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Genes That Best Predict Breast Cancer Risk Identified

FRIDAY, Feb. 5, 2021 -- Certain genes and pathogenic variants of some of these genes confer predisposition to breast cancer, according to two studies published in the Feb. 4 issue of the New England Journal of Medicine.

Leila Dorling, Ph.D., from the University of Cambridge in the United Kingdom, and colleagues used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,641 controls. The researchers found that protein-truncating variants in five genes were associated with a risk for breast cancer overall, with a P value < 0.0001 (ATM, BRCA1, BRCA2, CHEK2, and PALB2). Protein-truncating variants in four genes were associated with breast cancer risk overall, with a P value < 0.05 (BARD1, RAD51C, RAD51D, and TP53). Missense variants that would be classified as pathogenic according to standard criteria for BRCA1, BRCA2, and TP53 were associated with a risk for breast cancer overall.

Chunling Hu, M.D., Ph.D., from the Mayo Clinic in Rochester, Minnesota, and colleagues performed sequencing to identify germline pathogenic variants in 28 cancer-predisposition genes among 32,247 women with breast cancer and 32,544 unaffected women (controls). The researchers identified pathogenic variants in 12 established breast cancer-predisposition genes in 5.03 and 1.63 percent of cases and controls, respectively. Pathogenic variants in BRCA1 and BRCA2 were associated with elevated breast cancer risk, with odds ratios of 7.62 and 5.23, respectively. Moderately increased risk was seen for pathogenic variants in PALB2 (odds ratio, 3.83).

These studies "are useful in that they help to establish the genes that confer predisposition to breast cancer and those that do not," writes the author of an accompanying editorial. "These studies are less helpful in refining the lifetime cancer risks for women with mutations."

Several authors from both studies disclosed financial ties to the biopharmaceutical industry.

Abstract/Full Text - Dorling (subscription or payment may be required)

Abstract/Full Text - Hu (subscription or payment may be required)

Editorial (subscription or payment may be required)

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