Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA382641 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5444770.fastq.gz | Fastqsanger.gz | |||
| SRR5444780.fastq.gz | Fastqsanger.gz | |||
| SRR5444790.fastq.gz | Fastqsanger.gz | |||
| SRR5444800.fastq.gz | Fastqsanger.gz | |||
| SRR5444810.fastq.gz | Fastqsanger.gz |
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Project description:Molecular differences between individual cells can lead to dramatic differences in cell fate, such as the difference between death versus survival of cancer cells upon treatment with anti-cancer drugs. Despite some progress, these originating differences have largely remained hidden due to the difficulty in determining precisely what variable molecular features lead to which cellular fates. Here, we trace drug-resistant cell fates back to differences in the molecular profiles of their drug-naive melanoma precursors, revealing a rich substructure of variability underlying a number of resistant phenotypes at the single cell level. We make these connections using Rewind, a methodology that combines genetic barcoding with an RNA-based readout to directly capture rare cells that give rise to cellular behaviors of interest. We performed extensive single cell analysis to identify differences in gene expression and MAP-kinase signaling that mark a rare population of drug-naive cells (initial frequency of ~1:1000-1:10,000 cells) that ultimately gives rise to drug resistant clones. We demonstrate that this rare subpopulation has rich substructure and is composed of several distinct subpopulations, and the molecular differences between these subpopulations predict future differences in phenotypic behavior, such as the ultimate proliferative capacity of drug resistant cells. Similarly, we show that treatments that modify the frequency of resistance can allow otherwise non-resistant cells in the drug-naive population to become resistant, and that these new populations are marked by the variable expression of distinct genes. Together, our results reveal the presence of hidden, rare-cell variability that can underlie a range of latent phenotypic outcomes upon drug exposure.
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