Tan Zhiyong, Fu Shi, Feng Runlin, Huang Yinglong, Li Ning, Wang Haifeng, Wang Jiansong
Department of Urology, The Second Affiliated Hospital of Kunming Medical University, No. 347, Dianmian Street, Wuhua District, Kunming, 650101 Yunnan, 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, China.
J Oncol. 2022 Apr 19;2022:1802706. doi: 10.1155/2022/1802706. eCollection 2022.
. Bladder cancer (BLCA) is a highly malignant tumor that develops in the urinary system. Identification of biomarkers in progression and prognosis is crucial for the treatment of BLCA. BLCA-related differentially expressed genes (DEGs) were authenticated by screening the DEGs and weighted gene coexpression network analysis (WGCNA). LASSO and SVM-RFE algorithms were utilized to screen the feature genes in BLCA. Survival analysis was performed using the Kaplan-Meier curve provided by the 'survival' R package. The BLCA samples were clustered by hclust based on the immune score matrix calculated by the single-sample GSEA (ssGSEA) algorithm. The immune, stromal, and ESTIMATE scores of each BLCA patient were calculated by applying the ESTIMATE algorithm. ssGSEA was conducted to explore the function of characteristic genes in BLCA. The expression of characteristic genes in clinical cancer tissue, and the pericancerous tissue of BLCA patients was verified using qRT-PCR assays. A total of 189 BLCA-related DEGs were identified. Fourteen feature genes were defined by LASSO and SVM-RFE algorithms. Five characteristic genes, including SMYD2, GAPDHP1, ATP1A2, CILP, and THSD4, were related to the OS of BLCA. The correlation analysis of five characteristic genes and clinicopathological factors showed that five genes played a role in the progression of BLCA. Additionally, the expression of five characteristic genes in clinical cancer tissues and pericarcinomatous tissues from BLCA patients was verified by qRT-PCR, which was consistent with the result from the public database. Finally, we discovered five prognostic genes linked to BLCA progression, which might serve as a theoretical basis for prognosis and treatment targets for BLCA patients.
膀胱癌（BLCA）是一种发生于泌尿系统的高度恶性肿瘤。鉴定进展和预后中的生物标志物对于BLCA的治疗至关重要。通过筛选差异表达基因（DEGs）和加权基因共表达网络分析（WGCNA）来验证与BLCA相关的DEGs。利用LASSO和支持向量机递归特征消除（SVM-RFE）算法筛选BLCA中的特征基因。使用“生存”R包提供的Kaplan-Meier曲线进行生存分析。基于单样本基因集富集分析（ssGSEA）算法计算的免疫评分矩阵，通过层次聚类（hclust）对BLCA样本进行聚类。应用ESTIMATE算法计算每位BLCA患者的免疫、基质和ESTIMATE评分。进行ssGSEA以探索BLCA中特征基因的功能。使用定量逆转录聚合酶链反应（qRT-PCR）检测验证临床癌组织及BLCA患者癌旁组织中特征基因的表达。共鉴定出189个与BLCA相关的DEGs。通过LASSO和SVM-RFE算法确定了14个特征基因。包括SMYD2、GAPDHP1、ATP1A2、CILP和THSD4在内的5个特征基因与BLCA的总生存期（OS）相关。5个特征基因与临床病理因素的相关性分析表明，这5个基因在BLCA的进展中起作用。此外，通过qRT-PCR验证了BLCA患者临床癌组织和癌旁组织中5个特征基因的表达，这与公共数据库的结果一致。最后，我们发现了5个与BLCA进展相关的预后基因，这可能为BLCA患者的预后和治疗靶点提供理论依据。
