Literature DB >> 30191681

Evidence for PTGER4, PSCA, and MBOAT7 as risk genes for gastric cancer on the genome and transcriptome level.

Sophie K M Heinrichs1,2, Timo Hess1,2, Jessica Becker1,2, Lutz Hamann3, Yogesh K Vashist4, Katja Butterbach5, Thomas Schmidt6, Hakan Alakus7, Iurii Krasniuk8, Aksana Höblinger9, Philipp Lingohr10, Monika Ludwig11, Alexander F Hagel12, Claus W Schildberg13, Lothar Veits14, Ugne Gyvyte15, Katharina Weise1,2, Vitalia Schüller1,2,16, Anne C Böhmer1,2, Julia Schröder1,2, Jan Gehlen1,2, Nicole Kreuser17, Sebastian Hofer18, Hauke Lang18, Florian Lordick19, Peter Malfertheiner20, Markus Moehler21, Oliver Pech22, Nikolaos Vassos13, Ernst Rodermann23, Jakob R Izbicki4, Martin Kruschewski24, Katja Ott25, Ralf R Schumann3, Michael Vieth14, Elisabeth Mangold1,2, Evita Gasenko26,27, Limas Kupcinskas15, Hermann Brenner5,28,29, Peter Grimminger18, Luis Bujanda30,31, Federico Sopeña30,32,33, Jesús Espinel34, Concha Thomson35, Ángeles Pérez-Aísa36, Rafael Campo37, Fernando Geijo38, Daniela Collette39, Christiane Bruns7, Katharina Messerle7, Ines Gockel17, Markus M Nöthen1,2, Hans Lippert40, Karsten Ridwelski40,41, Angel Lanas30,32,33, Gisela Keller42, Michael Knapp16, Marcis Leja26,27, Juozas Kupcinskas15, Maria A García-González32,33,43, Marino Venerito20, Johannes Schumacher1,2,44.   

Abstract

Genetic associations between variants on chromosome 5p13 and 8q24 and gastric cancer (GC) have been previously reported in the Asian population. We aimed to replicate these findings and to characterize the associations at the genome and transcriptome level. We performed a fine-mapping association study in 1926 GC patients and 2012 controls of European descent using high dense SNP marker sets on both chromosomal regions. Next, we performed expression quantitative trait locus (eQTL) analyses using gastric transcriptome data from 143 individuals focusing on the GC associated variants. On chromosome 5p13 the strongest association was observed at rs6872282 (P = 2.53 × 10-04 ) and on chromosome 8q24 at rs2585176 (P = 1.09 × 10-09 ). On chromosome 5p13 we found cis-eQTL effects with an upregulation of PTGER4 expression in GC risk allele carrier (P = 9.27 × 10-11 ). On chromosome 8q24 we observed cis-eQTL effects with an upregulation of PSCA expression in GC risk allele carrier (P = 2.17 × 10-47 ). In addition, we found trans-eQTL effects for the same variants on 8q24 with a downregulation of MBOAT7 expression in GC risk allele carrier (P = 3.11 × 10-09 ). In summary, we confirmed and refined the previously reported GC associations at both chromosomal regions. Our data point to shared etiological factors between Asians and Europeans. Furthermore, our data imply an upregulated expression of PTGER4 and PSCA as well as a downregulated expression of MBOAT7 in gastric tissue as risk-conferring GC pathomechanisms.
© 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Entities:  

Keywords:  eQTL study; gene expression; genetic association study; stomach neoplasms

Mesh:

Substances:

Year:  2018        PMID: 30191681      PMCID: PMC6198243          DOI: 10.1002/cam4.1719

Source DB:  PubMed          Journal:  Cancer Med        ISSN: 2045-7634            Impact factor:   4.452


INTRODUCTION

The majority of gastric adenocarcinomas, here called gastric cancer (GC), is sporadic and has a multifactorial and heterogeneous etiology. According to its localization, GC is subdivided into a cardia and noncardia type and according to the histopathological classification of Lauren, GC is subdivided into a diffuse, intestinal or mixed type.1 On the etiological level, inflammation represents an important risk factor, which is mainly caused by Helicobacter pylori (H. pylori) infection.1 In multifactorial diseases, genome‐wide association studies (GWAS) have systematically led to the identification of risk loci involved in disease etiology. Accordingly, GWAS in GC have been carried out in the Asian population, which have led to the identification of risk loci on chromosome 1q22, 3q13, 5p13, 6p21, 7p15, 8q24, and 10q23.2, 3, 4, 5, 6 The risk loci on 5p137 and 8q248, 9 have been confirmed to contribute to GC development also in the European population. However, functional data on the underlying risk genes and on disease conferring pathomechanisms at these loci are scarce. Thus, we aimed to further confirm the role of 5p13 and 8q24 in the etiology of GC in Europeans and to characterize the associations on the genome and transcriptome level. However, it should be noted, that the locus on chromosome 1q22 was also independently replicated in an European GC sample under certain genetic models (dominant and recessive).10 Because no allelic association tests were presented in this study we did not follow up the association at the 1q22 locus.

