Angiogenesis-Related Gene Signature-Derived Risk Score for Glioblastoma: Prospects for Predicting Prognosis and Immune Heterogeneity in Glioblastoma
Background: Glioblastoma multiforme (GBM) is the most common malignant tumor in the central nervous system with poor prognosis and unsatisfactory therapeutic efficacy. Considering the high correlation between tumors and angiogenesis, we attempted to construct a more effective model with angiogenesis...
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| Format: | Article |
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Frontiers Media S.A.
2022-03-01
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| Series: | Frontiers in Cell and Developmental Biology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcell.2022.778286/full |
| _version_ | 1818392753247092736 |
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| author | Gang Wang Jin-Qu Hu Ji-Yuan Liu Xiao-Mei Zhang |
| author_facet | Gang Wang Jin-Qu Hu Ji-Yuan Liu Xiao-Mei Zhang |
| author_sort | Gang Wang |
| collection | DOAJ |
| description | Background: Glioblastoma multiforme (GBM) is the most common malignant tumor in the central nervous system with poor prognosis and unsatisfactory therapeutic efficacy. Considering the high correlation between tumors and angiogenesis, we attempted to construct a more effective model with angiogenesis-related genes (ARGs) to better predict therapeutic response and prognosis.Methods: The ARG datasets were downloaded from the NCBI-Gene and Molecular Signatures Database. The gene expression data and clinical information were obtained from TCGA and CGGA databases. The differentially expressed angiogenesis-related genes (DE-ARGs) were screened with the R package “DESeq2”. Univariate Cox proportional hazards regression analysis was used to screen for ARGs related to overall survival. The redundant ARGs were removed by least absolute shrinkage and selection operator (LASSO) regression analysis. Based on the gene signature of DE-ARGs, a risk score model was established, and its effectiveness was estimated through Kaplan–Meier analysis, ROC analysis, etc.Results: A total of 626 DE-ARGs were explored between GBM and normal samples; 31 genes were identified as key DE-ARGs. Then, the risk score of ARG signature was established. Patients with high-risk score had poor survival outcomes. It was proved that the risk score could predict some medical treatments’ response, such as temozolomide chemotherapy, radiotherapy, and immunotherapy. Besides, the risk score could serve as a promising prognostic predictor. Three key prognostic genes (PLAUR, ITGA5, and FMOD) were selected and further discussed.Conclusion: The angiogenesis-related gene signature-derived risk score is a promising predictor of prognosis and treatment response in GBM and will help in making appropriate therapeutic strategies. |
| first_indexed | 2024-12-14T05:34:25Z |
| format | Article |
| id | doaj.art-a6710777e82a4c64a9bdfc4c306aea1e |
| institution | Directory Open Access Journal |
| issn | 2296-634X |
| language | English |
| last_indexed | 2024-12-14T05:34:25Z |
| publishDate | 2022-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cell and Developmental Biology |
| spelling | doaj.art-a6710777e82a4c64a9bdfc4c306aea1e2022-12-21T23:15:14ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2022-03-011010.3389/fcell.2022.778286778286Angiogenesis-Related Gene Signature-Derived Risk Score for Glioblastoma: Prospects for Predicting Prognosis and Immune Heterogeneity in GlioblastomaGang Wang0Jin-Qu Hu1Ji-Yuan Liu2Xiao-Mei Zhang3Department of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of China Medical University, Shenyang, ChinaDepartment of Rheumatology and Immunology, ShengJing Hospital of China Medical University, Shenyang, ChinaBackground: Glioblastoma multiforme (GBM) is the most common malignant tumor in the central nervous system with poor prognosis and unsatisfactory therapeutic efficacy. Considering the high correlation between tumors and angiogenesis, we attempted to construct a more effective model with angiogenesis-related genes (ARGs) to better predict therapeutic response and prognosis.Methods: The ARG datasets were downloaded from the NCBI-Gene and Molecular Signatures Database. The gene expression data and clinical information were obtained from TCGA and CGGA databases. The differentially expressed angiogenesis-related genes (DE-ARGs) were screened with the R package “DESeq2”. Univariate Cox proportional hazards regression analysis was used to screen for ARGs related to overall survival. The redundant ARGs were removed by least absolute shrinkage and selection operator (LASSO) regression analysis. Based on the gene signature of DE-ARGs, a risk score model was established, and its effectiveness was estimated through Kaplan–Meier analysis, ROC analysis, etc.Results: A total of 626 DE-ARGs were explored between GBM and normal samples; 31 genes were identified as key DE-ARGs. Then, the risk score of ARG signature was established. Patients with high-risk score had poor survival outcomes. It was proved that the risk score could predict some medical treatments’ response, such as temozolomide chemotherapy, radiotherapy, and immunotherapy. Besides, the risk score could serve as a promising prognostic predictor. Three key prognostic genes (PLAUR, ITGA5, and FMOD) were selected and further discussed.Conclusion: The angiogenesis-related gene signature-derived risk score is a promising predictor of prognosis and treatment response in GBM and will help in making appropriate therapeutic strategies.https://www.frontiersin.org/articles/10.3389/fcell.2022.778286/fullglioblastomaangiogenesisgene signatureprognostic modelrisk score |
| spellingShingle | Gang Wang Jin-Qu Hu Ji-Yuan Liu Xiao-Mei Zhang Angiogenesis-Related Gene Signature-Derived Risk Score for Glioblastoma: Prospects for Predicting Prognosis and Immune Heterogeneity in Glioblastoma Frontiers in Cell and Developmental Biology glioblastoma angiogenesis gene signature prognostic model risk score |
| title | Angiogenesis-Related Gene Signature-Derived Risk Score for Glioblastoma: Prospects for Predicting Prognosis and Immune Heterogeneity in Glioblastoma |
| title_full | Angiogenesis-Related Gene Signature-Derived Risk Score for Glioblastoma: Prospects for Predicting Prognosis and Immune Heterogeneity in Glioblastoma |
| title_fullStr | Angiogenesis-Related Gene Signature-Derived Risk Score for Glioblastoma: Prospects for Predicting Prognosis and Immune Heterogeneity in Glioblastoma |
| title_full_unstemmed | Angiogenesis-Related Gene Signature-Derived Risk Score for Glioblastoma: Prospects for Predicting Prognosis and Immune Heterogeneity in Glioblastoma |
| title_short | Angiogenesis-Related Gene Signature-Derived Risk Score for Glioblastoma: Prospects for Predicting Prognosis and Immune Heterogeneity in Glioblastoma |
| title_sort | angiogenesis related gene signature derived risk score for glioblastoma prospects for predicting prognosis and immune heterogeneity in glioblastoma |
| topic | glioblastoma angiogenesis gene signature prognostic model risk score |
| url | https://www.frontiersin.org/articles/10.3389/fcell.2022.778286/full |
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