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The promise of precision medicine: Characterizing thousands of breast cancer gene variants

Updated: Jul 26, 2019



Variation in the genome shape who we are as individuals. This genetic variation influences how genes are expressed and explain, at least in part, why we look different from one another. And these differences go beyond our physical appearance: variation in our genes affects how we respond to drugs, vaccines, and pathogens and also influences our susceptibility to a number of diseases.


However, our understanding of how gene variants influence our predisposition for developing certain diseases is still poor. This is because we only understand a small percentage of gene variants in humans. The majority of these variants of uncertain significance has been identified in clinically actionable genes, which are known to play an important role in predisposition to diseases. Therefore, establishing a link between genetic variation and disease pathogenicity is crucial for personalized clinical management and improvements in precision medicine.



Linking genetic variation to disease predisposition: a challenge in precision medicine.

Source: Genetic Literacy Project.



Among actionable genes, BRCA1 has emerged in the last three decades as a potential candidate for understanding the link between genetic variation and cancer predisposition. BRCA1 is a DNA-repair associated gene. It encodes a protein that maintains genome integrity and acts as a tumour suppressor. Variation in BRCA1 may disrupt proper gene function and increase risk of early-onset breast and ovarian cancer. This is why knowledge of genetic variation has the potential for improving outcomes for patients identified with variants known to alter BRCA1 function.


Linking genetic variation to cancer predisposition is, however, not straightforward. There are thousands of BRCA1 variants. Most of them are rare and differ at a single nucleotide base in the DNA. In addition, the risk of developing cancer is unknown for the majority of BRCA1 variants and many have received conflicting interpretations in clinical databases.


Two approaches are typically used for understanding the pathogenic implications of BRCA1 variants. The first relies on comparing clinical data to genetic information by sequencing individuals and following their medical history to determine the risk of developing cancer. The second focuses on assays in vitro that measure how single-nucleotide variants affect various aspects of BRCA1 function. While relevant, both approaches fail to provide a fast solution to support risk assessment and clinical management of patients with BRCA1 variants. This happens because: 1) variants are rare, 2) sequence data is limited, 3) pathogenicity differs among patients, and 4) variants are typically characterized outside of important genomic interactions.



Variation in actionable genes can be used to assess cancer predisposition.

Source: Medicare World.


To overcome these challenges, scientists at the University of Washington and the Brotman Baty Institute of Precision Medicine in Seattle, WA, took on a much greater task: to characterize how thousands of BRCA1 variants affect gene function. Findlay and collaborators approached this task by editing the genome of cells using the CRISPR-Cas9 system. This system allows researchers to target and introduce specific changes in the genome, providing a revolutionary technology for the of study genetic variation in a wide range of organisms.


Using CRISPR-Cas9, scientists generated almost 4,000 BRCA1 variants, including a number that have not yet been observed in patients. This accounted for nearly all possible single-nucleotide variation in 13 exons that encode domains in the BRCA1 protein known to be key for tumour suppression. Variants were introduced by co-transfecting cells with two plasmids: one containing a Cas9/guide RNA construct to break a targeted region of the exon; the other containing a DNA template to repair and introduce a specific single-nucleotide variant where the break occurred in the genome. The cells used in this study were programmed to die if BRCA1 function was impaired. This allowed the researchers to classify each gene variant based on how much they affected cell survival.

The research group found that gene variants could be classified into three categories. Out of 3,893 BRCA1 variants generated through genome editing, 72.5% were classified as functional, whereas 21.1% scored as non-functional, resulting in cell death. A smaller proportion of 6.4% exhibited an intermediate effect. These results also allowed researchers to identify regions that are more susceptible to produce a non-functional gene in BRCA1 variants.


The next step was to determine how the functional classification could be used to predict pathogenicity. Using information from variant databases, scientists found that their classification was 95% accurate with clinical interpretation of known BRCA1variants. The majority of pathogenic cancer variants identified in patients were also observed to produce a non-functional gene that leads to cell death. By contrast, most variants identified as benign also scored as functional in the genome editing study.


Altogether, the results found by Findlay and collaborators provide an important step forward in the development of precision medicine. The functional classification can be used to interpret the potential risk of developing cancer in patients with a BRCA1 variant of unknown significance. These results can also be used to assess pathogenic risk in newly observed variants as well as to improve management of patients with clinically ambiguous variants. This is the first time genome editing has been applied to study such extensive number of gene variants and their effect on cancer predisposition. The framework proposed in this study shows great promise for testing the effect of genetic variation on genes with important implications in human health.


Functional classification of all 3,893 BRCA1 variants is available for non-profit and non-commercial use at “A Database of Functional Classifications of BRCA1 Variants Based on Saturation Genome Editing”.


Reference:

Findlay GM, Daza RM, Martin B, Zhang MD, Leigh MP, Gasperini M, Janizek JD, Huang X, Starita LM, Shendure J. Accurate classification of BRCA1 variants with saturation genome editing. Nature. 2018; 562(7726):217-222.



About the author:

Eduardo Gutierrez is a recent PhD with a passion for science writing and research communication. He believes good communication can make science accessible and interesting for everyone. An evolutionary biologist by training, he has expertise in molecular biology, sensory systems, and evolution, and is also interested in health and medical sciences.

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