MATERIALS AND METHODS

Samples

For the fine‐mapping association study at 5p13 and 8q24, we used a sample consisting of 1926 histopathologically confirmed GC patients (680 females, 1246 males) and 2012 ethnically matched controls (985 females, 1027 males) that were not screened for the presence of GC. All study subjects were of European descent and were recruited at four different study sites in Latvia, Lithuania, Spain and Germany. Table S1 provides sample details, including origin of samples and distribution of GC localization (cardia, noncardia) as well as Lauren type (diffuse, intestinal, and mixed). Informed consent was obtained from all participants and approval was obtained from the ethic board of each participating site. The expression quantitative trait locus (eQTL) analysis was based on 143 individuals of German descent (15 females, 128 males). All subjects were histopathologically diagnosed with intestinal metaplasia of the distal esophagus (Barrett's esophagous) and additionally, endoscopic biopsies of the gastric cardia were obtained during routine surveillance gastroscopies. Absence of pathological changes and H. pylori infection in the gastric mucosa was histopathologically confirmed for all cases. Informed consent was obtained from all participants as well as approval from the responsible ethic board.

Genotyping and expression analyses

For the fine‐mapping association study on 5p13 and 8q24, single‐nucleotide polymorphisms (SNPs) were selected for genotyping with the aim to impute a maximum number of genetic variants within both regions. To define the regions of interest the main recombination hotspots flanking both loci were determined using Haploview Version 4.2 and the HapMap dataset III (Release August 2010).11 Next, all SNPs with a minor allele frequency (MAF) of ≥5% on Illumina Human Core Exome Chip were used to reduce the number of necessary tagging SNPs within both regions. To prove that these SNPs cover the regions sufficiently an imputation on a genome‐wide genotyped test data set12 was performed. Finally, we used the test data set and ensured that all common publicly released SNPs within both regions were imputed with high imputation quality scores (INFO > 0.4). This resulted in 14 SNPs located within 5p13 and 6 SNPs within 8q24 (Table 1) as tagging markers for the respective loci. All 20 SNP markers were genotyped using a Sequenom MassARRAY iPlex Gold® system (Sequenom, San Diego, CA, USA). For quality control (QC), intra‐ and interplate duplicates were included. Furthermore, negative controls (H2O) were added to each 384 well plate in order to exclude contamination. Cluster plots of all SNPs were visually checked and manually corrected if necessary. The postgenotype QC comprised the exclusion of SNPs with Hardy‐Weinberg equilibrium (HWE) P < 1 × 10−04 in controls and P < 1 × 10−06 in patients, a call rate (CR) < 95% as well as exclusion of samples with a CR < 90%. A single marker (rs138377917 on chromosome 8q24) failed QC. Detailed information on primer sequences, genotyping and genotype calling is available upon request.
Table 1

Case‐control comparison (1926 GC cases, 2012 controls) of genotyped SNPs at chromosomal regions 5p13 and 8q24. One marker (rs138377917 on chromosome 8q24) failed QC and is not shown

SNPChrAllelea RR (95% CI)Combined P‐value
rs77169825 G/T1.06 (0.96‐1.16)2.31 × 10−01
rs68934305 C/T1.15 (1.03‐1.29)1.20 × 10−02
rs68611215 A/G1.07 (0.94‐1.23)3.07 × 10−01
rs77262375 G/A1.12 (1.02‐1.23)1.89 × 10−02
rs107379635 C/A1.08 (0.97‐1.19)1.60 × 10−01
rs125233295 C/T1.06 (0.96‐1.17)2.79 × 10−01
rs10024245 A/G1.16 (1.05‐1.29)3.09 × 10−03
rs2570095 C/T1.09 (0.99‐1.20)8.39 × 10−02
rs100536645 C/T1.06 (0.97‐1.16)2.23 × 10−01
rs133617075 C/T1.17 (1.06‐1.29)2.29 × 10−03
rs38054865 A/G1.13 (0.99‐1.29)6.20 × 10−02
rs4623665 T/C1.04 (0.94‐1.15)4.28 × 10−01
rs68763675 C/T1.12 (1.01‐1.24)2.70 × 10−02
rs22917825 A/G1.06 (0.96‐1.16)2.57 × 10−01
rs29764008 A/G1.04 (0.95‐1.15)3.70 × 10−01
rs29763928 A/G1.29 (1.18‐1.41)2.14 × 10−08
rs29763978 T/G1.30 (1.19‐1.42)7.18 × 10−09
rs121557588 A/G1.24 (1.13‐1.37)1.03 × 10−05
rs14354538 C/T1.23 (1.12‐1.34)6.98 × 10−06

Chr, chromosome; CI, confidence interval; RR, relative risk.

The underlined allele represents the GC risk allele.

