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一种在胃癌样本中得到验证的焦亡相关长链非编码RNA的预后特征,用于预测免疫治疗和化疗药物敏感性。

A prognostic signature of pyroptosis-related lncRNAs verified in gastric cancer samples to predict the immunotherapy and chemotherapy drug sensitivity.

作者信息

Wang Yanan, Chen Xiaowei, Jiang Fei, Shen Yan, Fang Fujin, Li Qiong, Yang Chuanli, Dong Yu, Shen Xiaobing

机构信息

Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China.

Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, Nanjing, China.

出版信息

Front Genet. 2022 Sep 6;13:939439. doi: 10.3389/fgene.2022.939439. eCollection 2022.

Abstract

Pyroptosis is a recently identified mode of programmed inflammatory cell death that has remarkable implications for cancer development. lncRNAs can be involved in cellular regulation through various pathways and play a critical role in gastric cancer (GC). However, pyroptosis -related lncRNAs (PRlncRNAs) have been rarely studied in GC. Pyroptosis-related gene were abstracted from the literature and GSEA Molecular Signatures data resource. PRlncRNAs were obtained using co-expression analysis. LASSO Cox regression assessment was employed to build a risk model. Kaplan-Meier (KM), univariate along with multivariate Cox regression analysis were adopted to verify the predictive efficiency of the risk model in terms of prognosis. qRT-PCR was adopted to validate the expression of PRlncRNAs in GC tissues. In addition, immune cell infiltration assessment and ESTIMATE score evaluation were adopted for assessing the relationship of the risk model with the tumor immune microenvironment (TME). Finally, immune checkpoint gene association analysis and chemotherapy drug sensitivity analysis were implemented to assess the worthiness of our risk model in immunotherapy and chemotherapy of GC. We identified 3 key PRlncRNAs (PVT1, CYMP-AS1 and AC017076.1) and testified the difference of their expression levels in GC tumor tissues and neighboring non-malignant tissues ( < 0.05). PRlncRNAs risk model was able to successfully estimate the prognosis of GC patients, and lower rate of survival was seen in the high-GC risk group relative to the low-GC risk group ( < 0.001). Other digestive system tumors such as pancreatic cancer further validated our risk model. There was a dramatic difference in TMB level between high-GC and low-GC risk groups ( < 0.001). Immune cell infiltration analysis and ESTIMATE score evaluation demonstrated that the risk model can be adopted as an indicator of TME status. Besides, the expressions of immunodetection site genes in different risk groups were remarkably different (CTLA-4 (r = -0.14, = 0.010), VISTA (r = 0.15, = 0.005), and B7-H3 (r = 0.14, = 0.009)). PRlncRNAs risk model was able to effectively establish a connection with the sensitivity of chemotherapeutic agents. The 3 PRlncRNAs identified in this study could be utilized to predict disease outcome in GC patients. It may also be a potential therapeutic target in GC therapy, including immunotherapy and chemotherapy.

摘要

细胞焦亡是最近发现的一种程序性炎症细胞死亡模式,对癌症发展具有重要意义。长链非编码RNA(lncRNAs)可通过多种途径参与细胞调控,并在胃癌(GC)中发挥关键作用。然而,与细胞焦亡相关的lncRNAs(PRlncRNAs)在GC中的研究很少。从文献和GSEA分子特征数据资源中提取与细胞焦亡相关的基因。使用共表达分析获得PRlncRNAs。采用LASSO Cox回归评估建立风险模型。采用Kaplan-Meier(KM)法、单因素和多因素Cox回归分析来验证风险模型在预后方面的预测效率。采用qRT-PCR验证PRlncRNAs在GC组织中的表达。此外,采用免疫细胞浸润评估和ESTIMATE评分评估来评估风险模型与肿瘤免疫微环境(TME)的关系。最后,进行免疫检查点基因关联分析和化疗药物敏感性分析,以评估我们的风险模型在GC免疫治疗和化疗中的价值。我们鉴定出3个关键的PRlncRNAs(PVT1、CYMP-AS1和AC017076.1),并证实了它们在GC肿瘤组织和邻近非恶性组织中的表达水平存在差异(<0.05)。PRlncRNAs风险模型能够成功预测GC患者的预后,高GC风险组的生存率低于低GC风险组(<0.001)。其他消化系统肿瘤如胰腺癌进一步验证了我们的风险模型。高GC风险组和低GC风险组之间的肿瘤突变负荷(TMB)水平存在显著差异(<0.001)。免疫细胞浸润分析和ESTIMATE评分评估表明,该风险模型可作为TME状态的指标。此外,不同风险组中免疫检测位点基因的表达存在显著差异(CTLA-4(r = -0.14,P = 0.010)、VISTA(r = 0.15,P = 0.005)和B7-H3(r = 0.14,P = 0.009))。PRlncRNAs风险模型能够有效地建立与化疗药物敏感性的联系。本研究中鉴定出的3个PRlncRNAs可用于预测GC患者的疾病转归。它也可能是GC治疗(包括免疫治疗和化疗)中的一个潜在治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/285f/9485603/143a9fe7950d/fgene-13-939439-g001.jpg

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