Identification of a nuclear transcriptional module associated with ERα and E2F/FOXM1 signaling across PAM50 breast cancer subtypes
TL;DR
The 34-gene panel is proposed as a candidate transcriptional framework that may provide insights into BC subtype-discrimination and potential utility as a biomarker signature for breast cancer stratification.
Abstract
Background Breast cancer is the most prevalent and lethal cancer among women worldwide. Although classification based on ERα, PR, and HER2 status guides treatment decisions, misclassification remains a challenge due to the complexity of ERα-associated transcriptional network. Identifying biomarkers that better reflect ERα activity may improve tumor stratification and therapeutic decision-making. We hypothesized that an ERα-related transcriptional framework could improve molecular characterization of breast cancer subtypes. Methods Clinicopathological features were evaluated in relation to PAM50 subtypes. Gene expression profiles from fresh breast tumor biopsies (n=65) were analyzed and integrated with ERα-related genes identified through literature review and pathway databases (KEGG, WikiPathways, Reactome, and IPA). Differentially expressed genes among subtypes were used to construct a nuclear module for functional enrichment and protein interaction analyses. Selected genes were evaluated by RT-qPCR in breast cancer cell lines. The reproducibility of the module expression was assessed in the independent public cohort GSE18229. Correlation analyses were performed to evaluate associations between module genes and MKI67/Ki-67 expression. Results Menopausal status showed a significant association with PAM50 subtypes. Among 647 ERα-related genes, a 34-gene nuclear module was identified as a highly interconnected network. Genes enriched in LumB, HER2-enriched, and basal and downregulated in LumA and normal-like subtypes were mainly associated with proliferation and cell cycle regulation (CCNE1, E2F2, FOXM1, PLK1, and SKP2). The ERα–E2F/FOXM1 axis emerged as a potential regulator of the transcriptional module. RT-qPCR supported the expression of selected genes E2F2, PAK2, and PARP1. The module showed reproducible expression patterns in an independent cohort. Correlation analysis revealed proliferation and chromatin-related genes positively and hormone-related genes negatively associated with MKI67/Ki-67, identifying the most significant associations in the study. Conclusion This 34-gene module represents an interconnected transcriptional program enriched in E2F/FOXM1 signaling and ERα-associated processes. The integrated analysis of genes involved in hormone signaling, proliferation, genome regulation, and cancer-related processes may reveal subtype-specific expression patterns reflecting ERα activity. We propose the 34-gene panel as a candidate transcriptional framework that may provide insights into BC subtype-discrimination. Further validation in larger cohorts and additional experimental validation are required to determine its potential utility as a biomarker signature for breast cancer stratification.