# PLCE1 Polymorphisms and Risk of Esophageal and Gastric Cancer in a Northwestern Chinese Population

Authors: Ping Liang; Wentao Zhang; Weihua Wang; Peng Dai; Qin Wang; Wei Yan; Wei Wang; Xiaoying Lei; Daxiang Cui; Zhen Yan
Journal: BioMed Research International
 (2019)

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## Abstract

The reported risk susceptibility betweenphospholipase C epsilon 1 (PLCE1)polymorphisms and esophageal cancer (EC) and gastric cancer (GC) remained inconsistent and controversial, especially on variants other than rs2274223. The relationship betweenPLCE1 polymorphisms and gene expression is also unclear. Here we conducted a case-control study from northwest China, genotyped seven tag single nucleotide polymorphisms (SNPs) inPLCE1 with multiplexed SNP MassARRAY assay. Stratified analysis was carried out andPLCE1 expression was evaluated in specified groups with the method of qRT-PCR and immunohistochemistry. Results showed that the minor alleles of rs3765524, rs2274223, and rs10509670 were associated with increased risk of EC and GC. Linkage disequilibrium analysis revealed protective haplotypes of CCAAGTC and CCAA. By stratification, a more significant association was found in subgroups of male, age ≥ 54, tumor stages of I-II and tumor size ≤ 5 cm, EC and cardia cancer (CC) of stomach, and moderate to well differentiated squamous carcinoma. In addition, a significant association for rs3765524 with noncardia cancer (NCC) and adenocarcinoma which is predominant in China was also observed. Further expression analysis identified thatPLCE1 was downregulated in NCC tissues comparing to their adjacent noncancerous tissues, and its protein expression was higher in genotype rs3765524 CT/TT than in rs3765524 CC. In summary, our study suggests thatPLCE1 polymorphisms may affect its gene expression and are associated with not only EC and CC, but also, to some extent, NCC risk in this study population.


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## Body

## 1. Introduction

Esophageal cancer (EC) and gastric cancer (GC) are the two most common cancers originating from digestive tract around world [1], especially in China [2, 3]. There are many differences between EC and GC, such as genetic background, histological type, andHelicobacter pylori infection, while they are both known to be the results of complex interactions between inherited and environmental factors [4, 5].Phospholipase C epsilon 1 (PLCE1) gene was reported to locate at 10q23, encoding a member of the human phosphoinositide-specific phospholipase C family [6]. It has been involved in the regulation of cell growth, differentiation, and oncogenesis [7]. Genome wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs), mostly rs2274223 A>G, and rs3765524 C>T inPLCE1 gene as shared susceptibility loci for EC and GC [8–10].Although several independent candidate-gene studies have confirmed the association between EC, GC, andPLCE1 SNPs subsequently, there is more limited data on variants other than rs2274223, especially for GC [11–24]. Moreover, whether these loci are associated with noncardia cancer in addition to cardia and esophageal is not clear; whether or notPLCE1 polymorphisms affect gene expression and protein function were only reported in few contradictory results [9, 14, 15, 23, 25–28].To further explore the association betweenPLCE1 polymorphisms and risk of EC and GC or their subtypes, we collected blood samples from Chinese northwestern population and used multiplexed SNP MassARRAY assay to sequence a panel of tag SNPs (tSNPs) ofPLCE1 in a case-control study. We completed a comprehensive analysis by logistic regression and stratification method and examined the expression ofPLCE1 in tissue samples.


## 2. Material and Methods

### 2.1. Study Population

A total of 324 GC or EC patients and 357 control volunteer individuals without known malignancies in the Xijing hospital of the Fourth Military Medical University in Xi’an city, China, during 2009 to 2012 were enrolled in the study. The cases had no previous history of other cancers, or prior chemotherapy or radiotherapy. All of the chosen subjects were Chinese Han living in Xi’an city and its surrounding areas. Generally, subjects with chronic diseases and conditions involving vital organs (heart, lung, liver, kidney, and brain) and severe endocrinological, metabolic, and nutritional diseases were excluded from this study. The purpose of the above exclusion procedures was to minimize the known environmental and therapeutic factors that influence the variation of human complex diseases. Peripheral blood samples from GC and EC patients were collected before or after surgery. Formalin-fixed, paraffin-embedded cancer and paired adjacent noncancerous tissues were collected after surgery from part of the GC patients. Patients’ clinical data and postoperative pathological reports including the pathological types, pTNM and clinical stages, and the degrees of tumor differentiation were indexed from medical records. The study was approved by the Ethical Committee of Xijing Hospital (Xi’an, China), and this study complied with the World Medical Association Declaration of Helsinki. Informed consent was given by all the subjects for participation in this study.


### 2.2. DNA Isolation and Genotyping Assays

A panel of seven tSNPs of rs3765524, rs3818432, rs2274223, rs10509670, rs11187852, rs3781264, and rs11187866 inPLCE1 gene were included in this study. All the SNPs have a disequilibrium (D′) threshold of 0.8 and minor allele frequency (MAF) > 0.05 in the HapMap Chinese Han population. Genomic DNA was extracted from peripheral blood using a Blood DNA Extraction Kit (TIANGEN, China), quantified with NanoDrop 2000 (Thermo, USA) and stored at −20°C until use. Primers were designed in a multiplexed SNP MassEXTEND assay with the Sequenom MassARRAY Assay Design 3.0 Software. SNP genotyping was performed by Sequenom MassARRAY RS1000 as reported previously [29]. Data management was conducted and analyzed by Sequenom Typer 4.0 Software.


### 2.3. Quantitative Real-Time PCR

Total RNA was extracted from tissue samples with E.Z.N.A.TM FFPE RNA Kit (OMEGA, USA). The protocol of total RNA isolation, cDNA preparation, and qRT-PCR was as reported previously by using the PrimeScriptTM RT Master Mix (Takara, Japan) on a 7500 fast real-time PCR system (Applied Biosystems) [29]. We used the following primers covering the twoPLCE1 spliceosomes, respectively:PLCE1A, forward 5′-ATCATAGAGACAGGCAGAGCACA-3′ and reverse 5′-ATGCCACATAGTTTTTCTTTTGC-3′;PLCE1B, forward 5′-GATTAATGGTTTCAGAAGGAAGTGC-3′ and reverse 5′- CTCCAGCATCCACATCCATCC-3′. Humanβ-actinwas used as an endogenous control. For each sample, we calculated the difference in threshold cycles for eachPLCE1copy by the 2-ΔCT method.


