MDM4rs4245739基因多态性与乳腺癌易感性的meta分析

doi:10.3969/j.issn.1004-583X.2022.11.003

摘要/Abstract

摘要：

目的探MDM4rs4245739基因多态性与乳腺癌易感性之间的相关性。方法在PubMed、EMBASE、Cochrane Library、中国知识基础设施数据库和万方电子数据库中检索MDM4rs4245739基因多态性与乳腺癌易感性的相关文献。用比值比和95%置信区间来评估相关性的强度。采用Begg's漏斗图和Egger's线性回归检验来评价发表偏倚。结果本研究共纳入6项研究,包括9 814名乳腺癌患者和45 202名健康对照者。MDM4rs4245739在等位基因模型(C vs A: OR=0.84, 95%CI: 0.67-1.05, P=0.118)、显性基因模型(AC+CC vs AA: OR=0.86, 95% CI: 0.67-1.11, P=0.245)、隐性基因模型 (AC+AA vs CC: OR =0.90, 95%CI: 0.61-1.32, P=0.585)、杂合子模型 (AC vs AA: OR=0.88, 95%CI: 0.69-1.12, P=0.305)、纯合子模型(CC vs AA: OR =0.90, 95%CI: 0.59-1.39, P=0.649)中均提示其与乳腺癌易感性无相关性。同时,GEPIA数据库亦证实MDM4的表达水平与乳腺癌的肿瘤分期及预后无关。结论 MDM4rs4245739基因多态性和MDM4的表达水平与乳腺癌患者的易感性和预后均无关。

关键词: 乳腺癌, 鼠双微体4, 易感性, 基因多态性, meta分析

Abstract:

Objective To explore associations between MDM4rs4245739 gene polymorphism and breast cancer susceptibility. Methods The papers related to polymorphisms of MDM4rs4245739 and breast cancer susceptibility were searched in PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure and Wanfang electronic database. Odds ratios (ORs) and 95% confidence intervals (CIs) were adopted to assess the strength of associations. Publication bias was evaluated by Begg's funnel plot and Egger's linear regression test. Results A total of 6 studies involving 9 814 breast cancer patients and 45 202 healthy individuals were included in the present study. MDM4rs4245739 in the allelic (C vs A: OR=0.84, 95%CI: 0.67-1.05, P =0.118), dominant (AC+CC vs AA: $O R$ =0.86, 95% CI: 0.67-1.11, P =0.245), recessive (AC+AA vs CC: OR=0.90, 95%CI: 0.61-1.32, P =0.585), heterozygous (AC vs AA: OR =0.88, 95%CI: 0.69-1.12, P=0.305), homozygous (CC vs AA: OR =0.90, 95% CI: 0.59-1.39, $P$ =0.649) genetic models show no association with the susceptibility to breast cancer. Moreover, GEPIA data confirmed that the expression level of MDM4 was not associated with the tumor staging and prognosis of breast cancer. Conclusion Neither MDM4rs4245739 gene polymorphism nor MDM4 expression level is associated with the susceptibility and prognosis in breast cancer patients.

Key words: breast cancer, murine double minute 4, susceptibility, gene polymorphism, meta analysis

中图分类号:

R604

姜焱, 李佳阳, 伍红瑜, 陈保林, 程晓明, 吕俊远. MDM4rs4245739基因多态性与乳腺癌易感性的meta分析[J]. 临床荟萃, 2022, 37(11): 977-984.

Jiang Yan, Li Jiayang, Wu Hongyu, Chen Baolin, Cheng Xiaoming, Lyu Junyuan. MDM4rs4245739 gene polymorphism and breast cancer susceptibility:A meta-analysis[J]. Clinical Focus, 2022, 37(11): 977-984.

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链接本文: https://huicui.hebmu.edu.cn/CN/10.3969/j.issn.1004-583X.2022.11.003

https://huicui.hebmu.edu.cn/CN/Y2022/V37/I11/977

图/表 12

图1 文献筛选流程图

表1 纳入文献的基本特征

第一作者	年份	地区	种族	病例/对照数	病例组			对照组			SOC	HWE	NOS
第一作者	年份	地区	种族	病例/对照数	AA	AC	CC	AA	AC	CC	SOC	HWE	NOS
Liu et al^[7]	2013	中国	非高加索人	800/800	733	67	0	686	111	3	PB	0.505	6
Liu et al^[7]	2013	中国	非高加索人	300/600	278	22	0	501	96	3	PB	0.483	6
Hashemi et al^[8]	2018	伊朗	非高加索人	265/221	175	83	7	142	70	9	HB	0.919	5
Montserrat et al^[10]	2013	混合	高加索人	6 512/41 451	3 318	2 637	557	22 825	15 798	2 828	Mixed	0.183	5
Gansmo et al^[25]	2015	挪威	高加索人	1 717/1 870	966	643	108	1 021	703	146	PB	0.106	6
Pedram et al^[26]	2016	伊朗	非高加索人	220/260	123	87	10	165	81	14	HB	0.335	6

