甲基化驱动基因ZC2HC1A的表达对肝癌预后的影响以及与免疫浸润的关系
Effect of Expression of Methylation Driver Gene ZC2HC1A on Prognosis of Hepatocellular Carcinoma and Its Association with Immune Infiltration
DOI: 10.12677/ACM.2023.132376, PDF,   
作者: 王彦芳, 聂 耶, 毛珍珍, 贾巍力, 石 文:西安医学院,陕西 西安;空军军医大学第一附属医院肝胆外科,陕西 西安 ;张潇剑:西安医学院,陕西 西安;宋文杰*:空军军医大学第一附属医院肝胆外科,陕西 西安
关键词: 甲基化驱动基因预后标志物免疫浸润HCCMethylation-Driven Gene Prognostic Marker Immune Infiltration HCC
摘要: 背景:肝细胞肝癌(HCC)是目前世界上发病率及死亡率较高的肿瘤,具有高度异质性,容易漏诊。本研究主要开发新的肿瘤标志物,提高HCC的诊断效能,为开发新型疗法提供新思路。方法:在癌症基因组图谱(TCGA)中下载HCC的表达数据和甲基化数据,筛选出甲基化驱动基因ZC2HC1A。分别在TCGA和ICGC (International Cancer Genome Consortium)数据库中研究ZC2HC1A的表达对HCC患者预后的影响。使用GSEA (Gene Set Enrichment Analysis),预测ZC2HC1A的功能通路。分析ZC2HC1A的表达与肿瘤免疫微环境中免疫细胞、免疫调节因子的关系。结果:发现甲基化驱动基因ZC2HC1A在HCC的患者中高表达,其中高表达组的肿瘤分级、临床分期和T分期更晚,1、3、5年生存率较低,提示预后不佳。GSEA分析得出ZC2HC1A高表达组与癌症和免疫相关的信号通路相关。ZC2HC1A高表达组抗肿瘤细胞CD8+T细胞、NK细胞、肥大细胞消耗过多,而促肿瘤细胞M0巨噬细胞明显升高。结论:ZC2HC1A表达量能够评估HCC预后;初步探索了ZC2HC1A与免疫治疗的相关性,指导临床医生精准治疗,并有望成为新的治疗靶点。
Abstract: Background: Hepatocellular carcinoma (HCC) is a tumor with high morbidity and mortality in the world, which is highly heterogeneous and easy to be missed. The purpose of this study is to develop new tumor markers, improve the diagnostic efficiency of HCC, and provide new ideas for the devel-opment of new therapies. Methods: Expression and methylation data of HCC were downloaded from cancer Genome Atlas (TCGA), and DNA methylation-driven gene ZC2HC1A was screened. The effects of ZC2HC1A expression on the prognosis of HCC patients were investigated in TCGA and Internation-al Cancer Genome Consortium (ICGC) databases. Gene Set Enrichment Analysis (GSEA) was used to predict the functional pathway of ZC2HC1A. The relationship between the expression of ZC2HC1A and immune cells in the tumor immune microenvironment was analyzed. Results: It was found that methylation-driven gene ZC2HC1A was highly expressed in HCC patients, and the tumor grade, clin-ical stage and T stage of the high expression group were later, and the survival rate of 1, 3 and 5 years was lower, suggesting poor prognosis. GSEA analysis showed that high expression of ZC2HC1A was associated with cancer and immune-related signaling pathways. CD8+T cells, NK cells and mast cells were consumed too much in the group with high expression of ZC2HC1A, while M0 macro-phages of tumor cells were significantly increased. Conclusions: The expression level of ZC2HC1A can evaluate the prognosis of HCC. This study preliminarily explored the correlation between ZC2HC1A and immunotherapy, guided clinicians to precision treatment, and is expected to become a new therapeutic target.
