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bioRxiv · 10.1101/2023.01.20.524887

Identification of glioblastoma stem cell-associated lncRNAs using single-cell RNA-sequencing datasets

Abstract

Glioblastoma multiforme (GBM) is an aggressive, heterogeneous grade IV brain tumor. Glioblastoma stem cells (GSCs) initiate the tumor and are known culprits of therapy resistance. Mounting evidence has demonstrated a regulatory role of long non-coding RNAs (lncRNAs) in various biological processes, including pluripotency, differentiation, and tumorigenesis. A few studies have suggested that aberrant expression of lncRNAs is associated with GSCs. However, a comprehensive single-cell analysis of the GSC-associated lncRNA transcriptome has not been carried out. Here, we analyzed recently published single-cell RNA-sequencing datasets of adult human GBM tumors, GBM organoids, GSC-enriched GBM tumors, and developing human brains to identify lncRNAs highly expressed in GBM. To categorize GSC populations in the GBM tumors, we used the GSC marker genes SOX2, PROM1, FUT4, and L1CAM. We found three major GSC population clusters: radial glia, oligodendrocyte progenitor cells, and neurons. We found 10-100 lncRNAs significantly enriched in different GSC populations. We also validated the level of expression and localization of several GSC-enriched lncRNAs using qRT-PCR, single-molecule RNA FISH, and sub-cellular fractionation. We found that the radial glia GSC-enriched lncRNA PANTR1 is highly expressed in GSC lines and is localized to both the cytoplasmic and nuclear fractions. In contrast, the neuronal GSC-enriched lncRNAs LINC01563 and MALAT1 are highly enriched in the nuclear fraction of GSCs. Together, this study identified a panel of uncharacterized GSC-specific lncRNAs. These findings set the stage for future in-depth studies to examine their role in GBM pathology and their potential as biomarkers and/or therapeutic targets in GBM.

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BibTeXRIS

Hazra, R., Utama, R., Naik, P., Dobin, A., Spector, D.. 2023-01-21. Identification of glioblastoma stem cell-associated lncRNAs using single-cell RNA-sequencing datasets. https://doi.org/10.1101/2023.01.20.524887

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