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Project description:Mosaic Analysis with Double Markers (MADM) based glioma mouse model, which homozygously lacks Tp53 and Nf1, spontaneously developed gliomas at the post-natal 90-120 days. Tp53 and Nf1 are among the most frequently mutated genes in human glioma patients. Investigating the changes of histone modifications induced by inactivation of Tp53 and Nf1 can be a clue to clarify the mechanism of gliomagenesis. We examined the histone modifications of glioma in MADM mouse at post-natal 150 days (n=3) and post-natal 8 days (n=1) and NSC, astrocyte derived from normal mice brain (both n=1) ). We used customized SurePrint G3 Mouse GE 2×400K array slides (G4858A, Agilent Technologies).
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Project description:We used microarrays to determine the gene expression profile of different types of glioma Keywords: Disease state analysis
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Project description:The paper describes a model of glioma.
Created by COPASI 4.26 (Build 213)
This model is described in the article:
A mathematical model of pre-diagnostic glioma growth
Marc Sturrock, Wenrui Hao, Judith Schwartzbaum, Grzegorz A. Rempala
J Theor Biol. 2015 September 7; 380: 299–308
Abstract:
Due to their location, the malignant gliomas of the brain in humans are very difficult to treat in advanced stages. Blood-based biomarkers for glioma are needed for more accurate evaluation of treatment response as well as early diagnosis. However, biomarker research in primary brain tumors is challenging given their relative rarity and genetic diversity. It is further complicated by variations in the permeability of the blood brain barrier that affects the amount of marker released into the bloodstream. Inspired by recent temporal data indicating a possible decrease in serum glucose levels in patients with gliomas yet to be diagnosed, we present an ordinary differential equation model to capture early stage glioma growth. The model contains glioma-glucose-immune interactions and poses a potential mechanism by which this glucose drop can be explained. We present numerical simulations, parameter sensitivity analysis, linear stability analysis and a numerical experiment whereby we show how a dormant glioma can become malignant.
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