### 2.4. Immunohistochemistry Staining

The procedure of immunochemistry staining has been described in our previous publication [29]. Paraffin-embedded tissue specimens were deparaffinized in xylene and then soaked in ethanol and then PBS. We performed antigen retrieval in 100 mM sodium citrate buffer at 100°C for 20 min. Subsequently, we blocked endogenous peroxidase activity in 3% hydrogen peroxide in methanol for 15 min and then blocked nonspecific binding in 5% normal goat serum overnight at 4°C. We incubated sections for 2 hours at room temperature with rabbit anti-PLCE1 (SIGMA, HPA015598, 1:20 dilution) antibody, and then with alkaline phosphatase conjugated anti-rabbit IgG antibody. We visualized PLCE1 protein by Histostain™–Plus Kits (ZYMED, SP-9001). At least three experienced pathologists examined the staining using the following criteria: strong positive (signal in the cancer cells is stronger than the normal gastric gland), positive (signal in the cancer cells is as strong as that in a normal gastric gland), weak positive (signal between positive and negative), and negative (signal is no more than the background signal in the surrounding stromal cells).


### 2.5. Statistical Analysis

We performed statistical analysis using Microsoft Excel and SPSS 16.0 statistical package (SPSS, Chicago, IL). AllP values in this study were two-sided. We consideredP ≤ 0.05 the threshold for statistical significance. We tested genotypic frequencies in control subjects for each SNP for departure from HWE using an exact test. We compared genotype frequencies of case and control subjects using the Chi2 test. We calculated OR and 95% CI by unconditional logistic regression analysis. There were two factors of age and gender adjusted for the analysis. We used the Haploview program to estimate the pairwise LD between markers and partition haplotype blocks. We inferred haplotypes using the Haploview software package (version 4.2).


## 2.1. Study Population

A total of 324 GC or EC patients and 357 control volunteer individuals without known malignancies in the Xijing hospital of the Fourth Military Medical University in Xi’an city, China, during 2009 to 2012 were enrolled in the study. The cases had no previous history of other cancers, or prior chemotherapy or radiotherapy. All of the chosen subjects were Chinese Han living in Xi’an city and its surrounding areas. Generally, subjects with chronic diseases and conditions involving vital organs (heart, lung, liver, kidney, and brain) and severe endocrinological, metabolic, and nutritional diseases were excluded from this study. The purpose of the above exclusion procedures was to minimize the known environmental and therapeutic factors that influence the variation of human complex diseases. Peripheral blood samples from GC and EC patients were collected before or after surgery. Formalin-fixed, paraffin-embedded cancer and paired adjacent noncancerous tissues were collected after surgery from part of the GC patients. Patients’ clinical data and postoperative pathological reports including the pathological types, pTNM and clinical stages, and the degrees of tumor differentiation were indexed from medical records. The study was approved by the Ethical Committee of Xijing Hospital (Xi’an, China), and this study complied with the World Medical Association Declaration of Helsinki. Informed consent was given by all the subjects for participation in this study.


## 2.2. DNA Isolation and Genotyping Assays

A panel of seven tSNPs of rs3765524, rs3818432, rs2274223, rs10509670, rs11187852, rs3781264, and rs11187866 inPLCE1 gene were included in this study. All the SNPs have a disequilibrium (D′) threshold of 0.8 and minor allele frequency (MAF) > 0.05 in the HapMap Chinese Han population. Genomic DNA was extracted from peripheral blood using a Blood DNA Extraction Kit (TIANGEN, China), quantified with NanoDrop 2000 (Thermo, USA) and stored at −20°C until use. Primers were designed in a multiplexed SNP MassEXTEND assay with the Sequenom MassARRAY Assay Design 3.0 Software. SNP genotyping was performed by Sequenom MassARRAY RS1000 as reported previously [29]. Data management was conducted and analyzed by Sequenom Typer 4.0 Software.


## 2.3. Quantitative Real-Time PCR

Total RNA was extracted from tissue samples with E.Z.N.A.TM FFPE RNA Kit (OMEGA, USA). The protocol of total RNA isolation, cDNA preparation, and qRT-PCR was as reported previously by using the PrimeScriptTM RT Master Mix (Takara, Japan) on a 7500 fast real-time PCR system (Applied Biosystems) [29]. We used the following primers covering the twoPLCE1 spliceosomes, respectively:PLCE1A, forward 5′-ATCATAGAGACAGGCAGAGCACA-3′ and reverse 5′-ATGCCACATAGTTTTTCTTTTGC-3′;PLCE1B, forward 5′-GATTAATGGTTTCAGAAGGAAGTGC-3′ and reverse 5′- CTCCAGCATCCACATCCATCC-3′. Humanβ-actinwas used as an endogenous control. For each sample, we calculated the difference in threshold cycles for eachPLCE1copy by the 2-ΔCT method.


## 2.4. Immunohistochemistry Staining

The procedure of immunochemistry staining has been described in our previous publication [29]. Paraffin-embedded tissue specimens were deparaffinized in xylene and then soaked in ethanol and then PBS. We performed antigen retrieval in 100 mM sodium citrate buffer at 100°C for 20 min. Subsequently, we blocked endogenous peroxidase activity in 3% hydrogen peroxide in methanol for 15 min and then blocked nonspecific binding in 5% normal goat serum overnight at 4°C. We incubated sections for 2 hours at room temperature with rabbit anti-PLCE1 (SIGMA, HPA015598, 1:20 dilution) antibody, and then with alkaline phosphatase conjugated anti-rabbit IgG antibody. We visualized PLCE1 protein by Histostain™–Plus Kits (ZYMED, SP-9001). At least three experienced pathologists examined the staining using the following criteria: strong positive (signal in the cancer cells is stronger than the normal gastric gland), positive (signal in the cancer cells is as strong as that in a normal gastric gland), weak positive (signal between positive and negative), and negative (signal is no more than the background signal in the surrounding stromal cells).


## 2.5. Statistical Analysis

We performed statistical analysis using Microsoft Excel and SPSS 16.0 statistical package (SPSS, Chicago, IL). AllP values in this study were two-sided. We consideredP ≤ 0.05 the threshold for statistical significance. We tested genotypic frequencies in control subjects for each SNP for departure from HWE using an exact test. We compared genotype frequencies of case and control subjects using the Chi2 test. We calculated OR and 95% CI by unconditional logistic regression analysis. There were two factors of age and gender adjusted for the analysis. We used the Haploview program to estimate the pairwise LD between markers and partition haplotype blocks. We inferred haplotypes using the Haploview software package (version 4.2).