Case‐control comparison (1926 GC cases, 2012 controls) of genotyped SNPs at chromosomal regions 5p13 and 8q24. One marker (rs138377917 on chromosome 8q24) failed QC and is not shown Chr, chromosome; CI, confidence interval; RR, relative risk. The underlined allele represents the GC risk allele. For the eQTL analysis DNA from 143 donors was extracted from peripheral blood and genotyped genome‐wide using Human OmniExpress‐v1.1 and HumanOmniExpressExome‐v1.2 BeadChips (Illumina, San Diego, CA, USA). The postgenotype QC comprised the exclusion of SNPs with HWE P < 1 × 10−05, minor allele frequency (MAF) <5% or a CR < 98% as well as the exclusion of samples with a CR < 99%. For the expression analysis, total RNA from gastric cardia biopsies was isolated using the AllPrep DNA/RNA Mini Kit (Qiagen, Hilden, Germany). The transcriptome was assessed using the HumanHT‐12v4 Expression BeadChip (Illumina) that targets more than 48 000 transcripts in the refseq database (Build 36.2, release 22). Only probes with a P detection < 0.01 in more than 5% of the samples were included for analysis. Furthermore, all probes were filtered for unique alignment and quality. Probes classified with a perfect or good quality as reported in the R package illuminaHumanv4.db were considered for further analysis.

Fine‐mapping and eQTL analyses

For the fine‐mapping association analysis, all genotyped SNPs were used for the imputation of additional markers at both regions. For this purpose, IMPUTE213 was used utilizing the 1000 Genomes Phase 3 data as reference.14 After imputation, all SNPs with an info score >0.7 were further processed, which resulted in 478 SNPs on 5p13 and 315 SNPs on 8q24. For each of the four study sites, association analysis of genotyped and imputed SNPs was performed by SNPTEST v2.5.15 A fixed‐effects meta‐analysis was performed to combine the results across study sites. We additionally performed genotype‐phenotype (GxP) analyses and stratified our cases according to tumor localization (cardia, noncardia) as well as histopathological Lauren type (diffuse, intestinal, or mixed). Moreover, pairwise linkage disequilibrium (LD) between markers was determined using SNAP16 and the 1000 Genomes Pilot 1 data from the European population.14 For the eQTL analysis genotypes of 568 265 autosomal SNPs and expression intensity data from 11 900 probes were used from all 143 probands. The expression data were quantile normalized and eQTLs were mapped using a linear regression model implemented in the MatrixEQTL R package.17 The associations were corrected for the top five principal components and eQTL effects with a false discovery rate (FDR) of <0.05 were considered as significant. In addition, eQTLs with a distance of <1 Mb to the corresponding probes were considered as cis‐regulatory variants. Vice versa, SNPs with a distance of >1 Mb to the corresponding probes were classified as trans‐eQTLs.

RESULTS

Association and eQTL findings on chromosome 5p13

Of all genotyped SNPs at 5p13 5 variants showed significant GC association (Table 1). Table S2 shows the association findings within each study site. The strongest association in the entire sample was observed for rs13361707 (P = 2.29 × 10−03, RR = 1.17 (95% CI = 1.06‐1.29)). The fine‐mapping at this region included 478 imputed SNPs, of which 28 showed GC association. The strongest association was observed for rs6872282 (P = 2.53 × 10−04, RR = 1.22 (95% CI = 1.09‐1.35), risk allele C, opposite allele T, see Table S3). Of note, rs13361707 and rs6872282 are in high LD with r 2 = 0.92. Figure 1A provides the regional association plot at 5p13 and shows that all associated variants encompass the coding regions of the genes PTGER4, TTC33, and PRKAA1. The GxP analysis at 5p13 using GC tumor localization and histopathological Lauren type as strata did not lead to an association improvement. Table S4 shows all GxP results for rs6872282, the strongest associated marker in the entire analysis. In addition, a conditional analysis using rs6872282 did not reveal any independent disease association (P > 0.5, data not shown).
Figure 1

Regional association plots of GC associations at chromosome 5p13 (A) and chromosome 8q24 (B). SNP association results are shown as ‐log P. The most significant associated SNP—rs6872282 at 5p13 (A), rs2585176 at 8q24 (B)—is shown as solid diamond. Pair‐wise correlation (r 2) between the most significant associated SNP and the other SNPs in a 500 kb flanking region is illustrated by the color scheme. The blue spikes show the estimated recombination rates. All annotated genes in both regions are shown at the bottom and their reading direction is given by arrows

