Document Type
Article
Publication Date
7-7-2025
Publication Title
Biomedicines
Abstract
Background: Despite remarkable progress in clinical management of patients and intensified screening, colorectal cancer remains the second most common cause of cancer-related death in the United States. The recent surge of next generation sequencing has enabled genomic analysis of colorectal cancer genomes. However, to date, there is little information about leveraging gene expression data and integrating it with somatic mutation information to discover potential biomarkers and therapeutic targets. Here, we integrated gene expression data with somatic mutation information to discover potential diagnostic and prognostic biomarkers and molecular drivers of colorectal cancer. Methods: We used publicly available gene expression and somatic mutation data generated on the same patient populations from The Cancer Genome Atlas. We compared gene expression data between tumors and controls and between dead and alive. Significantly differentially expressed genes were evaluated for the presence of somatic mutations and subjected to functional enrichment analysis to discover molecular networks and signaling pathways enriched for somatic mutations. Results: The investigation revealed a signature of somatic mutated genes transcriptionally associated with colorectal cancer and a signature of significantly differentially expressed somatic mutated genes distinguishing dead from alive. Enrichment analysis revealed molecular networks and signaling pathways enriched for somatic mutations. Conclusions: Integrative bioinformatics analysis combining gene expression with somatic mutation data is a powerful approach for the discovery of potential diagnostic and prognostic biomarkers and potential drivers of colorectal cancer.
PubMed ID
40722723
Volume
13
Issue
7
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Fertel, Mark; Alawad, Duaa Mohammad; and Hicks, Chindo, "An Integrative Genomics Approach for the Discovery of Potential Clinically Actionable Diagnostic and Prognostic Biomarkers in Colorectal Cancer" (2025). School of Graduate Studies Faculty Publications. 376.
https://digitalscholar.lsuhsc.edu/sogs_facpubs/376
10.3390/biomedicines13071651
Included in
Bioinformatics Commons, Biological Factors Commons, Computational Biology Commons, Digestive System Diseases Commons, Genetic Processes Commons, Neoplasms Commons