An integrative bioinformatics study identifies CLCA1, ZG16, AQP8, FCGBP, and SLC17A4 as potential biomarkers mediating colorectal cancer progression via cell cycle modulation

Colorectal cancer (CRC) is the second most prevalent type of cancer in Malaysia, with 54.3% of CRC patients diagnosed at late stages III and IV. The recent increase in transcriptome analysis in CRC has provided unprecedented opportunities to apply integrated methods in identifying potential prognostic biomarkers, which is important for risk stratification and therapy selection. In this study, an integrated approach combining differentially co-expressed genes (dCEGs) and differentially expressed genes (DEGs) was applied to transcriptomic datasets from 15 paired non-tumour and tumour tissue samples from Malaysian patients. dCEG-based modular and DEG-based networks were constructed, followed by enrichment analysis to identify gene associations with cancer-related pathways and processes. Subsequently, hub genes were identified, and prognostic analysis was performed to evaluate their impact on overall survival in CRC patients. The dCEG study revealed that three significant modules, M1, M3, and M7, and 26 DEGs were upregulated in the tumour group. The upregulated genes were associated with cell cycle-related processes such as the mitotic cell cycle, spindle organisation, cell division, and chromosome organisation, as well as cancer-related pathways like the Wnt signalling pathway and pathways in cancer. Collectively, 40 key hubs were discovered, where low expression of five hubs was linked to poor prognosis. This finding was biologically relevant to our study, in concordance with the downregulation of CLCA1 , ZG16 , AQP8 , FCGBP , and SLC17A4 in our tissue samples, suggesting the potential role of these five hubs as prognostic factors in mediating CRC progression via cell cycle modulation. This finding is crucial for improving survival outcomes and advancing the development of prognostic biomarkers in future colorectal cancer research.