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
Online Access:	View Fulltext in Publisher

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