Department of Urology, The First Hospital of China Medical University, Shenyang, 110013, P.R. China.
BMC Cancer. 2022 Aug 27;22(1):926. doi: 10.1186/s12885-022-09794-9.
This study developed a gene signature associated with a malignant and common tumor of the urinary system, the Bladder Urothelial Carcinoma (BLCA).
The Cancer Genome Atlas (TCGA) database was searched to obtain 414 BLCA samples and the expression spectra of 19 normal samples. Single-sample Gene Set Enrichment Analysis (ssGSEA) was conducted to determine the enrichment levels in the BLCA samples of the 29 immune genes. Unsupervised hierarchical clustering, gene set enrichment analysis (GSEA), single-factor Cox analysis, least absolute shrinkage and selection operator (LASSO) regression models, and GEO queues were used to determine the BLCA immune gene subtype, analyze the biological pathway differences between immune gene subtypes, determine the characteristic genes of BLCA associated with prognosis, identify the BLCA-related genes, and verify the gene signature, respectively.
We identified two immune gene subtypes (immunity_L and immunity_H). The latter was significantly related to receptors, JAK STAT signaling pathways, leukocyte interleukin 6 generation, and cell membrane signal receptor complexes. Four characteristic genes (RBP1, OAS1, LRP1, and AGER) were identified and constituted the gene signature. Significant survival advantages, higher mutation frequency, and superior immunotherapy were observed in the low-risk group patients. The gene signature had good predictive ability. The results of the validation group were consistent with TCGA queue results.
We constructed a 4-gene signature that helps monitor BLCA occurrence and prognosis, providing an important basis for developing personalized BLCA immunotherapy.
本研究开发了与泌尿系统常见恶性肿瘤膀胱癌（BLCA）相关的基因特征。
从癌症基因组图谱（TCGA）数据库中获取 414 例 BLCA 样本和 19 例正常样本的表达谱。进行单样本基因集富集分析（ssGSEA），以确定 29 个免疫基因在 BLCA 样本中的富集水平。采用无监督层次聚类、基因集富集分析（GSEA）、单因素 Cox 分析、最小绝对值收缩和选择算子（LASSO）回归模型以及 GEO 队列，确定 BLCA 免疫基因亚型，分析免疫基因亚型之间的生物学途径差异，确定与预后相关的 BLCA 特征基因，识别 BLCA 相关基因，并验证基因特征。
我们确定了两种免疫基因亚型（免疫_L 和免疫_H）。后者与受体、JAKSTAT 信号通路、白细胞白细胞介素 6 生成和细胞膜信号受体复合物显著相关。鉴定出四个特征基因（RBP1、OAS1、LRP1 和 AGER），构成了基因特征。低危组患者的生存优势显著，突变频率更高，免疫治疗效果更好。基因特征具有良好的预测能力。验证组的结果与 TCGA 队列的结果一致。
我们构建了一个 4 基因特征，可以帮助监测 BLCA 的发生和预后，为开发个性化 BLCA 免疫治疗提供重要依据。
