Bladder cancer is a malignancy characterized by significant heterogeneity. RNA methylation has received an increasing amount of attention in recent years. RNA data were collected from the GEO database, and cell subsets were classified according to specific cell markers. Epithelial, immunological, and fibroblast cells were clustered individually to explore the tumor heterogeneity. To distinguish between malignant and benign cells, the InferCNV R package was employed. The monocle2 R package was used for pseudotime analysis. The Decouple R package was used for transcription factor analysis of each cell subgroup, and PROGENy was used to predict the activity of pathways related to tumors. The target lncRNA was screened for model construction. In addition, the qPCR experiment was used to detect the transcription level of lncRNA. Epithelial cells, fibroblasts, and T cells significantly differ in tumor and normal tissues. The lncRNAs related to m6A/m5C/m1A were intersected to construct the model. Finally, six model lncRNAs (PSMB8–AS1, THUMPD3–AS1, U47924.27, XXbac–B135H6.15, MIR99AHG, and C14orf132) were screened. High-risk individuals were shown to have a better prognosis. qPCR experiments showed that the model lncRNA was differentially expressed between normal and tumor cells. Immunotherapy will be more effective in treating individuals with lower risk than those with higher risk using 4 candidate drugs. The prognostic m6A/m5C/m1A-related lncRNA model was constructed for evaluating the clinical outcomes of bladder cancer patients and guiding clinical medication.

膀胱癌是一种具有显着异质性特征的恶性肿瘤。近年来，RNA甲基化受到越来越多的关注。RNA数据从GEO数据库中收集，并根据特定的细胞标记对细胞亚群进行分类。将上皮细胞、免疫细胞和成纤维细胞单独聚集以探索肿瘤异质性。为了区分恶性和良性细胞，使用了 InferCNV R 软件包。monocle2 R 包用于伪时间分析。Depair R软件包用于每个细胞亚群的转录因子分析，PROGENy用于预测与肿瘤相关的通路的活性。筛选目标lncRNA用于模型构建。此外，还采用qPCR实验检测lncRNA的转录水平。肿瘤组织和正常组织中的上皮细胞、成纤维细胞和 T 细胞存在显着差异。将与m6A/m5C/m1A相关的lncRNA相交以构建模型。最后，筛选了六种模型lncRNA（PSMB8-AS1、THUMPD3-AS1、U47924.27、XXbac-B135H6.15、MIR99AHG和C14orf132）。高风险个体的预后较好。qPCR实验表明，模型lncRNA在正常细胞和肿瘤细胞之间存在差异表达。使用 4 种候选药物进行免疫疗法治疗风险较低的个体比治疗风险较高的个体更有效。构建m6A/m5C/m1A相关lncRNA预后模型，用于评估膀胱癌患者的临床结局并指导临床用药。