bioRxivBioinformaticsPreprint
Analysis of gene expression profiles to elucidate racial differences in African American and White patients with Triple-negative breast cancer
Hailey McAndrew, Jessica Rigler, Suneetha YeguvapalliiD, Kumaraswamy Naidu ChitralaiD
Abstract
Triple-negative breast cancer (TNBC) is the second most diagnosed subtype of breast cancer. It is known to be the most aggressive one that lacks known targetable receptors. One of the concerns in TNBC is the disparities in its prevalence and tumor pathogenesis among women with non-Hispanic African American backgrounds. Despite extensive research, the genetic underpinnings that lead to these disparities remain elusive. The current study aims to provide initiative for further clinical research in the development of targeted therapy for TNBC. Gene expression profiles from African American (AA) and European American (EA) patients with TNBC were collected from Gene Expression Omnibus and performed differential gene expression (DEG)analysis. Candidate genes for a significant correlation between expression and survival rates for breast invasive carcinoma were analyzed using UALCAN. The DAVID annotation tool, Enrichr web server, KEGG database, and Gene Ontology (GO) database were used for functional enrichment analysis of target genes. The Network Analyst server was used to identify ligands with strong affinities, SeamDock server for molecular docking between the biomarkers/associated ligands and examined protein-protein interactions (PPI) from the STRING server. Data from public breast cancer cohorts was utilized to identify expression patterns associated with poor survival outcomes of AA patients with TNBC. Our results showed three genes of interest (CCT3, LSM2, and MRPS16) and potential ligands for molecular docking. Molecular docking was performed for the ICG001 ligand to CCT3 (binding affinities of -9.3 kcal/mol and -8.9 kcal/mol) and other interacting proteins (CDC20 and PPP2CA) with high degrees of connectivity. The results determined molecular docking of ICG001 to the CDC20 protein resulted in the highest binding affinity. Our results demonstrated that CCT3 and its interacting partners could serve as potential biomarkers due to their association with the survival outcome of AA patients with TNBC and ICG 001 could be the therapeutic lead for these biomarkers.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 1
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