Targeting WNT Signaling for Multifaceted Glioblastoma Therapy

McCord, Matthew; Mukouyama, Yoh‐suke; Gilbert, Mark R.; Jackson, Sadhana

doi:10.3389/fncel.2017.00318

Cited by 92 publications

(73 citation statements)

References 97 publications

(117 reference statements)

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“…To the best of our knowledge, this is the first to demonstrate that β-catenin regulates the intracellular effects of miR-24 on the viability and autophagy of glioma cells. The present results also provide a direct mechanistic basis to support the growing pharmaceutical interest in targeting WNT signaling in high grade brain tumors (26).…”

Section: Discussionsupporting

confidence: 59%

β‑catenin regulates effects of miR‑24 on the viability and autophagy of glioma cells

Chen

et al. 2019

Exp Ther Med

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Mutations of the β-catenin gene are common in various cancer types. MicroRNA (miR)-24 suppresses gene expression during the cell cycle. However, the effects of miR-24 on the cell viability and autophagy of glioma cells, and how these biological processes are regulated by β-catenin are largely unclear. The current study aimed to investigate the role of β-catenin in regulating the effects of miR-24 on the cell viability and autophagy of glioma cells. The expression levels of microtubule-associated proteins 1A/1B light chain 3B (LC3B) and Beclin1 were detected by immunohistochemistry and western blotting. Glioma C6 cells were transfected with miR-24 mimics, miR-24 inhibitors and negative control miRNAs. C6 cells transfected with miR-24 mimics or negative control miRNAs were treated with the β-catenin inhibitor, XAV-939. An MTT assay was utilized to evaluate the viability of C6 cells. The expression of miR-24 and mRNA expression of autophagy related 4a cysteine peptidase (ATG4A) were detected by quantitative polymerase chain reaction analysis. The protein expression of LC3B and Beclin1 decreased significantly in glioma tissue and glioma C6 cells compared with normal brain tissue. Compared with the negative control group, C6 cells transfected with miR-24 mimics exhibited significantly higher cell viability at 24 and 48 h, and those transfected with miR-24 inhibitors exhibited significantly lower cell viability at 48 h. XAV-939 decreased the stimulatory effects of miR-24 mimics on the viability of C6 cells. The expression of miR-24 significantly decreased and ATG4A mRNA significantly increased in C6 cells transfected with XAV-939 compared with those transfected with the negative control miRNA. XAV-939 attenuated the miR-24-induced decrease of the protein expression of LC3B and Beclin1, and decreased the stimulatory effects of miR-24 mimics on cell viability. In addition, XAV-939 attenuated the miR-24-induced decrease of autophagy marker expression by attenuating miR-24 expression and increasing ATG4A mRNA expression in glioma C6 cells. To the best of our knowledge, the present study is the first to demonstrate whether β-catenin regulates the intracellular effects of miR-24 on the viability and autophagy of glioma cells. The results also provide some mechanistic basis to the pharmaceutical targeting of WNT signaling in high grade glial tumors.

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Section: Discussionsupporting

confidence: 59%

β‑catenin regulates effects of miR‑24 on the viability and autophagy of glioma cells

Chen

et al. 2019

Exp Ther Med

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“…The Wnt signalling is an evolutionarily conserved pathway that plays very important roles during embryonic development and tumourigenesis . In the absence of Wnt ligand, cytoplasmic β‐catenin protein is constantly being degraded by the action of the destruction complex composed of Axin, APC and 2 phosphokinases: casein kinase 1 (CK1) and glycogen synthase kinase 3 (GSK3).…”

Section: Introductionmentioning

confidence: 99%

Different behaviour of DVL1, DVL2, DVL3 in astrocytoma malignancy grades and their association to TCF1 and LEF1 upregulation

