Autonomous rhythmic activity in glioma networks drives brain tumor growth
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA889854 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR21882946_1.fastq.gz | Fastqsanger.gz | |||
| SRR21882946_2.fastq.gz | Fastqsanger.gz | |||
| SRR21882947_1.fastq.gz | Fastqsanger.gz | |||
| SRR21882947_2.fastq.gz | Fastqsanger.gz | |||
| SRR21882948_1.fastq.gz | Fastqsanger.gz |
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Project description:Virtually every mammalian tissue exhibits rhythmic expression in thousands of genes, which activate tissue-specific processes at appropriate times of the day. Much of this rhythmic expression is thought to be driven cell-autonomously by molecular circadian clocks present throughout the body. However, increasing evidence suggests that systemic signals, and more specifically rhythmic food intake (RFI), can regulate rhythmic gene expression independently of the circadian clock. To determine the relative contribution of cell autonomous clocks versus RFI in the regulation of rhythmic gene expression, we developed a system that allows long-term manipulation of the daily rhythm of food intake in the mouse, and analyzed liver gene expression by RNA-Seq in mice fed ad libitum, only at night, or arrhythmically (mouse eating 1/8th of their daily food intake every 3 hours). We show that 70% of the cycling mouse liver transcriptome loses rhythmicity under arrhythmic feeding. Remarkably, this loss of rhythmic gene expression under arrhythmic feeding is independent of the liver circadian clock, which continues to exhibit normal oscillations in core clock gene expression. Many genes that lose rhythmicity participate in the regulation of metabolic processes such as lipogenesis and glycogenesis, likely contributing to an increased sensitivity to insulin that was observed in arrhythmically-fed mice. We also show that night-restricted feeding significantly increases the number of rhythmically expressed genes as well as the amplitude of the rhythms. Together, these results indicate that metabolic transcription factors control a large fraction of the rhythmic mouse liver transcriptome, and demonstrate that systemic signals driven by rhythmic food intake play a more important role than the cell-autonomous circadian clock in driving rhythms in liver gene expression and metabolic functions.
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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.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models .
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide.
Please refer to CC0 Public Domain Dedication for more information.
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