Breast Cancer Polygenic Risk Score and Contralateral Breast Cancer Risk.
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ABSTRACT:
SUBMITTER: Kramer I
PROVIDER: S-EPMC7675034 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Breast cancer risk assessment can inform the use of screening and prevention modalities. We investigated the performance of the Breast Cancer Surveillance Consortium (BCSC) risk model in combination with a polygenic risk score (PRS) comprised of 83 single nucleotide polymorphisms identified from genome-wide association studies. We conducted a nested case-control study of 486 cases and 495 matched controls within a screening cohort. The PRS was calculated using a Bayesian approach. The contributions of the PRS and variables in the BCSC model to breast cancer risk were tested using conditional logistic regression. Discriminatory accuracy of the models was compared using the area under the receiver operating characteristic curve (AUROC). Increasing quartiles of the PRS were positively associated with breast cancer risk, with OR 2.54 (95 % CI 1.69-3.82) for breast cancer in the highest versus lowest quartile. In a multivariable model, the PRS, family history, and breast density remained strong risk factors. The AUROC of the PRS was 0.60 (95 % CI 0.57-0.64), and an Asian-specific PRS had AUROC 0.64 (95 % CI 0.53-0.74). A combined model including the BCSC risk factors and PRS had better discrimination than the BCSC model (AUROC 0.65 versus 0.62, p = 0.01). The BCSC-PRS model classified 18 % of cases as high-risk (5-year risk ?3 %), compared with 7 % using the BCSC model. The PRS improved discrimination of the BCSC risk model and classified more cases as high-risk. Further consideration of the PRS's role in decision-making around screening and prevention strategies is merited.
| S-EPMC5033764 | biostudies-literature
Project description:We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.
| S-EPMC7936056 | biostudies-literature
Project description:Importance:Radiation therapy for breast cancer is associated with increased risk of a second primary contralateral breast cancer, but the genetic factors modifying this association are not well understood. Objective:To determine whether a genetic risk score comprising single nucleotide polymorphisms in the nonhomologous end-joining DNA repair pathway is associated with radiation-associated contralateral breast cancer. Design, Setting, and Participants:This case-control study included a case group of women with contralateral breast cancer that was diagnosed at least 1 year after a first primary breast cancer who were individually matched to a control group of women with unilateral breast cancer. Inclusion criteria were receiving a first invasive breast cancer diagnosis prior to age 55 years between 1985 and 2008. Women were recruited through 8 population-based cancer registries in the United States, Canada, and Denmark as part of the Women's Environment, Cancer, and Radiation Epidemiology Studies I (November 2000 to August 2004) and II (March 2010 to December 2012). Data analysis was conducted from July 2017 to August 2019. Exposures:Stray radiation dose to the contralateral breast during radiation therapy for the first breast cancer. A novel genetic risk score comprised of genetic variants in the nonhomologous end-joining DNA repair pathway was considered the potential effect modifier, dichotomized as high risk if the score was above the median of 74 and low risk if the score was at or below the median. Main Outcomes and Measures:The main outcome was risk of contralateral breast cancer associated with stray radiation dose stratified by genetic risk score, age, and latency. Results:A total of 5953 women were approached for study participation, and 3732 women (62.7%) agreed to participate. The median (range) age at first diagnosis was 46 (23-54) years. After 5 years of latency or more, among women who received the first diagnosis when they were younger than 40 years, exposure to 1.0 Gy (to convert to rad, multiply by 100) or more of stray radiation was associated with a 2-fold increased risk of contralateral breast cancer compared with women who were not exposed (rate ratio, 2.0 [95% CI, 1.1-3.6]). The risk was higher among women with a genetic risk score above the median (rate ratio, 3.0 [95% CI, 1.1-8.1]), and there was no association among women with a genetic risk score below the median (rate ratio, 1.3 [95% CI, 0.5-3.7]). Among younger women with a high genetic risk score, the attributable increased risk for contralateral breast cancer associated with stray radiation dose was 28%. Conclusions and Relevance:This study found an increased risk of contralateral breast cancer that was attributable to stray radiation exposure among women with a high genetic risk score and who received a first breast cancer diagnosis when they were younger than 40 years after 5 years or more of latency. This genetic risk score may help guide treatment and surveillance for women with breast cancer.
