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摘要:
2型糖尿病和肿瘤是两类严重威胁人类健康的慢性疾病。大量的流行病学和临床研究表明,2型糖尿病患者肝癌、胰腺癌、子宫内膜癌、胆囊癌、结直肠癌和乳腺癌的风险增加。高血糖可通过多种直接和间接机制促进癌细胞增殖、迁移、侵袭和免疫逃逸。胰岛素抵抗和高胰岛素血症会通过胰岛素/IGF-I信号轴激活多条信号通路促进肿瘤发生。持续的慢性炎性反应可通过DNA损伤和促炎因子促进癌症的发生发展。肠道菌群失调主要与几种消化道肿瘤发生密切相关。本文将对2型糖尿病与恶性肿瘤发生发展的关系及可能的机制研究进展进行综述。
Abstract:Type 2 diabetes mellitus and malignant tumors are two kinds of chronic diseases with tremendous impact on human health. Numerous epidemiological and clinical studies have shown that type 2 diabetes mellitus increases the risk of liver, pancreatic, endometrial, gallbladder, colorectal and breast cancers. Hyperglycemia can promote cancer cell proliferation, migration, invasion and immune escape through a variety of direct and indirect mechanisms. Insulin resistance and hyperinsulinemia can activate multiple signal transduction pathways through insulin/IGF-I signaling axis and promote tumorigenesis. Sustained chronic inflammatory responses can promote the development of cancer through DNA damage and pro-inflammatory factors. Gut microbiome dysbiosis is closely related to the occurrence of several gastrointestinal tumors. This paper reviews the progress on the correlation between type 2 diabetes mellitus and the progression of malignant tumors and the possible mechanisms.
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Key words:
- Type 2 diabetes mellitus /
- Tumor /
- Hyperglycemia /
- Hyperinsulinemia /
- Chronic inflammation /
- Gut microbiome
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0 引言
肝癌是全球常见的恶性肿瘤之一,病理类型有肝细胞癌(hepatocellular carcinoma, HCC)、肝内胆管细胞癌、混合癌,其中肝细胞癌占85%~90%[1]。根据2020年癌症全球人数统计,肝癌是全球第三大癌症死亡原因,死亡人数占癌症总死亡人数的8.3%,是中国癌症死亡人数的第2名[2]。我国肝癌5年生存率不足15%[3]。甲胎蛋白(alpha-fetoprotein, AFP)是筛查HCC的常用指标,术后AFP升高常提示HCC复发,但约30%的患者AFP没有升高或不表达,延误治疗最佳时机[4]。临床上需要联合有效的指标协助判断患者预后,提高生存质量。
血清乳酸脱氢酶/白蛋白比值(lactate dehydrogenase to albumin ratio, LAR)是判断恶性肿瘤预后的血清学检测指标之一。在多种癌症的研究中显示,血清乳酸脱氢酶(LDH)水平是肿瘤缺氧、新生血管生成和预后不良的间接标志[5]。术前低蛋白血症是营养不良的指标,与胃癌和肝癌等患者的总体存活率低和复发率高有关[5-6]。LAR在胃癌和鼻咽癌等癌症中的不良预后作用已被验证,而在HCC中研究较少。本研究回顾性分析106例HCC患者临床资料,评价患者术前外周血LAR与预后的关系,并将LAR联合AFP来评估HCC患者预后的价值,以期为HCC的临床判断提供一定的参考。
