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Temozolomide-Induced RNA Interactome Uncovers Novel LncRNA Regulatory Loops in Glioblastoma
SIMPLE SUMMARY: Glioblastoma (GBM) is the most aggressive brain tumor and most resistant to therapy. The identification of novel predictive biomarkers or targets to counteract chemoresistance, requires a better understanding of the GBM primary response to therapy. The aim of our study was to assess...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7563839/ https://www.ncbi.nlm.nih.gov/pubmed/32927769 http://dx.doi.org/10.3390/cancers12092583 |
Sumario: | SIMPLE SUMMARY: Glioblastoma (GBM) is the most aggressive brain tumor and most resistant to therapy. The identification of novel predictive biomarkers or targets to counteract chemoresistance, requires a better understanding of the GBM primary response to therapy. The aim of our study was to assess the molecular response of GBM to the standard of care chemotherapy by temozolomide (TMZ). We established a comprehensive map of gene expression changes after treatment and discovered that GBM cells elicit a coordinated gene expression program after chemotherapy that differs between sensitive and resistant cells. We found that a novel class of genes expressed as long non-coding RNAs (lncRNAs) is involved in gene regulatory circuits in GBM and could represent novel markers of GBM patient prognosis. By shedding light on the involvement of the non-coding genome in GBM, our results may provide new mechanistic insight on lncRNAs and their importance in chemoresistance. ABSTRACT: Resistance to chemotherapy by temozolomide (TMZ) is a major cause of glioblastoma (GBM) recurrence. So far, attempts to characterize factors that contribute to TMZ sensitivity have largely focused on protein-coding genes, and failed to provide effective therapeutic targets. Long noncoding RNAs (lncRNAs) are essential regulators of epigenetic-driven cell diversification, yet, their contribution to the transcriptional response to drugs is less understood. Here, we performed RNA-seq and small RNA-seq to provide a comprehensive map of transcriptome regulation upon TMZ in patient-derived GBM stem-like cells displaying different drug sensitivity. In a search for regulatory mechanisms, we integrated thousands of molecular associations stored in public databases to generate a background “RNA interactome”. Our systems-level analysis uncovered a coordinated program of TMZ response reflected by regulatory circuits that involve transcription factors, mRNAs, miRNAs, and lncRNAs. We discovered 22 lncRNAs involved in regulatory loops and/or with functional relevance in drug response and prognostic value in gliomas. Thus, the investigation of TMZ-induced gene networks highlights novel RNA-based predictors of chemosensitivity in GBM. The computational modeling used to identify regulatory circuits underlying drug response and prioritizing gene candidates for functional validation is applicable to other datasets. |
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