Featured Publications
A systematic analysis of signaling reactivation and drug resistance
Kholodenko B, Rauch N, Kolch W, Rukhlenko O. A systematic analysis of signaling reactivation and drug resistance. Cell Reports 2021, 35: 109157. PMID: 34038718, PMCID: PMC8202068, DOI: 10.1016/j.celrep.2021.109157.Peer-Reviewed Original ResearchPeriodic propagating waves coordinate RhoGTPase network dynamics at the leading and trailing edges during cell migration
Bolado-Carrancio A, Rukhlenko O, Nikonova E, Tsyganov M, Wheeler A, Garcia-Munoz A, Kolch W, von Kriegsheim A, Kholodenko B. Periodic propagating waves coordinate RhoGTPase network dynamics at the leading and trailing edges during cell migration. ELife 2020, 9: e58165. PMID: 32705984, PMCID: PMC7380942, DOI: 10.7554/elife.58165.Peer-Reviewed Original ResearchScaffolding Protein Grb2-associated Binder 1 Sustains Epidermal Growth Factor-induced Mitogenic and Survival Signaling by Multiple Positive Feedback Loops*
Kiyatkin A, Aksamitiene E, Markevich NI, Borisov NM, Hoek JB, Kholodenko BN. Scaffolding Protein Grb2-associated Binder 1 Sustains Epidermal Growth Factor-induced Mitogenic and Survival Signaling by Multiple Positive Feedback Loops*. Journal Of Biological Chemistry 2006, 281: 19925-19938. PMID: 16687399, PMCID: PMC2312093, DOI: 10.1074/jbc.m600482200.Peer-Reviewed Original ResearchConceptsEpidermal growth factorRas/MAPK signalingGab1 tyrosine phosphorylationGrowth factorRole of Gab1PI3K/Akt activationMultiple positive feedback loopsProtein Grb2Mutant proteinsScaffold proteinTyrosine phosphorylationBinder 1Positive feedback loopMitogenic pathwaysMAPK signalingEssential functionsSurvival signalingDiverse perturbationsCellular responsesAkt activationCytokine receptorsPharmacological inhibitorsGab1EGF dosesGrb2
2024
Cell-specific models reveal conformation-specific RAF inhibitor combinations that synergistically inhibit ERK signaling in pancreatic cancer cells
Sevrin T, Imoto H, Robertson S, Rauch N, Dyn'ko U, Koubova K, Wynne K, Kolch W, Rukhlenko O, Kholodenko B. Cell-specific models reveal conformation-specific RAF inhibitor combinations that synergistically inhibit ERK signaling in pancreatic cancer cells. Cell Reports 2024, 43: 114710. PMID: 39240715, PMCID: PMC11474227, DOI: 10.1016/j.celrep.2024.114710.Peer-Reviewed Original ResearchConceptsPancreatic ductal adenocarcinomaResistance to RAFResistant PDAC cellsPancreatic cancer cellsPancreatic ductal adenocarcinoma cell linesProtein expression profilesTumor-specific variationsIsogenic pairsCell-specific modelsConformational specificityERK signalingInhibitor combinationsERK pathwayKRAS mutationsTargeted therapyExpression profilesMEK inhibitorsDuctal adenocarcinomaCancer cellsKRAS mutantPhospho-ERKCell linesPDAC cellsCell viabilityDifferential sensitivity
2023
Reversing pathological cell states: the road less travelled can extend the therapeutic horizon
Kholodenko B, Kolch W, Rukhlenko O. Reversing pathological cell states: the road less travelled can extend the therapeutic horizon. Trends In Cell Biology 2023, 33: 913-923. PMID: 37263821, PMCID: PMC10593090, DOI: 10.1016/j.tcb.2023.04.004.Peer-Reviewed Original Research
2020
Systems biology approaches to macromolecules: the role of dynamic protein assemblies in information processing
Rukhlenko O, Kholodenko B, Kolch W. Systems biology approaches to macromolecules: the role of dynamic protein assemblies in information processing. Current Opinion In Structural Biology 2020, 67: 61-68. PMID: 33126139, PMCID: PMC8062579, DOI: 10.1016/j.sbi.2020.09.007.Peer-Reviewed Original ResearchConceptsProtein assembliesProtein complex dynamicsDynamic protein assembliesMacromolecular protein assembliesSignal transduction networksSystems biology approachMEK-ERK pathwayProtein complexesTransduction networksCellular processesBiology approachMolecular machinesRAS-RAFOncogenic mutationsStructural studiesDrug resistanceTemporal dynamicsAssemblyRecent progressTumorigenesisMutationsPicture highlightsFine tuningPathwayDynamic processAcute Phase Response as a Biological Mechanism‐of‐Action of (Nano)particle‐Induced Cardiovascular Disease
