title: Model-based global sensitivity analysis as applied to identification of anti-cancer drug targets and biomarkers of drug resistance in the ErbB2/3 network.
abstract: High levels of variability in cancer-related cellular signalling networks and a lack of parameter identifiability in large-scale network models hamper translation of the results of modelling studies into the process of anti-cancer drug development. Recently global sensitivity analysis (GSA) has been recognised as a useful technique, capable of addressing the uncertainty of the model parameters and generating valid predictions on parametric sensitivities. Here we propose a novel implementation of model-based GSA specially designed to explore how multi-parametric network perturbations affect signal propagation through cancer-related networks. We use area-under-the-curve for time course of changes in phosphorylation of proteins as a characteristic for sensitivity analysis and rank network parameters with regard to their impact on the level of key cancer-related outputs, separating strong inhibitory from stimulatory effects. This allows interpretation of the results in terms which can incorporate the effects of potential anti-cancer drugs on targets and the associated biological markers of cancer. To illustrate the method we applied it to an ErbB signalling network model and explored the sensitivity profile of its key model readout, phosphorylated Akt, in the absence and presence of the ErbB2 inhibitor pertuzumab. The method successfully identified the parameters associated with elevation or suppression of Akt phosphorylation in the ErbB2/3 network. From analysis and comparison of the sensitivity profiles of pAkt in the absence and presence of targeted drugs we derived predictions of drug targets, cancer-related biomarkers and generated hypotheses for combinatorial therapy. Several key predictions have been confirmed in experiments using human ovarian carcinoma cell lines. We also compared GSA-derived predictions with the results of local sensitivity analysis and discuss the applicability of both methods. We propose that the developed GSA procedure can serve as a refining tool in combinatorial anti-cancer drug discovery.
authors.affiliation: Centre for Systems Biology, School of Informatics, University of Edinburgh, and Breakthrough Research Unit, IGMM, Western General Hospital, Edinburgh EH9 3JD, UK. galina.lebedeva@ed.ac.uk
authors.forename: Galina
authors.initials: G
authors.lastname: Lebedeva
authors.forename: Anatoly
authors.initials: A
authors.lastname: Sorokin
authors.forename: Dana
authors.initials: D
authors.lastname: Faratian
authors.forename: Peter
authors.initials: P
authors.lastname: Mullen
authors.forename: Alexey
authors.initials: A
authors.lastname: Goltsov
authors.forename: Simon P
authors.initials: SP
authors.lastname: Langdon
authors.forename: David J
authors.initials: DJ
authors.lastname: Harrison
authors.forename: Igor
authors.initials: I
authors.lastname: Goryanin
mesh_terms: D000465:Algorithms; D061067:Antibodies, Monoclonal, Humanized / Q000494:pharmacology; D000970:Antineoplastic Agents / Q000494:pharmacology*; D014408:Biomarkers, Tumor / Q000037:antagonists & inhibitors* / Q000378:metabolism; D045744:Cell Line, Tumor; D003198:Computer Simulation; D015195:Drug Design; D019008:Drug Resistance, Neoplasm; D005260:Female; D006801:Humans; D008954:Models, Biological; D058990:Molecular Targeted Therapy; D010051:Ovarian Neoplasms / Q000188:drug therapy* / Q000378:metabolism / Q000473:pathology; D010766:Phosphorylation; D051057:Proto-Oncogene Proteins c-akt / Q000378:metabolism; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000037:antagonists & inhibitors* / Q000378:metabolism; D020893:Receptor, ErbB-3 / Q000037:antagonists & inhibitors* / Q000378:metabolism; D015398:Signal Transduction / Q000187:drug effects*; D049490:Systems Biology; D013997:Time Factors
