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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_WM983b]

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

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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.

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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

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