Genome-Wide Gene Expression Analyses of BRCA1- and BRCA2-Associated Breast and Ovarian Tumours

SIMPLE SUMMARY: Variants in the breast cancer susceptibility genes BRCA1 and BRCA2 increase the risk of developing breast and ovarian cancers. Over the past two decades researchers have aimed to identify gene expression changes associated with high-risk BRCA1 and BRCA2 variants. In this review we explore the replicability of BRCA1- and BRCA2-associated gene expression profiles in diseased and normal tissue. We highlight the impact of experimental factors and study designs on the comparability and utility of gene expression profiles associated with high-risk BRCA1 and BRCA2 variants. Additionally, we emphasise the importance of controlling for confounding molecular features that may influence the design of study cohort groups. ABSTRACT: Germline pathogenic variants in BRCA1 and BRCA2 increase cumulative lifetime risk up to 75% for breast cancer and 76% for ovarian cancer. Genetic testing for BRCA1 and BRCA2 pathogenic variants has become an important part of clinical practice for cancer risk assessment and for reducing individual risk of developing cancer. Genetic testing can produce three outcomes: positive (a pathogenic variant), uninformative (no pathogenic variant) and uncertain significance (a variant of unknown clinical significance). More than one third of BRCA1 and BRCA2 variants identified have been classified as variants of uncertain significance, presenting a challenge for clinicians. To address this important clinical challenge, a number of studies have been undertaken to establish a gene expression phenotype for pathogenic BRCA1 and BRCA2 variant carriers in several diseased and normal tissues. However, the consistency of gene expression phenotypes described in studies has been poor. To determine if gene expression analysis has been a successful approach for variant classification, we describe the design and comparability of 23 published gene expression studies that have profiled cells from BRCA1 and BRCA2 pathogenic variant carriers. We show the impact of advancements in expression-based technologies, the importance of developing larger study cohorts and the necessity to better understand variables affecting gene expression profiles across different tissue types.