Association analysis between genetic variants in STAT4and pathological characteristics of primary liver cancer
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摘要:
目的 探讨STAT4遗传变异及其与运动的交互作用对原发性肝癌患者病理特征的影响。 方法 在601例新发肝癌患者中,采用多因素Logistic回归分析模型分析rs7574865、rs897200、rs1031507与肿瘤淋巴结转移(tumor node metastasis,TNM)分期、门脉癌栓的关联。应用相乘交互项和"Delta"法分别评价相乘和相加交互作用。 结果 在显性模型下,rs897200变异与患者首诊时晚期的风险存在临界统计学关联(调整OR=0.64,95%CI:0.41~1.01,P=0.057)。携带rs1031507 CC+AC基因型的患者晚期风险低于AA基因型患者(调整OR=0.63,95%CI:0.40~0.99,P=0.046)。叉生分析中,与携带rs897200 CT+CC基因型且有运动的患者相比,缺乏运动的TT基因型患者晚期风险增高(OR=3.71,95%CI:1.97~6.98,P < 0.001)。类似,rs1031507AA基因型与缺乏运动共同升高患者的晚期风险(OR=3.78,95%CI:2.01~7.13,P < 0.001)。但未观察到rs897200、rs1031507与运动存在影响肝癌分期的统计学交互作用。 结论 STAT4 rs897200和rs1031507遗传变异的独立效应及与运动的联合效应影响肝癌患者首诊时的临床分期。 Abstract:Objective To investigate the effect of genetic variants in STAT4 and its interaction with exercise on the pathological characteristics of patients with liver cancer. Methods In the 601 new patients with primary liver cancer, multivariate Logistic regression model was used to analyze the genetic association with the risks of advanced stage and portal vein tumor thrombosis at first diagnosis for patients. The multiplicative interaction term and the "Delta" method were used to evaluate the multiplicative and additive interactions, respectively. Results Under the dominant model, the rs897200 variant showed a marginally statistical association with the risk of advanced liver cancer at first diagnosis for patients (adjusted OR=0.64, 95% CI: 0.41-1.01, P=0.057). Carriers of the rs1031507 CC+AC genotype had a lower risk of advanced liver cancer than those with the AA genotype (adjusted OR=0.63, 95% CI: 0.40-0.99, P=0.046). In the crossover analysis, compared with the patients who carried the rs897200 CT+CC genotype and had exercise, the TT genotype carriers being lack of exercise showed an increased risk of advanced cancer (OR=3.71, 95% CI: 1.97-6.98, P < 0.001). Similarly, the rs1031507 AA genotype and the lack of exercise jointly increased the risk of advanced cancer (OR=3.78, 95% CI: 2.01-7.13, P < 0.001). However, no statistical interactions between the genetic factors and exercise were observed for liver cancer stages. Conclusion The genetic variants in STAT4, rs897200 and rs1031507, solely or jointly with exercise, affect the clinical stage of liver cancer at patients' first diagnosis. -
Key words:
- STAT4 /
- Primary liver cancer /
- Genetic variants /
- TNM stage /
- Portal vein cancer thrombus
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表 1 研究对象特征[n(%)]
Table 1. Characteristics of study subjects[n(%)]
