Glioblastoma and MiRNAs

Ahmed, Swalih P.; Castresana, Javier S.; Shahi, Mehdi H.

doi:10.3390/cancers13071581

Cited by 30 publications

(20 citation statements)

References 68 publications

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“…Seven years after the discovery, the first human-encoded miRNA Let-7 was described [ 61 ]. Currently, more than 3000 miRNAs are known to be present in the human genome and involved in numerous biological processes in almost all body fluids [ 62 , 63 ]. In 2013, the first miRNA mimic MRX34 (mimic of endogenous miR-34 that suppresses oncogenesis) entered into the clinical trials [ 64 ].…”

Section: Mirnas Targeting Dkk1 Expressionmentioning

confidence: 99%

Perspectives on miRNAs Targeting DKK1 for Developing Hair Regeneration Therapy

Papukashvili

Rcheulishvili

Liu

et al. 2021

Cells

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Androgenetic alopecia (AGA) remains an unsolved problem for the well-being of humankind, although multiple important involvements in hair growth have been discovered. Up until now, there is no ideal therapy in clinical practice in terms of efficacy and safety. Ultimately, there is a strong need for developing a feasible remedy for preventing and treating AGA. The Wnt/β-catenin signaling pathway is critical in hair restoration. Thus, AGA treatment via modulating this pathway is rational, although challenging. Dickkopf-related protein 1 (DKK1) is distinctly identified as an inhibitor of canonical Wnt/β-catenin signaling. Thus, in order to stimulate the Wnt/β-catenin signaling pathway, inhibition of DKK1 is greatly demanding. Studying DKK1-targeting microRNAs (miRNAs) involved in the Wnt/β-catenin signaling pathway may lay the groundwork for the promotion of hair growth. Bearing in mind that DKK1 inhibition in the balding scalp of AGA certainly makes sense, this review sheds light on the perspectives of miRNA-mediated hair growth for treating AGA via regulating DKK1 and, eventually, modulating Wnt/β-catenin signaling. Consequently, certain miRNAs regulating the Wnt/β-catenin signaling pathway via DKK1 inhibition might represent attractive candidates for further studies focusing on promoting hair growth and AGA therapy.

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Section: Mirnas Targeting Dkk1 Expressionmentioning

confidence: 99%

Perspectives on miRNAs Targeting DKK1 for Developing Hair Regeneration Therapy

Papukashvili

Rcheulishvili

Liu

et al. 2021

Cells

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“…We found that miR-148a and miR-92a have been reported by our previous GBM study using the relative regression method 27 . In another study, miR-92 was also reported 42 . Of course, the presence of miR-21 and miR-10b among these miRNAs was the beginning of this study, and it is also a feedback support for the results obtained.…”

Section: Discussionmentioning

confidence: 88%

Machine learning and bioinformatics approaches for classification and clinical detection of bevacizumab responsive glioblastoma subtypes based on miRNA expression

Shi

2022

Sci Rep

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For the precise treatment of patients with glioblastoma multiforme (GBM), we classified and detected bevacizumab (BVZ)-responsive subtypes of GBM and found their differential expression (DE) of miRNAs and mRNAs, clinical characteristics, and related functional pathways. Based on miR-21 and miR-10b expression z-scores, approximately 30% of GBM patients were classified as having the GBM BVZ-responsive subtype. For this subtype, GBM patients had a significantly shorter survival time than other GBM patients (p = 0.014), and vascular endothelial growth factor A (VEGF) methylation was significantly lower than that in other GBM patients (p = 0.005). It also revealed 14 DE miRNAs and 7 DE mRNAs and revealed functional characteristics between GBM BVZ subgroups. After comparing several machine learning algorithms, the construction and cross-validation of the SVM classifier were performed. For clinical use, miR-197 was optimized and added to the miRNA panel for better classification. Afterwards, we validated the classifier with several GBM datasets and discovered some key related issues. According to this study, GBM BVZ subtypes can be classified and detected by a combination of SVM classifiers and miRNA panels in existing tissue GBM datasets. With certain modifications, the classifier may be used for the classification and detection of GBM BVZ subtypes for future clinical use.

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“…In this case, some of the miRNAs acted as apoptotic genes, suppressing the proliferation and survival of glioblastomas or silencers of anti-apoptotic genes, thus favoring tumor growth. This potentiates the use of miRNA signatures as diagnostic biomarkers for glioblastoma, primarily with the use of liquid biopsies, which are easily obtainable [ 4 ]. miRNAs have been shown to regulate epithelial to mesenchymal transition (EMT) [ 5 ], a process whereby epithelial cells undergo biological processes that allow them to take on the phenotype of mesenchymal stem cells and adopt their enhanced migratory ability, invasive capacity and increased ability to resist apoptosis [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

MicroRNA Interrelated Epithelial Mesenchymal Transition (EMT) in Glioblastoma

Damane

Hull

Reis

et al. 2022

Genes

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MicroRNAs (miRNA) are small non-coding RNAs that are 20–23 nucleotides in length, functioning as regulators of oncogenes or tumor suppressor genes. They are molecular modulators that regulate gene expression by suppressing gene translation through gene silencing/degradation, or by promoting translation of messenger RNA (mRNA) into proteins. Circulating miRNAs have attracted attention as possible prognostic markers of cancer, which could aid in the early detection of the disease. Epithelial to mesenchymal transition (EMT) has been implicated in tumorigenic processes, primarily by promoting tumor invasiveness and metastatic activity; this is a process that could be manipulated to halt or prevent brain metastasis. Studies show that miRNAs influence the function of EMT in glioblastomas. Thus, miRNA-related EMT can be exploited as a potential therapeutic target in glioblastomas. This review points out the interrelation between miRNA and EMT signatures, and how they can be used as reliable molecular signatures for diagnostic purposes or targeted therapy in glioblastomas.

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Glioblastoma and MiRNAs

Cited by 30 publications

References 68 publications

Perspectives on miRNAs Targeting DKK1 for Developing Hair Regeneration Therapy

Perspectives on miRNAs Targeting DKK1 for Developing Hair Regeneration Therapy

Machine learning and bioinformatics approaches for classification and clinical detection of bevacizumab responsive glioblastoma subtypes based on miRNA expression

MicroRNA Interrelated Epithelial Mesenchymal Transition (EMT) in Glioblastoma

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