Correlation between the TNF-α-308 gene polymorphism and gastric cancer susceptibility: A meta-analysis

doi:10.3969/j.issn.1004-583X.2023.09.002

Abstract

Abstract:

Objective To investigate the correlation between tumor necrosis factor-α (TNF-α) promoter 308 locus (TNF-α-308) gene polymorphism and gastric cancer susceptibility. Methods Case-control studies on TNF-α-308 gene polymorphism and the susceptibility to gastric cancer published before June 2022 were searched in Pubmed, Embase, Web of Science, Cochrane library, Wanfang and China National Knowledge Infrastructure (CNKI). Literature screening, data extraction and evaluation of risk of bias were performed independently by 2 investigators. Meta-analysis was performed via Stata 16.0 software. Results A total of 41 case-control studies were included, involving 7528 gastric cancer patients and 10924 controls. Meta-analysis showed that in allelic, heterozygous and dominant models, TNF-α-308 gene polymorphisms were significantly correlated with with an increased risk of gastric cancer (A vs G: $O R$ =1.21, 95% $C I$ : 1.01-1.44, $P$ =0.039; AG vs GG: $O R$ =1.26, 95% $C I$ : 1.07-1.49, $P$ =0.392; AA+AG vs GG: $O R$ =1.22, 95% $C I$ : 1.00-1.47, $P$ =0.046). Five studies of gastric cancer caused by Helicobacter pylori infection showed that TNF-α-308 gene polymorphisms were not correlated with susceptibility to gastric cancer. Subgroup analyses showed that all genetic models in Asian areas (A vs G: $O R$ =1.29, 95% $C I$ : 1.04,1.61, $P$ =0.022; AG vs GG: $O R$ =1.35, 95% $C I$ : 1.06,1.71, $P$ =0.014; AA+AG vs GG: $O R$ =1.36, 95% $C I$ : 1.07,1.73, $P$ =0.013) and in African areas showed a significant correlation between TNF-α-308 gene polymorphisms and risk of gastric cancer ( $P$ <0.05), which was not correlated in American and European areas. All genetic models in Taqman typing study showed a significant correlation between TNF-α-308 locus gene polymorphisms and risk of gastric cancer ( $P$ <0.05). Conclusion A significant correlation between TNF-α-308 gene polymorphisms and risk of gastric cancer is found in Asian areas. It is not correlated with the susceptibility to gastric cancer caused by Helicobacter pylori infection.

Key words: stomach neoplasms, TNF-α-308, Helicobacter pylori infection, single nucleotide polymorphism, meta-analysis

CLC Number:

R735.2

Lyu Chang, Zhou Liming. Correlation between the TNF-α-308 gene polymorphism and gastric cancer susceptibility: A meta-analysis[J]. Clinical Focus, 2023, 38(9): 779-787.

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URL: https://huicui.hebmu.edu.cn/EN/10.3969/j.issn.1004-583X.2023.09.002