变量 TNM分期a 门脉癌栓b Ⅲ+Ⅳ(N=472) Ⅰ+Ⅱ(N=106) χ2值 P值 有(N=63) 无(N=530) χ2值 P值 年龄组(岁) 0.88 0.349 4.92 0.027 >50 307(80.58) 74(19.42) 34(8.63) 360(91.37) ≤50 165(83.76) 32(16.24) 29(14.57) 170(85.43) 性别 0.02 0.879 0.04 0.845 男 407(81.56) 92(18.44) 54(10.53) 459(89.47) 女 65(82.28) 14(17.72) 9(11.25) 71(88.75) 吸烟 0.28 0.598 0.93 0.336 否 155(82.89) 32(17.11) 24(12.37) 170(87.63) 是 317(81.07) 74(18.93) 39(9.77) 360(90.23) 饮酒 0.49 0.484 0.81 0.367 否 205(80.39) 50(19.61) 25(9.36) 242(90.64) 是 267(82.66) 56(17.34) 38(11.66) 288(88.34) 运动c 18.94 < 0.001 1.17 0.280 有 156(72.56) 59(27.44) 19(8.76) 198(91.24) 无 316(87.05) 47(12.95) 43(11.59) 328(88.41) HBV慢性感染 1.00 0.319 3.01 0.083 无 116(78.91) 31(21.09) 10(6.80) 137(93.20) 有 356(82.60) 75(17.40) 53(11.88) 393(88.12) 肝癌家族史 0.53 0.469 0.02 0.878 无 406(81.20) 94(18.80) 55(10.70) 459(89.30) 有 66(84.62) 12(15.38) 8(10.13) 71(89.87) 注:a23例患者缺失TNM分期信息。b 8例患者缺失门脉癌栓信息。c 5例患者缺失运动情况信息。 表 2 STAT4遗传变异与TNM分期的关联分析
Table 2. Association analysis between genetic variants in STAT4 and TNM stages
遗传变异 Ⅲ+Ⅳ/Ⅰ+Ⅱ χ2值 P值 OR(95% CI)值 P值 OR(95% CI)a值 Pa值 rs7574865 2.77 0.250 GG 226/47 1.00 1.00 GT 196/52 0.276 0.78(0.51~1.22) 0.276 0.81(0.52~1.27) 0.354 TT 50/7 0.362 1.49(0.63~3.48) 0.362 1.54(0.65~3.66) 0.328 显性模型b - 0.509 0.87(0.57~1.32) 0.509 0.90(0.58~1.38) 0.620 隐性模型c - 0.218 1.68(0.74~3.81) 0.218 1.71(0.74~3.94) 0.207 加性模型d - 0.950 1.01(0.73~1.39) 0.950 1.04(0.74~1.44) 0.838 rs897200 3.22 0.200 TT 200/35 1.00 1.00 CT 212/55 0.098 0.68(0.42~1.08) 0.098 0.64(0.40~1.03) 0.068 CC 59/16 0.193 0.65(0.33~1.25) 0.193 0.65(0.33~1.28) 0.214 显性模型e - 0.075 0.67(0.43~1.04) 0.075 0.64(0.41~1.01) 0.057 隐性模型f - 0.478 0.81(0.44~1.46) 0.478 0.84(0.45~1.54) 0.566 加性模型g - 0.101 0.77(0.57~1.05) 0.101 0.77(0.56~1.05) 0.097 rs1031507 3.49 0.174 AA 202/35 1.00 1.00 AC 210/55 0.082 0.66(0.42~1.05) 0.082 0.63(0.39~1.01) 0.054 CC 59/16 0.183 0.64(0.33~1.24) 0.183 0.64(0.33~1.27) 0.202 显性模型h - 0.063 0.66(0.42~1.02) 0.063 0.63(0.40~0.99) 0.046 隐性模型i - 0.478 0.81(0.44~1.46) 0.478 0.84(0.45~1.54) 0.566 加性模型j - 0.090 0.77(0.57~1.04) 0.090 0.76(0.56~1.04) 0.085 注:a调整性别、年龄、吸烟、饮酒、运动、HBV慢性感染和肝癌家族史;b GT+TT vs GG;c TT vs GT+GG;d TT vs GT vs GG;e CC+CT vs TT;f CC vs CT+CC;g CC vs CT vs TT;h CC+AC vs AA;i CC vs AC+AA;j CC vs AC vs AA。 表 3 STAT4遗传变异与门脉癌栓的关联分析
Table 3. Association analysis between genetic variants in STAT4 and portal vein tumor thrombosis
遗传变异 有/无 χ2值 P值 OR(95% CI) P值 OR(95% CI)a Pa值 rs7574865 0.33 0.846 GG 29/249 1.00 GT 29/228 0.751 1.09(0.63~1.88) 0.751 1.20(0.69~2.10) 0.521 TT 5/52 0.706 0.83(0.31~2.23) 0.706 0.84(0.31~2.29) 0.726 显性模型b - 0.876 1.04(0.62~1.76) 0.876 1.13(0.66~1.93) 0.660 隐性模型c - 0.631 0.79(0.30~2.06) 0.631 0.76(0.29~2.01) 0.585 加性模型d - 0.922 0.98(0.66~1.46) 0.922 1.02(0.68~1.52) 0.934 rs897200 1.03 0.596 TT 29/218 1.00 1.00 CT 25/245 0.358 0.77(0.44~1.35) 0.358 0.75(0.42~1.33) 0.321 CC 9/65 0.92 1.04(0.47~2.31) 0.922 1.04(0.46~2.34) 0.928 显性模型e - 0.471 0.82(0.49~1.39) 0.471 0.81(0.47~1.38) 0.432 隐性模型f - 0.655 1.19(0.56~2.52) 0.655 1.21(0.56~2.59) 0.632 加性模型g - 0.759 0.94(0.64~1.39) 0.759 0.93(0.63~1.39) 0.735 rs1031507 1.50 0.473 AA 30/219 1.00 1.00 AC 24/244 0.252 0.72(0.41~1.27) 0.252 0.70(0.39~1.24) 0.222 CC 9/65 0.979 1.01(0.46~2.24) 0.979 1.01(0.45~2.27) 0.983 显性模型h - 0.352 0.78(0.46~1.32) 0.352 0.76(0.45~1.30) 0.319 隐性模型i - 0.655 1.19(0.56~2.52) 0.655 1.21(0.56~2.59) 0.629 加性模型j - 0.645 0.91(0.62~1.35) 0.645 0.91(0.61~1.35) 0.624 注:a调整性别、年龄、吸烟、饮酒、运动、HBV慢性感染和肝癌家族史;bGT+TT vs GG;cTT vs GT+GG;dTT vs GT vs GG;eCC+CT vs TT;fCC vs CT+CC;gCC vs CT vs TT;hCC+AC vs AA;iCC vs AC+AA;jCC vs AC vs AA。 表 4 遗传风险评分与病理特征的关联分析