Regional association plots of GC associations at chromosome 5p13 (A) and chromosome 8q24 (B). SNP association results are shown as ‐log P. The most significant associated SNP—rs6872282 at 5p13 (A), rs2585176 at 8q24 (B)—is shown as solid diamond. Pair‐wise correlation (r 2) between the most significant associated SNP and the other SNPs in a 500 kb flanking region is illustrated by the color scheme. The blue spikes show the estimated recombination rates. All annotated genes in both regions are shown at the bottom and their reading direction is given by arrows The eQTL analysis at 5p13 was initially restricted to SNPs with r 2 > 0.8 to the most associated GC variant and revealed cis‐eQTL effects for the expression of PTGER4 in gastric tissue (P = 9.27 × 10−11 for rs10074991). Here, an upregulated expression of the transcript was observed in GC risk allele carrier (Figure 2A). We then tested all 5p13 SNPs for PTGER4 eQTL effects, which revealed that rs10074991 represents the strongest eQTL for the expression of PTGER4 at this locus. Finally, we did not observe any trans‐eQTL effects using GC associated risk variants at 5p13 and an FDR < 0.05.
Figure 2

eQTL effects for GC associated variants at chromosomal regions 5p13 and 8q24. Log2 gene expression, error bars for median log2 expression and standard deviation are shown as box plot (y axis) sorted by SNP genotype (x‐axis) with the common allele on the left. The individual log2 gene expression is indicated by small dots in blue (y‐axis). A, cis‐eQTL (rs10074991, risk allele G) for the expression of PTGER4 at 5p13 (P = 9.27 × 10−11, regression slope (β) = −56.18). B, cis‐eQTL (rs2920283, risk allele C) for the expression of PSCA (P = 2.17 × 10−47, β = 3958.10). C, trans‐eQTL (rs2294008, risk allele T) for the expression of MBOAT7 (P = 1.99 × 10−09, β = −40.57)

eQTL effects for GC associated variants at chromosomal regions 5p13 and 8q24. Log2 gene expression, error bars for median log2 expression and standard deviation are shown as box plot (y axis) sorted by SNP genotype (x‐axis) with the common allele on the left. The individual log2 gene expression is indicated by small dots in blue (y‐axis). A, cis‐eQTL (rs10074991, risk allele G) for the expression of PTGER4 at 5p13 (P = 9.27 × 10−11, regression slope (β) = −56.18). B, cis‐eQTL (rs2920283, risk allele C) for the expression of PSCA (P = 2.17 × 10−47, β = 3958.10). C, trans‐eQTL (rs2294008, risk allele T) for the expression of MBOAT7 (P = 1.99 × 10−09, β = −40.57)

Association and eQTL findings on chromosome 8q24

Of all genotyped SNPs at 8q24 4 variants showed significant GC association (Table 1). Table S2 shows the association findings within each study site. The strongest association in the entire sample was observed for rs2976397 (P = 7.18 × 10−09, RR = 1.30 (95% CI = 1.19‐1.42)). The fine‐mapping at 8q24 included 315 imputed SNPs. Of them 42 SNPs showed GC association with rs2585176 being the most associated variant (P = 1.09 × 10−09, RR = 1.34 (95% CI = 1.22‐1.47), risk allele T, opposite allele A, see Table S3). Notably, rs2976397 and rs2585176 are in high LD with r 2 = 0.90. Figure 1B shows the regional association plot at 8q24 and shows that all associated variants are located close to the genes JRK, PSCA, and LY6K. The GxP analysis at 8q24 using GC tumor localization and histopathological Lauren type as strata did not lead to the identification of a particular GC subtype with predominant association. Table S5 shows all GxP results for rs2585176, the strongest associated marker in the entire analysis. In addition, a conditional analysis using rs2585176 did not reveal any independent disease association (P > 0.5, data not shown). The eQTL analysis at 8q24 was initially restricted to SNPs with r 2 > 0.8 to the most associated GC variant and revealed cis‐eQTL effects for the expression of PSCA (P = 2.17 × 10−47). The lead eQTL is rs2920283 and an upregulated PSCA expression in gastric tissue was observed in GC risk allele carrier (Figure 2B). As for 5p13, we then tested all 8q24 SNPs for PSCA eQTL effects, which revealed that rs2920283 represents the strongest eQTL for the expression of PSCA at this locus. Finally, we tested for trans‐eQTL effects using GC associated risk variants at 8q24 with r 2 > 0.8 to the lead GC SNP. Here, we observed a regulatory effect for the expression of MBOAT7 in gastric tissue, which is located on chromosome 19q13. The most significant trans‐eQTL was rs2294008 (P = 1.99 × 10−09) and led to a downregulated expression of MBOAT7 in GC risk allele carrier [Figure 2C]. Notably, the lead cis‐ and trans‐eQTLs are in perfect LD (r 2 = 1.00) pointing to a common regulatory effect. However, it should be noted that the statistical significance of the cis‐eQTL is much higher than for the trans‐eQTL.

