Modeling glioblastoma heterogeneity as a dynamic network of cell states

Modeling glioblastoma heterogeneity as a dynamic network of cell states

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 su...

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Bibliographic Details
Main Authors: Dalmo, E. (Author), Doroszko, M. (Author), Elgendy, R. (Author), Jörnsten, R. (Author), Larsson, I. (Author), Nelander, S. (Author), Niklasson, M. (Author), Segerman, A. (Author), Westermark, B. (Author)
Format: Article
Language:English
Published: John Wiley and Sons Inc 2021
Subjects:
Article
astrocyte
bone morphogenetic protein 4
Brain Neoplasms
brain tumor
cancer cell
CD24 antigen
cell differentiation
cell growth
cell heterogeneity
Cell Line, Tumor
cell lineage
cell proliferation
cell state
cellular barcoding
controlled study
cyclin dependent kinase inhibitor 1A
flow cytometry
fluorescence activated cell sorting
gene set enrichment analysis
genetics
glioblastoma
Glioblastoma
Hermes antigen
human
human cell
Humans
Markov chain
mathematical model
Neoplasm Recurrence, Local
neural stem cell
oligodendrocyte precursor cell
patient-derived brain tumor cells
RNA
single cell analysis
single cell RNA seq
Single-Cell Analysis
single-cell lineage tracing
stochastic model
temozolomide
time-dependent computational models
transcription factor Sox2
transcription factor Sox4
transcriptome
tumor cell line
tumor recurrence
upregulation
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