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A 5-Gene Stemness Score for Rapid Determination of Risk in Multiple Myeloma

PURPOSE: Risk stratification in patients with multiple myeloma (MM) remains a challenge. As clinicopathological characteristics have been demonstrated insufficient for exactly defining MM risk, and molecular biomarkers have become the focuses of interests. Prognostic predictions based on gene ex...

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Autores principales: Bai, Hua, Chen, Bing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244240/
https://www.ncbi.nlm.nih.gov/pubmed/32547066
http://dx.doi.org/10.2147/OTT.S249895
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author Bai, Hua
Chen, Bing
author_facet Bai, Hua
Chen, Bing
author_sort Bai, Hua
collection PubMed
description PURPOSE: Risk stratification in patients with multiple myeloma (MM) remains a challenge. As clinicopathological characteristics have been demonstrated insufficient for exactly defining MM risk, and molecular biomarkers have become the focuses of interests. Prognostic predictions based on gene expression profiles (GEPs) have been the most accurate to this day. The purpose of our study was to construct a risk score based on stemness genes to evaluate the prognosis in MM. MATERIALS AND METHODS: Bioinformatics studies by ingenuity pathway analyses in side population (SP) and non-SP (MP) cells of MM patients were performed. Firstly, co-expression network was built to confirm hub genes associated with the top five Kyoto Encyclopedia of Genes and Genomes pathways. Functional analyses of hub genes were used to confirm the biologic functions. Next, these selective genes were utilized for construction of prognostic model, and this model was validated in independent testing sets. Finally, five stemness genes (ROCK1, GSK3B, BRAF, MAPK1 and MAPK14) were used to build a MM side population 5 (MMSP5) gene model, which was demonstrated to be forcefully prognostic compared to usual clinical prognostic parameters by multivariate cox analysis. MM patients in MMSP5 low-risk group were significantly related to better prognosis than those in high-risk group in independent testing sets. CONCLUSION: Our study provided proof-of-concept that MMSP5 model can be adopted to evaluate recurrence risk and clinical outcome for MM. The MMSP5 model evaluated in different databases clearly indicated novel risk stratification for personalized anti-MM treatments.
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spelling pubmed-72442402020-06-15 A 5-Gene Stemness Score for Rapid Determination of Risk in Multiple Myeloma Bai, Hua Chen, Bing Onco Targets Ther Original Research PURPOSE: Risk stratification in patients with multiple myeloma (MM) remains a challenge. As clinicopathological characteristics have been demonstrated insufficient for exactly defining MM risk, and molecular biomarkers have become the focuses of interests. Prognostic predictions based on gene expression profiles (GEPs) have been the most accurate to this day. The purpose of our study was to construct a risk score based on stemness genes to evaluate the prognosis in MM. MATERIALS AND METHODS: Bioinformatics studies by ingenuity pathway analyses in side population (SP) and non-SP (MP) cells of MM patients were performed. Firstly, co-expression network was built to confirm hub genes associated with the top five Kyoto Encyclopedia of Genes and Genomes pathways. Functional analyses of hub genes were used to confirm the biologic functions. Next, these selective genes were utilized for construction of prognostic model, and this model was validated in independent testing sets. Finally, five stemness genes (ROCK1, GSK3B, BRAF, MAPK1 and MAPK14) were used to build a MM side population 5 (MMSP5) gene model, which was demonstrated to be forcefully prognostic compared to usual clinical prognostic parameters by multivariate cox analysis. MM patients in MMSP5 low-risk group were significantly related to better prognosis than those in high-risk group in independent testing sets. CONCLUSION: Our study provided proof-of-concept that MMSP5 model can be adopted to evaluate recurrence risk and clinical outcome for MM. The MMSP5 model evaluated in different databases clearly indicated novel risk stratification for personalized anti-MM treatments. Dove 2020-05-18 /pmc/articles/PMC7244240/ /pubmed/32547066 http://dx.doi.org/10.2147/OTT.S249895 Text en © 2020 Bai and Chen. 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
Bai, Hua
Chen, Bing
A 5-Gene Stemness Score for Rapid Determination of Risk in Multiple Myeloma
title A 5-Gene Stemness Score for Rapid Determination of Risk in Multiple Myeloma
title_full A 5-Gene Stemness Score for Rapid Determination of Risk in Multiple Myeloma
title_fullStr A 5-Gene Stemness Score for Rapid Determination of Risk in Multiple Myeloma
title_full_unstemmed A 5-Gene Stemness Score for Rapid Determination of Risk in Multiple Myeloma
title_short A 5-Gene Stemness Score for Rapid Determination of Risk in Multiple Myeloma
title_sort 5-gene stemness score for rapid determination of risk in multiple myeloma
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244240/
https://www.ncbi.nlm.nih.gov/pubmed/32547066
http://dx.doi.org/10.2147/OTT.S249895
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