图2 等位基因模型(C vs A)的森林图

图3 显性基因模型(AC+CC vs AA)的森林图

图4 隐性基因模型(AC+AA vs CC)的森林图

图5 杂合子基因模型(AC vs AA)的森林图

图6 纯合子基因模型(CC vs AA)的森林图

表2 亚组分析结果

分组	数量	C vs A		AC+CC vs AA		AC+AA vs CC		AC vs AA		CC vs AA
分组	数量	$O R$ (95% $C I$ )	$P$	$O R$ (95% $C I$ )	$P$	$O R$ (95% $C I$ )	$P$	$O R$ (95% $C I$ )	$P$	$O R$ (95% $C I$ )	$P$
种族
非高加索人	4	0.70(0.46-1.06)^*	0.093	0.74(0.44-1.22)^*	0.236	0.67(0.36-1.24)^#	0.200	0.76(0.45-1.28)^*	0.302	0.71(0.38-1.32)^#	0.279
高加索人	2	1.04(0.83-1.30)^*	0.753	1.06(0.84-1.33)^*	0.639	1.02(0.64-1.63)^*	0.923	1.06(0.90-1.26)^*	0.478	1.04(0.61-1.79)^*	0.876
地区
亚洲	4	0.70(0.46-1.06)^*	0.093	0.74(0.44-1.22)^*	0.236	0.67(0.36-1.24)^#	0.200	0.76(0.45-1.28)^*	0.302	0.71(0.38-1.32)^#	0.279
欧洲	1	0.92(0.83-1.02)	0.116	0.93(0.82-1.06)	0.292	0.79(0.61-1.03)	0.080	0.96(0.84-1.11)	0.590	0.78(0.60-1.02)	0.068
混合	1	1.16(1.11-1.21)	0.000	1.18(1.12-1.24)	0.000	1.28(1.16-1.41)	0.000	1.15(1.09-1.21)	0.000	1.36(1.23-1.49)	0.000
样本量
>1 000	2	1.04(0.83-1.30)^*	0.753	1.06(0.84-1.33)^*	0.639	1.02(0.64-1.63)^*	0.923	1.06(0.90-1.26)^*	0.478	1.04(0.61-1.79)^*	0.876
<1 000	4	0.70(0.46-1.06)^*	0.093	0.74(0.44-1.22)^*	0.236	0.67(0.36-1.24)^#	0.200	0.76(0.45-1.28)^*	0.302	0.71(0.38-1.32)^#	0.279
基因分型检测方法
PCR-RFLP	4	0.70(0.46-1.06)^*	0.093	0.74(0.44-1.22)^*	0.236	0.67(0.36-1.24)^#	0.200	0.76(0.45-1.28)^*	0.302	0.71(0.38-1.32)^#	0.279
其他	2	1.04(0.83-1.30)^*	0.753	1.06(0.84-1.33)^*	0.639	1.02(0.64-1.24)^*	0.923	1.06(0.90-1.26)^*	0.478	1.04(0.61-1.79)^*	0.876
健康对照者来源
PB	3	0.62(0.38-1.01)^*	0.054	0.61(0.37-1.02)^*	0.060	0.78(0.60-1.01)^#	0.054	0.63(0.38-1.05)^*	0.079	0.77(0.59-0.99)^#	0.044
HB	2	1.00(0.80-1.25)^#	0.976	1.13(0.77-1.66)^*	0.542	0.75(0.40-1.42)^#	0.378	1.18(0.79-1.75)^*	0.415	0.81(0.42-1.54)^#	0.518
混合	1	1.16(1.11-1.21)	0.000	1.18(1.12-1.24)	0.000	1.28(1.16-1.41)	0.000	1.15(1.09-1.21)	0.000	1.35(1.23-1.49)	0.000
总共	6	0.84(0.67-1.05)^*	0.118	0.86(0.67-1.11)^*	0.245	0.90(0.61-1.32)^*	0.585	0.88(0.69-1.12)^*	0.305	0.90(0.59-1.40)^*	0.649

