remains a leading cause of cancer-related mortality in women, with recurrence, metastasis, and therapeutic resistance limiting outcomes. The role of vacuolar ATPase subunit ATP6V0B in breast cancer pathogenesis and immune regulation is poorly understood. METHODS: We integrated CRISPR screening, machine learning (LASSO/Random Forest), and multi-omics data (> 10,000 samples) to identify ATP6V0B as a cancer essential gene. Single-cell transcriptomics and ligand-receptor network analysis dissected its TME regulatory role. Prognostic modeling (Cox regression/nomogram) was validated across cohorts. RESULTS: ATP6V0B was overexpressed in tumors, correlating with larger size, lymph node metastasis, aggressive subtypes (basal-like/HER2-enriched), and poor prognosis (OS/RFS/DMFS, p < 0.001). ATP6V0B+ tumor subsets are associated with immunosuppression via VEGFA-VEGFR2/THBS1-CD47, correlating with MDSC infiltration and immunotherapy resistance. A nomogram integrating ATP6V0B-related signature, stage, and age improved prognostic accuracy (1/3/5-year OS AUC 0.78/0.74/0.72). CONCLUSION: ATP6V0B is a prognostic biomarker and therapeutic target in breast cancer, driving immune evasion. The nomogram enables individualized prognostic assessment, supporting precision oncology.
Authors: Jinbao Yin, Binbin Li, Hui Xiong, Hongmei Li, Enping Jiang, Lan Liang
Institution: Guangdong Medical College
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,990
OpenAlex ID: W4416734149