Variants in Notch signalling pathway genes, PSEN1 and MAML2, predict overall survival in Chinese patients with epithelial ovarian cancer.
Abstract
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.
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https://hdl.handle.net/10161/18499Published Version (Please cite this version)
10.1111/jcmm.13764Publication Info
Xu, Yuan; Cheng, Lei; Dai, Hongji; Zhang, Ruoxin; Wang, Mengyun; Shi, Tingyan; ...
Wei, Qingyi (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.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Qingyi Wei
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

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