Journal
MOLECULAR SYSTEMS BIOLOGY
Volume 17, Issue 9, Pages -Publisher
WILEY
DOI: 10.15252/msb.202010105
Keywords
cell state; cellular barcoding; patient-derived brain tumor cells; single-cell lineage tracing; time-dependent computational models
Categories
Funding
- Swedish Cancer Society
- Swedish Childhood Cancer Foundation
- Swedish Research Council
- Swedish Strategic Research Foundation
- Uppsala University
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The research establishes quantitative models of time-dependent transcriptional variation of patient-derived glioblastoma cells, revealing a hierarchical and plastic organization of GBM with cell state switching rates and patterns being partly patient-specific. Therapeutic interventions have complex dynamic effects, including inhibiting specific states and altering differentiation.
Tumor cell heterogeneity is a crucial characteristic of malignant brain tumors and underpins phenomena such as therapy resistance and tumor recurrence. Advances in single-cell analysis have enabled the delineation of distinct cellular states of brain tumor cells, but the time-dependent changes in such states remain poorly understood. Here, we construct quantitative models of the time-dependent transcriptional variation of patient-derived glioblastoma (GBM) cells. We build the models by sampling and profiling barcoded GBM cells and their progeny over the course of 3 weeks and by fitting a mathematical model to estimate changes in GBM cell states and their growth rates. Our model suggests a hierarchical yet plastic organization of GBM, where the rates and patterns of cell state switching are partly patient-specific. Therapeutic interventions produce complex dynamic effects, including inhibition of specific states and altered differentiation. Our method provides a general strategy to uncover time-dependent changes in cancer cells and offers a way to evaluate and predict how therapy affects cell state composition.
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