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Pre-determined diversity in resistant fates emerges from homogenous cells after anti-cancer drug treatment (single-cell data)

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE233766 | GEO | 2023/06/03

REPOSITORIES: GEO

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Pre-determined diversity in resistant fates emerges from homogenous cells after anti-cancer drug treatment

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

Variability within rare cell states enables multiple paths towards drug resistance [WM989_DOT1Li]

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

Variability within rare cell states enables multiple paths towards drug resistance [WM989_WM983b]

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A Single Cell Transcriptomic Analysis of Human Neocortical Development

Project description:<p>Defining the number, proportion, or lineage of distinct cell types in the developing human brain is an important goal of modern brain research. We produced single cell transcriptomic profiles for 40,000 cells at mid-gestation to define deep expression profiles corresponding to all known major cell types at this developmental period and compare this with bulk tissue profiles. We identified multiple transcription factors (TFs) and co-factors expressed in specific cell types, including multiple new cell-type-specific relationships, providing an unprecedented resource for understanding human neocortical development and evolution. This includes the first single-cell characterization of human subplate neurons and subtypes of developing glutamatergic and GABAergic neurons. We also used these data to deconvolute single cell regulatory networks that connect regulatory elements and transcriptional drivers to single cell gene expression programs in the developing CNS. We characterized major developmental trajectories that tie cell cycle progression with early cell fate decisions during early neurogenesis. Remarkably, we found that differentiation occurs on a transcriptomic continuum, so that differentiating cells not only express the few key TFs that drive cell fates, but express broad, mixed cell-type transcriptomes prior to telophase. Finally, we mapped neuropsychiatric disease genes to specific cell types, implicating dysregulation of specific cell types in ASD, ID, and epilepsy, as the mechanistic underpinnings of several neurodevelopmental disorders. Together these results provide an extensive catalog of cell types in human neocortex and extend our understanding of early cortical development, human brain evolution and the cellular basis of neuropsychiatric disease.</p>

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Clonal differences underlie variable responses to sequential and prolonged treatment

Project description:Cancer cells exhibit dramatic differences in gene expression at the single-cell level which can predict whether they become resistant to treatment. Treatment perpetuates this heterogeneity, resulting in a diversity of cell states among resistant clones. However, it remains unclear whether these differences lead to distinct responses when another treatment is applied or the same treatment is continued. In this study, we combined single-cell RNA-sequencing with barcoding to track resistant clones through prolonged and sequential treatments. We found that cells within the same clone have similar gene expression states after multiple rounds of treatment. Moreover, we demonstrated that individual clones have distinct and differing fates, including growth, survival, or death, when subjected to a second treatment or when the first treatment is continued. By identifying gene expression states that predict clone survival, this work provides a foundation for selecting optimal therapies that target the most aggressive resistant clones within a tumor.

2024-01-23 | GSE253739 | GEO

Resolving fate and transcriptome of hematopoietic stem cell clones [LT_ST_HSC]

Project description:Hematopoietic stem cell (HSC) differentiation into mature lineages has been studied under physiological conditions in vivo by genetic barcoding-driven lineage tracing. HSC clones differ in output (differentiation-inactive versus differentiation-active), and in fates (multilineage versus lineage-restricted). Single-cell sequencing data revealed transcriptome diversity of HSC and progenitors, and suggested differentiation pathways. However, molecular hallmarks of functionally distinct HSC clones have not been resolved because existing lineage tracing experiments did not provide transcriptomes, and single cell RNA sequencing lacked information on precursor-product relationships, and hence fate. To close this gap, here we introduce PolyloxExpress, a Cre recombinase-dependent DNA substrate for in situ barcoding in mice that is expressed as mRNA. PolyloxExpress barcoding allows parallel readout of clonal HSC fates (via comparison of barcodes in HSC and mature lineages), and transcriptomes (via single-cell RNA sequencing and barcode matching). Analysing a total of 91 individual HSC clones, we show that differentiation-inactive versus differentiation-active HSC clones reside in different regions of the transcriptional landscape. Inactive HSC clones are closer to the origin of the transcriptional trajectory, yet are proliferatively not more quiescent than active clones. Multilineage versus myelo-erythroid fate-restricted HSC clones show very few transcriptional differences at the HSC stage, yet pronounced fate-specific profiles at the multipotent progenitor stage. Projecting HSC clones with defined fates onto transcriptional landscapes provides a basis for future studies into the molecular determinants for stem cell fate.

2020-08-11 | GSE152555 | GEO

Resolving fate and transcriptome of hematopoietic stem cell clones [multiple cell types]

2020-08-11 | GSE144273 | GEO

Resolving fate and transcriptome of hematopoietic stem cell clones [multiple cell types]

Project description:Resolving fate and transcriptome of hematopoietic stem cell clones [multiple cell types]

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MicroRNA expression data from leukemia and breast cancer cell lines with/without treatment with microparticles

Project description:Microparticles (MPs) comprise the major source of systemic RNA including microRNA (miRNA), the aberrant expression of which appears to be associated with stage, progression and spread of many cancers. We have shown MPs to transfer multidrug resistance proteins accross both haematological and and non-haematological cancers. using microarray miRNA profiling analysis we now analyze changes in miRNA profiles of both cancer types following microparticle transfer. We identified certain upregulated miRNAs in both cancer types. Total RNA was extracted and pooled from duplicate experiments for hybridization on Affymetrix microarrays from (i) the parental drug sensitive leukaemia (CEM) or breast cancer (MCF-7) cells, (ii) their Multidrug Resistant strains leukaemia (VLB100) or breast cancer ( DX cells), (iii) the microparticles isolated from the resistant cells: VLBMP or DXMP, and (iv) the cocultured samples: sensitive cell co-incubated with MPs from their resistant cells ( leukaemia: CEM+VLBMP) or(breast cancer: MCF-7+DXMP). We sought to examine the miRNA profiles of the drug sensitve cells after MP transfer from drug resistant cells across leukaemia nd breact cancer cell lines.

2012-06-08 | E-GEOD-34560 | biostudies-arrayexpress

Heritable states influence stem cell fates upon acquisition of cancer mutations

Project description:Tumors with the same driver mutations can display a striking variation in their progression and treatment response, but the origins of this variation are still unclear. In this study, we use state-fate analysis to unveil that heritable stem cell states can influence how individual cells respond to the acquisition of the same cancer mutation. We develop a new methodological pipeline, single-cell Tracking of Recombinase Activation And Clonal Kinetics, and apply it to hematopoietic stem cells carrying Cre/Flp-conditional leukemia alleles. Tracking the gene expression changes and expansion kinetics of a common set of stem cell clones, with and without the same myeloid leukemia mutations, we unveil a striking heterogeneity in the malignant fates of diverse stem cells. First, we define that heritable clonal states persist in expansion cultures and cause the selection of a small group of clones with a specific fitness signature. Then, using mouse models of the most frequent initiating mutations, we define that these pre-existent stem cell states influence the mutation-induced changes in expansion, fate, and malignant gene expression programs. Initiating driver mutations increase the survival probability of clones with low fitness through enhancing their stemness programs. Surprisingly, the fate of high-fitness stem-cell clones is sometimes reversed, producing more mature leukemias, yet still carrying markers of their cell of origin. We further validate these HSC-of-origin signatures in bulk and single-cell RNAseq datasets from cancer patients. Our findings suggest that aggressive premalignant clonal expansions arise from low-fitness stem cells more frequently than previously expected.

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