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使用老年转化布尔模型对寿命分子决定因素的综合研究方法。

A comprehensive approach to the molecular determinants of lifespan using a Boolean model of geroconversion.

作者信息

Verlingue Loic, Dugourd Aurélien, Stoll Gautier, Barillot Emmanuel, Calzone Laurence, Londoño-Vallejo Arturo

机构信息

Institut Curie, CNRS, UMR3244, Telomere and Cancer Laboratory, PSL Research University, 75005, Paris, France.

Department of Medical Oncology, Institut Curie, 75005, Paris, France.

出版信息

Aging Cell. 2016 Dec;15(6):1018-1026. doi: 10.1111/acel.12504. Epub 2016 Sep 9.

DOI:10.1111/acel.12504
PMID:27613445
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6398530/
Abstract

Altered molecular responses to insulin and growth factors (GF) are responsible for late-life shortening diseases such as type-2 diabetes mellitus (T2DM) and cancers. We have built a network of the signaling pathways that control S-phase entry and a specific type of senescence called geroconversion. We have translated this network into a Boolean model to study possible cell phenotype outcomes under diverse molecular signaling conditions. In the context of insulin resistance, the model was able to reproduce the variations of the senescence level observed in tissues related to T2DM's main morbidity and mortality. Furthermore, by calibrating the pharmacodynamics of mTOR inhibitors, we have been able to reproduce the dose-dependent effect of rapamycin on liver degeneration and lifespan expansion in wild-type and HER2-neu mice. Using the model, we have finally performed an in silico prospective screen of the risk-benefit ratio of rapamycin dosage for healthy lifespan expansion strategies. We present here a comprehensive prognostic and predictive systems biology tool for human aging.

摘要

对胰岛素和生长因子（GF）的分子反应改变是导致2型糖尿病（T2DM）和癌症等缩短寿命的晚期疾病的原因。我们构建了一个控制S期进入和一种称为老年转化的特定衰老类型的信号通路网络。我们已将此网络转化为布尔模型，以研究在不同分子信号条件下可能的细胞表型结果。在胰岛素抵抗的背景下，该模型能够重现与T2DM主要发病率和死亡率相关的组织中观察到的衰老水平变化。此外，通过校准mTOR抑制剂的药效学，我们能够重现雷帕霉素对野生型和HER2-neu小鼠肝脏退化和寿命延长的剂量依赖性效应。使用该模型，我们最终对雷帕霉素剂量用于健康寿命延长策略的风险效益比进行了计算机前瞻性筛选。我们在此展示了一种用于人类衰老的综合预后和预测系统生物学工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/7ed5117daa90/ACEL-15-1018-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/ffd88c8847da/ACEL-15-1018-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/a6c56e1ee73d/ACEL-15-1018-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/54b2329a1a94/ACEL-15-1018-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/499a1a09b516/ACEL-15-1018-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/66c6b6f97280/ACEL-15-1018-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/7ed5117daa90/ACEL-15-1018-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/ffd88c8847da/ACEL-15-1018-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/a6c56e1ee73d/ACEL-15-1018-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/54b2329a1a94/ACEL-15-1018-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/499a1a09b516/ACEL-15-1018-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/66c6b6f97280/ACEL-15-1018-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f69f/6398530/7ed5117daa90/ACEL-15-1018-g006.jpg

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