Department of Urology, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.
Key Laboratory of Urological Diseases of Gansu provincial, Lanzhou, People's Republic of China.
Cancer Med. 2021 Aug;10(15):5375-5391. doi: 10.1002/cam4.4071. Epub 2021 Jun 24.
The emergence of immunotherapy has provided an option of treatment methods for bladder cancer (BC). However, the beneficiaries of immunotherapy are still limited to small-scale patients, and immunotherapy-related adverse events often occur. It is a major challenge for clinical work to study the immune subtypes of BC and the molecular mechanism of immune escape, and identify the immune responders accurately. Here, we explore the immune molecular subtypes of bladder cancer and potential escape mechanisms. First, we screened the expression profiles of 303 differentially expressed immune-related genes in BC patients from the Cancer Genome Atlas (TCGA) database, and successfully identified 4 molecular subtypes of BC. By comparing the clinical characteristics, immune cells infiltration, the expression of checkpoint genes, human leukocyte antigen (HLA) genes, and gene mutation status of different subtypes, we identified different clinical and immunological characteristics of 4 subtypes. Among 4 subtypes, Cluster 2 met the general characteristics of immunotherapy responders and responded well to immunotherapy, while Cluster 4 had the highest expression of immune characteristics, and is similar to the immune environment of normal bladder tissue. Then, the weighted gene co-expression network analysis (WGCNA) of immune-related genes revealed that brown module was positively correlated with subtypes. Pathway enrichment analysis explored the major pathways associated with subtypes, which are also associated with immune escape mechanisms. Moreover, the decision tree model, which was constructed by the principle of random forest screening factors, was also validated in internal validation set and external validation set from the Gene Expression Omnibus (GEO) cohort (GSE133624), and could achieve accurate subtypes prediction for BC patients with high-throughput sequencing. Taken together, we explored the immune molecular subtypes and their mechanisms of BC, and these results may provide guidance for the development of new BC immunotherapy strategies.
免疫疗法的出现为膀胱癌（BC）提供了一种治疗方法。然而，免疫疗法的受益者仍然局限于小规模的患者，并且经常发生免疫疗法相关的不良反应。研究 BC 的免疫亚型和免疫逃逸的分子机制，并准确识别免疫反应者，是临床工作的一大挑战。在这里，我们探讨了膀胱癌的免疫分子亚型和潜在的逃逸机制。首先，我们从癌症基因组图谱（TCGA）数据库中筛选了 303 个差异表达的免疫相关基因在 BC 患者中的表达谱，并成功鉴定了 4 种 BC 的分子亚型。通过比较不同亚型的临床特征、免疫细胞浸润、检查点基因、人类白细胞抗原（HLA）基因的表达和基因突变状态，我们确定了 4 种亚型的不同临床和免疫学特征。在这 4 种亚型中，Cluster 2 符合免疫治疗反应者的一般特征，对免疫治疗反应良好，而 Cluster 4 具有最高的免疫特征表达，与正常膀胱组织的免疫环境相似。然后，对免疫相关基因的加权基因共表达网络分析（WGCNA）显示，棕色模块与亚型呈正相关。通路富集分析探讨了与亚型相关的主要通路，这些通路也与免疫逃逸机制有关。此外，基于随机森林筛选因素的原理构建的决策树模型，也在来自基因表达综合数据库（GEO）队列（GSE133624）的内部验证集和外部验证集中得到了验证，能够为接受高通量测序的 BC 患者实现准确的亚型预测。综上所述，我们探讨了 BC 的免疫分子亚型及其机制，这些结果可能为开发新的 BC 免疫治疗策略提供指导。
