Integrative Bioinformatics Analysis: Unraveling Variant Signatures and Single-Nucleotide Polymorphism Markers Associated with 5-FU-Based Chemotherapy Resistance in Colorectal Cancer Patients.

Abstract

Background: Drug resistance in colorectal cancer (CRC) is modulated by multiple molecular factors, which can be ascertained through genetic investigation. Single nucleotide polymorphisms (SNPs) within key genes have the potential to impair the efficacy of chemotherapeutic agents such as 5-fluorouracil (5-FU). Therefore, the identification of SNPs linked to drug resistance can significantly contribute to the advancement of tailored therapeutic approaches and the enhancement of treatment outcomes in patients with CRC.

Material and method: To identify dysregulated genes in 5-FU-based chemotherapy responder or non-responder CRC patients, a meta-analysis was performed. Next, the protein-protein interaction (PPI) network of the identified genes was analyzed using the STRING database. The most significant module was chosen for further analysis. In addition, a literature review was conducted to identify drug resistance-related genes. Enrichment analysis was conducted to validate the main module genes and the genes identified from the literature review. The associations between SNPs and drug resistance were investigated, and the consequences of missense variants were assessed using in silico tools.

Result: The meta-analysis identified 796 dysregulated genes. Then, to conduct PPI analysis and enrichment analysis, we were able to discover 23 genes that are intricately involved in the cell cycle pathway. Consequently, these 23 genes were chosen for SNP analysis. By using the dbSNP database and ANNOVAR, we successfully detected and labeled SNPs in these specific genes. Additionally, after careful exclusion of SNPs with allele frequencies below 0.01, we evaluated 6 SNPs from the HDAC1, MCM2, CDK1, BUB1B, CDC14B, and CCNE1 genes using 8 bioinformatics tools. Therefore, these SNPs were identified as potentially harmful by multiple computational tools. Specifically, rs199958833 in CDK1 (Val124Gly) was predicted to be damaging by all tools used. Our analysis strongly indicates that this specific SNP could negatively affect the stability and functionality of the CDK1 protein.

Conclusion: Based on our current understanding, the evaluation of CDK1 polymorphisms in the context of drug resistance in CRC has yet to be undertaken. In this investigation, we showed that rs199958833 variant in the CDK1 gene may favor resistance to 5-FU-based chemotherapy. However, these findings need validation in an independent cohort of patients.