DISCUSSION

The GC associations at 5p13 and 8q24 have been initially reported in the Asian population.2, 4 It has subsequently been shown that both loci also play a role in GC etiology in European populations.7, 8, 9 In the present study, we aimed to further replicate the GC association in the largest so far analyzed European cohort as well as to refine and characterize the association signals on the genome and transcriptome level. On chromosome 5p13 all GC associated variants were in high LD (r 2 > 0.8) to the most associated marker (rs6872282) and in high LD (r 2 > 0.8) to all risk SNPs previously reported at this locus in Asians2, 18, 19, 20, 21, 22, 23 and Europeans.7 Thus, together with previous findings, our data provide evidence that one or more of these SNPs represent(s) the true GC conferring variant(s) in both the Asian and European population. Of the implicated SNPs rs3805495 is in perfect LD to the leading GC risk variant rs6872282 (r 2 = 1) and represents an interesting functional SNP. According to RegulomeDB24 this variant is predicted to alter motifs for several transcription factors and to affect histone modification in digestive tissues including gastric mucosa. In addition, we found that the GC risk alleles of the associated SNPs lead to an upregulated PTGER4 expression in gastric tissue, which represents a plausible GC pathomechanism at this locus. To our knowledge, this eQTL effect has not been reported so far and thus needs further replication in independent gastric tissue samples. Also on the functional level, PTGER4 represents an interesting candidate for GC. The gene encodes the prostaglandin E2 (PGE2) receptor 4 (EP4), which mediates cellular responses to PGE2. PGE2 is derived from arachidonic acids through the enzymatic activity of cyclooxygenase‐2 (COX‐2). It has already been shown that the COX‐2/PGE2 pathway plays a key role in generation of the inflammatory microenvironment in GC and represents a downstream effector of Toll‐like receptor (TLR) activation that is—among others—triggered through H. pylori infection,25 the most prominent environmental GC risk factor. Interestingly, one study with H. pylori positive and negative GC cases and controls found a gene‐environment interaction between 5p13 risk SNPs and H. pylori infection that showed association with GC.18 Genetic variability at 5p13 also contributes to other diseases with inflammatory components, including Crohn's disease,26, 27, 28, 29, 30, 31 ulcerative colitis,32, 33, 34 ankylosing spondylitis35 and multiple sclerosis.36, 37, 38 Furthermore, cis‐regulatory effects involving the expression of PTGER4 in some of these traits have been described previously in lymphoblastoid cell lines.39 However, all SNPs and eQTLs implicated in these studies are only in weak LD (r 2 < 0.3) to the GC variants and PTGER4‐eQTLs identified in the present study (see Table S6). The findings point to PTGER4 as risk gene for different diseases with inflammatory components. However, more complex pathomechanisms with disease‐ and/or tissue‐specific effects on the PTGER4 expression regulation seem to be present at this locus. On chromosome 8q24 all GC associated variants were in high LD (r 2 > 0.8) to the most associated marker (rs2585176) and in high LD (r 2 > 0.8) to all risk SNPs previously reported at this locus in Asians and Europeans (summarized in Ref. 40). As for 5p13, this provides evidence that shared etiological factors between Asians and Europeans contribute to GC risk at this locus and that one or more of the identified SNPs represent(s) the true GC conferring variant(s). Of the implicated SNPs rs2294008 (C>T, Met1Thr) represents an interesting functional variant, which is located in the translation starting site of PSCA, is in high LD (r 2 = 0.86) with the lead GC SNP and also the strongest trans‐eQTL for the expression of MBOAT7 (see below). This SNP leads to an alternative PSCA splice form on the protein level41 and thus has been favored as true GC risk variant at this locus. In addition, rs2585183 represents an interesting functional variant according to RegulomeDB.24 The variant is in high LD to the leading GC risk SNP (r 2 = 0.90) and is predicted to affect histone modification in digestive tissues including gastric mucosa. Moreover, we found that the risk alleles of the GC associated markers lead to an upregulated expression of PSCA. The presence of this eQTL in gastric tissue is supported by GTEx (version 7, dbGaP accession phs000424.v7.p2), where the strongest eQTL in our study (rs2920283) shows cis‐regulatory effects for PSCA with P = 8.1 × 10−33. Furthermore, cis‐eQTL effects involving the presented variants and PSCA have been shown previously in healthy gastric and gastric tumor tissue.42 Thus, the PSCA eQTL has been independently validated and represents a plausible GC pathomechanism at 8q24. Also on the functional level PSCA represents an interesting candidate for GC development. The gene encodes a glycosylphosphatidylinositol‐anchored cell‐surface protein with highest expression in tumor cells and seems to play a role in multiple cellular processes, including immune‐modulation, cell adhesion, proliferation and survival.43 The PSCA risk alleles of the GC associated SNPs also mediate risk for chronic atrophic gastritis,9, 44 an H. pylori ‐induced precursor lesion of GC. In contrast, the opposite alleles at the same variants lead to duodenal ulcer,41, 44, 45, 46 which is also induced by H. pylori infection, but characterized by severe antral mucosa inflammation and protective GC effects.47, 48, 49 Thus, it has been hypothesized that gastric H. pylori infection leads to chronic atrophic gastritis and GC in patients with GC risk alleles at PSCA variants, whereas carrier of the opposite alleles tend to develop severe antral mucosa inflammation and duodenal ulcer.41, 44, 45, 46 The same regulatory variants on 8q24 that represent cis‐eQTLs for the expression of PSCA lead to a downstream downregulated MBOAT7 expression in gastric tissue, which suggests that MBOAT7 might be also of relevance in GC etiology. Interestingly, MBOAT7 encodes an enzyme with lysophosphatidylinositol acyltransferase activity and has been implicated in anti‐inflammatory processes through the regulation of arachidonic acid‐derived prostaglandin (PG) levels.50 Recently, it has been shown that MBOAT7 plays a pivotal role in hepatic inflammation and fibrosis in patients with hepatitis C infection51 and alcohol‐related liver cirrhosis.52 Thus, MBOAT7 might also contribute to GC susceptibility via biological pathways that are involved in inflammation. However, although the expression of PSCA and MBOAT7 is regulated by the same SNPs, a cellular connection between them has not been described so far. In conclusion, our study has confirmed the role of 5p13 and 8q24 in the etiology of GC in Europeans and has characterized the associations on the genome and transcriptome level. Whereas the eQTL effect of PSCA has been described before, the eQTL effects involving PTGER4 and MBOAT7 have not been described before in the context of GC. Future work is now required as to whether the same eQTL effects are present in the remaining gastric regions or other tissues with relevance in GC development. Additionally, functional work is required to prove that the observed eQTL effects play a role in GC development rather than represent epiphenomena with no relevance for GC development. In this context, our fine‐mapping association and eQTL study with altered gastric expression of PTGER4, PSCA, and MBOAT7 in GC risk allele carriers may serve as impetus.

