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Plasmatic circRNA Predicting the Occurrence of Human Glioblastoma

BACKGROUND: Glioblastoma (GBM) is the most common primary malignant tumor in adult central nervous system and results in disappointing survival outcomes. Although the diagnosis and therapy approach have been developed recently, the prognosis of GBM remains poor. A novel, minimally invasive biomarker...

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Autores principales: Chen, Ainian, Zhong, Lingling, Ju, Keju, Lu, Ting, Lv, Jia, Cao, Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196774/
https://www.ncbi.nlm.nih.gov/pubmed/32425605
http://dx.doi.org/10.2147/CMAR.S248621
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author Chen, Ainian
Zhong, Lingling
Ju, Keju
Lu, Ting
Lv, Jia
Cao, Hua
author_facet Chen, Ainian
Zhong, Lingling
Ju, Keju
Lu, Ting
Lv, Jia
Cao, Hua
author_sort Chen, Ainian
collection PubMed
description BACKGROUND: Glioblastoma (GBM) is the most common primary malignant tumor in adult central nervous system and results in disappointing survival outcomes. Although the diagnosis and therapy approach have been developed recently, the prognosis of GBM remains poor. A novel, minimally invasive biomarker for GBM is necessary for early diagnosis or prognosis prediction. METHODS: All circRNAs were detected by qRT-PCR in GBM samples including training and validation sets. We used the risk score analysis to assume the diagnosis ability for GBM. The receiver operating characteristic curve was also employed. RESULTS: Among the 14 candidates, circRNA, circNT5E, circFOXO3, circ_0001946, circ_0029426, circ-SHPRH, and circMMP9 were detected with increased levels in the training set. Further investigation in the validation set indicated that circFOXO3, circ_0029426, and circ-SHPRH might be the fingerprints for GBM compared with controls. The risk score analysis revealed that the combination of three circRNAs could distinguish the GBM from healthy control with the area under curve value of 0.980 and 0.906, respectively. CONCLUSION: The three circRNAs might be novel fingerprints for predicting the occurrence of GBM.
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spelling pubmed-71967742020-05-18 Plasmatic circRNA Predicting the Occurrence of Human Glioblastoma Chen, Ainian Zhong, Lingling Ju, Keju Lu, Ting Lv, Jia Cao, Hua Cancer Manag Res Original Research BACKGROUND: Glioblastoma (GBM) is the most common primary malignant tumor in adult central nervous system and results in disappointing survival outcomes. Although the diagnosis and therapy approach have been developed recently, the prognosis of GBM remains poor. A novel, minimally invasive biomarker for GBM is necessary for early diagnosis or prognosis prediction. METHODS: All circRNAs were detected by qRT-PCR in GBM samples including training and validation sets. We used the risk score analysis to assume the diagnosis ability for GBM. The receiver operating characteristic curve was also employed. RESULTS: Among the 14 candidates, circRNA, circNT5E, circFOXO3, circ_0001946, circ_0029426, circ-SHPRH, and circMMP9 were detected with increased levels in the training set. Further investigation in the validation set indicated that circFOXO3, circ_0029426, and circ-SHPRH might be the fingerprints for GBM compared with controls. The risk score analysis revealed that the combination of three circRNAs could distinguish the GBM from healthy control with the area under curve value of 0.980 and 0.906, respectively. CONCLUSION: The three circRNAs might be novel fingerprints for predicting the occurrence of GBM. Dove 2020-04-29 /pmc/articles/PMC7196774/ /pubmed/32425605 http://dx.doi.org/10.2147/CMAR.S248621 Text en © 2020 Chen 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
Chen, Ainian
Zhong, Lingling
Ju, Keju
Lu, Ting
Lv, Jia
Cao, Hua
Plasmatic circRNA Predicting the Occurrence of Human Glioblastoma
title Plasmatic circRNA Predicting the Occurrence of Human Glioblastoma
title_full Plasmatic circRNA Predicting the Occurrence of Human Glioblastoma
title_fullStr Plasmatic circRNA Predicting the Occurrence of Human Glioblastoma
title_full_unstemmed Plasmatic circRNA Predicting the Occurrence of Human Glioblastoma
title_short Plasmatic circRNA Predicting the Occurrence of Human Glioblastoma
title_sort plasmatic circrna predicting the occurrence of human glioblastoma
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7196774/
https://www.ncbi.nlm.nih.gov/pubmed/32425605
http://dx.doi.org/10.2147/CMAR.S248621
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