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Background <p>Bimodal protein expression, defined as the distribution of protein expression with two modes, is linked to phenotypic variation across various biological systems. To advance the identification of cancer biomarkers and targets for precision oncology beyond RNA-based studies, we developed a proteomics-specific bimodality model.</p> Results <p>By analyzing proteomics data from various cancer types, 2401 tumor-associated bimodal proteins significantly linked to critical cancer pathways were identified, including amino acid metabolism, extracellular matrix-receptor interaction, and central carbon metabolism. Utilizing an AI-enhanced knowledge graph, we further delineated common patterns among pan-cancer tumor-associated bimodal proteins. A case study on <i>TROP2</i> in colon adenocarcinoma highlights up-regulation of <i>MYC</i> and <i>WNT</i>/β-catenin pathways and down-regulation of inflammatory pathways in <i>TROP2</i>-high groups.</p> Conclusion <p>This research highlights the biological differences impacting cancer heterogeneity and vulnerability, ultimately aiding treatment decisions. Our findings illustrate the value of proteomics in uncovering novel biomarkers and advancing precision medicine, paving the way for multi-omics integration and clinical validation.</p>

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Bimodality in pan-cancer proteomics reveals new opportunities for biomarker discovery

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月9日

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  • Wen Jiang,
  • Damian Bikiel,
  • Jan Zaucha,
  • Jixin Wang,
  • Sanddhya Jayabalan,
  • Yongjin Li,
  • Matthew Sung,
  • James Harper,
  • Jimmy Zhao,
  • Krishna Bulusu,
  • Wenyan Zhong

摘要

Background

Bimodal protein expression, defined as the distribution of protein expression with two modes, is linked to phenotypic variation across various biological systems. To advance the identification of cancer biomarkers and targets for precision oncology beyond RNA-based studies, we developed a proteomics-specific bimodality model.

Results

By analyzing proteomics data from various cancer types, 2401 tumor-associated bimodal proteins significantly linked to critical cancer pathways were identified, including amino acid metabolism, extracellular matrix-receptor interaction, and central carbon metabolism. Utilizing an AI-enhanced knowledge graph, we further delineated common patterns among pan-cancer tumor-associated bimodal proteins. A case study on TROP2 in colon adenocarcinoma highlights up-regulation of MYC and WNT/β-catenin pathways and down-regulation of inflammatory pathways in TROP2-high groups.

Conclusion

This research highlights the biological differences impacting cancer heterogeneity and vulnerability, ultimately aiding treatment decisions. Our findings illustrate the value of proteomics in uncovering novel biomarkers and advancing precision medicine, paving the way for multi-omics integration and clinical validation.