CONFLICT OF INTEREST

None declared. Click here for additional data file.
  53 in total

1.  SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap.

Authors:  Andrew D Johnson; Robert E Handsaker; Sara L Pulit; Marcia M Nizzari; Christopher J O'Donnell; Paul I W de Bakker
Journal:  Bioinformatics       Date:  2008-10-30       Impact factor: 6.937

2.  A genome-wide association study on a southern European population identifies a new Crohn's disease susceptibility locus at RBX1-EP300.

Authors:  Antonio Julià; Eugeni Domènech; Elena Ricart; Raül Tortosa; Valle García-Sánchez; Javier P Gisbert; Pilar Nos Mateu; Ana Gutiérrez; Fernando Gomollón; Juan Luís Mendoza; Esther Garcia-Planella; Manuel Barreiro-de Acosta; Fernando Muñoz; Maribel Vera; Cristina Saro; Maria Esteve; Montserrat Andreu; Arnald Alonso; María López-Lasanta; Laia Codó; Josep Lluís Gelpí; Andres C García-Montero; Jaume Bertranpetit; Devin Absher; Julián Panés; Sara Marsal
Journal:  Gut       Date:  2012-08-30       Impact factor: 23.059

3.  A genome-wide association study confirms PNPLA3 and identifies TM6SF2 and MBOAT7 as risk loci for alcohol-related cirrhosis.

Authors:  Stephan Buch; Felix Stickel; Eric Trépo; Michael Way; Alexander Herrmann; Hans Dieter Nischalke; Mario Brosch; Jonas Rosendahl; Thomas Berg; Monika Ridinger; Marcella Rietschel; Andrew McQuillin; Josef Frank; Falk Kiefer; Stefan Schreiber; Wolfgang Lieb; Michael Soyka; Nasser Semmo; Elmar Aigner; Christian Datz; Renate Schmelz; Stefan Brückner; Sebastian Zeissig; Anna-Magdalena Stephan; Norbert Wodarz; Jacques Devière; Nicolas Clumeck; Christoph Sarrazin; Frank Lammert; Thierry Gustot; Pierre Deltenre; Henry Völzke; Markus M Lerch; Julia Mayerle; Florian Eyer; Clemens Schafmayer; Sven Cichon; Markus M Nöthen; Michael Nothnagel; David Ellinghaus; Klaus Huse; Andre Franke; Steffen Zopf; Claus Hellerbrand; Christophe Moreno; Denis Franchimont; Marsha Y Morgan; Jochen Hampe
Journal:  Nat Genet       Date:  2015-10-19       Impact factor: 38.330

4.  Genetic variations in the PRKAA1 and ZBTB20 genes and gastric cancer susceptibility in a Korean population.

Authors:  Hye-Rim Song; Hee Nam Kim; Sun-Seog Kweon; Jin-Su Choi; Hyun Jeong Shim; Sang Hee Cho; Ik Joo Chung; Young-Kyu Park; Soo Hyun Kim; Yoo-Duk Choi; Kyung Woong Joo; Min-Ho Shin
Journal:  Mol Carcinog       Date:  2013-07-17       Impact factor: 4.784

5.  Natural history of Helicobacter pylori infection.

Authors:  P Correa; M B Piazuelo
Journal:  Dig Liver Dis       Date:  2008-04-18       Impact factor: 4.088

6.  Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci.

