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FAS-1377 G/A (rs2234767) Polymorphism and Cancer Susceptibility: A Meta-Analysis of 17,858 Cases and 24,311 Controls

  • Zhou Zhong-Xing ,

    Contributed equally to this work with: Zhou Zhong-Xing, Mi Yuan-Yuan, Ma Hai Zhen

    Affiliation Department of Urology, The Affiliated Changzhou No 2. Hospital of Nanjing Medical University, Changzhou, Jiangsu, China

  • Mi Yuan-Yuan ,

    Contributed equally to this work with: Zhou Zhong-Xing, Mi Yuan-Yuan, Ma Hai Zhen

    Affiliation Department of Urology, The Third Affiliated Hospital of Nantong University, Wuxi, Jiangsu, China

  • Ma Hai Zhen ,

    Contributed equally to this work with: Zhou Zhong-Xing, Mi Yuan-Yuan, Ma Hai Zhen

    Affiliation Department of Operating Room, The Third Affiliated Hospital of Nantong University, Wuxi, Jiangsu, China

  • Zou Jian-Gang ,

    zoujiangangmeta@hotmail.com (ZJ); zhanglifengmeta@hotmail.com (ZL)

    Affiliation Department of Urology, The Affiliated Changzhou No 2. Hospital of Nanjing Medical University, Changzhou, Jiangsu, China

  • Zhang Li-Feng

    zoujiangangmeta@hotmail.com (ZJ); zhanglifengmeta@hotmail.com (ZL)

    Affiliation Department of Urology, The Affiliated Changzhou No 2. Hospital of Nanjing Medical University, Changzhou, Jiangsu, China

Abstract

Background and Objectives

Disruption of apoptosis has been implicated in carcinogenesis. Specifically, various single-nucleotide polymorphisms (SNPs) in apoptotic genes, such as FAS-1377 G/A SNP, have been associated with cancer risk. FAS-1377 G/A SNP has been shown to alter FAS gene promoter transcriptional activity. Down-regulation of FAS and cell death resistance is key to many cancers, but an association between FAS-1377 G/A SNP and cancer risk is uncertain. Therefore, we conducted a meta-analysis of the current literature to clarify this relationship.

Methodology/Principal Findings

From PubMed and Chinese language (CNKI and WanFang) databases, we located articles published up to March 5, 2013, obtaining 44 case-control studies from 41 different articles containing 17,858 cases and 24,311 controls based on search criteria for cancer susceptibility related to the FAS gene -1377 G/A SNP. Odds ratios (ORs) and 95% confidence intervals (CI) revealed association strengths. Data show that the -1377 G allele was protective against cancer risk. Similar associations were detected in “source of control,” ethnicity and cancer type subgroups. Lower cancer risk was found in both smokers with a GG+GA genotype and in non-smokers with the GG+GA genotype, when compared to smokers and nonsmokers with the AA genotype. Males carrying the -1377G allele (GG+GA) had lower cancer incidence than those with the AA genotype. Individuals who carried both FAS-1377(GG+GA)/FASL-844(TT+TC) genotypes appeared to have lower risk of cancer than those who carried both FAS-1377 AA/FASL-844 CC genotypes.

Conclusions/Significance

The FAS-1377 G/A SNP may decrease cancer risk. Studies with larger samples to study gene-environment interactions are warranted to understand the role of FAS gene polymorphisms, especially -1377 G/A SNP, in cancer risk.

Introduction

In both economically developed and newly developing countries, cancer remains a significant cause of death [1]. Predisposition to cancer may be conferred by certain genetic polymorphisms that arise from single nucleotide polymorphisms (SNPs) [2]. In fact, numerous genome-wide studies of common cancers suggest a number of loci within the genome that, although they have a low-penetrance, may raise an individual’s susceptibility to cancer [35].

Apoptosis, the physiological mechanism of “programmed cell death” is crucial for normal tissue development and homeostasis [6], and aberrant regulation of apoptosis correlates with a variety of human diseases, including some cancers [7,8]. FAS (TNFRSF6/CD95/APO-1), a member of the tumor necrosis factor (TNF) receptor super-family, is a trans-membrane receptor involved in apoptotic signal transmission in many cell types. The apoptotic death signal cascade is initiated upon the cross-linking of FAS with its natural ligand (FASL) [9]. Decreased expression or mutation of the FAS gene and/or increased expression of FASL have been reported to occur in many malignant tumors, supposedly impairing the sensitivity of tumor cells to apoptotic signals. Then, tumor cells can evade or weaken the immune system’s ability to eliminate them through the FAS-FASL pathway [1012]. This may explain correlations between FAS and FASL and human carcinogenesis and/or aggressive tumor behavior [10,11]. Also, decreased FAS expression may protect transformed cells from being eliminated by anti-tumor immune responses, whereas heightened FASL expression may increase the ability of tumor cells to counter-attack the immune system by killing FAS-sensitive lymphocytes, contributing to cancer development [13]. Thus, cancers are not only associated with unlimited cell proliferation, but also with suppression of apoptosis.

The FAS gene (GenBank no. AY450925) is located on chromosome 10q24.1, and a polymorphism identified in the FAS promoter region is a G-to-A transition at position -1377 (FAS-1377 G/A, rs2234767) [14,15] (Figure 1). This polymorphism destroys the stimulatory protein (Sp) 1 and the signal transducer and activator of transcription (STAT) 1 protein-binding element, diminishing promoter activity and decreasing FAS expression [16,17]. Thus, the G-allele may protect transformed cells against apoptosis, whereas the A-allele maybe a risk factor for cancer.

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Figure 1. Genomic structure of the human FAS (TNFRSF6/CD95/APO-1) gene with a schematic representation of primer design used to amplify the 5’ flanking region.

Five sets of primers were synthesized, ranging from 240–450 bp. The G-to-A substitution polymorphism is located at the -1377 nucleotide position within the silencer region and is situated at the consensus sequence of the transcription factor SP-1 binding site. Another A-to-G substitution polymorphism is located at the -670 position of the promoter region and situated at the binding site of the signal transducer and activator of transcription (STAT) factor. F: forward primer; R: reverse primer. Solid lines represent PCR products, labeled as amplicon 1–5, respectively. Shadowed boxes are exons [15].

https://doi.org/10.1371/journal.pone.0073700.g001

Many epidemiologic studies suggest associations between SNPs in FAS genes, mostly the FAS-1377 G/A SNP, and cancer risk. However, conclusions across studies are inconsistent due, in part, to different study populations, case ascertainment, and/or small sample sizes. Thus, previous studies may have identified false-positives as well as suffered from a limited power to detect modest associations. Positive findings were detected in two previously published meta-analyses [18,19], but these studies were not sufficiently large for a comprehensive analysis.

