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Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
Published on: January 12, 2020
Ovarian cancer variant rs2072590 is associated with HOXD1 and HOXD3 gene expression
Liyuan Guo1, Yan Peng2, Lei Sun3
1Department of Gynecological Oncology, Cancer Hospital of Harbin Medical University, Harbin, China.
Abstract:
Ovarian cancer (OC) is a common cancer in women and the leading cause of deaths from gynaecological malignancies in the world. In addition to the candidate gene approach to identify OC susceptibility genes, the genome-wide association study (GWAS) methods have reported new variants that are associated with OC risk. The minor allele of rs2072590 at 2q31 was associated with an increased OC risk, and was primarily significant for serous subtype. The OC risk-associated SNP rs2072590 lies in non-coding DNA downstream of HOXD3 and upstream of HOXD1, and it tags SNPs in the HOXD3 3' UTR. We think that the non-coding rs2072590 variant may contribute to OC susceptibility by regulating the gene expression of HOXD1 and HOXD3. In order to investigate this association, we performed a bioinformatics analysis by a functional annotation of rs2072590 variant using RegulomeDB (version 1.1), HaploReg (version 4.1), and PhenoScanner (version 1.1). Using HaploReg, we identified 19 genetic variants tagged by rs2072590 variant with with r2 >= 0.8. Using RegulomeDB, we identified that three genetic variants are likely to affect TF binding + any motif + DNase Footprint + DNase peak. Other genetic variants are likely to affect TF binding + DNase peak. Using PhenoScanner (version 1.1), we identified that these 19 genetic variants could significantly regulate the expression of nearby genes, especially the HOXD1 and HOXD3 in human ovary tissue.
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