Hadrup N, Zhernovkov V, Jacobsen N, Voss C, Strunz M, Ansari M, Schiller H, Halappanavar S, Poulsen S, Kholodenko B, Stoeger T, Saber A, Vogel U. Acute Phase Response as a Biological Mechanism‐of‐Action of (Nano)particle‐Induced Cardiovascular Disease. Small 2020, 16: e1907476. PMID: 32227434, DOI: 10.1002/smll.201907476.Peer-Reviewed Original ResearchConceptsAcute phase responseCardiovascular diseaseInduced Cardiovascular DiseasePhase responseInhalation of particlesLung cancerLung depositionImportant scientific evidenceOccupational diseasesDiseaseScientific evidencePotential health hazardsBiological mechanismsHealth hazardsRiskResponseImportant mechanismHigh levelsRisk assessmentCausal relationshipInhalationCancerExtensive rewiring of the EGFR network in colorectal cancer cells expressing transforming levels of KRASG13D
Kennedy S, Jarboui M, Srihari S, Raso C, Bryan K, Dernayka L, Charitou T, Bernal-Llinares M, Herrera-Montavez C, Krstic A, Matallanas D, Kotlyar M, Jurisica I, Curak J, Wong V, Stagljar I, LeBihan T, Imrie L, Pillai P, Lynn M, Fasterius E, Al-Khalili Szigyarto C, Breen J, Kiel C, Serrano L, Rauch N, Rukhlenko O, Kholodenko B, Iglesias-Martinez L, Ryan C, Pilkington R, Cammareri P, Sansom O, Shave S, Auer M, Horn N, Klose F, Ueffing M, Boldt K, Lynn D, Kolch W. Extensive rewiring of the EGFR network in colorectal cancer cells expressing transforming levels of KRASG13D. Nature Communications 2020, 11: 499. PMID: 31980649, PMCID: PMC6981206, DOI: 10.1038/s41467-019-14224-9.Peer-Reviewed Original ResearchConceptsEpidermal growth factor receptor (EGFR) networkGrowth factor receptor networkFundamental biological processesColorectal cancer cellsCancer cellsEGFR networkTranscriptional regulationProtein complexesExtensive rewiringCellular phenotypesInteraction networksBiological processesOncogenic mutationsOncogenic KRAS mutationsReceptor networkGenetic alterationsProtein expressionPPInsMutationsCellsInteractorsPhosphorylationRewiringPoor patient outcomesSignal flow
2018
Impact of measurement noise, experimental design, and estimation methods on Modular Response Analysis based network reconstruction
Thomaseth C, Fey D, Santra T, Rukhlenko OS, Radde NE, Kholodenko BN. Impact of measurement noise, experimental design, and estimation methods on Modular Response Analysis based network reconstruction. Scientific Reports 2018, 8: 16217. PMID: 30385767, PMCID: PMC6212399, DOI: 10.1038/s41598-018-34353-3.Peer-Reviewed Original ResearchConceptsModular Response AnalysisNetwork reconstructionSteady-state response curvesStatistical conceptsMeasurement noisePropagation of noiseNoise settingsEstimation methodNetwork structureTerms of accuracyLarge perturbationsResponse analysisDifferent replicatesPerturbation dataRegression strategyNoiseDissecting RAF Inhibitor Resistance by Structure-based Modeling Reveals Ways to Overcome Oncogenic RAS Signaling
Rukhlenko OS, Khorsand F, Krstic A, Rozanc J, Alexopoulos LG, Rauch N, Erickson KE, Hlavacek WS, Posner RG, Gómez-Coca S, Rosta E, Fitzgibbon C, Matallanas D, Rauch J, Kolch W, Kholodenko BN. Dissecting RAF Inhibitor Resistance by Structure-based Modeling Reveals Ways to Overcome Oncogenic RAS Signaling. Cell Systems 2018, 7: 161-179.e14. PMID: 30007540, PMCID: PMC6149545, DOI: 10.1016/j.cels.2018.06.002.Peer-Reviewed Original ResearchConceptsOncogenic RASERK signalingRAS/ERK pathwayRAF inhibitorsOncogenic Ras signalingMEK/ERKStructure-based modelingRAF inhibitor resistanceRAS mutant tumorsRas signalingPosttranslational modificationsRaf kinaseERK activityRAF dimerizationDrug-protein interactionsERK pathwayMultiple inhibitorsColony formationSignalingMutant NRASCell proliferationDrug designParadoxical activationInhibitor resistanceMechanistic dynamic model
2016
Rac1 and RhoA: Networks, loops and bistability
Nguyen LK, Kholodenko BN, von Kriegsheim A. Rac1 and RhoA: Networks, loops and bistability. Small GTPases 2016, 9: 316-321. PMID: 27533896, PMCID: PMC5997137, DOI: 10.1080/21541248.2016.1224399.Peer-Reviewed Original ResearchHER2-HER3 dimer quantification by FLIM-FRET predicts breast cancer metastatic relapse independently of HER2 IHC status