Considering the important role of FAS-1377 G/A SNP in carcinogenesis, we studied all currently eligible case-control studies that included characteristics such as ethnicity, cancer type, smoking behaviors, sex, and control sources. Through a meta-analysis of these recent publications, we identified several novel data points, and to our knowledge, ours is the most comprehensive meta-analysis in the literature to study the association between the FAS-1377 G/A SNP and cancer risk.

Materials and Methods

Identification and eligibility of relevant studies

Searches were conducted in PubMed and in Chinese language (CNKI and WanFang) databases using key words ‘FAS’, ‘cancer’, or ‘polymorphism’. No restrictions were placed on language or publication year and the last search was updated on March 5, 2013. A total of 173 articles were retrieved using the abovementioned terms and 41 articles contained the inclusion criteria. References of the retrieved and review articles were also screened by hand.

Inclusion criteria and exclusion criteria

Studies that were included in our analysis had to meet all of the following criteria: (1) the study assessed the correlation between cancer risk and the FAS-1377 G/A SNP; (2) the study was case-controlled and (3) the study contained sufficient genotype numbers for cases and controls. The following exclusion criteria were used: (1) lack of a control population; (2) lack of available genotype frequency data; and (3) the study was a duplicate.

Data extraction

Two of the authors extracted all data independently according to the selection criteria. The following items were collected: last name of first author, year of publication, country of origin, ethnicity, cancer type, the total and number of each genotype frequency in case/control groups, ‘source of control’, Hardy-Weinberg equilibrium (HWE) of controls, and genotyping methods. Subgroup analysis, stratified by cancer type, was performed. If a cancer type appeared in only one study, it was placed into the ‘other cancers’ subgroup. Ethnicity was categorized as Caucasian and Asian. The ‘source of control’ subgroup analysis was performed on two groups and was classified as population-based (PB) or hospital-based (HB). Smoking (smoker or non-smoker) status and subject sex (man or woman) were also included in our meta-analysis.

Statistical analysis

Crude odds ratios (ORs) with 95% confidence intervals (CI) were used to measure the strength of the association between the FAS-1377 G/A SNP and cancer risk based on genotype frequencies in cases and controls. The fixed-effects model and the random-effects model were used to calculate the pooled OR value. The statistical significance of the summary OR was determined with the Z-test. A heterogeneity assumption was evaluated among studies using a Chi-square-based Q test. A P value of more than 0.10 for the Q-test indicated a lack of heterogeneity among the studies. If significant heterogeneity was detected, the random-effects model (DerSimonian-Laird method) was used. Otherwise, the fixed-effects model (Mantel-Haenszel method) was chosen [20,21].

We investigated the relationship between genetic variants of the FAS-1377 site and cancer risk by allelic contrast (G-allele vs. A-allele), comparison of homozygotes (GG vs. AA), comparison of heterozygotes (GA vs. AA) and the dominant genetic model (GG+GA vs. AA). Sensitivity analysis was performed by assessing the stability of the results after omitting each study, one at a time. The departure of the FAS-1377 G/A SNP from expected frequencies under HWE was assessed in controls using the Pearson Chi-square test (P < 0.05 was considered significant). Moreover, the multiplicative gene-gene interactions between FAS-1377G>A and FASL-844T>C polymorphisms was tested. Publication bias was identified using Egger’s linear regression method and a funnel plot. A P-value < 0.05 in Egger’s linear regression indicated the presence of potential publication bias [22]. All statistical tests for this meta-analysis were performed with STATA software (version 10.0; StataCorp LP, College Station, TX).

Genotyping methods

Methods for genotyping for the FAS gene -1377 G/A SNP was conducted in the retrieved literature using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), the ligase detection reaction-polymerase chain reaction (LDR-PCR), and Taqman technology.

Results

Study characteristics

A total of 169 articles were collected from the PubMed and Chinese language (CNKI and WanFang) databases via a literature search using different combinations of key terms. As shown in Figure 2, 41 articles (44 case-controlled studies including 17,858 cases and 24,311 controls) were ultimately identified [2363]. Study characteristics from published studies on the relationship between FAS-1377 G/A SNP and cancer risk are summarized in Table S1. The frequency of the G-allele was found to be significantly lower in control individuals of Asian ethnicity than in those of Caucasian ethnicity (P<0.001). A similar trend was found for the G-allele among Asian and Caucasian individuals with cancer (Figures 3 and 4). The distribution of genotypes among controls was consistent with HWE in all studies except six [37,45,51,53,57,62]. Seven different articles included the genotype detail and smoking status, and three articles included information regarding sex. In most of the studies, cases were histologically diagnosed, and controls were cancer-free. Six publications [25,28,45,46,52,55] contained information about gene-gene interactions between FAS-1377G/A and FASL-844T/C polymorphisms.

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Figure 2. Flowchart illustrating the search strategy used to identify association studies of FAS-1377 G/A polymorphisms and overall cancer risk for the meta-analysis.

A total of 173 published studies assessing the association of FAS-1377 G/A polymorphisms and cancer were identified by searching the Pubmed and WanFang databases. Through abstract appraisal, 59 articles were identified as eligible for full-text appraisal. From these, an additional 19 articles (2 duplications, 6 reviews, 2 clinical trials, 4 letters/comments and 5 meta-analyses) were excluded. Finally, 41 articles involving 44 case-control design, and data from these were extracted for further assessment in the meta-analysis.

https://doi.org/10.1371/journal.pone.0073700.g002

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Figure 3. G allele frequencies of FAS-1377 G/A polymorphism among cases stratified by ethnicity.

The -1377 G-allele frequency is 0.612 in Asian populations and 0.855 in Caucasians. The G-allele frequency in Asian cases was lower than that in European cases (P < 0.001). Vertical line: G-allele frequency; Horizontal line: ethnicity type.

https://doi.org/10.1371/journal.pone.0073700.g003

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Figure 4. G allele frequencies of FAS-1377 G/A polymorphism among controls stratified by ethnicity.

