A glycosylation-related gene signature predicts prognosis, immune microenvironment infiltration, and drug sensitivity in glioma
Glioma represents the most common primary cancer of the central nervous system in adults. Glycosylation is a prevalent post-translational modification that occurs in eukaryotic cells, leading to a wide array of modifications on proteins. We obtained the clinical information, bulk RNA-seq data, and s...
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| Format: | Article |
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Frontiers Media S.A.
2024-01-01
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| Series: | Frontiers in Pharmacology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphar.2023.1259051/full |
| _version_ | 1797354417969692672 |
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| author | Yanbo Yang Haiying Teng Haiying Teng Yulian Zhang Fei Wang Fei Wang Liyan Tang Chuanpeng Zhang Chuanpeng Zhang Ziyi Hu Ziyi Hu Yuxuan Chen Yuxuan Chen Yi Ge Zhong Wang Yanbing Yu |
| author_facet | Yanbo Yang Haiying Teng Haiying Teng Yulian Zhang Fei Wang Fei Wang Liyan Tang Chuanpeng Zhang Chuanpeng Zhang Ziyi Hu Ziyi Hu Yuxuan Chen Yuxuan Chen Yi Ge Zhong Wang Yanbing Yu |
| author_sort | Yanbo Yang |
| collection | DOAJ |
| description | Glioma represents the most common primary cancer of the central nervous system in adults. Glycosylation is a prevalent post-translational modification that occurs in eukaryotic cells, leading to a wide array of modifications on proteins. We obtained the clinical information, bulk RNA-seq data, and single-cell RNA sequencing (scRNA-seq) from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Gene Expression Omnibus (GEO), and Repository of Molecular Brain Neoplasia Data (Rembrandt) databases. RNA sequencing data for normal brain tissues were accessed from the Genotype-Tissue Expression (GTEx) database. Then, the glycosylation genes that were differentially expressed were identified and further subjected to variable selection using a least absolute shrinkage and selection operator (LASSO)-regularized Cox model. We further conducted enrichment analysis, qPCR, nomogram, and single-cell transcriptome to detect the glycosylation signature. Drug sensitivity analysis was also conducted. A five-gene glycosylation signature (CHPF2, PYGL, GALNT13, EXT2, and COLGALT2) classified patients into low- or high-risk groups. Survival analysis, qPCR, ROC curves, and stratified analysis revealed worse outcomes in the high-risk group. Furthermore, GSEA and immune infiltration analysis indicated that the glycosylation signature has the potential to predict the immune response in glioma. In addition, four drugs (crizotinib, lapatinib, nilotinib, and topotecan) showed different responses between the two risk groups. Glioma cells had been classified into seven lines based on single-cell expression profiles. The five-gene glycosylation signature can accurately predict the prognosis of glioma and may offer additional guidance for immunotherapy. |
| first_indexed | 2024-03-08T13:50:09Z |
| format | Article |
| id | doaj.art-44d481ab91d34c4aa6b7612fe2ad69b1 |
| institution | Directory Open Access Journal |
| issn | 1663-9812 |
| language | English |
| last_indexed | 2024-03-08T13:50:09Z |
| publishDate | 2024-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Pharmacology |
| spelling | doaj.art-44d481ab91d34c4aa6b7612fe2ad69b12024-01-16T04:35:29ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122024-01-011410.3389/fphar.2023.12590511259051A glycosylation-related gene signature predicts prognosis, immune microenvironment infiltration, and drug sensitivity in gliomaYanbo Yang0Haiying Teng1Haiying Teng2Yulian Zhang3Fei Wang4Fei Wang5Liyan Tang6Chuanpeng Zhang7Chuanpeng Zhang8Ziyi Hu9Ziyi Hu10Yuxuan Chen11Yuxuan Chen12Yi Ge13Zhong Wang14Yanbing Yu15China-Japan Friendship Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Neurosurgery and Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaSuzhou Medical College of Soochow University, Suzhou, Jiangsu, ChinaDepartment of Neurosurgery, China-Japan Friendship Hospital, Beijing, ChinaDepartment of Neurosurgery and Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaSuzhou Medical College of Soochow