Genomic Risk Prediction for Breast Cancer in Older Women.
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ABSTRACT:
SUBMITTER: Lacaze P
PROVIDER: S-EPMC8305131 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundAdvancements in cancer therapeutics have resulted in increases in cancer-related survival; however, there is a growing clinical dilemma. The current balancing of survival benefits and future cardiotoxic harms of oncotherapies has resulted in an increased burden of cardiovascular disease in breast cancer survivors. Risk stratification may help address this clinical dilemma. This study is the first to assess the association between a coronary artery disease-specific polygenic risk score and incident coronary artery events in female breast cancer survivors.MethodsWe utilized the Studies in Epidemiology and Research in Cancer Heredity prospective cohort involving 12,413 women with breast cancer with genotype information and without a baseline history of cardiovascular disease. Cause-specific hazard ratios for association of the polygenic risk score and incident coronary artery disease (CAD) were obtained using left-truncated Cox regression adjusting for age, genotype array, conventional risk factors such as smoking and body mass index, as well as other sociodemographic, lifestyle, and medical variables.ResultsOver a median follow-up of 10.3 years (IQR: 16.8) years, 750 incident fatal or non-fatal coronary artery events were recorded. A 1 standard deviation higher polygenic risk score was associated with an adjusted hazard ratio of 1.33 (95% CI 1.20, 1.47) for incident CAD.ConclusionsThis study provides evidence that a coronary artery disease-specific polygenic risk score can risk-stratify breast cancer survivors independently of other established cardiovascular risk factors.
| S-EPMC8482562 | biostudies-literature
Project description:Importance:First-degree family history is a strong risk factor for breast cancer, but controversy exists about the magnitude of the association among older women. Objective:To determine whether first-degree family history is associated with increased risk of breast cancer among older women, and identify whether the association varies by breast density. Design, Setting, and Participants:Prospective cohort study between 1996 and 2012 from 7 Breast Cancer Surveillance Consortium (BCSC) registries located in New Hampshire, North Carolina, San Francisco Bay area, western Washington state, New Mexico, Colorado, and Vermont. During a mean (SD) follow-up of 6.3 (3.2) years, 10?929 invasive breast cancers were diagnosed in a cohort of 403?268 women 65 years and older with data from 472?220 mammography examinations. We estimated the 5-year cumulative incidence of invasive breast cancer by first-degree family history, breast density, and age groups. Cox proportional hazards models were fit to estimate the association of first-degree family history with risk of invasive breast cancer (after adjustment for breast density, BCSC registry, race/ethnicity, body mass index, postmenopausal hormone therapy use, and benign breast disease for age groups 65 to 74 years and 75 years and older, separately). Data analyses were performed between June 2016 and June 2017. Exposure:First-degree family history of breast cancer. Main Outcomes and Measures:Incident breast cancer. Results:In 403 268 women 65 years and older, first-degree family history was associated with an increased risk of breast cancer among women ages 65 to 74 years (hazard ratio [HR],?1.48; 95% CI, 1.35-1.61) and 75 years and older (HR, 1.44; 95% CI, 1.28-1.62). Estimates were similar for women 65 to 74 years with first-degree relative's diagnosis age younger than 50 years (HR, 1.47; 95% CI, 1.25-1.73) vs 50 years and older (HR, 1.33; 95% CI, 1.17-1.51) and for women ages 75 years and older with the relative's diagnosis age younger than 50 years (HR, 1.31; 95% CI, 1.05-1.63) vs 50 years and older (HR, 1.55; 95% CI, 1.33-1.81). Among women ages 65 to 74 years, the risk associated with first-degree family history was highest among those with fatty breasts (HR, 1.67; 95% CI, 1.27-2.21), whereas in women 75 years and older the risk associated with family history was highest among those with dense breasts (HR, 1.55; 95% CI, 1.29-1.87). Conclusions and Relevance:First-degree family history was associated with increased risk of invasive breast cancer in all subgroups of older women irrespective of a relative's age at diagnosis.