The -1377 G-allele frequency is 0.623 in Asian populations and 0.862 in Caucasians. The G-allele frequency in Asian cases was lower than in European cases (P < 0.001). Vertical line: G-allele frequency; Horizontal line: ethnicity type.

https://doi.org/10.1371/journal.pone.0073700.g004

Quantitative synthesis

The results of the overall meta-analysis suggested a decreased association between the FAS-1377G/A SNP and cancer susceptibility (Homozygote comparison: OR = 0.86, 95% CI = 0.78-0.96, Pheterogeneity = 0.004, P = 0.006, dominant model: OR = 0.85, 95% CI = 0.78-0.94, Pheterogeneity = 0.010, P = 0.001 and allelic contrast: OR = 0.95, 95% CI = 0.91-1.00, Pheterogeneity = 0.000, P = 0.038). The overall association did not change after excluding the five studies that did not agree with HWE (Table 1).

VariablesNaCases/Controls  Allelic contrastHomozygote comparisonHeterozygote comparisonDominant genetic model
OR(95%CI)PbPcOR(95%CI)PbPcOR(95%CI)PbPcOR(95%CI)PbPc
Total4417858/243110.95(0.91-1.00)0.0000.0380.86(0.78-0.96)0.0040.0061.00(0.94-1.06)0.0150.9800.85(0.78-0.94)0.0100.001
HWE3815671/216580.95(0.90-1.00)0.0000.0400.85(0.77-0.96)0.0050.0090.99(0.93-1.06)0.0060.8760.85(0.77-0.94)0.0190.001
Ethnicity
Asian2911059/142010.95(0.90-1.01)0.0010.0860.87(0.77-0.98)0.0010.0201.03(0.96-1.09)0.1570.4190.86(0.77-0.95)0.0020.004
Caucasian156799/101300.94(0.85-1.05)0.0160.2781.00(0.99-1.00)0.4330.1630.99(0.97-1.01)0.5850.3261.00(0.99-1.00)0.4950.194
Source of control
HB195518/75460.94(0.87-1.02)0.0160.1350.81(0.67-0.96)0.0190.0171.02(0.99-1.02)0.2030.1530.97(0.96-0.99)0.1030.000
PB2511623/159450.96(0.90-1.02)0.0010.1570.90(0.79-1.03)0.0310.1130.91(0.80-1.03)0.0550.1220.90(0.79-1.02)0.0220.114
Cancer type
Gastric cancer71747/23280.98(0.95-1.01)0.3000.1280.95(0.91-0.99)0.4040.0301.01(0.95-1.08)0.8760.7200.97(0.95-0.99)0.4000.015
Prostate cancer2794/9271.05(1.00-1.11)0.1380.0631.06(0.97-1.06)0.2970.1791.00(0.94-1.07)0.7710.9621.01(0.97-1.05)0.7530.486
Leukemia31424/23080.94(0.65-1.36)0.0000.7451.01(0.62-1.64)0.0290.9751.02(0.97-1.07)0.6710.5251.01(0.99-1.03)0.1330.840
Cervical cancer41100/17061.01(0.97-1.05)0.3340.4891.01(0.96-1.07)0.3620.6290.98(0.93-1.03)0.2240.4771.00(0.97-1.02)0.3060.815
Esophageal carcinoma2776/9720.97(0.93-1.02)0.0820.3190.84(0.41-1.77)0.0380.6580.73(0.33-1.61)0.0260.4330.79(0.37-1.70)0.0230.544
Lung cancer43806/34430.99(0.97-1.01)0.1770.2240.85(0.59-1.22)0.0500.3770.79(0.56-1.12)0.0640.1840.82(0.58-1.16)0.0440.255
Ovarian carcinoma2389/3851.00(0.94-1.07)0.2980.963---
Melanoma31039/17891.01(0.99-1.04)0.1700.1821.01(1.00-1.02)0.7430.2081.02(0.97-1.07)0.4370.4271.01(1.00-1.02)0.6930.239
Skin carcinoma2570/16700.97(0.95-1.00)0.3220.0360.99(0.97-1.01)0.3020.2020.98(0.93-1.03)0.4470.4370.99(0.98-1.01)0.3290.238
Breast cancer42406/25930.97(0.95-0.99)0.3150.0390.96(0.94-0.99)0.3390.0050.96(0.92-1.01)0.1180.1100.98(0.96-1.00)0.1730.025
Other cancers113807/62100.97(0.95-0.99)0.0110.0020.96(0.94-0.98)0.0000.0000.95(0.92-0.98)0.1190.0020.97(0.96-0.99)0.2040.000
Smoking status
Smoker71968/1993---0.92(0.90-0.95)0.1040.000
Non-smoker61175/1974---0.95(0.92-0.98)0.0730.004
Sexual status
Man3908/1074---0.93(0.89-0.96)0.2300.000
Women2168/221---0.95(0.88-1.03)0.3600.205

Table 1. Total and stratified analysis of Fas -1377G/A SNP on cancer risk.

a Number of comparisons, bP value of Q-test for heterogeneity test, cP-value of Z-test for significant test
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In the stratified analysis by cancer type, a significant association was identified between the FAS-1377G/A SNP and gastric cancer, skin cancer, breast cancer and other cancers (gastric cancer: OR = 0.95, 95% CI = 0.91-0.99, Pheterogeneity = 0.404, P = 0.030 for GG vs. AA and OR = 0.97, 95% CI = 0.95-0.99, Pheterogeneity = 0.400, P = 0.015 for GG+GA vs. AA; skin cancer: OR = 0.97, 95% CI = 0.95-1.00, Pheterogeneity = 0.322, P = 0.036 for the G-allele vs. A-allele; breast cancer: OR = 0.97, 95% CI = 0.95-0.99, Pheterogeneity = 0.315, P = 0.039 for the G-allele vs. A-allele, OR = 0.96, 95% CI = 0.94-0.99, Pheterogeneity = 0.339, P = 0.005 for GG vs. AA, OR = 0.98, 95% CI = 0.96-1.00, Pheterogeneity = 0.173, P = 0.025 for GG+GA vs. AA; Other cancers: in all four genetic models). Similarly, a significantly decreased association was found in the HB subgroup (Table 1).

