bioRxivCancer BiologyPreprint
ASCL1 regulates neurodevelopmental transcription factors and cell cycle genes in glioblastoma
T. Y. Vue, R. Kollipara, M. D. Borromeo, T. Smith, T. Mashimo, D. K. Burns, R. M. Bachoo, J. E. Johnson
Abstract
Glioblastomas (GBMs) are incurable brain tumors with a high degree of cellular heterogeneity and genetic mutations. Transcription factors that normally regulate neural progenitors and glial development are aberrantly co-expressed in GBM, conferring cancer stem-like properties to drive tumor progression and therapeutic resistance. However, the functional role of individual transcription factors in GBMs in vivo remains elusive. Here, we demonstrate that the basic-helix-loop-helix (bHLH) transcription factor ASCL1 regulates transcriptional targets that are central to GBM development, including neural stem cell and glial transcription factors, oncogenic signaling molecules, chromatin modifying genes, and cell cycle and mitotic genes. We also show that the loss of ASCL1 significantly reduces the proliferation of GBMs induced in the brain of a genetically relevant glioma mouse model, resulting in extended survival times. RNA-seq analysis of mouse GBM tumors reveal that the loss of ASCL1 is associated with downregulation of cell cycle genes, illustrating an important role for ASCL1 in controlling the proliferation of GBM. TABLE OF CONTENTSO_ST_ABSMain PointsC_ST_ABSO_LIASCL1 is co-expressed with neural stem cell/glial transcription factors in GBM C_LIO_LIASCL1 binds to genes that are important for cell proliferation and cancer in the brain. C_LIO_LILoss of ASCL1 downregulates cell cycle genes and increase survival of glioma mouse model. C_LI Table of Content Image O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=178 SRC="FIGDIR/small/958132v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@8aa2d7org.highwire.dtl.DTLVardef@1c908edorg.highwire.dtl.DTLVardef@1690085org.highwire.dtl.DTLVardef@a13728_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: mouse
- assay: bulk RNA-seq
- research focus: cancer & tumor microenvironment
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
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