scholarly journals Common variants in breast cancer risk loci predispose to distinct tumor subtypes

2022 ◽  
Vol 24 (1) ◽  
Author(s):  
Thomas U. Ahearn ◽  
Haoyu Zhang ◽  
Kyriaki Michailidou ◽  
Roger L. Milne ◽  
Manjeet K. Bolla ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Growth Factor Receptor ◽  
Breast Cancer Susceptibility ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Luminal A ◽  
Logistic Regression Models ◽  
Multiple Tumor

Abstract Background Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. Methods Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. Results Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. Conclusion This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

scholarly journals Common variants in breast cancer risk loci predispose to distinct tumor subtypes

2019 ◽  
Author(s):  
Thomas U. Ahearn ◽  
Haoyu Zhang ◽  
Kyriaki Michailidou ◽  
Roger L. Milne ◽  
Manjeet K. Bolla ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Growth Factor Receptor ◽  
Breast Cancer Susceptibility ◽  
Genome Wide Association Studies ◽  
Luminal A ◽  
Logistic Regression Models ◽  
Multiple Tumor ◽  
Tumor Subtypes

AbstractGenome-wide association studies (GWAS) have identified over 170 common breast cancer susceptibility variants using standard GWAS methods. Many of these variants have differential associations by estrogen receptor (ER), but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. We used two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. Eighty-five of 178 variants were associated with at least one tumor feature (false discovery rate <5%), most commonly ER and grade followed by PR and HER2. Case-control comparisons among these 85 variants identified 65 variants strongly or exclusively associated (P<0.05) with luminal-like subtypes, 5 variants associated with all subtypes at differing strengths and 15 variants primarily associated with non-luminal subtypes, especially triple-negative (TN) disease. Five variants were associated with risk of Luminal A-like and TN subtypes in opposite directions. This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility loci and can inform investigations of subtype-specific risk prediction.

scholarly journals Critical Analysis of Genome-Wide Association Studies: Triple Negative Breast Cancer Quae Exempli Causa

2020 ◽  
Vol 21 (16) ◽  
pp. 5835
Author(s):  
Maria-Ancuta Jurj ◽  
Mihail Buse ◽  
Alina-Andreea Zimta ◽  
Angelo Paradiso ◽  
Schuyler S. Korban ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Genetic Risk ◽  
Triple Negative ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Breast Cancer Susceptibility ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genome Wide

Genome-wide association studies (GWAS) are useful in assessing and analyzing either differences or variations in DNA sequences across the human genome to detect genetic risk factors of diseases prevalent within a target population under study. The ultimate goal of GWAS is to predict either disease risk or disease progression by identifying genetic risk factors. These risk factors will define the biological basis of disease susceptibility for the purposes of developing innovative, preventative, and therapeutic strategies. As single nucleotide polymorphisms (SNPs) are often used in GWAS, their relevance for triple negative breast cancer (TNBC) will be assessed in this review. Furthermore, as there are different levels and patterns of linkage disequilibrium (LD) present within different human subpopulations, a plausible strategy to evaluate known SNPs associated with incidence of breast cancer in ethnically different patient cohorts will be presented and discussed. Additionally, a description of GWAS for TNBC will be presented, involving various identified SNPs correlated with miRNA sites to determine their efficacies on either prognosis or progression of TNBC in patients. Although GWAS have identified multiple common breast cancer susceptibility variants that individually would result in minor risks, it is their combined effects that would likely result in major risks. Thus, one approach to quantify synergistic effects of such common variants is to utilize polygenic risk scores. Therefore, studies utilizing predictive risk scores (PRSs) based on known breast cancer susceptibility SNPs will be evaluated. Such PRSs are potentially useful in improving stratification for screening, particularly when combining family history, other risk factors, and risk prediction models. In conclusion, although interpretation of the results from GWAS remains a challenge, the use of SNPs associated with TNBC may elucidate and better contextualize these studies.

scholarly journals In Search of Breast Cancer Culprits: Suspecting the Suspected and the Unsuspected

2008 ◽  
Vol 1 ◽  
pp. 117822340800100
Author(s):  
Goberdhan P. Dimri
Keyword(s):  
Breast Cancer ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Susceptibility Gene ◽  
Breast Cancer Susceptibility ◽  
Population Based ◽  
Breast Cancer Susceptibility Gene ◽  
Candidate Gene Association

I would like to welcome breast cancer research community to the first editorial of our newest journal “Breast Cancer: Basic and Clinical Research”. In pursuit of breast cancer culprits, we have come a long way since the early 90's when the first breast cancer susceptibility gene BRCA1 was mapped and cloned. In the past few years, several new loci associated with the various degree of breast cancer risk have been identified using “Candidate Gene Association Study (CGAS) and Genome-Wide Association Study (GWAS)” approaches. This editorial is meant to quickly glance over recent findings of these population-based association studies.

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