Gene Panel Testing for Breast Cancer Reveals Differential Effect of Prior BRCA1/2 Probability

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Abstract

Whilst panel testing of an extended group of genes including BRCA1/2 is commonplace, these studies have not been subdivided by histiotype or by a priori BRCA1/2 probability. Patients with a breast cancer diagnosis undergoing extended panel testing were assessed for frequency of actionable variants in breast cancer genes other than BRCA1/2 by histiotype and Manchester score (MS) to reflect a priori BRCA1/2 likelihood. Rates were adjusted by prior testing for BRCA1/2 in an extended series. 95/1398 (6.3%) who underwent panel testing were found to be positive for actionable non-BRCA1/2 breast/ovarian cancer genes (ATM, BARD1, CDH1, CHEK2, PALB2, PTEN, RAD51C, RAD51D, TP53). As expected, PALB2, CHEK2 and ATM were predominant with 80-(5.3%). The highest rate occurred in Grade-3 ER+/HER2− breast cancers-(9.6%). Rates of non-BRCA actionable genes was fairly constant over all likelihoods of BRCA1/2 but adjusted rates were three times higher with MS < 9 (BRCA1/2 = 1.5%, other = 4.7%), but was only 1.6% compared to 79.3% with MS ≥ 40. Although rates of detection of non-BRCA actionable genes are relatively constant across BRCA1/2 likelihoods this disguises an overall adjusted low frequency in high-likelihood families which have been heavily pre-tested for BRCA1/2. Any loss of detection sensitivity for BRCA1/2 actionable variants in breast cancer panels should lead to bespoke BRCA1/2 testing being conducted first.

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Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology

Sue Richards, Nazneen Aziz, Sherri Bale … (2015)

The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants. 1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next generation sequencing. By adopting and leveraging next generation sequencing, clinical laboratories are now performing an ever increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes and epigenetic assays for genetic disorders. By virtue of increased complexity, this paradigm shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context, the ACMG convened a workgroup in 2013 comprised of representatives from the ACMG, the Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP and CAP stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories including genotyping, single genes, panels, exomes and genomes. This report recommends the use of specific standard terminology: ‘pathogenic’, ‘likely pathogenic’, ‘uncertain significance’, ‘likely benign’, and ‘benign’ to describe variants identified in Mendelian disorders. Moreover, this recommendation describes a process for classification of variants into these five categories based on criteria using typical types of variant evidence (e.g. population data, computational data, functional data, segregation data, etc.). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a CLIA-approved laboratory with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or equivalent.

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The mutational constraint spectrum quantified from variation in 141,456 humans

Konrad J. Karczewski, Laurent C. Francioli, Grace Tiao … (2021)

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.

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Breast Cancer Risk Genes — Association Analysis in More than 113,000 Women

Leila Dorling, Sara Carvalho, Jamie Allen … (2021)

Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.