1 资料与方法
1.1 一般资料
回顾性分析2015年1月—2019年12月在兰州大学第一医院普外科行根治性手术的106例HCC患者的临床资料,其中男81例(76.4%),女25例(23.6%);年龄26~78(54.5±10.1)岁。临床分期按照2018年修改的AJCC第8版分期系统。纳入标准:(1)18~80岁;(2)术中肿瘤根治性切除;(3)术后病理证实为HCC;(4)无严重的心、肺、脑、肾严重功能障碍及血液系统疾病;(5)患者临床及随访资料完整。排除标准:(1)不可切除或非根治性切除的肝癌;(2)术后病理证实非HCC;(3)既往有其他恶性肿瘤病史者;(4)拒绝签署知情同意书及随访过程中失访者。本研究通过本院伦理委员会审批(批准号:LDYYLL2021-348)。
1.2 数据收集
收集患者的基本信息:性别、年龄、体重指数;术前1周内的血常规检查:肝炎病毒抗原、白蛋白(ALB)、LDH、AFP;影像学检查;疾病信息:肿瘤T分期、N分期、临床分期、术后有无介入手术治疗等。
1.3 随访情况
采用住院或门诊就诊、电话等方式进行随访,每3月随访一次,末次随访时间为2021年5月。总生存期(overall survival, OS)是从患者术后第1日开始至末次随访或死亡的时间;无病生存期(disease-free survival, DFS)是患者手术后第1日至疾病复发或(因任何原因)死亡之间的时间[7]。随访时间为0~77月,中位随访时间为28月。106例随访病例复发75例(70.8%),死亡30例(28.3%),1例未复发。
1.4 统计学方法
采用SPSS26.0软件进行统计学分析。根据中位数以LAR为4.58进行分层(LAR≥4.58和LAR < 4.58)。计数资料用例数和百分比表示,两组间比较采用χ2或Fisher精确检验,等级变量采用秩和检验。使用Kaplan-Meier绘制生存曲线并采用Log rank检验。利用Cox风险回归模型进行单多因素回归分析,判断影响HCC患者预后的危险因素;对LAR和AFP联合分组进行检验,并绘制Kaplan-Meier生存曲线。P < 0.05为差异有统计学意义。
2 结果
2.1 术前LAR水平与HCC患者临床、病理特征的关系
106例患者中,1年的DFS为49.1%,3年的DFS为9.4%,1年的OS为81.1%,3年的OS为22.6%。根据既往研究结果,取AFP截断值为400 μg/L,以LAR=4.58为阈值分层,单因素分析显示两组间T分期和临床分期比较差异有统计学意义(均P < 0.05),见表 1。
表 1 HCC患者的临床资料与LAR相关性分析(n(%))Table 1 Correlation between clinical data and LAR of HCC patients (n(%))2.2 LAR、AFP与HCC患者预后的关系
高LAR组(LAR≥4.58, n=53),低LAR组(LAR < 4.58, n=53);高AFP组(AFP≥400 μg/L, n=24),低AFP组(AFP < 400 μg/L, n=82)。Log rank检验单因素分析显示,高LAR组和高AFP组的DFS和OS显著短于低LAR组和低AFP组,差异有统计学意义(P < 0.05),Kaplan-Meier生存曲线见图 1。
2.3 影响HCC患者术后DFS和OS的Cox单多因素回归分析
按照中位数患者被分为高LAR组(LAR≥4.58, n=53)和低LAR组(LAR < 4.58, n=53)。根据既往文献对T分期进行分类(T1~T2/T3~T4),将HCC患者性别、年龄、BMI、肝炎病毒抗原、LAR、AFP、T分期、N分期和术后介入治疗等因素纳入Cox单因素回归分析,结果表明LAR、AFP、T分期与DFS相关(P < 0.05),LAR、AFP、T分期、术后介入治疗与OS相关(P < 0.05)。将单因素分析中有临床意义的变量纳入多因素回归分析,结果显示高LAR、高AFP和T3~T4期是HCC患者DFS和OS的独立危险因素(P < 0.05),术后行介入手术治疗可延长HCC患者的OS,见表 2。
表 2 HCC患者DFS和OS的Cox单多因素回归分析Table 2 Cox univariate and multivariate regression analyses of DFS and OS in HCC patients2.4 血清LAR联合AFP与HCC患者术后DFS和OS的关系
结果显示高LAR且高AFP组(LAR≥4.58且AFP≥400 μg/L, n=12)的DFS和OS最短,低LAR且低AFP组(LAR < 4.58且AFP < 400 μg/L, n=41)的DFS和OS最长(P < 0.05),见图 2。
