Evidence map›Paper›PMID 28659828›Full record

ArticleFrontiers in physiology2017

Formal Modeling of mTOR Associated Biological Regulatory Network Reveals Novel Therapeutic Strategy for the Treatment of Cancer.

Zurah Bibi, Jamil Ahmad, Amnah Siddiqa, Rehan Z Paracha, Tariq Saeed, Amjad Ali, Hussnain Ahmed Janjua, Shakir Ullah, Emna Ben Abdallah, Olivier Roux

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 34% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 3 countries.

Zurah BibiResearch Centre for Modeling and Simulation, National University of Sciences and TechnologyIslamabad, Pakistan.
Jamil AhmadResearch Centre for Modeling and Simulation, National University of Sciences and TechnologyIslamabad, Pakistan.
Amnah SiddiqaResearch Centre for Modeling and Simulation, National University of Sciences and TechnologyIslamabad, Pakistan.
Rehan Z ParachaResearch Centre for Modeling and Simulation, National University of Sciences and TechnologyIslamabad, Pakistan.
Tariq SaeedResearch Centre for Modeling and Simulation, National University of Sciences and TechnologyIslamabad, Pakistan.
Amjad AliAtta-Ur-Rahman School of Applied Biosciences, National University of Sciences and TechnologyIslamabad, Pakistan.
Hussnain Ahmed JanjuaAtta-Ur-Rahman School of Applied Biosciences, National University of Sciences and TechnologyIslamabad, Pakistan.
Shakir UllahSchool of Business, Stratford UniversityFalls Church, VA, United States.
Emna Ben AbdallahIRCCyN UMR Centre National de la Recherche Scientifique 6597, BP 92101Nantes, France.
Olivier RouxIRCCyN UMR Centre National de la Recherche Scientifique 6597, BP 92101Nantes, France.
National University of Sciences and Technology · PKCentre National de la Recherche Scientifique · FRStratford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cellular homeostasis is a continuous phenomenon that if compromised can lead to several disorders including cancer. There is a need to understand the dynamics of cellular proliferation to get deeper insights into the prevalence of cancer. Mechanistic Target of Rapamycin (mTOR) is implicated as the central regulator of the metabolic pathway involved in growth whereas its two distinct complexes mTORC1 and mTORC2 perform particular functions in cellular propagation. To date, mTORC1 is a well defined therapeutic target to inhibit uncontrolled cell division, while the role of mTORC2 is not well characterized. Therefore, the current study is designed to understand the signaling dynamics of mTOR and its partner proteins such as PI3K, PTEN, mTORC2, PKB (Akt), mTORC1, and FOXO. For this purpose, a qualitative model of mTOR-associated Biological Regulatory Network (BRN) is constructed to predict its regulatory behaviors which may not be predictable otherwise. The depleted expression of PTEN and FOXO along with the overexpression of PI3K, mTORC2, mTORC1 and Akt is predicted as a stable steady state which is in accordance with their observed expression levels in the progression of various cancers. The qualitative model also predicts the homeostasis of all the entities in the form of qualitative cycles. The significant qualitative (discrete) cycle is identified by analyzing betweenness centralities of the qualitative (discrete) states. This cycle is further refined as a linear hybrid automaton model with the production (activation) and degradation (inhibition) time delays in order to analyze the real-time constraints for its existence. The analysis of the hybrid model provides a formal proof that during homeostasis the inhibition time delay of Akt is less than the inhibition time delay of mTORC2. In conclusion, our observations characterize that in homeostasis Akt is degraded with a faster rate than mTORC2 which suggests that the inhibition of Akt along with the activation of mTORC2 may be a better therapeutic strategy for the treatment of cancer.

Indexed as

Biological regulatory networks (BRNs)CancerModel checkingmTOR signaling pathwayQualitative modelingRené ThomasSMBioNet

Identifiers

PMID28659828
PMCPMC5468443
OpenAlexW2624869776

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.