Authors:  Philip L De Jager; Xiaoming Jia; Joanne Wang; Paul I W de Bakker; Linda Ottoboni; Neelum T Aggarwal; Laura Piccio; Soumya Raychaudhuri; Dong Tran; Cristin Aubin; Rebeccah Briskin; Susan Romano; Sergio E Baranzini; Jacob L McCauley; Margaret A Pericak-Vance; Jonathan L Haines; Rachel A Gibson; Yvonne Naeglin; Bernard Uitdehaag; Paul M Matthews; Ludwig Kappos; Chris Polman; Wendy L McArdle; David P Strachan; Denis Evans; Anne H Cross; Mark J Daly; Alastair Compston; Stephen J Sawcer; Howard L Weiner; Stephen L Hauser; David A Hafler; Jorge R Oksenberg
Journal:  Nat Genet       Date:  2009-06-14       Impact factor: 38.330

7.  Prostate stem-cell antigen gene is associated with diffuse and intestinal gastric cancer in Caucasians: results from the EPIC-EURGAST study.

Authors:  Núria Sala; Xavier Muñoz; Noemie Travier; Antonio Agudo; Eric J Duell; Víctor Moreno; Kim Overvad; Anne Tjonneland; Marie Christine Boutron-Ruault; Françoise Clavel-Chapelon; Federico Canzian; Rudolf Kaaks; Heiner Boeing; Karina Meidtner; Antonia Trichopoulos; Konstantine Tsiotas; Dimosthenis Zylis; Paolo Vineis; Salvatore Panico; Domenico Palli; Vittorio Krogh; Rosario Tumino; Eiliv Lund; H Bas Bueno-de-Mesquita; Mattjis E Numans; Petra H M Peeters; J Ramon Quirós; María-José Sánchez; Camen Navarro; Eva Ardanaz; Miren Dorronsoro; Göran Hallmans; Roger Stenling; Jonas Manjer; Naomi E Allen; Ruth C Travis; Kay-Tee Khaw; Mazda Jenab; G Johan A Offerhaus; Elio Riboli; Carlos A González
Journal:  Int J Cancer       Date:  2011-08-12       Impact factor: 7.396

8.  Additive interactions between PRKAA1 polymorphisms and Helicobacter pylori CagA infection associated with gastric cancer risk in Koreans.

Authors:  Sang-Yong Eom; Seon-Mi Hong; Dong-Hyuk Yim; Hyo-Jin Kwon; Dae-Hoon Kim; Hyo-Yung Yun; Young-Jin Song; Sei-Jin Youn; Taisun Hyun; Joo-Seung Park; Byung Sik Kim; Yong-Dae Kim; Heon Kim
Journal:  Cancer Med       Date:  2016-10-11       Impact factor: 4.452

Review 9.  Inflammation in gastric cancer: Interplay of the COX-2/prostaglandin E2 and Toll-like receptor/MyD88 pathways.

Authors:  Kanae Echizen; Osamu Hirose; Yusuke Maeda; Masanobu Oshima
Journal:  Cancer Sci       Date:  2016-03-18       Impact factor: 6.716

10.  Identification of new susceptibility loci for gastric non-cardia adenocarcinoma: pooled results from two Chinese genome-wide association studies.

Authors:  Zhaoming Wang; Juncheng Dai; Nan Hu; Xiaoping Miao; Christian C Abnet; Ming Yang; Neal D Freedman; Jinfei Chen; Laurie Burdette; Xun Zhu; Charles C Chung; Chuanli Ren; Sanford M Dawsey; Meilin Wang; Ti Ding; Jiangbo Du; Yu-Tang Gao; Rong Zhong; Carol Giffen; Wenting Pan; Woon-Puay Koh; Ningbing Dai; Linda M Liao; Caiwang Yan; You-Lin Qiao; Yue Jiang; Xiao-Ou Shu; Jiaping Chen; Chaoyu Wang; Hongxia Ma; Hua Su; Zhendong Zhang; Lemin Wang; Chen Wu; Yong-Bing Xiang; Zhibin Hu; Jian-Min Yuan; Lu Xie; Wei Zheng; Dongxin Lin; Stephen J Chanock; Yongyong Shi; Alisa M Goldstein; Guangfu Jin; Philip R Taylor; Hongbing Shen
Journal:  Gut       Date:  2015-12-23       Impact factor: 23.059

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  10 in total

1.  Development and validation of a novel lipid metabolism-related gene prognostic signature and candidate drugs for patients with bladder cancer.

Authors:  Ke Zhu; Liu Xiaoqiang; Wen Deng; Gongxian Wang; Bin Fu
Journal:  Lipids Health Dis       Date:  2021-10-27       Impact factor: 3.876

2.  International Union of Basic and Clinical Pharmacology. CIX. Differences and Similarities between Human and Rodent Prostaglandin E2 Receptors (EP1-4) and Prostacyclin Receptor (IP): Specific Roles in Pathophysiologic Conditions.