| S-EPMC5876845 | biostudies-other
Project description:Estrogen receptor (ER) ? is highly expressed in normal breast epithelium and a putative tumor suppressor. Atypical hyperplasia substantially increases breast cancer risk, but identification of biomarkers to further improve risk stratification is needed. We evaluated ER? expression in breast tissues from women with atypical hyperplasia and association with subsequent breast cancer risk. ER? expression was examined by immunohistochemistry in a well-characterized 171-women cohort with atypical hyperplasia diagnosed 1967-1991. Nuclear ER? percent and intensity was scored in the atypia and adjacent normal lobules. An ER? sum score (percent + intensity) was calculated and grouped as low, moderate, or high. Competing risks regression was used to assess associations of ER? expression with breast cancer risk. After 15-year median follow-up, 36 women developed breast cancer. ER? expression was lower in atypia lobules in than normal lobules, by percent staining and intensity (both P < 0.001). Higher ER? expression in the atypia or normal lobules, evaluated by percent staining, intensity or sum score, decreased the risk of subsequent breast cancer by 2-fold (P = 0.04) and 2.5-fold (P = 0.006). High normal lobule ER? expression conferred the strongest protective effect in premenopausal women: the 20-year cumulative incidence of breast cancer was 0% for women younger than 45 years with high versus 31% for low-moderate ER? expression (P = 0.0008). High ER? expression was associated with a significantly decreased risk of breast cancer in women with atypical hyperplasia. These data suggest that ER? may be a useful biomarker for risk stratification and a novel therapeutic target for breast cancer risk reduction.
| S-EPMC4633335 | biostudies-literature
Project description:PurposeSclerosing adenosis (SA), found in ¼ of benign breast disease (BBD) biopsies, is a histological feature characterized by lobulocentric proliferation of acini and stromal fibrosis and confers a two-fold increase in breast cancer risk compared to women in the general population. We evaluated a NanoString-based gene expression assay to model breast cancer risk using RNA derived from formalin-fixed, paraffin-embedded (FFPE) biopsies with SA.MethodsThe study group consisted of 151 women diagnosed with SA between 1967 and 2001 within the Mayo BBD cohort, of which 37 subsequently developed cancer within 10 years (cases) and 114 did not (controls). RNA was isolated from benign breast biopsies, and NanoString-based methods were used to assess expression levels of 61 genes, including 35 identified by previous array-based profiling experiments and 26 from biological insight. Diagonal linear discriminant analysis of these data was used to predict cancer within 10 years. Predictive performance was assessed with receiver operating characteristic area under the curve (ROC-AUC) values estimated from 5-fold cross-validation.ResultsGene expression prediction models achieved cross-validated ROC-AUC estimates ranging from 0.66 to 0.70. Performing univariate associations within each of the five folds consistently identified genes DLK2, EXOC6, KIT, RGS12, and SORBS2 as significant; a model with only these five genes showed cross-validated ROC-AUC of 0.75, which compared favorably to risk prediction using established clinical models (Gail/BCRAT: 0.57; BBD-BC: 0.67).ConclusionsOur results demonstrate that biomarkers of breast cancer risk can be detected in benign breast tissue years prior to cancer development in women with SA. These markers can be assessed using assay methods optimized for RNA derived from FFPE biopsy tissues which are commonly available.
| S-EPMC5668350 | biostudies-literature
Project description:BackgroundRisk assessment is important for breast cancer prevention and early detection. We aimed to examine whether common risk factors, mammographic features, and breast cancer risk prediction scores of a woman were associated with breast cancer risk for her sisters.MethodsWe included 53 051 women from the Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) study. Established risk factors were derived using self-reported questionnaires, mammograms, and single nucleotide polymorphism genotyping. Using the Swedish Multi-Generation Register, we identified 32 198 sisters of the KARMA women (including 5352 KARMA participants and 26 846 nonparticipants). Cox models were used to estimate the hazard ratios of breast cancer for both women and their sisters, respectively.ResultsA higher breast cancer polygenic risk score, a history of benign breast disease, and higher breast density in women were associated with an increased risk of breast cancer for both women and their sisters. No statistically significant association was observed between breast microcalcifications and masses in women and breast cancer risk for their sisters. Furthermore, higher breast cancer risk scores in women were associated with an increased risk of breast cancer for their sisters. Specifically, the hazard ratios for breast cancer per 1 standard deviation increase in age-adjusted KARMA, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), and Tyrer-Cuzick risk scores were 1.16 (95% confidence interval [CI] = 1.07 to 1.27), 1.23 (95% CI = 1.12 to 1.35), and 1.21 (95% CI = 1.11 to 1.32), respectively.ConclusionA woman's breast cancer risk factors are associated with her sister's breast cancer risk. However, the clinical utility of these findings requires further investigation.
