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Potential of long non-coding RNAs as a therapeutic target and molecular markers in glioblastoma pathogenesis

Glioblastoma (GB) is by far the most hostile type of malignant tumor that primarily affects the brain and spine, derived from star-shaped glial cells that are astrocytes and oligodendrocytes. Despite of significant efforts in recent years in glioblastoma research, the clinical efficacy of existing m...

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Detalles Bibliográficos
Autor principal: Chaudhary, Rishabh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988331/
https://www.ncbi.nlm.nih.gov/pubmed/33786397
http://dx.doi.org/10.1016/j.heliyon.2021.e06502
Descripción
Sumario:Glioblastoma (GB) is by far the most hostile type of malignant tumor that primarily affects the brain and spine, derived from star-shaped glial cells that are astrocytes and oligodendrocytes. Despite of significant efforts in recent years in glioblastoma research, the clinical efficacy of existing medical intervention is still limited and very few potential diagnostic markers are available. Long non-coding RNAs (lncRNAs) that lacks protein-coding capabilities were previously thought to be “junk sequences” in mammalian genomes are quite indispensible epigenetic regulators that can positively or negatively regulate gene expression and nuclear architecture, with significant roles in the initiation and development of tumors. Nevertheless, the precise mechanism of these distortedly expressed lncRNAs in glioblastoma pathogenesis is not yet fully understood. Since the advent of high-throughput sequencing technologies, more and more research have elucidated that lncRNAs are one of the most promising prognostic biomarkers and therapeutic targets for glioblastoma. In this paper, I briefly outlined the existing findings of lncRNAs. And also summarizes the profiles of different lncRNAs that have been broadly classified in glioblastoma research, with emphasis on both their prognostic and therapeutic values.