Table 4. Association analysis between genetic risk score and pathological characteristics
遗传评分a TNM分期 门脉癌栓 Ⅲ+Ⅳ/Ⅰ+Ⅱ OR(95% CI) OR(95% CI)b 有/无 OR(95% CI) OR(95% CI)b 0~2 270/71 1.00 1.00 33/310 1.00 1.00 3~4 202/35 1.52(0.97~2.37) 1.58(1.00~2.49) 30/219 1.29(0.76~2.17) 1.32(0.77~2.25) 注:ars897200和rs1031507的危险等位基因分别为T和A。b调整性别、年龄、吸烟、饮酒、运动、HBV慢性感染和肝癌家族史。 表 5 rs897200、rs1031507与运动的交互作用分析
Table 5. Interaction analysis between rs897200, rs1031507, and exercise
运动情况 遗传变异 TNM分期 门脉癌栓 Ⅲ+Ⅳ/Ⅰ+Ⅱ OR(95%CI)a P值ab P值ac 有/无 OR(95%CI)a P值ab P值ac rs897200 0.374 0.914 0.114 0.266 有 CT+CC 86/41 1.00 8/120 1.00 有 TT 70/18 1.90(1.00~3.62) 11/77 2.36(0.90~6.20) 无 CT+CC 185/30 2.94(1.71~5.04) 26/188 1.99(0.87~4.57) 无 TT 130/17 3.71(1.97~6.98) 17/139 1.83(0.76~4.44) rs1031507 0.363 0.924 0.054 0.210 有 AC+CC 85/41 1.00 7/120 1.00 有 AA 71/18 1.95(1.03~3.71) 12/77 2.92(1.09~7.81) 无 AC+CC 184/30 2.95(1.72~5.07) 26/187 2.27(0.95~5.42) 无 AA 131/17 3.78(2.01~7.13) 17/140 2.07(0.82~5.20) 注:a调整性别、年龄、吸烟、饮酒、HBV慢性感染和肝癌家族史。b相乘交互作用。c相加交互作用。 -
[1] Bray F, Ferlay J, Soerjomataram I, et al. Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries[J]. CA Cancer J Clin, 2018, 68(6): 394-424. DOI: 10.3322/caac.21492. [2] 李岸花, 谭超, 刘顺, 等. FOXO基因多态性与肝细胞癌临床病理特征的关系[J]. 中华疾病控制杂志, 2015, 19(5): 454-457. DOI: 0.16462/j.cnki.zhjbkz.2015.05.007.Li AH, Tan C, Liu S, et al. Correlation of FOXO gene polymorphisms with clinico-pathological characteristics of hepatocellular carcinoma[J]. Chin J Dis Control Prev, 2015, 19(5): 454-457. DOI: 0.16462/j.cnki.zhjbkz.2015.05.007.zhjbkz.2015.05.007. [3] Jiang DK, Sun J, Cao G, et al. Genetic variants in STAT4 and HLA-DQ genes confer risk of hepatitis B virus-related hepatocellular carcinoma[J]. Nat Genet, 2013, 45(1): 72-75. DOI: 10.1038/ng.2483. [4] O'Shea JJ, Holland SM, Staudt LM. JAKs and STATs in immunity, immunodeficiency, and cancer[J]. N Engl J Med, 2013, 368(2): 161-170. DOI: 10.1056/NEJMra1202117. [5] 中华人民共和国卫生部. 原发性肝癌诊疗规范(2011年版)[J]. 临床肿瘤学杂志, 2011, 16(10): 929-946. DOI: 10.3760/cma.j.issn.1007-3418.2012.06.007.Ministry of health of the People's Republic of China. Guidelines for the diagnosis and treatment of primary liver cancer (2011 edition)[J]. Chin Clin Oncol, 2011, 16(10): 929-946. DOI: 10.3760/cma.j.issn.1007-3418.2012.06.007. [6] Edge SB, Compton CC. The American joint committee on cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM[J]. Ann Surg Oncol, 2010, 17(6): 1471-1474. DOI: 10.1245/s10434-010-0985-4. [7] 林子博, 祁永芬, 周新凤, 等. 广东顺德地区原发性肝癌发病危险因素研究[J]. 