Unmasking early colorectal cancer clues: in silico and in vitro investigation of downregulated IGF2, SOCS1, MLH1, and CACNA1G in SSA polyps.

Background and Aim: Colorectal cancer (CRC) originates from pre-existing polyps in the colon. The development of different subtypes of CRC is influenced by various genetic and epigenetic characteristics. CpG island methylator phenotype (CIMP) is found in about 15-20% of sporadic CRCs and is associated with hypermethylation of certain gene promoters. This study aims to find prognostic genes and compare their expression and methylation status as potential biomarkers in patients with serrated sessile adenomas/polyps (SSAP) and CRC, in order to evaluate which, one is a better predictor of disease.
Method: This study employed a multi-phase approach to investigate genes associated with CRC and SSAP. Initially, two gene expression datasets were analyzed using R and Limma package to identify differentially expressed genes (DEGs). Venn diagram analysis further refined the selection, revealing four genes from the Weissenberg panel with significant changes. These genes, underwent thorough in silico evaluations. Once confirmed, they proceeded to wet lab experimentation, focusing on expression and methylation status. This comprehensive methodology ensured a robust examination of the genes involved in CRC and SSAP.
Result: This study identified cancer-specific genes, with 8,351 and 1,769 genes specifically down-regulated in SSAP and CRC tissues, respectively. The down-regulated genes were associated with cell adhesion, negative regulation of cell proliferation, and drug response. Four highly downregulated genes in the Weissenberg panel, including CACNA1G, IGF2, MLH1, and SOCS1. In vitro analysis showed that they are hypermethylated in both SSAP and CRC samples while their expressions decreased only in CRC samples.
Conclusion: This suggests that the decrease in gene expression could help determine whether a polyp will become cancerous. Using both methylation status and gene expression status of genes in the Weissenberg panel in prognostic tests may lead to better prognoses for patients.
(© 2024. The Author(s).)