Single-Cell Transcriptomics: Technical Advances, Applications and Challenges in Cancer Drug Discovery
With advancements in technology, single-cell RNA sequencing has emerged as a power-ful tool in cancer drug discovery. This technique enables the construction of gene expression profiles at the individual cell level, offering detailed insights into cellular heterogeneity and molecular path-ways involved in tumor development. It enables researchers to gain a deeper understanding of tumor heterogeneity. Researchers can study cell subpopulations and gene expression patterns. This under-standing helps in identifying potential drug targets. Additionally, it aids in predicting therapeutic responses. This high-resolution gene expression analysis provides a new perspective and oppor-tunity for cancer drug development, which is expected to accelerate the discovery and development process of new anti-cancer drugs. This article provides a comprehensive overview of the basic pro-cesses and developmental trajectory of single-cell RNA sequencing technology, with a particular emphasis on its applications in various aspects of cancer drug discovery. It also addresses the chal-lenges faced by single-cell RNA sequencing and potential future directions. This review aims to enhance readers' understanding of single-cell sequencing, inspire new ideas for oncology drug de-velopment, and support the translation of clinical research into practice, ultimately enabling physi-cians to design more precise and personalized treatment strategies.
Authors
- Jianjun Tan
- Teng Zhang (ORCID: https://orcid.org/0000-0002-6318-2708)
- Lingyu Meng
- Yueying Yang
Institutions
- China International Science and Technology Cooperation (CN)
- University of Science and Technology Beijing (CN)
Publication Details
- Journal
- Current Cancer Drug Targets
- Published
- 2025-07-30
- DOI
- https://doi.org/10.2174/0115680096372729250715050452
- Citations
- 1
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.81