Bioinformatics analysis of gene expression profiles of triple-negative breast cancer from the African-Descent population

Background: Triple-negative breast cancer (TNBC) is the most aggressive form of breast cancer among the breast cancer subtypes. Race plays a crucial role in TNBC, with a African American (AA) women having higher incidence rates compared to European Americans (EAs). In the present study, we aim to analyze differentially expressed genes (DEGs) among African Ghanaian (AG), African Ethiopian (AE), and African American populations using the bioinformatics approach.

Material and Methods: Gene expression profiles for Ghanaian, Ethiopian, and African American populations were downloaded from the GEO database. DEG analysis was performed using GEO2R. Tumor-infiltrating immune cells were analyzed for the DEGs using TIMER. Upstream regulatory networks from signatures of DEGs were identified using X2kweb.

Results: Our results showed that 863 genes were differentially expressed between AA versus AE, 160 genes were differentially expressed between AE versus AG, and 35 genes were differentially expressed between AA versus AE. Among the identified DEGs, genes CSF3, CXCL2, CXCL3, PRKCB, and PTGER4 were found to be common among all the population groups. Further, gene enrichment analysis on the DEGs showed that these genes were found to be significantly enriched among the B-cell receptor signaling, B-cell differentiation, and B-cell activation pathways.

Conclusion: These findings indicate that these genes could be potential immune biomarkers for identifying TNBC in the African-descent population.