Tan Zhiyong, Chen Xiaorong, Li Haihao, Huang Yinglong, Fu Shi, Ding Mingxia, Wang Jiansong, Wang Haifeng
Department of Urology, The Second Affiliated Hospital of Kunming Medical University, No. 347, Dianmian Street, Wuhua District, Kunming, 650101, Yunnan, People's Republic of China.
Urological disease clinical medical center of Yunnan province, The Second Affiliated Hospital of Kunming Medical University, No. 347, Dianmian Street, Wuhua District, Kunming, 650101, Yunnan, People's Republic of China.
J Cancer. 2024 Jan 21;15(6):1624-1641. doi: 10.7150/jca.92657. eCollection 2024.
Patients with bladder cancer (BLCA) have a poor prognosis and little progress has been made in treatment. Therefore, the purpose of this work was to employ Mendelian randomization (MR) and transcriptome analysis to identify a novel biomarker that could be used to reliably diagnose BLCA. TCGA-BLCA and GSE121711 datasets were obtained from public databases. Genome-wide association study (GWAS) data of BLCA outcome (373,295 samples containing 9,904,926 single nucleotide polymorphisms) were obtained through the IEU OpenGWAS database. Differentially expressed genes were applied as exposure factors, and MR analysis was performed to identify genes that had a causal relationship with BLCA. Then, the patients were divided into high and low expression groups according to the expression levels of candidate genes, and genes with survival differences were identified. Univariate and multivariate Cox regression were used to investigate the prognostic value of the expression of these genes. A nomogram was constructed based on independent prognostic factors, and we analyzed the functions and pathways associated with the identified genes as well as their relationship with the immune microenvironment. was identified as a biomarker. status, age, and stage were identified as independent prognostic factors, and an excellent nomogram was established. Bioinformatic analysis suggested that might be associated with the activation of the immune response, bone development, and cancer pathways. The BLCA samples were divided into high and low groups. The stromal score and 33 immune cells were remarkably different between the two groups, with expression being negatively correlated with macrophages and mast cells, and positively correlated with eosinophils and central memory CD4+ T cells. Finally, was up-regulated in cancer samples in both TCGA-BLCA and GSE121711 datasets. This study identified as an independent prognostic factor for BLCA outcome based on MR and transcriptome analysis, which provides useful information for future research on and treatment of BLCA.
膀胱癌（BLCA）患者预后较差，治疗方面进展甚微。因此，本研究旨在利用孟德尔随机化（MR）和转录组分析来鉴定一种可用于可靠诊断BLCA的新型生物标志物。从公共数据库中获取了TCGA - BLCA和GSE121711数据集。通过IEU OpenGWAS数据库获得了BLCA结局的全基因组关联研究（GWAS）数据（373,295个样本，包含9,904,926个单核苷酸多态性）。将差异表达基因作为暴露因素，进行MR分析以鉴定与BLCA存在因果关系的基因。然后，根据候选基因的表达水平将患者分为高表达组和低表达组，并鉴定出生存存在差异的基因。使用单变量和多变量Cox回归研究这些基因表达的预后价值。基于独立预后因素构建了列线图，并分析了与鉴定出的基因相关的功能和通路以及它们与免疫微环境的关系。 被鉴定为一种生物标志物。 状态、年龄和分期被确定为独立预后因素，并建立了一个出色的列线图。生物信息学分析表明， 可能与免疫反应激活、骨骼发育和癌症通路有关。将BLCA样本分为高 和低 组。两组之间的基质评分和33种免疫细胞存在显著差异， 表达与巨噬细胞和肥大细胞呈负相关，与嗜酸性粒细胞和中枢记忆CD4 + T细胞呈正相关。最后，在TCGA - BLCA和GSE121711数据集中，癌症样本中的 均上调。本研究基于MR和转录组分析确定 为BLCA结局的独立预后因素，为未来BLCA的研究和治疗提供了有用信息。
