Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Lower-Grade Glioma
ObjectiveDespite several clinicopathological factors being integrated as prognostic biomarkers, the individual variants and risk stratification have not been fully elucidated in lower grade glioma (LGG). With the prevalence of gene expression profiling in LGG, and based on the critical role of the i...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2020-04-01
|
| Series: | Frontiers in Genetics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fgene.2020.00363/full |
| _version_ | 1819105245719953408 |
|---|---|
| author | Mingwei Zhang Mingwei Zhang Mingwei Zhang Mingwei Zhang Mingwei Zhang Xuezhen Wang Xiaoping Chen Qiuyu Zhang Jinsheng Hong Jinsheng Hong Jinsheng Hong |
| author_facet | Mingwei Zhang Mingwei Zhang Mingwei Zhang Mingwei Zhang Mingwei Zhang Xuezhen Wang Xiaoping Chen Qiuyu Zhang Jinsheng Hong Jinsheng Hong Jinsheng Hong |
| author_sort | Mingwei Zhang |
| collection | DOAJ |
| description | ObjectiveDespite several clinicopathological factors being integrated as prognostic biomarkers, the individual variants and risk stratification have not been fully elucidated in lower grade glioma (LGG). With the prevalence of gene expression profiling in LGG, and based on the critical role of the immune microenvironment, the aim of our study was to develop an immune-related signature for risk stratification and prognosis prediction in LGG.MethodsRNA-sequencing data from The Cancer Genome Atlas (TCGA), Genome Tissue Expression (GTEx), and Chinese Glioma Genome Atlas (CGGA) were used. Immune-related genes were obtained from the Immunology Database and Analysis Portal (ImmPort). Univariate, multivariate cox regression, and Lasso regression were employed to identify differentially expressed immune-related genes (DEGs) and establish the signature. A nomogram was constructed, and its performance was evaluated by Harrell’s concordance index (C-index), receiver operating characteristic (ROC), and calibration curves. Relationships between the risk score and tumor-infiltrating immune cell abundances were evaluated using CIBERSORTx and TIMER.ResultsNoted, 277 immune-related DEGs were identified. Consecutively, 6 immune genes (CANX, HSPA1B, KLRC2, PSMC6, RFXAP, and TAP1) were identified as risk signature and Kaplan–Meier curve, ROC curve, and risk plot verified its performance in TCGA and CGGA datasets. Univariate and multivariate Cox regression indicated that the risk group was an independent predictor in primary LGG. The prognostic signature showed fair accuracy for 3- and 5-year overall survival in both internal (TCGA) and external (CGGA) validation cohorts. However, predictive performance was poor in the recurrent LGG cohort. The CIBERSORTx algorithm revealed that naïve CD4+ T cells were significant higher in low-risk group. Conversely, the infiltration levels of M1-type macrophages, M2-type macrophages, and CD8+T cells were significant higher in high-risk group in both TCGA and CGGA cohorts.ConclusionThe present study constructed a robust six immune-related gene signature and established a prognostic nomogram effective in risk stratification and prediction of overall survival in primary LGG. |
| first_indexed | 2024-12-22T02:19:11Z |
| format | Article |
| id | doaj.art-cc30273112c14b35841e3eb19cd63ac9 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-22T02:19:11Z |
| publishDate | 2020-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-cc30273112c14b35841e3eb19cd63ac92022-12-21T18:42:11ZengFrontiers Media S.A.Frontiers in Genetics1664-80212020-04-011110.3389/fgene.2020.00363523455Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Lower-Grade GliomaMingwei Zhang0Mingwei Zhang1Mingwei Zhang2Mingwei Zhang3Mingwei Zhang4Xuezhen Wang5Xiaoping Chen6Qiuyu Zhang7Jinsheng Hong8Jinsheng Hong9Jinsheng Hong10Department of Radiation Oncology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, ChinaInstitute of Immunotherapy, Fujian Medical University, Fuzhou, ChinaKey Laboratory of Radiation Biology (Fujian Medical University), Fujian Province University, Fuzhou, ChinaFujian Key Laboratory of Individualized Active Immunotherapy, Fuzhou, ChinaFujian Medical University Union Hospital, Fuzhou, ChinaDepartment of Radiation Oncology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, ChinaDepartment of Statistics, College of Mathematics and Informatics & FJKLMAA, Fujian Normal University, Fuzhou, ChinaInstitute of Immunotherapy, Fujian Medical University, Fuzhou, ChinaDepartment of Radiation Oncology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, ChinaKey Laboratory of Radiation Biology (Fujian Medical University), Fujian Province University, Fuzhou, ChinaFujian Key Laboratory of Individualized Active