## 3. Results

### 3.1. Overall Association between the PLCE1 tSNPs and the Risk of EC and GC

The characteristics of all cases and controls included in the study were listed in Table1. Seven tSNPs inPLCE1 gene were genotyped and all of the tSNPs were in Hardy-Weinberg equilibrium (HWE) in the control population (P > 0.05).Table 1
Characteristics of case and control.
Variables Case (324) Control (357) No. (%) No. (%) Age, mean years (SD) 57.4 (11.4) 50.4 (12.7) Sex Male 252 (77.8) 212 (59.4) Female 72 (22.2) 145 (40.6) Tumor site EC 48 (14.8) CC 35 (10.8) NCC 241 (74.4) Pathology Adenocarcinoma 223 (68.8) Squamous carcinoma 38 (11.7) Unspecified 63 (19.4) Differentiation Poor 117 (36.1) Moderate to well 117 (36.1) Unspecified 90 (27.8) Tumor size ≤5cm 153 (36.2) >5cm 71 (16.8) Unspecified 199 (47.0) Tumor stage I-II 174 (53.7) III-IV 62 (19.1) Unspecified 88 (27.2) EC, esophageal cancer; CC, cardia cancer; NCC, noncardia cancer.After genotyping, we conducted logistic regression to evaluate the association of each tSNP with the risk of EC and GC (Table2). Results showed that there were three tSNPs (rs3765524, rs2274223, and rs10509670) associated with the risk of EC and GC: rs3765524 (CT vs CC, OR = 1.66, 95% CI 1.16-2.38,P = 0.006; CT/TT vs CC, OR = 1.65, 95% CI 1.17-2.34,P = 0.004); rs2274223 (AG vs AA, OR = 1.57, 95% CI 1.10-2.26,P = 0.014; AG/GG vs AA, OR = 1.55, 95% CI 1.10-2.20,P = 0.013); rs10509670 (AG vs AA, OR = 1.54, 95% CI 1.07-2.21,P = 0.019; AG/GG vs AA, OR = 1.54, 95% CI 1.09-2.18,P = 0.014).Table 2
Logistic regression of candidate tSNPs inPLCE1 and their association with EC and GC risk.
ID Genotype Case (n = 324) Control (n = 357) Crude OR P Adjusted OR P HWE-P No. (%) No. (%) (95%CI) (95%CI) rs3765524 CC 168 (51.9) 223 (62.6) 1   1   0.896 CT 136 (42.0) 117 (32.9) 1.54 (1.12-2.12) 0.008 1.66 (1.16-2.38) 0.006 TT 20 (6.2) 16 (4.5) 1.66 (0.83-3.30) 0.149 1.60 (0.72-3.55) 0.247 CT/TT 156 (48.1) 133 (37.4) 1.56 (1.15-2.11) 0.005 1.65 (1.17-2.34) 0.004 rs3818432 CC 104 (57.5) 193 (65.6) 1   1   0.856 CA 73 (40.3) 91 (31.0) 1.49 (1.01-2.20) 0.045 1.47 (0.97-2.23) 0.073 AA 4 (2.2) 10 (3.4) 0.74 (0.23-2.42) 0.622 0.87 (0.24-3.09) 0.826 CA/AA 77 (42.5) 101 (34.4) 1.41 (0.97-2.07) 0.074 1.41 (0.94-2.13) 0.098 rs2274223 AA 177 (54.8) 229 (64.1) 1   1   0.457 AG 126 (39.0) 111 (31.1) 1.47 (1.06-2.03) 0.019 1.57 (1.10-2.26) 0.014 GG 20 (6.2) 17 (4.8) 1.52 (0.77-2.99) 0.223 1.43 (0.66-3.14) 0.367 AG/GG 146 (45.2) 128 (35.9) 1.48 (1.08-2.01) 0.013 1.55 (1.10-2.20) 0.013 rs10509670 AA 178 (54.9) 229 (64.5) 1   1   0.391 AG 124 (38.3) 109 (30.7) 1.46 (1.06-2.02) 0.021 1.54 (1.07-2.21) 0.019 GG 22 (6.8) 17 (4.8) 1.66 (0.86-3.23) 0.132 1.54 (0.72-3.32) 0.268 AG/GG 146 (45.1) 126 (35.5) 1.49 (1.10-2.03) 0.011 1.54 (1.09-2.18) 0.014 rs11187852 GG 122 (67.4) 212 (72.1) 1   1   0.506 GA 56 (30.9) 77 (26.2) 1.26 (0.84-1.90) 0.263 1.33 (0.85-2.07) 0.212 AA 3 (1.7) 5 (1.7) 1.04 (0.24-4.44) 0.955 1.68 (0.34-8.18) 0.522 GA/AA 59 (32.6) 82 (27.9) 1.25 (0.84-1.87) 0.276 1.34 (0.87-2.08) 0.185 rs3781264 TT 120 (66.3) 206 (70.1) 1   1   0.511 TC 58 (32.0) 82 (27.9) 1.21 (0.81-1.82) 0.347 1.24 (0.80-1.92) 0.331 CC 3 (1.7) 6 (2.0) 0.86 (0.21-3.49) 0.831 1.07 (0.23-5.00) 0.932 TC/CC 61 (33.7) 88 (29.9) 1.19 (0.80-1.77) 0.390 1.23 (0.80-1.89) 0.340 rs11187866 CC 120 (66.7) 210 (71.4) 1   1   0.723 CG 56 (31.1) 76 (25.9) 1.29 (0.85-1.95) 0.226 1.33 (0.85-2.08) 0.210 GG 4 (2.2) 8 (2.7) 0.88 (0.26-2.97) 0.830 1.13 (0.30-4.23) 0.857 CG/GG 60 (33.3) 84 (28.6) 1.25 (0.84-1.86) 0.274 1.31 (0.85-2.03) 0.218 Notes. The adjusted OR is derived from the correction for age and gender. The results were in bold, if the P value < 0.05. EC, esophageal cancer; GC, gastric cancer.