When studies were stratified according to ethnicity, there was a significantly decreased association between the FAS-1377G/A SNP and cancer susceptibility in Asians (OR = 0.87, 95% CI = 0.77-0.98, Pheterogeneity = 0.001, P = 0.020 for GG vs. AA and OR = 0.86, 95% CI = 0.77-0.95, Pheterogeneity = 0.002, P = 0.004 for GG+GA vs. AA) (Table 1).

Interestingly, compared to AA genotypes, individuals with GG+GA genotypes had lower cancer risk if they were also smokers (GG+GA vs. AA: OR = 0.92, 95% CI = 0.90-0.95, Pheterogeneity = 0.104, P = 0.000) compared to non-smokers (GG+GA vs. AA: OR = 0.95, 95% CI = 0.92-0.98, Pheterogeneity = 0.073, P = 0.004). Men who carried the -1377G allele (GG+GA) also appeared to have a lower incidence of cancer (GG+GA vs. AA: OR = 0.92, 95% CI = 0.90-0.95, Pheterogeneity = 0.230, P = 0.000) than did women who carried the same allele (GG+GA vs. AA: OR = 0.95, 95% CI = 0.88-1.03, Pheterogeneity = 0.360, P = 0.205) (Table 1).

To evaluate the genotype-genotype interaction, we analyzed the association between cancer risk and the combined genotypes of FAS-1377G/A and FASL-844T/C. Individuals who carried both FAS-1377(GG+GA)/FASL-844(TT+TC) genotypes had a decreased cancer risk compared to those who carried both FAS-1377 AA/FASL-844 CC genotypes (OR = 0.47, 95% CI = 0.25-0.90, Pheterogeneity = 0.000, P = 0.023) (Table 2, Figure 5). The reduced influence for cancer risk was lower than FAS -1377 G/A polymorphism alone.

GenotypesCaseControlOR(95%CI)P for heterogeneityPEgger’s test
FAS -1377(GG+GA)/FASL-844(TT+TC)1116356
FAS -1377 AA/FASL-844 CC17612460.47(0.25-0.90)0.0000.023T = 0.15, P = 0.886

Table 2. Association test for cancer risk with Fas/FasL gene-gene interaction.

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Figure 5. Forest plots illustrate the association of gene-gene interactions between FAS-1377G/A and FASL-844T/C polymorphisms with cancer risk for GG+GA/TT+TC vs. AA/CC.

For each study, the odds ratio (OR) and 95% confidence interval (CI) values are indicted. The size of each box is proportional to the weight of each study. Diamonds indicate the summary effects based on all studies. The squares and horizontal lines correspond to the OR and 95% CI, and the diamond represents the summary OR and 95% CI.

https://doi.org/10.1371/journal.pone.0073700.g005

Sensitivity analysis and bias diagnosis

Using a sensitivity analysis, we investigated whether modification of the inclusion criteria for the meta-analysis affected the final results. No other single study influenced the summary OR qualitatively (data not shown). Egger’s test was performed to assess publication bias and to provide statistical evidence of funnel plot symmetry, and data did not reveal evidence of publication bias.

Discussion

Studies suggest that down-regulation of the FAS gene may protect tumor cells against elimination by anti-tumor immune responses. Furthermore, FASL gene up-regulation may increase the ability of tumor cells to counter-attack the immune system via inducing apoptosis of FAS-sensitive lymphocytes [64,65]. Alteration of FAS and FASL gene expression decreases cellular apoptotic capacities, allowing many tumor cells to evade or suppress the immune system. Most previous studies indicate that decreased FAS expression and/or increased FASL expression was a common feature of malignant transformation and an early event associated with the development of most human cancers, including gastric cancer, prostate cancer, nasopharyngeal carcinoma, renal cell carcinoma and oral squamous cell carcinoma [2527,55,66]. Given the critical roles of FAS and FASL in the apoptotic process, it is biologically plausible that an alteration in either of these factors via a genetic polymorphism may affect cancer risk.

To the best of our knowledge, the current report is a timely, updated analysis that combines the findings of all previous publications that evaluated the FAS-1377G/A SNP and cancer risk. We performed a meta-analysis involving 17,858 cancer cases and 24,311 healthy controls. In the overall analysis, a decreased association was found between the FAS-1377G allele and cancer susceptibility in the three genetic models. Five studies inconsistent with HWE were deleted to increase the power of the current analysis. Similar findings were also indicated for overall cancer risk. In addition, the disruption of the FAS-1377G/A SNP diminishes promoter activity and decreases FAS gene expression. These findings suggest that the -1377G allele in the FAS gene protects against the development of cancer and that the -1377A allele confers an increased risk for the development of cancer.

A vital property of gene polymorphisms is their substantial variation in incidence among different racial or ethnic populations. In the ethnicity subgroup analysis, we found that a significant association between the FAS-1377G allele and a decreased risk of cancer in Asians, suggesting genetic-based ethnic diversity. Two possible reasons may explain this difference. On one hand, differences in genetic and environmental backgrounds exist among different ethnicities. On the other hand, different populations usually have different linkage disequilibrium patterns. A polymorphism may be in close linkage with different but nearby causal variants in different populations [67].

In the cancer type subgroup analysis, significant associations were detected between the FAS-1377 G/A SNP and skin carcinoma, breast cancer and ‘other cancers’, rather than gastric, lung, and prostate cancers. A possible explanation for this phenomenon is that cancer is a multi-factorial disease that results from complex interactions between many genetic and environmental factors. Thus, a single gene or a single environmental factor is not likely to have a large effect on cancer susceptibility [68].

It is well known that smoking is a risk factor for various diseases, including cancer and that chronic smoking enhances FAS and FASL expression in peripheral blood lymphocytes, which can result in lymphocyte self-destruction or lymphocyte-mediated destruction of other lymphocytes and subsequent immune impairment in smokers [69,70]. The FAS-1377 SNP G-to-A substitution destroyed the binding element of transcription factor STAT1, reduced transcription activity, and decreased FAS expression. Possibly, individuals who carry the FAS-1377 A allele and smoke may have a higher risk of cancer, and this concept was supported by the data in our meta-analysis.

In the stratified analysis by ‘source of control’ group, moderate strength was observed in HB but not PB controls. This discrepancy may result from a differential influence of selection criteria in different cancers, as well as the weight of each study, which was dictated by sample size in our meta-analysis. HB controls were not strictly healthy individuals, and confounding results may have arisen from the inclusion of controls who were not disease-free, leading to poor statistical representation and publication bias.

