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pmid:39513108

Identification of an Immune signature assisted prognosis, and immunotherapy prediction for IDH wildtype glioblastoma.

Xuetao Han · Huandi Zhou · Xiaohui Ge · Liubing Hou · Haonan Li · Dongdong Zhang · Yu Wang · Xiaoying Xue

Journal of Cancer · 2024 doi:10.7150/jca.100144

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:39513108
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science-record
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2026-11-01T20:29:46Z
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2026-11-01T22:13:04Z
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paper object · 10 fields
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title
Identification of an Immune signature assisted prognosis, and immunotherapy prediction for IDH wildtype glioblastoma.
doi
10.7150/jca.100144
pmid
39513108
authors array · 8 items
[0]
Xuetao Han
[1]
Huandi Zhou
[2]
Xiaohui Ge
[3]
Liubing Hou
[4]
Haonan Li
[5]
Dongdong Zhang
[6]
Yu Wang
[7]
Xiaoying Xue
journal
Journal of Cancer
year
2024
abstract
IDH-wildtype glioblastoma (GBM) is the most common and malignant primary brain tumor. The purpose of this study is to establish a prognostic gene signature for IDH-wildtype GBM. RNA sequencing data of normal brain tissue and GBM patients were obtained from TCGA, CGGA, GEO and the GTEx databases. Identification of prognostic differentially expressed genes (DEGs) with | log2 fold change | > 0.5 and adjust p < 0.05 in TCGA and CGGA databases by "limma" method. By LASSO regression analysis and multivariate Cox analysis, a 3-gene prognostic signature composed of FMOD, MXRA5 and RAB36 was established. The 3-gene prognostic risk model is validated by TCGA and GSE43378 datasets. The expression of FMOD, MXRA5 and RAB36 in GBM patients was significantly higher than that in normal brain tissues in CCGA, TCGA and GSE29796 data sets. In order to further verify this result, total RNA was extracted from tumors and paracancerous tissues of 9 GBM patients. RT-PCR results showed that the expression of FMOD, MXRA5 and RAB36 in tumor tissues of most patients was higher than that in paracancerous tissues. The results of GSEA showed that the pathway enrichment of the 3-gene signature was mainly related to tumor immunity. Immune cell infiltration analyzed by ssGSEA showed that there were significant differences in macrophages between high- and low-risk groups. Immune checkpoint genes correlation analysis showed that PD-L1 gene expression is closely related to risk score. Our study identifies a prognostic-associated risk model and provides a potential effective immunotherapy target for IDH-wildtype GBM patients.
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By LASSO regression analysis and multivariate Cox analysis, a 3-gene prognostic signature composed of FMOD, MXRA5 and RAB36 was established.
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By LASSO regression analysis and multivariate Cox analysis, a 3-gene prognostic signature composed of FMOD, MXRA5 and RAB36 was established.
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The RNA sequencing data were obtained from TCGA (https://portal.gdc.cancer.gov/), CGGA (http://www.cgga.org.cn, mRNAseq_325 dataset), GEO (http://www.ncbi.nlm.nih.gov/geo/, GSE43378, GSE29796) database and GTEx (http://commonfund.nih.gov/GTEx/).
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The RNA sequencing data were obtained from TCGA (https://portal.gdc.cancer.gov/), CGGA (http://www.cgga.org.cn, mRNAseq_325 dataset), GEO (http://www.ncbi.nlm.nih.gov/geo/, GSE43378, GSE29796) database and GTEx (http://commonfund.nih.gov/GTEx/).
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By LASSO regression analysis and multivariate Cox analysis, a 3-gene prognostic signature composed of FMOD, MXRA5 and RAB36 was established.
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RNA sequencing data of normal brain tissue and GBM patients were obtained from TCGA, CGGA, GEO and the GTEx databases.
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By LASSO regression analysis and multivariate Cox analysis, a 3-gene prognostic signature composed of FMOD, MXRA5 and RAB36 was established.
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sections[17] "Construction of a prognostic gene signature model" paragraph 2
quote
In addition, ROC curve analysis also showed that the established model could well predict the prognosis of GBM patients (Figure 2G, 1-year, 3-year and 5-year ROC area under the curve (AUC) were 0.74, 0.87 and 0.94, respectively).
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By LASSO regression analysis and multivariate Cox analysis, a 3-gene prognostic signature composed of FMOD, MXRA5 and RAB36 was established.
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The RNA sequencing data were obtained from TCGA (https://portal.gdc.cancer.gov/), CGGA (http://www.cgga.org.cn, mRNAseq_325 dataset), GEO (http://www.ncbi.nlm.nih.gov/geo/, GSE43378, GSE29796) database and GTEx (http://commonfund.nih.gov/GTEx/).
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Transcriptional Differences between Normal and Glioma-Derived Glial Progenitor Cells Identify a Core Set of Dysregulated Genes.
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The RNA sequencing data were obtained from TCGA (https://portal.gdc.cancer.gov/), CGGA (http://www.cgga.org.cn, mRNAseq_325 dataset), GEO (http://www.ncbi.nlm.nih.gov/geo/, GSE43378, GSE29796) database and GTEx (http://commonfund.nih.gov/GTEx/).
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By LASSO regression analysis and multivariate Cox analysis, a 3-gene prognostic signature composed of FMOD, MXRA5 and RAB36 was established.
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By LASSO regression analysis and multivariate Cox analysis, a 3-gene prognostic signature composed of FMOD, MXRA5 and RAB36 was established.
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Complete file
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RNA sequencing data of normal brain tissue and GBM patients were obtained from TCGA, CGGA, GEO and the GTEx databases. Identification of prognostic differentially expressed genes (DEGs) with | log2 fold change | > 0.5 and adjust p < 0.05 in TCGA and CGGA databases by \"limma\" method. By LASSO regression analysis and multivariate Cox analysis, a 3-gene prognostic signature composed of FMOD, MXRA5 and RAB36 was established. The 3-gene prognostic risk model is validated by TCGA and GSE43378 datasets. The expression of FMOD, MXRA5 and RAB36 in GBM patients was significantly higher than that in normal brain tissues in CCGA, TCGA and GSE29796 data sets. In order to further verify this result, total RNA was extracted from tumors and paracancerous tissues of 9 GBM patients. RT-PCR results showed that the expression of FMOD, MXRA5 and RAB36 in tumor tissues of most patients was higher than that in paracancerous tissues. 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