Multi-omics pan-cancer analysis reveals heterogeneous BCAA metabolism and its impact on the tumor immune microenvironment and prognosis

BACKGROUND: Reprogramming of branched-chain amino acid (BCAA) metabolism is a metabolic hallmark of cancer that fuels tumor progression. However, a comprehensive understanding of its pan-cancer heterogeneity and its crosstalk with the tumor immune microenvironment (TIME) remains elusive. METHODS: We performed an integrated multi-omics analysis of 33 cancer types from TCGA. Eighteen core BCAA metabolic genes were curated. Their genetic alterations, transcriptional regulation, and heterogeneous expression patterns across cellular subpopulations were systematically characterized using bulk, single-cell RNA-seq, and epigenomic data. A BCAA activity score was quantified via ssGSEA. Cancer-specific prognostic models were constructed using a rigorous penalty-optimized LASSO-Cox regression framework coupled with cross-validation strategy to effectively minimize overfitting. RESULTS: Comprehensive landscape analysis revealed extensive heterogeneity in the expression and regulation of BCAA metabolic genes between tumors and normal tissues across multiple cancer types. At single-cell resolution, these genes displayed distinct cell-type-specific expression profiles within epithelial, myeloid, and T cell lineages, strictly dependent on tissue context (normal, adjacent, or tumor). High BCAA scores were fundamentally associated with the inhibition of epithelial-mesenchymal transition and apoptosis. Notably, the high BCAA phenotype strongly correlated with an immunosuppressive TIME, marked by M2 macrophage enrichment, restricted CD8 + T cell infiltration, and elevated expression of key immune checkpoints (e.g., PDCD1, CTLA4, LAG3). Based on these core genes, robust cancer-specific prognostic signatures were developed and validated for 23 malignancies. Patients stratified into the high-risk group exhibited enhanced genomic instability, augmented proliferative signaling, and inferior clinical outcomes following immunotherapy. Furthermore, 13 potential therapeutic targets (including AURKB and PLK1) were prioritized, alongside the prediction of therapeutic agents with highly specific sensitivity profiles. CONCLUSION: This study successfully maps the pan-cancer landscape of BCAA metabolic heterogeneity, highlighting its instrumental role in remodeling the TIME and promoting tumor progression. The validated BCAA-derived prognostic signature represents a reliable biomarker for patient risk stratification and the rational guidance of immunotherapeutic interventions. Collectively, these insights into the intersection of metabolic reprogramming and microenvironmental immunity offer a conceptual framework for developing innovative, metabolism-targeted immunotherapeutic paradigms.

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Publication Details

Journal
Discover Oncology
Published
2026-07-02
DOI
https://doi.org/10.1007/s12672-026-05527-7
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
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article

Multi-omics pan-cancer analysis reveals heterogeneous BCAA metabolism and its impact on the tumor immune microenvironment and prognosis

Jinqin Qian, Fang Wang, Liqun Zhou, Qian Zhou
Discover Oncology
Cancer Immunotherapy and Biomarkers
article

Multi-omics pan-cancer analysis reveals heterogeneous BCAA metabolism and its impact on the tumor immune microenvironment and prognosis

Jinqin Qian, Fang Wang, Liqun Zhou, Qian Zhou
article en

Abstract

BACKGROUND: Reprogramming of branched-chain amino acid (BCAA) metabolism is a metabolic hallmark of cancer that fuels tumor progression. However, a comprehensive understanding of its pan-cancer heterogeneity and its crosstalk with the tumor immune microenvironment (TIME) remains elusive. METHODS: We performed an integrated multi-omics analysis of 33 cancer types from TCGA. Eighteen core BCAA metabolic genes were curated. Their genetic alterations, transcriptional regulation, and heterogeneous expression patterns across cellular subpopulations were systematically characterized using bulk, single-cell RNA-seq, and epigenomic data. A BCAA activity score was quantified via ssGSEA. Cancer-specific prognostic models were constructed using a rigorous penalty-optimized LASSO-Cox regression framework coupled with cross-validation strategy to effectively minimize overfitting. RESULTS: Comprehensive landscape analysis revealed extensive heterogeneity in the expression and regulation of BCAA metabolic genes between tumors and normal tissues across multiple cancer types. At single-cell resolution, these genes displayed distinct cell-type-specific expression profiles within epithelial, myeloid, and T cell lineages, strictly dependent on tissue context (normal, adjacent, or tumor). High BCAA scores were fundamentally associated with the inhibition of epithelial-mesenchymal transition and apoptosis. Notably, the high BCAA phenotype strongly correlated with an immunosuppressive TIME, marked by M2 macrophage enrichment, restricted CD8 + T cell infiltration, and elevated expression of key immune checkpoints (e.g., PDCD1, CTLA4, LAG3). Based on these core genes, robust cancer-specific prognostic signatures were developed and validated for 23 malignancies. Patients stratified into the high-risk group exhibited enhanced genomic instability, augmented proliferative signaling, and inferior clinical outcomes following immunotherapy. Furthermore, 13 potential therapeutic targets (including AURKB and PLK1) were prioritized, alongside the prediction of therapeutic agents with highly specific sensitivity profiles. CONCLUSION: This study successfully maps the pan-cancer landscape of BCAA metabolic heterogeneity, highlighting its instrumental role in remodeling the TIME and promoting tumor progression. The validated BCAA-derived prognostic signature represents a reliable biomarker for patient risk stratification and the rational guidance of immunotherapeutic interventions. Collectively, these insights into the intersection of metabolic reprogramming and microenvironmental immunity offer a conceptual framework for developing innovative, metabolism-targeted immunotherapeutic paradigms.

Discover Oncology
Peking University (CN), Southern University of Science and Technology (CN), Peking University First Hospital (CN), Shenzhen University Health Science Center (CN)
Zero hunger
Openalex Percentile: Top 9%
Cancer Immunotherapy and Biomarkers
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