Authors:  Xavier Norel; Yukihiko Sugimoto; Gulsev Ozen; Heba Abdelazeem; Yasmine Amgoud; Amel Bouhadoun; Wesam Bassiouni; Marie Goepp; Salma Mani; Hasanga D Manikpurage; Amira Senbel; Dan Longrois; Akos Heinemann; Chengcan Yao; Lucie H Clapp
Journal:  Pharmacol Rev       Date:  2020-10       Impact factor: 25.468

3.  Gastritis Stages in Monozygotic and Dizygotic Dyspeptic Twins.

Authors:  Mindaugas Urba; Jurgita Skieceviciene; Dainius Janciauskas; Laimas Jonaitis; Limas Kupcinskas; Matteo Fassan; Massimo Rugge; Juozas Kupcinskas
Journal:  Gastroenterol Res Pract       Date:  2020-07-02       Impact factor: 2.260

4.  Evidence for PTGER4, PSCA, and MBOAT7 as risk genes for gastric cancer on the genome and transcriptome level.

Authors:  Sophie K M Heinrichs; Timo Hess; Jessica Becker; Lutz Hamann; Yogesh K Vashist; Katja Butterbach; Thomas Schmidt; Hakan Alakus; Iurii Krasniuk; Aksana Höblinger; Philipp Lingohr; Monika Ludwig; Alexander F Hagel; Claus W Schildberg; Lothar Veits; Ugne Gyvyte; Katharina Weise; Vitalia Schüller; Anne C Böhmer; Julia Schröder; Jan Gehlen; Nicole Kreuser; Sebastian Hofer; Hauke Lang; Florian Lordick; Peter Malfertheiner; Markus Moehler; Oliver Pech; Nikolaos Vassos; Ernst Rodermann; Jakob R Izbicki; Martin Kruschewski; Katja Ott; Ralf R Schumann; Michael Vieth; Elisabeth Mangold; Evita Gasenko; Limas Kupcinskas; Hermann Brenner; Peter Grimminger; Luis Bujanda; Federico Sopeña; Jesús Espinel; Concha Thomson; Ángeles Pérez-Aísa; Rafael Campo; Fernando Geijo; Daniela Collette; Christiane Bruns; Katharina Messerle; Ines Gockel; Markus M Nöthen; Hans Lippert; Karsten Ridwelski; Angel Lanas; Gisela Keller; Michael Knapp; Marcis Leja; Juozas Kupcinskas; Maria A García-González; Marino Venerito; Johannes Schumacher
Journal:  Cancer Med       Date:  2018-09-06       Impact factor: 4.452

5.  Bioinformatics analysis of microarray data to identify the candidate biomarkers of lung adenocarcinoma.

Authors:  Tingting Guo; Hongtao Ma; Yubai Zhou
Journal:  PeerJ       Date:  2019-07-10       Impact factor: 2.984

6.  A Novel Diagnosis Method Based on Methylation Analysis of SHOX2 and Serum Biomarker for Early Stage Lung Cancer.

Authors:  Wenhai Huang; Hao Huang; Shuishen Zhang; Xueping Wang; Juan Ouyang; Zhichao Lin; Peisong Chen
Journal:  Cancer Control       Date:  2020 Jan-Dec       Impact factor: 3.302

7.  Risk Signature Related to Immunotherapy Reaction of Hepatocellular Carcinoma Based on the Immune-Related Genes Associated With CD8+ T Cell Infiltration.

Authors:  Yiping Zou; Zhihong Chen; Hongwei Han; Shiye Ruan; Liang Jin; Yuanpeng Zhang; Zhengrong Chen; Zuyi Ma; Qi Lou; Ning Shi; Haosheng Jin
Journal:  Front Mol Biosci       Date:  2021-03-19

8.  SNP rs2920280 in PSCA Is Associated with Susceptibility to Gastric Mucosal Atrophy and Is a Promising Biomarker in Japanese Individuals with Helicobacter pylori Infection.

Authors:  Hajime Isomoto; Takuki Sakaguchi; Tatsuo Inamine; Shintaro Takeshita; Daisuke Fukuda; Ken Ohnita; Tsutomu Kanda; Kayoko Matsushima; Tetsuro Honda; Takaaki Sugihara; Tatsuro Hirayama; Kazuhiko Nakao; Kazuhiro Tsukamoto
Journal:  Diagnostics (Basel)       Date:  2022-08-16

9.  Gastric cancer in autoimmune gastritis: A case-control study from the German centers of the staR project on gastric cancer research.

Authors:  Friederike Weise; Michael Vieth; Dirk Reinhold; Johannes Haybaeck; Elisabetta Goni; Hans Lippert; Karsten Ridwelski; Philipp Lingohr; Claus Schildberg; Nikolaos Vassos; Martin Kruschewski; Iurii Krasniuk; Peter P Grimminger; Oliver Waidmann; Ulrich Peitz; Lothar Veits; Nicole Kreuser; Hauke Lang; Christiane Bruns; Markus Moehler; Florian Lordick; Ines Gockel; Johannes Schumacher; Peter Malfertheiner; Marino Venerito
Journal:  United European Gastroenterol J       Date:  2019-11-26       Impact factor: 4.623

10.  Identification and Validation of an Energy Metabolism-Related lncRNA-mRNA Signature for Lower-Grade Glioma.

Authors:  Jingwei Zhao; Le Wang; Bo Wei
Journal:  Biomed Res Int       Date:  2020-07-27       Impact factor: 3.411

  10 in total

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