SNPs for breast cancer risk assessment

Cuzick, Jack; Brentnall, Adam R.; Dowsett, Mitchell

doi:10.18632/oncotarget.22278

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…This demands tools that are easy to use, do not disrupt routine clinical practice, and reflect current science in understanding contributions of factors driving breast cancer risk. Studies show that measures of mammographic breast density (MD), polygenic risk score (PRS), and modifiable and nonmodifiable "life course risk factors" are independently related to risk for breast cancer (1,2).…”

Section: Introductionmentioning

confidence: 99%

Simplified Breast Risk Tool Integrating Questionnaire Risk Factors, Mammographic Density, and Polygenic Risk Score: Development and Validation

Rosner

Tamimi

Kraft

et al. 2020

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background: Clinical use of breast cancer risk prediction requires simplified models. We evaluate a simplified version of the validated Rosner-Colditz model and add percent mammographic density (MD) and polygenic risk score (PRS), to assess performance from ages 45-74. We validate using the Mayo Mammography Health Study (MMHS). Methods:We derived the model in the Nurses' Health Study (NHS) based on: MD, 77SNP PRS and a questionnaire score (QS) (lifestyle and reproductive factors). 2799 invasive breast cancer cases were diagnosed from 1990-2000. MD (using Cumulus software) and PRS were assessed in a nested case-control study. We assess model performance using this case-control data set and

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Section: Introductionmentioning

confidence: 99%

Simplified Breast Risk Tool Integrating Questionnaire Risk Factors, Mammographic Density, and Polygenic Risk Score: Development and Validation

Rosner

Tamimi

Kraft

et al. 2020

Cancer Epidemiology, Biomarkers &Amp; Prevention

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“…This would involve tailoring screening initiation and frequency to a woman's individual risk profile (e.g., age, breast density, genetics, family cancer history) through use of a validated risk model and consideration of women's preferences (e.g., values and beliefs). 3,11,12 Currently, there are no guidelines for clinicians on how to evaluate and incorporate patients' individual breast cancer risks (beyond age) and preferences in shared decision making regarding mammography screening. Implementing risk-based screening may be challenging.…”

Section: Introductionmentioning

confidence: 99%

How Do Women View Risk-Based Mammography Screening? A Qualitative Study

Schifferdecker

Ozanne

et al. 2018

J GEN INTERN MED

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“…In contrast to high penetrance mutations, genetic polymorphisms are very common in the general population, but are typically associated with a modest risk of cancer. However, it is believed that when a large number of such polymorphisms are combined, the magnitude of the risk conferred could be very significant 5 . In recent years, polymorphisms in microRNA genes have been widely investigated as the gene products play important roles in regulating the expression of many cancer-related genes [6][7][8] .…”

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confidence: 99%

Association between MIR499A rs3746444 polymorphism and breast cancer susceptibility: a meta-analysis

Tan

Lim

Fang

et al. 2020

Sci Rep

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Numerous studies have investigated the association of MIR499A rs3746444 polymorphism with breast cancer susceptibility, but the results have been inconsistent. In this work, we performed a meta-analysis to obtain a more reliable estimate of the association between the polymorphism and susceptibility to breast cancer. A comprehensive literature search was conducted on PubMed, Scopus, Web of Science (WoS), China National Knowledge Infrastructure (CNKI), VIP and Wanfang databases up to January 2020. A total of 14 studies involving 6,797 cases and 8,534 controls were included for analysis under five genetic models: homozygous (GG vs. AA), heterozygous (AG vs. AA), dominant (AG + GG vs. AA), recessive (GG vs. AA + AG) and allele (G vs. A). A statistically significant association was observed between the polymorphism and an increased breast cancer susceptibility under all genetic models (homozygous, OR = 1.33, 95% CI = 1.03-1.71, P = 0.03; heterozygous, OR = 1.08, 95% ci = 1.00-1.16, P = 0.04; dominant, OR = 1.15, 95% CI = 1.02-1.30; P = 0.03; recessive, OR = 1.35, 95% ci = 1.06-1.72, P = 0.01; allele, OR = 1.12, 95% CI = 1.00-1.26, P = 0.04). Subgroup analysis based on ethnicity suggested that significant association was present only among Asians, but not Caucasians. In conclusion, MIR499A rs3746444 polymorphism was significantly associated with breast cancer susceptibility among Asians, suggesting its potential use as a genetic risk marker in this population.

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SNPs for breast cancer risk assessment

Cited by 6 publications

References 6 publications

Simplified Breast Risk Tool Integrating Questionnaire Risk Factors, Mammographic Density, and Polygenic Risk Score: Development and Validation

Simplified Breast Risk Tool Integrating Questionnaire Risk Factors, Mammographic Density, and Polygenic Risk Score: Development and Validation

How Do Women View Risk-Based Mammography Screening? A Qualitative Study

Association between MIR499A rs3746444 polymorphism and breast cancer susceptibility: a meta-analysis

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