Identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study
BACKGROUND: Gliomas are the most common primary tumors of the central nervous system. The complexity and heterogeneity of the tumor makes it difficult to obtain good biomarkers for drug development. In this study, through The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), we anal...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121073/ https://www.ncbi.nlm.nih.gov/pubmed/34026352 http://dx.doi.org/10.7717/peerj.11350 |
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author | Liu, Jieting Zhang, Hongrui Zhang, Jingyun Bing, Zhitong Wang, Yingbin Li, Qiao Yang, Kehu |
author_facet | Liu, Jieting Zhang, Hongrui Zhang, Jingyun Bing, Zhitong Wang, Yingbin Li, Qiao Yang, Kehu |
author_sort | Liu, Jieting |
collection | PubMed |
description | BACKGROUND: Gliomas are the most common primary tumors of the central nervous system. The complexity and heterogeneity of the tumor makes it difficult to obtain good biomarkers for drug development. In this study, through The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), we analyze the common diagnostic and prognostic moleculer markers in Caucasian and Asian populations, which can be used as drug targets in the future. METHODS: The RNA-seq data from Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) were analyzed to identify signatures. Based on the signatures, the prognosis index (PI) of every patient was constructed to predict the prognostic risk. Also, gene ontology (GO) functional enrichment analysis and KEGG analysis were conducted to investigate the biological functions of these mRNAs. Glioma patients’ data in the CGGA database were introduced to validate the effectiveness of the signatures among Chinese populations. Excluding the previously reported prognostic markers of gliomas from this study, the expression of HSPA5 and MTPN were examined by qRT-PCR and immunohistochemical assay. RESULTS: In total, 20 mRNAs were finally selected to build PI for patients from TCGA, including 16 high-risk genes and four low-risk genes. For Chinese patients, the log-rank test p values of PI were both less than 0.0001 in two independent datasets. And the AUCs were 0.831 and 0.907 for 3 years of two datasets, respectively. Moreover, among these 20 mRNAs, 10 and 15 mRNAs also had a significant predictive effect via univariate COX analysis in CGGA_693 and CGGA_325, respectively. qRT-PCR and Immunohistochemistry assay indicated that HSPA5 and MTPN over-expressed in Glioma samples compared to normal samples. CONCLUSION: The 20-gene signature can forecast the risk of Glioma in TCGA effectively, moreover it can also predict the risks of Chinese patients through validation in the CGGA database. HSPA5 and MTPN are possible biomarkers of gliomas suitable for all populations to improve the prognosis of these patients. |
format | Online Article Text |
id | pubmed-8121073 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81210732021-05-20 Identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study Liu, Jieting Zhang, Hongrui Zhang, Jingyun Bing, Zhitong Wang, Yingbin Li, Qiao Yang, Kehu PeerJ Bioinformatics BACKGROUND: Gliomas are the most common primary tumors of the central nervous system. The complexity and heterogeneity of the tumor makes it difficult to obtain good biomarkers for drug development. In this study, through The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), we analyze the common diagnostic and prognostic moleculer markers in Caucasian and Asian populations, which can be used as drug targets in the future. METHODS: The RNA-seq data from Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) were analyzed to identify signatures. Based on the signatures, the prognosis index (PI) of every patient was constructed to predict the prognostic risk. Also, gene ontology (GO) functional enrichment analysis and KEGG analysis were conducted to investigate the biological functions of these mRNAs. Glioma patients’ data in the CGGA database were introduced to validate the effectiveness of the signatures among Chinese populations. Excluding the previously reported prognostic markers of gliomas from this study, the expression of HSPA5 and MTPN were examined by qRT-PCR and immunohistochemical assay. RESULTS: In total, 20 mRNAs were finally selected to build PI for patients from TCGA, including 16 high-risk genes and four low-risk genes. For Chinese patients, the log-rank test p values of PI were both less than 0.0001 in two independent datasets. And the AUCs were 0.831 and 0.907 for 3 years of two datasets, respectively. Moreover, among these 20 mRNAs, 10 and 15 mRNAs also had a significant predictive effect via univariate COX analysis in CGGA_693 and CGGA_325, respectively. qRT-PCR and Immunohistochemistry assay indicated that HSPA5 and MTPN over-expressed in Glioma samples compared to normal samples. CONCLUSION: The 20-gene signature can forecast the risk of Glioma in TCGA effectively, moreover it can also predict the risks of Chinese patients through validation in the CGGA database. HSPA5 and MTPN are possible biomarkers of gliomas suitable for all populations to improve the prognosis of these patients. PeerJ Inc. 2021-05-11 /pmc/articles/PMC8121073/ /pubmed/34026352 http://dx.doi.org/10.7717/peerj.11350 Text en ©2021 Liu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Liu, Jieting Zhang, Hongrui Zhang, Jingyun Bing, Zhitong Wang, Yingbin Li, Qiao Yang, Kehu Identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study |
title | Identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study |
title_full | Identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study |
title_fullStr | Identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study |
title_full_unstemmed | Identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study |
title_short | Identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study |
title_sort | identification of robust diagnostic and prognostic gene signatures in different grades of gliomas: a retrospective study |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121073/ https://www.ncbi.nlm.nih.gov/pubmed/34026352 http://dx.doi.org/10.7717/peerj.11350 |
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