An additive gene–gene interaction was observed between FAS-1377G/A and FASL-844T/C polymorphisms and decreased risk of cancer [71], suggesting that both polymorphisms may be active in the same causal pathway. The statistical interaction between FAS-1377G/A and FASL-844T/C polymorphisms is biologically plausible because these two molecules comprise a receptor-ligand system, and apoptotic cell death requires both normal FAS and FASL [72]. Therefore, if a cell carries functional polymorphisms in both genes that affect expression, a greater-than-additive effect is to be expected. In cancer development, transformed cells carrying the FASL-844CC genotype that express increased FASL may create an immuno-privileged site by killing cytotoxic immune cells, thereby escaping host immuno-surveillance. In contrast, reduced FAS expression due to the FAS-1377AA genotype may assist the transformed cells in evading FAS- mediated cell death. Thus, subjects carrying both FAS-1377AA and FASL-844CC could be at higher risk for developing cancer than those carrying either FAS-1377AA or FASL-844CC alone [45,73,74]. In other words, individuals carrying both FAS -1377(GG+GA) and FASL -844(TT+TC) genotypes could be at lower risk for developing cancer than those carrying either FAS-1377(GG+GA) alone, which was consistent with our results.

Meta-analysis is an effective method for investigating various clinical questions by summarizing and reviewing published, quantitative studies. Limitations in the present meta-analysis include the suboptimal number of published studies for a comprehensive analysis, especially in terms of linking smoking status, sex and other cancer types. Secondly, gene–gene and gene–environment interactions as well as interactions between different polymorphic loci of the same gene may modulate cancer risk. Thus, these factors should be included in future research and analysis. In addition, our meta-analysis was based on unadjusted estimates. A more precise analysis should be conducted if individual data are available to adjust for other covariates including age, sex, family history, environmental factors, cancer stage, and lifestyle. Finally, controls may not have been truly healthy individuals. In spite of these limitations, there were two advantages to our meta-analysis. First, a substantial number of cases and controls were pooled from different studies, which significantly increased the statistical power of the analysis. Second, the quality of case–control studies included in the current meta-analysis was satisfactory based on our selection criteria.

In summary, in the present meta-analysis, a significantly decreased association was found between FAS-1377 G/A SNP and cancer risk. Specifically, the-1377G allele was considered to be a protective factor against cancer. Therefore, further large studies, particularly examining gene–gene and gene–environment interactions, are warranted. These future studies could lead to a better and more comprehensive understanding of the association between the FAS-1377 G/A polymorphism and development of cancer risk.

Supporting Information

Table S1.

Study characteristics from published studies on the relationship between Fas -1377 G/A SNP and cancer risk.

https://doi.org/10.1371/journal.pone.0073700.s001

(DOC)

Author Contributions

Conceived and designed the experiments: ZZ MY. Performed the experiments: MY MHZ. Analyzed the data: ZL ZJ. Contributed reagents/materials/analysis tools: ZJ. Wrote the manuscript: MY ZL.

