8 research outputs found

    miR-96/HBP1/Wnt/β-catenin regulatory circuitry promotes glioma growth

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    AbstractWe found that miR-96 is overexpressed in glioma, and its level inversely correlates with the survival of patients. The reduction in miR-96 abundance suppresses the proliferation and colony formation of glioma cells. The tumorigenicity of U-87 MG cells is reduced by miR-96 silencing. miR-96 contributes to the activation of Wnt/β-catenin pathway in glioma cells. HMG-box transcription factor 1 (HBP-1), a Wnt/β-catenin pathway inhibitor, is suppressed by miR-96. The reactivation of Wnt/β-catenin signaling causes an increase in the proliferation of glioma cells, and a decrease in miR-96 expression. On the other hand, HBP1 silencing promotes miR-96 expression. Collectively, miR-96 contributes to the progression of glioma by enhancing the activation of the Wnt/β-catenin pathway, and the miR-96/HBP1/Wnt/β-catenin regulatory circuitry promotes the proliferation of glioma cells

    Unveiling the intratumoral microbiota within cancer landscapes

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    Summary: Recent advances in cancer research have unveiled a significant yet previously underappreciated aspect of oncology: the presence and role of intratumoral microbiota. These microbial residents, encompassing bacteria, fungi, and viruses within tumor tissues, have been found to exert considerable influence on tumor development, progression, and the efficacy of therapeutic interventions. This review aims to synthesize these groundbreaking discoveries, providing an integrated overview of the identification, characterization, and functional roles of intratumoral microbiota in cancer biology. We focus on elucidating the complex interactions between these microorganisms and the tumor microenvironment, highlighting their potential as novel biomarkers and therapeutic targets. The purpose of this review is to offer a comprehensive understanding of the microbial dimension in cancer, paving the way for innovative approaches in cancer diagnosis and treatment

    Role-based approaches for operational tasks modeling and flexible decomposition

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