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Introduction <p>Exosomes influence tumor progression via altered cargo, yet cross-cancer analyses of exosomal protein–metabolite associations remain scarce. We mined ExoCarta to identify cancer-specific exosomal proteins, integrated them with metabolomics data, and mapped them to pathways, revealing a protein–metabolite–pathway axis for understanding cancer metabolic reprogramming.</p> Methods <p>We retrieved exosomal proteins unique to ten cancer types from the ExoCarta database. Hub genes were identified via CytoHubba and their expression was&#xa0;validated through expression datasets such as gene expression profiling interactive analysis (GEPIA), University of ALabama at Birmingham CANcer data analysis Portal (UALCAN), OncoDB, and TNMPlot. Functional enrichment was done using Gene Ontology, Reactome, and CancerHallmarks. Transcription factors were analyzed using Harmonizome. Proteins were mapped to metabolites using Human Metabolome Database (HMDB), Enrichr, and Appyter. Metabolite Set Enrichment Analysis was performed in MetaboAnalyst.</p> Results <p>Enrichment analysis of exosome-associated proteins across cancers revealed distinct biologic processes and molecular functions, including ion transport, protease regulation, and metabolic signaling. Hub genes specific to each cancer include—<i>SLC5A6, ALPP</i> (bladder); <i>LIPG, CEL</i> (colorectal); <i>LYZ</i> (liver); <i>SDHB</i> (pancreatic); <i>PRKD1</i> (prostate); and <i>ATP6V0D1</i> (ovarian) were significantly upregulated in tumors. These genes were enriched in angiogenesis, metastasis, and metabolic reprogramming pathways. Cancer-specific enrichments included lipid metabolism (PRKD1, ATP6V0D1), mitochondrial respiration (SDHB), and amino sugar/fatty acid pathways (LYZ, LIPG, CEL, SLC5A6, ALPP). Metabolite set enrichment linked them to diacylglycerol, phosphate, and ubiquinone metabolism, reinforcing their role in tumor-specific metabolic alterations and highlighting their importance.</p> Conclusion <p>This bioinformatics analysis reveals exosomal proteins as metabolic modulators, warranting further experimental and clinical validation.</p>

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Exosomal proteins in cancer: a bioinformatics approach to metabolic dysregulation and diagnostics

  • 期刊论文

  • 发表日期：

    2025年7月14日

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  • Usha Adiga,
  • Sachidananda Adiga,
  • S. Sriharikrishnaa,
  • Navya Prabhu Basrur,
  • Ganesha Poojary,
  • Alfred J. Augustine,
  • Sampara Vasishta

摘要

Introduction

Exosomes influence tumor progression via altered cargo, yet cross-cancer analyses of exosomal protein–metabolite associations remain scarce. We mined ExoCarta to identify cancer-specific exosomal proteins, integrated them with metabolomics data, and mapped them to pathways, revealing a protein–metabolite–pathway axis for understanding cancer metabolic reprogramming.

Methods

We retrieved exosomal proteins unique to ten cancer types from the ExoCarta database. Hub genes were identified via CytoHubba and their expression was validated through expression datasets such as gene expression profiling interactive analysis (GEPIA), University of ALabama at Birmingham CANcer data analysis Portal (UALCAN), OncoDB, and TNMPlot. Functional enrichment was done using Gene Ontology, Reactome, and CancerHallmarks. Transcription factors were analyzed using Harmonizome. Proteins were mapped to metabolites using Human Metabolome Database (HMDB), Enrichr, and Appyter. Metabolite Set Enrichment Analysis was performed in MetaboAnalyst.

Results

Enrichment analysis of exosome-associated proteins across cancers revealed distinct biologic processes and molecular functions, including ion transport, protease regulation, and metabolic signaling. Hub genes specific to each cancer include—SLC5A6, ALPP (bladder); LIPG, CEL (colorectal); LYZ (liver); SDHB (pancreatic); PRKD1 (prostate); and ATP6V0D1 (ovarian) were significantly upregulated in tumors. These genes were enriched in angiogenesis, metastasis, and metabolic reprogramming pathways. Cancer-specific enrichments included lipid metabolism (PRKD1, ATP6V0D1), mitochondrial respiration (SDHB), and amino sugar/fatty acid pathways (LYZ, LIPG, CEL, SLC5A6, ALPP). Metabolite set enrichment linked them to diacylglycerol, phosphate, and ubiquinone metabolism, reinforcing their role in tumor-specific metabolic alterations and highlighting their importance.

Conclusion

This bioinformatics analysis reveals exosomal proteins as metabolic modulators, warranting further experimental and clinical validation.