文章引用:王彦芳, 张潇剑, 聂耶, 毛珍珍, 贾巍力, 石文, 宋文杰. 甲基化驱动基因ZC2HC1A的表达对肝癌预后的影响以及与免疫浸润的关系[J]. 临床医学进展, 2023, 13(2): 2661-2674. https://doi.org/10.12677/ACM.2023.132376

参考文献

[1] Sung, H., et al. (2021) Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians, 71, 209-249. [Google Scholar] [CrossRef] [PubMed]
[2] Zhou, J., et al. (2020) Guidelines for the Diagnosis and Treatment of Hepatocellular Carcinoma (2019 Edition). Liver Cancer, 9, 682-720. [Google Scholar] [CrossRef] [PubMed]
[3] Zeng, Z., et al. (2021) Elevated CDK5R1 Predicts Worse Prognosis in Hepatocellular Carcinoma Based on TCGA Data. Bio-science Reports, 41, BSR20203594. [Google Scholar] [CrossRef
[4] Michalak, E.M., et al. (2019) The Roles of DNA, RNA and Histone Methylation in Ageing and Cancer. Nature Reviews Molecular Cell Biology, 20, 573-589. [Google Scholar] [CrossRef] [PubMed]
[5] Mehdipour, P., Murphy, T. and De Carvalho, D.D. (2020) The Role of DNA-Demethylating Agents in Cancer Therapy. Pharmacology & Therapeutics, 205, Article ID: 107416. [Google Scholar] [CrossRef] [PubMed]
[6] Laugsand, E.A., et al. (2015) Genetic and Non-Genetic Factors Associated with Constipation in Cancer Patients Receiving Opioids. Clinical and Translational Gastroenterology, 6, e90. [Google Scholar] [CrossRef] [PubMed]
[7] McPherson, S., McMullin, M.F. and Mills, K. (2017) Epigenetics in Myeloproliferative Neoplasms. Journal of Cellular and Molecular Medicine, 21, 1660-1667. [Google Scholar] [CrossRef] [PubMed]
[8] Pajares, M.A. and Perez-Sala, D. (2018) Mammalian Sulfur Amino Acid Metabolism: A Nexus between Redox Regulation, Nutrition, Epigenetics, and Detoxification. Antioxidants & Redox Sig-naling, 29, 408-452. [Google Scholar] [CrossRef] [PubMed]
[9] Obeid, R., et al. (2018) Effect of Adding B-Vitamins to Vitamin D and Calcium Supplementation on CpG Methylation of Epigenetic Aging Markers. Nutrition, Metabolism and Cardiovascular Diseases, 28, 411-417. [Google Scholar] [CrossRef] [PubMed]
[10] Wu, F., et al. (2020) Classification of Diffuse Lower-Grade Glioma Based on Immunological Profiling. Molecular Oncology, 14, 2081-2095. [Google Scholar] [CrossRef] [PubMed]
[11] Tomczak, K., Czerwinska, P. and Wiznerowicz, M. (2015) The Cancer Genome Atlas (TCGA): An Immeasurable Source of Knowledge. Contemporary Oncology (Pozn), 19, A68-A77. [Google Scholar] [CrossRef] [PubMed]
[12] Ding, W., et al. (2020) DNMIVD: DNA Methylation Interactive Vis-ualization Database. Nucleic Acids Research, 48, D856-D862. [Google Scholar] [CrossRef] [PubMed]
[13] Subramanian, A., et al. (2005) Gene Set Enrichment Analysis: A Knowledge-Based Approach for Interpreting Genome-Wide Expression Profiles. Proceedings of the National Academy of Sciences of the United States of America, 102, 15545-15550. [Google Scholar] [CrossRef] [PubMed]
[14] Li, T., et al. (2017) TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells. Cancer Research, 77, e108-e110. [Google Scholar] [CrossRef
[15] Li, C., et al. (2021) GEPIA2021: Integrating Multiple De-convolution-Based Analysis into GEPIA. Nucleic Acids Research, 49, W242-W246. [Google Scholar] [CrossRef] [PubMed]
[16] Zhang, H.K., et al. (2008) Decreased Expression of ING2 Gene and Its Clinicopathological Significance in Hepatocellular Carcinoma. Cancer Letters, 261, 183-192. [Google Scholar] [CrossRef] [PubMed]
[17] Hartke, J., Johnson, M. and Ghabril, M. (2017) The Diagnosis and Treatment of Hepatocellular Carcinoma. Seminars in Diagnostic Pathology, 34, 153-159. [Google Scholar] [CrossRef] [PubMed]
[18] Wallace, M.C., et al. (2015) The Evolving Epidemiology of Hepatocellular Carcinoma: A Global Perspective. Expert Review of Gastroenterology & Hepatology, 9, 765-779. [Google Scholar] [CrossRef] [PubMed]
[19] Xu, X., et al. (2016) Global Proteomic Profiling in Multistep Hepatocarcinogenesis and Identification of PARP1 as a Novel Molecular Marker in Hepatocellular Carcinoma. Oncotar-get, 7, 13730-13741. [Google Scholar] [CrossRef] [PubMed]
[20] Klingenberg, M., et al. (2017) Non-Coding RNA in Hepatocellular Carcinoma: Mechanisms, Biomarkers and Therapeutic Targets. Journal of Hepatology, 67, 603-618. [Google Scholar] [CrossRef] [PubMed]
[21] Qiu, L., et al. (2019) Circular RNAs in Hepatocellular Carcinoma: Biomarkers, Functions and Mechanisms. Life Sciences, 231, Article ID: 116660. [Google Scholar] [CrossRef] [PubMed]