https://huicui.hebmu.edu.cn/EN/Y2023/V38/I9/779

Figures/Tables 8

References 49

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纳入研究	国家	地区	检测方式	病例组			对照组			HWE 检验	NOS 评分
纳入研究	国家	地区	检测方式	GG	GA	AA	GG	GA	AA	HWE 检验	NOS 评分
Jang 2001^[7]	朝鲜	亚洲	RFLP	46	4	2	85	7	0	0.704	8
Wu 2002^[8]	中国	亚洲	直接分型	114	27	9	180	27	13	<0.01	6
El-Omar 2003^[9]	美国	美洲	Taqman	201	87	26	152	52	6	0.548	8
Machado 2003^[10]	葡萄牙	欧洲	PCR/SSCP	179	105	3	231	69	4	0.650	8
Wu 2003^[11]	中国	亚洲	直接分型	176	31	13	185	29	16	<0.01	8
Glas 2004^[12]	德国	欧洲	RFLP	66	19	3	105	36	4	0.669	8
Lee 2004^[13]	朝鲜	亚洲	直接分型	297	43	1	218	42	1	0.493	8
Wu 2004^[14]	中国	亚洲	RFLP	163	29	12	171	26	13	<0.01	7
Garza-González 2005^[15]	墨西哥	美洲	直接分型	0	8	55	1	35	179	0.608	6
Lee 2005^[16]	朝鲜	亚洲	RFLP	112	10	0	103	17	0	0.404	8
Li 2005^[17]	中国	亚洲	RFLP	55	4	0	228	34	2	0.560	8
Lu 2005^[18]	中国	亚洲	DNPLC	214	36	0	274	24	2	0.081	8
Perri 2005^[19]	意大利	欧洲	RFLP	152	30	2	290	65	7	0.146	8
Zambon 2005^[20]	意大利	欧洲	Taqman	95	31	3	496	138	10	0.910	7
Kamanrar 2006^[21]	芬兰	欧洲	Taqman	86	23	3	154	52	2	0.292	6
Kim 2006^[22]	朝鲜	亚洲	RFLP	199	34	4	400	59	2	0.911	8
Morgan 2006^[23]	洪都拉斯	美洲	Taqman	151	17	0	149	12	0	0.623	8
邢培祥2006^[24]	中国	亚洲	芯片检测	36	27	2	50	20	1	0.523	8
Hou 2007^[25]	波兰	欧洲	Taqman	186	98	21	304	109	15	0.187	8
Sugimoto 2007^[26]	日本	亚洲	RFLP	101	4	0	169	3	0	0.908	7
曾庆东2007^[27]	中国	亚洲	芯片检测	72	54	4	100	40	2	0.367	8
Crusius 2008^[28]	欧洲	欧洲	Real-time PCR	170	64	2	820	274	31	0.165	8
Barbosa 2009^[29]	巴西	美洲	RFLP	24	5	1	86	13	1	0.528	7
贾皑2009^[30]	中国	亚洲	PCR	96	2	8	91	3	14	<0.01	7
Burada 2012^[31]	罗马	欧洲	Taqman	78	26	1	196	44	2	0.784	8
王美丽2012^[32]	中国	亚洲	RFLP	16	75	21	14	64	21	0.003	7
尹东2011^[33]	中国	亚洲	PCR	265	43	3	398	79	8	0.085	7
Bhayal 2013^[34]	印度	亚洲	ARMSPCR	32	76	6	76	128	25	0.007	8
Hong 2012^[35]	中国	亚洲	Taqman	746	179	11	895	156	9	0.448	8
Gonzalez 2014^[36]	智利	美洲	Taqman	128	18	1	147	23	2	0.322	8
张军喜2014^[37]	中国	亚洲	PCR	56	9	0	113	16	1	0.608	8
Oliveira 2015^[38]	巴西	美洲	RFLP	138	66	3	167	69	4	0.297	8
Stubljar 2015^[39]	斯洛文尼亚	欧洲	RFLP	27	5	0	83	22	3	0.312	7
Zabaglia 2015^[40]	巴西	美洲	RFLP	17	4	3	33	4	3	0.001	6
张德忠2015^[41]	中国	亚洲	RFLP	373	112	15	396	95	9	0.243	8
Du 2017^[42]	中国	亚洲	RFLP	204	184	12	326	60	14	<0.01	7
Xu 2016^[43]	中国	亚洲	RFLP	142	66	88	237	50	32	<0.01	8
Fukayama 2019^[44]	日本	亚洲	RFLP	120	2	7	101	2	0	0.921	8
Bounder 2020^[45]	摩洛哥	非洲	直接测序	26	6	8	56	4	3	<0.01	7
Dantas 2020^[46]	巴西	美洲	DSASP	74	0	28	8	41	53	0.986	8
Nezamzadeh 2021^[47]	伊朗	亚洲	RFLP	41	7	3	73	5	1	0.020	7

