非常规 T 细胞在泌尿系统肿瘤中:能抓住就抓住
Unconventional T cells in urological cancers: catch them if you can.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA.
Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA.
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TIL(肿瘤浸润淋巴细胞)是一类具有重要免疫功能的细胞,在膀胱癌(BCa)中发挥着至关重要的作用。多项研究已表明TIL在预测预后和免疫治疗疗效方面具有临床意义。利用加权基因共表达网络分析筛选TIL相关基因模块。
我们利用单因素Cox回归分析、最小绝对收缩和选择算子(LASSO)Cox回归分析以及多因素Cox回归分析筛选出八个TIL相关基因。随后,我们建立了一个包含这八个选定基因的TIL相关特征模型,并将所有患者分为两组,即高风险组和低风险组。在不同风险亚组之间评估了基因突变状态、预后、免疫细胞浸润、免疫亚型、TME、临床特征和免疫治疗反应。结果证实,TIL相关特征模型是BCa总生存期(OS)的可靠预测因子,并在两个队列中被确定为BCa患者的独立危险因素。
此外,风险评分与年龄、肿瘤分期、TNM分期和病理分级显著相关。两个风险组之间在肿瘤微环境(TME)中具有不同的突变谱、生物学通路、免疫评分、基质评分和免疫细胞浸润。特别是,免疫检查点基因的表达在两个风险组之间显著不同,低风险组患者对免疫检查点抑制(ICI)治疗反应更好。
总之,我们的研究表明,TIL相关模型是预测预后、免疫状态和免疫治疗反应的可靠特征,有助于筛选对免疫治疗有反应的患者。
Tumor-infiltrating lymphocyte (TIL) is a class of cells with important immune functions and plays a crucial role in bladder cancer (BCa). Several studies have shown the clinical significance of TIL in predicting the prognosis and immunotherapy efficacy. TIL-related gene module was screened utilizing weighted gene coexpression network analysis.
We screened eight TIL-related genes utilizing univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) Cox regression analysis, and multivariate Cox regression analysis. Then, we established a TIL-related signature model containing the eight selected genes and subsequently classified all patients into two groups, that is, the high-risk as well as low-risk groups.
Gene mutation status, prognosis, immune cell infiltration, immune subtypes, TME, clinical features, and immunotherapy response were assessed among different risk subgroups. The results affirmed that the TIL-related signature model was a reliable predictor of overall survival (OS) for BCa and was determined as an independent risk factor for BCa patients in two cohorts.
Moreover, the risk score was substantially linked to age, tumor staging, TNM stage, and pathological grade. And there were different mutational profiles, biological pathways, immune scores, stromal scores, and immune cell infiltration in the tumor microenvironment (TME) between the two risk groups. In particular, immune checkpoint genes' expression was remarkably different between the two risk groups, with patients belonging to the low-risk group responding better to immune checkpoint inhibition (ICI) therapy.
In conclusion, our study demonstrates that the TIL-related model was a reliable signature in anticipating prognosis, immune status, and immunotherapy response, which can help in screening patients who respond to immunotherapy.
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