Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Four Genetic Polymorphisms of Lymphotoxin-Alpha Gene and Cancer Risk: A Systematic Review and Meta-Analysis

Abstract

Lymphotoxin-alpha (LTA) is a pro-inflammatory cytokine that plays an important role in the inflammatory and immunologic response. Numerous studies have shown LTA polymorphisms as risk factors for cancers, but the results remain inconclusive. The goal of the present meta-analyses is to establish the associations between cancers and four LTA variants (rs1041981, rs2239704, rs2229094 and rs746868). A total of 30 case-control studies involving 58,649 participants were included in the current meta-analyses. Our results showed significant associations with increased cancer risk for rs1041981 (odd ratio (OR) = 1.15, 99% confidential interval (CI) = 1.07-1.25, P < 0.0001, I2 = 12.2%), rs2239704 (OR = 1.08, 99% CI = 1.01-1.16, P = 0.021, I2 = 0.0%) and rs2229094 (OR = 1.28, 99% CI = 1.09-1.50, P = 0.003, I2 = 0.0%). No evidence was found for the association between rs746868 and cancer risk (OR = 1.01, 99% CI = 0.93-1.10, P = 0.771, I2 = 0.0%). Subgroup meta-analysis suggested that rs2239704 was likely to increase the risk of hematological malignancy (OR = 1.10, 99% CI = 1.01–1.20, P = 0.023, I2 = 0.0%), and rs2229094 was specific for the increased risk of adenocarcinoma (OR = 1.33, 99% CI = 1.11-1.59, P = 0.002, I2 = 0.0%). In conclusion, our meta-analyses suggested that the LTA rs1041981, rs2239704 and rs2229094 polymorphisms contributed to the increased risk of cancers. Future functional studies were needed to clarify the mechanistic roles of the three variants in the cancer risk.

Introduction

With the high prevalence and mortality rate, cancers have become one of the main causes of morbidity and mortality worldwide [1]. There are over 200 different known cancers in humans, and the mechanisms of cancer pathogenesis remain obscure [2]. Large epidemiologic and clinical studies have illustrated that inflammation may be associated with the development of cancers [3,4]. Increasing evidence suggests that predisposition to cancer is associated with cytokines [5,6], such as tumor necrosis factors (TNF) [7,8].

Lymphotoxin-alpha (LTA) is a pro-inflammatory cytokine belong to the TNF family which plays an important role in the inflammatory and immunologic response [9]. LTA is a product of stimulated T cells [10,11], and it can help communicate lymphocytes and stromal cells and subsequently eliciting cytotoxic effects on cancer cells [9,12]. LTA gene is located on the 6p21.3 that harbors the class III region of the major histocompatibility complex (MHC) locus [13]. Genetic variations of inflammation-related genes are shown to alter both the regulation of the inflammatory response and modulation of susceptibility to radiation-induced normal tissue damage [14]. LTA gene polymorphisms are shown to be associated with the inflammatory and immunomodulatory diseases including cancers [15,16]. The association is significant between LTA polymorphisms and cancers including gastric [15] and breast [17] cancers in Asians, colorectal cancer [18] in Germans, and Non-Hodgkin Lymphoma (NHL) in Europeans [19-21]. However, discrepancies remain for the association of LTA polymorphisms with cancers in different ethnic groups [15,16,22-24].

Four LTA polymorphisms (rs1041981:Thr26Asn; rs2239704; rs2229094: Cys13Arg; rs746868) have been extensively investigated as potential risk factor for cancer. These mutations may exert possible regulatory regulation on the gene expression and the level of cytokine production [25,26]. Single nucleic polymorphism (SNP) rs1041981 (Thr26Asn) [27] is associated with the transcriptional regulation of LTA, which may activate the lymphocytes and induce apoptosis [27]. SNP rs2239704 can modulate both LTA levels and subsequent inflammatory response to pathogens [28]. SNP rs746868 is shown to be in high linkage disequilibrium (LD) with rs1041981 (r2 > 0.8) [29]. SNPs rs746868 and rs2239704 are significant predictive variables of LTA protein production [28]. Haplotype of SNP rs2229094 is shown to be associated with altered LTA expression and increased levels of vascular- and autoimmune-mediated inflammation [30].

The associations of LTA variations with cancer risk have been evaluated by several case-control studies [18-20,31-52]. Previous studies have suggested that the functional polymorphism rs909253 is associated with gastric [15] and breast [17] cancers in Asians. Although the four SNPs (rs1041981, rs2239704, rs2229094 and rs746868) are present in high LD with rs909253 [27,28], inconsistent results of the four SNPs and cancer risk are observed for different cancers in Asian, North American and European populations [18-20,22-24,31-51]. In the current study, we perform a comprehensive meta-analysis to evaluate the effects of the four functional SNPs (rs1041981, rs2239704, rs2229094 and rs746868) on cancer risk.

Materials and Methods

Publication search

The literatures included in the analysis were obtained from the databases of PubMed, Web of Science, and China National Knowledge Infrastructure (CNKI). The keywords applied the Medical Subject Headings (MeSH) in the US National Library of Medicine terms including “LTA”, “Lymphotoxin alpha”, “TNF-beta”, “polymorphism”, and “rs1041981”, “Thr26Asn”, “rs746868”, “rs2229094”, “Cys13Arg” or “rs2239704” paired with “cancer” or “tumor”. Meanwhile, the manuscripts should be published in Chinese or English up to July 2013. Full texts were read to select the relevant information. The related articles in the MEDLINE as well as the reference lists of all retrieved studies were also checked for citations of other relevant publications that were not identified initially.

Inclusion criteria

Articles enrolled in our meta-analyses met the following inclusion criteria: (1) evaluating the association between LTA polymorphism rs1041981, rs2239704, rs2229094 or rs746868 and cancer risk; (2) case-control study; (3) results with sufficient published data to estimate an OR with a 95% CI; (4) the genotype distribution in controls met Hardy-Weinberg equilibrium (HWE).

Data extraction

Two investigators (YH and XY) independently extracted the data from all eligible publications basis on the selection criteria listed above. Any disagreements were established by discussion until a consensus was reached. If there were numerous publications from the same study group, the most complete and recent results were extracted. Useful information collected from each study comprise the first author’s surname, the year of publication, country, ethnic population, source of control groups (population- or hospital-based), cancer type, total sample size, genotyping method and the number of genotype distribution in cases and controls.

