scholarly journals Identifying 31 novel breast cancer susceptibility loci using data from genome-wide association studies conducted in Asian and European women

2019 ◽  
Author(s):  
Xiang Shu ◽  
Jirong Long ◽  
Qiuyin Cai ◽  
Sun-Seog Kweon ◽  
Ji-Yeob Choi ◽  
...  

ABSTRACTCommon genetic variants in 183 loci have been identified in relation to breast cancer risk in genome-wide association studies (GWAS). These risk variants combined explain only a relatively small proportion of breast cancer heritability, particularly in Asian populations. To search for additional genetic susceptibility loci for breast cancer, we performed a meta-analysis of data from GWAS conducted in Asians (24,206 cases and 24,775 controls). Variants showing an association with breast cancer risk at P < 0.01 were evaluated in GWAS conducted in European women including 122,977 cases and 105,974 controls. In the combined analysis of data from both Asian and European women, the lead variant in 28 loci not previously reported showed an association with breast cancer risk at P < 5 ×10−8. In the meta-analysis of all GWAS data from Asian and European descendants, we identified SNPs in three additional loci in association with breast cancer risk at P < 5 ×10−8. The associations for 10 of these loci were replicated in an independent sample of 16,787 cases and 16,680 controls of Asian women (P < 0.05). Expression quantitative trait locus (eQTL) and gene-based analyses provided evidence for the possible involvement of the YBEY, MAN2C1, SNUPN, TBX1, SEMA4A, STC1, MUTYH, LOXL2, and LINC00886 genes underlying the associations observed in eight of these 28 newly identified risk loci. In addition, we replicated the association for 78 of the 166 previously reported risk variants at P < 0.05 in women of Asian descent using GWAS data. These findings improve our understanding of breast cancer genetics and etiology and extend to Asian populations previous findings from studies of European women.

2021 ◽  
Author(s):  
Natasha K Tuano ◽  
Jonathan Beesley ◽  
Murray Manning ◽  
Wei Shi ◽  
Luis Malver-Ortega ◽  
...  

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.


2013 ◽  
Vol 45 (4) ◽  
pp. 392-398 ◽  
Author(s):  
Montserrat Garcia-Closas ◽  
◽  
Fergus J Couch ◽  
Sara Lindstrom ◽  
Kyriaki Michailidou ◽  
...  

2016 ◽  
Vol 1 (4) ◽  
pp. 77-82
Author(s):  
Ali Sanjari Moghaddam ◽  
Morteza Roodgar ◽  
Hamid Mansourpour ◽  
Alireza Mosavi Jarrahi

In this meta-analysis, we tried to clear the relationship between breast cancer risk and LSP1 gene rs3817198T>C polymorphism. This meta-analysis was conducted according to PRISMA protocol. We searched PubMed/Medline, Web of sciences and EMBASE. All literature investigating the association of LSP1 gene rs3817198T>C and breast cancer risk were considered to include in the meta-analysis. We pooled ORs using both fixed and random-effect models. Egger’s test and funnel plot were used to evaluate Publication bias and small study effect. After evaluation and screening of citations, 14 publications were eligible for final analysis after applying of inclusion and exclusion criteria. Overall, 30,204 cases and 35,282 controls included in this meta-analysis. There was the significant association between LSP1 gene rs3817198T>C polymorphism and breast cancer only in homozygote genetic model (OR=1.14 [1.05-1.24]) and no association was found in heterozygotes (OR=1.03 [0.98-1.07]). The association was significant for popula ion-based studies and European & American & African population in both homozygote and heterozygote genetic model. There was no evidence of bias of literature and no small study effect. In conclusion, it seems that LSP1 gene rs3817198 polymorphism play its role in breast cancer incidence and other SNPs and environment are such triggers. Nevertheless, we recommend genome-wide association studies to evaluate the effect of SNPs in combination, not as single SNPs.


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