3 讨论
肝癌是我国第四大常见恶性肿瘤[8],据2018年世界卫生组织(WHO)统计,我国肝癌人数占全球肝癌病例总数的46.7%[9]。肝癌主要的危险因素有慢性乙型病毒性肝炎、慢性丙型病毒性肝炎、酗酒、代谢性肝病等。目前AFP作为临床最常用的血液学检测方法对HCC进行筛查和预后监测,但其敏感度较低,为25%~65%[1]。因此需联合简单可行的血液学检测方法对HCC预后进行判断,早期实施干预措施,改善HCC预后。
高LDH和低ALB水平提示恶性肿瘤的不良预后,LAR将LDH与ALB结合可在肿瘤血管生成、细胞存活和机体营养状况等方面综合判断肿瘤预后,准确性较单个指标更高,其不良预后作用在结直肠癌、食管癌等多种肿瘤中得到验证[10-11]。Gan等[6]对1 041例原发性肝癌患者进行分析,发现LAR是原发性肝癌患者OS和无进展生存期(progression-free survival, PFS)的准确预测因子。本研究发现术前LAR与肿瘤的T分期和临床分期相关,与以往研究结果一致,高LAR是HCC的独立不良预后因素,高LAR水平的HCC患者,术后复发风险比低LAR组高约1.606倍。
LDH是一种参与无氧糖酵解的代谢酶[11],高LDH与肿瘤血管生成、细胞存活和肿瘤形成相关[12],是胃癌、胰腺癌等恶性肿瘤的不良预后因素[10-11, 13]。Wu等[14]研究显示LDH是原发性肝癌患者OS和PFS的独立预后因素。高LDH提示不良预后的可能原因有:(1)肿瘤细胞增殖活跃、肿瘤微环境氧耗增加[15]、缺氧诱导因子-1(HIF-1)的异常激活可上调肿瘤细胞中的LDH-A,确保肿瘤细胞在低氧条件下进行糖酵解代谢并且减少对氧气的需求[16];(2)PI3K/Akt/mTOR通路是肿瘤中最常被激活的信号通路之一,可通过调节LDH促进肿瘤细胞增殖、生长[17];(3)异常激活的热休克蛋白通过其转录调节因子热休克因子(HSF-1),调节葡萄糖代谢和增加乳酸脱氢酶(LDH-A)的表达[18],促进肿瘤细胞的增值、侵袭和转移。ALB作为肝脏合成的糖蛋白,是判断肝功能是否损伤的早期重要指标[19]。Fox等[20]通过分析2 918例患者的临床资料发现术前低蛋白血症为原发性肝癌不良预后的重要因素。术前白蛋白水平较低的原因可能有:肝功能障碍引起白蛋白合成、分泌较少;肿瘤相关的炎性反应引起蛋白分解加速[5]。LAR为LDH和ALB值之比,LAR升高不仅可以反应LDH升高,也可反应ALB降低。本研究通过对106例患者分析发现高LAR组患者的DFS和OS短于低LAR组患者,且差异有统计学意义(P < 0.05),与上述研究结果基本一致。
本研究发现,LAR和AFP均与HCC的不良预后密切相关,LAR和AFP均升高的组预后最差,对HCC患者术后DFS和OS的判断有统计学意义。本研究为单中心、小样本的回顾性研究,存在一定的局限性,未来需进行多中心、大样本的前瞻性研究,进一步了解影响肝癌预后的危险因素,提高对肝癌预后判断的准确性,及时干预治疗,延长DFS和OS,提高患者生存质量。
Competing interests: The authors declare that they have no competing interests.作者贡献:周韩:文献收集、文章撰写盛德乔:文章设计、指导及修改 -
表 1 T2DM促进癌症发生的机制
Table 1 Mechanisms of T2DM promoting carcinogenesis
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[1] WHO. Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. WHO; 2020. ACCESSED DECEMBER 11, 2020. https://www.who.int/data/gho/data/themes/theme-details/GHO/mortality-and-global-health-estimates/causes-of-death
[2] International Diabetes Federation. IDF Diabetes Atlas 2021[EB]. https://diabetesatlas.org/atlas/tenth-edition/
[3] Luo Z, Fabre G, Rodwin VG. Meeting the Challenge of Diabetes in China[J]. Int J Health Policy Manag, 2020, 9(2): 47-52.
