Abstract P1-09-04: Association between a breast cancer polygenic risk score and contralateral breast cancer risk

Author(s):  
I Kramer ◽  
MJ Hooning ◽  
N Mavaddat ◽  
S Canisius ◽  
R Keeman ◽  
...  
2020 ◽  
Vol 107 (5) ◽  
pp. 837-848
Author(s):  
Iris Kramer ◽  
Maartje J. Hooning ◽  
Nasim Mavaddat ◽  
Michael Hauptmann ◽  
Renske Keeman ◽  
...  

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Clara Bodelon ◽  
Hannah Oh ◽  
Andriy Derkach ◽  
Joshua N. Sampson ◽  
Brian L. Sprague ◽  
...  

Abstract Terminal duct lobular units (TDLUs) are the predominant anatomical structures where breast cancers originate. Having lesser degrees of age-related TDLU involution, measured as higher TDLUs counts or more epithelial TDLU substructures (acini), is related to increased breast cancer risk among women with benign breast disease (BBD). We evaluated whether a recently developed polygenic risk score (PRS) based on 313-common variants for breast cancer prediction is related to TDLU involution in the background, normal breast tissue, as this could provide mechanistic clues on the genetic predisposition to breast cancer. Among 1398 women without breast cancer, higher values of the PRS were significantly associated with higher TDLU counts (P = 0.004), but not with acini counts (P = 0.808), in histologically normal tissue samples from donors and diagnostic BBD biopsies. Mediation analysis indicated that TDLU counts may explain a modest proportion (≤10%) of the association of the 313-variant PRS with breast cancer risk. These findings suggest that TDLU involution might be an intermediate step in the association between common genetic variation and breast cancer risk.


2020 ◽  
Author(s):  
Feng Zhao ◽  
Zhixiang Hao ◽  
Yanan Zhong ◽  
Yinxue Xu ◽  
Meng Guo ◽  
...  

Abstract Background In this study, we aim to uncover the relationship between estrogen levels and the genetic polymorphism of estrogen metabolism-related enzymes with breast cancer (BC) and establish a risk prediction model based on polygenic risk score. Methods Unrelated BC patients and healthy subjects were recruited for analysis of the estrogen levels and the single nucleotide polymorphisms (SNPs) of estrogen metabolism-related enzymes. The polygenic risk score (PRS) was used to explore the combined effect of multiple genes which was calculated using a Bayesian approach. The independent sample t test was used to evaluate the difference between PRS scores of BC and healthy subjects. Discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve (ROC). Results The estrogen homeostasis profile was disturbed in BC patients, with parent estrogens (E1, E2) and carcinogenic catechol estrogens (2/4-OHE1, 2-OHE2, 4-OHE2) significantly accumulated in the serum of BC patients. Then,we established PRS model to evaluate the role of multiple genes SNPs. The PRS model 1 (M1) was established from 6 GWAS-identified high risk genes SNPs. On the basis of M1, we added 7 estrogen metabolism enzyme genes SNPs to establish PRS model 2 (M2). The independent sample t test results show that there is no difference between BC and healthy subjects in M1 (P = 0.17), however, there is significant difference between BC and healthy subjects in M2 (P = 4.9*10− 5). The ROC curve results also show that the accuracy of M2 (AUC = 62.18%) in breast cancer risk identification was better than M1 (AUC = 54.56%). Conclusion Estrogens and the related metabolic enzymes gene polymorphisms are closely related to BC. The model constructed by adding estrogen metabolic enzyme genes SNPs has a good ability in breast cancer risk prediction, and the accuracy is greatly improved comparing PRS model only includes GWAS-identified genes SNPs.


2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Celine M. Vachon ◽  
Christopher G. Scott ◽  
Rulla M. Tamimi ◽  
Deborah J. Thompson ◽  
Peter A. Fasching ◽  
...  

2017 ◽  
Vol 163 (1) ◽  
pp. 131-138 ◽  
Author(s):  
Yi-Chen Hsieh ◽  
Shih-Hsin Tu ◽  
Chien-Tien Su ◽  
Er-Chieh Cho ◽  
Chih-Hsiung Wu ◽  
...  

2016 ◽  
Vol 159 (3) ◽  
pp. 513-525 ◽  
Author(s):  
Yiwey Shieh ◽  
Donglei Hu ◽  
Lin Ma ◽  
Scott Huntsman ◽  
Charlotte C. Gard ◽  
...  

2019 ◽  
Author(s):  
Yiwey Shieh ◽  
Laura Fejerman ◽  
Sarah D. Sawyer ◽  
Donglei Hu ◽  
Scott Huntsman ◽  
...  

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