Inference of Subpathway Activity Profiles Reveals Metabolism Abnormal Subpathway Regions in Glioblastoma Multiforme
Glioblastoma, also known as glioblastoma multiforme (GBM), is the most malignant form of glioma and represents 81% of malignant brain and central nervous system (CNS) tumors. Like most cancers, GBM causes metabolic recombination to promote cell survival, proliferation, and invasion of cancer cells....
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-09-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fonc.2020.01549/full |
| _version_ | 1818558359586996224 |
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| author | Xudong Han Donghua Wang Ping Zhao Chonghui Liu Yue Hao Lulu Chang Jiarui Zhao Wei Zhao Lili Mu Jinghua Wang Hulun Li Hulun Li Qingfei Kong Qingfei Kong Junwei Han |
| author_facet | Xudong Han Donghua Wang Ping Zhao Chonghui Liu Yue Hao Lulu Chang Jiarui Zhao Wei Zhao Lili Mu Jinghua Wang Hulun Li Hulun Li Qingfei Kong Qingfei Kong Junwei Han |
| author_sort | Xudong Han |
| collection | DOAJ |
| description | Glioblastoma, also known as glioblastoma multiforme (GBM), is the most malignant form of glioma and represents 81% of malignant brain and central nervous system (CNS) tumors. Like most cancers, GBM causes metabolic recombination to promote cell survival, proliferation, and invasion of cancer cells. In this study, we propose a method for constructing the metabolic subpathway activity score matrix to accurately identify abnormal targets of GBM metabolism. By integrating gene expression data from different sequencing methods, our method identified 25 metabolic subpathways that were significantly abnormal in the GBM patient population, and most of these subpathways have been reported to have an effect on GBM. Through the analysis of 25 GBM-related metabolic subpathways, we found that (S)-2,3-Epoxysqualene, which was at the central region of the sterol biosynthesis subpathway, may have a greater impact on the entire pathway, suggesting a potential high association with GBM. Analysis of CCK8 cell activity indicated that (S)-2,3-Epoxysqualene can indeed inhibit the activity of U87-MG cells. By flow cytometry, we demonstrated that (S)-2,3-Epoxysqualene not only arrested the U87-MG cell cycle in the G0/G1 phase but also induced cell apoptosis. These results confirm the reliability of our proposed metabolic subpathway identification method and suggest that (S)-2,3-Epoxysqualene has potential therapeutic value for GBM. In order to make the method more broadly applicable, we have developed an R system package crmSubpathway to perform disease-related metabolic subpathway identification and it is freely available on the GitHub (https://github.com/hanjunwei-lab/crmSubpathway). |
| first_indexed | 2024-12-14T00:11:25Z |
| format | Article |
| id | doaj.art-8cac48b06b394dbeb0cd14f54a654629 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-14T00:11:25Z |
| publishDate | 2020-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-8cac48b06b394dbeb0cd14f54a6546292022-12-21T23:25:44ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2020-09-011010.3389/fonc.2020.01549522433Inference of Subpathway Activity Profiles Reveals Metabolism Abnormal Subpathway Regions in Glioblastoma MultiformeXudong Han0Donghua Wang1Ping Zhao2Chonghui Liu3Yue Hao4Lulu Chang5Jiarui Zhao6Wei Zhao7Lili Mu8Jinghua Wang9Hulun Li10Hulun Li11Qingfei Kong12Qingfei Kong13Junwei Han14Department of Neurobiology, Harbin Medical University, Heilongjiang Provincial Key Laboratory of Neurobiology, Harbin, ChinaDepartment of General Surgery, General Hospital of Heilongjiang Province Land Reclamation Bureau, Harbin, ChinaDepartment of Neurobiology, Harbin Medical University, Heilongjiang Provincial Key Laboratory of Neurobiology, Harbin, ChinaDepartment of Neurobiology, Harbin Medical University, Heilongjiang Provincial Key Laboratory of Neurobiology, Harbin, ChinaDepartment of Neurobiology, Harbin Medical University, Heilongjiang Provincial Key Laboratory of Neurobiology, Harbin, ChinaDepartment of Neurobiology, Harbin Medical University, Heilongjiang Provincial Key Laboratory of Neurobiology, Harbin, ChinaDepartment of Neurobiology, Harbin Medical University, Heilongjiang Provincial Key Laboratory