University, Suzhou, Jiangsu, ChinaDepartment of Neurosurgery and Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaDepartment of Neurosurgery, Peking University China-Japan Friendship School of Clinical Medicine, Beijing, ChinaDepartment of Neurosurgery, China-Japan Friendship Hospital, Beijing, ChinaDepartment of Neurosurgery and Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaSuzhou Medical College of Soochow University, Suzhou, Jiangsu, ChinaDepartment of Neurosurgery and Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaSuzhou Medical College of Soochow University, Suzhou, Jiangsu, ChinaThe Affiliated Changzhou Second People’s Hospital of Nanjing Medical University, Nanjing, Jiangsu, ChinaDepartment of Neurosurgery and Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaChina-Japan Friendship Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaGlioma represents the most common primary cancer of the central nervous system in adults. Glycosylation is a prevalent post-translational modification that occurs in eukaryotic cells, leading to a wide array of modifications on proteins. We obtained the clinical information, bulk RNA-seq data, and single-cell RNA sequencing (scRNA-seq) from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Gene Expression Omnibus (GEO), and Repository of Molecular Brain Neoplasia Data (Rembrandt) databases. RNA sequencing data for normal brain tissues were accessed from the Genotype-Tissue Expression (GTEx) database. Then, the glycosylation genes that were differentially expressed were identified and further subjected to variable selection using a least absolute shrinkage and selection operator (LASSO)-regularized Cox model. We further conducted enrichment analysis, qPCR, nomogram, and single-cell transcriptome to detect the glycosylation signature. Drug sensitivity analysis was also conducted. A five-gene glycosylation signature (CHPF2, PYGL, GALNT13, EXT2, and COLGALT2) classified patients into low- or high-risk groups. Survival analysis, qPCR, ROC curves, and stratified analysis revealed worse outcomes in the high-risk group. Furthermore, GSEA and immune infiltration analysis indicated that the glycosylation signature has the potential to predict the immune response in glioma. In addition, four drugs (crizotinib, lapatinib, nilotinib, and topotecan) showed different responses between the two risk groups. Glioma cells had been classified into seven lines based on single-cell expression profiles. The five-gene glycosylation signature can accurately predict the prognosis of glioma and may offer additional guidance for immunotherapy.https://www.frontiersin.org/articles/10.3389/fphar.2023.1259051/fullglycosylationgliomatumor microenvironmentprognosisimmunitydrug sensitivity |
| spellingShingle | Yanbo Yang Haiying Teng Haiying Teng Yulian Zhang Fei Wang Fei Wang Liyan Tang Chuanpeng Zhang Chuanpeng Zhang Ziyi Hu Ziyi Hu Yuxuan Chen Yuxuan Chen Yi Ge Zhong Wang Yanbing Yu A glycosylation-related gene signature predicts prognosis, immune microenvironment infiltration, and drug sensitivity in glioma Frontiers in Pharmacology glycosylation glioma tumor microenvironment prognosis immunity drug sensitivity |
| title | A glycosylation-related gene signature predicts prognosis, immune microenvironment infiltration, and drug sensitivity in glioma |
| title_full | A glycosylation-related gene signature predicts prognosis, immune microenvironment infiltration, and drug sensitivity in glioma |
| title_fullStr | A glycosylation-related gene signature predicts prognosis, immune microenvironment infiltration, and drug sensitivity in glioma |
| title_full_unstemmed | A glycosylation-related gene signature predicts prognosis, immune microenvironment infiltration, and drug sensitivity in glioma |
| title_short | A glycosylation-related gene signature predicts prognosis, immune microenvironment infiltration, and drug sensitivity in glioma |
| title_sort | glycosylation related gene signature predicts prognosis immune microenvironment infiltration and drug sensitivity in glioma |
| topic | glycosylation glioma tumor microenvironment prognosis immunity drug sensitivity |
| url | https://www.frontiersin.org/articles/10.3389/fphar.2023.1259051/full |
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