PS4-05-17: Identifying hub genes among different breast cancer subtypes and racial diversity through integrated bioinformatics analysis (WGCNA)

Abstract Introduction: Focusing only on driver genes may ignore important interactions and pathways in breast cancer across subtypes and racial groups. Understanding their dysfunctional network or hub genes is crucial, as these are related to mRNA expression patterns. Our goal is to identify key hub genes related to race and subtype. Methods and materials: RNA-seq counts and clinical data from TCGA (GSE62944) were filtered to include only invasive breast cancer cases with complete information on race (White, Black, Asian), intrinsic subtype (Luminal A/B, HER2-enriched, Basal-like), and survival status. Differential expression analysis was performed using DESeq2 to compare tumor samples from deceased versus living patients within each race×subtype group. Genes with |log2fold change|>1 and FDR0.8) and gene significance (GS>0.2). We prioritized hub genes that were prevalent across multiple traits. Results: A total of 3548 DEGs were identified across intrinsic subtypes and race and finally 7 gene coexpression modules were recognized. The turquoise module was the largest (709 genes), followed by blue (538 genes) and brown (407 genes). However, the last one exhibited the strongest inverse correlation with basal-like tumors across racial groups, including both White (R=-0.66, p