Identification and validation of ferroptosis-related lncRNA signatures as a novel prognostic model for glioma
Background: Ferroptosis is a newly discovered form of regulated cell death with distinct properties and recognizing functions involved in physical conditions or various diseases, including cancers. However, the relationship between gliomas and ferroptosis-related lncRNAs (FRLs) remains unclear.Metho...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.927142/full |
| _version_ | 1828228029925556224 |
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| author | Liang Huang Juan Zhang Fanghua Gong Yuhua Han Xing Huang Wanxiang Luo Huaan Cai Fan Zhang |
| author_facet | Liang Huang Juan Zhang Fanghua Gong Yuhua Han Xing Huang Wanxiang Luo Huaan Cai Fan Zhang |
| author_sort | Liang Huang |
| collection | DOAJ |
| description | Background: Ferroptosis is a newly discovered form of regulated cell death with distinct properties and recognizing functions involved in physical conditions or various diseases, including cancers. However, the relationship between gliomas and ferroptosis-related lncRNAs (FRLs) remains unclear.Methods: We collected a total of 1850 samples from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEX) databases, including 698 tumor and 1,152 normal samples. A list of ferroptosis-related genes was downloaded from the Ferrdb website. Differentially expressed FRLs (DEFRLS) were analyzed using the “limma” package in R software. Subsequently, prognosis-related FRLs were obtained by univariate Cox analysis. Finally, a prognostic model based on the 3 FRLs was constructed using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm. The prognostic power of the model was assessed using receiver operating characteristic (ROC) curve analysis and Kaplan-Meier (K-M) survival curve analysis. In addition, we further explored the relationship of the immune landscape and somatic mutations to prognostic model characteristics. Finally, we validated the function of LINC01426 in vitro.Results: We successfully constructed a 3-FRLs signature and classified glioma patients into high-risk and low-risk groups based on the risk score calculated from this signature. Compared with traditional clinicopathological features [age, sex, grade, isocitrate dehydrogenase (IDH) status], the prognostic accuracy of this model is more stable and stronger. Additionally, the model had stable predictive power for overall survival over a 5-year period. In addition, we found significant differences between the two groups in cellular immunity, the numbers of many immune cells, including NK cells, CD4+, CD8+ T-cells, and macrophages, and the expression of many immune-related genes. Finally, the two groups were also significantly different at the level of somatic mutations, especially in glioma prognosis-related genes such as IDH1 and ATRX, with lower mutation rates in the high-risk group leading to poorer prognosis. Finally, we found that the ferroptosis process of glioma cells was inhibited after knocking down the expression of LINC01426.Conclusion: The proposed 3-FRL signature is a promising biomarker for predicting prognostic features in glioma patients. |
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| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-12T18:15:23Z |
| publishDate | 2022-09-01 |
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| series | Frontiers in Genetics |
| spelling | doaj.art-e37b40b51a774e9a9aa83417bb5189f92022-12-22T03:21:39ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-09-011310.3389/fgene.2022.927142927142Identification and validation of ferroptosis-related lncRNA signatures as a novel prognostic model for gliomaLiang Huang0Juan Zhang1Fanghua Gong2Yuhua Han3Xing Huang4Wanxiang Luo5Huaan Cai6Fan Zhang7Department of Rehabilitation Medicine, Hunan Provincial People’s Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, ChinaDepartment of Rehabilitation Medicine, Hunan Provincial People’s Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, ChinaDepartment of Nursing, Hunan Provincial People’s Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, ChinaDepartment of Cadre Health Care, Hunan Provincial People’s Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, ChinaDepartment of General Surgery, Hunan Provincial People’s Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, ChinaDepartment of Rehabilitation Medicine, Hunan Provincial People’s Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, ChinaDepartment of Rehabilitation Medicine, Hunan Provincial People’s Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, ChinaDepartment of Rehabilitation Medicine, Hunan Provincial People’s Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, ChinaBackground: Ferroptosis is a newly discovered form of regulated cell death with distinct properties and recognizing functions involved in physical conditions or various diseases, including cancers. However, the relationship between gliomas and ferroptosis-related lncRNAs (FRLs) remains unclear.Methods: We collected a total of 1850 samples from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEX) databases, including 698 tumor and 1,152 normal samples. A list of ferroptosis-related genes was downloaded from the Ferrdb website. Differentially expressed FRLs (DEFRLS) were analyzed using the “limma” package in R software. Subsequently, prognosis-related FRLs were obtained by univariate Cox analysis. Finally, a prognostic model based on the 3 FRLs was constructed using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm. The prognostic power of the model was assessed using receiver operating characteristic (ROC) curve analysis and Kaplan-Meier (K-M) survival curve analysis. In addition, we further explored the relationship of the immune landscape and somatic mutations to prognostic model characteristics. Finally, we validated the function of LINC01426 in vitro.Results: We successfully constructed a 3-FRLs signature and classified glioma patients into high-risk and low-risk groups based on the risk score calculated from this signature. Compared with traditional clinicopathological features [age, sex, grade, isocitrate dehydrogenase (IDH) status], the prognostic accuracy of this model is more stable and stronger. Additionally, the model had stable predictive power for overall survival over a 5-year period. In addition, we found significant differences between the two groups in cellular immunity, the numbers of many immune cells, including NK cells, CD4+, CD8+ T-cells, and macrophages, and the expression of many immune-related genes. Finally, the two groups were also significantly different at the level of somatic mutations, especially in glioma prognosis-related genes such as IDH1 and ATRX, with lower mutation rates in the high-risk group leading to poorer prognosis. Finally, we found that the ferroptosis process of glioma cells was inhibited after knocking down the expression of LINC01426.Conclusion: The proposed 3-FRL signature is a promising biomarker for predicting prognostic features in glioma patients.https://www.frontiersin.org/articles/10.3389/fgene.2022.927142/fulllncRNAferroptosisgliomaprognostic signatureimmune microenvironment |
| spellingShingle | Liang Huang Juan Zhang Fanghua Gong Yuhua Han Xing Huang Wanxiang Luo Huaan Cai Fan Zhang Identification and validation of ferroptosis-related lncRNA signatures as a novel prognostic model for glioma Frontiers in Genetics lncRNA ferroptosis glioma prognostic signature immune microenvironment |
| title | Identification and validation of ferroptosis-related lncRNA signatures as a novel prognostic model for glioma |
| title_full | Identification and validation of ferroptosis-related lncRNA signatures as a novel prognostic model for glioma |
| title_fullStr | Identification and validation of ferroptosis-related lncRNA signatures as a novel prognostic model for glioma |
| title_full_unstemmed | Identification and validation of ferroptosis-related lncRNA signatures as a novel prognostic model for glioma |
| title_short | Identification and validation of ferroptosis-related lncRNA signatures as a novel prognostic model for glioma |
| title_sort | identification and validation of ferroptosis related lncrna signatures as a novel prognostic model for glioma |
| topic | lncRNA ferroptosis glioma prognostic signature immune microenvironment |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.927142/full |
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