纳入研究	国家	地区	检测方式	病例组			对照组			HWE 检验	NOS 评分
纳入研究	国家	地区	检测方式	GG	GA	AA	GG	GA	AA	HWE 检验	NOS 评分
Jang 2001^[7]	朝鲜	亚洲	RFLP	46	4	2	85	7	0	0.704	8
Wu 2002^[8]	中国	亚洲	直接分型	114	27	9	180	27	13	<0.01	6
El-Omar 2003^[9]	美国	美洲	Taqman	201	87	26	152	52	6	0.548	8
Machado 2003^[10]	葡萄牙	欧洲	PCR/SSCP	179	105	3	231	69	4	0.650	8
Wu 2003^[11]	中国	亚洲	直接分型	176	31	13	185	29	16	<0.01	8
Glas 2004^[12]	德国	欧洲	RFLP	66	19	3	105	36	4	0.669	8
Lee 2004^[13]	朝鲜	亚洲	直接分型	297	43	1	218	42	1	0.493	8
Wu 2004^[14]	中国	亚洲	RFLP	163	29	12	171	26	13	<0.01	7
Garza-González 2005^[15]	墨西哥	美洲	直接分型	0	8	55	1	35	179	0.608	6
Lee 2005^[16]	朝鲜	亚洲	RFLP	112	10	0	103	17	0	0.404	8
Li 2005^[17]	中国	亚洲	RFLP	55	4	0	228	34	2	0.560	8
Lu 2005^[18]	中国	亚洲	DNPLC	214	36	0	274	24	2	0.081	8
Perri 2005^[19]	意大利	欧洲	RFLP	152	30	2	290	65	7	0.146	8
Zambon 2005^[20]	意大利	欧洲	Taqman	95	31	3	496	138	10	0.910	7
Kamanrar 2006^[21]	芬兰	欧洲	Taqman	86	23	3	154	52	2	0.292	6
Kim 2006^[22]	朝鲜	亚洲	RFLP	199	34	4	400	59	2	0.911	8
Morgan 2006^[23]	洪都拉斯	美洲	Taqman	151	17	0	149	12	0	0.623	8
邢培祥2006^[24]	中国	亚洲	芯片检测	36	27	2	50	20	1	0.523	8
Hou 2007^[25]	波兰	欧洲	Taqman	186	98	21	304	109	15	0.187	8
Sugimoto 2007^[26]	日本	亚洲	RFLP	101	4	0	169	3	0	0.908	7
曾庆东2007^[27]	中国	亚洲	芯片检测	72	54	4	100	40	2	0.367	8
Crusius 2008^[28]	欧洲	欧洲	Real-time PCR	170	64	2	820	274	31	0.165	8
Barbosa 2009^[29]	巴西	美洲	RFLP	24	5	1	86	13	1	0.528	7
贾皑2009^[30]	中国	亚洲	PCR	96	2	8	91	3	14	<0.01	7
Burada 2012^[31]	罗马	欧洲	Taqman	78	26	1	196	44	2	0.784	8
王美丽2012^[32]	中国	亚洲	RFLP	16	75	21	14	64	21	0.003	7
尹东2011^[33]	中国	亚洲	PCR	265	43	3	398	79	8	0.085	7
Bhayal 2013^[34]	印度	亚洲	ARMSPCR	32	76	6	76	128	25	0.007	8
Hong 2012^[35]	中国	亚洲	Taqman	746	179	11	895	156	9	0.448	8
Gonzalez 2014^[36]	智利	美洲	Taqman	128	18	1	147	23	2	0.322	8
张军喜2014^[37]	中国	亚洲	PCR	56	9	0	113	16	1	0.608	8
Oliveira 2015^[38]	巴西	美洲	RFLP	138	66	3	167	69	4	0.297	8
Stubljar 2015^[39]	斯洛文尼亚	欧洲	RFLP	27	5	0	83	22	3	0.312	7
Zabaglia 2015^[40]	巴西	美洲	RFLP	17	4	3	33	4	3	0.001	6
张德忠2015^[41]	中国	亚洲	RFLP	373	112	15	396	95	9	0.243	8
Du 2017^[42]	中国	亚洲	RFLP	204	184	12	326	60	14	<0.01	7
Xu 2016^[43]	中国	亚洲	RFLP	142	66	88	237	50	32	<0.01	8
Fukayama 2019^[44]	日本	亚洲	RFLP	120	2	7	101	2	0	0.921	8
Bounder 2020^[45]	摩洛哥	非洲	直接测序	26	6	8	56	4	3	<0.01	7
Dantas 2020^[46]	巴西	美洲	DSASP	74	0	28	8	41	53	0.986	8
Nezamzadeh 2021^[47]	伊朗	亚洲	RFLP	41	7	3	73	5	1	0.020	7