Dataset Information

Unveiling a Ghost Proteome in the Glioblastoma Non-Coding RNAs.

ABSTRACT: Glioblastoma is the most common brain cancer in adults. Nevertheless, the median survival time is 15 months, if treated with at least a near total resection and followed by radiotherapy in association with temozolomide. In glioblastoma (GBM), variations of non-coding ribonucleic acid (ncRNA) expression have been demonstrated in tumor processes, especially in the regulation of major signaling pathways. Moreover, many ncRNAs present in their sequences an Open Reading Frame (ORF) allowing their translations into proteins, so-called alternative proteins (AltProt) and constituting the "ghost proteome." This neglected world in GBM has been shown to be implicated in protein-protein interaction (PPI) with reference proteins (RefProt) reflecting involvement in signaling pathways linked to cellular mobility and transfer RNA regulation. More recently, clinical studies have revealed that AltProt is also involved in the patient's survival and bad prognosis. We thus propose to review the ncRNAs involved in GBM and highlight their function in the disease.

SUBMITTER: Cardon T

PROVIDER: S-EPMC8733697 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Unveiling a Ghost Proteome in the Glioblastoma Non-Coding RNAs.

Cardon Tristan T Fournier Isabelle I Salzet Michel M

Frontiers in cell and developmental biology 20211223

Glioblastoma is the most common brain cancer in adults. Nevertheless, the median survival time is 15 months, if treated with at least a near total resection and followed by radiotherapy in association with temozolomide. In glioblastoma (GBM), variations of non-coding ribonucleic acid (ncRNA) expression have been demonstrated in tumor processes, especially in the regulation of major signaling pathways. Moreover, many ncRNAs present in their sequences an Open Reading Frame (ORF) allowing their tra ...[more]

PMID: 35004666

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Project description:Glioblastoma multiforme represents the most prevalent primary malignant brain tumour, while long non-coding RNA assumes a pivotal role in the pathogenesis and progression of glioblastoma multiforme. Nonetheless, the successful delivery of long non-coding RNA-based therapeutics to the tumour site has encountered significant obstacles attributable to inadequate biocompatibility and inefficient drug delivery systems. In this context, the use of a biofunctional surface modification of graphene oxide has emerged as a promising strategy to surmount these challenges. By changing the surface of graphene oxide, enhanced biocompatibility can be achieved, facilitating efficient transport of long non-coding RNA-based therapeutics specifically to the tumour site. This innovative approach presents the opportunity to exploit the therapeutic potential inherent in long non-coding RNA biology for treating glioblastoma multiforme patients. This study aimed to extract relevant genes from The Cancer Genome Atlas database and associate them with long non-coding RNAs to identify graphene therapy-related long non-coding RNA. We conducted a series of analyses to achieve this goal, including univariate Cox regression, least absolute shrinkage and selection operator regression and multivariate Cox regression. The resulting graphene therapy-related long non-coding RNAs were utilized to develop a risk score model. Subsequently, we conducted Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses on the identified graphene therapy-related long non-coding RNAs. Additionally, we employed the risk model to construct the tumour microenvironment model and analyse drug sensitivity. To validate our findings, we referenced the IMvigor210 immunotherapy model. Finally, we investigated differences in the tumour stemness index. Through our investigation, we identified four promising graphene therapy-related long non-coding RNAs (AC011405.1, HOXC13-AS, LINC01127 and LINC01574) that could be utilized for treating glioblastoma multiforme patients. Furthermore, we identified 16 compounds that could be utilized in graphene therapy. Our study offers novel insights into the treatment of glioblastoma multiforme, and the identified graphene therapy-related long non-coding RNAs and compounds hold promise for further research in this field. Furthermore, additional biological experiments will be essential to validate the clinical significance of our model. These experiments can help confirm the potential therapeutic value and efficacy of the identified graphene therapy-related long non-coding RNAs and compounds in treating glioblastoma multiforme.

Dataset Information

Unveiling a Ghost Proteome in the Glioblastoma Non-Coding RNAs.

Publications

Unveiling a Ghost Proteome in the Glioblastoma Non-Coding RNAs.

Similar Datasets

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