chemical_list: D061067:Antibodies, Monoclonal, Humanized; D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor; D051057:Proto-Oncogene Proteins c-akt; D018719:Erb-b2 Receptor Tyrosine Kinases; D020893:Receptor, ErbB-3; C508053:ERBB2 protein, human; C485206:pertuzumab
references.citation: Genome Med. 2009 Jan 20;1(1):2
references.pmid: 19348689
references.citation: Carcinogenesis. 2007 Jul;28(7):1379-86
references.pmid: 17341655
references.citation: Nat Rev Clin Oncol. 2009 Aug;6(8):455-64
references.pmid: 19581910
references.citation: Bioinformatics. 1999 Sep;15(9):749-58
references.pmid: 10498775
references.citation: Biochem J. 2008 Jan 15;409(2):519-24
references.pmid: 17877460
references.citation: Sci Signal. 2009 Jun 30;2(77):ra31
references.pmid: 19567914
references.citation: Nat Rev Cancer. 2008 Mar;8(3):227-34
references.pmid: 18273038
references.citation: J Theor Biol. 2008 Sep 7;254(1):178-96
references.pmid: 18572196
references.citation: Mol Syst Biol. 2009;5:239
references.pmid: 19156131
references.citation: Mol Biosyst. 2006 Dec;2(12):640-9
references.pmid: 17216045
references.citation: BMC Bioinformatics. 2008 Aug 15;9:342
references.pmid: 18706080
references.citation: Mol Syst Biol. 2007;3:144
references.pmid: 18004277
references.citation: Biochem J. 2009 Jan 1;417(1):e5-7
references.pmid: 19061482
references.citation: BMC Bioinformatics. 2010 Apr 23;11:202
references.pmid: 20416044
references.citation: PLoS One. 2008 Mar 12;3(3):e1782
references.pmid: 18335053
references.citation: J Cell Sci. 2007 Dec 1;120(Pt 23):4071-9
references.pmid: 18032782
references.citation: PLoS One. 2009;4(2):e4560
references.pmid: 19234599
references.citation: J Cell Sci. 2000 Dec;113 Pt 24:4499-510
references.pmid: 11082043
references.citation: Nature. 2010 Aug 12;466(7308):869-73
references.pmid: 20668451
references.citation: BMC Syst Biol. 2010 Aug 10;4:109
references.pmid: 20698988
references.citation: Cancer Res. 2010 Mar 1;70(5):1773-82
references.pmid: 20179207
references.citation: Cancer Res. 2010 Mar 15;70(6):2485-94
references.pmid: 20215504
references.citation: BMC Syst Biol. 2010 Feb 17;4:11
references.pmid: 20163703
references.citation: Syst Biol (Stevenage). 2006 Jul;153(4):201-11
references.pmid: 16986622
references.citation: Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Aug;68(2 Pt 1):021904
references.pmid: 14525003
references.citation: Cancer Res. 2009 Aug 15;69(16):6713-20
references.pmid: 19638581
references.citation: Biochem J. 2003 Jul 15;373(Pt 2):451-63
references.pmid: 12691603
references.citation: Carcinogenesis. 2010 Jan;31(1):2-8
references.pmid: 19861649
references.citation: Br J Cancer. 2008 Apr 22;98(8):1415-24
references.pmid: 18349831
references.citation: Bioinformatics. 2007 Oct 1;23(19):2612-8
references.pmid: 17660526
references.citation: Nat Protoc. 2008;3(11):1796-808
references.pmid: 18974738
references.citation: Bioinformatics. 2010 Jul 1;26(13):1675-6
references.pmid: 20444837
references.citation: Biosystems. 2006 Feb-Mar;83(2-3):248-65
references.pmid: 16236429
references.citation: Cancer Metastasis Rev. 2008 Jun;27(2):159-68
references.pmid: 18213449
references.citation: Mol Biosyst. 2007 Feb;3(2):111-6
references.pmid: 17245490
references.citation: J Biol Chem. 2011 Apr 1;286(13):11337-45
references.pmid: 21282108
references.citation: Genome Med. 2009 Sep 29;1(9):88
references.pmid: 19754960
references.citation: Nat Biotechnol. 2009 Aug;27(8):735-41
references.pmid: 19668183
references.citation: J Biol Chem. 1999 Oct 15;274(42):30169-81
references.pmid: 10514507
references.citation: Hum Mol Genet. 2011 Nov 1;20(21):4132-42
references.pmid: 21828076
references.citation: Biochem J. 2009 Jan 1;417(1):361-70
references.pmid: 18976239
references.citation: ChemMedChem. 2008 Dec;3(12):1810-38
references.pmid: 18972468
references.citation: Breast Cancer Res Treat. 2010 Nov;124(1):1-11
references.pmid: 20803067
references.citation: Cell Signal. 2011 Feb;23(2):407-16
references.pmid: 20951800