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Sorting nexin 10 sustains PDGF receptor signaling in glioblastoma stem cells via endosomal protein sorting
Ryan C. Gimple, … , Sameer Agnihotri, Jeremy N. Rich
Ryan C. Gimple, … , Sameer Agnihotri, Jeremy N. Rich
Published February 16, 2023
Citation Information: JCI Insight. 2023;8(6):e158077. https://doi.org/10.1172/jci.insight.158077.
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Research Article Oncology Stem cells

Sorting nexin 10 sustains PDGF receptor signaling in glioblastoma stem cells via endosomal protein sorting

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Abstract

Glioblastoma is the most malignant primary brain tumor, the prognosis of which remains dismal even with aggressive surgical, medical, and radiation therapies. Glioblastoma stem cells (GSCs) promote therapeutic resistance and cellular heterogeneity due to their self-renewal properties and capacity for plasticity. To understand the molecular processes essential for maintaining GSCs, we performed an integrative analysis comparing active enhancer landscapes, transcriptional profiles, and functional genomics profiles of GSCs and non-neoplastic neural stem cells (NSCs). We identified sorting nexin 10 (SNX10), an endosomal protein sorting factor, as selectively expressed in GSCs compared with NSCs and essential for GSC survival. Targeting SNX10 impaired GSC viability and proliferation, induced apoptosis, and reduced self-renewal capacity. Mechanistically, GSCs utilized endosomal protein sorting to promote platelet-derived growth factor receptor β (PDGFRβ) proliferative and stem cell signaling pathways through posttranscriptional regulation of the PDGFR tyrosine kinase. Targeting SNX10 expression extended survival of orthotopic xenograft–bearing mice, and high SNX10 expression correlated with poor glioblastoma patient prognosis, suggesting its potential clinical importance. Thus, our study reveals an essential connection between endosomal protein sorting and oncogenic receptor tyrosine kinase signaling and suggests that targeting endosomal sorting may represent a promising therapeutic approach for glioblastoma treatment.

Authors

Ryan C. Gimple, Guoxin Zhang, Shuai Wang, Tengfei Huang, Jina Lee, Suchet Taori, Deguan Lv, Deobrat Dixit, Matthew E. Halbert, Andrew R. Morton, Reilly L. Kidwell, Zhen Dong, Briana C. Prager, Leo J.Y. Kim, Zhixin Qiu, Linjie Zhao, Qi Xie, Qiulian Wu, Sameer Agnihotri, Jeremy N. Rich

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Figure 1

Integrated epigenetic and transcriptomic analysis of glioblastoma stem cells and non-neoplastic neural stem cells identified essential gene candidates.

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Integrated epigenetic and transcriptomic analysis of glioblastoma stem c...
(A) Summary figure of RNA-seq and H3K27ac ChIP-seq performed in NSCs (n = 5) and patient-derived GSCs (n = 38). (B) Volcano plot showing differentially expressed genes by RNA-seq (27) between GSCs and NSCs. Differential expression cutoffs were (i) log2-transformed mRNA expression fold change greater than 2 and (ii) adjusted P value less than 1 × 10–3. (C) Gene set enrichment pathway connectivity diagram depicting gene sets enriched among genes upregulated in GSCs versus NSCs by RNA-seq. (D) MA plot showing differential H3K27ac ChIP-seq peaks (27) between GSCs (n = 38) and NSCs (n = 5). Differential peak cutoffs were (i) log2-transformed H3K27ac signal fold change greater than 2 and (ii) adjusted P value less than 1 × 10–3. (E) Gene set enrichment pathway connectivity diagram depicting gene sets enriched among genes upregulated in GSCs versus NSCs by H3K27ac ChIP-seq. (F) The fraction of GSC-specific H3K27ac peaks displayed in D that are components of super-enhancers versus typical enhancers. (G) Venn diagram overlap of genes upregulated in GSCs identified by both RNA-seq and ChIP-seq analysis in comparisons between GSCs and NSCs.

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