Statistical analyses

ORs and 99% CIs in the case-control studies were employed to assess the association between the LTA polymorphisms and cancer risk. The pooled ORs were performed under the additive, dominant, and recessive models. Z test was employed to estimate the significance of pooled OR. The departure of HWE for the genotype distribution in controls were analyzed by the Arlequin program (version 3.5) [53]. The meta-analyses were performed using the Review Manger and Stata software (version 11.0, Stata Corporation, College Station, TX) [54]. A chi-square based Q-statistic test was calculated for the heterogeneity of studies in the meta-analysis [55,56]. The inconsistency index (I2 statistic) was examined to judge the heterogeneity between studies [56]. An I2 > 50% suggested a significant heterogeneity in the meta-analysis. Random-effect [57] or fixed-effect [55,58] models were used for, the meta-analysis with significant heterogeneity (I2 > 50%) or the one with minimal to moderate heterogeneity (I2 < 50%), respectively. Subgroup meta-analyses were performed by cancer type, population, and source of control. A sensitivity analysis was also performed by excluding each study. The Begg’s funnel plots and Egger regression test were used to evaluate the Publication bias [59]. A two-tailed P < 0.05 was considered statistically significant.

Results

Literature flow

As shown in Figure 1, the literature search identified a total of 248 potentially relevant records. After reading the title or abstract, 50 studies concerning the association for the four LTA polymorphisms and cancer risk were considered for the following step. A total of 16 articles were excluded for insufficient genotyping information, or ineligible samples, or other LTA polymorphism, or duplicated studies. Finally, we collected 24 articles [18-20,31-52] (including 30 study stages) focusing on the relationship of rs1041981, rs2239704, rs2229094 or rs746868 polymorphisms with cancer risk.

thumbnail
Figure 1. Flow diagram depicts literature search and study selection.

https://doi.org/10.1371/journal.pone.0082519.g001

Study characteristics

Characteristics of enrolled studies were summarized in Table 1. Among the 24 eligible studies, 8 articles [18,20,31,34,35,39,48,52] (including 11 stages with 7,483 cases and 11,938 controls) focused on the association between rs1041981 and cancers. A total of 10 studies [19,33,36,38,40,41,43,46,47], reported the association of cancers with rs2239704 including 13 stages among 6,049 cases and 7,621 controls. And 5 studies (including 9 stages) [19,31,46,51,52] among 7,133 cases and 10,305 controls evaluated the contribution of rs2229094 to the risk of cancers. There were 7 articles (including 3,487 cases and 4,633 controls) [32,37,42,44-46,49] involved with the association between rs746868 and cancers. All the records were collected from English publications. There were 7 Asian studies, 9 European studies, and 14 North American studies. Most of the cancer types were adenocarcinoma and hematological malignancy including gastric [31,34,42,45,46,49], breast [32,51,52], lung [31], prostate [38,44], and cervical cancers [35,39,48], colorectal adenoma [18,37], Non-Hodgkin Lymphoma (NHL) [19,20,33,36,40,47], Chronic Lymphocytic Leukaemia (CLL) [43] and Testicular Germ Cell Tumors (TGCT) [41]. The 30 selected studies in the meta-analysis included 13 studies with hospital-based controls, 17 studies with population-based controls. The controls were primarily population-based ones matched for ethnicity, age, gender or study region.

First author (year)Case/controlCancer typePopulationsSNPSource of controlMatching
Takei K (2008)570/581ACAsianrs2229094, rs1041981HBEthnicity, study region
Takei K (2008)159/581ACAsianrs2229094, rs1041981HBEthnicity, study region
Takei K (2008)177/581ACAsianrs2229094, rs1041981HBEthnicity, study region
Mahajan R (2008)301/415ACEuropeanrs2229094, rs2239704, rs746868PBAge, gender, study region, ethnicity
Wang SS (2009)990/827HMNorth Americanrs2229094,rs2239704PBEthnicity, frequency
Wang SS (2009)434/515HMNorth Americanrs2229094,rs2239704PBEthnicity, frequency
Wang SS (2009)518/462HMNorth Americanrs2229094,rs2239704PBEthnicity, frequency
Abbas S (2010)3136/5477ACEuropeanrs2229094,rs1041981PBAge, study region, ethnicity
Madeleine MM (2011)848/866ACNorth Americanrs2229094PBAge, ethnicity
Wang SS (2006)1029/842HMNorth Americanrs2239704PBAge, gender
Lan Q (2006)417/499HMNorth Americanrs2239704PBAge, ethnicity, residence
Liu X (2006)822/861ACNorth Americanrs2239704PBAge, ethnicity, date of blood collection
Purdue MP (2007)210/602OCbNorth Americanrs2239704PBAge, gender, ethnicity, date of collection
Purdue MP (2007)296/602OCbNorth Americanrs2239704PBAge, gender, ethnicity, date of collection
Purdue MP (2007)352/463HMEuropeanrs2239704HBAge, gender, residence
Cerhan JR (2008)441/474HMNorth Americanrs2239704HBAge, gender, residence
Jacobs EJ (2008)453/1184ACNorth Americanrs2239704, rs746868HBAge, ethnicity, date of blood collection
Ennas MG (2008)38/112HMEuropeanrs2239704PBAge, gender
Lee SG (2004)328/253ACAsianrs1041981PBGender, study region
Niwa Y (2005)44/320ACAsianrs1041981HBGender, study region
Niwa Y (2005)87/320SCbAsianrs1041981HBGender, study region
Niwa Y (2007)110/220ACAsianrs1041981HBAge, gender
Aissani B (2009)135/140HMNorth Americanrs1041981HBCD4+ counts, the duration of HIV infection
Castro FA (2009)951/1707SCbEuropeanrs1041981PBAge, ethnicity, study region
Sainz J (2012)1760/1727ACEuropeanrs1041981PBAge, gender, study region
Gunter MJ (2006)219/205ACNorth Americanrs746868HBAge, gender, ethnicity, study region
Gaudet MM (2007)1622/1288ACNorth Americanrs746868PBAge, residence
Garcia-Gonzalez (2007)404/404ACEuropeanrs746868HBAge, gender, ethnicity, residence
Crusius JB (2008)428/1124ACEuropeanrs746868PBAge, gender, residence, date of collection
García-González (2009)57/24ACEuropeanrs746868HBEthnicity, study region

Table 1. Characteristics of studies included in the meta-analysesa.

a: PB, Population based; HB, Hospital based; AC: Adenocarcinoma; HM: Hematological malignancy; SC: Squamous carcinoma; OC: Other cancer
b: The two studies of squamous carcinoma are all cervical cancer; the two studies of other cancer are testicular germ cell tumors (TGCT) including seminoma and no seminoma.
CSV
Download CSV

As shown in Table 2, the genotype distribution of the four SNPs and the genotyping method of the collected studies were retrieved carefully. Genotype distributions of four polymorphisms in all the controls met HWE (P > 0.05).

