Development and Validation of a Clinical Polygenic Risk Score to Predict Breast Cancer Risk
| Autor: | Shannon Gallagher, Johnathan M. Lancaster, Judy Garber, Jerry S. Lanchbury, Eric Rosenthal, Mark E. Robson, Susan M. Domchek, Alexander Gutin, Allison W. Kurian, Thaddeus Judkins, Benjamin B. Roa, Placede Tshiaba, Susanne Wagner, Jeffrey N. Weitzel, Elisha Hughes |
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| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Oncology Cancer Research medicine.medical_specialty medicine.diagnostic_test business.industry MEDLINE medicine.disease 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Breast cancer 030220 oncology & carcinogenesis Internal medicine Original Reports Medicine Hereditary Cancer Polygenic risk score Family history business Genetic testing |
| Zdroj: | JCO Precision Oncology |
| ISSN: | 2473-4284 |
| DOI: | 10.1200/po.19.00360 |
| Popis: | PURPOSE Women with a family history of breast cancer are frequently referred for hereditary cancer genetic testing, yet < 10% are found to have pathogenic variants in known breast cancer susceptibility genes. Large-scale genotyping studies have identified common variants (primarily single-nucleotide polymorphisms [SNPs]) with individually modest breast cancer risk that, in aggregate, account for considerable breast cancer susceptibility. Here, we describe the development and empirical validation of an SNP-based polygenic breast cancer risk score. METHODS A panel of 94 SNPs was examined for association with breast cancer in women of European ancestry undergoing hereditary cancer genetic testing and negative for pathogenic variants in breast cancer susceptibility genes. Candidate polygenic risk scores (PRSs) as predictors of personal breast cancer history were developed through multivariable logistic regression models adjusted for age, cancer history, and ancestry. An optimized PRS was validated in 2 independent cohorts (n = 13,174; n = 141,160). RESULTS Within the training cohort (n = 24,259), 4,291 women (18%) had a personal history of breast cancer and 8,725 women (36%) reported breast cancer in a first-degree relative. The optimized PRS included 86 variants and was highly predictive of breast cancer status in both validation cohorts ( P = 6.4 × 10−66; P < 10−325). The odds ratio (OR) per unit standard deviation was consistent between validations (OR, 1.45 [95% CI, 1.39 to 1.52]; OR 1.47 [95% CI, 1.45 to 1.49]). In a direct comparison, the 86-SNP PRS outperformed a previously described PRS of 77 SNPs. CONCLUSION The validation and implementation of a PRS for women without pathogenic variants in known breast cancer susceptibility genes offers potential for risk stratification to guide surveillance recommendations. |
| Databáze: | OpenAIRE |
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