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<p>Colorectal cancer is driven by complex genetic and molecular alterations, necessitating reliable targets for diagnosis and therapy. Single-omics studies offer limited insight. We performed a systematic in silico multi-omics integration using four public databases: GEO (differential expression), cBioPortal (genomic alterations), DisGeNET (gene–disease associations), and GeneCards (annotated/predicted CRC genes). Genes identified in ≥ 2 independent sources were curated into a high-confidence panel comprising 996 CRC-associated genes. Functional enrichment analysis of this panel revealed significant over-representation of pathways critical to CRC pathogenesis, including cell cycle regulation, apoptosis, DNA repair, and canonical signalling cascades (Wnt, MAPK, PI3K–AKT). PPI network analysis in Cytoscape using the Maximal Clique Centrality algorithm identified ten high-centrality hub genes: <i>AKT1</i>,<i> STAT3</i>,<i> TP53</i>,<i> CTNNB1</i>,<i> BCL2</i>,<i> MYC</i>,<i> CCND1</i>,<i> PTEN</i>,<i> ESR1</i>, and <i>JUN</i>. Eight of these are established CRC drivers, confirming the credibility of the approach, whereas <i>ESR1</i> and <i>JUN</i> emerged as potentially under-investigated candidates. Hub gene relevance was independently confirmed via cBioPortal (alterations and correlations), TCGA/GEPIA2 (tumour–normal and stage-specific expression), the Human Protein Atlas (protein abundance), and TIMER2.0 (immune infiltration). This in silico multi-omics research work prioritises high-confidence therapeutic targets in CRC using publicly available data and nominates <i>ESR1</i> and <i>JUN</i> for further investigation, while highlighting the need for experimental validation. The framework demonstrates the power of cross-platform evidence for biomarker discovery in complex diseases and is readily adaptable to other malignancies.</p>

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Multi-omics integration and network analysis identify therapeutic hub genes in colorectal cancer

  • 期刊论文

  • 发表日期：

    2025年12月19日

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  • Emi Mathew,
  • Philip Litto Thomas,
  • Linu Mathew

摘要

Colorectal cancer is driven by complex genetic and molecular alterations, necessitating reliable targets for diagnosis and therapy. Single-omics studies offer limited insight. We performed a systematic in silico multi-omics integration using four public databases: GEO (differential expression), cBioPortal (genomic alterations), DisGeNET (gene–disease associations), and GeneCards (annotated/predicted CRC genes). Genes identified in ≥ 2 independent sources were curated into a high-confidence panel comprising 996 CRC-associated genes. Functional enrichment analysis of this panel revealed significant over-representation of pathways critical to CRC pathogenesis, including cell cycle regulation, apoptosis, DNA repair, and canonical signalling cascades (Wnt, MAPK, PI3K–AKT). PPI network analysis in Cytoscape using the Maximal Clique Centrality algorithm identified ten high-centrality hub genes: AKT1, STAT3, TP53, CTNNB1, BCL2, MYC, CCND1, PTEN, ESR1, and JUN. Eight of these are established CRC drivers, confirming the credibility of the approach, whereas ESR1 and JUN emerged as potentially under-investigated candidates. Hub gene relevance was independently confirmed via cBioPortal (alterations and correlations), TCGA/GEPIA2 (tumour–normal and stage-specific expression), the Human Protein Atlas (protein abundance), and TIMER2.0 (immune infiltration). This in silico multi-omics research work prioritises high-confidence therapeutic targets in CRC using publicly available data and nominates ESR1 and JUN for further investigation, while highlighting the need for experimental validation. The framework demonstrates the power of cross-platform evidence for biomarker discovery in complex diseases and is readily adaptable to other malignancies.