AUTHOR=Li Deng-xiong , Feng De-chao , Shi Xu , Wu Rui-cheng , Chen Kai , Han Ping TITLE=Identification of endothelial-related molecular subtypes for bladder cancer patients JOURNAL=Frontiers in Oncology VOLUME=13 YEAR=2023 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1101055 DOI=10.3389/fonc.2023.1101055 ISSN=2234-943X ABSTRACT=Background

Bladder cancer (BC) is a disease with significant heterogeneity and poor prognosis. The prognosis and therapeutic response of BC patients are significantly influenced by endothelial cells in the tumor microenvironment. In order to understand BC from the perspective of endothelial cells, we orchestrated molecular subtypes and identified key genes.

Methods

Single-cell and bulk RNA sequencing data were extracted from online databases. R and its relative packages were used to analyze these data. Cluster analysis, prognostic value analysis, function analysis, immune checkpoints, tumor immune environment and immune prediction were conducted.

Results

Five endothelial-related genes (CYTL1, FAM43A, HSPG2, RBP7, and TCF4) divided BC patients in the TCGA, GSE13507, and GSE32894 datasets into two clusters, respectively. In prognostic value analysis, patients in the cluster 2 were substantially associated with worse overall survival than those in the cluster 1 according to the results of TCGA, GSE13507 and GSE32894 datasets. In the results of functional analysis, the endothelial-related clusters was enriched in immune-related, endothelial-related and metabolism-related pathways. Samples in the cluster 1 had a statistically significant increase in CD4+ T cells and NK-cell infiltration. Cluster 1 was positively correlated with the cancer stem score and tumor mutational burden score. The results of immune prediction analysis indicated that 50.6% (119/235) of patients in the cluster 1 responded to immunotherapy, while the response rate in the cluster 2 decreased to 16.7% (26/155).

Conclusion

In this study, we categorized and discovered distinctive prognosis-related molecular subtypes and key genes from the perspective of endothelial cells at the genetic level by integrating single-cell and bulk RNA sequencing data, primarily to provide a roadmap for precision medicine.