一种新型肾透明细胞癌焦亡相关基因预后风险模型的建立和验证

doi:10.16098/j.issn.0529-1356.2022.05.012

摘要/Abstract

摘要：

目的建立一种新型肾透明细胞癌焦亡相关基因风险模型。方法从癌症基因组图谱(TCGA)数据库、基因型组织表达(GTEx)数据库分别下载了522例肾透明细胞癌(KIRC)患者和72例正常组织样本。对TCGA和GTEx的数据进行差异分析，采用单因素和多因素COX回归分析以及LASSO Cox回归分析构建基因风险模型。使用国际癌症基因组联盟 (ICGC)数据作为外部验证数据集。对TCGA_KIRC队列的高、低风险组进行基因本体论(GO)富集分析与京都基因与基因组百科全书(KEGG)通路富集分析，探讨高、低风险组之间基因功能和通路的差异。利用CIBERSORT数据库探讨高、低风险组的免疫浸润情况。结果通过差异分析，得到13个差异表达的焦亡相关基因。采用单因素、多因素和LASSO Cox回归分析构建1个6基因风险模型。Kaplan-Meier分析结果显示，两个队列中高风险组生存时间均短于低风险组。在TCGA_KIRC队列中，1、2、3年曲线下面积(AUC)分别为0.710、0.683和0.727。在ICGC_RECA队列中，1、2、3年曲线下面积为0.592、0.531和0.545。独立预后分析显示，风险分数是1个独立预后因素。GO功能富集分析和KEGG通路富集分析结果表明，其主要与免疫和炎症反应相关。肿瘤的免疫浸润结果表明，高风险组中CD4+T细胞调节性T细胞、自然杀伤细胞、单核细胞、M2巨噬细胞和嗜酸性粒细胞浸润水平低，B细胞、CD8⁺T细胞、滤泡辅助性T细胞浸润水平高。结论细胞焦亡相关基因可能在KIRC肿瘤免疫中发挥重要作用，联合与细胞焦亡相关的6基因风险模型可以为KIRC患者的个性化治疗方案提供预测依据。

关键词: 肾透明细胞癌, 免疫浸润, 预后, LASSO Cox回归分析, 人

Abstract:

Objective To establish a novel defined pyroptosis-related genes risk model of kidney renal clear cell carcinoma. Methods Data of 522 patients with KIRC and 72 normal tissue samples were respectively downloaded from the Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) database. Differential analysis was performed between data of TCGA and GTEx. Univariate Cox regression analysis, multivariate Cox regression analyses and LASSO Cox regression analysis were used to establish a prognostic risk model. Data from the International Cancer Genome Consortium (ICGC) database was used as an external validation cohort. Gene ontology (GO) enrichment analysis and Kyoto Encylopedia of Genes and Genomes (KEGG) pathway analysis were used to explore the differences of gene functions and pathways between high-risk and low-risk groups. The CIBERSORT database was used to explore the immune infiltration of high-risk and low-risk groups. Results Through differential analysis, we obtained 13 differentially expressed pyroptosis-related genes. Univariate Cox regression analysis, multivariable Cox regression analyses and LASSO Cox regression analysis were used to establish a 6-gene risk model. Kaplan-Meier analysis indicated that survival time in high-risk group was shorter than low-risk group in both cohorts. The area under the curve (AUC) was 0.710 for 1-year, 0.683 for 2-year, and 0.727 for 3-year survival in the TCGA_KIRC cohort. The AUC was 0.592 for 1-year, 0.531 for 2-year, and 0.545 for 3-year survival in the ICGC_RECA cohort. Independent prognostic analysis indicated that risk score was an independent prognostic factor. GO enrichment analysis and KEGG pathway analysis showed that it was mainly associated with immune and inflammatory responses. The result of tumor immune infiltration showed that the high-risk group had low infiltration levels of regulatory T cells , natural killer cells, monocytes, M2 macrophages and eosinophils and igh infiltration level of B cells, CD8⁺T cells and follicular helper T cells. Conclusion Pyrolysis-related genes may play an important role in KIRC tumor immunity, and the 6-gene risk model can provide a forecast basis for personalized treatment of patients with KIRC.

Key words: Kidney renal clear cell carcinoma, Immune infiltration, Prognosis, LASSO Cox regression analysis, Human

中图分类号:

R730.1

王万里任伟南赵千石贞玉厉永强. 一种新型肾透明细胞癌焦亡相关基因预后风险模型的建立和验证[J]. 解剖学报, 2022, 53(5): 620-627.