of Neurobiology, Harbin, ChinaDepartment of Neurobiology, Harbin Medical University, Heilongjiang Provincial Key Laboratory of Neurobiology, Harbin, ChinaDepartment of Neurobiology, Harbin Medical University, Heilongjiang Provincial Key Laboratory of Neurobiology, Harbin, ChinaDepartment of Neurobiology, Harbin Medical University, Heilongjiang Provincial Key Laboratory of Neurobiology, Harbin, ChinaDepartment of Neurobiology, Harbin Medical University, Heilongjiang Provincial Key Laboratory of Neurobiology, Harbin, ChinaKey Laboratory of Preservation of Human Genetic Resources and Disease Control in China (Harbin Medical University), Ministry of Education, Harbin, ChinaDepartment of Neurobiology, Harbin Medical University, Heilongjiang Provincial Key Laboratory of Neurobiology, Harbin, ChinaKey Laboratory of Preservation of Human Genetic Resources and Disease Control in China (Harbin Medical University), Ministry of Education, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaGlioblastoma, also known as glioblastoma multiforme (GBM), is the most malignant form of glioma and represents 81% of malignant brain and central nervous system (CNS) tumors. Like most cancers, GBM causes metabolic recombination to promote cell survival, proliferation, and invasion of cancer cells. In this study, we propose a method for constructing the metabolic subpathway activity score matrix to accurately identify abnormal targets of GBM metabolism. By integrating gene expression data from different sequencing methods, our method identified 25 metabolic subpathways that were significantly abnormal in the GBM patient population, and most of these subpathways have been reported to have an effect on GBM. Through the analysis of 25 GBM-related metabolic subpathways, we found that (S)-2,3-Epoxysqualene, which was at the central region of the sterol biosynthesis subpathway, may have a greater impact on the entire pathway, suggesting a potential high association with GBM. Analysis of CCK8 cell activity indicated that (S)-2,3-Epoxysqualene can indeed inhibit the activity of U87-MG cells. By flow cytometry, we demonstrated that (S)-2,3-Epoxysqualene not only arrested the U87-MG cell cycle in the G0/G1 phase but also induced cell apoptosis. These results confirm the reliability of our proposed metabolic subpathway identification method and suggest that (S)-2,3-Epoxysqualene has potential therapeutic value for GBM. In order to make the method more broadly applicable, we have developed an R system package crmSubpathway to perform disease-related metabolic subpathway identification and it is freely available on the GitHub (https://github.com/hanjunwei-lab/crmSubpathway).https://www.frontiersin.org/article/10.3389/fonc.2020.01549/fullGBMgenemetabolic subpathwaysteroid biosynthesisU87-MG cell(S)-2,3-Epoxysqualene |
| spellingShingle | Xudong Han Donghua Wang Ping Zhao Chonghui Liu Yue Hao Lulu Chang Jiarui Zhao Wei Zhao Lili Mu Jinghua Wang Hulun Li Hulun Li Qingfei Kong Qingfei Kong Junwei Han Inference of Subpathway Activity Profiles Reveals Metabolism Abnormal Subpathway Regions in Glioblastoma Multiforme Frontiers in Oncology GBM gene metabolic subpathway steroid biosynthesis U87-MG cell (S)-2,3-Epoxysqualene |
| title | Inference of Subpathway Activity Profiles Reveals Metabolism Abnormal Subpathway Regions in Glioblastoma Multiforme |
| title_full | Inference of Subpathway Activity Profiles Reveals Metabolism Abnormal Subpathway Regions in Glioblastoma Multiforme |
| title_fullStr | Inference of Subpathway Activity Profiles Reveals Metabolism Abnormal Subpathway Regions in Glioblastoma Multiforme |
| title_full_unstemmed | Inference of Subpathway Activity Profiles Reveals Metabolism Abnormal Subpathway Regions in Glioblastoma Multiforme |
| title_short | Inference of Subpathway Activity Profiles Reveals Metabolism Abnormal Subpathway Regions in Glioblastoma Multiforme |
| title_sort | inference of subpathway activity profiles reveals metabolism abnormal subpathway regions in glioblastoma multiforme |
| topic | GBM gene metabolic subpathway steroid biosynthesis U87-MG cell (S)-2,3-Epoxysqualene |
| url | https://www.frontiersin.org/article/10.3389/fonc.2020.01549/full |
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