scholarly journals Alternative splicing regulation by GWAS risk loci for breast cancer

2019 ◽  
Author(s):  
Juliana Machado ◽  
Ramiro Magno ◽  
Joana M Xavier ◽  
Ana-Teresa Maia
Keyword(s):  
Breast Cancer ◽  
Alternative Splicing ◽  
Target Genes ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Normal Breast ◽  
Genome Wide Association Studies ◽  
Functional Characterisation ◽  
Genome Wide ◽  
Gene Isoforms

ABSTRACTRecent genome-wide association studies (GWAS) have revealed the association of hundreds of single nucleotide polymorphisms (SNPs) with breast cancer (BC) risk, which mostly locate in non-coding regions, suggesting regulatory roles to the causal variants. Functional characterisation of GWAS loci has been biased towards the effect of regulatory SNPs on transcription factor binding. Here we set out to determine the extent of the contribution of breast cancer risk-associated SNPs to alternative splicing (AS).We screened genome-wide significant (P ≤ 5 × 10−8) BC risk SNPs for association with AS, using expression and genotype data from normal breast samples, from the GTEx project. We identified four splicing quantitative trait loci (sQTL). In locus 6p22.1, rs6456883 is a significant cis-sQTL for the expression of ZNF311 gene isoforms. Three SNPs in locus 8p23.3, rs6682326, rs3008282 and rs2906324, were also identified as significant cis-sQTLs/svQTLs for the expression of RPL23AP53 gene isoforms. In-silico functional analysis revealed that these variants can potentially alter enhancer splicing elements within the target genes.Our work shows that BC risk-associated variants at two loci are associated with AS isoforms in normal breast tissue, thus demonstrating that AS plays an important role in breast cancer susceptibility. Furthermore, it supports that all cis-regulatory mechanisms should be considered in the functional characterisation of risk loci.

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 Allele-specific miRNA-binding analysis identifies candidate target genes for breast cancer risk

2019 ◽  
Author(s):  
Ana Jacinta-Fernandes ◽  
Joana M. Xavier ◽  
Ramiro Magno ◽  
Joel G. Lage ◽  
Ana-Teresa Maia
Keyword(s):  
Breast Cancer ◽  
Target Genes ◽  
Association Studies ◽  
Mirna Gene ◽  
Genome Wide Association Studies ◽  
Binding Prediction ◽  
Cis Regulation ◽  
Genome Wide ◽  
Candidate Target ◽  
Allele Specific

ABSTRACTMost breast cancer (BC) risk-associated variants (raSNPs) identified in genome-wide association studies (GWAS) are believed to cis-regulate the expression of genes. We hypothesise that cis-regulatory variants contributing to disease risk may be affecting miRNA genes and/or miRNA-binding. To test this we adapted two miRNA-binding prediction algorithms — TargetScan and miRanda — to perform allele-specific queries, and integrated differential allelic expression (DAE) and expression quantitative trait loci (eQTL) data, to query 150 genome-wide significant (P ≤ 5 × 10−8) raSNPs, plus proxies. We found that no raSNP mapped to a miRNA gene, suggesting that altered miRNA targeting is an unlikely mechanism involved in BC risk. Also, 11.5% (6 out of 52) raSNPs located in 3’UTRs of putative miRNA target genes were predicted to alter miRNA∷mRNA pair binding stability in five candidate target genes. Of these, we propose RNF115, at locus 1q21.1, as a strong novel target gene associated with BC risk, and re-inforce the role of miRNA mediated cis-regulation at locus 19p13.11. We believe that integrating allele-specific querying in miRNA-binding prediction, and data supporting cis-regulation of expression, improves the identification of candidate target genes in BC risk, as well as in other common cancers and complex diseases.

scholarly journals Chromatin interactome mapping at 139 independent breast cancer risk signals

2020 ◽  
Vol 21 (1) ◽  
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

Abstract Background Genome-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. Results 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. Conclusions 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.

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