Metastatic Breast Cancer: Biomolecular Characterization and Targeted Therapy

University dissertation from Oncology, MV

Abstract: Metastasis is a complex process that remains a major challenge in the clinical management of cancer, because most cancer-related deaths are attributed to disseminated disease rather than the primary tumor. Despite the significant advances in the prediction of prognosis, and therapeutic management of primary breast cancers, coupled with the substantial improvement in our understanding of the molecular determinants of metastasis, breast cancer relapse and death rates remain unacceptably high. The aim of the research presented in this thesis was to characterize the biomolecular heterogeneity of breast cancer across tumor progression stages and to identify novel biomarkers and therapeutic strategies which may improve prognostication and personalization of therapy for women diagnosed with metastatic breast cancer. By analysis of tumor biopsies collected at different stages of disease progression, we showed that, in general, the phenotype of the primary tumor is typically conserved during tumor progression. However, in a clinically relevant number of cases, a phenotypic drift in biomarkers and tumor molecular subtypes occurs longitudinally with disease progression, with a change to a more aggressive phenotype being associated with an inferior clinical outcome. We also uncovered that breast cancer liver metastases are transcriptionally different from metastases in other anatomical sites and identified candidate liver metastasis-selective genes with the potential to specifically predict liver metastatic relapse and more generally, the time to any recurrence in early stage breast cancer. Furthermore, we demonstrated that co-targeting of PARP1 and PI3K may represent an improved and specific treatment strategy for BRCA1 deficient breast cancers. The results we present continue to emphasize the clinical significance of breast cancer heterogeneity and highlight possible ways to improve the accuracy of predicting prognosis and effectively treating patients with metastatic disease, a step towards achieving the promise of personalized cancer management and overcoming the clinical burden of metastatic breast cancer.

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