Abstract PS4-02-24: Identifying Prognostic Epithelial-Mesenchymal Transition and Tumor Stem Cell Markers in Breast Cancer Subtypes

Abstract Introduction: Breast cancer (BC) remains the most prevalent malignancy among women, excluding skin tumors. Despite significant therapeutic advancements, a high relapse rate, affecting approximately 20% of all cases, persists. To improve clinical outcomes and develop novel therapeutic strategies, a deeper understanding of mechanisms driving tumor resistance, such as epithelial-mesenchymal transition (EMT) and tumor stem cell (TSC) biology, is crucial. Objective: This study aimed to identify immunohistochemically targetable markers related to EMT and TSC in different breast cancer subtypes with prognostic significance. Methods: We analyzed a public The Cancer Genomic Atlas (TCGA) breast cancer patient database encompassing clinical, histopathological, transcriptomic, and prognostic data. Bioinformatics tools were employed to identify differentially expressed genes (DEGs) impacting survival, analyze associated biological processes, construct co-expression networks, and investigate interactions with EMT and TSC-related pathways. Patients were categorized by their clinical immunohistochemical subtypes: triple-negative (TNBC), HER2-positive, and hormone receptor-positive (HR+) tumors. Protein-protein interaction (PPI) network analysis was integrated to identify the most relevant proteins within each subtype that correlated with survival. Results: Analysis of 989 BC patients from the Firehose Legacy TCGA database revealed DEGs and co-expression gene communities correlated with breast cancer clinical subtypes. Within these communities, DEGs related to EMT and TSC were identified, and those with a significant impact on survival were selected. PPI analysis pinpointed proteins within each community exhibiting a high degree of interaction and clinical endpoint impact. Following integration with genomic findings, the following potential protein markers were identified for further investigation in paraffin-embedded patient material: CCNB1 and CDCA8 (TNBC); COMP, P4HA3, and ECM2 (HER2-positive tumors); PPARG, ADIPOQ, LIPE, LEP, FABP4, DGAT2; CAV1,KLF4, FOS, IGF1, CLDN5, FOB, ALDH1A1, EGR1,PGM5, AKAP12, CAV2 (HR+ tumors). Conclusion: We identified subtype-specific prognostic protein markers associated with EMT and TSC in breast cancer. These findings are currently undergoing validation through immunohistochemical analysis of paraffin-embedded material from Brazilian patients, Brazilian patients RNA analysis, and in commercial breast cancer tissue microarray. Citation Format: V. D. Bertoni, B. Cavalcante, G. Rocha, C. Gurgel. Identifying Prognostic Epithelial-Mesenchymal Transition and Tumor Stem Cell Markers in Breast Cancer Subtypes abstract. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS4-02-24.