### 3.2. Linkage Disequilibrium and Haplotype Evaluation for the PLCE1 tSNPs

Linkage disequilibrium (LD) analysis revealed that the seven tSNPs ofPLCE1linked with each other (Figure 1). Haplotype “CCAAGTC” accounted for 71.5% of the whole haplotypes in EC and GC cases. This is a protective haplotype against the risk of EC/GC (OR = 0.72; 95% CI = 0.53–0.97;P = 0.029) (Table 3). Further analysis revealed that the LD block could be divided into two subblocks (Figure 1(a)). Subblock 1 (r2 > 0.79) was composed of four tSNPs of rs3765524, rs3818432, rs2274223, and rs10509670, where the three risk SNPs identified above were included. Subblock 2 (r2 > 0.87) included the later three tSNPs of rs11187852, rs3781264, and rs11187866. In subblock 1, “CCAA” accounted for 72.4% of the whole haplotypes in EC/GC cases and was found to be the protective haplotype against the risk of EC/GC (OR = 0.67; 95% CI = 0.49–0.91;P = 0.009).Table 3
Haplotypes ofPLCE1 and their association with EC and GC risk.
ID Block Haplotype Frequencya OR (95%CI) Chi2 P b Case Control 1 Global CCAAGTC 71.5% 77.8% 0.72 (0.53-0.97) 4.742 0.029 2  TAGGACG 16.8% 14.6% 1.18 (0.83-1.69) 0.861 0.354 3  TAGGGTC 4.7% 2.9% 1.66 (0.83-3.28) 2.115 0.146 4  TCAAGTC 3.0% 1.2% 2.49 (0.97-6.41) 3.834 0.050 5  TCGGGTC 2.2% 1.2% 1.82 (0.66-5.03) 1.381 0.240 6 Sub-1 CCAA 72.4% 79.7% 0.67 (0.49-0.91) 6.756 0.009 7  TAGG 22.1% 17.6% 1.33 (0.96-1.84) 2.859 0.091 8  TCAA 3.0% 1.2% 2.48 (0.95-6.42) 3.752 0.053 9  TCGG 2.2% 1.2% 1.81 (0.65-5.04) 1.331 0.249 10 Sub-2 GTC 81.5% 83.2% 0.89 (0.63-1.25) 0.436 0.509 11  ACG 17.1% 14.8% 1.19 (0.83-1.70) 0.921 0.337 Notes. (A) Only haplotypes with frequencies of ≥ 3% are shown. (B) The results were in bold, if the P value < 0.05. EC, esophageal cancer; GC, gastric cancer.Figure 1
Linkage disequilibrium (LD) analysis of PLCE1 tSNPs. (a) r2 of LD analysis, which showed that the seven tSNPs are linked to each other and could be divided into two subblocks. (b) D’ of LD analysis.
(a) (b)


### 3.3. Stratified Analysis for the Clinicopathologic Data of Patients

Anatomically, gastric cancer includes cardia cancer (CC) and noncardia cancers (NCC). Pathologically, gastric cancer has adenocarcinoma and squamous carcinoma. Then we performed a stratified analysis to determine the association between the three tSNPs (rs3765524, rs2274223, and rs10509670) and clinicopathologic data in dominant model (Table4). Significant association between the three tSNPs and risk of EC and GC was observed for subgroup patients of male, age ≥54, tumor stages of I-II and tumor size ≤ 5 cm, EC and cardia cancer (CC), and moderate to well differentiated squamous carcinoma. In addition, a significant association for rs3765524 with noncardia cancer (NCC) and adenocarcinoma was also observed.Table 4
Stratified analysis for the association between tSNPs inPLCE1 and EC and GC risk.
Variables rs3765524 Adjusted OR P rs2274223 Adjusted OR P rs10509670 Adjusted OR P (Case/Control) (Case/Control) (Case/Control) CC CT/TT (95%CI) AA AG/GG (95%CI) AA AG/GG (95%CI) Age, years ≤ 53 58/159 55/109 1.34 (0.86-2.10) 0.203 62/161 50/107 1.18 (0.75-1.86) 0.464 63/161 50/105 1.18 (0.75-1.85) 0.478 >53 110/64 101/24 2.56 (1.41-4.64) 0.002 115/68 96/21 2.63 (1.43-4.82) 0.002 115/68 96/21 2.63 (1.43-4.82) 0.002 Sex Male 130/137 122/74 1.84 (1.19-2.82) 0.006 136/139 116/73 1.72 (1.12-2.64) 0.014 135/139 117/72 1.76 (1.15-2.71) 0.010 Female 38/86 34/59 1.34 (0.74-2.42) 0.339 41/90 30/55 1.25 (0.68-2.28) 0.476 43/90 29/54 1.16 (0.63-2.12) 0.636 Tumor site EC 25/223 23/133 2.61 (1.22-5.55) 0.013 24/229 23/128 3.01 (1.39-6.50) 0.005 25/229 23/126 1.40 (1.05-1.86) 0.022 CC 11/223 24/133 5.99 (2.28-15.77) <0.001 12/229 23/128 5.31 (2.09-13.50) <0.001 12/229 23/126 5.31 (2.09-13.50) <0.001 NCC 142/223 114/133 1.47 (1.03-2.12) 0.036 152/229 104/128 1.36 (0.95-1.96) 0.098 152/229 104/126 1.36 (0.95-1.96) 0.096 Pathology Adenocarcinoma 172/223 141/133 1.45 (1.02-2.06) 0.041 181/229 132/128 1.36 (0.95-1.94) 0.092 180/229 133/126 1.38 (0.97-1.97) 0.078 Squamous carcinoma 21/223 20/133 2.23 (1.05-4.72) 0.037 20/229 21/128 2.71 (1.28-5.76) 0.010 20/229 21/126 2.72 (1.28-5.77) 0.009 Differentiation Poor 85/223 59/133 1.30 (0.85-1.97) 0.222 86/229 58/128 1.33 (0.87-2.03) 0.182 86/229 58/126 1.40 (1.05-1.86) 0.022 Moderate to well 92/223 83/133 1.72 (1.07-2.76) 0.026 97/229 78/128 1.61 (1.00-2.58) 0.050 96/229 79/126 1.67 (1.04-2.68) 0.034 Tumor size ≤ 5 cm 104/223 100/133 1.81 (1.20-2.72) 0.005 114/229 90/128 1.59 (1.05-2.39) 0.027 115/229 89/126 1.54 (1.02-2.32) 0.039 > 5 cm 58/223 43/133 1.44 (0.88-2.34) 0.148 60/229 41/128 1.39 (0.85-2.27) 0.192 60/229 41/126 1.40 (0.85-2.28) 0.183 Tumor stage I-II 129/223 115/133 1.60 (1.09-2.33) 0.016 136/229 108/128 1.50 (1.03-2.19) 0.036 137/229 107/126 1.47 (1.01-2.15) 0.047 III-IV 45/223 32/133 1.38 (0.79-2.40) 0.262 47/229 30/128 1.35 (0.77-2.36) 0.297 45/229 32/126 1.53 (0.88-2.68) 0.134 Notes. The adjusted OR is derived from the correction for age and gender. The results were in bold, if the P value < 0.05. EC, esophageal cancer; GC, gastric cancer; CC, cardia cancer; NCC, noncardia cancer.