SNPFirst author (Year)Case (AA/Aa/aa)Control (AA/Aa/aa)HWEGenotyping
rs2229094 Takei K (2008)374/179/17396/172/130.30Melting curve
(TT/TC/CC)Takei K (2008)98/52/9396/172/130.30Melting curve
Takei K (2008)110/58/9396/172/130.30Melting curve
Mahajan R (2008)206/74/21247/150/180.48TaqMan
Wang SS (2009)530/387/73433/333/610.86TaqMan
Wang SS (2009)231/167/36269/209/370.74TaqMan
Wang SS (2009)282/179/39276/160/260.69TaqMan
Abbas S (2010)1686/1199/2512965/2153/3590.23MassArray
Madeleine MM (2011)444/329/75475/334/570.93SNPlex
rs2239704Wang SS (2006)421/446/162332/370/1400.05TaqMan
(CC/AC/AA)Lan Q (2006)165/189/63186/226/870.23TaqMan
Liu X (2006)285/537351/510> 0.05TaqMan
Purdue MP (2007)82/99/29221/290/910.86TaqMan
Purdue MP (2007)89/154/53221/290/910.86TaqMan
Purdue MP (2007)138/168/46162/229/720.63TaqMan
Cerhan JR (2008)169/217/55170/225/790.78TaqMan
Ennas MG (2008)14/17/736/53/230.70TaqMan
Mahajan R (2008)85/138/76105/223/850.12TaqMan
Wang SS (2009)357/373/132284/311/1160.06TaqMan
Wang SS (2009)143/152/51162/189/740.15TaqMan
Wang SS (2009)197/229/58153/214/660.62TaqMan
rs1041981 Lee SG (2004)109/156/6374/132/470.44PCR-sequencing
(CC/AC/AA)Niwa Y (2005)17/23/4107/165/480.25AmpliTaq Gold
Niwa Y (2005)43/36/8107/165/480.25AmpliTaq Gold
Niwa Y (2007)51/43/1671/114/350.40AmpliTaq Gold
Takei K (2008)211/280/87195/304/890.11Melting curve
Takei K (2008)73/71/20195/304/890.11Melting curve
Takei K (2008)74/73/32195/304/890.11Melting curve
Aissani B (2009)50/63/2271/61/80.39BeadArray
Castro FA (2009)341/456/154557/813/3370.20MassArray
Abbas S (2010)1498/1317/3322481/2399/6070.47MassArray
Sainz J (2012)833/729/198794/760/1730.69KASPar Assay
rs746868Gunter MJ (2006)85/107/2776/102/270.46TaqMan
(GG/GC/CC)Gaudet MM (2007)576/769/277446/621/2210.86AmpFlSTR
Garcia-Gonzalez (2007)135/194/75142/191/710.48TaqMan
Mahajan R (2008)83/143/74108/220/840.16TaqMan
Crusius JB (2008)151/205/72398/545/1810.85TaqMan
García-González (2009)19/26/129/10/50.67RFLP

Table 2. Distribution of the four SNPs genotypes between cancer and control group included in the meta-analysesc.

c: The results of Jacobs EJ et al (2008) are not listed in the table because they only proved the A allele frequency. The study of Liu X et al (2006) only proves the number of CC/CA+AA.
CSV
Download CSV

Meta-analysis of rs1041981

The main results of the meta-analysis for rs1041981 polymorphism were presented in Table 3. No heterogeneity existed in the involved studies (I2 = 16.0%, P = 0.29). The summary effect OR was 1.10 for G allele (99% CI = 1.04-1.16, P = 0.001, Figure 2). Subgroup analysis suggested that rs1041981 increased the risk of several types of cancer, such as adenocarcinoma (OR = 1.07, 99% CI = 1.01-1.14, P = 0.030, I2 = 0.08%), squamous carcinoma (OR = 1.19, 99% CI = 1.03-1.37, P = 0.018, I2 = 46.0%), hematological malignancy (OR = 1.73, 99% CI = 1.08-2.77, P = 0.023). The significant association were also found in multiple populations including Asians (OR = 1.18, 99% CI = 1.04-1.34, P = 0.010, I2 = 0.0%) and Europeans (OR = 1.07, 99% CI = 1.00-1.14, P = 0.047, I2 = 0.0%). In addition, the source analysis showed positive association in both hospital-based group (OR = 1.24, 99% CI = 1.09-1.42, P = 0.001, I2 = 0.0%) and population-based group (OR = 1.07, 99% CI = 1.00-1.14, P = 0.042, I2 = 0.0%, Table 3).

VariablesAdditive model Dominant modelRecessive model
NP, OR(99% CI)P(Q-test), I2P, OR(99% CI)P(Q-test), I2P, OR(99% CI)P(Q-test), I2
Total110.001, 1.10(1.04-1.16)0.29, 16.0%<0.0001, 1.15(1.07-1.25)0.33, 12.2%0.035, 1.13(1.01-1.27)0.76, 0.0%
Cancer type
Adenocarcinoma 80.030, 1.07(1.01-1.14)0.69, 0.08%0.003, 1.14(1.04-1.24)0.43, 0.0%0.246, 1.08(0.95-1.23)0.99, 0.0%
Squamous carcinoma20.018, 1.19(1.03-1.37)0.17, 46.0%0.061, 1.21(0.99-1.49)0.12, 58.3%0.053, 1.30(1.00-1.69)0.56, 0.0%
Hematological malignancy10.023, 1.73(1.08-2.77)NA0.083, 1.75(0.93-3.29)NA0.040, 3.21(1.05-9.80)NA
Population
Asian70.010, 1.18(1.04-1.34)0.64, 0.0%<0.0001, 1.39(1.16-1.66)0.35, 11.4%0.357, 1.12(0.88-1.43)0.93, 0.0%
North American10.023, 1.73(1.08-2.77)NA0.083, 1.75(0.93-3.29)NA0.040, 3.21(1.05-9.80)NA
European30.047, 1.07(1.00-1.14)0.38, 0.0%0.035, 1.10(1.01-1.20)0.84, 0.0%0.096, 1.12(0.98-1.28)0.52, 0.0%
Source of control
Hospital based70.001, 1.24(1.09-1.42)0.44, 0.0%<0.0001, 1.45(1.20-1.74)0.68, 0.0%0.121, 1.23(0.95-1.60)0.61, 0.0%
Population based40.042, 1.07(1.00-1.14)0.58, 0.0%0.027, 1.10(1.01-1.20)0.92, 0.0%0.114, 1.11(0.98-1.26)0.66, 0.0%

Table 3. Meta-analysis of rs1041981.