[22] Xu, W., et al. (2018) Identification of Biomarkers for Barcelona Clinic Liver Cancer Staging and Overall Survival of Patients with Hepatocellular Carcinoma. PLOS ONE, 13, e0202763. [Google Scholar] [CrossRef] [PubMed]
[23] Scartozzi, M., et al. (2014) VEGF and VEGFR Genotyping in the Prediction of Clinical Outcome for HCC Patients Receiving Sorafenib: The ALICE-1 Study. International Journal of Cancer, 135, 1247-1256. [Google Scholar] [CrossRef] [PubMed]
[24] Bharadwaj, M., et al. (2013) Tackling Hepatitis B Virus-Associated Hepato-cellular Carcinoma—The Future Is Now. Cancer and Metastasis Reviews, 32, 229-268. [Google Scholar] [CrossRef] [PubMed]
[25] Fabregat, I., et al. (2016) TGF-Beta Signalling and Liver Disease. FEBS Journal, 283, 2219-2232. [Google Scholar] [CrossRef] [PubMed]
[26] Yamada, D., et al. (2013) Role of Crosstalk between Interleukin-6 and Transforming Growth Factor-Beta 1 in Epithelial-Mesenchymal Transition and Chemoresistance in Biliary Tract Cancer. European Journal of Cancer, 49, 1725-1740. [Google Scholar] [CrossRef] [PubMed]
[27] Abulaiti, A., et al. (2013) Interaction between Non-Small-Cell Lung Cancer Cells and Fibroblasts via Enhancement of TGF-Beta Signaling by IL-6. Lung Cancer, 82, 204-213. [Google Scholar] [CrossRef] [PubMed]
[28] Yan, W., et al. (2015) Tim-3 Fosters HCC Development by Enhancing TGF-Beta-Mediated Alternative Activation of Macrophages. Gut, 64, 1593-1604. [Google Scholar] [CrossRef] [PubMed]
[29] Tortelote, G.G., et al. (2017) Complexity of the Wnt/Betacatenin Pathway: Searching for an Activation Model. Cell Signal, 40, 30-43. [Google Scholar] [CrossRef] [PubMed]
[30] Langeswaran, K., et al. (2013) Influence of Limonin on Wnt Signalling Molecule in HepG2 Cell Lines. Journal of Natural Science, Biology and Medicine, 4, 126-133. [Google Scholar] [CrossRef] [PubMed]
[31] Pez, F., et al. (2013) Wnt Signaling and Hepatocarcinogenesis: Molecular Targets for the Development of Innovative Anticancer Drugs. Journal of Hepatology, 59, 1107-1117. [Google Scholar] [CrossRef] [PubMed]
[32] Tsao, C.M., et al. (2012) SOX1 Functions as a Tumor Suppressor by Antagonizing the WNT/Beta-Catenin Signaling Pathway in Hepatocellular Carcinoma. Hepatology, 56, 2277-2287. [Google Scholar] [CrossRef] [PubMed]
[33] Johnson, S.D., De Costa, A.M. and Young, M.R. (2014) Effect of the Premalignant and Tumor Microenvironment on Immune Cell Cytokine Production in Head and Neck Cancer. Cancers (Basel), 6, 756-770. [Google Scholar] [CrossRef] [PubMed]
[34] Xue, Y., et al. (2019) Tumorinfiltrating M2 Macrophages Driven by Specific Genomic Alterations Are Associated with Prognosis in Bladder Cancer. Oncology Reports, 42, 581-594. [Google Scholar] [CrossRef] [PubMed]
[35] Gordon, S. and Martinez, F.O. (2010) Alternative Activation of Macro-phages: Mechanism and Functions. Immunity, 32, 593-604. [Google Scholar] [CrossRef] [PubMed]
[36] Martinez, F.O., Helming, L. and Gordon, S. (2009) Alternative Activation of Macrophages: An Immunologic Functional Perspective. Annual Review of Immunology, 27, 451-483. [Google Scholar] [CrossRef] [PubMed]
[37] Leblond, M.M., et al. (2017) M2 Macrophages Are More Resistant than M1 Macrophages Following Radiation Therapy in the Context of Glioblastoma. Oncotarget, 8, 72597-72612. [Google Scholar] [CrossRef] [PubMed]
[38] Hanagiri, T., et al. (2012) Antitumor Activity of Human Gammadelta T Cells Transducted with CD8 and with T-Cell Receptors of tumor-Specific Cytotoxic T Lympho-cytes. Cancer Science, 103, 1414-1419. [Google Scholar] [CrossRef] [PubMed]
[39] Schuster, S.J., et al. (2017) Chimeric Antigen Receptor T Cells in Refractory B-Cell Lymphomas. The New England Journal of Medicine, 377, 2545-2554. [Google Scholar] [CrossRef
[40] Chiossone, L., et al. (2018) Natural Killer Cells and Other Innate Lymphoid Cells in Cancer. Nature Reviews Immunology, 18, 671-688. [Google Scholar] [CrossRef] [PubMed]
[41] Streltsova, M.A., et al. (2018) Current Approaches to Engineering of NK Cells for Cancer Immunotherapy. Current Pharmaceutical Design, 24, 2810-2824. [Google Scholar] [CrossRef] [PubMed]
[42] Derakhshani, A., et al. (2019) Mast Cells: A Dou-ble-Edged Sword in Cancer. Immunology Letters, 209, 28-35. [Google Scholar] [CrossRef] [PubMed]
[43] El-Galaly, T.C., et al. (2020) Potentials, Challenges and Future of Chimeric Antigen Receptor T-Cell Therapy in Non-Hodgkin Lymphomas. Acta Oncologica, 59, 766-774. [Google Scholar] [CrossRef