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      Evaluation of Germline Genetic Testing Criteria in a Hospital-Based Series of Women With Breast Cancer

      research-article
      , MD 1 , , PhD 2 , , PhD 3 , , PhD 3 , , PhD 3 , , MS 3 , , MS 3 , , PhD 2 , , BS 3 , , MS 3 , , MS 3 , , MD 4 , , MD 4 , , MD 4 , , MD 4 , , MD, PhD 4 , , MD 4 , , MD 4 , , MD 1 , , MD 1 , , PhD 3 , , MS 3 , , MD 1 , , MD 5 , , MD 6 , , MD, MPH 1 , , PhD 2
      Journal of Clinical Oncology
      American Society of Clinical Oncology

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          Abstract

          PURPOSE

          To determine the sensitivity and specificity of genetic testing criteria for the detection of germline pathogenic variants in women with breast cancer.

          MATERIALS AND METHODS

          Women with breast cancer enrolled in a breast cancer registry at a tertiary cancer center between 2000 and 2016 were evaluated for germline pathogenic variants in 9 breast cancer predisposition genes ( ATM , BRCA1, BRCA2, CDH1, CHEK2, NF1, PALB2, PTEN, and TP53). The performance of the National Comprehensive Cancer Network (NCCN) hereditary cancer testing criteria was evaluated relative to testing of all women as recommended by the American Society of Breast Surgeons.

          RESULTS

          Of 3,907 women, 1,872 (47.9%) meeting NCCN criteria were more likely to carry a pathogenic variant in 9 predisposition genes compared with women not meeting criteria (9.0% v 3.5%; P < .001). Of those not meeting criteria (n = 2,035), 14 (0.7%) had pathogenic variants in BRCA1 or BRCA2. The sensitivity of NCCN criteria was 70% for 9 predisposition genes and 87% for BRCA1 and BRCA2, with a specificity of 53%. Expansion of the NCCN criteria to include all women diagnosed with breast cancer at ≤ 65 years of age achieved > 90% sensitivity for the 9 predisposition genes and > 98% sensitivity for BRCA1 and BRCA2.

          CONCLUSION

          A substantial proportion of women with breast cancer carrying germline pathogenic variants in predisposition genes do not qualify for testing by NCCN criteria. Expansion of NCCN criteria to include all women diagnosed at ≤ 65 years of age improves the sensitivity of the selection criteria without requiring testing of all women with breast cancer.

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          Most cited references35

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          A breast cancer prediction model incorporating familial and personal risk factors.

          Many factors determine a woman's risk of breast cancer. Some of them are genetic and relate to family history, others are based on personal factors such as reproductive history and medical history. While many papers have concentrated on subsets of these risk factors, no papers have incorporated personal risk factors with a detailed genetic analysis. There is a need to combine these factors to provide a better overall determinant of risk. The discovery of the BRCA1 and BRCA2 genes has explained some of the genetic determinants of breast cancer risk, but these genes alone do not explain all of the familial aggregation of breast cancer. We have developed a model incorporating the BRCA genes, a low penetrance gene and personal risk factors. For an individual woman her family history is used in conjuction with Bayes theorem to iteratively produce the likelihood of her carrying any genes predisposing to breast cancer, which in turn affects her likelihood of developing breast cancer. This risk was further refined based on the woman's personal history. The model has been incorporated into a computer program that gives a personalised risk estimate. Copyright 2004 John Wiley & Sons, Ltd.
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            Association Between Inherited Germline Mutations in Cancer Predisposition Genes and Risk of Pancreatic Cancer