NA: not applicable for the heterogeneity test.
CSV
Download CSV
thumbnail
Figure 2. Meta-analysis of LTA rs1041981 polymorphism and cancer risk in the additive model stratified by cancer type.

https://doi.org/10.1371/journal.pone.0082519.g002

Meta-analysis result of rs2239704

Figure 3 showed the forest plot for the rs2239704 stratified by cancer type. Significantly increased cancer risk was found in the G versus A model based on the studies (OR = 1.08, 99% CI = 1.01-1.16, P = 0.021, I2 = 0.0%, Table 4). In the subgroup meta-analysis by cancer type, the rs2239704-G was observed with positive association with hematological malignancy (OR = 1.10, 99% CI = 1.01-1.20, P = 0.023, I2 = 0.0%, Table 4). Significant associations of rs2239704 with hematological malignancy cancers were also found in North American populations (OR = 1.09, 99% CI = 1.01-1.17, P = 0.025, I2 = 2.7%) and in the population-based group (OR = 1.08, 99% CI = 1.00-1.17, P = 0.044, I2 = 2.2%, Table 4).

thumbnail
Figure 3. Meta-analysis of LTA rs2239704 polymorphism and cancer risk stratified by cancer type.

https://doi.org/10.1371/journal.pone.0082519.g003

VariablesAdditive model Dominant modelRecessive model
NP, OR(99% CI)P(Q-test), I2P, OR(99% CI)P(Q-test), I2P, OR(99% CI)P(Q-test), I2
Total130.021, 1.08(1.01-1.16)0.60, 0.0%0.019, 1.11(1.02-1.21)0.76, 0.0%0.027, 1.12(1.01-1.24)0.70, 0.0%
Cancer type
Hematological malignancy80.023, 1.10(1.01-1.20)0.99, 0.0%0.072, 1.12(0.99-1.26)0.99, 0.0%0.051, 1.17(1.00-1.38)0.99, 0.0%
Adenocarcinoma 30.132 1.10(0.97-1.25)0.11, 55.1%0.036, 1.16(1.01-1.34)0.25, 27.6%0.135, 1.11(0.97-1.28)0.05, 65.8%
Other cancer20.440, 0.93(0.76-1.13)0.18, 44.7%0.414, 0.89(0.67-1.18)0.18, 45.1%0.691, 0.93(0.63-1.35)0.44, 0.0%
Population
North American100.025, 1.09(1.01-1.17)0.41, 2.7%0.039, 1.10(1.00-1.21)0.53, 0.0%0.015, 1.14(1.03-1.27)0.75, 0.0%
European30.532, 1.06(0.88-1.28)0.64, 0.0%0.214, 1.19(0.90-1.57)0.99, 0.0%0.727, 0.94(0.68-1.31)0.38, 0.0%
Source of control
Hospital based30.257, 1.08(0.94-1.24)0.61, 0.0%0.444, 1.07(0.90-1.26)0.72, 0.0%0.386, 1.09(0.90-1.31)0.44, 0.0%
Population based100.044, 1.08(1.00-1.17)0.42, 2.2%0.022, 1.13(1.02-1.24)0.60, 0.0%0.038, 1.14(1.01-1.28)0.61, 0.0%

Table 4. Meta-analysis of rs2239704.

CSV
Download CSV

Meta-analysis result of rs2229094

The main pooled data for rs2229094 polymorphism were listed in Table 5. For the overall data of the enrolled 9 study stages, significant association of rs2229094 polymorphism with cancer risk were shown on Figure 4 (OR = 1.28, 99% CI = 1.09-1.50, P = 0.003, I2 = 0.0%). In the additional analysis, significantly increased risks were observed in adenocarcinoma (OR = 1.33, 99% CI = 1.11-1.59, P = 0.002, I2 = 0.0%). In the stratified analysis by population, strong association of rs2229094 with adenocarcinoma cancers was found in Asians (OR = 1.92, 99% CI = 1.04-3.57, P = 0.038, I2 = 0.0%) and Europeans (OR = 1.26, 99%CI = 1.02-1.56, P = 0.029, I2 = 0.0%). Further subgroup analysis in recessive model, statistically associations were presented both hospital-based (OR = 1.92, 99% CI = 1.04-3.57, P = 0.038, I2 = 0.0%) and population based groups (OR = 1.24, 99% CI = 1.05-1.46, P = 0.010, I2 = 0.0%, Table 5).

VariablesAdditive model Dominant modelRecessive model
NP, OR(99% CI)P(Q-test), I2P, OR(99% CI)P(Q-test), I2P, OR(99% CI)P(Q-test), I2
Total90.076, 1.06(0.99-1.13)0.55, 0.0%0.476, 1.03(0.95-1.12)0.46, 0.0%0.003, 1.28(1.09-1.50)0.82, 0.0%
Cancer type
Adenocarcinoma 60.064, 1.07(1.00-1.15)0.37, 7.0%0.415, 1.04(0.95-1.14)0.25, 24.8%0.002, 1.33(1.11-1.59)0.70, 0.0%
Hematological malignancy30.762, 1.06(0.99-1.13)0.57, 0.0%0.996, 1.00(0.85-1.18)0.64, 0.0%0.456, 1.13(0.82-1.57)0.70, 0.0%
Population
Asian30.041, 1.23(1.01-1.50)0.65, 0.0%0.104, 1.21(0.96-1.52)0.79 0.0%0.038, 1.92(1.04-3.57)0.82, 0.0%
European20.457, 1.03(0.95-1.13)0.19, 42.4%0.868, 0.99(0.89-1.11)0.06, 71.4%0.029, 1.26(1.02-1.56)0.52, 0.0%
North American40.347, 1.06(0.94-1.18)0.62, 0.0%0.645, 1.03(0.90-1.19)0.71, 0.0%0.168, 1.21(0.92-1.58)0.76, 0.0%
Source of control
Hospital based30.041, 1.23(1.01-1.50)0.65, 0.0%0.104, 1.21(0.96-1.52)0.79 0.0%0.038, 1.92(1.04-3.57)0.63, 0.0%
Population based60.244, 1.04(0.97-1.12)0.61, 0.0%0.877, 1.01(0.92-1.10)0.40, 1.9%0.010, 1.24(1.05-1.46)0.90, 0.0%

Table 5. Meta-analysis of rs2229094.

CSV
Download CSV
thumbnail
Figure 4. Meta-analysis of LTA rs2229094 polymorphism and cancer risk stratified by cancer type.

https://doi.org/10.1371/journal.pone.0082519.g004

Meta-analysis result of rs746868

There was no evidence of association between rs746868 and cancer risk (OR = 1.01, 99% CI = 0.93-1.10, P = 0.771, I2 = 0.0%, Table S1). Alternative genetic models and subgroup meta-analyses did not reveal any significant results (Table S1).

