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Deciphering cancer cell state plasticity with single-cell genomics and artificial intelligence.
Emily Holton1,2,3, Walter Muskovic1,3, Joseph E Powell4,5,6
1Garvan Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, The Kinghorn Cancer Centre, Darlinghurst, NSW, 2010, Australia.
Genome Medicine
|February 26, 2024
Summary
Cancer cell plasticity allows tumor cells to change states, impacting cancer progression and treatment. Single-cell technologies and artificial intelligence reveal complex cell state landscapes, improving our understanding of cancer biology.
Area of Science:
- Cancer Biology
- Genomics
- Computational Biology
Background:
- Cancer stem cell plasticity describes dynamic state transitions in tumor cells.
- These transitions influence tumor progression, metastasis, dormancy, and therapeutic response.
- Traditional bulk genomic analysis masks the contribution of cell state plasticity.
Purpose of the Study:
- To explore the role of cancer cell state plasticity in tumor ecosystems.
- To highlight the utility of single-cell technologies and AI in studying this phenomenon.
- To provide a detailed model for investigating cancer plasticity.
Main Methods:
- Utilizing single-cell assays to measure genomic features of individual cancer cells.
- Applying artificial intelligence methods to analyze high-dimensional single-cell data.
- Characterizing the cell state landscape of tumor ecosystems.
Main Results:
- Single-cell technologies provide a high-dimensional view of the tumor ecosystem.
- AI methods are crucial for depicting complex cancer cell state landscapes.
- Detailed models of cancer plasticity can be created using these advanced techniques.
Conclusions:
- Cancer cell plasticity is a key factor in tumor behavior and treatment outcomes.
- Single-cell resolution and AI are essential for dissecting cancer plasticity.
- Understanding cell state dynamics offers new avenues for cancer research and therapy.
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