Advancing Cancer Genetic Testing to Improve Prevention and Patient Treatment

Certain BRCA2 gene variants are associated with cancer predisposition, and BRCA2 genetic testing is routine when considering a hereditary cause for breast, ovarian, prostate, and pancreatic cancers. However, scientists have had trouble predicting the functional effects of many BRCA2 variants, resulting in thousands of variants of uncertain significance (VUS) that, without better classification, cannot help guide clinical cancer management.

A new functional study is shifting the genetic testing paradigm for cancer, providing information on nearly 7,000 BRCA2 gene variants, including thousands of VUS.¹ In this Innovation Spotlight, Marcy Richardson, the associate director of clinical research at Ambry Genetics, discusses the challenges that BRCA2 testing has historically posed and the impact that this innovative research will have on cancer testing and treatment.

What do BRCA2 variants tell us about a person’s cancer risk?

Pathogenic variants in BRCA2 predispose a person to several cancers, primarily breast and ovarian cancer, but also others such as prostate and pancreatic cancer. These variants are inherited, so the risk of developing cancer can run in families and can be passed down to children. Thus, identifying a pathogenic BRCA2 variant in one person may suggest a potential predisposition to cancer in other family members.

What are the challenges associated with BRCA2 variant testing and analysis?

Variant interpretation is challenging in genes where pathogenic mutations predispose a person to breast cancer. This is because breast cancer is very common and we cannot distinguish between a breast cancer caused by genetics and a sporadic breast cancer. That means that most people we test have breast cancer in their families, but very few of them have a pathogenic variant that explains it. Unless a variant is common enough to use statistical modeling, we cannot use the occurrence of breast cancer as a line of evidence for variant interpretation. This leaves very few and often weaker lines of evidence that can be used to classify a variant.

How did the scientists involved in this new study develop a way to overcome these challenges?

In the absence of the ability to use phenotype—breast cancer in this case—to interpret rare variants, we must lean heavily on the remaining evidence types to classify a variant. For those to lead to a classification, we need a line of evidence that is both strong and readily available. In silco and computational tools are readily available but are often weighted conservatively because they are indirect lines of evidence. Population frequency can be strong but only for common variants and in the benign direction: A pathogenic variant is usually rare, but so are most benign variants. The observation of a variant with another known pathogenic variant can be strong, but is only rarely observed, so not readily available. Lastly, functional data can be strong but are often not readily available for every variant, having historically only been studied after being observed in a patient. That is, until now.

In this work, the scientists involved created a functional study that has a readout for virtually every single-nucleotide variant that could exist, even if it hasn’t yet been seen in a patient. For the first time for BRCA2, we have a strong and readily available line of evidence for every variant in this clinically relevant domain. The power of this line of evidence is envisaged by the theoretical implementation of these data into variant interpretation schema leading to vastly fewer VUS.

What were some of the study’s most notable results?

The volume of functional data that are now available for BRCA2 (nearly 7,000 variants from this study) is a feat unto itself. Notably, the data from this study were co-published in the same volume with a parallel study using a different model.² This is the first study of its kind where multiple ultra-high-throughput studies on the same gene can be directly compared and assimilated for variant interpretation purposes. This is a critical milestone because when something is scaled to this magnitude, the potential for error increases. Having two studies will help us better understand and trust data that are consistent and better investigate data that are discrepant. The other notable result is the power that these data can have for variant re-interpretation. Variants that do not have enough data are usually classified as VUS. BRCA2 is already in a worse spot than other genes because breast cancer is so common and we cannot use this phenotype to decide if a variant is pathogenic or benign. Therefore, BRCA2 has a lot of VUS, and this is evident in the variant interpretation repository, ClinVar. Using these functional data to reinterpret these variants with an ACMG/AMP model would theoretically cut the number of VUS in ClinVar from 1,390 to 680.

What do these findings mean for laboratories?

Each clinical diagnostic laboratory will have nuanced ways of considering and applying lines of variant interpretation evidence, including the results of this functional study. However, across the board, it can be expected that each laboratory will reclassify some variants currently classified as VUS. While the majority of these reclassifications will be from VUS to benign, it is expected that some variant reclassifications will be from VUS to pathogenic, which will impact patient management recommendations. A VUS classification is not actionable, so having fewer variants classified as VUS is a big win for everyone: the lab, the clinician, and, most importantly, the patient.

What excites you most about the future of cancer testing and treatment?

We have been studying BRCA2 for a long time. Thanks to the results of this study, we now know more than ever about this gene and its variants. We can apply the lessons learned from BRCA2 and this study to all genes in the cancer genetics testing space.

For example, within the amassed data we are starting to see nuances that we could not see before. Not all pathogenic variants have the same risk, and we have known this theoretically for a long time. Now, we have the tools to understand how these variants differ with respect to function and clinical risk. Additionally, using BRCA2 as a model, we can point to personalized medicine. There are therapeutic options for cancer patients who have germline pathogenic variants in BRCA2. Historically, a breast cancer patient may have to wait years for new data to emerge that informs the classification of their rare variant, and by that time, if their variant turns out to be pathogenic, their options for cancer treatment are moot. Now, with functional data readily available, , we are more likely to classify it the first time we see it, which is important for someone undergoing genetic testing due to a recent breast cancer diagnosis because they now become eligible for PARP-inhibitor therapy.

BRCA2 is a great model for the future of precision medicine in cancer genetics.