References

  1. 1. World Health Organization (2008) The Global Burden of Disease: 2004 Update. Geneva: World Health Prganization.
  2. 2. Dong LM, Potter JD, White E, Ulrich CM, Cardon LR et al. (2008) Genetic susceptibility to cancer: the role of polymorphisms in candidate genes. JAMA 299: 2423-2436. doi:https://doi.org/10.1001/jama.299.20.2423. PubMed: 18505952.
  3. 3. Zintzaras E (2010) The generalized odds ratio as a measure of genetic risk effect in the analysis and meta-analysis of association studies. Stat Appl Genet Mol Biol 9: Article21 . PubMed: 20597847.
  4. 4. Wokolorczyk D, Gliniewicz B, Sikorski A, Zlowocka E, Masojc B et al. (2008) A range of cancers is associated with the rs6983267 marker on chromosome 8. Cancer Res 68: 9982-9986. doi:https://doi.org/10.1158/0008-5472.CAN-08-1838. PubMed: 19047180.
  5. 5. Harismendy O, Frazer KA (2009) Elucidating the role of 8q24 in colorectal cancer. Nat Genet 41: 868-869. doi:https://doi.org/10.1038/ng0809-868. PubMed: 19639026.
  6. 6. Danial NN, Korsmeyer SJ (2004) Cell death: critical control points. Cell 116: 205-219. doi:https://doi.org/10.1016/S0092-8674(04)00046-7. PubMed: 14744432.
  7. 7. Evan GI, Vousden KH (2001) Proliferation, cell cycle and apoptosis in cancer. Nature 411: 342-348. doi:https://doi.org/10.1038/35077213. PubMed: 11357141.
  8. 8. Lowe SW, Lin AW (2000) Apoptosis in cancer. Carcinogenesis 21: 485-495. doi:https://doi.org/10.1093/carcin/21.3.485. PubMed: 10688869.
  9. 9. Nagata S, Golstein P (1995) The Fas death factor. Science 267: 1449-1456. doi:https://doi.org/10.1126/science.7533326. PubMed: 7533326.
  10. 10. Gastman BR, Atarshi Y, Reichert TE, Saito T, Balkir L et al. (1999) Fas ligand is expressed on human squamous cell carcinomas of the head and neck, and it promotes apoptosis of T lymphocytes. Cancer Res 59: 5356-5364. PubMed: 10537320.
  11. 11. Viard-Leveugle I, Veyrenc S, French LE, Brambilla C, Brambilla E (2003) Frequent loss of Fas expression and function in human lung tumours with overexpression of FasL in small cell lung carcinoma. J Pathol 201: 268-277. doi:https://doi.org/10.1002/path.1428. PubMed: 14517844.
  12. 12. Lee SH, Shin MS, Park WS, Kim SY, Kim HS et al. (1999) Alterations of Fas (Apo-1/CD95) gene in non-small cell lung cancer. Oncogene 18: 3754-3760. doi:https://doi.org/10.1038/sj.onc.1202769. PubMed: 10391683.
  13. 13. Bennett MW, O’Connell J, O’Sullivan GC, Brady C, Roche D et al. (1998) The Fas counterattack in vivo: apoptotic depletion of tumor-infiltrating lymphocytes associated with Fas ligand expression by human esophageal carcinoma. J Immunol 160: 5669-5675. PubMed: 9605174.
  14. 14. Aguilar-Reina J, Ruiz-Ferrer M, Pizarro MA, Antiñolo G (2005) The -670A > G polymorphism in the promoter region of the FAS gene is associated with necrosis in periportal areas in patients with chronic hepatitis C. J Viral Hepat 12: 568-573. https://doi.org/10.1111/j.1365-2893.2005.00639.x PubMed: 16255757.
  15. 15. Huang QR, Morris D, Manolios N (1997) Identification and characterization of polymorphisms in the promoter region of the human Apo-1/Fas (CD95) gene. Mol Immunol 34: 577-582. doi:https://doi.org/10.1016/S0161-5890(97)00081-3. PubMed: 9393960.
  16. 16. Sibley K, Rollinson S, Allan JM, Smith AG, Law GR et al. (2003) Functional FAS promoter polymorphisms are associated with increased risk of acute myeloid leukemia. Cancer Res 63: 4327-4330. PubMed: 12907599.
  17. 17. Sun T, Zhou Y, Li H, Han X, Shi Y et al. (2005) FASL -844C polymorphism is associated with increased activation-induced T cell death and risk of cervical cancer. J Exp Med 202: 967-974. https://doi.org/10.1084/jem.20050707 PubMed: 16186185.
  18. 18. Qiu LX, Shi J, Yuan H, Jiang X, Xue K et al. (2009) FAS -1,377 G/A polymorphism is associated with cancer susceptibility: evidence from 10,564 cases and 12,075 controls. Hum Genet 125: 431-435. doi:https://doi.org/10.1007/s00439-009-0639-4. PubMed: 19225810.
  19. 19. Zhang Z, Xue H, Gong W, Wang M, Yuan L et al. (2009) FAS promoter polymorphisms and cancer risk: a meta-analysis based on 34 case-control studies. Carcinogenesis 30: 487-493. doi:https://doi.org/10.1093/carcin/bgp016. PubMed: 19168581.
  20. 20. Mantel N, Haenszel W (1959) Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst 22: 719-748. PubMed: 13655060.
  21. 21. DerSimonian R, Laird N (1986) Meta-analysis in clinical trials. Control Clin Trials 7: 177-188. doi:https://doi.org/10.1016/0197-2456(86)90046-2. PubMed: 3802833.
  22. 22. Hayashino Y, Noguchi Y, Fukui T (2005) Systematic evaluation and comparison of statistical tests for publication bias. J Epidemiol 15: 235-243. doi:https://doi.org/10.2188/jea.15.235. PubMed: 16276033.
  23. 23. Kupcinskas J, Wex T, Bornschein J, Selgrad M, Leja M et al. (2011) Lack of association between gene polymorphisms of Angiotensin converting enzyme, Nod-like receptor 1, Toll-like receptor 4, FAS/FASL and the presence of Helicobacter pylori-induced premalignant gastric lesions and gastric cancer in Caucasians. BMC Med Genet 12: 112. doi:https://doi.org/10.1186/1471-2350-12-112. PubMed: 21864388.
  24. 24. Shao P, Ding Q, Qin C, Wang M, Tang J et al. (2011) Functional polymorphisms in cell death pathway genes FAS and FAS ligand and risk of prostate cancer in a Chinese population. Prostate 71: 1122-1130. doi:https://doi.org/10.1002/pros.21328. PubMed: 21557277.
  25. 25. Cao Y, Miao XP, Huang MY, Deng L, Lin DX et al. (2010) Polymorphisms of death pathway genes FAS and FASL and risk of nasopharyngeal carcinoma. Mol Carcinog 49: 944-950. doi:https://doi.org/10.1002/mc.20676. PubMed: 20842669.
  26. 26. Zhu J, Qin C, Wang M, Yan F, Ju X et al. (2010) Functional polymorphisms in cell death pathway genes and risk of renal cell carcinoma. Mol Carcinog 49: 810-817. PubMed: 20572163.
