Predictive mathematical models of cancer signalling pathways

被引：47

作者：

Bachmann, J. ^{[1
]}

Raue, A. ^{[2
,3
,4
]}

Schilling, M. ^{[1
]}

Becker, V. ^{[1
]}

Timmer, J. ^{[2
,3
,4
]}

Klingmueller, U. ^{[1
]}

机构：

[1] German Canc Res Ctr, DKFZ ZMBH Alliance, D-6900 Heidelberg, Germany

[2] Univ Freiburg, Inst Phys, BIOSS Ctr Biol Signalling Studies, D-79106 Freiburg, Germany

[3] Univ Freiburg, Freiburg Inst Adv Studies FRIAS, D-79106 Freiburg, Germany

[4] Univ Freiburg, Zentrum Biosyst Anal ZBSA, D-79106 Freiburg, Germany

来源：

JOURNAL OF INTERNAL MEDICINE | 2012年 / 271卷 / 02期

关键词：

cancer; cell biology; cytokines; hematology; lung cancer; TO-CELL VARIABILITY; SYSTEMS BIOLOGY; RECEPTOR; SURVIVAL; IDENTIFIABILITY; ERYTHROPOIESIS; TRANSCRIPTOME; HEPATOCYTES; ACTIVATION; EXPRESSION;

D O I：

10.1111/j.1365-2796.2011.02492.x

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Complex intracellular signalling networks integrate extracellular signals and convert them into cellular responses. In cancer cells, the tightly regulated and fine-tuned dynamics of information processing in signalling networks is altered, leading to uncontrolled cell proliferation, survival and migration. Systems biology combines mathematical modelling with comprehensive, quantitative, time-resolved data and is most advanced in addressing dynamic properties of intracellular signalling networks. Here, we introduce different modelling approaches and their application to medical systems biology, focusing on the identifiability of parameters in ordinary differential equation models and their importance in network modelling to predict cellular decisions. Two related examples are given, which include processing of ligand-encoded information and dual feedback regulation in erythropoietin (Epo) receptor signalling. Finally, we review the current understanding of how systems biology could foster the development of new treatment strategies in the context of lung cancer and anaemia.

引用

页码：155 / 165

页数：11

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