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Updated: Jun 4, 2025
Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection
Published on: June 8, 2020
Utilizing an In-silico Approach to Pinpoint Potential Biomarkers for Enhanced Early Detection of Colorectal Cancer
Alireza Gharebaghi1, Saeid Afshar2,3, Leili Tapak4,5
1Neurophysiology Research Center, Hamadan University of Medical Sciences, Hamadan, Iran.
Objectives:
Colorectal cancer (CRC) is a prevalent disease characterized by significant dysregulation of gene expression. Non-invasive tests that utilize microRNAs (miRNAs) have shown promise for early CRC detection. This study aims to determine the association between miRNAs and key genes in CRC.
Methods:
Two datasets (GSE106817 and GSE23878) were extracted from the NCBI Gene Expression Omnibus database. Penalized logistic regression (PLR) and artificial neural networks (ANN) were used to identify relevant miRNAs and evaluate the classification accuracy of the selected miRNAs. The findings were validated through bipartite miRNA-mRNA interactions.
Results:
Our analysis identified 3 miRNAs: miR-1228, miR-6765-5p, and miR-6787-5p, achieving a total accuracy of over 90%. Based on the results of the mRNA-miRNA interaction network, CDK1 and MAD2L1 were identified as target genes of miR-6787-5p.
Conclusions:
Our results suggest that the identified miRNAs and target genes could serve as non-invasive biomarkers for diagnosing colorectal cancer, pending laboratory confirmation.
