Development of an MCL-1-related prognostic signature and inhibitors screening for glioblastoma

作者：Ao Zhang, Zhen Guo, Jia-xin Ren, Hongyu Chen, Wenzhuo Yang, Yang Zhou, Lin Pan, Zhuopeng Chen, Fei Ren, Youqi Chen, Menghan Zhang, Fei Peng, Wanting Chen, Xinhui Wang, Zhiyun Zhang, Hui Wu · 发表于：Frontiers in Pharmacology · 年份：2023 · DOI：10.3389/fphar.2023.1162540 · 被引用次数：8 · 研究领域：Ferroptosis and cancer prognosis、MicroRNA in disease regulation、interferon and immune responses

Introduction: The effect of the conventional treatment methods of glioblastoma (GBM) is poor and the prognosis of patients is poor. The expression of MCL-1 in GBM is significantly increased, which shows a high application value in targeted therapy. In this study, we predicted the prognosis of glioblastoma patients, and therefore constructed MCL-1 related prognostic signature (MPS) and the development of MCL-1 small molecule inhibitors. Methods: In this study, RNA-seq and clinical data of 168 GBM samples were obtained from the TCGA website, and immunological analysis, differential gene expression analysis and functional enrichment analysis were performed. Subsequently, MCL-1-associated prognostic signature (MPS) was constructed and validated by LASSO Cox analysis, and a nomogram was constructed to predict the prognosis of patients. Finally, the 17931 small molecules downloaded from the ZINC15 database were screened by LibDock, ADME, TOPKAT and CDOCKER modules and molecular dynamics simulation in Discovery Studio2019 software, and two safer and more effective small molecule inhibitors were finally selected. Results: Immunological analysis showed immunosuppression in the MCL1_H group, and treatment with immune checkpoint inhibitors had a positive effect. Differential expression gene analysis identified 449 differentially expressed genes. Build and validate MPS using LASSO Cox analysis. Use the TSHR HIST3H2A, ARGE OSMR, ARHGEF25 build risk score, proved that low risk group of pat...