[4] Chen W, Zheng R, Baade PD, et al. Cancer statistics in China, 2015[J]. CA Cancer J Clin, 2016, 66(2): 115-132. doi: 10.3322/caac.21338
[5] Talib WH, Mahmod AI, Abuarab SF, et al. Diabetes and Cancer: Metabolic Association, Therapeutic Challenges, and the Role of Natural Products[J]. Molecules, 2021, 26(8): 2179. doi: 10.3390/molecules26082179
[6] Pearson-Stuttard J, Zhou B, Kontis V, et al. Worldwide burden of cancer attributable to diabetes and high body-mass index: a comparative risk assessment[J]. Lancet Diabetes Endocrinol, 2018, 6(6): e6-e15. doi: 10.1016/S2213-8587(18)30150-5
[7] Tsilidis KK, Kasimis JC, Lopez DS, et al. Type 2 diabetes and cancer: umbrella review of meta-analyses of observational studies[J]. BMJ, 2015, 350: g7607. doi: 10.1136/bmj.g7607
[8] Liu XD, Hemminki K, Forsti A, et al. Cancer risk in patients with type 2 diabetes mellitus and their relatives[J]. Int J Cancer, 2015, 137(4): 903-10. doi: 10.1002/ijc.29440
[9] Saarela K, Tuomilehto J, Sund R, et al. Cancer incidence among Finnish people with type 2 diabetes during 1989-2014[J]. Eur J Epidemiol, 2019, 34(3): 259-265. doi: 10.1007/s10654-018-0438-0
[10] de Jong R, Peeters P, Burden AM, et al. Gastrointestinal cancer incidence in type 2 diabetes mellitus; results from a large population-based cohort study in the UK[J]. Cancer Epidemiol, 2018, 54: 104-111. doi: 10.1016/j.canep.2018.04.008
[11] Chen Y, Wu F, Saito E, et al. Association between type 2 diabetes and risk of cancer mortality: a pooled analysis of over 771, 000 individuals in the Asia Cohort Consortium[J]. Diabetologia, 2017, 60(6): 1022-1032. doi: 10.1007/s00125-017-4229-z
[12] 赵佳, 韩雪, 谢梦, 等. 2型糖尿病并发恶性肿瘤患者的流行病学分析[J]. 中国慢性病预防与控制, 2018, 26(7): 514-516. doi: 10.16386/j.cjpccd.issn.1004-6194.2018.07.008 Zhao J, Han X, Xie M, et al. Epidemiological analysis of patients with type 2 diabetes mellitus complicated with malignant tumor[J]. Zhongguo Man Xing Bing Yu Fang Yu Kong Zhi, 2018, 26(7): 514-516. doi: 10.16386/j.cjpccd.issn.1004-6194.2018.07.008
[13] Gini A, Bidoli E, Zanier L, et al. Cancer among patients with type 2 diabetes mellitus: A population-based cohort study in northeastern Italy[J]. Cancer Epidemiol, 2016, 41: 80-87. doi: 10.1016/j.canep.2016.01.011
[14] Linkeviciute-Ulinskiene D, Patasius A, Zabuliene L, et al. Increased Risk of Site-Specific Cancer in People with Type 2 Diabetes: A National Cohort Study[J]. Int J Environ Res Public Health, 2019, 17(1): 246. doi: 10.3390/ijerph17010246
[15] Pang Y, Kartsonaki C, Guo Y, et al. Diabetes, plasma glucose and incidence of pancreatic cancer: A prospective study of 0.5 million Chinese adults and a meta-analysis of 22 cohort studies[J]. Int J Cancer, 2017, 140(8): 1781-1788. doi: 10.1002/ijc.30599
[16] Yuan S, Kar S, Carter P, et al. Is Type 2 Diabetes Causally Associated With Cancer Risk? Evidence From a Two-Sample Mendelian Randomization Study[J]. Diabetes, 2020, 69(7): 1588-1596. doi: 10.2337/db20-0084
[17] Gallagher EJ, LeRoith D. Obesity and Diabetes: The Increased Risk of Cancer and Cancer-Related Mortality[J]. Physiol Rev, 2015, 95(3): 727-748. doi: 10.1152/physrev.00030.2014
[18] Chang SC, Yang WV. Hyperglycemia, tumorigenesis, and chronic inflammation[J]. Crit Rev Oncol Hematol, 2016, 108: 146-153. doi: 10.1016/j.critrevonc.2016.11.003