Kafka

Bačić²,

Tomas

et al. 2018

J Cellular Molecular Medi

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Key regulators of the Wnt signalling, DVL1, DVL2 and DVL3, in astrocytomas of different malignancy grades were investigated. Markers for DVL1,DVL2 and DVL3 were used to detect microsatellite instability (MSI) and gross deletions (LOH), while immunohistochemistry and immunoreactivity score were used to determine the signal strengths of the three DVL proteins and transcription factors of the pathway, TCF1 and LEF1. Our findings demonstrated that MSI at all three DVL loci was constantly found across tumour grades with the highest number in grade II (P = 0.008). Collectively, LOHs were more frequent in high‐grade tumours than in low grade ones. LOHs of DVL3 gene were significantly associated with grade IV tumours (P = 0.007). The results on protein expressions indicated that high‐grade tumours expressed less DVL1 protein as compared with low grade ones. A significant negative correlation was established between DVL1 expression and malignancy grades (P < 0.001). The expression of DVL2 protein was found similar across grades, while DVL3 expression significantly increased with malignancy grades (P < 0.001). The signal strengths of expressed DVL1 and DVL3 were negatively correlated (P = 0.002). However, TCF1 and LEF1 were both significantly upregulated and increasing with astrocytoma grades (P = 0.001). A positive correlation was established between DVL3 and both TCF1 (P = 0.020) and LEF1 (P = 0.006) suggesting their joint involvement in malignant progression. Our findings suggest that DVL1 and DVL2 may be involved during early stages of the disease, while DVL3 may have a role in later phases and together with TCF1 and LEF1 promotes the activation of Wnt signalling.

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“…all have been reported as survival time related in GBM ( (McCord et al 2017) , (Liu et al 2015) . Interestingly (Bridge et al 2019) show that in GBM, EWSR1 is often fused with PATZ1 which was in the past related to worse survival rates (McCord et al 2017;Guadagno et al 2017) .…”

Section: Second-order Combined (Black) and Las Only Second-order Connmentioning

confidence: 95%

Knowledge guided multi-level network inference

Ogris

Arloth

et al. 2020

Preprint

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Constantly decreasing costs of high-throughput profiling on many molecular levels generate vast amounts of so-called multi-omics data. Studying one biomedical question on two or more omic levels provides deeper insights into underlying molecular processes or disease pathophysiology. For the majority of multi-omics data projects, the data analysis is performed level-wise, followed by a combined interpretation of results. Few exceptions exist, for example the pairwise integration for quantitative trait analysis. However, the full potential of integrated data analysis is not leveraged yet, presumably due to the complexity of the data and the lacking toolsets. Here we propose a versatile approach, to perform a multi-level integrated analysis: The Knowledge guIded Multi-Omics Network inference approach, KiMONo. KiMONo performs network inference using statistical modeling on top of a powerful knowledge-guided strategy exploiting prior information from biological sources. Within the resulting network, nodes represent features of all input types and edges refer to associations between them, e.g. underlying a disease. Our method infers the network by combining sparse grouped-LASSO regression with a genomic position-confined Biogrid protein-protein interaction prior. In a comprehensive evaluation, we demonstrate that our method is robust to noise and still performs on low-sample size data. Applied to the five-level data set of the publicly available Pan-cancer collection, KiMONO integrated mutation, epigenetics, transcriptomics, proteomics and clinical information, detecting cancer specific omic features. Moreover, we analysed a four-level data set from a major depressive disorder cohort, including genetic, epigenetic, transcriptional and clinical data. Here we demonstrated KiMONo's analytical power to identify expression quantitative trait methylation sites and loci and show it's advantage to state-of-the-art methods. Our results show the general applicability to the full spectrum multi-omics data and demonstrating that KiMONo is a powerful approach towards leveraging the full potential of data sets. The method is freely available as an R package ( https://github.com/cellmapslab/kimono ).

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Targeting WNT Signaling for Multifaceted Glioblastoma Therapy

Cited by 92 publications

References 97 publications

β‑catenin regulates effects of miR‑24 on the viability and autophagy of glioma cells

β‑catenin regulates effects of miR‑24 on the viability and autophagy of glioma cells

Different behaviour of DVL1, DVL2, DVL3 in astrocytoma malignancy grades and their association to TCF1 and LEF1 upregulation

Knowledge guided multi-level network inference

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