中华疾病控制杂志, 2017, 21(10): 993-996. DOI: 10.16462/j.cnki.zhjbkz.2017.10.006.Lin ZB, Qi YF, Zhou XF, et al. Analysis of the risk factors for primary liver cancer in Shunde region, Guangdong[J]. Chin J Dis Control Prev, 2017, 21(10): 993-996. DOI: 10.16462/j.cnki.zhjbkz.2017.10.006. [8] Wacholder S, Chanock S, Garciaclosas M, et al. Assessing the probability that a positive report is false: an approach for molecular epidemiology studies[J]. J Natl Cancer Inst, 2004, 96(6): 434-442. DOI: 10.1093/jnci/djh075. [9] 王铖, 戴俊程, 孙义民, 等. 遗传风险评分的原理与方法[J]. 中华流行病学杂志, 2015, 36(10): 1062-1064. DOI: 10.3760/cma.j.issn.0254-6450.2015.10.005.Wang C, Dai JC, Sun YM, et al. Genetic risk score: principle, methods and application[J]. Chin J Epidemiol, 2015, 36(10): 1062-1064. DOI: 10.3760/cma.j.issn.0254-6450.2015.10.005. [10] 袁悦, 李楠, 任爱国, 等. 流行病学研究中相加和相乘尺度交互作用的分析[J]. 现代预防医学, 2015, 42(6): 961-965. https://www.cnki.com.cn/Article/CJFDTOTAL-XDYF201506001.htmYuan Y, li N, Ren AG, et al. Analysis of the application of the additive model and the multiplicative statistical model in biologial interaction[J]. Modern Preventive Medicine, 2015, 42(6): 961-965. https://www.cnki.com.cn/Article/CJFDTOTAL-XDYF201506001.htm [11] 陶一明, 冯铁诚, 王志明. 原发性肝癌患者TNM分期与术后生存关系: SEER数据库分析[J]. 中国普通外科杂志, 2016, 25(7): 952-956. DOI: 10.3978/j.issn.1005-6947.2016.07.004.Tao YM, Feng TC, Wang ZM. Association of TNM stage with postoperative survival in patients with primary liver cancer: an analysis of SEER database[J], Chin J Gen Surg, 2016, 25(7): 952-956. DOI: 10.3978/j.issn.1005-6947.2016.07.004. [12] Ignacio A, Breda CNS, Camara NOS. Innate lymphoid cells in tissue homeostasis and diseases[J]. World J Hepatol, 2017, 9(23): 979-989. DOI: 10.4254/wjh.v9.i23.979. [13] Zhao L, Ji G, Le X, et al. An integrated analysis identifies STAT4 as a key regulator of ovarian cancer metastasis[J]. Oncogene, 2017, 36(24): 3384-3396. DOI: 10.1038/onc.2016.487. [14] Wubetu GY, Utsunomiya T, Ishikawa D, et al. High STAT4 expression is a better prognostic indicator in patients with hepatocellular carcinoma after hepatectomy[J]. Ann Surg Oncol, 2014, 21 Suppl 4: S721-S728. DOI: 10.1245/s10434-014-3861-9. [15] Hou S, Yang Z, Du L, et al. Identification of a susceptibility locus in STAT4 for Behcet's disease in Han Chinese in a genome-wide association study[J]. Arthritis Rheum, 2012, 64(12): 4104-4113. DOI: 10.1002/art.37708. [16] Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans[J]. Science, 2015, 348(6235): 648-660. DOI: 10.1126/science.1262110. [17] 杨欢, 熊晶, 洛文靖, 等. 转录因子DEC1在肿瘤发生发展过程中的作用[J]. 中国药科大学学报, 2015, 46(5): 541-547. DOI: 10.11665/j.issn.1000-5048.20150504.Yang H, Xiong J, Luo WJ, et al. Role of transcription factor DEC1 in the initiation and progression of malignant tumors[J]. J Chin Pharm Univ, 2015, 46(5): 541-547. DOI: 10.11665/j.issn.1000-5048.20150504. [18] Saran U, Guarino M, Rodriguez S, et al. Anti-tumoral effects of exercise on hepatocellular carcinoma growth[J]. Hepatol Commun, 2018, 2(5): 607-620. DOI: 10.1002/hep4.1159. [19] Hargreaves M. Exercise and gene expression[J]. Prog Mol Biol Transl Sci, 2015, 135: 457-469. DOI: 10.1016/bs.pmbts.2015.07.006.