WANG Wan-li REN Wei-nan ZHAO Qian SHI Zhen-yu LI Yong-qiang . A novel defined pyroptosis-related genes prognostic risk model for predicting the prognosis of kidney renal clear cell carcinoma#br#

#br#

[J]. Acta Anatomica Sinica, 2022, 53(5): 620-627.

参考文献

[1]. Siegel, R.L., K.D. Miller, and A. Jemal, Cancer statistics, 2018. CA Cancer J Clin, 2018. 68(1): p. 7-30.
[2]. Bhatt, J.R. and A. Finelli, Landmarks in the diagnosis and treatment of renal cell carcinoma. Nat Rev Urol, 2014. 11(9): p. 517-25.
[3]. Kovacs, G., et al., The Heidelberg classification of renal cell tumours. J Pathol, 1997. 183(2): p. 131-3.
[4]. Shuch, B., et al., Understanding pathologic variants of renal cell carcinoma: distilling therapeutic opportunities from biologic complexity. Eur Urol, 2015. 67(1): p. 85-97.
[5]. Makhov, P., et al., Resistance to Systemic Therapies in Clear Cell Renal Cell Carcinoma: Mechanisms and Management Strategies. Mol Cancer Ther, 2018. 17(7): p. 1355-1364.
[6]. Kovacs, S.B. and E.A. Miao, Gasdermins: Effectors of Pyroptosis. Trends Cell Biol, 2017. 27(9): p. 673-684.
[7]. 王熹芝, et al., 炎症反应在细胞焦亡和动脉粥样硬化之间的作用 [J] .解剖学报, 2019. 50(04): p. 543-548.
[8]. Frank, D. and J.E. Vince, Pyroptosis versus necroptosis: similarities, differences, and crosstalk. Cell Death Differ, 2019. 26(1): p. 99-114.
[9]. Ding, J., et al., Pore-forming activity and structural autoinhibition of the gasdermin family. Nature, 2016. 535(7610): p. 111-6.
[10]. Xia, X., et al., The role of pyroptosis in cancer: pro-cancer or pro-"host"? Cell Death Dis, 2019. 10(9): p. 650.
[11]. Li, L., Y. Li, and Y. Bai, Role of GSDMB in Pyroptosis and Cancer. Cancer Manag Res, 2020. 12: p. 3033-3043.
[12]. Burgener, S.S., et al., Cathepsin G Inhibition by Serpinb1 and Serpinb6 Prevents Programmed Necrosis in Neutrophils and Monocytes and Reduces GSDMD-Driven Inflammation. Cell Rep, 2019. 27(12): p. 3646-3656.e5.
[13]. Panganiban, R.A., et al., A functional splice variant associated with decreased asthma risk abolishes the ability of gasdermin B to induce epithelial cell pyroptosis. J Allergy Clin Immunol, 2018. 142(5): p. 1469-1478.e2.
[14]. Chen, Q., et al., GSDMB promotes non-canonical pyroptosis by enhancing caspase-4 activity. J Mol Cell Biol, 2019. 11(6): p. 496-508.
[15]. Garcia, J., N. Callewaert, and L. Borsig, P-selectin mediates metastatic progression through binding to sulfatides on tumor cells. Glycobiology, 2007. 17(2): p. 185-96.
[16]. Feng, S., D. Fox, and S.M. Man, Mechanisms of Gasdermin Family Members in Inflammasome Signaling and Cell Death. J Mol Biol, 2018. 430(18 Pt B): p. 3068-3080.
[17]. Hergueta-Redondo, M., et al., Gasdermin B expression predicts poor clinical outcome in HER2-positive breast cancer. Oncotarget, 2016. 7(35): p. 56295-56308.
[18]. Kim, L.H., et al., Genetic variants of the gasdermin B gene associated with the development of aspirin-exacerbated respiratory diseases. Allergy Asthma Proc, 2017. 38(1): p. 4-12.
[19]. S?derman, J., L. Berglind, and S. Almer, Gene Expression-Genotype Analysis Implicates GSDMA, GSDMB, and LRRC3C as Contributors to Inflammatory Bowel Disease Susceptibility. Biomed Res Int, 2015. 2015: p. 834805.
[20]. Chu, A.Y., et al., Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation. Nat Genet, 2017. 49(1): p. 125-130.
[21]. Levy, M., et al., NLRP6: A Multifaceted Innate Immune Sensor. Trends Immunol, 2017. 38(4): p. 248-260.
[22]. Shen, C., et al., Molecular mechanism for NLRP6 inflammasome assembly and activation. Proc Natl Acad Sci U S A, 2019. 116(6): p. 2052-2057.
[23]. Elliott, E.I. and F.S. Sutterwala, Initiation and perpetuation of NLRP3 inflammasome activation and assembly. Immunol Rev, 2015. 265(1): p. 35-52.
