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A systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk

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...

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Autores principales: Ye, Zhuo-Miao, Li, Li-Juan, Luo, Ming-Bo, Qing, Hong-Yuan, Zheng, Jing-Hui, Zhang, Chi, Lu, Yun-Xin, Tang, You-Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803556/
https://www.ncbi.nlm.nih.gov/pubmed/33226370
http://dx.doi.org/10.18632/aging.104128
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author Ye, Zhuo-Miao
Li, Li-Juan
Luo, Ming-Bo
Qing, Hong-Yuan
Zheng, Jing-Hui
Zhang, Chi
Lu, Yun-Xin
Tang, You-Ming
author_facet Ye, Zhuo-Miao
Li, Li-Juan
Luo, Ming-Bo
Qing, Hong-Yuan
Zheng, Jing-Hui
Zhang, Chi
Lu, Yun-Xin
Tang, You-Ming
author_sort Ye, Zhuo-Miao
collection PubMed
description 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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spelling pubmed-78035562021-01-15 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 Aging (Albany NY) Research Paper 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. Impact Journals 2020-11-20 /pmc/articles/PMC7803556/ /pubmed/33226370 http://dx.doi.org/10.18632/aging.104128 Text en Copyright: © 2020 Ye et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Ye, Zhuo-Miao
Li, Li-Juan
Luo, Ming-Bo
Qing, Hong-Yuan
Zheng, Jing-Hui
Zhang, Chi
Lu, Yun-Xin
Tang, You-Ming
A systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk
title A systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk
title_full A systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk
title_fullStr A systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk
title_full_unstemmed A systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk
title_short A systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk
title_sort systematic review and network meta-analysis of single nucleotide polymorphisms associated with pancreatic cancer risk
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803556/
https://www.ncbi.nlm.nih.gov/pubmed/33226370
http://dx.doi.org/10.18632/aging.104128
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