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通过多组学分析和实验验证鉴定预测膀胱癌癌症免疫治疗反应的肿瘤特异性T细胞特征

Identification of tumor-specific T cell signature predicting cancer immunotherapy response in bladder cancer by multi-omics analysis and experimental verification.

作者信息

Liu Xiufeng, Chen Chujun, Li Jiashan, Li Linna, Ma Meng

机构信息

State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510080, People's Republic of China.

Key Specialty of Clinical Pharmacy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, 510080, People's Republic of China.

出版信息

Cancer Cell Int. 2024 Jul 20;24(1):255. doi: 10.1186/s12935-024-03447-6.

Abstract

BACKGROUND

Numerous gene signatures predicting the prognosis of bladder cancer have been identified. However, a tumor-specific T cell signature related to immunotherapy response in bladder cancer remains under investigation.

METHODS

Single-cell RNA and TCR sequencing from the Gene expression omnibus (GEO) database were used to identify tumor-specific T cell-related genes in bladder cancer. Subsequently, we constructed a tumor-specific T cell signature (TstcSig) and validated its clinical relevance for predicting immunotherapy response in multiple immunotherapy cohorts. Further analyses explored the immune characteristics of TstcSig in bladder cancer patients from other cohorts in the TCGA and GEO databases. Western blot (WB), multicolor immunofluorescence (MIF), qRT-PCR and flow cytometry assays were performed to validate the results of bioinformatics analysis.

RESULTS

The established TstcSig, based on five tumor-specific T cell-related genes, could predict outcomes in a bladder cancer immunotherapy cohort. This was verified using two additional immunotherapy cohorts and showed better predictive performance compared to 109 published T cell signatures. TstcSig was strongly correlated with immune characteristics such as immune checkpoint gene expression, tumor mutation burden, and T cell infiltration, as validated by single-cell and spatial transcriptomics datasets. Notably, the positive correlation between TstcSig and T cell infiltration was confirmed in the TCGA cohort. Furthermore, pan-cancer analysis demonstrated the heterogeneity of the prognostic value of TstcSig. Tumor-specific T cells highly expressed CD27, IFNG, GZMB and CXCL13 and secreted more effector cytokines for tumor cell killing, as validated experimentally.

CONCLUSION

We developed a five-gene signature (including VAMP5, TIGIT, LCK, CD27 and CACYBP) based on tumor-specific T cell-related genes to predict the immunotherapy response in bladder cancer patients.

摘要

背景

已鉴定出许多预测膀胱癌预后的基因特征。然而,与膀胱癌免疫治疗反应相关的肿瘤特异性T细胞特征仍在研究中。

方法

利用来自基因表达综合数据库(GEO)的单细胞RNA和TCR测序来鉴定膀胱癌中肿瘤特异性T细胞相关基因。随后,我们构建了一个肿瘤特异性T细胞特征(TstcSig),并在多个免疫治疗队列中验证了其预测免疫治疗反应的临床相关性。进一步的分析探讨了TCGA和GEO数据库中其他队列的膀胱癌患者中TstcSig的免疫特征。进行了蛋白质免疫印迹(WB)、多色免疫荧光(MIF)、qRT-PCR和流式细胞术检测以验证生物信息学分析结果。

结果

基于五个肿瘤特异性T细胞相关基因建立的TstcSig可以预测膀胱癌免疫治疗队列的结果。使用另外两个免疫治疗队列验证了这一点,并且与109个已发表的T细胞特征相比,显示出更好的预测性能。单细胞和空间转录组学数据集验证了TstcSig与免疫检查点基因表达、肿瘤突变负担和T细胞浸润等免疫特征密切相关。值得注意的是,在TCGA队列中证实了TstcSig与T细胞浸润之间呈正相关。此外,泛癌分析证明了TstcSig预后价值的异质性。实验验证了肿瘤特异性T细胞高表达CD27、IFNG、GZMB和CXCL13,并分泌更多用于杀伤肿瘤细胞的效应细胞因子。

结论

我们基于肿瘤特异性T细胞相关基因开发了一个五基因特征(包括VAMP5、TIGIT、LCK、CD27和CACYBP)来预测膀胱癌患者的免疫治疗反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e61c/11264995/933980977704/12935_2024_3447_Fig1_HTML.jpg

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