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

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.

Keywords: FPRP; network meta-analysis; pancreatic cancer; single nucleotide polymorphisms.

Figure 1

Network meta-analysis results for the genetic models of the PC risk-related SNPs. The figure shows the network meta-analysis results for the (1) Allele (2) Homozygous (3) Heterozygous (4) Dominant (5) Recessive and (6) Additive genetic models of the following SNPs: (C) XPC rs2607775; (D) XPC rs2228001; (K) ERCC2 rs13181; (L) ERCC1 rs3212986; (V) ABO rs657152; (W) ABO rs505922; (X) ABO rs495828; (V) ABO rs657152; (N) COX2-765; (O) COX2-1195; (H) MUM1L1-CXorf57 rs379742; (I) MORC4 rs12837024; (d) HIF-1α G1790A rs11549467; (e) HIF-1α C1772T rs11549465; (P) CDKN2A/B rs3731249; (Q) CDKN2A/B rs3731211; (R) CDKN2A/B rs3218009; (S) CDKN2A/B rs3217992; (T) CDKN2A/B rs2518719; (U) CDKN2A/B rs1063192; (Y) CDKN2A/B rs1063192; (A) XRCC4 rs2075685; (B) XRCC1 rs25487; (F) VDR rs2228570; (G) TP53 rs9895829; (M) CTLA-4 rs231775; (E) VEGF +405 rs2010963; (c) MTHFR rs1801133; (J) FTO rs9939609; (b) TERT rs2853677. D.

Figure 2

Rank probabilities for the six genetic models of the SNPs related to PC risk. The rank probabilities for the allele (1), homozygous (2), heterozygous (3), dominant (4), recessive (5) and additive (6) genetic models for the following SNPs: (C) XPC rs2607775; (D) XPC rs2228001; (K) ERCC2 rs13181; (L) ERCC1 rs3212986; (V) ABO rs657152; (W) ABO rs505922; (X) ABO rs495828; (V) ABO rs657152; (N) COX2-765; (O) COX2-1195; (H) MUM1L1-CXorf57 rs379742; (I) MORC4 rs12837024; (d) HIF1α-G1790A rs11549467; (e) HIF1α-C1772T rs11549465; (P) CDKN2A/B rs3731249; (Q) CDKN2A/B rs3731211; (R) CDKN2A/B rs3218009; (S) CDKN2A/B rs3217992; (T) CDKN2A/B rs2518719; (U) CDKN2A/B rs1063192; (Y) CDKN2A/B rs1063192; (A) XRCC4 rs2075685; (B) XRCC1 rs25487; (F) VDR rs2228570; (G) TP53 rs9895829; (M) CTLA-4 rs231775; (E) VEGF +405 rs2010963; (c) MTHFR rs1801133; (J) FTO rs9939609; (b) TERT rs2853677. Note: Genetic model of an SNP with best mean probability is considered the optimal genetic model.

Figure 3

PRISMA flow diagram of study search and selection.