Integrated Transcriptomics-Proteomics Analysis Identifies Molecular Phenotypic Alterations Associated with Colorectal...

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Colorectal cancer (CRC) diagnosis and treatment rely on understanding its pathogenesis and identifying diagnostic markers.
• Integrated transcriptomics and proteomics offer a powerful approach to characterize molecular alterations and uncover the pathogenesis of CRC.

Purpose of the Study:

• To identify pathological molecular pathways and diagnostic biomarkers for colorectal cancer (CRC).
• To employ a novel strategy integrating transcriptomics and proteomics for biomarker discovery in CRC.

Main Methods:

• Weighted gene coexpression network analysis (WGCNA) was used to identify differentially expressed proteins and coexpressed genes, intersecting them to find key CRC phenotype genes.
• Pathway enrichment analysis and protein-protein interaction analysis were performed on key genes to identify central genes and understand their roles in CRC-associated metabolic pathways.
• Statistical analysis combining transcriptomics and proteomics data was applied to screen for diagnostic biomarkers.

Main Results:

• Sixty-three key genes associated with the CRC phenotype were identified.
• Pathway enrichment analysis indicated significant roles for coagulation and peptidase regulator activity in CRC development.
• The genes Itih3 and Lrg1 were identified as potential diagnostic biomarkers for colorectal cancer.

Conclusions:

• The integrated transcriptomics-proteomics strategy is accurate and reliable for discovering diagnostic biomarkers in CRC.
• The identified candidate biomarkers (Itih3, Lrg1) and enriched pathways offer valuable insights for CRC diagnosis and treatment strategies.