Single-cell RNA sequencing reveals the cellular and molecular characteristics of high-grade and metastatic bladder cancer

Cell Oncol (Dordr). 2023 Oct;46(5):1415-1427. doi: 10.1007/s13402-023-00820-x. Epub 2023 May 11.

Abstract

Purpose: Metastatic bladder cancer (BC) has the highest somatic mutation frequency and recurrence rate of all tumors. However, the cellular and molecular characteristics of BC remain unclear.

Methods: We performed single-cell RNA sequencing (scRNA-seq) on the samples of paracancerous normal tissue (PNT), primary tumor (PT) and lymph node metastasis (LNM). The proportions and gene expression profiles of different cell types in the tumor microenvironment (TME) were investigated.

Results: In total, 50,158 cells were classified into six populations. Malignant cells of PT and LNM exhibited large mutant DNA fragments, while the cell phenotypes and gene expression profiles differed during differentiation. Metastasis was associated with a poorer prognosis than PT. Tumor-associated stromal cells and inhibitory immune cells were the main cell populations in PT and LNM. Cell-cell communication analysis revealed the roles of signaling pathways of inflammatory cancer-associated fibroblast (iCAF) and tumor-associated macrophage (TAM) in exhaustion of T cells. In addition, iCAF may recruit TAM to promote formation of the TME earlier than the differentiation of tumor cells.

Conclusion: This study through scRNA-seq enhanced our understanding of new features about the cellular and molecular similarities and differences of high-grade and metastatic bladder cancer, which might provide potential therapeutic targets in future treatment.

Keywords: Bladder cancer; Cancer associated fibroblast; Metastasis; Single-cell RNA sequencing; Tumor associated macrophage; Tumor microenvironment.

MeSH terms

  • Cancer-Associated Fibroblasts*
  • Cell Communication
  • Cell Differentiation
  • Humans
  • Lymphatic Metastasis
  • Sequence Analysis, RNA
  • Tumor Microenvironment / genetics
  • Urinary Bladder Neoplasms* / genetics