表2 亚组分析结果

分组	数量	C vs A		AC+CC vs AA		AC+AA vs CC		AC vs AA		CC vs AA
分组	数量	$O R$ (95% $C I$ )	$P$	$O R$ (95% $C I$ )	$P$	$O R$ (95% $C I$ )	$P$	$O R$ (95% $C I$ )	$P$	$O R$ (95% $C I$ )	$P$
种族
非高加索人	4	0.70(0.46-1.06)^*	0.093	0.74(0.44-1.22)^*	0.236	0.67(0.36-1.24)^#	0.200	0.76(0.45-1.28)^*	0.302	0.71(0.38-1.32)^#	0.279
高加索人	2	1.04(0.83-1.30)^*	0.753	1.06(0.84-1.33)^*	0.639	1.02(0.64-1.63)^*	0.923	1.06(0.90-1.26)^*	0.478	1.04(0.61-1.79)^*	0.876
地区
亚洲	4	0.70(0.46-1.06)^*	0.093	0.74(0.44-1.22)^*	0.236	0.67(0.36-1.24)^#	0.200	0.76(0.45-1.28)^*	0.302	0.71(0.38-1.32)^#	0.279
欧洲	1	0.92(0.83-1.02)	0.116	0.93(0.82-1.06)	0.292	0.79(0.61-1.03)	0.080	0.96(0.84-1.11)	0.590	0.78(0.60-1.02)	0.068
混合	1	1.16(1.11-1.21)	0.000	1.18(1.12-1.24)	0.000	1.28(1.16-1.41)	0.000	1.15(1.09-1.21)	0.000	1.36(1.23-1.49)	0.000
样本量
>1 000	2	1.04(0.83-1.30)^*	0.753	1.06(0.84-1.33)^*	0.639	1.02(0.64-1.63)^*	0.923	1.06(0.90-1.26)^*	0.478	1.04(0.61-1.79)^*	0.876
<1 000	4	0.70(0.46-1.06)^*	0.093	0.74(0.44-1.22)^*	0.236	0.67(0.36-1.24)^#	0.200	0.76(0.45-1.28)^*	0.302	0.71(0.38-1.32)^#	0.279
基因分型检测方法
PCR-RFLP	4	0.70(0.46-1.06)^*	0.093	0.74(0.44-1.22)^*	0.236	0.67(0.36-1.24)^#	0.200	0.76(0.45-1.28)^*	0.302	0.71(0.38-1.32)^#	0.279
其他	2	1.04(0.83-1.30)^*	0.753	1.06(0.84-1.33)^*	0.639	1.02(0.64-1.24)^*	0.923	1.06(0.90-1.26)^*	0.478	1.04(0.61-1.79)^*	0.876
健康对照者来源
PB	3	0.62(0.38-1.01)^*	0.054	0.61(0.37-1.02)^*	0.060	0.78(0.60-1.01)^#	0.054	0.63(0.38-1.05)^*	0.079	0.77(0.59-0.99)^#	0.044
HB	2	1.00(0.80-1.25)^#	0.976	1.13(0.77-1.66)^*	0.542	0.75(0.40-1.42)^#	0.378	1.18(0.79-1.75)^*	0.415	0.81(0.42-1.54)^#	0.518
混合	1	1.16(1.11-1.21)	0.000	1.18(1.12-1.24)	0.000	1.28(1.16-1.41)	0.000	1.15(1.09-1.21)	0.000	1.35(1.23-1.49)	0.000
总共	6	0.84(0.67-1.05)^*	0.118	0.86(0.67-1.11)^*	0.245	0.90(0.61-1.32)^*	0.585	0.88(0.69-1.12)^*	0.305	0.90(0.59-1.40)^*	0.649

表3 Meta回归结果

协变量	N	C vs A	AC+CC vs AA	AC+AA vs CC	AC vs AA	CC vs AA
种族	2	0.201	0.341	0.244	0.388	0.301
地区	3	0.000	0.000	0.000	0.000	0.000
样本量	2	0.201	0.341	0.244	0.388	0.301
基因分型检测方法	2	0.201	0.341	0.244	0.388	0.301
健康对照者来源	3	0.000	0.000	0.000	0.000	0.000

图7 5种基因模型的敏感性分析 a. C vs A; b. AC+CC vs AA; c. AC+AA vs CC; d. AC vs AA; e. CC vs AA

图8 5种基因模型发表偏倚检验的Begg's漏斗图 a. C vs A; b. AC+CC vs AA; c. AC+AA vs CC; d. AC vs AA; e CC vs AA

图9 GEPIA数据库分析图 a. M D M 4在不同类型肿瘤中的表达情况; b. M D M 4在乳腺癌不同临床分期中的表达情况; c. 乳腺癌患者 M D M 4表达与无病生存率的关系; d 乳腺癌患者 M D M 4表达与总生存率的关系

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