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Simulation predicts IGFBP2-HIF1α interaction drives glioblastoma growth.

Lin KW, Liao A, Qutub AA - PLoS Comput. Biol. (2015)

Bottom Line: Tremendous strides have been made in improving patients' survival from cancer with one glaring exception: brain cancer.The average overall survival remains less than 1 year.The root cause of this accelerated progression has been hypothesized to involve the insulin signaling pathway.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioengineering, Rice University, Houston, Texas, United States of America.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Computational model results compared to glioblastoma growth data.(A) In vitro data using U87 cell line, R2 = 0.86. (B) In vivo data using LN229 cell line, R2 = 0.95. Blue points represent in vitro experiments and red lines represent the computational simulations.
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pcbi.1004169.g002: Computational model results compared to glioblastoma growth data.(A) In vitro data using U87 cell line, R2 = 0.86. (B) In vivo data using LN229 cell line, R2 = 0.95. Blue points represent in vitro experiments and red lines represent the computational simulations.

Mentions: We performed the following in vitro assay in order to form glioblastoma spheroids and track their growth: U87 cells were collected from cells plated on tissue culture flasks, and the cells were suspended to a final concentration of 45,000 cells/mL using Lonza DMEM media with 5% methocel. The cell suspensions were plated as droplets on 60 mm petri dish lids. Each plate lid contained approximately 20 droplets of 20 μl cell suspension. The lids were then inverted over a petri dish bottom containing 2 ml of PBS to keep the media from evaporating. The inverted droplets were kept in an incubator at 37°C with 5% CO2. By observing the spheroids using phase contrast imaging (Ti-E Nikon automated stage microscope system), we measured the minor and major axes of the spheroid diameters on days 1, 4, 5, and 6 after they had been seeded. The average of these measurements are displayed (Fig 2A).


Simulation predicts IGFBP2-HIF1α interaction drives glioblastoma growth.

Lin KW, Liao A, Qutub AA - PLoS Comput. Biol. (2015)

Computational model results compared to glioblastoma growth data.(A) In vitro data using U87 cell line, R2 = 0.86. (B) In vivo data using LN229 cell line, R2 = 0.95. Blue points represent in vitro experiments and red lines represent the computational simulations.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4401766&req=5

pcbi.1004169.g002: Computational model results compared to glioblastoma growth data.(A) In vitro data using U87 cell line, R2 = 0.86. (B) In vivo data using LN229 cell line, R2 = 0.95. Blue points represent in vitro experiments and red lines represent the computational simulations.
Mentions: We performed the following in vitro assay in order to form glioblastoma spheroids and track their growth: U87 cells were collected from cells plated on tissue culture flasks, and the cells were suspended to a final concentration of 45,000 cells/mL using Lonza DMEM media with 5% methocel. The cell suspensions were plated as droplets on 60 mm petri dish lids. Each plate lid contained approximately 20 droplets of 20 μl cell suspension. The lids were then inverted over a petri dish bottom containing 2 ml of PBS to keep the media from evaporating. The inverted droplets were kept in an incubator at 37°C with 5% CO2. By observing the spheroids using phase contrast imaging (Ti-E Nikon automated stage microscope system), we measured the minor and major axes of the spheroid diameters on days 1, 4, 5, and 6 after they had been seeded. The average of these measurements are displayed (Fig 2A).

Bottom Line: Tremendous strides have been made in improving patients' survival from cancer with one glaring exception: brain cancer.The average overall survival remains less than 1 year.The root cause of this accelerated progression has been hypothesized to involve the insulin signaling pathway.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioengineering, Rice University, Houston, Texas, United States of America.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus