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Cell Commun Signal. 2017 Jan 19;15(1):6. doi: 10.1186/s12964-016-0159-5.

Unraveling the regulation of mTORC2 using logical modeling.

Author information

1
Group for Discrete Biomathematics, Department for Mathematics and Computer Science, Freie Universitaet Berlin, Arnimallee 7, Berlin, 14195, Germany. kirsten.thobe@fu-berlin.de.
2
International Research School for Scientific Computing and Computational Biology, Max-Plank Institute for Molecular Genetics, Berlin, Germany. kirsten.thobe@fu-berlin.de.
3
Laboratory of Molecular Tumor Pathology, Institute of Pathology, Charité Universitätsmedizin Berlin, Berlin, Germany.
4
Group for Discrete Biomathematics, Department for Mathematics and Computer Science, Freie Universitaet Berlin, Arnimallee 7, Berlin, 14195, Germany.
5
International Research School for Scientific Computing and Computational Biology, Max-Plank Institute for Molecular Genetics, Berlin, Germany.

Abstract

BACKGROUND:

The mammalian target of rapamycin (mTOR) is a regulator of cell proliferation, cell growth and apoptosis working through two distinct complexes: mTORC1 and mTORC2. Although much is known about the activation and inactivation of mTORC1, the processes controlling mTORC2 remain poorly characterized. Experimental and modeling studies have attempted to explain the regulation of mTORC2 but have yielded several conflicting hypotheses. More specifically, the Phosphoinositide 3-kinase (PI3K) pathway was shown to be involved in this process, but the identity of the kinase interacting with and regulating mTORC2 remains to be determined (Cybulski and Hall, Trends Biochem Sci 34:620-7, 2009).

METHOD:

We performed a literature search and identified 5 published hypotheses describing mTORC2 regulation. Based on these hypotheses, we built logical models, not only for each single hypothesis but also for all combinations and possible mechanisms among them. Based on data provided by the original studies, a systematic analysis of all models was performed.

RESULTS:

We were able to find models that account for experimental observations from every original study, but do not require all 5 hypotheses to be implemented. Surprisingly, all hypotheses were in agreement with all tested data gathered from the different studies and PI3K was identified as an essential regulator of mTORC2.

CONCLUSION:

The results and additional data suggest that more than one regulator is necessary to explain the behavior of mTORC2. Finally, this study proposes a new experiment to validate mTORC1 as second essential regulator.

KEYWORDS:

Cancer signaling; Logical modeling; mTORC2 regulation

PMID:
28103956
PMCID:
PMC5244562
DOI:
10.1186/s12964-016-0159-5
[Indexed for MEDLINE]
Free PMC Article

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