### 3.4. Expression Distribution of PLCE1 Protein in Stomach Tissue

Now that the association betweenPLCE1 polymorphisms and GC risk exhibited disparity according to the tumor subsites, we then evaluated the expression distribution of PLCE1 protein in human GC and adjacent noncancer tissues (ANC) by tissue microarray. In the ANC tissue, PLCE1 protein expression was positive in the cytoplasm of columnar epithelial cells and mainly distributed in the junction of cardia and gastric fundus glands (Figure 2(a)). In the GC tissue, the structure distortion and confusion of tubular glands, obvious heterogeneity of epithelial cells with irregular nuclear staining, and lower expression of PLCE1 protein were observed (Figure 2(b)). These suggested, together with the results of rs3765524 genotyping by stratified analysis, that PLCE1 protein may be involved in carcinogenesis of NCC and adenocarcinoma, although more significant association has been found with EC, CC, and squamous carcinoma.Figure 2
Representative images of PLCE1 expression distribution in gastric cancer (GC) and adjacent noncancerous (ANC) tissues by tissue microarray. (a) ANC tissues. PLCE1 protein was expressed in the cytoplasm of columnar epithelial cells and mainly distributed in the junction of cardia and gastric fundus glands (200×). (b) GC tissues. Structure distortion and confusion of tubular glands, heterogeneity of epithelial cells with irregular nuclear staining, and lower expression of PLCE1 were observed (200×).
(a) (b)


### 3.5. Effect of PLCE1 Polymorphisms on Its Expression in NCC and ANC Tissues

Because NCC and adenocarcinoma have been the predominant subtype of gastric cancer in China, we then examined the expression ofPLCE1 in adenocarcinoma of NCC and their ANC tissues with different genotypes of rs3765524. For mRNA transcription, we identified twoPLCE1 processing units,PLCE1A andPLCE1B, by quantitative real-time PCR (qRT-PCR). As presented in Figures 3(a)(i) and 3(a)(ii), compared with ANC tissues, the two procession units were both downregulated in NCC tissues (PLCE1A: 22 of 28, 78.57%,P = 0.034;PLCE1B: 21 of 28, 75.00%,P = 0.021), while there was no significant difference between genotype rs3765524 CC and rs3765524 CT/TT both in ANC (Figures 3(b)(i) and 3(b)(ii)) and in NCC (Figures 3(c)(i) and 3(c)(ii)).Figure 3
PLCE1 mRNA expression in adenocarcinoma of noncardia cancer (NCC) and adjacent noncancerous (ANC) tissues by qRT-PCR. (a)PLCE1A (i) andPLCE1B (ii) mRNA expression in ANC and NCC tissues, respectively. (b)PLCE1A (i) andPLCE1B (ii) mRNA expression in ANC tissues with different genotypes of rs3765524. (c)PLCE1A (i) andPLCE1B (ii) mRNA expression in NCC tissues with different genotypes of rs3765524. Horizontal lines indicate mean ± SE (n = 28).
(a) (b) (c)For protein translation, immunohistochemistry (IHC) staining revealed that PLCE1 protein expression was generally downregulated in NCC than in their ANC tissues regardless of rs3765524 genotype (6 of 13, 46.15%,P = 0.018, see in Figures 4(a), 4(b), and 4(c)(i)). By genotyping, the PLCE1 protein expression was found higher in group of rs3765524 CT/TT than in group of rs3765524 CC both in ANC (Figure 4(c)(ii).P = 0.031) and NCC tissues (Figure 4(c)(iii).P = 0.045).Figure 4
PLCE1 protein expression in adenocarcinoma of noncardia cancer (NCC) and adjacent noncancerous (ANC) tissues by immunohistochemistry (IHC) staining. (a) Representative images of PLCE1 expression in ANC tissues with different genotypes of rs3765524 ((i) CC, (ii) CT, and (iii) TT) (400×). (b) Representative images of PLCE1 expression in NCC tissues with different genotypes of rs3765524 ((i) CC, (ii) CT, and (iii) TT) (400×). (c) IHC staining score comparison of PLCE1 (i) between ANC and NCC tissues regardless of rs3765524 genotyping, (ii) in ANC tissues with different genotypes of rs3765524, (iii) in NCC tissues with different genotypes of rs3765524. The data was represented as mean ± SE (n = 13).
(a) (b) (c)


## 3.1. Overall Association between the PLCE1 tSNPs and the Risk of EC and GC

The characteristics of all cases and controls included in the study were listed in Table1. Seven tSNPs inPLCE1 gene were genotyped and all of the tSNPs were in Hardy-Weinberg equilibrium (HWE) in the control population (P > 0.05).Table 1
Characteristics of case and control.
Variables Case (324) Control (357) No. (%) No. (%) Age, mean years (SD) 57.4 (11.4) 50.4 (12.7) Sex Male 252 (77.8) 212 (59.4) Female 72 (22.2) 145 (40.6) Tumor site EC 48 (14.8) CC 35 (10.8) NCC 241 (74.4) Pathology Adenocarcinoma 223 (68.8) Squamous carcinoma 38 (11.7) Unspecified 63 (19.4) Differentiation Poor 117 (36.1) Moderate to well 117 (36.1) Unspecified 90 (27.8) Tumor size ≤5cm 153 (36.2) >5cm 71 (16.8) Unspecified 199 (47.0) Tumor stage I-II 174 (53.7) III-IV 62 (19.1) Unspecified 88 (27.2) EC, esophageal cancer; CC, cardia cancer; NCC, noncardia cancer.After genotyping, we conducted logistic regression to evaluate the association of each tSNP with the risk of EC and GC (Table2). Results showed that there were three tSNPs (rs3765524, rs2274223, and rs10509670) associated with the risk of EC and GC: rs3765524 (CT vs CC, OR = 1.66, 95% CI 1.16-2.38,P = 0.006; CT/TT vs CC, OR = 1.65, 95% CI 1.17-2.34,P = 0.004); rs2274223 (AG vs AA, OR = 1.57, 95% CI 1.10-2.26,P = 0.014; AG/GG vs AA, OR = 1.55, 95% CI 1.10-2.20,P = 0.013); rs10509670 (AG vs AA, OR = 1.54, 95% CI 1.07-2.21,P = 0.019; AG/GG vs AA, OR = 1.54, 95% CI 1.09-2.18,P = 0.014).Table 2
Logistic regression of candidate tSNPs inPLCE1 and their association with EC and GC risk.
ID Genotype Case (n = 324) Control (n = 357) Crude OR P Adjusted OR P HWE-P No. (%) No. (%) (95%CI) (95%CI) rs3765524 CC 168 (51.9) 223 (62.6) 1   1   0.896 CT 136 (42.0) 117 (32.9) 1.54 (1.12-2.12) 0.008 1.66 (1.16-2.38) 0.006 TT 20 (6.2) 16 (4.5) 1.66 (0.83-3.30) 0.149 1.60 (0.72-3.55) 0.247 CT/TT 156 (48.1) 133 (37.4) 1.56 (1.15-2.11) 0.005 1.65 (1.17-2.34) 0.004 rs3818432 CC 104 (57.5) 193 (65.6) 1   1   0.856 CA 73 (40.3) 91 (31.0) 1.49 (1.01-2.20) 0.045 1.47 (0.97-2.23) 0.073 AA 4 (2.2) 10 (3.4) 0.74 (0.23-2.42) 0.622 0.87 (0.24-3.09) 0.826 CA/AA 77 (42.5) 101 (34.4) 1.41 (0.97-2.07) 0.074 1.41 (0.94-2.13) 0.098 rs2274223 AA 177 (54.8) 229 (64.1) 1   1   0.457 AG 126 (39.0) 111 (31.1) 1.47 (1.06-2.03) 0.019 1.57 (1.10-2.26) 0.014 GG 20 (6.2) 17 (4.8) 1.52 (0.77-2.99) 0.223 1.43 (0.66-3.14) 0.367 AG/GG 146 (45.2) 128 (35.9) 1.48 (1.08-2.01) 0.013 1.55 (1.10-2.20) 0.013 rs10509670 AA 178 (54.9) 229 (64.5) 1   1   0.391 AG 124 (38.3) 109 (30.7) 1.46 (1.06-2.02) 0.021 1.54 (1.07-2.21) 0.019 GG 22 (6.8) 17 (4.8) 1.66 (0.86-3.23) 0.132 1.54 (0.72-3.32) 0.268 AG/GG 146 (45.1) 126 (35.5) 1.49 (1.10-2.03) 0.011 1.54 (1.09-2.18) 0.014 rs11187852 GG 122 (67.4) 212 (72.1) 1   1   0.506 GA 56 (30.9) 77 (26.2) 1.26 (0.84-1.90) 0.263 1.33 (0.85-2.07) 0.212 AA 3 (1.7) 5 (1.7) 1.04 (0.24-4.44) 0.955 1.68 (0.34-8.18) 0.522 GA/AA 59 (32.6) 82 (27.9) 1.25 (0.84-1.87) 0.276 1.34 (0.87-2.08) 0.185 rs3781264 TT 120 (66.3) 206 (70.1) 1   1   0.511 TC 58 (32.0) 82 (27.9) 1.21 (0.81-1.82) 0.347 1.24 (0.80-1.92) 0.331 CC 3 (1.7) 6 (2.0) 0.86 (0.21-3.49) 0.831 1.07 (0.23-5.00) 0.932 TC/CC 61 (33.7) 88 (29.9) 1.19 (0.80-1.77) 0.390 1.23 (0.80-1.89) 0.340 rs11187866 CC 120 (66.7) 210 (71.4) 1   1   0.723 CG 56 (31.1) 76 (25.9) 1.29 (0.85-1.95) 0.226 1.33 (0.85-2.08) 0.210 GG 4 (2.2) 8 (2.7) 0.88 (0.26-2.97) 0.830 1.13 (0.30-4.23) 0.857 CG/GG 60 (33.3) 84 (28.6) 1.25 (0.84-1.86) 0.274 1.31 (0.85-2.03) 0.218 Notes. The adjusted OR is derived from the correction for age and gender. The results were in bold, if the P value < 0.05. EC, esophageal cancer; GC, gastric cancer.