[19] Khalid M, Alkaabi J, Khan MAB, et al. Insulin Signal Transduction Perturbations in Insulin Resistance[J]. Int J Mol Sci, 2021, 22(16): 8590. doi: 10.3390/ijms22168590
[20] Fernandez CJ, George AS, Subrahmanyan NA, et al. Epidemiological link between obesity, type 2 diabetes mellitus and cancer[J]. World J Methodol, 2021, 11(3): 23-45. doi: 10.5662/wjm.v11.i3.23
[21] Hosseini L, Alinezhad F, Kharazi U, et al. The Association of Type 2 Diabetes and Site-Specific Cancers: Linking Mechanisms[J]. Crit Rev Oncog, 2019, 24(3): 259-267. doi: 10.1615/CritRevOncog.2019031108
[22] Teng JA, Wu SG, Chen JX, et al. The Activation of ERK1/2 and JNK MAPK Signaling by Insulin/IGF-1 Is Responsible for the Development of Colon Cancer with Type 2 Diabetes Mellitus[J]. PLoS One, 2016, 11(2): e0149822. doi: 10.1371/journal.pone.0149822
[23] Kong L, Wang Q, Jin J, et al. Insulin resistance enhances the mitogen-activated protein kinase signaling pathway in ovarian granulosa cells[J]. PLoS One, 2017, 12(11): e0188029. doi: 10.1371/journal.pone.0188029
[24] Bowers LW, Rossi EL, O'Flanagan CH, et al. The Role of the Insulin/IGF System in Cancer: Lessons Learned from Clinical Trials and the Energy Balance-Cancer Link[J]. Front Endocrinol (Lausanne), 2015, 6: 77.
[25] Esser N, Legrand-Poels S, Piette J, et al. Inflammation as a link between obesity, metabolic syndrome and type 2 diabetes[J]. Diabetes Res Clin Pract, 2014, 105(2): 141-150. doi: 10.1016/j.diabres.2014.04.006
[26] Iyengar NM, Hudis CA, Dannenberg AJ. Obesity and cancer: local and systemic mechanisms[J]. Annu Rev Med, 2015, 66: 297-309. doi: 10.1146/annurev-med-050913-022228
[27] Chu DT, Phuong TNT, Tien NLB, et al. The Effects of Adipocytes on the Regulation of Breast Cancer in the Tumor Microenvironment: An Update[J]. Cells, 2019, 8(8): 857. doi: 10.3390/cells8080857
[28] Rokavec M, Oner MG, Hermeking H. Inflammation-induced epigenetic switches in cancer[J]. Cell Mol Life Sci, 2016, 73(1): 23-39. doi: 10.1007/s00018-015-2045-5
[29] Shlomai G, Neel B, LeRoith D, et al. Type 2 Diabetes Mellitus and Cancer: The Role of Pharmacotherapy[J]. J Clin Oncol, 2016, 34(35): 4261-4269. doi: 10.1200/JCO.2016.67.4044
[30] Nicholson JK, Holmes E, Kinross J, et al. Host-gut microbiota metabolic interactions[J]. Science, 2012, 336(6086): 1262-1267. doi: 10.1126/science.1223813
[31] Pickard JM, Zeng MY, Caruso R, et al. Gut microbiota: Role in pathogen colonization, immune responses, and inflammatory disease[J]. Immunol Rev, 2017, 279(1): 70-89. doi: 10.1111/imr.12567
[32] Gagniere J, Raisch J, Veziant J, et al. Gut microbiota imbalance and colorectal cancer[J]. World J Gastroenterol, 2016, 22(2): 501-518. doi: 10.3748/wjg.v22.i2.501
[33] Qin J, Li Y, Cai Z, et al. A metagenome-wide association study of gut microbiota in type 2 diabetes[J]. Nature, 2012, 490(7418): 55-60. doi: 10.1038/nature11450
[34] Sheflin AM, Whitney AK, Weir TL. Cancer-promoting effects of microbial dysbiosis[J]. Curr Oncol Rep, 2014, 16(10): 406. doi: 10.1007/s11912-014-0406-0
[35] Weng MT, Chiu YT, Wei PY, et al. Microbiota and gastrointestinal cancer[J]. J Formos Med Assoc, 2019, 118 Suppl 1: S32-S41.
