Variability within rare cell states enables multiple paths towards drug resistance.
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA676147 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Variability within rare cell states enables multiple paths towards drug resistance [WM989_DOT1Li]
| PRJNA676154 | ENA
Project description:Variability within rare cell states enables multiple paths towards drug resistance [WM989_WM983b]
| PRJNA676155 | ENA
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.
2020-11-12 | GSE161298 | GEO
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.
2020-11-12 | GSE161299 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2020-11-12 | GSE161300 | GEO
Project description: Not available
| S-EPMC8277666 | biostudies-literature
Project description:The widespread application of single-cell genomics technologies has accelerated our understanding of the breadth and depth of heterogeneity of cell states across diverse contexts. As single-cell RNA sequencing (scRNA-seq) has been the most popular modality used for profiling, many populations have been described primarily based on specific marker transcript profiles compared to classical cytometry approaches relying on protein expression. Additionally, many single cell studies require the isolation of nuclei from tissue, eliminating the ability to enrich learned rare cell states based on extranuclear protein markers. To address this limitation, we describe Programmable Enrichment via RNA Flow-FISH by sequencing (PERFF-seq), a scalable assay that enables single cell and single nuclei RNA-seq profiling from subpopulations of complex cellular mixtures solely defined by the abundance of RNA transcripts. Across vignettes of immune cell populations as well as nuclei from fresh frozen and formalin-fixed paraffin-embedded brain tissue, we demonstrate the enrichment of cell populations via RNA-based cytometry upstream of high-throughput scRNA-seq. Together, our approach provides a rational, programmable method for studying cell identities and transcriptional heterogeneity of rare populations identifiable by as few as one marker transcript, advancing the rational study of cellular diversity across fresh and archived tissue materials.
2024-03-26 | GSE262355 | GEO
Project description:Therapies targeting signaling molecules mutated in cancers can often have striking short-term effects, but the emergence of resistant cancer cells is a major barrier to full cures. Resistance can sometimes result from a secondary mutations in rare cells, but other times, there is no clear genetic cause, raising leaving the possibility of non-genetic rare cell variability. Here, we show that melanoma cells can display profound transcriptional variability at the single cell level that predicts which cells will ultimately resist drug treatment. This variability involves semi-coordinated transcription of a number of resistance markers at high levels in a very small percentage of cells. The addition of drug then induces an epigenetic reprogramming in these cells, converting the transient transcriptional state to a stably resistant state. This reprogramming begins withis a progressive process consisting of a loss of SOX10-mediated differentiation followed by activation of new signaling pathways, partially mediated by activity of Jun-AP-1 and TEAD. Our work reveals the multistage nature of the acquisition of drug resistance and provides a framework for understanding resistance dynamics. We find that other cell types also exhibit sporadic expression of many of these same marker genes, suggesting the existence of a general rare-cell expression program.
2017-04-13 | GSE97680 | GEO
Project description:Therapies targeting signaling molecules mutated in cancers can often have striking short-term effects, but the emergence of resistant cancer cells is a major barrier to full cures. Resistance can sometimes result from a secondary mutations in rare cells, but other times, there is no clear genetic cause, raising leaving the possibility of non-genetic rare cell variability. Here, we show that melanoma cells can display profound transcriptional variability at the single cell level that predicts which cells will ultimately resist drug treatment. This variability involves semi-coordinated transcription of a number of resistance markers at high levels in a very small percentage of cells. The addition of drug then induces an epigenetic reprogramming in these cells, converting the transient transcriptional state to a stably resistant state. This reprogramming begins with a progressive process consisting of a loss of SOX10-mediated differentiation followed by activation of new signaling pathways, partially mediated by activity of Jun-AP-1 and TEAD. Our work reveals the multistage nature of the acquisition of drug resistance and provides a framework for understanding resistance dynamics. We find that other cell types also exhibit sporadic expression of many of these same marker genes, suggesting the existence of a general rare-cell expression program.
2017-04-13 | GSE97679 | GEO