Drug Tolerant Cells: An Emerging Target With Unique Transcriptomic Features
- PMID: 31636480
- PMCID: PMC6787876
- DOI: 10.1177/1176935119881633
Drug Tolerant Cells: An Emerging Target With Unique Transcriptomic Features
Abstract
Long-term outcome of cancer therapy is often severely perturbed by the acquisition of drug resistance. Recent evidence point toward the survival of a subpopulation of tumor cells under acute drug stress that over time can re-populate the tumor. These transiently existing, weakly proliferative, drug-tolerant cells facilitate tumor cell survival until more stable resistance mechanisms are acquired. From a therapeutic perspective, understanding the molecular features of the tolerant cells is critical to attenuation of resistance. In this article, we discuss the transcriptomic features of drug-tolerant osteosarcoma cells that survive a high dose of cisplatin shock. We present the unique transcriptome of the minimally dividing tolerant cells in comparison with the proliferative persisters or resistant cells derived from the tolerant cells. Targeting the tolerant cells can represent an efficient therapeutic strategy impeding tumor recurrence.
Keywords: Osteosarcoma; RNA sequencing; drug resistance; drug-tolerant persister; epigenetic alteration.
© The Author(s) 2019.
Conflict of interest statement
Declaration of conflicting interests:The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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Comment on
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A global transcriptomic pipeline decoding core network of genes involved in stages leading to acquisition of drug-resistance to cisplatin in osteosarcoma cells.Bioinformatics. 2019 May 15;35(10):1701-1711. doi: 10.1093/bioinformatics/bty868. Bioinformatics. 2019. PMID: 30307528
References
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- Niveditha D, Mukherjee S, Majumder S, Chowdhury R, Chowdhury S. A global transcriptomic pipeline decoding core network of genes involved in stages leading to acquisition of drug-resistance to cisplatin in osteosarcoma cells. Bioinformatics. 2019;35:1701-1711. doi:10.1093/bioinformatics/bty868 - DOI - PubMed
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