Design, synthesis, and evaluation of antitumor activity in Pseudolaric acid B Azole derivatives: Novel and potent angiogenesis inhibitor via regulation of the PI3K/AKT and MAPK mediated HIF-1/VEGF signaling pathway

Deng, Hao; Xu, Qian; Li, Xiao-Ting; Huang, Xing; Liu, Jin-Ying; Yan, Rui; Quan, Zhe-Shan; Shen, Qing-Kun; Guo, Hong-Yan

doi:10.1016/j.ejmech.2024.116813

European Journal of Medicinal Chemistry

2024

DOI: 10.1016/j.ejmech.2024.116813

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Design, synthesis, and evaluation of antitumor activity in Pseudolaric acid B Azole derivatives: Novel and potent angiogenesis inhibitor via regulation of the PI3K/AKT and MAPK mediated HIF-1/VEGF signaling pathway

Hao Deng,

Qian Xu,

Xiao-Ting Li

et al.

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2024

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Machine learning model reveals the role of angiogenesis and EMT genes in glioma patient prognosis and immunotherapy

Feng,

Zhu,

Qin

et al. 2024

Biol Direct

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Gliomas represent a highly aggressive class of tumors located in the brain. Despite the availability of multiple treatment modalities, the prognosis for patients diagnosed with glioma remains unfavorable. Therefore, further exploration of new biomarkers is crucial to enhance the prognostic assessment of glioma and to investigate more effective treatment options. In this research, we utilized multiple machine learning techniques to assess the significance of genes related to angiogenesis and epithelial-mesenchymal transition (EMT) in the context of prognosis and treatment for glioma patients. The random forest algorithm highlighted the significance of CALU, and further analysis indicated that the effect of CALU on glioma progression may be regulated by MYC. Different machine learning approaches were employed in our investigation to uncover crucial genes associated with angiogenesis and EMT in glioma. Our findings verify the connection between these genes and the prognosis of patients with glioma, as well as the results of immunotherapeutic interventions. Notably, through experimental verification, we identified CALU as a new prognostic marker for glioma, and inhibiting the expression of CALU can impede the progression of glioma. Supplementary Information The online version contains supplementary material available at 10.1186/s13062-024-00565-z.

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Machine learning model reveals the role of angiogenesis and EMT genes in glioma patient prognosis and immunotherapy

Feng,

Zhu,

Qin

et al. 2024

Biol Direct

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Design, synthesis, and evaluation of antitumor activity in Pseudolaric acid B Azole derivatives: Novel and potent angiogenesis inhibitor via regulation of the PI3K/AKT and MAPK mediated HIF-1/VEGF signaling pathway

Cited by 1 publication

References 50 publications

Machine learning model reveals the role of angiogenesis and EMT genes in glioma patient prognosis and immunotherapy

Machine learning model reveals the role of angiogenesis and EMT genes in glioma patient prognosis and immunotherapy

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