ArticleOncotarget2016
The precision relationships between eight GWAS-identified genetic variants and breast cancer in a Chinese population.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Genetic and lifestyle factors for breast cancer risk assessment in Southeast China.Cancer medicine · 2023Trial
- The association of CASC16 variants with breast Cancer risk in a northwest Chinese female population.Molecular medicine (Cambridge, Mass.) · 2020Article
- ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration.BioData mining · 2019Article
- Subtype-specific associations between breast cancer risk polymorphisms and the survival of early-stage breast cancer.Journal of translational medicine · 2018Article
- Evaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese.Oncotarget · 2018Article
- Polymorphisms of long non-coding RNA HOTAIR with breast cancer susceptibility and clinical outcomes for a southeast Chinese Han population.Oncotarget · 2018Article
- IL-8 -251A/T and +781C/T polymorphisms were associated with risk of breast cancer in a Chinese population.International journal of clinical and experimental pathology · 2017Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Some of the new breast cancer susceptibility loci discovered in recent Genome-wide association studies (GWASs) have not been confirmed in Chinese populations. To determine whether eight novel Single-Nucleotide Polymorphisms (SNPs) have associations with breast cancer risk in women from southeast China, we conducted a case-control study of 1,156 breast cancer patients and 1,256 healthy controls. We first validated that the SNPs rs12922061, rs2290203, and rs2981578 were associated with overall breast cancer risk in southeast Chinese women, with the per-allele OR of 1.209 (95%CI: 1.064-1.372), 1.176 (95%CI: 1.048-1.320), and 0.852 (95%CI: 0.759-0.956), respectively. Rs12922061 and rs2290203 even passed the threshold for Bonferroni correction (P value: 0.00625). In stratified analysis, we found another three SNPs were significantly associated within different subgroups. However, after Bonferroni correction (P value: 0.000446), there were no statistically significant was observed. In gene-environment interaction analysis, we observed gene-environment interactions played a potential role of in the risk of breast cancer. These findings provide new insight into the associations between the genetic susceptibility and fine classifications of breast cancer. Based on these results, we encourage further large series studies and functional research to confirm these finding.
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