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=Volume 13 - 2023

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 high heterogeneity and poor prognosis. Endothelial cells in the BC microenvironment play a vital role in prognosis and medical response. We orchestrated molecular subtypes and identified key genes for BC from the perspective of endothelial cells collected by integrating single-cell and bulk RNA sequencing data.
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: Finally, 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 cluster 2 were significantly associated with worse overall survival than those in cluster 1 according to the results of TCGA, GSE13507, and GSE32894 datasets. In the results of analysis, the ERC was enriched in immune-related, endothelial-related, and metabolism-related pathways. Samples in cluster 1 were significantly associated with a higher proportion of 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 cluster 1 responded to immunotherapy, while the response rate in cluster 2 decreased to 16.7% (26/155).
Conclusion: In this study, we classified and identified distinctly 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, mainly to provide a roadmap for precision medicine.