Predicting Prognosis and Distinguishing Cold and Hot Tumors in Bladder Urothelial Carcinoma Based on Necroptosis-Associated lncRNAs.
Predicting Prognosis and Distinguishing Cold and Hot Tumors in Bladder Urothelial Carcinoma Based on Necroptosis-Associated lncRNAs.
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DOI：
10.3389/fimmu.2022.916800
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发表时间：
2022
影响因子：
7.3
通讯作者：
中科院分区：
文献类型：
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作者：
根据先前的研究，坏死性凋亡在癌症发展中起着重要作用。我们的团队决定探索与膀胱尿路上皮癌（BLCA）中坏死性凋亡相关的长链非编码RNA（lncRNA）的潜在预后价值及其与肿瘤微环境（TME）和精确剂量的免疫应答的关系。为获得所需数据，从癌症基因组图谱（TCGA）中检索膀胱尿路上皮癌转录组数据（）。我们使用共表达分析、差异表达分析和单变量考克斯回归来筛选与BLCA中坏死性凋亡相关的预后性lncRNA。然后采用最小绝对收缩选择算子（LASSO）构建坏死性凋亡相关lncRNA模型。基于此模型，我们还进行了Kaplan-Meier分析和时间依赖的受试者工作特征（ROC）来估计风险评分的预后能力。进行多因素和单因素考克斯回归分析，建立列线图。校正曲线和时间依赖的ROC也被用来评估诺模图。主成分分析（PCA）揭示了高风险和低风险群体之间的差异。此外，我们还对构建的模型进行了免疫分析、基因集富集分析（GSEA）和半数抑制浓度（IC 50）评价。最后，基于坏死性凋亡相关lncRNA模型将整个样品分为三个簇，以进一步比较冷肿瘤和热肿瘤中的免疫治疗。基于坏死性凋亡相关lncRNA建立模型。该模型显示了良好的一致性之间的校准图和预后预测。1年、3年和5年OS的ROC曲线下面积（AUC）分别为0.707、0.679和0.675。风险组可能有助于全身治疗，因为风险组之间的IC 50显著不同。令人高兴的是，集群可以有效地识别冷肿瘤和热肿瘤，这将有利于准确的调解。第2、3组为热瘤，对免疫抑制药物敏感。结果提示，necroposis-associated lncRNAs可有效预测BLCA患者的预后，有助于区分肿瘤的冷热，提高BLCA的个体化治疗水平。
In reference to previous studies, necroptosis played an important role in cancer development. Our team decided to explore the potential prognostic values of long non-coding RNAs (lncRNAs) associated with necroptosis in bladder urothelial carcinoma (BLCA) and their relationship with the tumor microenvironment (TME) and the immunotherapeutic response for accurate dose. To obtain the required data, bladder urothelial carcinoma transcriptome data were searched from Cancer Genome Atlas (TCGA) (). We used co-expression analysis, differential expression analysis, and univariate Cox regression to screen out prognostic lncRNAs associated with necroptosis in BLCA. Then the least absolute shrinkage and selection operator (LASSO) was conducted to construct the necroptosis-associated lncRNAs model. Based on this model, we also performed the Kaplan–Meier analysis and time-dependent receiver operating characteristics (ROC) to estimate the prognostic power of risk score. Multivariate and univariate Cox regression analysis were performed to build up a nomogram. Calibration curves, and time-dependent ROC were also conducted to evaluate nomogram. Principal component analysis (PCA) revealed a difference between high- and low-risk groups. In addition, we explored immune analysis, gene set enrichment analyses (GSEA), and evaluation of the half-maximal inhibitory concentration (IC50) in constructed model. Finally, the entire samples were divided into three clusters based on model of necroptosis-associated lncRNAs to further compare immunotherapy in cold and hot tumors. A model was built up based on necroptosis-associated lncRNAs. The model revealed good consistence between calibration plots and prognostic prediction. The area of 1-, 3-, and 5-year OS under the ROC curve (AUC) were 0.707, 0.679, and 0.675. Risk groups could be helpful for systemic therapy due to the markedly diverse IC50 between risk groups. To our delight, clusters could effectively identify cold and hot tumors, which would be beneficial to accurate mediation. Clusters 2 and 3 were considered the hot tumor, which was more sensitive to immunotherapeutic drugs. The outcomes of our study suggested that necroptosis-associated lncRNAs could effectively predict patients with BLCA prognosis, which may be helpful for distinguishing the cold and hot tumors and improving individual treatment of BLCA.
影响因子：
3.7
作者：
Zhang L;Zhang H;Li L;Xiao Y;Rao E;Miao Z;Chen H;Sun L;Li H;Liu G;Zhao Y
通讯作者：
Zhao Y