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

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 gliobl...

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Autores principales: Zhang, Ao, Guo, Zhen, Ren, Jia-xin, Chen, Hongyu, Yang, Wenzhuo, Zhou, Yang, Pan, Lin, Chen, Zhuopeng, Ren, Fei, Chen, Youqi, Zhang, Menghan, Peng, Fei, Chen, Wanting, Wang, Xinhui, Zhang, Zhiyun, Wu, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10394558/
https://www.ncbi.nlm.nih.gov/pubmed/37538176
http://dx.doi.org/10.3389/fphar.2023.1162540
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author Zhang, Ao
Guo, Zhen
Ren, Jia-xin
Chen, Hongyu
Yang, Wenzhuo
Zhou, Yang
Pan, Lin
Chen, Zhuopeng
Ren, Fei
Chen, Youqi
Zhang, Menghan
Peng, Fei
Chen, Wanting
Wang, Xinhui
Zhang, Zhiyun
Wu, Hui
author_facet Zhang, Ao
Guo, Zhen
Ren, Jia-xin
Chen, Hongyu
Yang, Wenzhuo
Zhou, Yang
Pan, Lin
Chen, Zhuopeng
Ren, Fei
Chen, Youqi
Zhang, Menghan
Peng, Fei
Chen, Wanting
Wang, Xinhui
Zhang, Zhiyun
Wu, Hui
author_sort Zhang, Ao
collection PubMed
description 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 patients prognosis is better. Univariate and multivariate analysis proved that risk could be used as an independent predictor of patient prognosis. Construct a nomogram to predict the survival probability of patients at 1,2,3 years. Using a series of computer-aided techniques, two more reasonable lead compounds ZINC000013374322 and ZINC000001090002 were virtually selected. These compounds have potential inhibitory effects on MCL-1 and provide a basis for the design and further development of MCL-1 specific small molecule inhibitors. Discussion: This study analyzed the effect of MCL-1 on the prognosis of glioblastoma patients from the perspective of immunology, constructed a new prognostic model to evaluate the survival rate of patients, and further screened 2 MCL-1 small molecule inhibitors, which provides new ideas for the treatment and prognosis of glioblastoma.
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spelling pubmed-103945582023-08-03 Development of an MCL-1-related prognostic signature and inhibitors screening for glioblastoma Zhang, Ao Guo, Zhen Ren, Jia-xin Chen, Hongyu Yang, Wenzhuo Zhou, Yang Pan, Lin Chen, Zhuopeng Ren, Fei Chen, Youqi Zhang, Menghan Peng, Fei Chen, Wanting Wang, Xinhui Zhang, Zhiyun Wu, Hui Front Pharmacol Pharmacology 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 patients prognosis is better. Univariate and multivariate analysis proved that risk could be used as an independent predictor of patient prognosis. Construct a nomogram to predict the survival probability of patients at 1,2,3 years. Using a series of computer-aided techniques, two more reasonable lead compounds ZINC000013374322 and ZINC000001090002 were virtually selected. These compounds have potential inhibitory effects on MCL-1 and provide a basis for the design and further development of MCL-1 specific small molecule inhibitors. Discussion: This study analyzed the effect of MCL-1 on the prognosis of glioblastoma patients from the perspective of immunology, constructed a new prognostic model to evaluate the survival rate of patients, and further screened 2 MCL-1 small molecule inhibitors, which provides new ideas for the treatment and prognosis of glioblastoma. Frontiers Media S.A. 2023-07-19 /pmc/articles/PMC10394558/ /pubmed/37538176 http://dx.doi.org/10.3389/fphar.2023.1162540 Text en Copyright © 2023 Zhang, Guo, Ren, Chen, Yang, Zhou, Pan, Chen, Ren, Chen, Zhang, Peng, Chen, Wang, Zhang and Wu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Zhang, Ao
Guo, Zhen
Ren, Jia-xin
Chen, Hongyu
Yang, Wenzhuo
Zhou, Yang
Pan, Lin
Chen, Zhuopeng
Ren, Fei
Chen, Youqi
Zhang, Menghan
Peng, Fei
Chen, Wanting
Wang, Xinhui
Zhang, Zhiyun
Wu, Hui
Development of an MCL-1-related prognostic signature and inhibitors screening for glioblastoma
title Development of an MCL-1-related prognostic signature and inhibitors screening for glioblastoma
title_full Development of an MCL-1-related prognostic signature and inhibitors screening for glioblastoma
title_fullStr Development of an MCL-1-related prognostic signature and inhibitors screening for glioblastoma
title_full_unstemmed Development of an MCL-1-related prognostic signature and inhibitors screening for glioblastoma
title_short Development of an MCL-1-related prognostic signature and inhibitors screening for glioblastoma
title_sort development of an mcl-1-related prognostic signature and inhibitors screening for glioblastoma
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10394558/
https://www.ncbi.nlm.nih.gov/pubmed/37538176
http://dx.doi.org/10.3389/fphar.2023.1162540
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