## 3.2. Linkage Disequilibrium and Haplotype Evaluation for the PLCE1 tSNPs

Linkage disequilibrium (LD) analysis revealed that the seven tSNPs ofPLCE1linked with each other (Figure 1). Haplotype “CCAAGTC” accounted for 71.5% of the whole haplotypes in EC and GC cases. This is a protective haplotype against the risk of EC/GC (OR = 0.72; 95% CI = 0.53–0.97;P = 0.029) (Table 3). Further analysis revealed that the LD block could be divided into two subblocks (Figure 1(a)). Subblock 1 (r2 > 0.79) was composed of four tSNPs of rs3765524, rs3818432, rs2274223, and rs10509670, where the three risk SNPs identified above were included. Subblock 2 (r2 > 0.87) included the later three tSNPs of rs11187852, rs3781264, and rs11187866. In subblock 1, “CCAA” accounted for 72.4% of the whole haplotypes in EC/GC cases and was found to be the protective haplotype against the risk of EC/GC (OR = 0.67; 95% CI = 0.49–0.91;P = 0.009).Table 3
Haplotypes ofPLCE1 and their association with EC and GC risk.
ID Block Haplotype Frequencya OR (95%CI) Chi2 P b Case Control 1 Global CCAAGTC 71.5% 77.8% 0.72 (0.53-0.97) 4.742 0.029 2  TAGGACG 16.8% 14.6% 1.18 (0.83-1.69) 0.861 0.354 3  TAGGGTC 4.7% 2.9% 1.66 (0.83-3.28) 2.115 0.146 4  TCAAGTC 3.0% 1.2% 2.49 (0.97-6.41) 3.834 0.050 5  TCGGGTC 2.2% 1.2% 1.82 (0.66-5.03) 1.381 0.240 6 Sub-1 CCAA 72.4% 79.7% 0.67 (0.49-0.91) 6.756 0.009 7  TAGG 22.1% 17.6% 1.33 (0.96-1.84) 2.859 0.091 8  TCAA 3.0% 1.2% 2.48 (0.95-6.42) 3.752 0.053 9  TCGG 2.2% 1.2% 1.81 (0.65-5.04) 1.331 0.249 10 Sub-2 GTC 81.5% 83.2% 0.89 (0.63-1.25) 0.436 0.509 11  ACG 17.1% 14.8% 1.19 (0.83-1.70) 0.921 0.337 Notes. (A) Only haplotypes with frequencies of ≥ 3% are shown. (B) The results were in bold, if the P value < 0.05. EC, esophageal cancer; GC, gastric cancer.Figure 1
Linkage disequilibrium (LD) analysis of PLCE1 tSNPs. (a) r2 of LD analysis, which showed that the seven tSNPs are linked to each other and could be divided into two subblocks. (b) D’ of LD analysis.
(a) (b)


