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Anthony Tao

According to the National Breast Cancer Foundation, 1 in 8 women will have breast cancer in their lifetime. In 2024, an estimated 300,000 women and nearly 3000 men were diagnosed with breast cancer.^1,2 In many cases, breast cancer can be attributed to two genes ‒ BRCA1 and BRCA2 (collectively known as BRCA1/2). BRCA1/2 prevents cancer formation by repairing incidental damage to a cell’s DNA or genome. Unfortunately, some people have BRCA1/2 genes that do not work well due to specific inherited mutations, or variants, and therefore have a greater risk of breast cancer. With genetic testing for BRCA1/2, clinicians can identify who is at high risk and thus begin cancer screening at an earlier age, leading to earlier detection and better clinical outcomes.³

Testing for BRCA

The genetic test involves a technique known as DNA sequencing, which allows geneticists to read out the BRCA1/2 gene code for a particular individual. In doing so, they search for specific mutations in this code to identify the variant, like searching for typos in a paragraph. However, not all variants are created equal. Most are random and do not confer cancerous properties ‒ that is, they are benign variants. Only a minority pose any cancer risk ‒ the pathogenic variants. To make matters more complicated, thousands of BRCA1/2 variants exist, and geneticists do not know whether most of these are benign or pathogenic.^{3, 4}

Thus, the following problem arises: How can we develop tools to predict the effect of these unknown variants, otherwise known as variants of undetermined significance? Answering this question requires us to know how these variants affect the function of BRCA1/2 on DNA repair. Of course, there are many methods available that allow us to experimentally test the effect of a mutation on the BRCA1/2 function. However, to do so for all variants would require thousands of assays. Thus, to address this issue, two groups of researchers employed a technique known as CRISPR-based saturation genome editing to efficiently survey and predict the effects of 6-7 thousand BRCA variants on cancer function, specifically for BRCA2.⁵

CRISPR-based saturation genome editing

The CRISPR (Clustered Regularly Interspaced Short Palindrome Repeats) system allows researchers to target and cut specific genes in a living cell. By targeting CRISPR to the BRCA2 gene, scientists can replace it with a different BRCA2 variant and test how the variant affects the cell. By scaling up this method, researchers generated thousands of cells containing different variants of the BRCA2 gene within one experiment. By nature, the survival of these cells depends on proper BRCA2 function. Thus, by identifying which variants lead to cell death, scientists could predict whether a certain variant should be labelled benign or pathogenic (Figure 1).

Figure 1. Schematic of CRISPR-based saturation genome editing. CRISPR-editing of the BRCA2 gene allows a BRCA2 variant to be introduced into a cell. Pathogenic variants (red) cause cell death, resulting in a reduction in cells carrying in the variant over time. Benign variants (not illustrated), on the other hand, would have no effect and act similar to the normal cells (grey).

Through this technique, both groups of scientists ‒ one located at Mayo Clinic and the other at the National Cancer Institute (NCI) ‒ were able to classify close to 7000 different variants of BRCA2. Their method correctly predicted many of the pathogenic and benign variants that were already known. Importantly, their analyses also predicted the pathogenicity of thousands of variants of undetermined significance.^{5, 6}

The group at the NCI further wondered whether their pathogenic variants were clinically correlated with the incidence of breast cancer. To address this, they relied on a large dataset of over 5000 patients carrying over 1000 unique BRCA2 variants, many of which were variants of undetermined significance. Looking at these cases retrospectively, they found that patients carrying a predicted pathogenic variant of BRCA2 exhibited a 2.5-fold increased risk of developing breast cancer, which further validates the researcher’s model.

With this information, clinicians and geneticists may be better able to assess cancer risk in individual patients, especially those harboring unknown BRCA2 variants. Importantly, a separate group of researchers used the same technique to predict the pathogenicity of thousands of variants for BRCA1. Together, this information can be leveraged to make more informed decisions regarding cancer screening and clinical care.

Figure 2. Correlation of function scores for shared variants between the NCI and Mayo studies. Function scores were defined as the log2-ratio of day 14 cells over day 3 (NCI) or day 5 (Mayo) cells. Each dot represents a different variant for BRCA2. Negative function scores for a variant indicate a stronger effect on cell survival, and thus, predictive of higher pathogenicity. Pearson’s correlation (rho) and significance (p-value) are indicated and reflect how well the two studies agree. A rho of 1.0 would indicate 100% agreement, whereas a rho of 0 would indicate no agreement. Analysis was conducted using Matlab/R2022b (Mathworks). 

However, there are shortfalls inherent in these types of screens. Often, high-volume data such as these can suffer from statistical noise or experimental bias, deriving from the experimental setup or even the specimens used for the experiments. For instance, the two groups that analyzed BRCA2 relied on two different cell types to conduct their experiments. And though their analyses exhibit significant correlation, there is extensive disagreement regarding many of the individual variants (Figure 2). The fact that their results, which address the same question, have such discordance suggests that caution should be exercised when utilizing these results in practice.

Beyond BRCA

Overall, these approaches hold promise for the future of oncology and clinical screening. Beyond BRCA1/2, many other genes carry significant cancer risks, yet have thousands of unknown variants, including BAP1, RAD51C, VHL, CHEK2, and ATM. Together, these genes have been linked to various cancers such as breast, renal, colon, and skin. Excitingly, variants of BAP1, RAD51C, and VHL were also recently surveyed using CRISPR-based saturation genome editing in 2024. Though these methods and analyses require further refinement before being clinically employed, it is clear they represent a pivotal step toward enabling more precise and personalized approaches to cancer screening.

Header Image Source: Ernesto del Aguila III (2018). CRISPR Cas9. National Human Genome Research Institute, NIH. https://www.flickr.com/photos/nihgov/41124064215

Figure 1 Source: Created by Author, using Biorender

Figure 2 Source: Created by Author, using Matlab

Edited by Alina Panjwani

References

1. National Breast Cancer Foundation [Internet]. [cited 2025 Mar 17]. Breast cancer facts & stats 2024 – incidence, age, survival, & more. Available from: https://www.nationalbreastcancer.org/breast-cancer-facts/
2. SEER [Internet]. [cited 2025 Mar 17]. Common cancer sites – cancer stat facts. Available from: https://seer.cancer.gov/statfacts/html/common.html
3. BRCA gene changes: cancer risk and genetic testing fact sheet – nci [Internet]. 2024 [cited 2025 Mar 17]. Available from: https://www.cancer.gov/about-cancer/causes-prevention/genetics/brca-fact-sheet
4. DNA sequencing fact sheet [Internet]. [cited 2025 Mar 17]. Available from: https://www.genome.gov/about-genomics/fact-sheets/DNA-Sequencing-Fact-Sheet
5. Chehelgerdi M, Chehelgerdi M, Khorramian-Ghahfarokhi M, Shafieizadeh M, Mahmoudi E, Eskandari F, et al. Comprehensive review of CRISPR-based gene editing: mechanisms, challenges, and applications in cancer therapy. Mol Cancer [Internet]. 2024 Jan 9 [cited 2025 Mar 17];23:9. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC10775503/
6. More brca2 variants linked to cancer [Internet]. [cited 2025 Mar 17]. Available from: https://www.breastcancer.org/news/brca2-variants-reclassified