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A systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk.
Ye, Zhuo-Miao; Li, Li-Juan; Luo, Ming-Bo; Qing, Hong-Yuan; Zheng, Jing-Hui; Zhang, Chi; Lu, Yun-Xin; Tang, You-Ming.
Afiliação
  • Ye ZM; Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China; Ruikang School of Clinical Medicine, Guangxi University of Chinese Medicine, Nanning 530001, China.
  • Li LJ; Ruikang School of Clinical Medicine, Guangxi University of Chinese Medicine, Nanning 530001, China.
  • Luo MB; The First Clinical Faculty of Guangxi University of Chinese Medicine, Guangxi University of Chinese Medicine, Nanning 530222, China.
  • Qing HY; Ruikang School of Clinical Medicine, Guangxi University of Chinese Medicine, Nanning 530001, China.
  • Zheng JH; Ruikang School of Clinical Medicine, Guangxi University of Chinese Medicine, Nanning 530001, China.
  • Zhang C; Department of Cardiology, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning 530011, China.
  • Lu YX; Graduate School, Guangxi University of Chinese Medicine, Nanning 530001, Guangxi, China.
  • Tang YM; Department of Oncology, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning 530011, China.
Aging (Albany NY) ; 12(24): 25256-25274, 2020 11 20.
Article em En | MEDLINE | ID: mdl-33226370
ABSTRACT
In this meta-analysis, we systematically investigated the correlation between single nucleotide polymorphisms (SNPs) and pancreatic cancer (PC) risk. We searched PubMed, Network Science, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Science and Technology Periodical Database (VIP), and Wanfang databases up to January 2020 for studies on PC risk-associated SNPs. We identified 45 case-control studies (36,360 PC patients and 54,752 non-cancer individuals) relating to investigations of 27 genes and 54 SNPs for this meta-analysis. Direct meta-analysis followed by network meta-analysis and Thakkinstian algorithm analysis showed that homozygous genetic models for CTLA-4 rs231775 (OR =0.326; 95% CI 0.218-0.488) and VDR rs2228570 (OR = 1.976; 95% CI 1.496-2.611) and additive gene model for TP53 rs9895829 (OR = 1.231; 95% CI 1.143-1.326) were significantly associated with PC risk. TP53 rs9895829 was the most optimal SNP for diagnosing PC susceptibility with a false positive report probability < 0.2 at a stringent prior probability value of 0.00001. This systematic review and meta-analysis suggest that TP53 rs9895829, VDR rs2228570, and CTLA-4 rs231775 are significantly associated with PC risk. We also demonstrate that TP53 rs9895829 is a potential diagnostic biomarker for estimating PC risk.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Pancreáticas / Proteína Supressora de Tumor p53 / Receptores de Calcitriol / Predisposição Genética para Doença / Antígeno CTLA-4 Tipo de estudo: Etiology_studies / Observational_studies / Risk_factors_studies / Systematic_reviews Limite: Humans Idioma: En Revista: Aging (Albany NY) Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Pancreáticas / Proteína Supressora de Tumor p53 / Receptores de Calcitriol / Predisposição Genética para Doença / Antígeno CTLA-4 Tipo de estudo: Etiology_studies / Observational_studies / Risk_factors_studies / Systematic_reviews Limite: Humans Idioma: En Revista: Aging (Albany NY) Ano de publicação: 2020 Tipo de documento: Article