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A Multi-Element Expression Score Is A Prognostic Factor In Glioblastoma Multiforme
PURPOSE: Glioblastoma multiforme (GBM) is a highly malignant tumor of the central nervous system. Although primary GBM patients receive extensive therapies, tumors may recur within months, and there is no objective and scientific method to predict prognosis. Adoptive immunotherapy holds great promis...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805247/ https://www.ncbi.nlm.nih.gov/pubmed/31695490 http://dx.doi.org/10.2147/CMAR.S228174 |
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author | Li, Jun-Qi Wang, Qian-Ting Nie, Ying Xiao, Yun-Peng Lin, Tao Han, Ru-Jin Li, Zhe Fan, Yu-Ying Yuan, Xiao-Hui Wang, Yue-Ming Zhang, Jian He, You-Wen Liao, Hua-Xin |
author_facet | Li, Jun-Qi Wang, Qian-Ting Nie, Ying Xiao, Yun-Peng Lin, Tao Han, Ru-Jin Li, Zhe Fan, Yu-Ying Yuan, Xiao-Hui Wang, Yue-Ming Zhang, Jian He, You-Wen Liao, Hua-Xin |
author_sort | Li, Jun-Qi |
collection | PubMed |
description | PURPOSE: Glioblastoma multiforme (GBM) is a highly malignant tumor of the central nervous system. Although primary GBM patients receive extensive therapies, tumors may recur within months, and there is no objective and scientific method to predict prognosis. Adoptive immunotherapy holds great promise for GBM treatment. However, the expression profiles of the tumor-associated antigens (TAAs) and tumor immune microenvironment (TME) genes used in immunotherapy of GBM patients have not been fully described. The present study aimed to develop a predictive tool to evaluate patient survival based on full analysis of the expression levels of TAAs and TME genes. METHODS: Expression profiles of a panel of 87 TAAs and 8 TME genes significantly correlated with poor prognosis were evaluated in 44 GBM patients and 10 normal brain tissues using quantitative real-time polymerase chain reaction (qRT-PCR). A linear formula (the LASSO algorithm based in the R package) weighted by regression coefficients was used to develop a multi-element expression score to predict prognosis; this formula was cross-validated by the leave-one-out method in different GBM cohorts. RESULTS: After analysis of gene expression, clinical features, and overall survival (OS), a total of 8 TAAs (CHI3L1, EZH2, TRIOBP, PCNA, PIK3R1, PRKDC, SART3 and EPCAM), 1 TME gene (FOXP3) and 4 clinical features (neutrophil-to-lymphocyte (NLR), number of basophils (BAS), age and treatment with standard radiotherapy and chemotherapy) were included in the formula. There were significant differences between high and low scoring groups identified using the formula in different GBM cohorts (TCGA (n=732) and GEO databases (n=84)), implying poor and good prognosis, respectively. CONCLUSION: The multi-element expression score was significantly associated with OS of GBM patients. The improve understanding of TAAs and TMEs and well-defined formula could be implemented in immunotherapy for GBM to provide better care. |
format | Online Article Text |
id | pubmed-6805247 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-68052472019-11-06 A Multi-Element Expression Score Is A Prognostic Factor In Glioblastoma Multiforme Li, Jun-Qi Wang, Qian-Ting Nie, Ying Xiao, Yun-Peng Lin, Tao Han, Ru-Jin Li, Zhe Fan, Yu-Ying Yuan, Xiao-Hui Wang, Yue-Ming Zhang, Jian He, You-Wen Liao, Hua-Xin Cancer Manag Res Original Research PURPOSE: Glioblastoma multiforme (GBM) is a highly malignant tumor of the central nervous system. Although primary GBM patients receive extensive therapies, tumors may recur within months, and there is no objective and scientific method to predict prognosis. Adoptive immunotherapy holds great promise for GBM treatment. However, the expression profiles of the tumor-associated antigens (TAAs) and tumor immune microenvironment (TME) genes used in immunotherapy of GBM patients have not been fully described. The present study aimed to develop a predictive tool to evaluate patient survival based on full analysis of the expression levels of TAAs and TME genes. METHODS: Expression profiles of a panel of 87 TAAs and 8 TME genes significantly correlated with poor prognosis were evaluated in 44 GBM patients and 10 normal brain tissues using quantitative real-time polymerase chain reaction (qRT-PCR). A linear formula (the LASSO algorithm based in the R package) weighted by regression coefficients was used to develop a multi-element expression score to predict prognosis; this formula was cross-validated by the leave-one-out method in different GBM cohorts. RESULTS: After analysis of gene expression, clinical features, and overall survival (OS), a total of 8 TAAs (CHI3L1, EZH2, TRIOBP, PCNA, PIK3R1, PRKDC, SART3 and EPCAM), 1 TME gene (FOXP3) and 4 clinical features (neutrophil-to-lymphocyte (NLR), number of basophils (BAS), age and treatment with standard radiotherapy and chemotherapy) were included in the formula. There were significant differences between high and low scoring groups identified using the formula in different GBM cohorts (TCGA (n=732) and GEO databases (n=84)), implying poor and good prognosis, respectively. CONCLUSION: The multi-element expression score was significantly associated with OS of GBM patients. The improve understanding of TAAs and TMEs and well-defined formula could be implemented in immunotherapy for GBM to provide better care. Dove 2019-10-17 /pmc/articles/PMC6805247/ /pubmed/31695490 http://dx.doi.org/10.2147/CMAR.S228174 Text en © 2019 Li et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Li, Jun-Qi Wang, Qian-Ting Nie, Ying Xiao, Yun-Peng Lin, Tao Han, Ru-Jin Li, Zhe Fan, Yu-Ying Yuan, Xiao-Hui Wang, Yue-Ming Zhang, Jian He, You-Wen Liao, Hua-Xin A Multi-Element Expression Score Is A Prognostic Factor In Glioblastoma Multiforme |
title | A Multi-Element Expression Score Is A Prognostic Factor In Glioblastoma Multiforme |
title_full | A Multi-Element Expression Score Is A Prognostic Factor In Glioblastoma Multiforme |
title_fullStr | A Multi-Element Expression Score Is A Prognostic Factor In Glioblastoma Multiforme |
title_full_unstemmed | A Multi-Element Expression Score Is A Prognostic Factor In Glioblastoma Multiforme |
title_short | A Multi-Element Expression Score Is A Prognostic Factor In Glioblastoma Multiforme |
title_sort | multi-element expression score is a prognostic factor in glioblastoma multiforme |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805247/ https://www.ncbi.nlm.nih.gov/pubmed/31695490 http://dx.doi.org/10.2147/CMAR.S228174 |
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