Abstract

Simple SummaryVariants 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.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.

Highlights

  • Germline pathogenic variants in the tumour-suppressor genes, BRCA1 and BRCA2, predispose humans to breast and ovarian cancer with reduced effects on the risk of cancer in other tissues

  • We reviewed a total of nine studies (Table 1) that assessed differences in gene expression profiles between breast tumours from BRCA1 pathogenic variant carriers and non-BRCA1 pathogenic variant carriers

  • Walker et al [15] used a pooled-RNA strategy to assess 27 lymphoblastoid cell lines (LCLs) derived from affected women in high-risk breast cancer families (9 BRCA1, 9 BRCA2 pathogenic variant carriers and 9 BRCAx) and 9 LCLs from healthy individuals, before and after treatment with mitomycin C

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Summary

Introduction

Germline pathogenic variants in the tumour-suppressor genes, BRCA1 and BRCA2, predispose humans to breast and ovarian cancer with reduced effects on the risk of cancer in other tissues. Predictive genetic testing can identify individuals who carry variants in BRCA1 and BRCA2 which confer risk and are of clinical importance. Despite efforts to identify BRCA-associated gene expression signatures, the level of consensus between studies is unclear It remains uncertain whether gene expression analysis has been a successful approach for variant classification and whether results could translate into a diagnostic setting. We address these issues by reviewing reported gene expression profiles from BRCA1 and BRCA2 pathogenic variant carriers, and consider the impact of the design of studies on their comparability.

BRCA1- and BRCA2-Associated Breast Tumours
BRCA1- and BRCA2-Associated Ovarian Tumours
Fibroblasts
Peripheral Blood
Reproducibility between Expression Studies
Sample Selection
Differences in DNA Damaging Treatments of Normal Tissue
Advancement in Technologies and Statistical Approaches
Methods of Transcriptome Analysis
Conclusions
Findings
Study design
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