| S-EPMC10637039 | biostudies-literature
Project description:BackgroundSeveral studies have proposed personalized strategies based on women's individual breast cancer risk to improve the effectiveness of breast cancer screening. We designed and internally validated an individualized risk prediction model for women eligible for mammography screening.MethodsRetrospective cohort study of 121,969 women aged 50 to 69 years, screened at the long-standing population-based screening program in Spain between 1995 and 2015 and followed up until 2017. We used partly conditional Cox proportional hazards regression to estimate the adjusted hazard ratios (aHR) and individual risks for age, family history of breast cancer, previous benign breast disease, and previous mammographic features. We internally validated our model with the expected-to-observed ratio and the area under the receiver operating characteristic curve.ResultsDuring a mean follow-up of 7.5 years, 2,058 women were diagnosed with breast cancer. All three risk factors were strongly associated with breast cancer risk, with the highest risk being found among women with family history of breast cancer (aHR: 1.67), a proliferative benign breast disease (aHR: 3.02) and previous calcifications (aHR: 2.52). The model was well calibrated overall (expected-to-observed ratio ranging from 0.99 at 2 years to 1.02 at 20 years) but slightly overestimated the risk in women with proliferative benign breast disease. The area under the receiver operating characteristic curve ranged from 58.7% to 64.7%, depending of the time horizon selected.ConclusionsWe developed a risk prediction model to estimate the short- and long-term risk of breast cancer in women eligible for mammography screening using information routinely reported at screening participation. The model could help to guiding individualized screening strategies aimed at improving the risk-benefit balance of mammography screening programs.
| S-EPMC7987139 | biostudies-literature
Project description:Background: Risk prediction models have been widely used to identify women at higher risk of breast cancer. We aimed to develop a model for absolute breast cancer risk prediction for Nigerian women.Methods: A total of 1,811 breast cancer cases and 2,225 controls from the Nigerian Breast Cancer Study (NBCS, 1998-2015) were included. Subjects were randomly divided into the training and validation sets. Incorporating local incidence rates, multivariable logistic regressions were used to develop the model.Results: The NBCS model included age, age at menarche, parity, duration of breastfeeding, family history of breast cancer, height, body mass index, benign breast diseases, and alcohol consumption. The model developed in the training set performed well in the validation set. The discriminating accuracy of the NBCS model [area under ROC curve (AUC) = 0.703, 95% confidence interval (CI), 0.687-0.719] was better than the Black Women's Health Study (BWHS) model (AUC = 0.605; 95% CI, 0.586-0.624), Gail model for white population (AUC = 0.551; 95% CI, 0.531-0.571), and Gail model for black population (AUC = 0.545; 95% CI, 0.525-0.565). Compared with the BWHS and two Gail models, the net reclassification improvement of the NBCS model were 8.26%, 13.45%, and 14.19%, respectively.Conclusions: We have developed a breast cancer risk prediction model specific to women in Nigeria, which provides a promising and indispensable tool to identify women in need of breast cancer early detection in Sub-Saharan Africa populations.Impact: Our model is the first breast cancer risk prediction model in Africa. It can be used to identify women at high risk for breast cancer screening. Cancer Epidemiol Biomarkers Prev; 27(6); 636-43. ©2018 AACR.