| S-EPMC6777239 | biostudies-literature
Project description:BackgroundPolygenic risk scores (PRS) could potentially improve breast cancer screening recommendations. Before a PRS can be considered for implementation, it needs rigorous evaluation, using performance measures that can inform about its future clinical value.ObjectivesTo evaluate the prognostic performance of a regression model with a previously developed, prevalence-based PRS and age as predictors for breast cancer incidence in women from the Estonian biobank (EstBB) cohort; to compare it to the performance of a model including age only.MethodsWe analyzed data on 30,312 women from the EstBB cohort. They entered the cohort between 2002 and 2011, were between 20 and 89 years, without a history of breast cancer, and with full 5-year follow-up by 2015. We examined PRS and other potential risk factors as possible predictors in Cox regression models for breast cancer incidence. With 10-fold cross-validation we estimated 3- and 5-year breast cancer incidence predicted by age alone and by PRS plus age, fitting models on 90% of the data. Calibration, discrimination, and reclassification were calculated on the left-out folds to express prognostic performance.ResultsA total of 101 (3.33‰) and 185 (6.1‰) incident breast cancers were observed within 3 and 5 years, respectively. For women in a defined screening age of 50-62 years, the ratio of observed vs PRS-age modelled 3-year incidence was 0.86 for women in the 75-85% PRS-group, 1.34 for the 85-95% PRS-group, and 1.41 for the top 5% PRS-group. For 5-year incidence, this was respectively 0.94, 1.15, and 1.08. Yet the number of breast cancer events was relatively low in each PRS-subgroup. For all women, the model's AUC was 0.720 (95% CI: 0.675-0.765) for 3-year and 0.704 (95% CI: 0.670-0.737) for 5-year follow-up, respectively, just 0.022 and 0.023 higher than for the model with age alone. Using a 1% risk prediction threshold, the 3-year NRI for the PRS-age model was 0.09, and 0.05 for 5 years.ConclusionThe model including PRS had modest incremental performance over one based on age only. A larger, independent study is needed to assess whether and how the PRS can meaningfully contribute to age, for developing more efficient screening strategies.
| S-EPMC8691010 | biostudies-literature
Project description:We evaluated whether 13 single nucleotide polymorphisms (SNPs) identified in genome-wide association studies interact with one another and with reproductive and menstrual risk factors in association with breast cancer risk. DNA samples and information on parity, breastfeeding, age at menarche, age at first birth, and age at menopause were collected through structured interviews from 1,484 breast cancer cases and 1,307 controls who participated in a population-based case-control study conducted in three US states. A polygenic score was created as the sum of risk allele copies multiplied by the corresponding log odds estimate. Logistic regression was used to test the associations between SNPs, the score, reproductive and menstrual factors, and breast cancer risk. Nonlinearity of the score was assessed by the inclusion of a quadratic term for polygenic score. Interactions between the aforementioned variables were tested by including a cross-product term in models. We confirmed associations between rs13387042 (2q35), rs4973768 (SLC4A7), rs10941679 (5p12), rs2981582 (FGFR2), rs3817198 (LSP1), rs3803662 (TOX3), and rs6504950 (STXBP4) with breast cancer. Women in the score's highest quintile had 2.2-fold increased risk when compared to women in the lowest quintile (95 % confidence interval: 1.67-2.88). The quadratic polygenic score term was not significant in the model (p = 0.85), suggesting that the established breast cancer loci are not associated with increased risk more than the sum of risk alleles. Modifications of menstrual and reproductive risk factors associations with breast cancer risk by polygenic score were not observed. Our results suggest that the interactions between breast cancer susceptibility loci and reproductive factors are not strong contributors to breast cancer risk.
| S-EPMC3799826 | biostudies-literature
Project description:The risk of developing breast cancer is increased in women with family history of breast cancer and particularly in families with multiple cases of breast or ovarian cancer. Nevertheless, many women with a positive family history never develop the disease. Polygenic risk scores (PRSs) based on the risk effects of multiple common genetic variants have been proposed for individual risk assessment on a population level. We investigate the applicability of the PRS for risk prediction within breast cancer families. We studied the association between breast cancer risk and a PRS based on 75 common genetic variants in 52 Finnish breast cancer families including 427 genotyped women and pedigree information on ~4000 additional individuals by comparing the affected to healthy family members, as well as in a case-control dataset comprising 1272 healthy population controls and 1681 breast cancer cases with information on family history. Family structure was summarized using the BOADICEA risk prediction model. The PRS was associated with increased disease risk in women with family history of breast cancer as well as in women within the breast cancer families. The odds ratio (OR) for breast cancer within the family dataset was 1.55 [95 % CI 1.26-1.91] per unit increase in the PRS, similar to OR in unselected breast cancer cases of the case-control dataset (1.49 [1.38-1.62]). High PRS-values were informative for risk prediction in breast cancer families, whereas for the low PRS-categories the results were inconclusive. The PRS is informative in women with family history of breast cancer and should be incorporated within pedigree-based clinical risk assessment.
| S-EPMC4963452 | biostudies-literature
Project description:Background:Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors. Methods:Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status. Results:The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction?=?0.009), adult height (P-interaction?=?0.025) and current use of combined MHT (P-interaction?=?0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P?=?0.013 for global and 0.18 for tail-based tests). Conclusions:The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.
