Molecular Subtypes Based on the Stemness Index Predict Prognosis in Glioma Patients
Glioma is the common histological subtype of malignancy in the central nervous system, with high morbidity and mortality. Glioma cancer stem cells (CSCs) play essential roles in tumor recurrence and treatment resistance. Thus, exploring the stem cell-related genes and subtypes in glioma is important...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-03-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2021.616507/full |
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| author | Jun Tan Hecheng Zhu Guihua Tang Hongwei Liu Hongwei Liu Siyi Wanggou Siyi Wanggou Yudong Cao Zhaoqi Xin Quanwei Zhou Chaohong Zhan Zhaoping Wu Youwei Guo Zhipeng Jiang Ming Zhao Caiping Ren Xingjun Jiang Wen Yin |
| author_facet | Jun Tan Hecheng Zhu Guihua Tang Hongwei Liu Hongwei Liu Siyi Wanggou Siyi Wanggou Yudong Cao Zhaoqi Xin Quanwei Zhou Chaohong Zhan Zhaoping Wu Youwei Guo Zhipeng Jiang Ming Zhao Caiping Ren Xingjun Jiang Wen Yin |
| author_sort | Jun Tan |
| collection | DOAJ |
| description | Glioma is the common histological subtype of malignancy in the central nervous system, with high morbidity and mortality. Glioma cancer stem cells (CSCs) play essential roles in tumor recurrence and treatment resistance. Thus, exploring the stem cell-related genes and subtypes in glioma is important. In this study, we collected the RNA-sequencing (RNA-seq) data and clinical information of glioma patients from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. With the differentially expressed genes (DEGs) and weighted gene correlation network analysis (WGCNA), we identified 86 mRNA expression-based stemness index (mRNAsi)-related genes in 583 samples from TCGA RNA-seq dataset. Furthermore, these samples from TCGA database could be divided into two significantly different subtypes with different prognoses based on the mRNAsi corresponding gene, which could also be validated in the CGGA database. The clinical characteristics and immune cell infiltrate distribution of the two stemness subtypes are different. Then, functional enrichment analyses were performed to identify the different gene ontology (GO) terms and pathways in the two different subtypes. Moreover, we constructed a stemness subtype-related risk score model and nomogram to predict the prognosis of glioma patients. Finally, we selected one gene (ETV2) from the risk score model for experimental validation. The results showed that ETV2 can contribute to the invasion, migration, and epithelial-mesenchymal transition (EMT) process of glioma. In conclusion, we identified two distinct molecular subtypes and potential therapeutic targets of glioma, which could provide new insights for the development of precision diagnosis and prognostic prediction for glioma patients. |
| first_indexed | 2024-12-13T17:43:22Z |
| format | Article |
| id | doaj.art-ead78a693b264b008cd1c73fc712d978 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-13T17:43:22Z |
| publishDate | 2021-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-ead78a693b264b008cd1c73fc712d9782022-12-21T23:36:42ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-03-011210.3389/fgene.2021.616507616507Molecular Subtypes Based on the Stemness Index Predict Prognosis in Glioma PatientsJun Tan0Hecheng Zhu1Guihua Tang2Hongwei Liu3Hongwei Liu4Siyi Wanggou5Siyi Wanggou6Yudong Cao7Zhaoqi Xin8Quanwei Zhou9Chaohong Zhan10Zhaoping Wu11Youwei Guo12Zhipeng Jiang13Ming Zhao14Caiping Ren15Xingjun Jiang16Wen Yin17Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaChangsha Kexin Cancer Hospital, Changsha, ChinaDepartment of Clinical Laboratory, Hunan Provincial People’s Hospital (First Affiliated Hospital of Hunan Normal University), Changsha, ChinaDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaHunan International Scientific and Technological Cooperation Base of Brain Tumor Research, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaHunan International Scientific and Technological Cooperation Base of Brain Tumor Research, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaChangsha Kexin Cancer Hospital, Changsha, ChinaKey Laboratory for Carcinogenesis of Chinese Ministry of Health, School of Basic Medical Science, Cancer Research Institute, Central South University, Changsha, ChinaDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, ChinaGlioma is the common histological subtype of malignancy in the central nervous system, with high morbidity and mortality. Glioma cancer stem cells (CSCs) play essential roles in tumor recurrence and treatment resistance. Thus, exploring the stem cell-related genes and subtypes in glioma is important. In this study, we collected the RNA-sequencing (RNA-seq) data and clinical information of glioma patients from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. With the differentially expressed genes (DEGs) and weighted gene correlation network analysis (WGCNA), we identified 86 mRNA expression-based stemness index (mRNAsi)-related genes in 583 samples from TCGA RNA-seq dataset. Furthermore, these samples from TCGA database could be divided into two significantly different subtypes with different prognoses based on the mRNAsi corresponding gene, which could also be validated in the CGGA database. The clinical characteristics and immune cell infiltrate distribution of the two stemness subtypes are different. Then, functional enrichment analyses were performed to identify the different gene ontology (GO) terms and pathways in the two different subtypes. Moreover, we constructed a stemness subtype-related risk score model and nomogram to predict the prognosis of glioma patients. Finally, we selected one gene (ETV2) from the risk score model for experimental validation. The results showed that ETV2 can contribute to the invasion, migration, and epithelial-mesenchymal transition (EMT) process of glioma. In conclusion, we identified two distinct molecular subtypes and potential therapeutic targets of glioma, which could provide new insights for the development of precision diagnosis and prognostic prediction for glioma patients.https://www.frontiersin.org/articles/10.3389/fgene.2021.616507/fullmolecular subtypesstemness indexgliomaprognostic signatureimmune infiltration |
| spellingShingle | Jun Tan Hecheng Zhu Guihua Tang Hongwei Liu Hongwei Liu Siyi Wanggou Siyi Wanggou Yudong Cao Zhaoqi Xin Quanwei Zhou Chaohong Zhan Zhaoping Wu Youwei Guo Zhipeng Jiang Ming Zhao Caiping Ren Xingjun Jiang Wen Yin Molecular Subtypes Based on the Stemness Index Predict Prognosis in Glioma Patients Frontiers in Genetics molecular subtypes stemness index glioma prognostic signature immune infiltration |
| title | Molecular Subtypes Based on the Stemness Index Predict Prognosis in Glioma Patients |
| title_full | Molecular Subtypes Based on the Stemness Index Predict Prognosis in Glioma Patients |
| title_fullStr | Molecular Subtypes Based on the Stemness Index Predict Prognosis in Glioma Patients |
| title_full_unstemmed | Molecular Subtypes Based on the Stemness Index Predict Prognosis in Glioma Patients |
| title_short | Molecular Subtypes Based on the Stemness Index Predict Prognosis in Glioma Patients |
| title_sort | molecular subtypes based on the stemness index predict prognosis in glioma patients |
| topic | molecular subtypes stemness index glioma prognostic signature immune infiltration |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2021.616507/full |
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