posted on 2023-11-01, 10:20authored byJingjing Liu, Xinghua Jin, Chengchao Qiu, Ping Han, Yixuan Wang, Jian Zhao, Jing Wu, Neng Yan, Xiaofeng Song
Understanding the pathogenesis and finding diagnostic
markers for
colorectal cancer (CRC) are the key to its diagnosis and treatment.
Integrated transcriptomics and proteomics analysis can be used to
characterize alterations of molecular phenotypes and reveal the hidden
pathogenesis of CRC. This study employed a novel strategy integrating
transcriptomics and proteomics to identify pathological molecular
pathways and diagnostic biomarkers of CRC. First, differentially expressed
proteins and coexpressed genes generated from weighted gene coexpression
network analysis (WGCNA) were intersected to obtain key genes of the
CRC phenotype. In total, 63 key genes were identified, and pathway
enrichment analysis showed that the process of coagulation and peptidase
regulator activity could both play important roles in the development
of CRC. Second, protein–protein interaction analysis was then
conducted on these key genes to find the central genes involved in
the metabolic pathways underpinning CRC. Finally, Itih3 and Lrg1 were further screened out as diagnostic
biomarkers of CRC by applying statistical analysis on central genes
combining transcriptomics and proteomics data. The deep involvement
of central genes in tumorigenesis demonstrates the accuracy and reliability
of this novel transcriptomics–proteomics integration strategy
in biomarker discovery. The identified candidate biomarkers and enriched
metabolic pathways provide insights for CRC diagnosis and treatment.