Sensitivity analyses and publication bias

The sensitivity analyses were performed by excluding each study. The statistical significance of the results was not changed (data not shown). The Egger’s population bias plot indicated no visual publication bias in the meta-analysis (Figure 5, P = 0.084 for rs1041981; P = 0.602 for rs2239704; P = 0.433 for rs2229094; P = 0.343 for rs746868).

thumbnail
Figure 5. Funnel plots of LTA polymorphisms and cancer risk data for publication bias.

https://doi.org/10.1371/journal.pone.0082519.g005

Discussion

In the systematic review and meta-analysis, we analyze 30 case-control studies among 58,649 participants to verify the association between the four SNPs and cancer risk. Our findings suggest that rs1041981, rs2239704 and rs2229094 are able to increase cancer risk by the significant association results under different genetic models. No evidence is found for the association between rs746868 and cancer risk.

In subgroup meta-analyses stratified by cancer type, our results show that rs2239704 and rs2229094 are likely to increase the risk of hematological malignancy and adenocarcinoma, respectively. Hematological malignancy is one cancer of uncontrolled proliferation of clonal B-cells, T-cell or NK-cell at different stages of maturations [60]. Adenocarcinoma can arise in many tissues of the body including stomach, breast, pancreas, colon and so on [61]. Both adenocarcinoma and hematological malignancy are multi-factorial diseases with complex interactions of genetic and environmental factors [62]. Accumulating evidences have reported that genetic variations in immune genes are susceptibility loci for hematological malignancy [47,63]. LTA rs2239704 polymorphism is the main predictor of LTA production in human B cells [28]. Adenocarcinoma is the most common histologic type of cancer. The LTA variants are shown to be associated with cancer risks under different genetic models. These genetic models consist of additive (per variant allele vs. common allele), dominant (variant allele carriers vs. homozygotes for the common allele) and recessive (homozygotes for the variant allele vs. all others) genetic models [64,65]. LTA rs1041981 is associated with a significantly lower presence of Japanese male lung cancer under the dominant model (CA+AA versus CC) [28]; LTA rs909253 is associated with high risk of Asian gastric cancer in the heterozygote comparison (GA versus AA) [15]; LTA rs2009658 is shown to be associated with significantly elevated risk of breast cancer among Caucasian women aged 45–64 years under the additive model (C versus G) [51]. Our results showed that LTA rs1041981 and rs2239704 polymorphisms were correlated with cancer in three genetic models, suggesting an additive effect for these two polymorphisms on the risk of cancer. In contrast, rs2229094 was associated with the risk of adenocarcinoma in recessive model, implying a lack of contribution for the heterozygote to the risk of adenocarcinoma. The results could partly be attributed to different LTA polymorphisms that play different roles in different cancers and different populations. Additionally, the different tumors in humans may be generated by special carcinogenic mechanisms which would lead to multiple connections with one same genetic locus [66].

Our subgroup meta-analyses by ethnicity find that rs1041981 shows a negative relationship with cancers in Asians under the recessive model. SNP rs2239704 shows positive association in North Americans but not Europeans. Additionally, rs2229094 is associated with cancer in Asians but not in North Americans or Europeans. This might be explained by the different genotype and allele frequencies of these SNPs in subjects with different clinical characteristics, geographic distributions, and ethnic descent. Therefore, we could not exclude that the negative association in Europeans or North Americans may be due to a lack of power. Thus, matching criteria and selection bias and the stages of the cancers should be considered in the future case-control studies. Large sample size and various populations study would get more believable result in the future.

In the present study, we have collected a series of parameters (including cancer type, population, source of control, genotyping method, and matching condition) to yield reliable result in the meta-analyses. We require that the genotype distribution in the controls met HWE (P > 0.05). We also perform subgroup meta-analyses by the collected parameters to reduce the potential stratification among the involved case-control studies. However, there are some limitations in our meta-analysis should be mentioned. Firstly, our meta-analyses combine the genetic studies from various cancers that may introduce dramatic stratifications in the meta-analyses, although we have controlled several parameters. Secondly, Our results can’t tell the true causal variant of cancer risk from the three significant SNPs (rs1041981, rs2239704, rs2229094) since they are in high LD. Moreover, it is possible that the true causal variant may be other variant in high LD with them. Future investigation for the mechanistic roles of them is needed. Thirdly, there are only a few studies in the African populations. Future study in African populations needed to be performed in a large size cohort to investigate whether the negative results of subgroup meta-analysis in the African populations is due to a lack of power or genetic heterogeneity.

In summary, the overall data of the present analyses suggest that three LTA variants (rs1041981, rs2239704 and rs2229094) can significantly increase the risk of cancers. Further well-designed studies in view of these variants are needed to explore their mechanistic roles in the pathogenesis of cancers.

Author Contributions

Conceived and designed the experiments: YH SD XG. Performed the experiments: XY SZ ZL JS NF LW. Analyzed the data: SN J. Wu BF J. Wang FG. Contributed reagents/materials/analysis tools: XL LX MY. Wrote the manuscript: YH SD.

