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Pre-existing cell states predict resistance to multiple treatments

ABSTRACT: Pre-existing cell states predict resistance to multiple treatments

PROVIDER: PRJNA1171004 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR30929779.fastq.gz	Fastqsanger.gz
	SRR30929780.fastq.gz	Fastqsanger.gz
	SRR30929781.fastq.gz	Fastqsanger.gz
	SRR30929782.fastq.gz	Fastqsanger.gz
	SRR30929783.fastq.gz	Fastqsanger.gz

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Pre-existing cell states predict resistance to multiple treatments

Project description:Pre-existing differences between individual cancer cells can predict which cells will become resistant upon the application of treatment. This understanding has been furthered by novel methods in DNA barcoding that allow tracking of clones and their cell states during treatment. However, previous studies using these techniques have been limited in their scope, focusing on how single cell-states lead to resistance to a single treatment. In this study, we performed multi-treatment, high-throughput clonal tracking and single-cell RNA-sequencing to trace rare clones through the development of resistance to many different treatments in parallel with the goal of identifying cell states associated with multi-treatment resistance. We found that clones that will go on to develop resistance to one treatment had an increased chance of separately developing resistance to other treatments with diverse mechanisms of action. Additionally, we identified high CD44 expression in treatment-naive cells as a predictor of future resistance to multiple different treatments. Furthermore, for cells within the same treatment condition, we found that differences in gene expression states prior to treatment can lead cells to follow divergent paths towards their ultimate resistance fate. This work provides a framework for extracting targetable gene expression states from complex resistance dynamics across multiple treatments to eliminate multi-treatment resistance.

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