Publications by authors named "Garcia-Closas M"

Introduction: Incorporation of mammographic density to breast cancer risk models could improve risk stratification to tailor screening and prevention strategies according to risk. Robust evaluation of the value of adding mammographic density to models with comprehensive information on questionnaire-based risk factors and polygenic risk score is needed to determine its effectiveness in improving risk stratification of such models.

Methods: We used the Individualized Coherent Absolute Risk Estimator (iCARE) tool for risk model building and validation to incorporate density to a previously validated literature-based model with questionnaire-based risk factors and a 313-variant polygenic risk score (PRS).

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Genome-wide association studies have identified approximately 200 genetic risk loci for breast cancer, but the causal variants and target genes are mostly unknown. We sought to fine-map all known breast cancer risk loci using genome-wide association study data from 172,737 female breast cancer cases and 242,009 controls of African, Asian and European ancestry. We identified 332 independent association signals for breast cancer risk, including 131 signals not reported previously, and for 50 of them, we narrowed the credible causal variants down to a single variant.

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Background: Prolactin, a hormone produced by the pituitary gland, regulates breast development and may contribute to breast cancer etiology. However, most epidemiologic studies of prolactin and breast cancer have been restricted to single, often small, study samples with limited exploration of effect modification.

Methods: The Biomarkers in Breast Cancer Risk Prediction consortium includes 8,279 postmenopausal women sampled from four prospective cohort studies, of whom 3,441 were diagnosed with invasive breast cancer after enrollment.

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  • Known genetic risk factors account for about one-third of familial endometrial cancer cases, but the link between rare germline copy number variants (CNVs) and cancer risk is not well understood.
  • A study analyzed DNA from over 4,000 endometrial cancer patients and nearly 18,000 controls, finding that the cancer group had a significantly higher number of CNVs.
  • The research identified 141 gene loci potentially related to endometrial cancer risk, highlighting a specific area (16p11.2) with recurrent deletions that could help further investigations into genetic susceptibility.
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  • Normal tissues adjacent to breast tumors (NATs) may contain early signs of breast cancer development due to a phenomenon called field cancerization.
  • A study using advanced genomic techniques on samples from 43 breast cancer patients in Hong Kong revealed that NATs often had single-nucleotide variants (SNVs) in driver genes also found in tumor samples, but rarely had large-scale genomic changes.
  • The researchers identified different evolutionary patterns among NAT and tumor pairs, indicating distinct genomic characteristics and the influence of the tumor microenvironment on cancer development.
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Purpose: Most breast biopsies are diagnosed as benign breast disease (BBD), with 1.5- to fourfold increased breast cancer (BC) risk. Apart from pathologic diagnoses of atypical hyperplasia, few factors aid in BC risk assessment of these patients.

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  • Clinical genetic testing helps find cancer risks by identifying gene changes, but some of these changes are confusing because we don't know what they mean (called VUS).
  • Researchers studied a huge number of breast cancer patients and healthy people to understand these confusing gene changes better.
  • They found that their method of analyzing data closely matches what other experts say about which gene changes are harmless or harmful, giving more information about 785 unclear changes.
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Background: Breast cancer is comprised of distinct molecular subtypes. Studies have reported differences in risk factor associations with breast cancer subtypes, especially by tumor estrogen receptor (ER) status, but their consistency across racial and ethnic populations has not been comprehensively evaluated.

Methods: We conducted a qualitative, scoping literature review using the Preferred Reporting Items for Systematic Reviews and Meta-analysis, extension for Scoping Reviews to investigate consistencies in associations between 18 breast cancer risk factors (reproductive, anthropometric, lifestyle, and medical history) and risk of ER-defined subtypes in women who self-identify as Asian, Black or African American, Hispanic or Latina, or White.

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  • * Analysis of data from over 55,000 breast cancer patients showed that co-observation of variants in BRCA1, BRCA2, and PALB2 with other breast cancer genes occurred less frequently than expected, suggesting a potential correlation with pathogenicity.
  • * The findings indicate that identifying a variant of uncertain significance alongside a known pathogenic variant supports evidence against the variant's pathogenicity, which could improve variant classification in clinical settings and for other genetic conditions.
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Background: Breast cancer consists of distinct molecular subtypes. Studies have reported differences in risk factor associations with breast cancer subtypes, especially by tumor estrogen receptor (ER) status, but their consistency across racial and ethnic populations has not been comprehensively evaluated.

