He Yang, Wu Yongxin, Liu Zhe, Li Boping, Jiang Ning, Xu Peng, Xu Abai
Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Department of Urology, The First People's Hospital of Kashgar Prefecture, Kashgar, China.
Front Genet. 2021 Sep 13;12:694777. doi: 10.3389/fgene.2021.694777. eCollection 2021.
Bladder cancer has become the tenth most diagnosed cancer worldwide. The prognosis has been shown to differ between non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer (MIBC). We aimed to identify signature genes that are associated with the invasiveness and survival of bladder cancer and to identify potential treatments. We downloaded gene expression profiles of bladder cancer from the Gene Expression Omnibus database to identify differentially expressed genes and perform weighted gene co-expression network analysis. Functional enrichment was analyzed by GO and KEGG analyses. Hub genes were identified from the significant module. Another dataset was also acquired to verify the expression of hub genes. Univariate and multivariate Cox regression analyses were applied to the dataset downloaded from The Cancer Genome Atlas database. Risk scores were calculated and the effect was evaluated by Kaplan-Meier survival analysis. A nomogram was constructed and validated using training and testing samples, respectively. Analysis of the tumor immune microenvironment was conducted with the CIBERSORT algorithm. In total, 1,245 differentially expressed genes (DEGs) were identified. A distinct module was identified that was significantly correlated to invasiveness. The genes within this module were found to be significantly associated with extracellular exosomes, GTPase activity, metabolic pathways, etc. Three hub genes (VSIG2, PPFIBP2, and DENND2D) were identified as biomarkers of invasiveness; two of these (PPFIBP2 and DENND2D) were closely associated with prognosis. The risk score was regarded as an independent prognostic factor. The nomogram was associated with acceptable accuracy for predicting 1- and 5-year overall survival. The infiltrating levels of resting NK cells, activated natural killer (NK) cells, CD8 T cells, activated memory CD4 T cells, and T follicular helper cells, were significantly higher in the group with lower risk scores. The group with higher risk scores showed predominant infiltration by regulatory T cells (Tregs). We successfully identified three signature genes related to invasiveness and constructed a nomogram of bladder cancer with acceptable performance. Differences suggested by risk scores between groups of patients showing diverse patterns of immune cell infiltration may be beneficial for selecting therapeutic approaches and predicting prognosis.
膀胱癌已成为全球第十大最常被诊断出的癌症。研究表明,非肌层浸润性膀胱癌(NMIBC)和肌层浸润性膀胱癌(MIBC)的预后有所不同。我们旨在识别与膀胱癌侵袭性和生存率相关的特征基因,并确定潜在的治疗方法。我们从基因表达综合数据库下载了膀胱癌的基因表达谱,以识别差异表达基因并进行加权基因共表达网络分析。通过基因本体(GO)和京都基因与基因组百科全书(KEGG)分析进行功能富集分析。从显著模块中识别出枢纽基因。还获取了另一个数据集以验证枢纽基因的表达。对从癌症基因组图谱数据库下载的数据集应用单变量和多变量Cox回归分析。计算风险评分,并通过Kaplan-Meier生存分析评估其效果。分别使用训练样本和测试样本构建并验证了列线图。使用CIBERSORT算法对肿瘤免疫微环境进行分析。总共识别出1245个差异表达基因(DEG)。识别出一个与侵袭性显著相关的独特模块。发现该模块内的基因与细胞外囊泡、GTP酶活性、代谢途径等显著相关。三个枢纽基因(VSIG2、PPFIBP2和DENND2D)被识别为侵袭性的生物标志物;其中两个(PPFIBP2和DENND2D)与预后密切相关。风险评分被视为独立的预后因素。该列线图在预测1年和5年总生存率方面具有可接受的准确性。在风险评分较低的组中,静息自然杀伤(NK)细胞、活化的NK细胞、CD8 T细胞、活化的记忆CD4 T细胞和T滤泡辅助细胞的浸润水平显著更高。风险评分较高的组显示调节性T细胞(Treg)占主导性浸润。我们成功识别出三个与侵袭性相关的特征基因,并构建了一个性能可接受的膀胱癌列线图。不同免疫细胞浸润模式的患者组之间风险评分所显示的差异可能有助于选择治疗方法和预测预后。