Immunotherapy, Fuzhou, ChinaObjectiveDespite several clinicopathological factors being integrated as prognostic biomarkers, the individual variants and risk stratification have not been fully elucidated in lower grade glioma (LGG). With the prevalence of gene expression profiling in LGG, and based on the critical role of the immune microenvironment, the aim of our study was to develop an immune-related signature for risk stratification and prognosis prediction in LGG.MethodsRNA-sequencing data from The Cancer Genome Atlas (TCGA), Genome Tissue Expression (GTEx), and Chinese Glioma Genome Atlas (CGGA) were used. Immune-related genes were obtained from the Immunology Database and Analysis Portal (ImmPort). Univariate, multivariate cox regression, and Lasso regression were employed to identify differentially expressed immune-related genes (DEGs) and establish the signature. A nomogram was constructed, and its performance was evaluated by Harrell’s concordance index (C-index), receiver operating characteristic (ROC), and calibration curves. Relationships between the risk score and tumor-infiltrating immune cell abundances were evaluated using CIBERSORTx and TIMER.ResultsNoted, 277 immune-related DEGs were identified. Consecutively, 6 immune genes (CANX, HSPA1B, KLRC2, PSMC6, RFXAP, and TAP1) were identified as risk signature and Kaplan–Meier curve, ROC curve, and risk plot verified its performance in TCGA and CGGA datasets. Univariate and multivariate Cox regression indicated that the risk group was an independent predictor in primary LGG. The prognostic signature showed fair accuracy for 3- and 5-year overall survival in both internal (TCGA) and external (CGGA) validation cohorts. However, predictive performance was poor in the recurrent LGG cohort. The CIBERSORTx algorithm revealed that naïve CD4+ T cells were significant higher in low-risk group. Conversely, the infiltration levels of M1-type macrophages, M2-type macrophages, and CD8+T cells were significant higher in high-risk group in both TCGA and CGGA cohorts.ConclusionThe present study constructed a robust six immune-related gene signature and established a prognostic nomogram effective in risk stratification and prediction of overall survival in primary LGG.https://www.frontiersin.org/article/10.3389/fgene.2020.00363/fulllower grade gliomaThe Cancer Genome AtlasChinese Glioma Genome Atlasimmune-related signatureprognosis |
| spellingShingle | Mingwei Zhang Mingwei Zhang Mingwei Zhang Mingwei Zhang Mingwei Zhang Xuezhen Wang Xiaoping Chen Qiuyu Zhang Jinsheng Hong Jinsheng Hong Jinsheng Hong Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Lower-Grade Glioma Frontiers in Genetics lower grade glioma The Cancer Genome Atlas Chinese Glioma Genome Atlas immune-related signature prognosis |
| title | Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Lower-Grade Glioma |
| title_full | Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Lower-Grade Glioma |
| title_fullStr | Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Lower-Grade Glioma |
| title_full_unstemmed | Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Lower-Grade Glioma |
| title_short | Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Lower-Grade Glioma |
| title_sort | novel immune related gene signature for risk stratification and prognosis of survival in lower grade glioma |
| topic | lower grade glioma The Cancer Genome Atlas Chinese Glioma Genome Atlas immune-related signature prognosis |
| url | https://www.frontiersin.org/article/10.3389/fgene.2020.00363/full |
| work_keys_str_mv | AT mingweizhang novelimmunerelatedgenesignatureforriskstratificationandprognosisofsurvivalinlowergradeglioma AT mingweizhang novelimmunerelatedgenesignatureforriskstratificationandprognosisofsurvivalinlowergradeglioma AT mingweizhang novelimmunerelatedgenesignatureforriskstratificationandprognosisofsurvivalinlowergradeglioma AT mingweizhang novelimmunerelatedgenesignatureforriskstratificationandprognosisofsurvivalinlowergradeglioma AT mingweizhang novelimmunerelatedgenesignatureforriskstratificationandprognosisofsurvivalinlowergradeglioma AT xuezhenwang novelimmunerelatedgenesignatureforriskstratificationandprognosisofsurvivalinlowergradeglioma AT xiaopingchen novelimmunerelatedgenesignatureforriskstratificationandprognosisofsurvivalinlowergradeglioma AT qiuyuzhang novelimmunerelatedgenesignatureforriskstratificationandprognosisofsurvivalinlowergradeglioma AT jinshenghong novelimmunerelatedgenesignatureforriskstratificationandprognosisofsurvivalinlowergradeglioma AT jinshenghong novelimmunerelatedgenesignatureforriskstratificationandprognosisofsurvivalinlowergradeglioma AT jinshenghong novelimmunerelatedgenesignatureforriskstratificationandprognosisofsurvivalinlowergradeglioma |