scholarly journals Can cancer GWAS variants modulate immune cells in the tumor microenvironment?

2018 ◽  
Author(s):  
Yi Zhang ◽  
Mohith Manjunath ◽  
Jialu Yan ◽  
Brittany A. Baur ◽  
Shilu Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Cells ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Immune Surveillance ◽  
Tumor Infiltrating Lymphocytes ◽  
Cell Types ◽  
Potential Effect ◽  
Chromatin Interaction ◽  
Genome Wide Association Studies

AbstractGenome-wide association studies (GWAS) have hitherto identified several genetic variants associated with cancer susceptibility, but the molecular functions of these risk modulators remain largely uncharacterized. Recent studies have begun to uncover the regulatory potential of non-coding GWAS SNPs by using epigenetic information in corresponding cancer cell types and matched normal tissues. However, this approach does not explore the potential effect of risk germline variants on other important cell types that constitute the microenvironment of tumor or its precursor. This paper presents evidence that the breast cancer-associated variant rs3903072 may regulate the expression of CTSW in tumor infiltrating lymphocytes. CTSW is a candidate tumor-suppressor gene, with expression highly specific to immune cells and also positively correlated with breast cancer patient survival. Integrative analyses suggest a putative causative variant in a GWAS-linked enhancer in lymphocytes that loops to the 3’ end of CTSW through three-dimensional chromatin interaction. Our work thus poses the possibility that a cancer-associated genetic variant might regulate a gene not only in the cell of cancer origin, but also in immune cells in the microenvironment, thereby modulating the immune surveillance by T lymphocytes and natural killer cells and affecting the clearing of early cancer initiating cells.

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 Chromatin interactome mapping at 139 independent breast cancer risk signals

2019 ◽  
Author(s):  
Jonathan Beesley ◽  
Haran Sivakumaran ◽  
Mahdi Moradi Marjaneh ◽  
Luize G. Lima ◽  
Kristine M. Hillman ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Target Genes ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Breast Cancer Cell Lines ◽  
Open Chromatin ◽  
Genome Wide Association Studies ◽  
Candidate Target

ABSTRACTGenome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression. We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals, and explore the functional mechanism underlying altered risk at the 12q24 risk region. Our results demonstrate the power of combining genetics, computational genomics and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals.

scholarly journals A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

2021 ◽  
Author(s):  
Shweta Ramdas ◽  
Jonathan Judd ◽  
Sarah E Graham ◽  
Stavroula Kanoni ◽  
Yuxuan Wang ◽  
...  
Keyword(s):  
Association Studies ◽  
Density Lipoprotein ◽  
Genomic Analysis ◽  
Enrichment Analysis ◽  
Cell Types ◽  
Chromatin Interaction ◽  
Genome Wide Association Studies ◽  
Functional Genomic ◽  
Selective Enrichment ◽  
Functional Genomic Analysis

AbstractA major challenge of genome-wide association studies (GWAS) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations, and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels, and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. Two prioritized genes, CREBRF and RRBP1, show convergent evidence across functional datasets supporting their roles in lipid biology.

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 Risks and Function of Breast Cancer Susceptibility Alleles

Cancers ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 3953
Author(s):  
Saeideh Torabi Dalivandan ◽  
Jasmine Plummer ◽  
Simon A. Gayther
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Disease Risk ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Treatment Strategies ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Degree Relative ◽  
Risk Variants

Family history remains one of the strongest risk factors for breast cancer. It is well established that women with a first-degree relative affected by breast cancer are twice as likely to develop the disease themselves. Twins studies indicate that this is most likely due to shared genetics rather than shared epidemiological/lifestyle risk factors. Linkage and targeted sequencing studies have shown that rare high- and moderate-penetrance germline variants in genes involved in the DNA damage response (DDR) including BRCA1, BRCA2, PALB2, ATM, and TP53 are responsible for a proportion of breast cancer cases. However, breast cancer is a heterogeneous disease, and there is now strong evidence that different risk alleles can predispose to different subtypes of breast cancer. Here, we review the associations between the different genes and subtype-specificity of breast cancer based on the most comprehensive genetic studies published. Genome-wide association studies (GWAS) have also been used to identify an additional hereditary component of breast cancer, and have identified hundreds of common, low-penetrance susceptibility alleles. The combination of these low penetrance risk variants, summed as a polygenic risk score (PRS), can identify individuals across the spectrum of disease risk. However, there remains a substantial bottleneck between the discovery of GWAS-risk variants and their contribution to tumorigenesis mainly because the majority of these variants map to the non-protein coding genome. A range of functional genomic approaches are needed to identify the causal risk variants and target susceptibility genes and establish their underlying role in disease biology. We discuss how the application of these multidisciplinary approaches to understand genetic risk for breast cancer can be used to identify individuals in the population that may benefit from clinical interventions including screening for early detection and prevention, and treatment strategies to reduce breast cancer-related mortalities.

scholarly journals Genome-Wide Association Studies (GWAS) breast cancer susceptibility loci in Arabs: susceptibility and prognostic implications in Tunisians

2012 ◽  
Vol 135 (3) ◽  
pp. 715-724 ◽  
Author(s):  
Jingxuan Shan ◽  
Wijden Mahfoudh ◽  
Shoba P. Dsouza ◽  
Elham Hassen ◽  
Noureddine Bouaouina ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Breast Cancer Susceptibility ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Susceptibility Loci ◽  
Genome Wide ◽  
Prognostic Implications

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 Fine-mapping of 150 breast cancer risk regions identifies 178 high confidence target genes

2019 ◽  
Author(s):  
Laura Fachal ◽  
Hugues Aschard ◽  
Jonathan Beesley ◽  
Daniel R. Barnes ◽  
Jamie Allen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Target Genes ◽  
Association Studies ◽  
Chromatin Interaction ◽  
Dna Integrity ◽  
Genomic Feature ◽  
Genome Wide Association Studies ◽  
Causal Variants

ABSTRACTGenome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants (CCVs) in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium, and enriched genomic features to determine variants with high posterior probabilities (HPPs) of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of potentially causal variants, using gene expression (eQTL), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways, were over-represented among the 178 highest confidence target genes.

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