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一种用于预测肌层浸润性膀胱癌(MIBC)患者预后和免疫治疗反应的免疫相关特征。

An immune relevant signature for predicting prognoses and immunotherapeutic responses in patients with muscle-invasive bladder cancer (MIBC).

作者信息

Jiang Wen, Zhu Dandan, Wang Chenghe, Zhu Yu

机构信息

Department of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

出版信息

Cancer Med. 2020 Apr;9(8):2774-2790. doi: 10.1002/cam4.2942. Epub 2020 Feb 25.

Abstract

Immune checkpoint inhibitors (ICIs) are novel treatments that significantly improve the survival time of MIBC patients, but immunotherapeutic responses are different among MIBC patients. Therefore, it is urgent to find predictive biomarkers that can accurately identify MIBC patients who are sensitive to ICIs. In this study, we computed the relative abundances of 24 immune cells based on the expression profiles of MIBC patients using single-sample gene set enrichment analysis (ssGSEA). Unsupervised clustering analysis of the 24 immune cells was performed to classify MIBC patients into different immune-infiltrating groups. Genome (gene mutation and copy number variation), transcriptome (mRNA, lncRNA, and miRNA), and functional enrichment were found to be heterogeneous among different immune-infiltrating groups. We identified 282 differentially expressed genes (DEGs) associated with immune infiltration by comparing the expression profiles of patients with different immune infiltration profiles, and 20 core prognostic DEGs were identified by univariate Cox regression analysis. An immune-relevant gene signature (TIM signature) consisting of nine key prognostic DEGs (CCDC80, CD3D, CIITA, FN1, GBP4, GNLY, SPINK1, UBD, and VIM) was constructed using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Receiver operating characteristic (ROC) curves and subgroup analysis confirmed that the TIM signature was an ideal biomarker for predicting the prognosis of MIBC patients. Its value in predicting immunotherapeutic responses was also validated in The Cancer Genome Atlas (TCGA) cohort (AUC = 0.69, 95% CI = 0.63-0.74) and the IMvigor210 cohort (AUC = 0.64, 95% = 0.55-0.74). The TIM signature demonstrates a powerful ability to distinguish MIBC patients with different prognoses and immunotherapeutic responses, but more prospective studies are needed to assess its reliability in the future.

摘要

免疫检查点抑制剂(ICIs)是显著延长肌层浸润性膀胱癌(MIBC)患者生存时间的新型治疗方法,但MIBC患者的免疫治疗反应存在差异。因此,迫切需要找到能够准确识别对ICIs敏感的MIBC患者的预测性生物标志物。在本研究中,我们使用单样本基因集富集分析(ssGSEA),根据MIBC患者的表达谱计算了24种免疫细胞的相对丰度。对这24种免疫细胞进行无监督聚类分析,将MIBC患者分为不同的免疫浸润组。发现不同免疫浸润组之间的基因组(基因突变和拷贝数变异)、转录组(mRNA、lncRNA和miRNA)以及功能富集存在异质性。通过比较不同免疫浸润谱患者的表达谱,我们鉴定出282个与免疫浸润相关的差异表达基因(DEGs),并通过单变量Cox回归分析确定了20个核心预后DEGs。使用最小绝对收缩和选择算子(LASSO)Cox回归分析构建了由9个关键预后DEGs(CCDC80、CD3D、CIITA、FN1、GBP4、GNLY、SPINK1、UBD和VIM)组成的免疫相关基因特征(TIM特征)。受试者工作特征(ROC)曲线和亚组分析证实,TIM特征是预测MIBC患者预后的理想生物标志物。其在预测免疫治疗反应方面的价值也在癌症基因组图谱(TCGA)队列(AUC = 0.69,95%CI = 0.63 - 0.74)和IMvigor210队列(AUC = 0.64,95% = 0.55 - 0.74)中得到验证。TIM特征显示出强大的区分不同预后和免疫治疗反应的MIBC患者的能力,但未来还需要更多的前瞻性研究来评估其可靠性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93b4/7163112/dec8f2e766a0/CAM4-9-2774-g001.jpg

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