Glioblastoma is the most aggressive brain tumor and, even with the current multimodal therapy, is an invariably lethal cancer with a life expectancy that depends on the tumor subtype but, even in the most favorable cases, rarely exceeds 2 years. Epigenetic factors play an important role in gliomagenesis, are strong predictors of outcome, and are important determinants for the resistance to radio- and chemotherapy. The latest addition to the epigenetic machinery is the noncoding RNA (ncRNA), that is, RNA molecules that are not translated into a protein and that exert their function by base pairing with other nucleic acids in a reversible and nonmutational mode. MicroRNAs (miRNA) are a class of ncRNA of about 22 bp that regulate gene expression by binding to complementary sequences in the mRNA and silence its translation into proteins. MicroRNAs reversibly regulate transcription through nonmutational mechanisms; accordingly, they can be considered as epigenetic effectors. In this review, we will discuss the role of miRNA in glioma focusing on their role in drug resistance and on their potential applications in the therapy of this tumor.
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http://dx.doi.org/10.1155/2017/7639084 | DOI Listing |
Methods Mol Biol
December 2024
Department of Cancer Biology and Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA.
Non-coding RNAs (ncRNAs) play crucial roles in gene expression regulation, translation, and disease development, including cancer. They are classified by size in short and long non-coding RNAs. This chapter focuses on the functional implications of adenosine-to-inosine (A-to-I) RNA editing in both short (e.
View Article and Find Full Text PDFProg Biophys Mol Biol
December 2024
Guilan Road Trauma Research Center, Trauma Institute, Guilan University of Medical Sciences, Rasht, Iran; Neuroscience Research Center, Trauma Institute, Guilan University of Medical Sciences, Rasht, Iran. Electronic address:
Glioblastoma (GBM) is a very deadly type of brain tumor with a poor prognosis and a short survival rate. Recent advancements in understanding GBM's molecular and genetic characteristics have led to the development of various therapeutic and diagnostic strategies. Key elements such as microRNAs, lncRNAs, exosomes, angiogenesis, and chromatin modifications are highlighted, alongside significant epigenetic alterations that impact therapy and diagnosis.
View Article and Find Full Text PDFFASEB J
December 2024
Graduate Program in Biological Sciences: Biochemistry, Institute of Basic Health Sciences, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.
We explored key microRNAs (miRNAs) related to tumorigenesis and immune modulation in glioblastoma (GBM), employing in silico, in vitro, and ex vivo analysis along with an assessment of the cellular impacts resulting from miRNA inhibition. GBM and T cells miRNA expression profiles from public datasets were used to evaluate differentially expressed miRNAs (DEmiRNAs). Some DEmiRNAs were chosen for validation in GBM cell lines, primary cell cultures, and brain tumor patient samples, using RT-qPCR.
View Article and Find Full Text PDFExtracell Vesicles Circ Nucl Acids
July 2024
Laboratory of James G. Patton, Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA.
Aim: Extracellular communication via the transfer of vesicles and nanoparticles is now recognized to play an important role in tumor microenvironment interactions. Cancer cells upregulate and secrete abundant levels of and that can alter gene expression in donor and recipient cells. In this study, we sought to identify targets of and and conclusively demonstrate that microRNAs (miRNAs) can be functionally transferred from donor to recipient cells.
View Article and Find Full Text PDFBrief Bioinform
November 2024
State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan, Nanjing 210023, China.
High-throughput sequencing methods have brought about a huge change in omics-based biomedical study. Integrating various omics data is possibly useful for identifying some correlations across data modalities, thus improving our understanding of the underlying biological mechanisms and complexity. Nevertheless, most existing graph-based feature extraction methods overlook the complementary information and correlations across modalities.
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