  27. 27. Wang LH, Ting SC, Chen CH, Tsai CC, Lung O et al. (2010) Polymorphisms in the apoptosis-associated genes FAS and FASL and risk of oral cancer and malignant potential of oral premalignant lesions in a Taiwanese population. J Oral Pathol Med 39: 155-161. doi:https://doi.org/10.1111/j.1600-0714.2009.00873.x. PubMed: 20359312.
  28. 28. Zhou RM, Wang N, Chen ZF, Duan YN, Sun DL et al. (2010) Polymorphisms in promoter region of FAS and FASL gene and risk of cardia gastric adenocarcinoma. J Gastroenterol Hepatol 25: 555-561. doi:https://doi.org/10.1111/j.1440-1746.2009.06116.x. PubMed: 20074157.
  29. 29. Wang M, Wu D, Tan M, Gong W, Xue H et al. (2009) FAS and FAS ligand polymorphisms in the promoter regions and risk of gastric cancer in Southern China. Biochem Genet 47: 559-568. doi:https://doi.org/10.1007/s10528-009-9264-0. PubMed: 19565204.
  30. 30. Ter-Minassian M, Zhai R, Asomaning K, Su L, Zhou W et al. (2008) Apoptosis gene polymorphisms, age, smoking and the risk of non-small cell lung cancer. Carcinogenesis 29: 2147-2152. doi:https://doi.org/10.1093/carcin/bgn205. PubMed: 18757527.
  31. 31. Yang M, Sun T, Wang L, Yu D, Zhang X et al. (2008) Functional variants in cell death pathway genes and risk of pancreatic cancer. Clin Cancer Res 14: 3230-3236. doi:https://doi.org/10.1158/1078-0432.CCR-08-0177. PubMed: 18483392.
  32. 32. Hsu PI, Lu PJ, Wang EM, Ger LP, Lo GH et al. (2008) Polymorphisms of death pathway genes FAS and FASL and risk of premalignant gastric lesions. Anticancer Res 28: 97-103. PubMed: 18383830.
  33. 33. Koshkina NV, Kleinerman ES, Li G, Zhao CC, Wei Q et al. (2007) Exploratory analysis of Fas gene polymorphisms in pediatric osteosarcoma patients. J Pediatr Hematol/Oncol 29: 815-821. doi:https://doi.org/10.1097/MPH.0b013e3181581506. PubMed: 18090928.
  34. 34. Kang S, Dong SM, Seo SS, Kim JW, Park SY (2008) FAS -1377 G/A polymorphism and the risk of lymph node metastasis in cervical cancer. Cancer Genet Cytogenet 180: 1-5. doi:https://doi.org/10.1016/j.cancergencyto.2007.09.002. PubMed: 18068525.
  35. 35. Crew KD, Gammon MD, Terry MB, Zhang FF, Agrawal M et al. (2007) Genetic polymorphisms in the apoptosis-associated genes FAS and FASL and breast cancer risk. Carcinogenesis 28: 2548-2551. doi:https://doi.org/10.1093/carcin/bgm211. PubMed: 17962219.
  36. 36. Jung YJ, Kim YJ, Kim LH, Lee SO, Park BL et al. (2007) Putative association of Fas and FasL gene polymorphisms with clinical outcomes of hepatitis B virus infection. Intervirology 50: 369-376. doi:https://doi.org/10.1159/000109751. PubMed: 17938571.
  37. 37. Gormus U, Ergen A, Yaylim-Eraltan I, Yilmaz H, Turna A et al. (2007) Fas-1377 A/G polymorphism in lung cancer. In Vivo 21: 663-666. PubMed: 17708363.
  38. 38. Ho T, Li G, Zhao C, Zheng R, Wei Q et al. (2008) Fas single nucleotide polymorphisms and risk of thyroid and salivary gland carcinomas: a case-control analysis. Head Neck 30: 297-305. doi:https://doi.org/10.1002/hed.20699. PubMed: 17657791.
  39. 39. Gormus U, Ergen A, Yilmaz H, Dalan B, Berkman S et al. (2007) Fas-1377A/G and FasL-844 T/C gene polymorphisms and epithelial ovarian cancer. Anticancer Res 27: 991-994. PubMed: 17465232.
  40. 40. Zhang B, Sun T, Xue L, Han X, Zhang B et al. (2007) Functional polymorphisms in FAS and FASL contribute to increased apoptosis of tumor infiltration lymphocytes and risk of breast cancer. Carcinogenesis 28: 1067-1073. PubMed: 17183065.
  41. 41. Zhang Z, Wang LE, Sturgis EM, El-Naggar AK, Hong WK et al. (2006) Polymorphisms of FAS and FAS ligand genes involved in the death pathway and risk and progression of squamous cell carcinoma of the head and neck. Clin Cancer Res 12: 5596-5602. doi:https://doi.org/10.1158/1078-0432.CCR-05-1739. PubMed: 17000697.
  42. 42. Li C, Larson D, Zhang Z, Liu Z, Strom SS et al. (2006) Polymorphisms of the FAS and FAS ligand genes associated with risk of cutaneous malignant melanoma. Pharmacogenet Genomics 16: 253-263. doi:10.1097/01.fpc.0000199501.54466.de. PubMed: 16538172.
  43. 43. Li C, Wu W, Liu J, Qian L, Li A et al. (2006) Functional polymorphisms in the promoter regions of the FAS and FAS ligand genes and risk of bladder cancer in south China: a case-control analysis. Pharmacogenet Genomics 16: 245-251. doi:https://doi.org/10.1097/01.fpc.0000194425.58511.a7. PubMed: 16538171.
  44. 44. Sun T, Zhou Y, Li H, Han X, Shi Y et al. (2005) FASL -844C polymorphism is associated with increased activation-induced T cell death and risk of cervical cancer. FASL -844C polymorphism is associated with increased activation-induced T cell death and risk of cervical cancer. J Exp Med 202: 967-974. doi:10.1084/jem.20050707. PubMed: 16186185.
  45. 45. Zhang X, Miao X, Sun T, Tan W, Qu S et al. (2005) Functional polymorphisms in cell death pathway genes FAS and FASL contribute to risk of lung cancer. J Med Genet 42: 479-484. doi:https://doi.org/10.1136/jmg.2004.030106. PubMed: 15937082.
  46. 46. Sun T, Miao X, Zhang X, Tan W, Xiong P et al. (2004) Polymorphisms of death pathway genes FAS and FASL in esophageal squamous-cell carcinoma. J Natl Cancer Inst 96: 1030-1036. doi:https://doi.org/10.1093/jnci/djh187. PubMed: 15240787.
  47. 47. Sibley K, Rollinson S, Allan JM, Smith AG, Law GR et al. (2003) Functional FAS promoter polymorphisms are associated with increased risk of acute myeloid leukemia. Cancer Res 63: 4327-4330. PubMed: 12907599.
  48. 48. Wang W, Zheng Z, Yu W, Lin H, Cui B et al. (2012) Polymorphisms of the FAS and FASL genes and risk of breast cancer. Oncol Lett 3: 625-628. PubMed: 22740964.
  49. 49. Tong N, Zhang L, Sheng X, Wang M, Zhang Z et al. (2012) Functional polymorphisms in FAS, FASL and CASP8 genes and risk of childhood acute lymphoblastic leukemia: a case-control study. Leuk Lymphoma 53: 1360-1366. doi:https://doi.org/10.3109/10428194.2011.654117. PubMed: 22211869.