## 3.3. Stratified Analysis for the Clinicopathologic Data of Patients

Anatomically, gastric cancer includes cardia cancer (CC) and noncardia cancers (NCC). Pathologically, gastric cancer has adenocarcinoma and squamous carcinoma. Then we performed a stratified analysis to determine the association between the three tSNPs (rs3765524, rs2274223, and rs10509670) and clinicopathologic data in dominant model (Table4). Significant association between the three tSNPs and risk of EC and GC was observed for subgroup patients of male, age ≥54, tumor stages of I-II and tumor size ≤ 5 cm, EC and cardia cancer (CC), and moderate to well differentiated squamous carcinoma. In addition, a significant association for rs3765524 with noncardia cancer (NCC) and adenocarcinoma was also observed.Table 4
Stratified analysis for the association between tSNPs inPLCE1 and EC and GC risk.
Variables rs3765524 Adjusted OR P rs2274223 Adjusted OR P rs10509670 Adjusted OR P (Case/Control) (Case/Control) (Case/Control) CC CT/TT (95%CI) AA AG/GG (95%CI) AA AG/GG (95%CI) Age, years ≤ 53 58/159 55/109 1.34 (0.86-2.10) 0.203 62/161 50/107 1.18 (0.75-1.86) 0.464 63/161 50/105 1.18 (0.75-1.85) 0.478 >53 110/64 101/24 2.56 (1.41-4.64) 0.002 115/68 96/21 2.63 (1.43-4.82) 0.002 115/68 96/21 2.63 (1.43-4.82) 0.002 Sex Male 130/137 122/74 1.84 (1.19-2.82) 0.006 136/139 116/73 1.72 (1.12-2.64) 0.014 135/139 117/72 1.76 (1.15-2.71) 0.010 Female 38/86 34/59 1.34 (0.74-2.42) 0.339 41/90 30/55 1.25 (0.68-2.28) 0.476 43/90 29/54 1.16 (0.63-2.12) 0.636 Tumor site EC 25/223 23/133 2.61 (1.22-5.55) 0.013 24/229 23/128 3.01 (1.39-6.50) 0.005 25/229 23/126 1.40 (1.05-1.86) 0.022 CC 11/223 24/133 5.99 (2.28-15.77) <0.001 12/229 23/128 5.31 (2.09-13.50) <0.001 12/229 23/126 5.31 (2.09-13.50) <0.001 NCC 142/223 114/133 1.47 (1.03-2.12) 0.036 152/229 104/128 1.36 (0.95-1.96) 0.098 152/229 104/126 1.36 (0.95-1.96) 0.096 Pathology Adenocarcinoma 172/223 141/133 1.45 (1.02-2.06) 0.041 181/229 132/128 1.36 (0.95-1.94) 0.092 180/229 133/126 1.38 (0.97-1.97) 0.078 Squamous carcinoma 21/223 20/133 2.23 (1.05-4.72) 0.037 20/229 21/128 2.71 (1.28-5.76) 0.010 20/229 21/126 2.72 (1.28-5.77) 0.009 Differentiation Poor 85/223 59/133 1.30 (0.85-1.97) 0.222 86/229 58/128 1.33 (0.87-2.03) 0.182 86/229 58/126 1.40 (1.05-1.86) 0.022 Moderate to well 92/223 83/133 1.72 (1.07-2.76) 0.026 97/229 78/128 1.61 (1.00-2.58) 0.050 96/229 79/126 1.67 (1.04-2.68) 0.034 Tumor size ≤ 5 cm 104/223 100/133 1.81 (1.20-2.72) 0.005 114/229 90/128 1.59 (1.05-2.39) 0.027 115/229 89/126 1.54 (1.02-2.32) 0.039 > 5 cm 58/223 43/133 1.44 (0.88-2.34) 0.148 60/229 41/128 1.39 (0.85-2.27) 0.192 60/229 41/126 1.40 (0.85-2.28) 0.183 Tumor stage I-II 129/223 115/133 1.60 (1.09-2.33) 0.016 136/229 108/128 1.50 (1.03-2.19) 0.036 137/229 107/126 1.47 (1.01-2.15) 0.047 III-IV 45/223 32/133 1.38 (0.79-2.40) 0.262 47/229 30/128 1.35 (0.77-2.36) 0.297 45/229 32/126 1.53 (0.88-2.68) 0.134 Notes. The adjusted OR is derived from the correction for age and gender. The results were in bold, if the P value < 0.05. EC, esophageal cancer; GC, gastric cancer; CC, cardia cancer; NCC, noncardia cancer.


## 3.4. Expression Distribution of PLCE1 Protein in Stomach Tissue

Now that the association betweenPLCE1 polymorphisms and GC risk exhibited disparity according to the tumor subsites, we then evaluated the expression distribution of PLCE1 protein in human GC and adjacent noncancer tissues (ANC) by tissue microarray. In the ANC tissue, PLCE1 protein expression was positive in the cytoplasm of columnar epithelial cells and mainly distributed in the junction of cardia and gastric fundus glands (Figure 2(a)). In the GC tissue, the structure distortion and confusion of tubular glands, obvious heterogeneity of epithelial cells with irregular nuclear staining, and lower expression of PLCE1 protein were observed (Figure 2(b)). These suggested, together with the results of rs3765524 genotyping by stratified analysis, that PLCE1 protein may be involved in carcinogenesis of NCC and adenocarcinoma, although more significant association has been found with EC, CC, and squamous carcinoma.Figure 2
Representative images of PLCE1 expression distribution in gastric cancer (GC) and adjacent noncancerous (ANC) tissues by tissue microarray. (a) ANC tissues. PLCE1 protein was expressed in the cytoplasm of columnar epithelial cells and mainly distributed in the junction of cardia and gastric fundus glands (200×). (b) GC tissues. Structure distortion and confusion of tubular glands, heterogeneity of epithelial cells with irregular nuclear staining, and lower expression of PLCE1 were observed (200×).
(a) (b)


## 3.5. Effect of PLCE1 Polymorphisms on Its Expression in NCC and ANC Tissues

Because NCC and adenocarcinoma have been the predominant subtype of gastric cancer in China, we then examined the expression ofPLCE1 in adenocarcinoma of NCC and their ANC tissues with different genotypes of rs3765524. For mRNA transcription, we identified twoPLCE1 processing units,PLCE1A andPLCE1B, by quantitative real-time PCR (qRT-PCR). As presented in Figures 3(a)(i) and 3(a)(ii), compared with ANC tissues, the two procession units were both downregulated in NCC tissues (PLCE1A: 22 of 28, 78.57%,P = 0.034;PLCE1B: 21 of 28, 75.00%,P = 0.021), while there was no significant difference between genotype rs3765524 CC and rs3765524 CT/TT both in ANC (Figures 3(b)(i) and 3(b)(ii)) and in NCC (Figures 3(c)(i) and 3(c)(ii)).Figure 3
PLCE1 mRNA expression in adenocarcinoma of noncardia cancer (NCC) and adjacent noncancerous (ANC) tissues by qRT-PCR. (a)PLCE1A (i) andPLCE1B (ii) mRNA expression in ANC and NCC tissues, respectively. (b)PLCE1A (i) andPLCE1B (ii) mRNA expression in ANC tissues with different genotypes of rs3765524. (c)PLCE1A (i) andPLCE1B (ii) mRNA expression in NCC tissues with different genotypes of rs3765524. Horizontal lines indicate mean ± SE (n = 28).
(a) (b) (c)For protein translation, immunohistochemistry (IHC) staining revealed that PLCE1 protein expression was generally downregulated in NCC than in their ANC tissues regardless of rs3765524 genotype (6 of 13, 46.15%,P = 0.018, see in Figures 4(a), 4(b), and 4(c)(i)). By genotyping, the PLCE1 protein expression was found higher in group of rs3765524 CT/TT than in group of rs3765524 CC both in ANC (Figure 4(c)(ii).P = 0.031) and NCC tissues (Figure 4(c)(iii).P = 0.045).Figure 4
PLCE1 protein expression in adenocarcinoma of noncardia cancer (NCC) and adjacent noncancerous (ANC) tissues by immunohistochemistry (IHC) staining. (a) Representative images of PLCE1 expression in ANC tissues with different genotypes of rs3765524 ((i) CC, (ii) CT, and (iii) TT) (400×). (b) Representative images of PLCE1 expression in NCC tissues with different genotypes of rs3765524 ((i) CC, (ii) CT, and (iii) TT) (400×). (c) IHC staining score comparison of PLCE1 (i) between ANC and NCC tissues regardless of rs3765524 genotyping, (ii) in ANC tissues with different genotypes of rs3765524, (iii) in NCC tissues with different genotypes of rs3765524. The data was represented as mean ± SE (n = 13).
(a) (b) (c)