            IMPORTANCE Individuals genetically predisposed to pancreatic cancer may benefit from early detection. Genes that predispose to pancreatic cancer and the risks of pancreatic cancer associated with mutations in these genes are not well defined. OBJECTIVE To determine whether inherited germline mutations in cancer predisposition genes are associated with increased risks of pancreatic cancer. DESIGN, SETTING, AND PARTICIPANTS Case-control analysis to identify pancreatic cancer predisposition genes; longitudinal analysis of patients with pancreatic cancer for prognosis. The study included 3030 adults diagnosed as having pancreatic cancer and enrolled in a Mayo Clinic registry between October 12, 2000, and March 31, 2016, with last follow-up on June 22, 2017. Reference controls were 123 136 individuals with exome sequence data in the public Genome Aggregation Database and 53 105 in the Exome Aggregation Consortium database. EXPOSURES Individuals were classified based on carrying a deleterious mutation in cancer predisposition genes and having a personal or family history of cancer. MAIN OUTCOMES AND MEASURES Germline mutations in coding regions of 21 cancer predisposition genes were identified by sequencing of products from a custom multiplex polymerase chain reaction–based panel; associations of genes with pancreatic cancer were assessed by comparing frequency of mutations in genes of pancreatic cancer patients with those of reference controls. RESULTS Comparing 3030 case patients with pancreatic cancer (43.2% female; 95.6% non-Hispanic white; mean age at diagnosis, 65.3 [SD, 10.7] years) with reference controls, significant associations were observed between pancreatic cancer and mutations in CDKN2A (0.3% of cases and 0.02% of controls; odds ratio [OR], 12.33; 95% CI, 5.43–25.61); TP53 (0.2% of cases and 0.02% of controls; OR, 6.70; 95% CI, 2.52–14.95); MLH1 (0.13% of cases and 0.02% of controls; OR, 6.66; 95% CI, 1.94–17.53) ; BRCA2 (1.9% of cases and 0.3% of controls; OR, 6.20; 95% CI, 4.62–8.17); ATM (2.3% of cases and 0.37% of controls; OR, 5.71; 95% CI, 4.38–7.33); and BRCA1 (0.6% of cases and 0.2% of controls; OR, 2.58; 95% CI, 1.54–4.05). CONCLUSIONS AND RELEVANCE In this case-control study, mutations in 6 genes associated with pancreatic cancer were found in 5.5% of all0 pancreatic cancer patients, including 7.9% of patients with a family history of pancreatic cancer and 5.2% of patients without a family history of pancreatic cancer. Further research is needed for replication in other populations.
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              Triple-Negative Breast Cancer Risk Genes Identified by Multigene Hereditary Cancer Panel Testing

              Abstract Background Germline genetic testing with hereditary cancer gene panels can identify women at increased risk of breast cancer. However, those at increased risk of triple-negative (estrogen receptor–negative, progesterone receptor–negative, human epidermal growth factor receptor–negative) breast cancer (TNBC) cannot be identified because predisposition genes for TNBC, other than BRCA1, have not been established. The aim of this study was to define the cancer panel genes associated with increased risk of TNBC. Methods Multigene panel testing for 21 genes in 8753 TNBC patients was performed by a clinical testing laboratory, and testing for 17 genes in 2148 patients was conducted by a Triple Negative Breast Cancer Consortium (TNBCC) of research studies. Associations between deleterious mutations in cancer predisposition genes and TNBC were evaluated using results from TNBC patients and reference controls. Results Germline pathogenic variants in BARD1, BRCA1, BRCA2, PALB2, and RAD51D were associated with high risk (odds ratio > 5.0) of TNBC and greater than 20% lifetime risk for overall breast cancer among Caucasians. Pathogenic variants in BRIP1, RAD51C, and TP53 were associated with moderate risk (odds ratio > 2) of TNBC. Similar trends were observed for the African American population. Pathogenic variants in these TNBC genes were detected in 12.0% (3.7% non-BRCA1/2) of all participants. Conclusions Multigene hereditary cancer panel testing can identify women with elevated risk of TNBC due to mutations in BARD1, BRCA1, BRCA2, PALB2, and RAD51D. These women can potentially benefit from improved screening, risk management, and cancer prevention strategies. Patients with mutations may also benefit from specific targeted therapeutic strategies.
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                Author and article information

                Journal
                J Clin Oncol
                J. Clin. Oncol
                jco
                jco
                JCO
                Journal of Clinical Oncology
                American Society of Clinical Oncology
                0732-183X
                1527-7755
                1 May 2020
                3 March 2020
                3 March 2020
                : 38
                : 13
                : 1409-1418
                Affiliations
                [ 1 ]Department of Oncology, Mayo Clinic, Rochester, MN
                [ 2 ]Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
                [ 3 ]Department of Health Sciences Research, Mayo Clinic, Rochester, MN
                [ 4 ]Department of Medicine, Mayo Clinic, Rochester, MN
                [ 5 ]Perelman School of Medicine, University of Pennsylvania, and Basser Center for BRCA, Philadelphia, PA
                [ 6 ]Department of Surgery, Mayo Clinic, Rochester, MN
                Author notes
                Fergus J. Couch, PhD, Department of Laboratory Medicine and Pathology, 200 First St SW, Mayo Clinic, Rochester, MN 55905; e-mail: couch.fergus@ 123456mayo.edu .
                Article
                1902190
                10.1200/JCO.19.02190
                7193748
                32125938
                818b50de-7f80-4103-8d25-cd4f23b8bd7a
                © 2020 by American Society of Clinical Oncology

                Creative Commons Attribution Non-Commercial No Derivatives 4.0 License: https://creativecommons.org/licenses/by-nc-nd/4.0/

                History
                : 17 January 2020
                Page count
                Figures: 4, Tables: 12, Equations: 2, References: 50, Pages: 24
                Product
                Categories
                [BC1], Epidemiology
                [GDNL2], Clinical Guidelines: Non-ASCO Guidelines
                [EPID6], Genetic Epidemiology
                ORIGINAL REPORTS
                Genetic Testing for Cancer
                Custom metadata
                v1

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