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Understanding the mTOR signaling pathway via mathematical modeling.

ABSTRACT: The mechanistic target of rapamycin (mTOR) is a central regulatory pathway that integrates a variety of environmental cues to control cellular growth and homeostasis by intricate molecular feedbacks. In spite of extensive knowledge about its components, the molecular understanding of how these function together in space and time remains poor and there is a need for Systems Biology approaches to perform systematic analyses. In this work, we review the recent progress how the combined efforts of mathematical models and quantitative experiments shed new light on our understanding of the mTOR signaling pathway. In particular, we discuss the modeling concepts applied in mTOR signaling, the role of multiple feedbacks and the crosstalk mechanisms of mTOR with other signaling pathways. We also discuss the contribution of principles from information and network theory that have been successfully applied in dissecting design principles of the mTOR signaling network. We finally propose to classify the mTOR models in terms of the time scale and network complexity, and outline the importance of the classification toward the development of highly comprehensive and predictive models. WIREs Syst Biol Med 2017, 9:e1379. doi: 10.1002/wsbm.1379 For further resources related to this article, please visit the WIREs website.

SUBMITTER: Sulaimanov N

PROVIDER: S-EPMC5573916 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Understanding the mTOR signaling pathway via mathematical modeling.

Sulaimanov Nurgazy N Klose Martin M Busch Hauke H Boerries Melanie M

Wiley interdisciplinary reviews. Systems biology and medicine 20170210 4

The mechanistic target of rapamycin (mTOR) is a central regulatory pathway that integrates a variety of environmental cues to control cellular growth and homeostasis by intricate molecular feedbacks. In spite of extensive knowledge about its components, the molecular understanding of how these function together in space and time remains poor and there is a need for Systems Biology approaches to perform systematic analyses. In this work, we review the recent progress how the combined efforts of m ...[more]

PMID: 28186392

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Project description:BackgroundEndometrial carcinoma (EC) is one of the most common gynecological malignancies among women. Maternal embryonic leucine Zipper Kinase (MELK) is upregulated in a variety of human tumors, where it contributes to malignant phenotype and correlates with a poor prognosis. However, the biological function of MELK in EC progression remains largely unknown.MethodsWe explored the MELK expression in EC using TCGA and GEO databases and verified it using clinical samples by IHC methods. CCK-8 assay, colony formation assay, cell cycle assay, wound healing assay and subcutaneous xenograft mouse model were generated to estimate the functions of MELK and its inhibitor OTSSP167. qRT-PCR, western blotting, co-immunoprecipitation, chromatin immunoprecipitation and luciferase reporter assay were performed to uncover the underlying mechanism concerning MELK during the progression of EC.FindingsMELK was significantly elevated in patients with EC, and high expression of MELK was associated with serous EC, high histological grade, advanced clinical stage and reduced overall survival and disease-free survival. MELK knockdown decreased the ability of cell proliferation and migration in vitro and subcutaneous tumorigenesis in vivo. In addition, high expression of MELK could be regulated by transcription factor E2F1. Moreover, we found that MELK had a direct interaction with MLST8 and then activated mTORC1 and mTORC2 signaling pathway for EC progression. Furthermore, OTSSP167, an effective inhibitor, could inhibit cell proliferation driven by MELK in vivo and vitro assays.InterpretationWe have explored the crucial role of the E2F1/MELK/mTORC1/2 axis in the progression of EC, which could be served as potential therapeutic targets for treatment of EC.FundingThis research was supported by National Natural Science Foundation of China (No:81672565), the Natural Science Foundation of Shanghai (Grant NO:17ZR1421400 to Dr. Zhihong Ai) and the fundamental research funds for central universities (No: 22120180595).

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Understanding the mTOR signaling pathway via mathematical modeling.

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Understanding the mTOR signaling pathway via mathematical modeling.

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