## 4. Discussion

SNPs are the most common type of genetic variation, which makes them excellent biological markers [30]. On the other hand, SNPs, including those that fall within the coding or noncoding regions of genes, may affect the gene transcription and translation, as well as the structure and function of protein, contributing to changing the host susceptibility to diseases [31].GWAS study found that some SNPs inPLCE1 corresponding to Y, C2, and RA domain were associated with the risk of EC and GC [8–10]. These are very important domains to PLCE1. The Y domain folds to form the catalytic core of the phospholipase and the C2 domain can bind to phospholipid [32]. RA domain is in the C terminal of PLCE1 protein, which interacts directly with upstream regulators of Ras, Rap, and others [33]. The genomic region for Y, C2, and RA domains spans from exon 24 to exon 33. By referring to the frequencies of SNPs in Chinese Han population in HapMap database, after removing the SNPs with minimum allele frequency (MAF) less than 0.05, seven candidate SNPs in the region were selected in our study, where rs3765524 was in exon 24 and in Y domain, rs3818432 was in intron 24, rs2274223 was in exon 26 and in C2 domain, rs10509670 was in intron 26, rs11187852 and rs3781264 were in intron 27, and rs11187866 was in intron 32.By genotyping and logistic regression, we not only confirmed the two previous reported SNPs of rs3765524 and rs2274223 [8–10] but also revealed that another SNP of rs10509670 inPLCE1 was associated with the risk of EC and GC susceptibility. rs3765524 C>T causes an amino acid change from Thr to Ile (ACC1777ATC), and rs2274223 A>G can also cause a missense mutation of His to Arg (CAC1927CGC). These two SNPs are corresponding to the Y and C2 domain of PLCE1 protein, respectively. We noticed that Thr, His, and Arg are frequently modified amino acid residues in human proteins. Different posttranslational modification may alter the structure, stability, and function of PLCE1 protein [34]. In the case of rs3765524, we found that although there was no difference in mRNA transcription between wild type and mutant type (Figure 3), there was a difference in protein expression (Figure 4). Among them, the expression of CT/TT genotype was higher than that of CC genotype in both NCC and ANC groups, implying that the amino acid change by the polymorphism of rs3765524 might lead to different protein modifications or structural changes, ultimately affectingPLCE1 expression or stability.The third loci of rs10509670 located in the intron ofPLCE1 gene has also shown to be associated with risk of EC and GC in the experiment. We hypothesize that rs10509670 A>G may affectPLCE1 gene structure or expression by regulating gene splicing or transcription [31]. In the study, the seven tSNPs have been proved to be in LD. Moreover, we identified two haplotypes associated with EC and GC risk. The haplotype of “CCAAGTC” (corresponding to Y, C2, and RA domains) and the haplotype in subblock 1 of “CCAA” (corresponding to Y and C2 domains) have decreased risk of EC and GC of 33% and 28%, respectively.Previous studies have exhibited different associations betweenPLCE1 polymorphisms and the risk of EC and GC, especially for different tumor subsites of GC in several candidate-gene studies [11–24]. The latest large meta-analyses confirmed the G allele ofPLCE1rs2274223 to be associated with an increased risk of cardia cancer (CC) rather than noncardia cancer (NCC) [35]. In our stratification analysis, we not only confirmed the T allele of rs3765524 and G allele of rs2274223 but also identified that the G allele of rs10509670 was associated with increased risk of EC and CC susceptibility. Furthermore, we revealed a significant association of rs3765524 C>T with the increased risk of NCC and adenocarcinoma. As we know, NCC has predominant incidence among digestive tract tumors in China [36, 37].So far, the literature reports aboutPLCE1 expression and distribution were still unclear and conflicting. Previously, we conducted a comprehensive analysis ofPLCE1expression in atrophic gastritis and GC tissues, which revealed that differential expression ofPLCE1 may distinguish GC from inflammation lesions [28]. In terms of tumorous-normal comparison, upregulation and downregulation ofPLCE1 were both found in EC and CC at mRNA and/or protein levels [9, 15, 25, 26], while there was only one study that identified downregulation ofPLCE1 at mRNA level in NCC [26]. In terms of the comparison of minor-major alleles of rs2274223 withPLCE1 expression, the results for EC were also inconsistent [14, 15, 38], and there is no report about CC and NCC until now. Another two studies reported the expression ofPLCE1 in GC but without specific tumor subsites information (CC or NCC), which presented opposite conclusions for tumorous to normal comparison [23, 28].By tissue microarray, we identified that PLCE1 protein is expressed not only in cardia but also in gastric fundus glands both in GC and ANC tissues. This result, together with the association of rs3765524 C>T with NCC risk, suggests that PLCE1 protein may be involved in carcinogenesis of NCC. Therefore, we used qRT-PCR and IHC to study genetic variation effects onPLCE1 expression in NCC and their ANC tissues. Results showed that the expression ofPLCE1 at both mRNA and protein levels was lower in NCC tissues than in their ANC tissues, which supports the hypothesis that PLCE1 may function as a tumor suppressor. We also found that rs3765524 genotype may affectPLCE1 expression, wherePLCE1 expression was higher in group of rs3765524 CT/TT than in group of CC. This strongly suggests, as one of the contributors, the reference allele C of rs3765524 loss of expression in tumor, but the mutated T allele, on the other hand, produces a “dominant negative” phenotype, which is related to the increased risk of NCC. Of course, the exact mechanism needs to be studied further. To our knowledge, this is the first report aboutPLCE1 expression distribution in NCC by genotypes.PLCE1A and PLCE1B arise from alternative splicing at the amino terminus of PLCE1 protein. PLCE1A is composed of 2303aa. PLCE1B is composed of 1994aa which is truncated at the amino terminal of the peptide [39]. The different distribution and function of the two subunits in gastric carcinogenesis have not been studied yet. We demonstrated, through qRT-PCR, that bothPLCE1AandPLCE1B were downregulated in NCC than their ANC tissues. This suggests thatPLCE1AandPLCE1Bmay be involved in NCC carcinogenesis.


## 5. Conclusion

Our study reveals thatPLCE1 polymorphisms may affect gene expression and function and are associated with the risk of not only EC and CC, but also, to some extent, NCC in northwestern Chinese population. The tSNPs ofPLCE1 may have a potential possibility to be biomarkers for prewarning and diagnosis against these diseases.



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