The tumor microenvironment and prognostic role of autophagy- and immune-related genes in bladder cancer.

IF 1.9

Cancer biomarkers : section A of Disease markers Pub Date : 2022-01-01 DOI:10.3233/CBM-220058

Zhenhua Gao, Cheng Chen, Peng Gu, Jianheng Chen, Xiaodong Liu, Jihong Shen

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引用次数: 1

Abstract

Background: Autophagy-related genes and immune-related genes contribute significantly to the initiation and prognosis of bladder cancer (BLCA).

Objective: We aimed to explore differentially expressed autophagy-related genes (DEARGs) and immune-related genes (DEIRGs) in BLCA to create a prognostic risk assessment model and gain some insights into BLCA's molecular underpinnings.

Methods: The prognostic DEARGs and DEIRGs were evaluated for BLCA through The Cancer Genome Atlas (TCGA) database (n= 399) and GSE13507 dataset (n= 165). The BLCA risk model was constructed and verified. The immune score, stromal score, and estimate score in different risk groups were calculated by the ESTIMATE algorithm. Immune infiltration levels were assessed by a single sample gene set enrichment analysis (GSEA) algorithm.

Results: In the risk model, AURKA, ACTC1, MYLK, PDGFD, PDGFRA and TNC were significantly associated with the overall survival. The pathways in cancer, T cell receptor signaling pathway and B cell receptor signaling pathway were significantly gathered in the high-risk group. Moreover, the risk score was significantly correlated with infiltrating immune cells, expression of critical immune checkpoints and mismatch repair genes including MSH6, MLH1, and MSH2.

Conclusions: In this study, three DEARGs (AURKA, ACTC1, MYLK) and three DEIRGs (PDGFD, PDGFRA, TNC) were demonstrated to be potential prognostic biomarkers for BLCA patients through bioinformatics methods, which might be novel therapeutic targets and prognostic markers for BLCA, in follow up studies, we will combine experiments to verify this.

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肿瘤微环境及自噬和免疫相关基因在膀胱癌中的预后作用。

背景:自噬相关基因和免疫相关基因对膀胱癌(BLCA)的发生和预后有重要影响。目的:探讨BLCA中差异表达的自噬相关基因(DEARGs)和免疫相关基因(DEIRGs)，建立预后风险评估模型，并进一步了解BLCA的分子基础。方法:通过癌症基因组图谱(TCGA)数据库(n= 399)和GSE13507数据集(n= 165)评估BLCA的预后DEARGs和DEIRGs。构建并验证了BLCA风险模型。采用estimate算法计算不同危险组的免疫评分、基质评分和估计评分。通过单样本基因集富集分析(GSEA)算法评估免疫浸润水平。结果:在风险模型中，AURKA、ACTC1、MYLK、PDGFD、PDGFRA、TNC与总生存率显著相关。高危组肿瘤通路、T细胞受体信号通路和B细胞受体信号通路明显聚集。此外，风险评分与浸润免疫细胞、关键免疫检查点表达和错配修复基因MSH6、MLH1和MSH2显著相关。结论:本研究通过生物信息学方法证实了3种DEARGs (AURKA、ACTC1、MYLK)和3种DEIRGs (PDGFD、PDGFRA、TNC)是BLCA患者潜在的预后生物标志物，可能成为BLCA新的治疗靶点和预后标志物，在后续研究中，我们将结合实验进行验证。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Cancer biomarkers : section A of Disease markers

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