[24]. Elinav, E., et al., NLRP6 inflammasome regulates colonic microbial ecology and risk for colitis. Cell, 2011. 145(5): p. 745-57.
[25]. Anand, P.K., et al., NLRP6 negatively regulates innate immunity and host defence against bacterial pathogens. Nature, 2012. 488(7411): p. 389-93.
[26]. Nambayan, R.J.T., et al., The inflammasome adapter ASC assembles into filaments with integral participation of its two Death Domains, PYD and CARD. J Biol Chem, 2019. 294(2): p. 439-452.
[27]. McConnell, B.B. and P.M. Vertino, Activation of a caspase-9-mediated apoptotic pathway by subcellular redistribution of the novel caspase recruitment domain protein TMS1. Cancer Res, 2000. 60(22): p. 6243-7.
[28]. Mohamed, R.A., et al., Palonosetron/Methyllycaconitine Deactivate Hippocampal Microglia 1, Inflammasome Assembly and Pyroptosis to Enhance Cognition in a Novel Model of Neuroinflammation. Molecules, 2021. 26(16).
[29]. Tzeng, T.C., et al., Inflammasome-derived cytokine IL18 suppresses amyloid-induced seizures in Alzheimer-prone mice. Proc Natl Acad Sci U S A, 2018. 115(36): p. 9002-9007.
[30]. Xiong, W., X.F. Meng, and C. Zhang, NLRP3 Inflammasome in Metabolic-Associated Kidney Diseases: An Update. Front Immunol, 2021. 12: p. 714340.
[31]. Lugrin, J. and F. Martinon, The AIM2 inflammasome: Sensor of pathogens and cellular perturbations. Immunol Rev, 2018. 281(1): p. 99-114.
[32]. Man, S.M., R. Karki, and T.D. Kanneganti, AIM2 inflammasome in infection, cancer, and autoimmunity: Role in DNA sensing, inflammation, and innate immunity. Eur J Immunol, 2016. 46(2): p. 269-80.
[33]. Wang, B., et al., Immunobiology and structural biology of AIM2 inflammasome. Mol Aspects Med, 2020. 76: p. 100869.
[34]. Sharma, B.R., R. Karki, and T.D. Kanneganti, Role of AIM2 inflammasome in inflammatory diseases, cancer and infection. Eur J Immunol, 2019. 49(11): p. 1998-2011.
[35]. Ekabe, C.J., et al., The Role of Inflammasome Activation in Early HIV Infection. J Immunol Res, 2021. 2021: p. 1487287.
[36]. Ogura, Y., et al., Nod2, a Nod1/Apaf-1 family member that is restricted to monocytes and activates NF-kappaB. J Biol Chem, 2001. 276(7): p. 4812-8.
[37]. Butera, A., et al., Nod2 Deficiency in mice is Associated with Microbiota Variation Favouring the Expansion of mucosal CD4+ LAP+ Regulatory Cells. Sci Rep, 2018. 8(1): p. 14241.
[38]. Sorbara, M.T., et al., The protein ATG16L1 suppresses inflammatory cytokines induced by the intracellular sensors Nod1 and Nod2 in an autophagy-independent manner. Immunity, 2013. 39(5): p. 858-73.
[39]. Cooney, R., et al., NOD2 stimulation induces autophagy in dendritic cells influencing bacterial handling and antigen presentation. Nat Med, 2010. 16(1): p. 90-7.
[40]. Caruso, R. and G. Nú?ez, Innate Immunity: ER Stress Recruits NOD1 and NOD2 for Delivery of Inflammation. Curr Biol, 2016. 26(12): p. R508-r511.
[41]. Adams, C.J., et al., Structure and Molecular Mechanism of ER Stress Signaling by the Unfolded Protein Response Signal Activator IRE1. Front Mol Biosci, 2019. 6: p. 11.
[42]. Zangara, M.T., et al., Mediators of Metabolism: An Unconventional Role for NOD1 and NOD2. Int J Mol Sci, 2021. 22(3).
[43]. Jacob, F., S. Vernaldi, and T. Maekawa, Evolution and Conservation of Plant NLR Functions. Front Immunol, 2013. 4: p. 297.
[44]. Kobayashi, K.S., et al., Nod2-dependent regulation of innate and adaptive immunity in the intestinal tract. Science, 2005. 307(5710): p. 731-4.
[45]. Xu, D., et al., NOD2 maybe a biomarker for the survival of kidney cancer patients. Oncotarget, 2017. 8(60): p. 101489-101499.