References

  1. 1. Kimman M, Norman R, Jan S, Kingston D, Woodward M (2012) The burden of cancer in member countries of the Association of Southeast Asian Nations (ASEAN). Asian Pac J Cancer Prev 13: 411-420. doi:https://doi.org/10.7314/APJCP.2012.13.2.411. PubMed: 22524799.
  2. 2. Barzan D, Veldwijk MR, Herskind C, Li Y, Zhang B et al. (2013) Comparison of genetic variation of breast cancer susceptibility genes in Chinese and German populations. Eur J Hum Genet 21: 1286–1292. PubMed: 23486537.
  3. 3. Coussens LM, Werb Z (2002) Inflammation and cancer. Nature 420: 860-867. doi:https://doi.org/10.1038/nature01322. PubMed: 12490959.
  4. 4. Feller L, Altini M, Lemmer J (2013) Inflammation in the context of oral cancer. Oral Oncol 49: 887-892. doi:https://doi.org/10.1016/j.oraloncology.2013.07.003. PubMed: 23910564.
  5. 5. Akhurst RJ, Hata A (2012) Targeting the TGFbeta signalling pathway in disease. Nat Rev Drug Discov 11: 790-811. doi:https://doi.org/10.1038/nrd3810. PubMed: 23000686.
  6. 6. Wang K, Grivennikov SI, Karin M (2013) Implications of anti-cytokine therapy in colorectal cancer and autoimmune diseases. Ann Rheum Dis 72 (Suppl 2): ii100-ii103. PubMed: 23253923.
  7. 7. Morishige T, Yoshioka Y, Narimatsu S, Ikemizu S, Tsunoda S et al. (2013) Mutants of lymphotoxin-alpha with augmented cytotoxic activity via TNFR1 for use in cancer therapy. Cytokine 61: 578-584. doi:https://doi.org/10.1016/j.cyto.2012.11.005. PubMed: 23246116.
  8. 8. Allensworth JL, Sauer SJ, Lyerly HK, Morse MA, Devi GR (2013) Smac mimetic Birinapant induces apoptosis and enhances TRAIL potency in inflammatory breast cancer cells in an IAP-dependent and TNF-alpha-independent mechanism. Breast Cancer Res Treat 137: 359-371. doi:https://doi.org/10.1007/s10549-012-2352-6. PubMed: 23225169.
  9. 9. Aggarwal BB (2003) Signalling pathways of the TNF superfamily: a double-edged sword. Nat Rev Immunol 3: 745-756. doi:https://doi.org/10.1038/nri1184. PubMed: 12949498.
  10. 10. Cuturi MC, Murphy M, Costa-Giomi MP, Weinmann R, Perussia B et al. (1987) Independent regulation of tumor necrosis factor and lymphotoxin production by human peripheral blood lymphocytes. J Exp Med 165: 1581-1594. doi:https://doi.org/10.1084/jem.165.6.1581. PubMed: 3108447.
  11. 11. Cope AP (1998) Regulation of autoimmunity by proinflammatory cytokines. Curr Opin Immunol 10: 669-676. doi:https://doi.org/10.1016/S0952-7915(98)80087-3. PubMed: 9914219.
  12. 12. Vassalli P (1992) The pathophysiology of tumor necrosis factors. Annu Rev Immunol 10: 411-452. doi:https://doi.org/10.1146/annurev.iy.10.040192.002211. PubMed: 1590993.
  13. 13. Carroll MC, Katzman P, Alicot EM, Koller BH, Geraghty DE et al. (1987) Linkage map of the human major histocompatibility complex including the tumor necrosis factor genes. Proc Natl Acad Sci U S A 84: 8535-8539. doi:https://doi.org/10.1073/pnas.84.23.8535. PubMed: 2825194.
  14. 14. Barnett GC, West CM, Dunning AM, Elliott RM, Coles CE et al. (2009) Normal tissue reactions to radiotherapy: towards tailoring treatment dose by genotype. Nat Rev Cancer 9: 134-142. doi:https://doi.org/10.1038/nrc2587. PubMed: 19148183.
  15. 15. Lu R, Dou X, Gao X, Zhang J, Ni J et al. (2012) A functional polymorphism of lymphotoxin-alpha (LTA) gene rs909253 is associated with gastric cancer risk in an Asian population. Cancer Epidemiol 36: e380-e386. doi:https://doi.org/10.1016/j.canep.2012.05.014. PubMed: 22748850.
  16. 16. Zhang Y, Wang MY, He J, Wang JC, Yang YJ et al. (2012) Tumor necrosis factor-alpha induced protein 8 polymorphism and risk of non-Hodgkin's lymphoma in a Chinese population: a case-control study. PLOS ONE 7: e37846. doi:https://doi.org/10.1371/journal.pone.0037846. PubMed: 22666399.
  17. 17. Zhou P, Huang W, Chu X, Du LF, Li JP et al. (2012) The lymphotoxin-alpha 252AG polymorphism and breast cancer: a meta-analysis. Asian Pac J Cancer Prev 13: 1949-1952. doi:https://doi.org/10.7314/APJCP.2012.13.5.1949. PubMed: 22901152.
  18. 18. Sainz J, Rudolph A, Hoffmeister M, Frank B, Brenner H et al. (2012) Effect of type 2 diabetes predisposing genetic variants on colorectal cancer risk. J Clin Endocrinol Metab 97: E845-E851. doi:https://doi.org/10.1210/jc.2011-2565. PubMed: 22419714.
  19. 19. Wang SS, Purdue MP, Cerhan JR, Zheng T, Menashe I et al. (2009) Common gene variants in the tumor necrosis factor (TNF) and TNF receptor superfamilies and NF-kB transcription factors and non-Hodgkin lymphoma risk. PLOS ONE 4: e5360. doi:https://doi.org/10.1371/journal.pone.0005360. PubMed: 19390683.
  20. 20. Aissani B, Ogwaro KM, Shrestha S, Tang J, Breen EC et al. (2009) The major histocompatibility complex conserved extended haplotype 8.1 in AIDS-related non-Hodgkin lymphoma. J Acquir Immune Defic Syndr 52: 170-179. doi:https://doi.org/10.1097/QAI.0b013e3181b017d5. PubMed: 19654554.
  21. 21. Skibola CF, Bracci PM, Nieters A, Brooks-Wilson A, de Sanjosé S et al. (2010) Tumor necrosis factor (TNF) and lymphotoxin-alpha (LTA) polymorphisms and risk of non-Hodgkin lymphoma in the InterLymph Consortium. Am J Epidemiol 171: 267-276. doi:https://doi.org/10.1093/aje/kwp383. PubMed: 20047977.
  22. 22. García-González MA, Nicolás-Pérez D, Lanas A, Bujanda L, Carrera P et al. (2012) Prognostic role of host cyclooxygenase and cytokine genotypes in a Caucasian cohort of patients with gastric adenocarcinoma. PLOS ONE 7: e46179. doi:https://doi.org/10.1371/journal.pone.0046179. PubMed: 23029430.
  23. 23. Rausch SM, Gonzalez BD, Clark MM, Patten C, Felten S et al. (2012) SNPs in PTGS2 and LTA predict pain and quality of life in long term lung cancer survivors. Lung Cancer 77: 217-223. doi:https://doi.org/10.1016/j.lungcan.2012.02.017. PubMed: 22464751.
