Prognostic and Predictive Biomarkers in Familial Breast Cancer

Simple Summary The importance of identifying and targeting in treating familial breast cancers is becoming increasingly recognized, in particular with increased availability of PARPi-based therapies. This review paper focuses on recognized and emerging prognostic and predictive tumour biomarkers, both recognized and emerging, specifically within familial breast cancer. In particular, these familial breast cancers appear to be different to sporadic lesions, with different interactions and clinical relevance of well-described cancer networks. More so, pre-clinical studies and in vitro models also demonstrate potentially relevant clinical biomarkers, as yet not studied in these groups. Currently, the wider literature has largely focused on prognostic and predictive factors in all breast cancers in general, or biomarkers for genetic susceptibility. This review is novel as there are none currently reviewing biomarkers only within familial breast cancers. Large numbers of breast cancers arise within a familial context, either with known inherited germline mutations largely within DNA repair genes, or with a strong family history of breast and/or ovarian cancer, with unknown genetic underlying mechanisms. These cancers appear to be different to sporadic cases, with earlier age of onset, increased multifocality and with association with specific breast cancer histological and phenotypic subtypes. Furthermore, tumours showing homologous recombination deficiency, due to loss of BRCA1, BRCA2, PALB2 and CHEK2 function, have been shown to be especially sensitive to platinum-based chemotherapeutics and PARP inhibition. While there is extensive research and data accrued on risk stratification and genetic predisposition, there are few data pertaining to relevant prognostic and predictive biomarkers within this breast cancer subgroup. The following is a review of such biomarkers in male and female familial breast cancer, although the data for the former are particularly sparse.