Molecular Subtype-Specific Gene Expression Profiles in Breast Cancer. Doctoral Thesis

Abstract

Breast cancer is the most diagnosed cancer among women worldwide, representing a significant and growing burden on global public health. Biologically and molecularly, breast cancer is a highly diverse disease. While its incidence continues to rise, mortality rates are gradually decreasing due to advancements in early detection and therapeutic interventions. Breast cancer research field is increasingly focusing on transcriptomic research to uncover molecular pathways and prognostic biomarkers in order to improve disease management. This Thesis brings together findings of two linked studies, investigating triple negative breast cancer (TNBC) and transcriptomic signatures in monoallelic somatic BRCA1 inactivation, to provide insights into potential therapeutic targets and prognostic markers. The first part of the study focuses on TNBC, a highly aggressive subtype of breast cancer characterised by the absence of oestrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression. The transcriptome of 19 breast cancers was sequenced and analysed to identify differentially expressed genes and enriched pathways specific to TNBC. A total of 229 differentially expressed genes were identified, with identified 4 hub genes – FOXA1, ESR1, GATA3, and TFF1 as possible biomarkers. Functional enrichment and protein–protein interaction analyses indicated alterations in hormone signalling and extracellular matrix pathways, contributing to understanding of TNBC biology with potential to offer useful information for biomarker-driven therapies. The second part of the study explores transcriptomic patterns linked with monoallelic somatic BRCA1 inactivation and its correlation with event free survival in breast cancer patients. In this study, 36 breast cancer tissue samples were sequenced and categorised based on BRCA1 inactivation status. Differential gene expression analysis revealed differential expression of genes, including TPSD1, FABP4, CARTPT, GPX2 and MMP9, which are associated with homologous recombination deficient tumors. Kaplan-Meier analysis indicated a tendency towards improved event free survival for patients with monoallelic somatic BRCA1 inactivation, suggesting this as a potentially favourable prognostic factor. Enrichment analysis showed significant involvement of extracellular proteins, providing additional insight into biology of the tumor microenvironment. The acquired results highlight the importance of transcriptomics in breast cancer research, demonstrating the value of identifying cancer subtype-specific gene expression patterns. These findings contribute to better understanding of breast cancer biology and provide potential for the development of personalised treatment strategies, advancing care for breast cancer patients in the future.