  24. 24. Nieves-Ramirez ME, Partida-Rodriguez O, Alegre-Crespo PE, Tapia-Lugo Mdel C, Perez-Rodriguez ME (2011) Characterization of Single-Nucleotide Polymorphisms in the Tumor Necrosis Factor alpha Promoter Region and in Lymphotoxin alpha in Squamous Intraepithelial Lesions, Precursors of Cervical Cancer. Transl Oncol 4: 336-344.
  25. 25. Messer G, Spengler U, Jung MC, Honold G, Blömer K et al. (1991) Polymorphic structure of the tumor necrosis factor (TNF) locus: an NcoI polymorphism in the first intron of the human TNF-beta gene correlates with a variant amino acid in position 26 and a reduced level of TNF-beta production. J Exp Med 173: 209-219. doi:https://doi.org/10.1084/jem.173.1.209. PubMed: 1670638.
  26. 26. Tan JH, Temple SE, Kee C, Waterer GW, Tan CR et al. (2011) Characterisation of TNF block haplotypes affecting the production of TNF and LTA. Tissue Antigens 77: 100-106. doi:https://doi.org/10.1111/j.1399-0039.2010.01582.x. PubMed: 21214521.
  27. 27. Ozaki K, Ohnishi Y, Iida A, Sekine A, Yamada R et al. (2002) Functional SNPs in the lymphotoxin-alpha gene that are associated with susceptibility to myocardial infarction. Nat Genet 32: 650-654. doi:https://doi.org/10.1038/ng1047. PubMed: 12426569.
  28. 28. Knight JC, Keating BJ, Kwiatkowski DP (2004) Allele-specific repression of lymphotoxin-alpha by activated B cell factor-1. Nat Genet 36: 394-399. doi:https://doi.org/10.1038/ng1331. PubMed: 15052269.
  29. 29. Boraska V, Rayner NW, Groves CJ, Frayling TM, Diakite M et al. (2010) Large-scale association analysis of TNF/LTA gene region polymorphisms in type 2 diabetes. BMC Med Genet 11: 69. doi:https://doi.org/10.1186/1471-2350-11-69. PubMed: 20459604.
  30. 30. Belfer I, Buzas B, Hipp H, Dean M, Evans C et al. (2004) Haplotype structure of inflammatory cytokines genes (IL1B, IL6 and TNF/LTA) in US Caucasians and African Americans. Genes Immun 5: 505-512. doi:https://doi.org/10.1038/sj.gene.6364118. PubMed: 15306845.
  31. 31. Takei K, Ikeda S, Arai T, Tanaka N, Muramatsu M et al. (2008) Lymphotoxin-alpha polymorphisms and presence of cancer in 1,536 consecutive autopsy cases. BMC Cancer 8: 235. doi:https://doi.org/10.1186/1471-2407-8-235. PubMed: 18700950.
  32. 32. Gaudet MM, Egan KM, Lissowska J, Newcomb PA, Brinton LA et al. (2007) Genetic variation in tumor necrosis factor and lymphotoxin-alpha (TNF-LTA) and breast cancer risk. Hum Genet 121: 483-490. doi:https://doi.org/10.1007/s00439-006-0315-x. PubMed: 17216494.
  33. 33. Wang SS, Cerhan JR, Hartge P, Davis S, Cozen W et al. (2006) Common genetic variants in proinflammatory and other immunoregulatory genes and risk for non-Hodgkin lymphoma. Cancer Res 66: 9771-9780. doi:https://doi.org/10.1158/0008-5472.CAN-06-0324. PubMed: 17018637.
  34. 34. Lee SG, Kim B, Yook JH, Oh ST, Lee I et al. (2004) TNF/LTA polymorphisms and risk for gastric cancer/duodenal ulcer in the Korean population. Cytokine 28: 75-82. doi:https://doi.org/10.1016/j.cyto.2004.06.009. PubMed: 15381184.
  35. 35. Niwa Y, Hirose K, Matsuo K, Tajima K, Ikoma Y et al. (2005) Lymphotoxin-alpha polymorphism and the risk of cervical cancer in Japanese subjects. Cancer Lett 218: 63-68. doi:https://doi.org/10.1016/j.canlet.2004.09.021. PubMed: 15639341.
  36. 36. Lan Q, Zheng T, Rothman N, Zhang Y, Wang SS et al. (2006) Cytokine polymorphisms in the Th1/Th2 pathway and susceptibility to non-Hodgkin lymphoma. Blood 107: 4101-4108. doi:https://doi.org/10.1182/blood-2005-10-4160. PubMed: 16449530.
  37. 37. Gunter MJ, Canzian F, Landi S, Chanock SJ, Sinha R et al. (2006) Inflammation-related gene polymorphisms and colorectal adenoma. Cancer Epidemiol Biomarkers Prev 15: 1126-1131. doi:https://doi.org/10.1158/1055-9965.EPI-06-0042. PubMed: 16775170.
  38. 38. Liu X, Plummer SJ, Nock NL, Casey G, Witte JS (2006) Nonsteroidal antiinflammatory drugs and decreased risk of advanced prostate cancer: modification by lymphotoxin alpha. Am J Epidemiol 164: 984-989. doi:https://doi.org/10.1093/aje/kwj294. PubMed: 16931544.
  39. 39. Niwa Y, Ito H, Matsuo K, Hirose K, Ito N et al. (2007) Lymphotoxin-alpha polymorphisms and the risk of endometrial cancer in Japanese subjects. Gynecol Oncol 104: 586-590. doi:https://doi.org/10.1016/j.ygyno.2006.09.007. PubMed: 17045328.
  40. 40. Purdue MP, Lan Q, Kricker A, Grulich AE, Vajdic CM et al. (2007) Polymorphisms in immune function genes and risk of non-Hodgkin lymphoma: findings from the New South Wales non-Hodgkin Lymphoma Study. Carcinogenesis 28: 704-712. PubMed: 17056605.
  41. 41. Purdue MP, Sakoda LC, Graubard BI, Welch R, Chanock SJ et al. (2007) A case-control investigation of immune function gene polymorphisms and risk of testicular germ cell tumors. Cancer Epidemiol Biomarkers Prev 16: 77-83. doi:https://doi.org/10.1158/1055-9965.EPI-06-0573. PubMed: 17220333.
  42. 42. García-González MA, Lanas A, Quintero E, Nicolás D, Parra-Blanco A et al. (2007) Gastric cancer susceptibility is not linked to pro-and anti-inflammatory cytokine gene polymorphisms in whites: a Nationwide Multicenter Study in Spain. Am J Gastroenterol 102: 1878-1892. doi:https://doi.org/10.1111/j.1572-0241.2007.01423.x. PubMed: 17640324.
  43. 43. Ennas MG, Moore PS, Zucca M, Angelucci E, Cabras MG et al. (2008) Interleukin-1B (IL1B) and interleukin-6 (IL6) gene polymorphisms are associated with risk of chronic lymphocytic leukaemia. Hematol Oncol 26: 98-103. doi:https://doi.org/10.1002/hon.843. PubMed: 18271063.
  44. 44. Jacobs EJ, Hsing AW, Bain EB, Stevens VL, Wang Y et al. (2008) Polymorphisms in angiogenesis-related genes and prostate cancer. Cancer Epidemiol Biomarkers Prev 17: 972-977. doi:https://doi.org/10.1158/1055-9965.EPI-07-2787. PubMed: 18398039.
