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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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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. |
format | Online Article Text |
id | pubmed-4401766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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