Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma.
Human cancers are complex ecosystems composed of cells with distinct phenotypes, genotypes, and epigenetic states, but current models do not adequately reflect tumor composition in patients. We used single-cell RNA sequencing (RNA-seq) to profile 430 cells from five primary glioblastomas, which we found to be inherently variable in their expression of diverse transcriptional programs related to oncogenic signaling, proliferation, complement/immune response, and hypoxia. We also observed a continuum of stemness-related expression states that enabled us to identify putative regulators of stemness in vivo. Finally, we show that established glioblastoma subtype classifiers are variably expressed across individual cells within a tumor and demonstrate the potential prognostic implications of such intratumoral heterogeneity. Thus, we reveal previously unappreciated heterogeneity in diverse regulatory programs central to glioblastoma biology, prognosis, and therapy.
Duke Scholars
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- Single-Cell Analysis
- Sequence Analysis, RNA
- RNA, Messenger
- Prognosis
- Humans
- Glioblastoma
- Genetic Variation
- General Science & Technology
- Gene Expression Profiling
- Brain Neoplasms
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Single-Cell Analysis
- Sequence Analysis, RNA
- RNA, Messenger
- Prognosis
- Humans
- Glioblastoma
- Genetic Variation
- General Science & Technology
- Gene Expression Profiling
- Brain Neoplasms