Methods: We conducted a qualitative, scoping literature review using the Preferred Reporting Items for Systematic Reviews and Meta-analysis, extension for Scoping Reviews to investigate consistencies in associations between 18 breast cancer risk factors (reproductive, anthropometric, lifestyle, and medical history) and risk of ER-defined subtypes in women who self-identify as Asian, Black or African American, Hispanic or Latina, or White.

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  • The stromal microenvironment (SME) in breast cancer plays a crucial role in tumor behavior and response to treatment; its relationship with pre-diagnostic factors, especially in women of African ancestry, is not well understood.
  • A study analyzed 792 breast cancer patients to identify how pre-diagnostic host factors influenced SME characteristics using machine learning on tissue images, revealing that certain factors like parity and family history correlated with higher stromal cellular density.
  • The results suggest that epidemiological risk factors may impact tumor biology through changes in the SME, emphasizing the importance of considering these factors in breast cancer studies.
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  • Scientists looked at the timing of when girls start their periods (called menarche) and how it can affect their health later in life.
  • They studied about 800,000 women and found over a thousand genetic signals that influence when menstruation starts.
  • Some women have a much higher chance of starting their periods too early or too late based on their genetic makeup, suggesting that genes play a big role in this process!
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Objectives: Absolute risk models estimate an individual's future disease risk over a specified time interval. Applications utilizing server-side risk tooling, the R-based iCARE (R-iCARE), to build, validate, and apply absolute risk models, face limitations in portability and privacy due to their need for circulating user data in remote servers for operation. We overcome this by porting iCARE to the web platform.

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Breast cancer includes several subtypes with distinct characteristic biological, pathologic, and clinical features. Elucidating subtype-specific genetic etiology could provide insights into the heterogeneity of breast cancer to facilitate the development of improved prevention and treatment approaches. In this study, we conducted pairwise case-case comparisons among five breast cancer subtypes by applying a case-case genome-wide association study (CC-GWAS) approach to summary statistics data of the Breast Cancer Association Consortium.

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  • - The study analyzed genetic factors linked to breast cancer in a diverse sample of 18,034 African ancestry cases and 22,104 controls, identifying 12 genetic variants tied to increased risk.
  • - Key findings included a rare variant (rs61751053) associated with overall breast cancer risk (odds ratio 1.48) and a common variant (rs76664032) connected to triple-negative breast cancer (odds ratio 1.30).
  • - A polygenic risk score (PRS) showed a predictive capability (0.60 area under the curve) for breast cancer risk, illustrating improved accuracy compared to PRS based on European data and highlighting the significance of diversity in genetic research.
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African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3' UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls.

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The associations of certain factors, such as age and menopausal hormone therapy, with breast cancer risk are known to differ for interval and screen-detected cancers. However, the extent to which associations of other established breast cancer risk factors differ by mode of detection is unclear. We investigated associations of a wide range of risk factors using data from a large UK cohort with linkage to the National Health Service Breast Screening Programme, cancer registration, and other health records.

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Purpose: Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI, circulating sex hormone concentrations, and mammographic density phenotypes using Mendelian randomization (MR).

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Background: A high body mass index (BMI, kg/m) is associated with decreased risk of breast cancer before menopause, but increased risk after menopause. Exactly when this reversal occurs in relation to menopause is unclear. Locating that change point could provide insight into the role of adiposity in breast cancer etiology.

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  • Scientists looked at how certain genes may affect breast cancer in women with African ancestry.
  • They studied 9,241 women with breast cancer and compared them to 10,193 healthy women to find links between the genes and the disease.
  • They found specific gene variations that could increase the risk of breast cancer, especially types of cancer that don't depend on estrogen.
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Epidemiologic data on insecticide exposures and breast cancer risk are inconclusive and mostly from high-income countries. Using data from 1071 invasive pathologically confirmed breast cancer cases and 2096 controls from the Ghana Breast Health Study conducted from 2013 to 2015, we investigated associations with mosquito control products to reduce the spread of mosquito-borne diseases, such as malaria. These mosquito control products were insecticide-treated nets, mosquito coils, repellent room sprays, and skin creams for personal protection against mosquitos.

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Background: Online questionnaires are commonly used to collect information from participants in epidemiological studies. This requires building questionnaires using machine-readable formats that can be delivered to study participants using web-based technologies such as progressive web applications. However, the paucity of open-source markup standards with support for complex logic make collaborative development of web-based questionnaire modules difficult.

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Objective: Absolute risk models estimate an individual's future disease risk over a specified time interval. Applications utilizing server-side risk tooling, such as the R-based iCARE (R-iCARE), to build, validate, and apply absolute risk models, face serious limitations in portability and privacy due to their need for circulating user data in remote servers for operation. Our objective was to overcome these limitations.

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