  50. 50. Lai HC, Lin WY, Lin YW, Chang CC, Yu MH et al. (2005) Genetic polymorphisms of FAS and FASL (CD95/CD95L) genes in cervical carcinogenesis: An analysis of haplotype and gene-gene interaction. Gynecol Oncol 99: 113-118. doi:https://doi.org/10.1016/j.ygyno.2005.05.010. PubMed: 15996722.
  51. 51. Zhang H, Sun XF, Synnerstad I, Rosdahl I (2007) Importance of FAS-1377, FAS-670, and FASL-844 polymorphisms in tumor onset, progression, and pigment phenotypes of Swedish patients with melanoma: a case-control analysis. Cancer J 13: 233-237. doi:https://doi.org/10.1097/PPO.0b013e318046f214. PubMed: 17762757.
  52. 52. Kim HJ, Jin XM, Kim HN, Lee IK, Park KS et al. (2010) Fas and FasL polymorphisms are not associated with acute myeloid leukemia risk in Koreans. DNA Cell Biol 29: 619-624. doi:https://doi.org/10.1089/dna.2010.1032. PubMed: 20438363.
  53. 53. Mandal RK, Mittal RD (2012) Are cell cycle and apoptosis genes associated with prostate cancer risk in North Indian population? Are cell cycle and apoptosis genes associated with prostate cancer risk in North Indian population? Urol Oncol 30: 555-561. doi:https://doi.org/10.1016/j.urolonc.2010.05.006. PubMed: 20822933.
  54. 54. Qureshi A, Nan H, Dyer M, Han J (2010) Polymorphisms of FAS and FAS ligand genes and risk of skin cancer. J Dermatol Sci 58: 78-80. doi:https://doi.org/10.1016/j.jdermsci.2010.01.003. PubMed: 20219325.
  55. 55. Zhang W, Li C, Wang J, He C (2012) Functional polymorphisms in FAS/FASL system contribute to the risk of occurrence but not progression of gastric cardiac adenocarcinoma. Hepatogastroenterology 59: 141-146. PubMed: 21940365.
  56. 56. Li Y, Hao YL, Kang S, Zhou RM, Wang N et al. (2013) Genetic polymorphisms in the Fas and FasL genes are associated with epithelial ovarian cancer risk and clinical outcomes. Gynecol Oncol 128: 584-589. doi:https://doi.org/10.1016/j.ygyno.2012.12.002. PubMed: 23234803.
  57. 57. Park SH, Choi JE, Kim EJ, Jang JS, Lee WK et al. (2006) Polymorphisms in the FAS and FASL genes and risk of lung cancer in a Korean population. Lung Cancer 54: 303-308. doi:https://doi.org/10.1016/j.lungcan.2006.09.002. PubMed: 17014925.
  58. 58. Zhang MJ, Liu CH, Wang WQ, Xu CQ, Chen ZP et al. (2010) Aossociation between Fas -1377 gene polymorphism and susceptibility of gastric cancer (Chinese). ShanDongYinYao 50: 36-37.
  59. 59. Li H, Guo HY, Sun T, Zhou YF, Lin DX et al. (2009) Association between Fas/Fas L gene promoter polymorphisms and pathogenic risk of cervical cancer (Chinese). Chin J Oncol 31: 38-41.
  60. 60. Yang S, Miao XP, Zhang XM, Sun T, Qu SN et al. (2005) Genetic polymorphisms of apoptosis-associated genes FAS and FASL and risk of colorectal cancer (Chinese). Natl Med J China 85: 2132-2135.
  61. 61. Zhou RM, Wang N, Sun DL, Duan YN, Hou XR et al. (2010) Correlation of polymorphism in apoptosis-associated genes FAS and FASL to the risk of gastric cardiac adenocarcinoma (Chinese). Chin J Cancer Prev Treat 17: 1609-1622.
  62. 62. Hashemi M, Fazaeli A, Ghavami S, Eskandari-Nasab E, Arbabi F et al. (2013) Functional polymorphisms of FAS and FASL gene and risk of breast cancer - pilot study of 134 cases. PLOS ONE 8: e53075. doi:https://doi.org/10.1371/journal.pone.0053075. PubMed: 23326385.
  63. 63. Liu L, Wu C, Wang Y, Zhong R, Wang F et al. (2011) Association of candidate genetic variations with gastric cardia adenocarcinoma in Chinese population: a multiple interaction analysis. Carcinogenesis 32: 336-342. doi:https://doi.org/10.1093/carcin/bgq264. PubMed: 21148629.
  64. 64. Müschen M, Warskulat U, Beckmann MW (2000) Defining CD95 as a tumor suppressor gene. J Mol Med (Berl) 78: 312-325. doi:https://doi.org/10.1007/s001090000112. PubMed: 11001528.
  65. 65. Reichmann E (2002) The biological role of the Fas/FasL system during tumor formation and progression. Semin Cancer Biol 12: 309-315. doi:https://doi.org/10.1016/S1044-579X(02)00017-2. PubMed: 12147205.
  66. 66. Ueda M, Terai Y, Kanda K, Kanemura M, Takehara M et al. (2006) Fas gene promoter -670 polymorphism in gynecological cancer. Int J Gynecol Cancer 16 Suppl 1: 179-182. doi:https://doi.org/10.1111/j.1525-1438.2006.00505.x. PubMed: 16515587.
  67. 67. Li TF, Ren KW, Liu PF (2012) Meta-analysis of epidermal growth factor polymorphisms and cancer risk: involving 9,779 cases and 15,932 controls. DNA Cell Biol 31: 568-574. doi:https://doi.org/10.1089/dna.2011.1394. PubMed: 22070650.
  68. 68. Pharoah PD, Dunning AM, Ponder BA, Easton DF (2004) Association studies for finding cancer-susceptibility genetic variants. Nat Rev Cancer 4: 850-860. doi:https://doi.org/10.1038/nrc1476. PubMed: 15516958.
  69. 69. Bijl M, Horst G, Limburg PC, Kallenberg CG (2001) Effects of smoking on activation markers, Fas expression and apoptosis of peripheral blood lymphocytes. Eur J Clin Invest 31: 550-553. doi:https://doi.org/10.1046/j.1365-2362.2001.00842.x. PubMed: 11422406.
  70. 70. Suzuki N, Wakisaka S, Takeba Y, Mihara S, Sakane T (1999) Effects of cigarette smoking on Fas/Fas ligand expression of human lymphocytes. Cell Immunol 192: 48-53. doi:https://doi.org/10.1006/cimm.1998.1432. PubMed: 10066346.
  71. 71. Brennan P (2002) Gene-environment interaction and aetiology of cancer: what does it mean and how can we measure it? Carcinogenesis 23: 381-387. doi:https://doi.org/10.1093/carcin/23.3.381. PubMed: 11895852.
  72. 72. Krammer PH (2000) CD95’s deadly mission in the immune system. Nature 407: 789-795. doi:https://doi.org/10.1038/35037728. PubMed: 11048730.
  73. 73. Zhong R, Liu L, Zou L, Sheng W, Zhu B et al. (2013) Genetic variations in the TGFβ signaling pathway, smoking and risk of colorectal cancer in a Chinese population. Carcinogenesis 34: 936-942. doi:https://doi.org/10.1093/carcin/bgs395. PubMed: 23275154.
  74. 74. Wu C, Miao X, Huang L, Che X, Jiang G et al. (2011) Genome-wide association study identifies five loci associated with susceptibility to pancreatic cancer in Chinese populations. Nat Genet 44: 62-66. doi:https://doi.org/10.1038/ng.1020. PubMed: 22158540.