基因突变 乳腺癌易感基因1 gene can significantly increase a person’s risk of breast and ovarian cancer—but not every mutation in the gene is harmful. To better equip patients and their doctors to understand and manage individual cancer risk, researchers from 亨茨曼癌症研究所 have evaluated how hundreds of different mutations impact a key function of the 乳腺癌易感基因1 蛋白质.
在一个 研究 published June 2, 2022, in the American Journal of Human 遗传学, 肖恩·塔夫蒂吉安博士, 亨茨曼癌症研究所 researcher and University of Utah (U of U) professor of oncological sciences, explains that this information can be used to assess the clinical significance of each of those mutations—only a fraction of which they found to cause disease.
Genetic testing can determine whether a person carries a mutation within the 乳腺癌易感基因1 gene that is known to increase cancer risk. Those who do may need more frequent cancer screening than is recommended for people of average risk. They may also consider prophylactic surgery or chemoprevention to reduce their risk. But when testing reveals a variant of unknown significance, patients and clinicians lack the information they need to guide such decisions.
"There are tens of thousands of patients with unclassified variants in 乳腺癌易感基因1," says Tavtigian, who led the new 研究. Many of these, he says, cause subtle changes to the 乳腺癌易感基因1 蛋白质, altering just one of the nearly 2,000 amino acids from which it is constructed. Some of these changes—known as missense substitutions—interfere with 乳腺癌易感基因1的 ability to do its work and increase the likelihood that cancer will develop. 其他人则不然.
通过实验室测试, 计算分析, 临床数据, researchers are teasing out the impacts of these mutations. "We are reaching the point where we should be able to classify all possible missense substitutions in 乳腺癌易感基因1 over the course of the next few years," Tavtigian says. That information will improve doctors’ ability to assess their patients’ risk of developing cancer based on genetic testing. His team’s new work moves researchers closer to that goal.
To evaluate a large set of potential missense mutations, Tavtigian and his colleagues zeroed in on a critical region of 乳腺癌易感基因1: the segment the 蛋白质 needs to interact with an essential partner, BARD1. Nearly 600 different missense substitutions can occur within this region. Tavtigian’s team made versions of 乳腺癌易感基因1 with each of them and tested how efficiently they bound to BARD1 inside human cells grown in the lab.
因为 乳腺癌易感基因1 can’t function if it cannot bind to BARD1, the team was able to use the results of this lab test to score the likelihood that each missense substitution would increase a carrier’s cancer risk. 使用数学方法, point-based system that Tavtigian’s team had previously developed, they determined that 89% of the missense substitutions were either benign, 可能良性, 致病性, or likely 致病性—categories recommended by the American College of Medical 遗传学 (ACMG) for the evaluation of variants in disease-associated genes. Fewer than 20% of the missense mutations the team tested were found to be 致病性, and just a fraction of the mutations remained in the uncertain significance category.
Data from hundreds of thousands of people with and without cancer were used to validate the findings and confirm that 乳腺癌易感基因1的 相互作用 BARD1 in their laboratory tests were a reliable indicator of the mutations’ likelihood to cause disease.
Tavtigian notes that the scores his team calculated for each mutation’s likelihood of 致病性ity are easily converted into the discrete categories used by the ACMG, but he encourages researchers to adopt a more quantitative approach. He says the statistics-based method, which can be applied to variants in any disease-associated gene and requires no sophisticated computational tools, more rigorously categorizes a mutation’s potential impact. 最终, that will convey valuable information to help clinicians understand how patients’ personal genetics may impact their health.
Tavtigian recognizes critical contributions by other 亨茨曼癌症研究所 scientists, including 杰森·格茨, 凯瑟琳·瓦利, 肯尼斯·鲍彻大卫·戈德加，还有 艾伦·托马斯博士， along with additional colleagues, 犹他大学医学院, the Lady Davis Institute for Medical 研究 in Montreal, and McGill University in Montreal. The research was funded by the National Institutes of Health and the Canadian Institutes of Health 研究.
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