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基于膀胱癌免疫基因组图谱分析的预后指数开发和预后相关基因筛选。

Development of a prognostic index and screening of prognosis related genes based on an immunogenomic landscape analysis of bladder cancer.

机构信息

Department of Urology, Zhuzhou Central Hospital, Zhuzhou 412007, China.

Department of Urology, The First Affiliated Hospital of Xiamen University, Xiamen 361003, China.

出版信息

Aging (Albany NY). 2021 Apr 22;13(8):12099-12112. doi: 10.18632/aging.202917.

DOI:10.18632/aging.202917
PMID:33888644
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8109062/
Abstract

BACKGROUND

Bladder cancer (BLCA) is one of the most common urinary tract malignant tumors. It is associated with poor outcomes, and its etiology and pathogenesis are not fully understood. There is great hope for immunotherapy in treating many malignant tumors; therefore, it is worthwhile to explore the use of immunotherapy for BLCA.

METHODS

Gene expression profiles and clinical information were obtained from The Cancer Genome Atlas (TCGA), and immune-related genes (IRGs) were downloaded from the Immunology Database and Analysis Portal. Differentially-expressed and survival-associated IRGs in patients with BLCA were identified using computational algorithms and Cox regression analysis. We also performed functional enrichment analysis. Based on IRGs, we employed multivariate Cox analysis to develop a new prognostic index.

RESULTS

We identified 261 IRGs that were differentially expressed between BLCA tissue and adjacent tissue, 30 of which were significantly associated with the overall survival (all P<0.01). According to multivariate Cox analysis, nine survival-related IRGs (MMP9, PDGFRA, AHNAK, OAS1, OLR1, RAC3, IGF1, PGF, and SH3BP2) were high-risk genes. We developed a prognostic index based on these IRGs and found it accurately predicted BLCA outcomes associated with the TNM stage. Intriguingly, the IRG-based prognostic index reflected infiltration of macrophages.

CONCLUSIONS

An independent IRG-based prognostic index provides a practical approach for assessing patients' immune status and prognosis with BLCA. This index independently predicted outcomes of BLCA.

摘要

背景

膀胱癌（BLCA）是最常见的泌尿系统恶性肿瘤之一。其预后较差，病因和发病机制尚未完全阐明。免疫疗法在治疗许多恶性肿瘤方面有很大的希望；因此，探索免疫疗法治疗 BLCA 是值得的。

方法

从癌症基因组图谱（TCGA）获取基因表达谱和临床信息，并从免疫数据库和分析门户下载免疫相关基因（IRGs）。使用计算算法和 Cox 回归分析鉴定 BLCA 患者中差异表达和与生存相关的 IRGs。我们还进行了功能富集分析。基于 IRGs，我们采用多变量 Cox 分析构建了新的预后指标。

结果

我们鉴定出 261 个在 BLCA 组织和相邻组织之间差异表达的 IRGs，其中 30 个与总生存率显著相关（均 P<0.01）。根据多变量 Cox 分析，9 个与生存相关的 IRGs（MMP9、PDGFRA、AHNAK、OAS1、OLR1、RAC3、IGF1、PGF 和 SH3BP2）是高风险基因。我们基于这些 IRGs 开发了一个预后指标，并发现它能准确预测与 TNM 分期相关的 BLCA 结局。有趣的是，基于 IRG 的预后指标反映了巨噬细胞的浸润。

结论

一个独立的基于 IRG 的预后指标为评估 BLCA 患者的免疫状态和预后提供了一种实用的方法。该指标独立预测了 BLCA 的结局。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/9274838bf5d1/aging-13-202917-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/6d8d4d0eca99/aging-13-202917-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/d031d06c52ea/aging-13-202917-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/066d0044e802/aging-13-202917-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/9a24e2715993/aging-13-202917-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/701abef15e77/aging-13-202917-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/c2859cfaf7b3/aging-13-202917-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/302cda1ef14f/aging-13-202917-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/9274838bf5d1/aging-13-202917-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/6d8d4d0eca99/aging-13-202917-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/d031d06c52ea/aging-13-202917-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/066d0044e802/aging-13-202917-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/9a24e2715993/aging-13-202917-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/701abef15e77/aging-13-202917-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/c2859cfaf7b3/aging-13-202917-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/302cda1ef14f/aging-13-202917-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8d3/8109062/9274838bf5d1/aging-13-202917-g008.jpg

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