Single-cell transcriptomic analysis of tumor heterogeneity and intercellular networks in human urothelial carcinoma. Issue 6 (20th March 2023)

• Record Type: Journal Article
• Authors: Jin, Xingwei; Wang, Qizhang; Luo, Fangxiu; Pan, Junwei; Lu, Tingwei; Zhao, Yang; Zhang, Xiang; Xiang, Enfei; Zhou, Chenghua; Huang, Baoxing; Lu, Guoliang; Chen, Peizhan; Shao, Yuan
• Editors: Ji, Yuanyuan
• Is Part Of: Chinese medical journal. Volume 136:Issue 6(2023)
• Page Start: 690
• Page End: 706
• Publication Date: 2023-03-20
• Subjects: Transitional cell carcinoma -- Single-cell RNA Seq -- Tumor microenvironment -- Prognosis; Medicine -- Periodicals; Medicine, Oriental -- Periodicals; Medicine; Medicine, Oriental; Medicine; Medicine, East Asian Traditional; Periodicals; Electronic journals; 610.5
• DOI: 10.1097/CM9.0000000000002573
• Languages: English
• ISSNs: 0366-6999

Abstract

Abstract: Background: Heterogeneity of tumor cells and the tumor microenvironment (TME) is significantly associated with clinical outcomes and treatment responses in patients with urothelial carcinoma (UC). Comprehensive profiling of the cellular diversity and interactions between malignant cells and TME may clarify the mechanisms underlying UC progression and guide the development of novel therapies. This study aimed to extend our understanding of intra-tumoral heterogeneity and the immunosuppressive TME in UC and provide basic support for the development of novel UC therapies. Methods: Seven patients with UC were included who underwent curative surgery at our hospital between July 2020 and October 2020. We performed single-cell RNA sequencing (scRNA-seq) analysis in seven tumors with six matched adjacent normal tissues and integrated the results with two public scRNA-seq datasets. The functional properties and intercellular interactions between single cells were characterized, and the results were validated using multiplex immunofluorescence staining, flow cytometry, and bulk transcriptomic datasets. All statistical analyses were performed using the R package with two-sided tests. Wilcoxon-rank test, log-rank test, one-way analysis of variance test, and Pearson correlation analysis were used properly. Results: Unsupervised t-distributed stochastic neighbor embedding clustering analysis identified ten main cellular subclusters in urothelial tissues. Of them, seven urothelial subtypes were noted, and malignant urothelial cells were characterized with enhanced cellular proliferation and reduced immunogenicity. CD8 + T cell subclusters exhibited enhanced cellular cytotoxicity activities along with increased exhaustion signature in UC tissues, and the recruitment of CD4 + T regulatory cells was also increased in tumor tissues. Regarding myeloid cells, coordinated reprogramming of infiltrated neutrophils, M2-type polarized macrophages, and LAMP3 + dendritic cells contribute to immunosuppressive TME in UC tissues. Tumor tissues demonstrated enhanced angiogenesis mediated by KDR + endothelial cells and RGS5 + /ACTA2 + pericytes. Through deconvolution analysis, we identified multiple cellular subtypes may influence the programmed death-ligand 1 (PD-L1) immunotherapy response in patients with UC. Conclusion: Our scRNA-seq analysis clarified intra-tumoral heterogeneity and delineated the pro-tumoral and immunosuppressive microenvironment in UC tissues, which may provide novel therapeutic targets.