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基于加权基因共表达网络分析构建预测膀胱癌生存及免疫治疗效果的T细胞耗竭模型

Construction of T cell exhaustion model for predicting survival and immunotherapy effect of bladder cancer based on WGCNA.

作者信息

Xue Yuwen, Zhao Guanghui, Pu Xiaoxin, Jiao Fangdong

机构信息

Department of Pulmonary and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan, China.

Peking University People's Hospital, Qingdao Women and Children's Hospital, Qingdao, China.

出版信息

Front Oncol. 2023 May 30;13:1196802. doi: 10.3389/fonc.2023.1196802. eCollection 2023.

DOI:10.3389/fonc.2023.1196802
PMID:37324016
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10266200/
Abstract

INTRODUCTION

The prognosis of bladder cancer (BLCA) and response to immune checkpoint inhibitors (ICIs) are determined by multiple factors. Existed biomarkers for predicting the effect of immunotherapy cannot accurately predict the response of BLCA patients to ICIs.

METHODS

To further accurately stratify patients' response to ICIs and identify potential novel predictive biomarkers, we used the known T cell exhaustion (TEX)-related specific pathways, including tumor necrosis factor (TNF), interleukin (IL)-2, interferon (IFN)-g, and T- cell cytotoxicpathways, combined with weighted correlation network analysis (WGCNA) to analyze the characteristics of TEX in BLCA in detail, constructed a TEX model.

RESULTS

This model including 28 genes can robustly predict the survival of BLCA and immunotherapeutic efficacy. This model could divide BLCA into two groups, TEXhigh and TEXlow, with significantly different prognoses, clinical features, and reactivity to ICIs. The critical characteristic genes, such as potential biomarkers Charged Multivesicular Body Protein 4C (CHMP4C), SH2 Domain Containing 2A (SH2D2A), Prickle Planar Cell Polarity Protein 3 (PRICKLE3) and Zinc Finger Protein 165 (ZNF165) were verified in BLCA clinical samples by real-time quantitative chain reaction (qPCR) and immunohistochemistry (IHC).

DISCUSSION

Our findings show that the TEX model can serve as biological markers for predicting the response to ICIs, and the involving molecules in the TEX model might provide new potential targets for immunotherapy in BLCA.

摘要

引言

膀胱癌（BLCA）的预后及对免疫检查点抑制剂（ICIs）的反应由多种因素决定。现有的预测免疫治疗效果的生物标志物无法准确预测BLCA患者对ICIs的反应。

方法

为了进一步准确分层患者对ICIs的反应并识别潜在的新型预测生物标志物，我们使用已知的与T细胞耗竭（TEX）相关的特定通路，包括肿瘤坏死因子（TNF）、白细胞介素（IL）-2、干扰素（IFN）-γ和T细胞细胞毒性通路，结合加权基因共表达网络分析（WGCNA）详细分析BLCA中TEX的特征，构建了一个TEX模型。

结果

该模型包含28个基因，能够可靠地预测BLCA的生存率和免疫治疗疗效。该模型可将BLCA分为两组，即TEX高组和TEX低组，两组在预后、临床特征以及对ICIs的反应性方面存在显著差异。通过实时定量聚合酶链反应（qPCR）和免疫组织化学（IHC）在BLCA临床样本中验证了关键特征基因，如潜在生物标志物多囊泡体蛋白4C（CHMP4C）、含SH2结构域蛋白2A（SH2D2A）、刺状平面细胞极性蛋白3（PRICKLE3）和锌指蛋白165（ZNF165）。

讨论

我们的研究结果表明，TEX模型可作为预测对ICIs反应的生物标志物，并且TEX模型中涉及的分子可能为BLCA的免疫治疗提供新的潜在靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/935894e9cba0/fonc-13-1196802-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/ac80d47521de/fonc-13-1196802-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/6a7450a9b85f/fonc-13-1196802-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/fcda65f12838/fonc-13-1196802-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/8b90ecf6a0cd/fonc-13-1196802-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/861562dc248f/fonc-13-1196802-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/935894e9cba0/fonc-13-1196802-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/ac80d47521de/fonc-13-1196802-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/6a7450a9b85f/fonc-13-1196802-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/fcda65f12838/fonc-13-1196802-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/8b90ecf6a0cd/fonc-13-1196802-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/861562dc248f/fonc-13-1196802-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6cb/10266200/935894e9cba0/fonc-13-1196802-g006.jpg

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