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Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy
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Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy
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Journal Article
Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy
2020
Overview
Cancer stem cells are critical for cancer initiation, development, and treatment resistance. Our understanding of these processes, and how they relate to glioblastoma heterogeneity, is limited. To overcome these limitations, we performed single-cell RNA sequencing on 53586 adult glioblastoma cells and 22637 normal human fetal brain cells, and compared the lineage hierarchy of the developing human brain to the transcriptome of cancer cells. We find a conserved neural tri-lineage cancer hierarchy centered around glial progenitor-like cells. We also find that this progenitor population contains the majority of the cancer’s cycling cells, and, using RNA velocity, is often the originator of the other cell types. Finally, we show that this hierarchal map can be used to identify therapeutic targets specific to progenitor cancer stem cells. Our analyses show that normal brain development reconciles glioblastoma development, suggests a possible origin for glioblastoma hierarchy, and helps to identify cancer stem cell-specific targets.
Glioblastoma is thought to arise from neural stem cells. Here, to investigate this, the authors use single-cell RNA-sequencing to compare glioblastoma to the fetal human brain, and find a similarity between glial progenitor cells and a subpopulation of glioblastoma cells.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
/ 13/106
/ 13/31
/ 13/51
/ 14/19
/ 14/5
/ 38/91
/ 59/5
/ 64/60
/ Adult
/ Animals
/ Antineoplastic Agents, Alkylating - pharmacology
/ Brain
/ Cancer
/ Cell Survival - drug effects
/ Female
/ Fetus
/ Fetuses
/ Humanities and Social Sciences
/ Humans
/ Neoplastic Stem Cells - drug effects
/ Neoplastic Stem Cells - metabolism
/ RNA
/ Science
/ Sequence Analysis, RNA - methods
