Identification of a Glycolysis-Related LncRNA Signature to Predict Survival in Diffuse Glioma Patients
Glycolysis refers to one of the critical phenotypes of tumor cells, regulating tumor cell phenotypes and generating sufficient energy for glioma cells. A range of noticeable genes [such as isocitrate dehydrogenase (IDH), phosphatase, and tensin homolog (PTEN), or Ras] overall impact cell proliferati...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-02-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2020.597877/full |
| _version_ | 1818452166921158656 |
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| author | Yangyang Wang Wenjianlong Zhou Shunchang Ma Xiudong Guan Dainan Zhang Jiayi Peng Xi Wang Linhao Yuan Peiliang Li Beibei Mao Peng Kang Deling Li Chuanbao Zhang Wang Jia Wang Jia Wang Jia |
| author_facet | Yangyang Wang Wenjianlong Zhou Shunchang Ma Xiudong Guan Dainan Zhang Jiayi Peng Xi Wang Linhao Yuan Peiliang Li Beibei Mao Peng Kang Deling Li Chuanbao Zhang Wang Jia Wang Jia Wang Jia |
| author_sort | Yangyang Wang |
| collection | DOAJ |
| description | Glycolysis refers to one of the critical phenotypes of tumor cells, regulating tumor cell phenotypes and generating sufficient energy for glioma cells. A range of noticeable genes [such as isocitrate dehydrogenase (IDH), phosphatase, and tensin homolog (PTEN), or Ras] overall impact cell proliferation, invasion, cell cycle, and metastasis through glycolysis. Moreover, long non-coding RNAs (LncRNAs) are increasingly critical to disease progression. Accordingly, this study aimed to identify whether glycolysis-related LncRNAs have potential prognostic value for glioma patients. First, co-expression network between glycolysis-related protein-coding RNAs and LncRNAs was established according to Pearson correlation (Filter: |r| > 0.5 & P < 0.001). Furthermore, based on univariate Cox regression, the Least Absolute Shrinkage and Selection Operator (LASSO) analysis and multivariate Cox regression, a predictive model were built; vital glycolysis-related LncRNAs were identified; the risk score of every single patient was calculated. Moreover, receiver operating characteristic (ROC) curve analysis, gene set enrichment analysis (GSEA), GO and KEGG enrichment analysis were performed to assess the effect of risk score among glioma patients. 685 cases (including RNA sequences and clinical information) from two different cohorts of the Chinese Glioma Genome Atlas (CGGA) database were acquired. Based on the mentioned methods, the risk score calculation formula was yielded as follows: Risk score = (0.19 × EXPFOXD2-AS1) + (−0.27 × EXPAC062021.1) + (−0.16 × EXPAF131216.5) + (−0.05 × EXPLINC00844) + (0.11 × EXPCRNDE) + (0.35 × EXPLINC00665). The risk score was independently related to prognosis, and every single mentioned LncRNAs was significantly related to the overall survival of patients. Moreover, functional enrichment analysis indicated that the biologic process of the high-risk score was mainly involved in the cell cycle and DNA replication signaling pathway. This study confirmed that glycolysis-related LncRNAs significantly impact poor prognosis and short overall survival and may act as therapeutic targets in the future. |
| first_indexed | 2024-12-14T21:18:47Z |
| format | Article |
| id | doaj.art-d59d9cd422a94b4bb3f609529463f32f |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-14T21:18:47Z |
