Upregulation of microRNA-21 (miR-21) is known to be strongly associated with the proliferation, invasion, and radio-resistance of glioma cells. However, the regulatory mechanism that governs the biogenesis of miR-21 in glioma is still unclear. Here, we demonstrate that the DEAD-box RNA helicase, DDX23, promotes miR-21 biogenesis at the post-transcriptional level. The expression of DDX23 was enhanced in glioma tissues compared to normal brain, and expression level of DDX23 was highly associated with poor survival of glioma patients. Specific knockdown of DDX23 expression suppressed glioma cell proliferation and invasion in vitro and in vivo, which is similar to the function of miR-21. We found that DDX23 increased the level of miR-21 by promoting primary-to-precursor processing of miR-21 through an interaction with the Drosha microprocessor. Mutagenesis experiments critically demonstrated that the helicase activity of DDX23 was essential for the processing (cropping) of miR-21, and we further found that ivermectin, a RNA helicase inhibitor, decreased miR-21 levels by potentially inhibiting DDX23 activity and blocked invasion and cell proliferation. Moreover, treatment of ivermectin decreased glioma growth in mouse xenografts. Taken together, these results suggest that DDX23 plays an essential role in glioma progression, and might thus be a potential novel target for the therapeutic treatment of glioma.
Epidermal growth factor receptor variant III (EGFRvIII) has been associated with glioma stemness, but the direct molecular mechanism linking the two is largely unknown. Here, we show that EGFRvIII induces the expression and secretion of pigment epithelium-derived factor (PEDF) via activation of signal transducer and activator of transcription 3 (STAT3), thereby promoting self-renewal and tumor progression of glioma stem cells (GSCs). Mechanistically, PEDF sustained GSC self-renewal by Notch1 cleavage, and the generated intracellular domain of Notch1 (NICD) induced the expression of Sox2 through interaction with its promoter region. Furthermore, a subpopulation with high levels of PEDF was capable of infiltration along corpus callosum. Inhibition of PEDF diminished GSC self-renewal and increased survival of orthotopic tumor-bearing mice. Together, these data indicate the novel role of PEDF as a key regulator of GSC and suggest clinical implications.
Glioma stemness has been recognized as the most important reason for glioma relapse and drug resistance. Differentiation of glioma stem cells (GSCs) has been implicated as a novel approach to target recurrent glioma. However, the detailed molecular mechanism involved in the differentiation of GSCs has not yet been elucidated. This study identified CPEB1 as the key modulator that induces the differentiation of GSCs at the post-transcriptional level. Gain and loss of function experiments showed that CPEB1 expression reduced sphere formation ability and the expression of stemness markers such as Nestin and Notch. To elucidate the detailed molecular mechanism underlying the action of CPEB1, we investigated the interacting ribonome of the CPEB1 complex using a Ribonomics approach. CPEB1 specifically suppressed the translation of HES1 and SIRT1 by interacting with a cytoplasmic polyadenylation element. The expression profile of CPEB1 negatively correlated with overall survival in glioma patients. Overexpression of CPEB1 decreased the number of GSCs in an orthotopically implanted glioma animal model. These results suggest that CPEB1-mediated translational control is essential for the differentiation of GSCs and provides novel therapeutic concepts for differentiation therapy.
Hepatocyte growth factor (HGF) and its receptor, cMET, play critical roles in cell proliferation, angiogenesis and invasion in a wide variety of cancers. We therefore examined the anti-tumor activity of the humanized monoclonal anti-HGF antibody, YYB-101, in nude mice bearing human glioblastoma xenografts as a single agent or in combination with temozolomide. HGF neutralization, The extracellular signal-related kinases 1 and 2 (ERK1/2) phosphorylation, and HGF-induced scattering were assessed in HGF-expressing cell lines treated with YYB-101. To support clinical development, we also evaluated the preclinical pharmacokinetics and toxicokinetics in cynomolgus monkeys, and human and cynomolgus monkey tissue was stained with YYB-101 to test tissue cross-reactivity. We found that YYB-101 inhibited cMET activation in vitro and suppressed tumor growth in the orthotopic mouse model of human glioblastoma. Combination treatment with YYB-101 and temozolomide decreased tumor growth and increased overall survival compared with the effects of either agent alone. Five cancer-related genes (TMEM119, FST, RSPO3, ROS1 and NBL1) were overexpressed in YYB-101-treated mice that showed tumor regrowth. In the tissue cross-reactivity assay, critical cross-reactivity was not observed. The terminal elimination half-life was 21.7 days. Taken together, the in vitro and in vivo data demonstrated the anti-tumor efficacy of YYB-101, which appeared to be mediated by blocking the HGF/cMET interaction. The preclinical pharmacokinetics, toxicokinetics and tissue cross-reactivity data support the clinical development of YYB-101 for advanced cancer.
Gait, the style of human walking, has been studied as a behavioral characteristic of an individual. Several studies have utilized gait to identify individuals with the aid of machine learning and computer vision techniques. However, there is a lack of studies on the nature of gait, such as the identification power or the uniqueness. This study aims to quantify the uniqueness of gait in a cohort. Three-dimensional full-body joint kinematics were obtained during normal walking trials from 488 subjects using a motion capture system. The joint angles of the gait cycle were converted into gait vectors. Four gait vectors were obtained from each subject, and all the gait vectors were pooled together. Two gait vectors were randomly selected from the pool and tested if they could be accurately classified if they were from the same person or not. The gait from the cohort was classified with an accuracy of 99.71% using the support vector machine with a radial basis function kernel as a classifier. Gait of a person is as unique as his/her facial motion and finger impedance, but not as unique as fingerprints.
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