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Background <p>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.</p> Methods <p>We integrated CRISPR screening, machine learning (LASSO/Random Forest), and multi-omics data (&gt; 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.</p> Results <p>ATP6V0B was overexpressed in tumors, correlating with larger size, lymph node metastasis, aggressive subtypes (basal-like/HER2-enriched), and poor prognosis (OS/RFS/DMFS, <i>p</i> &lt; 0.001). ATP6V0B<sup>+</sup> 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).</p> Conclusion <p>ATP6V0B is a prognostic biomarker and therapeutic target in breast cancer, driving immune evasion. The nomogram enables individualized prognostic assessment, supporting precision oncology.</p>

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Cross-cohort integrative multi-omics analysis of cancer essential gene ATP6V0B to dissect functional characteristics and clinical implications in breast cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月27日

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  • Jinbao Yin,
  • Binbin Li,
  • Hui Xiong,
  • Hongmei Li,
  • Enping Jiang,
  • Lan Liang

摘要

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.