[36] Huang QY, Yao F, Zhou CR, et al. Role of gut microbiome in regulating the effectiveness of metformin in reducing colorectal cancer in type 2 diabetes[J]. World J Clin Cases, 2020, 8(24): 6213-6228. doi: 10.12998/wjcc.v8.i24.6213
[37] Wong SH, Yu J. Gut microbiota in colorectal cancer: mechanisms of action and clinical applications[J]. Nat Rev Gastroenterol Hepatol, 2019, 16(11): 690-704. doi: 10.1038/s41575-019-0209-8
[38] Gleeson MW. Interplay of Liver Disease and Gut Microbiota in the Development of Colorectal Neoplasia[J]. Curr Treat Options Gastroenterol, 2019, 17(3): 378-393. doi: 10.1007/s11938-019-00241-6
[39] Jiang JW, Chen XH, Ren Z, et al. Gut microbial dysbiosis associates hepatocellular carcinoma via the gut-liver axis[J]. Hepatobiliary Pancreat Dis Int, 2019, 18(1): 19-27. doi: 10.1016/j.hbpd.2018.11.002
[40] Yu LX, Schwabe RF. The gut microbiome and liver cancer: mechanisms and clinical translation[J]. Nat Rev Gastroenterol Hepatol, 2017, 14(9): 527-539. doi: 10.1038/nrgastro.2017.72
[41] Wang C, Li J. Pathogenic Microorganisms and Pancreatic Cancer[J]. Gastrointest Tumors, 2015, 2(1): 41-47. doi: 10.1159/000380896
[42] Pothuraju R, Rachagani S, Junker WM, et al. Pancreatic cancer associated with obesity and diabetes: an alternative approach for its targeting[J]. J Exp Clin Cancer Res, 2018, 37(1): 319. doi: 10.1186/s13046-018-0963-4
[43] Chiefari E, Mirabelli M, La Vignera S, et al. Insulin Resistance and Cancer: In Search for a Causal Link[J]. Int J Mol Sci, 2021, 22(20): 11137. doi: 10.3390/ijms222011137
[44] Vincent EE, Yaghootkar H. Using genetics to decipher the link between type 2 diabetes and cancer: shared aetiology or downstream consequence?[J]. Diabetologia, 2020, 63(9): 1706-1717. doi: 10.1007/s00125-020-05228-y
[45] Wang M, Yang Y, Liao Z. Diabetes and cancer: Epidemiological and biological links[J]. World J Diabetes, 2020, 11(6): 227-238. doi: 10.4239/wjd.v11.i6.227
[46] Vancura A, Bu P, Bhagwat M, et al. Metformin as an Anticancer Agent[J]. Trends Pharmacol Sci, 2018, 39(10): 867-878. doi: 10.1016/j.tips.2018.07.006
[47] Wynn A, Vacheron A, Zuber J, et al. Metformin Associated With Increased Survival in Type 2 Diabetes Patients With Pancreatic Cancer and Lymphoma[J]. Am J Med Sci, 2019, 358(3): 200-203. doi: 10.1016/j.amjms.2019.06.002
[48] Helmink BA, Khan MAW, Hermann A, et al. The microbiome, cancer, and cancer therapy[J]. Nat Med, 2019, 25(3): 377-388. doi: 10.1038/s41591-019-0377-7
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