| S-EPMC6086588 | biostudies-literature
Project description:For African American or Hispanic women, the extent to which clinical breast cancer risk prediction models are improved by including information on susceptibility single nucleotide polymorphisms (SNPs) is unknown, even though these women comprise increasing proportions of the US population and represent a large proportion of the world's population. We studied 7539 African American and 3363 Hispanic women from the Women's Health Initiative. The age-adjusted 5-year risks from the BCRAT and IBIS risk prediction models were measured and combined with a risk score based on >70 independent susceptibility SNPs. Logistic regression, adjusting for age group, was used to estimate risk associations with log-transformed age-adjusted 5-year risks. Discrimination was measured by the odds ratio (OR) per standard deviation (SD) and the area under the receiver operator curve (AUC). When considered alone, the ORs for African American women were 1.28 for BCRAT, and 1.04 for IBIS. When combined with the SNP risk score (OR 1.23), the corresponding ORs were 1.39 and 1.22. For Hispanic women the corresponding ORs were 1.25 for BCRAT, and 1.15 for IBIS. When combined with the SNP risk score (OR 1.39), the corresponding ORs were 1.48 and 1.42. There was no evidence that any of the combined models were not well calibrated. Including information on known breast cancer susceptibility loci provides approximately 10 and 19% improvement in risk prediction using BCRAT for African Americans and Hispanics, respectively. The corresponding figures for IBIS are approximately 18 and 26%, respectively.
| S-EPMC4661211 | biostudies-literature
Project description:NF1 mutations predispose to neurofibromatosis type 1 (NF1) and women with NF1 have a moderately elevated risk for breast cancer, especially under age 50. Germline genomic analysis may better define the risk so screening and prevention can be applied to the individuals who benefit the most. Survey conducted in several neurofibromatosis clinics in the United States has demonstrated a 17.2% lifetime risk of breast cancer in women affected with NF1. Cumulated risk to age 50 is estimated to be 9.27%. For genomic profiling, fourteen women with NF1 and a history of breast cancer were recruited and underwent whole exome sequencing (WES), targeted genomic DNA based and RNA-based analysis of the NF1 gene. Deleterious NF1 pathogenic variants were identified in each woman. Frameshift mutations because of deletion/duplication/complex rearrangement were found in 50% (7/14) of the cases, nonsense mutations in 21% (3/14), in-frame splice mutations in 21% (3/14), and one case of missense mutation (7%, 1/14). No deleterious mutation was found in the following high/moderate-penetrance breast cancer genes: ATM, BRCA1, BRCA2, BARD1, BRIP1, CDH1, CHEK2, FANCC, MRE11A, NBN, PALB2, PTEN, RAD50, RAD51C, TP53, and STK11. Twenty-five rare or common variants in cancer related genes were discovered and may have contributed to the breast cancers in these individuals. Breast cancer predisposition modifiers in women with NF1 may involve a great variety of molecular and cellular functions.
| S-EPMC7771338 | biostudies-literature
Project description:Sporadic breast cancer develops through the accumulation of molecular abnormalities in normal breast tissue, resulting from exposure to estrogens and other carcinogens beginning at adolescence and continuing throughout life. These molecular changes may take a variety of forms, including numerical and structural chromosomal abnormalities, epigenetic changes, and gene expression alterations. To characterize these abnormalities, a review of the literature has been conducted to define the molecular changes in each of the above major genomic categories in normal breast tissue considered to be either at normal risk or at high risk for sporadic breast cancer. This review indicates that normal risk breast tissues (such as reduction mammoplasty) contain evidence of early breast carcinogenesis including loss of heterozygosity, DNA methylation of tumor suppressor and other genes, and telomere shortening. In normal tissues at high risk for breast cancer (such as normal breast tissue adjacent to breast cancer or the contralateral breast), these changes persist, and are increased and accompanied by aneuploidy, increased genomic instability, a wide range of gene expression differences, development of large cancerized fields, and increased proliferation. These changes are consistent with early and long-standing exposure to carcinogens, especially estrogens. A model for the breast carcinogenic pathway in normal risk and high-risk breast tissues is proposed. These findings should clarify our understanding of breast carcinogenesis in normal breast tissue and promote development of improved methods for risk assessment and breast cancer prevention in women.
| S-EPMC4990153 | biostudies-literature