Role of Polymorphisms of FAM13A, PHLDB1, and CYP24A1 in Breast Cancer Risk

Author(s): Ying Wei, Xiaolin Wang, Zhe Zhang, Mingrui Xie, Yuyao Li, Hongxin Cao, Xinhan Zhao*

Journal Name: Current Molecular Medicine

Volume 19 , Issue 8 , 2019

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Background: Single-nucleotide polymorphisms (SNPs) are important indicators of susceptibility to breast cancer.

Objective: To assess the associations between SNPs in the FAM13A, PHLDB1, and CYP24A1 gene and breast cancer risk in the Chinese Han population.

Methods: We performed a case-control study including 379 female breast cancer patients and 407 female healthy controls. The three SNPs were genotyped using Agena MassARRAY platform. The χ2 test was used to compare alleles and genotypes frequencies of polymorphisms between case and control groups. Genetic models analyses to assess the associations between SNPs and breast cancer risk by computing odds ratios (ORs) and 95% confidence intervals (CIs) using logistic regression. RegulomeDB and HaploReg databases were used to calculate possible functional effects of polymorphisms.

Results: Overall analysis results showed that rs4809957 was associated with an increased risk of breast cancer (allele A: OR = 1.27, 95% CI: 1.03-1.55, p = 0.024; AA vs. GG: OR = 1.80, 95% CI: 1.15–2.82, p = 0.010; recessive model: OR = 1.70, 95% CI: 1.12–2.58, p = 0.012); and rs1059122 was found to be associated with a reduced breast cancer risk in the recessive model (OR = 0.71, 95% CI: 0.51–0.98, p = 0.039). Stratification analysis found significant associations between the three SNPs (rs1059122, rs17748, and rs4809957) and breast cancer risk.

Conclusion: Our results suggested that rs1059122 (FAM13A), rs17748 (PHLDB1), and rs4809957 (CYP24A1) might contribute to breast cancer susceptibility in the Chinese Han population. Future studies with large samples are required to confirm our findings, as well as functional studies are needed to explore their function in the breast cancer development.

Keywords: Breast Neoplasms, FAM13A, PHLDB1, CYP24A1, single nucleotide polymorphisms, cancer.

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Article Details

Year: 2019
Published on: 05 September, 2019
Page: [579 - 588]
Pages: 10
DOI: 10.2174/1566524019666190619125109
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