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Simulation Predicts IGFBP2-HIF1α Interaction Drives Glioblastoma Growth

Tremendous strides have been made in improving patients’ survival from cancer with one glaring exception: brain cancer. Glioblastoma is the most common, aggressive and highly malignant type of primary brain tumor. The average overall survival remains less than 1 year. Notably, cancer patients with o...

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Detalles Bibliográficos
Autores principales: Lin, Ka Wai, Liao, Angela, Qutub, Amina A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4401766/
https://www.ncbi.nlm.nih.gov/pubmed/25884993
http://dx.doi.org/10.1371/journal.pcbi.1004169
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author Lin, Ka Wai
Liao, Angela
Qutub, Amina A.
author_facet Lin, Ka Wai
Liao, Angela
Qutub, Amina A.
author_sort Lin, Ka Wai
collection PubMed
description Tremendous strides have been made in improving patients’ survival from cancer with one glaring exception: brain cancer. Glioblastoma is the most common, aggressive and highly malignant type of primary brain tumor. The average overall survival remains less than 1 year. Notably, cancer patients with obesity and diabetes have worse outcomes and accelerated progression of glioblastoma. The root cause of this accelerated progression has been hypothesized to involve the insulin signaling pathway. However, while the process of invasive glioblastoma progression has been extensively studied macroscopically, it has not yet been well characterized with regards to intracellular insulin signaling. In this study we connect for the first time microscale insulin signaling activity with macroscale glioblastoma growth through the use of computational modeling. Results of the model suggest a novel observation: feedback from IGFBP2 to HIF1α is integral to the sustained growth of glioblastoma. Our study suggests that downstream signaling from IGFI to HIF1α, which has been the target of many insulin signaling drugs in clinical trials, plays a smaller role in overall tumor growth. These predictions strongly suggest redirecting the focus of glioma drug candidates on controlling the feedback between IGFBP2 and HIF1α.
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spelling pubmed-44017662015-04-21 Simulation Predicts IGFBP2-HIF1α Interaction Drives Glioblastoma Growth Lin, Ka Wai Liao, Angela Qutub, Amina A. PLoS Comput Biol Research Article Tremendous strides have been made in improving patients’ survival from cancer with one glaring exception: brain cancer. Glioblastoma is the most common, aggressive and highly malignant type of primary brain tumor. The average overall survival remains less than 1 year. Notably, cancer patients with obesity and diabetes have worse outcomes and accelerated progression of glioblastoma. The root cause of this accelerated progression has been hypothesized to involve the insulin signaling pathway. However, while the process of invasive glioblastoma progression has been extensively studied macroscopically, it has not yet been well characterized with regards to intracellular insulin signaling. In this study we connect for the first time microscale insulin signaling activity with macroscale glioblastoma growth through the use of computational modeling. Results of the model suggest a novel observation: feedback from IGFBP2 to HIF1α is integral to the sustained growth of glioblastoma. Our study suggests that downstream signaling from IGFI to HIF1α, which has been the target of many insulin signaling drugs in clinical trials, plays a smaller role in overall tumor growth. These predictions strongly suggest redirecting the focus of glioma drug candidates on controlling the feedback between IGFBP2 and HIF1α. Public Library of Science 2015-04-17 /pmc/articles/PMC4401766/ /pubmed/25884993 http://dx.doi.org/10.1371/journal.pcbi.1004169 Text en © 2015 Lin et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Lin, Ka Wai
Liao, Angela
Qutub, Amina A.
Simulation Predicts IGFBP2-HIF1α Interaction Drives Glioblastoma Growth
title Simulation Predicts IGFBP2-HIF1α Interaction Drives Glioblastoma Growth
title_full Simulation Predicts IGFBP2-HIF1α Interaction Drives Glioblastoma Growth
title_fullStr Simulation Predicts IGFBP2-HIF1α Interaction Drives Glioblastoma Growth
title_full_unstemmed Simulation Predicts IGFBP2-HIF1α Interaction Drives Glioblastoma Growth
title_short Simulation Predicts IGFBP2-HIF1α Interaction Drives Glioblastoma Growth
title_sort simulation predicts igfbp2-hif1α interaction drives glioblastoma growth
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4401766/
https://www.ncbi.nlm.nih.gov/pubmed/25884993
http://dx.doi.org/10.1371/journal.pcbi.1004169
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