The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy

Mil Med Res. 2024 Apr 11;11(1):21. doi: 10.1186/s40779-024-00526-7.

Abstract

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

Keywords: Precision medicine; Prostate cancer; Single-cell RNA sequencing (scRNA-seq); Treatment resistance; Tumor heterogeneity; Tumor microenvironment.

Publication types

  • Review

MeSH terms

  • Animals
  • Cell Differentiation
  • Humans
  • Immunotherapy
  • Male
  • Mice
  • Prostate
  • Prostatic Neoplasms* / genetics
  • Prostatic Neoplasms* / therapy
  • Single-Cell Gene Expression Analysis*