  45. 45. Crusius JB, Canzian F, Capellá G, Peña AS, Pera G et al. (2008) Cytokine gene polymorphisms and the risk of adenocarcinoma of the stomach in the European prospective investigation into cancer and nutrition (EPIC-EURGAST). Ann Oncol 19: 1894-1902. doi:https://doi.org/10.1093/annonc/mdn400. PubMed: 18628242.
  46. 46. Mahajan R, El-Omar EM, Lissowska J, Grillo P, Rabkin CS et al. (2008) Genetic variants in T helper cell type 1, 2 and 3 pathways and gastric cancer risk in a Polish population. Jpn J Clin Oncol 38: 626-633. doi:https://doi.org/10.1093/jjco/hyn075. PubMed: 18687755.
  47. 47. Cerhan JR, Liu-Mares W, Fredericksen ZS, Novak AJ, Cunningham JM et al. (2008) Genetic variation in tumor necrosis factor and the nuclear factor-kappaB canonical pathway and risk of non-Hodgkin's lymphoma. Cancer Epidemiol Biomarkers Prev 17: 3161-3169. doi:https://doi.org/10.1158/1055-9965.EPI-08-0536. PubMed: 18990758.
  48. 48. Castro FA, Haimila K, Sareneva I, Schmitt M, Lorenzo J et al. (2009) Association of HLA-DRB1, interleukin-6 and cyclin D1 polymorphisms with cervical cancer in the Swedish population--a candidate gene approach. Int J Cancer 125: 1851-1858. doi:https://doi.org/10.1002/ijc.24529. PubMed: 19585495.
  49. 49. García-González MA, Aísa MA, Strunk M, Benito R, Piazuelo E et al. (2009) Relevance of IL-1 and TNF gene polymorphisms on interleukin-1beta and tumor necrosis factor-alpha gastric mucosal production. Hum Immunol 70: 935-945. doi:https://doi.org/10.1016/j.humimm.2009.07.024. PubMed: 19664671.
  50. 50. Abbas S, Beckmann L, Chang-Claude J, Hein R, Kropp S et al. (2010) Polymorphisms in the BRCA1 and ABCB1 genes modulate menopausal hormone therapy associated breast cancer risk in postmenopausal women. Breast Cancer Res Treat 120: 727-736. doi:https://doi.org/10.1007/s10549-009-0489-8. PubMed: 19672706.
  51. 51. Madeleine MM, Johnson LG, Malkki M, Resler AJ, Petersdorf EW et al. (2011) Genetic variation in proinflammatory cytokines IL6, IL6R, TNF-region, and TNFRSF1A and risk of breast cancer. Breast Cancer Res Treat 129: 887-899. doi:https://doi.org/10.1007/s10549-011-1520-4. PubMed: 21523452.
  52. 52. Abbas S, Beckmann L, Chang-Claude J, Hein R, Kropp S et al. (2010) Polymorphisms in the BRCA1 and ABCB1 genes modulate menopausal hormone therapy associated breast cancer risk in postmenopausal women. Breast Cancer Res Treat 120: 727-736. doi:https://doi.org/10.1007/s10549-009-0489-8. PubMed: 19672706.
  53. 53. Excoffier L, Lischer HE (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour 10: 564-567. doi:https://doi.org/10.1111/j.1755-0998.2010.02847.x. PubMed: 21565059.
  54. 54. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD et al. (2000) Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-Analysis of Observational Studies in Epidemiology (MOOSE) Group. JAMA 283: 2008-2012.
  55. 55. Higgins JP, Thompson SG, Deeks JJ, Altman DG (2003) Measuring inconsistency in meta-analyses. BMJ 327: 557-560. doi:https://doi.org/10.1136/bmj.327.7414.557. PubMed: 12958120.
  56. 56. Lau J, Ioannidis JP, Schmid CH (1997) Quantitative synthesis in systematic reviews. Ann Intern Med 127: 820-826. doi:https://doi.org/10.7326/0003-4819-127-9-199711010-00008. PubMed: 9382404.
  57. 57. 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.
  58. 58. Higgins JP, Thompson SG (2002) Quantifying heterogeneity in a meta-analysis. Stat Med 21: 1539-1558. doi:https://doi.org/10.1002/sim.1186. PubMed: 12111919.
  59. 59. Seagroatt V, Stratton I (1998) Bias in meta-analysis detected by a simple, graphical test. Test had 10% false positive rate. BMJ 316: 470; author reply: 471.
  60. 60. Alexander DD, Mink PJ, Adami HO, Chang ET, Cole P et al. (2007) The non-Hodgkin lymphomas: a review of the epidemiologic literature. Int J Cancer 120(Suppl 12): 1-39. doi:https://doi.org/10.1002/ijc.22719. PubMed: 17405121.
  61. 61. Clouston D, Bolton D (2012) In situ and intraductal epithelial proliferations of prostate: definitions and treatment implications. Part 2: intraductal carcinoma and ductal adenocarcinoma of prostate. BJU Int 110(Suppl 4): 22-24. doi:https://doi.org/10.1111/j.1464-410X.2012.11612.x. PubMed: 23194119.
  62. 62. Shih CM, Lee YL, Chiou HL, Chen W, Chang GC et al. (2006) Association of TNF-alpha polymorphism with susceptibility to and severity of non-small cell lung cancer. Lung Cancer 52: 15-20. doi:https://doi.org/10.1016/j.lungcan.2005.11.011. PubMed: 16476505.
  63. 63. Cerhan JR, Ansell SM, Fredericksen ZS, Kay NE, Liebow M et al. (2007) Genetic variation in 1253 immune and inflammation genes and risk of non-Hodgkin lymphoma. Blood 110: 4455-4463. doi:https://doi.org/10.1182/blood-2007-05-088682. PubMed: 17827388.
  64. 64. Liu Y, Sheng H, Lu L, Wu Z, Chen Q et al. (2011) Haplotype-based association of four lymphotoxin-alpha gene polymorphisms with the risk of coronary artery disease in Han Chinese. Tohoku J Exp Med 224: 119-125. doi:https://doi.org/10.1620/tjem.224.119. PubMed: 21628868.
  65. 65. Clarke R, Xu P, Bennett D, Lewington S, Zondervan K et al. (2006) Lymphotoxin-alpha gene and risk of myocardial infarction in 6,928 cases and 2,712 controls in the ISIS case-control study. PLoS Genet 2: e107. doi:https://doi.org/10.1371/journal.pgen.0020107. PubMed: 16839190.
  66. 66. Weinstein IB (1988) The origins of human cancer: molecular mechanisms of carcinogenesis and their implications for cancer prevention and treatment--twenty-seventh G.H.A. Clowes memorial award lecture. Cancer Res 48: 4135-4143. PubMed: 3292040.