In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 4_Supplement ( 2020-02-15), p. P2-10-05-P2-10-05
Kurzfassung:
Background: Polygenic risk scores (PRS) integrate risk information from breast cancer associated SNPs (single nucleotide polymorphism). The risk scores have mostly been developed in populations of European ancestry, and have been shown to improve risk prediction over standard breast cancer risk models in these populations. The ability of the PRS to personalize screening is currently being studied. We included PRS as a component of breast cancer risk assessment in the WISDOM Study, a trial of personalized vs. annual breast cancer screening. In order to account for race/ethnicity in PRS risk assessment, we developed a race/ethnicity calibrated and inclusive PRS risk score that we incorporated here into the Gail model to determine impact on risk stratification. Methods: We constructed two different PRS for each race/ethnicity: For Caucasian populations, we constructed two PRS based on SNPs discovered in European-ancestry populations. One PRS was based on 167 SNPs (PRS-167) and the other based on 313 SNPs (PRS-313) from the Breast Cancer Association Consortium studies as previously published. For each of the Asian-, Hispanic- and African-ancestry populations we added additional ancestry specific SNPs to the PRS-167 or the PRS-313, that were literature curated or our own identified race/ethnicity SNPs that we validated to provide independent risk prediction for their ancestry group: Asian added 10 or 4 additional SNPs, Hispanic 2 SNPs, and African 8 and 12 SNPs, respectively to each model. We tested this approach using datasets from several case-control studies of multiple racial/ethnic populations and compared discrimination of the models using area under the receiver operating characteristic curve (AUROC). Furthermore, we applied our multi-racial/ethnic PRS-313 in a sample of ~3000 multi-racial/ethnic women from the Athena Breast Screening Registry, case-control sampled by Gail score to be at elevated (Gail & gt;1.67) or average (Gail≤1.67) risk, to evaluate the impact of our multi-ethnic adjustment on risk stratification. Results: A multi-race/ethnicity adjusted PRS-313 and PRS-167 plus ethnicity specific SNPs has moderate-high discriminatory power with AUROCs of 0.65 and 0.64, respectively. The specificity of our PRS-167 in the different race/ethnicity ancestries performs relatively well in Asian (AUROC 0.59) and Hispanic (AUROC 0.63) populations, but less so in African-ancestry (AUROC 0.56). Incorporating multi-race/ethnicity PRS into Gail model selected women, resulted in 20% of average-risk women transitioning to risk above 1.67%, and conversely, 38% of elevated risk patients were reclassified to average risk. Conclusion: We constructed a PRS risk score that can be applied to multi-ethnic populations and found moderate-high discrimination. Additional work is needed for the African-ancestry population. The addition of a multi-race/ethnicity SNP model to risk classification based on the Gail model significantly changes risk stratification and clinical care recommendations due to down- or up-reclassification of women at average versus elevated risk. Citation Format: Sarah Theiner, Donglei Hu, Scott Huntsman, Yiwey Shieh, Laura Fejerman, Irene Acerbi, Sarah D Sawyer, Paige Kendall, Wei Zheng, Dezheng Huo, Olufunmilayo I Olopade, Christopher Haiman, Karla Kerlikowske, Steven Cummings, Ester John, Gabriela Torres-Mejia, Lawrence H Kushi, Denise Wolf, Jeffery A Tice, David A Pearce, Laura Esserman, Athena Breast Health Network Investigators and Advocate Partners, Laura J van ‘t Veer, Elad Ziv. A breast cancer multi-racial/ethnic polygenic risk score for improved personalized breast cancer screening [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-10-05.
Materialart:
Online-Ressource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.SABCS19-P2-10-05
Sprache:
Englisch
Verlag:
American Association for Cancer Research (AACR)
Publikationsdatum:
2020
ZDB Id:
2036785-5
ZDB Id:
1432-1
ZDB Id:
410466-3
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