Ontology highlight
ABSTRACT:
PROVIDER: PRJNA972638 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR24557400_1.fastq.gz | Fastqsanger.gz | |||
| SRR24557400_2.fastq.gz | Fastqsanger.gz | |||
| SRR24557401_1.fastq.gz | Fastqsanger.gz | |||
| SRR24557401_2.fastq.gz | Fastqsanger.gz | |||
| SRR24557402_1.fastq.gz | Fastqsanger.gz |
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Project description:Pre-determined diversity in resistant fates emerges from homogenous cells after anti-cancer drug treatment
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Project description:Pre-determined diversity in resistant fates emerges from homogenous cells after anti-cancer drug treatment (single-cell data)
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Project description:Even amongst genetically identical cancer cells, therapy resistance often only emerges from a very small subset of those cells. Much effort has gone into uncovering the molecular differences in rare individual cells in the initial population that may allow certain cells to become therapy resistant; however, comparatively little is known about variability in the resistant outcomes themselves. Here, we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically, and functionally distinct fate types. These different resistant types are largely predetermined by molecular differences between cells before addition of drug and not by extrinsic cell-specific microenvironmental factors. Changes in dose and kind of drug can, however, switch the resistant fate type of an initial cell, even resulting in the generation and elimination of certain fate types. Diversity in resistant fates was observed across several single-cell-derived cancer cell lines and types treated with a variety of drugs. Cell fate diversity as a result of variability in intrinsic cell states may be a generic feature of response to external cues.
2023-05-31 | GSE233622 | GEO
Project description:Even amongst genetically identical cancer cells, therapy resistance often only emerges from a very small subset of those cells. Much effort has gone into uncovering the molecular differences in rare individual cells in the initial population that may allow certain cells to become therapy resistant; however, comparatively little is known about variability in the resistant outcomes themselves. Here, we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically, and functionally distinct fate types. These different resistant types are largely predetermined by molecular differences between cells before addition of drug and not by extrinsic cell-specific microenvironmental factors. Changes in dose and kind of drug can, however, switch the resistant fate type of an initial cell, even resulting in the generation and elimination of certain fate types. Diversity in resistant fates was observed across several single-cell-derived cancer cell lines and types treated with a variety of drugs. Cell fate diversity as a result of variability in intrinsic cell states may be a generic feature of response to external cues.
2023-06-03 | GSE233766 | GEO
Project description:Xenografts are useful in vivo tumour models for investigating cancer progression, therapeutic responses and predicting anti-cancer drug response in patients with cancer of a similar phenotype. We have generated bulk RNA-seq data from LNCaP xenografts of a large and well-annotated prostate cancer progression study, investigating responsiveness and subsequent resistance to therapies targeting the androgen receptor (AR). LNCaP xenograft tumour establishment and initial growth are dependent on androgens in male mice (PRE-CX / pre-castration group). Upon castration, AR activity and tumour growth are suppressed (POST-CX / post-castration group), however, this initial responsiveness to castration reproducibly gives way to castration-resistance (CRPC / castration-resistant prostate cancer). Further treatment of CRPC with the AR targeting drug enzalutamide (ENZ) initially provides a therapeutic response (ENZ Sensitive; ENZS), however, resistance emerges in time (ENZ Resistant; ENZR).
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2015-08-05 | E-GEOD-66549 | biostudies-arrayexpress
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: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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Project description:The treatment of advanced prostate cancer has been transformed by novel antiandrogen therapies such as enzalutamide. Using the LnCaP/AR xenograft model, we identified induction of glucocorticoid receptor (GR) expression as a common feature of drug resistant tumors. From a resistant xenograft tumor, we derived a GR expressing resistant subline called LREX' which maintains the resistant phenotype. mRNA expression was used to characterize resistant tissues. LnCaP/AR cells were injected into castrate mice and tumors were established. Mice were then treated with vehicle (Con), 4 days of anti-androgen (ARN-509 10mgkg), or were maintained on anti-androgen (10mg/kg ARN-509 or enzalutamide) until emergence of resistance. Resistant tissues continued to be exposed to anti-androgen through time of harvest. LREX' (LnCaP/AR Resistant to Enzalutamide Xenograft Derived) was derived from an enzalutamide resistant xenograft and was re-injected into castrate mice undergoing continual treatment with enzalutamide. The GR probe on the Illumina array failed to detect GR expression. Therefore, GR expression as determined by qPCR is annotated separately. Of the 10 control tissues, 8 were analyzed twice (technical duplicates annotated as A and B).
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