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.

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 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.

FGFR2 genotype and risk of radiation-associated breast cancer in Hodgkin lymphoma

Blood ◽  
2012 ◽  
Vol 119 (4) ◽  
pp. 1029-1031 ◽  
Author(s):  
Yussanne P. Ma ◽  
Flora E. van Leeuwen ◽  
Rosie Cooke ◽  
Annegien Broeks ◽  
Victor Enciso-Mora ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Hodgkin Lymphoma ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Control Series ◽  
Cancer Risk Factors ◽  
Increased Risk

Abstract Women treated at young ages with supradiaphragmatic radiotherapy for Hodgkin lymphoma (HL) have a highly increased risk of breast cancer. For personalized advice and follow-up regimens for patients, information is needed on how the radiotherapy-related risk is affected by other breast cancer risk factors. Genome-wide association studies have identified 14 independently replicated common single nucleotide polymorphisms that influence breast cancer risk. To examine whether these variants contribute to risk of radiation-associated breast cancer in HL, we analyzed 2 independent case-control series, from the United Kingdom and The Netherlands, totaling 693 HL patients, 232 with breast cancer and 461 without. rs1219648, which annotates the FGFR2 gene, was associated with risk in both series (combined per-allele odds ratio = 1.59, 95% confidence interval: 1.26-2.02; P = .000111). These data provide evidence that genetic variation in FGFR2 influences radiation-induced breast cancer risk.

scholarly journals Candidate Causal Variants at the 8p12 Breast Cancer Risk Locus Regulate DUSP4

2019 ◽  
Author(s):  
Dylan M. Glubb ◽  
Wei Shi ◽  
Jonathan Beesley ◽  
Laura Fachal ◽  
Jayne-Louise Pritchard ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Promoter Region ◽  
Risk Allele ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Enhancer Element ◽  
Causal Variants ◽  
Risk Locus

Genome-wide association studies have revealed a locus at 8p12 that is associated with breast cancer risk. Fine-mapping of this locus identified 16 candidate causal variants (CCVs). However, as these variants are intergenic, their function is unclear. To map chromatin looping from this risk locus to a previously identified candidate target gene, DUSP4, we performed chromatin conformation capture analyses in normal and tumoral breast cell lines. We identified putative regulatory elements, containing CCVs, that loop to the DUSP4 promoter region. Using reporter gene assays, we found that the risk allele of CCV rs7461885 reduced the activity of a DUSP4 enhancer element, consistent with the function of DUSP4 as a tumor suppressor gene. Furthermore, the risk allele of CCV rs12155535, located in another DUSP4 enhancer element, was negatively correlated with looping of this element to the DUSP4 promoter region, suggesting that this allele would be associated with reduced expression. These findings provide the first evidence that CCV risk alleles downregulate DUSP4 expression, suggesting that this gene is a regulatory target of the 8p12 breast cancer risk locus.

scholarly journals CRISPR screens identify gene targets and drug repositioning opportunities at breast cancer risk loci

2021 ◽  
Author(s):  
Natasha K Tuano ◽  
Jonathan Beesley ◽  
Murray Manning ◽  
Wei Shi ◽  
Luis Malver-Ortega ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Risk ◽  
Drug Repositioning ◽  
Association Studies ◽  
Drug Repurposing ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Genome Wide ◽  
Causal Variants ◽  
Cancer Phenotypes

Genome-wide association studies (GWAS) have identified >200 loci associated with breast cancer (BC) risk. The majority of candidate causal variants (CCVs) are in non-coding regions and are likely to modulate cancer risk by regulating gene expression. We recently developed a scoring system, INQUISIT, to predict candidate risk genes at BC-risk loci. Here, we used pooled CRISPR activation and suppression screens to validate INQUISIT predictions, and to define the cancer phenotypes they mediate. We measured proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on the DNA damage response. We performed 60 CRISPR screens and identified 21 high-confidence INQUISIT predictions that mediate a cancer phenotype. We validated the direct regulation of a subset of genes by BC-risk variants using HiCHIP and CRISPRqtl. Furthermore, we show the utility of expression profiling for drug repurposing against these targets. We provide a platform for identifying gene targets of risk variants, and lay a blueprint of interventions for BC risk reduction and treatment.

scholarly journals Functional annotation of breast cancer risk loci: current progress and future directions

2021 ◽  
Author(s):  
Shirleny Romualdo Cardoso ◽  
Andrea Gillespie ◽  
Syed Haider ◽  
Olivia Fletcher
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Target Genes ◽  
Regulatory Sequences ◽  
Fine Scale ◽  
Functional Variants ◽  
Putative Target ◽  
Causal Variants ◽  
Fine Scale Mapping

AbstractGenome-wide association studies coupled with large-scale replication and fine-scale mapping studies have identified more than 150 genomic regions that are associated with breast cancer risk. Here, we review efforts to translate these findings into a greater understanding of disease mechanism. Our review comes in the context of a recently published fine-scale mapping analysis of these regions, which reported 352 independent signals and a total of 13,367 credible causal variants. The vast majority of credible causal variants map to noncoding DNA, implicating regulation of gene expression as the mechanism by which functional variants influence risk. Accordingly, we review methods for defining candidate-regulatory sequences, methods for identifying putative target genes and methods for linking candidate-regulatory sequences to putative target genes. We provide a summary of available data resources and identify gaps in these resources. We conclude that while much work has been done, there is still much to do. There are, however, grounds for optimism; combining statistical data from fine-scale mapping with functional data that are more representative of the normal “at risk” breast, generated using new technologies, should lead to a greater understanding of the mechanisms that influence an individual woman’s risk of breast cancer.

scholarly journals CRISPR screens identify gene targets and drug repositioning opportunities at breast cancer risk loci

2022 ◽  
Author(s):  
Joseph Rosenbluh ◽  
Natasha Tuano ◽  
Jonathan Beesley ◽  
Murray Manning ◽  
Wei Shi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Risk ◽  
Target Genes ◽  
Drug Repositioning ◽  
Association Studies ◽  
Drug Repurposing ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Breast Cells ◽  
Cancer Phenotypes

Abstract Genome-wide association studies (GWAS) have identified >200 loci associated with breast cancer (BC) risk. The majority of candidate causal variants (CCVs) are in non-coding regions and likely modulate cancer risk by regulating gene expression. However, pinpointing the exact target of the association and identifying the phenotype it mediates is a major challenge in the interpretation and translation of GWAS. Here, we used pooled CRISPR activation and suppression screens to evaluate predicted GWAS target genes, and to define the cancer phenotypes they mediate. We measured proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on DNA repair. We performed 60 CRISPR screens and identified 21 genes predicted with high confidence to be GWAS targets that drive a cancer phenotype by driving a proliferation or DNA damage response in breast cells. We validated the regulation of a subset of these genes by BC-risk variants, and show the utility of expression profiling for drug repurposing. We provide a platform for identifying gene targets of risk variants, and present a blueprint of interventions for BC risk reduction and treatment.

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