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. 2020 Dec 14;112(12):1231-1241.
doi: 10.1093/jnci/djaa023.

The Contribution of Germline Predisposition Gene Mutations to Clinical Subtypes of Invasive Breast Cancer From a Clinical Genetic Testing Cohort

Affiliations

The Contribution of Germline Predisposition Gene Mutations to Clinical Subtypes of Invasive Breast Cancer From a Clinical Genetic Testing Cohort

Chunling Hu et al. J Natl Cancer Inst. .

Abstract

Background: The germline cancer predisposition genes associated with increased risk of each clinical subtype of breast cancer, defined by estrogen receptor (ER), progesterone receptor (PR), and HER2, are not well defined.

Methods: A total of 54 555 invasive breast cancer patients with 56 480 breast tumors were subjected to clinical hereditary cancer multigene panel testing. Heterogeneity for predisposition genes across clinical breast cancer subtypes was assessed by comparing mutation frequencies by gene among tumor subtypes and by association studies between each tumor subtype and reference controls.

Results: Mutations in 15 cancer predisposition genes were detected in 8.6% of patients with ER+/HER2-; 8.9% with ER+/HER2+; 7.7% with ER-/HER2+; and 14.4% of ER-/PR-/HER2- tumors. BRCA1, BRCA2, BARD1, and PALB2 mutations were enriched in ER- and HER2- tumors; RAD51C and RAD51D mutations were enriched in ER- tumors only; TP53 mutations were enriched in HER2+ tumors, and ATM and CHEK2 mutations were enriched in both ER+ and/or HER2+ tumors. All genes were associated with moderate (odds ratio > 2.00) or strong (odds ratio > 5.00) risks of at least one subtype of breast cancer in case-control analyses. Mutations in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53 had predicted lifetime absolute risks of at least 20.0% for breast cancer.

Conclusions: Germline mutations in hereditary cancer panel genes confer subtype-specific risks of breast cancer. Combined tumor subtype, age at breast cancer diagnosis, and family history of breast and/or ovarian cancer information provides refined categorical estimates of mutation prevalence for women considering genetic testing.

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Figures

Figure 1.
Figure 1.
Enrichment of gene-specific mutations in breast cancer subtypes. Pairwise comparisons of gene-specific mutations in breast cancer clinical tumor subtypes defined as ER+/HER2+, ER+/HER2-, ER-/HER2+, and triple-negative breast cancer (TNBC) are shown. Only genes with one or more statistically significant odds ratio among the six pairwise comparisons were included.
Figure 2.
Figure 2.
Associations between mutations in cancer predisposition genes and breast cancer subtypes. Semi-log (x-axis) plot of odds ratios estimated by comparing gene-specific mutation frequencies from breast cancer cases in each subtype with Genome Aggregation Database reference controls. Subtypes (ER+HER2+, ER+HER2-; ER-HER2+; and triple-negative breast cancer [TNBC]) were defined by estrogen receptor (ER), progesterone receptor, and HER2 status of tumors and are shown in color. Odds ratio estimates of statistically significant associations (P < .05) are labeled as “*” and nonstatistically significant associations are shown as “•.” 95% confidence intervals are shown as “whiskers.”
Figure 3.
Figure 3.
Absolute risk estimates for overall and clinical subtypes of breast cancer in non-Hispanic white population. Age-related (x-axis) absolute risk (y-axis) curves for clinical subtypes defined by hormone receptor (HR) and HER2 status (HR+/HER2+, HR+/HER2-; HR-/HER2+; and triple-negative breast cancer [TNBC]) and overall breast cancer (BC) are shown as colored lines for breast cancer patients with gene-specific mutations. Confidence intervals are shown as shadow around the cumulative risk curves.

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