| S-EPMC5913605 | biostudies-literature
Project description:ImportanceTo date, few studies have examined the extent to which polygenic single-nucleotide variation (SNV) (formerly single-nucleotide polymorphism) scores modify risk for carriers of pathogenic variants (PVs) in breast cancer susceptibility genes. In previous reports, polygenic risk modification was reduced for BRCA1 and BRCA2 PV carriers compared with noncarriers, but limited information is available for carriers of CHEK2, ATM, or PALB2 PVs.ObjectiveTo examine an 86-SNV polygenic risk score (PRS) for BRCA1, BRCA2, CHEK2, ATM, and PALB2 PV carriers.Design, setting, and participantsA retrospective case-control study using data on 150 962 women tested with a multigene hereditary cancer panel between July 19, 2016, and January 11, 2019, was conducted in a commercial testing laboratory. Participants included women of European ancestry between the ages of 18 and 84 years.Main outcomes and measuresMultivariable logistic regression was used to examine the association of the 86-SNV score with invasive breast cancer after adjusting for age, ancestry, and personal and/or family cancer history. Effect sizes, expressed as standardized odds ratios (ORs) with 95% CIs, were assessed for carriers of PVs in each gene as well as for noncarriers.ResultsThe median age at hereditary cancer testing of the population was 48 years (range, 18-84 years); there were 141 160 noncarriers in addition to carriers of BRCA1 (n = 2249), BRCA2 (n = 2638), CHEK2 (n = 2564), ATM (n = 1445), and PALB2 (n = 906) PVs included in the analysis. The 86-SNV score was associated with breast cancer risk in each of the carrier populations (P < 1 × 10-4). Stratification was more pronounced for noncarriers (OR, 1.47; 95% CI, 1.45-1.49) and CHEK2 PV carriers (OR, 1.49; 95% CI, 1.36-1.64) than for carriers of BRCA1 (OR, 1.20; 95% CI, 1.10-1.32) or BRCA2 (OR, 1.23; 95% CI, 1.12-1.34) PVs. Odds ratios for ATM (OR, 1.37; 95% CI, 1.21-1.55) and PALB2 (OR, 1.34; 95% CI, 1.16-1.55) PV carrier populations were intermediate between those for BRCA1/2 and CHEK2 noncarriers.Conclusions and relevanceIn this study, the 86-SNV score was associated with modified risk for carriers of BRCA1, BRCA2, CHEK2, ATM, and PALB2 PVs. This finding supports previous reports of reduced PRS stratification for BRCA1 and BRCA2 PV carriers compared with noncarriers. Modification of risk in CHEK2 carriers associated with the 86-SNV score appeared to be similar to that observed in women without a PV. Larger studies are needed to provide more refined estimates of polygenic modification of risk for women with PVs in other moderate-penetrance genes.
| S-EPMC7330720 | biostudies-literature
Project description:Hereditary factors have a strong influence on prostate cancer (PC) risk and poorer outcomes, thus stratification by genetic factors addresses a critical need for targeted PC screening and risk-adapted follow-up. In this Finnish population-based retrospective study 2283 clinically diagnosed and 455 screen-detected patients from the Finnish Randomised Study of Screening for Prostate Cancer (FinRSPC), 2400 healthy individuals have been involved. Individual genetic risk through establishment of a polygenic risk score based on 55 PC risk SNPs identified through the Finnish subset of the Collaborative Oncological Gene-Environment Study was assessed. Men with PC had significantly higher median polygenic risk score compared to the controls (6.59 vs. 3.83, P < 0.0001). The polygenic risk score above the control median was a significant predictor of PC (OR 2.13, 95% CI 1.90-2.39). The polygenic risk score predicted the risk of PC with an AUC of 0.618 (95% CI 0.60-0.63). Men in the highest polygenic risk score quartile were 2.8-fold (95% CI 2.4-3.30) more likely to develop PC compared with men in the lowest quartile. In the FinRSPC cohort, a significantly higher percentage of men had a PSA level of ≥ 4 ng/mL in polygenic risk score quartile four compared to quartile one (18.7% vs 8.3%, P < 0.00001). Adding the PRS to a PSA-only model contributed additional information in predicting PC in the FinRSPC model. Results strongly suggest that use of the polygenic risk score would facilitate the identification of men at increased risk for PC.
| S-EPMC7553910 | biostudies-literature
Project description:IntroductionWhether and to what extent the relationship between physical activity (PA) and colorectal cancer (CRC) differs according to CRC-related genetic risk remains to be determined, and no studies to date have quantified how much genetically determined risk could be compensated for with active exercise.MethodsGenetic risk was quantified by a polygenic risk score (PRS) summarizing the estimated effect of 140 CRC-associated genetic variants. Associations of PA with CRC risk were estimated by multivariable logistic regression across PRS levels. We also compared the impact of PA and specific PA types to the PRS using "genetic risk equivalent (GRE)", a novel approach to enhance effective risk communication.ResultsAmong 5058 CRC patients and 4134 controls, we observed no significant association between overall PA level in quartiles and CRC risk. However, the highest versus lowest lifetime leisure time physical activity (LTPA) was associated with a 13% lower CRC risk [odds ratio 0.87, 95% confidence interval (CI) 0.77-1.00] independent of PRS levels (adjusted p value for interaction = 0.18). This effect was equivalent to the effect of having 11 percentiles lower PRS (GRE -10.6, 95% CI -20.7 to -0.6). The GRE (95% CI) for the highest lifetime sports tertile was -23.0 (-33.9 to -12.0).ConclusionsLTPA was inversely associated with CRC risk irrespective of polygenic risk for CRC, which reinforces the importance of LTPA in CRC prevention among the general population. Adequate sports activity can compensate for a large share of polygenic risk for CRC.
| S-EPMC9972112 | biostudies-literature