Variants in Notch signalling pathway genes, PSEN1 and MAML2, predict overall survival in Chinese patients with epithelial ovarian cancer.
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To identify genetic variants in Notch signalling pathway genes that may predict survival of Han Chinese patients with epithelial ovarian cancer (EOC), we analysed a total of 1273 single nucleotide polymorphisms (SNPs) within 75 Notch genes in 480 patients from a published EOC genomewide association study (GWAS). We found that PSEN1 rs165934 and MAML2 rs76032516 were associated with overall survival (OS) of patients by multivariate Cox proportional hazards regression analysis. Specifically, the PSEN1 rs165934 AA genotype was associated with a poorer survival (adjusted hazards ratio [adjHR] = 1.41, 95% CI = 1.07-1.84, and P = .014), compared with the CC + CA genotype, while MAML2 rs76032516 AA + AC genotypes were associated with a poorer survival (adjHR = 1.58, 95% CI = 1.16-2.14, P = .004), compared with the CC genotype. The combined analysis of these two SNPs revealed that the death risk increased as the number of unfavourable genotypes increased in a dose-dependent manner (Ptrend < .001). Additionally, the expression quantitative trait loci analysis revealed that the SNP rs165932 in the rs165934 LD block (r2 = .946) was associated with expression levels of PSEN1, which might be responsible for the observed association with SNP rs165934. The associations of PSEN1 rs165934 and MAML2 rs76032516 of the Notch signalling pathway genes with OS in Chinese EOC patients are novel findings, which need to be validated in other large and independent studies.
Published Version (Please cite this version)10.1111/jcmm.13764
Publication InfoWei, Qingyi; Xu, Yuan; Cheng, Lei; Dai, Hongji; Zhang, Ruoxin; Wang, Mengyun; ... Cheng, Xi (2018). Variants in Notch signalling pathway genes, PSEN1 and MAML2, predict overall survival in Chinese patients with epithelial ovarian cancer. Journal of cellular and molecular medicine, 22(10). pp. 4975-4984. 10.1111/jcmm.13764. Retrieved from https://hdl.handle.net/10161/18499.
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Professor in Population Health Sciences
Qingyi Wei, MD, PhD, Professor in the Department of Medicine, is Associate Director for Cancer Control and Population Sciences, Co-leader of CCPS and Co-leader of Epidemiology and Population Genomics (Focus Area 1). He is a professor of Medicine and an internationally recognized epidemiologist focused on the molecular and genetic epidemiology of head and neck cancers, lung cancer, and melanoma. His research focuses on biomarkers and genetic determinants for the DNA repair deficient phenotype and