| publishDate | 2021-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-d59d9cd422a94b4bb3f609529463f32f2022-12-21T22:46:59ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2021-02-011010.3389/fonc.2020.597877597877Identification of a Glycolysis-Related LncRNA Signature to Predict Survival in Diffuse Glioma PatientsYangyang Wang0Wenjianlong Zhou1Shunchang Ma2Xiudong Guan3Dainan Zhang4Jiayi Peng5Xi Wang6Linhao Yuan7Peiliang Li8Beibei Mao9Peng Kang10Deling Li11Chuanbao Zhang12Wang Jia13Wang Jia14Wang Jia15Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaBeijing Neurosurgery Research Institute, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaBeijing Neurosurgery Research Institute, Capital Medical University, Beijing, ChinaChina National Clinical Research Center for Neurological Diseases (NCRC-ND), Beijing, ChinaGlycolysis refers to one of the critical phenotypes of tumor cells, regulating tumor cell phenotypes and generating sufficient energy for glioma cells. A range of noticeable genes [such as isocitrate dehydrogenase (IDH), phosphatase, and tensin homolog (PTEN), or Ras] overall impact cell proliferation, invasion, cell cycle, and metastasis through glycolysis. Moreover, long non-coding RNAs (LncRNAs) are increasingly critical to disease progression. Accordingly, this study aimed to identify whether glycolysis-related LncRNAs have potential prognostic value for glioma patients. First, co-expression network between glycolysis-related protein-coding RNAs and LncRNAs was established according to Pearson correlation (Filter: |r| > 0.5 & P < 0.001). Furthermore, based on univariate Cox regression, the Least Absolute Shrinkage and Selection Operator (LASSO) analysis and multivariate Cox regression, a predictive model were built; vital glycolysis-related LncRNAs were identified; the risk score of every single patient was calculated. Moreover, receiver operating characteristic (ROC) curve analysis, gene set enrichment analysis (GSEA), GO and KEGG enrichment analysis were performed to assess the effect of risk score among glioma patients. 685 cases (including RNA sequences and clinical information) from two different cohorts of the Chinese Glioma Genome Atlas (CGGA) database were acquired. Based on the mentioned methods, the risk score calculation formula was yielded as follows: Risk score = (0.19 × EXPFOXD2-AS1) + (−0.27 × EXPAC062021.1) + (−0.16 × EXPAF131216.5) + (−0.05 × EXPLINC00844) + (0.11 × EXPCRNDE) + (0.35 × EXPLINC00665). The risk score was independently related to prognosis, and every single mentioned LncRNAs was significantly related to the overall survival of patients. Moreover, functional enrichment analysis indicated that the biologic process of the high-risk score was mainly involved in the cell cycle and DNA replication signaling pathway. This study confirmed that glycolysis-related LncRNAs significantly impact poor prognosis and short overall survival and may act as therapeutic targets in the future.https://www.frontiersin.org/articles/10.3389/fonc.2020.597877/fullgliomaglycolysislong non-coding RNAs (LncRNA)prognosisrisk model |
| spellingShingle | Yangyang Wang Wenjianlong Zhou Shunchang Ma Xiudong Guan Dainan Zhang Jiayi Peng Xi Wang Linhao Yuan Peiliang Li Beibei Mao Peng Kang Deling Li Chuanbao Zhang Wang Jia Wang Jia Wang Jia Identification of a Glycolysis-Related LncRNA Signature to Predict Survival in Diffuse Glioma Patients Frontiers in Oncology glioma glycolysis long non-coding RNAs (LncRNA) prognosis risk model |
| title | Identification of a Glycolysis-Related LncRNA Signature to Predict Survival in Diffuse Glioma Patients |
| title_full | Identification of a Glycolysis-Related LncRNA Signature to Predict Survival in Diffuse Glioma Patients |
| title_fullStr | Identification of a Glycolysis-Related LncRNA Signature to Predict Survival in Diffuse Glioma Patients |
| title_full_unstemmed | Identification of a Glycolysis-Related LncRNA Signature to Predict Survival in Diffuse Glioma Patients |
| title_short | Identification of a Glycolysis-Related LncRNA Signature to Predict Survival in Diffuse Glioma Patients |
| title_sort | identification of a glycolysis related lncrna signature to predict survival in diffuse glioma patients |
| topic | glioma glycolysis long non-coding RNAs (LncRNA) prognosis risk model |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2020.597877/full |
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