Weitsman G, Barber PR, Nguyen LK, Lawler K, Patel G, Woodman N, Kelleher MT, Pinder SE, Rowley M, Ellis PA, Purushotham AD, Coolen AC, Kholodenko BN, Vojnovic B, Gillett C, Ng T. HER2-HER3 dimer quantification by FLIM-FRET predicts breast cancer metastatic relapse independently of HER2 IHC status. Oncotarget 2016, 7: 51012-51026. PMID: 27618787, PMCID: PMC5239455, DOI: 10.18632/oncotarget.9963.Peer-Reviewed Original ResearchConceptsGroup of patientsMetastatic relapsePredictive biomarkersHER2 proteinHER2 IHC statusOnly predictive biomarkerInvasive breast cancerNovel prognostic biomarkerOverexpression of HER2Important prognostic markerBreast cancer tissuesHistology-based analysisSignificant clinical utilityHER2-HER3 dimersIHC statusHER2 expressionTissue microarray coresPrognostic markerBreast cancerPrognostic biomarkerHER2-HER3 heterodimersClinical utilityCancer tissuesTumor progressionDriver of proliferationThree-factor models versus time series models: quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data
Frank TD, Kiyatkin A, Cheong A, Kholodenko BN. Three-factor models versus time series models: quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data. Mathematical Medicine And Biology A Journal Of The IMA 2016, 34: 177-191. PMID: 27079221, DOI: 10.1093/imammb/dqw001.Peer-Reviewed Original ResearchConceptsBeta-adrenoceptor agonist clenbuterolGlucocorticoid receptor systemHuman embryonic kidney 293 cellsEmbryonic kidney 293 cellsAgonist clenbuterolTumor necrosisCritical time windowExtracellular signal-regulated kinases 1Mood disordersAntagonist drugsEpidermal growth factorAnimal studiesKidney 293 cellsCell responsesSignal-regulated kinases 1Behavioral levelGrowth factorCertain antagonistsLongitudinal dataERK activationHEK293 cellsKinase 1Cellular levelTime effectsTranscriptional activity
2015
Drug Resistance Resulting from Kinase Dimerization Is Rationalized by Thermodynamic Factors Describing Allosteric Inhibitor Effects
Kholodenko BN. Drug Resistance Resulting from Kinase Dimerization Is Rationalized by Thermodynamic Factors Describing Allosteric Inhibitor Effects. Cell Reports 2015, 12: 1939-1949. PMID: 26344764, DOI: 10.1016/j.celrep.2015.08.014.Peer-Reviewed Original ResearchG Protein–Coupled Receptor Signaling Networks from a Systems Perspective
Roth S, Kholodenko B, Smit M, Bruggeman F. G Protein–Coupled Receptor Signaling Networks from a Systems Perspective. Molecular Pharmacology 2015, 88: 604-616. PMID: 26162865, DOI: 10.1124/mol.115.100057.Peer-Reviewed Original ResearchConceptsG protein-coupled receptorsRole of GPCRsSignal transduction networksProtein-protein interactionsSystems biology studiesSystems biology researchProtein-coupled receptorsCell surface receptorsSignaling networksExtracellular signalsMammalian cellsSignaling routeSingle proteinIntracellular proteinsExternal cuesAdaptive responseBiophysical conceptsProteinReceptorsFeedforward circuitryCellsConformationResponseCuesMitogen-Inducible Gene-6 Mediates Feedback Inhibition from Mutated BRAF towards the Epidermal Growth Factor Receptor and Thereby Limits Malignant Transformation
Milewska M, Romano D, Herrero A, Guerriero ML, Birtwistle M, Quehenberger F, Hatzl S, Kholodenko BN, Segatto O, Kolch W, Zebisch A. Mitogen-Inducible Gene-6 Mediates Feedback Inhibition from Mutated BRAF towards the Epidermal Growth Factor Receptor and Thereby Limits Malignant Transformation. PLOS ONE 2015, 10: e0129859. PMID: 26065894, PMCID: PMC4466796, DOI: 10.1371/journal.pone.0129859.Peer-Reviewed Original ResearchMeSH Keywords3T3 CellsAdaptor Proteins, Signal TransducingAdultAnimalsCell Transformation, NeoplasticChlorocebus aethiopsCOS CellsErbB ReceptorsFeedback, PhysiologicalGene Expression Regulation, NeoplasticHEK293 CellsHumansMiceMiddle AgedMutation, MissenseProto-Oncogene Proteins B-rafThyroid NeoplasmsTumor Suppressor ProteinsConceptsMitogen-inducible gene 6Epidermal growth factor receptorOncogenic BRAFGrowth factor receptorGene 6Mig-6 expressionRAS-ERK pathwayRAS-ERK signalingFactor receptorNegative regulatory loopSignal-regulated kinaseInducible gene 6Focus formation assayBRAF kinase activityGenetic interactionsPI3K/AktCellular transformationTranscriptional levelBRAF functionCell line modelsKinase activityEGFR activationMethylation dataRegulatory loopNegative feedback circuitSignalling mechanisms regulating phenotypic changes in breast cancer cells
Volinsky N, McCarthy CJ, von Kriegsheim A, Saban N, Okada-Hatakeyama M, Kolch W, Kholodenko BN. Signalling mechanisms regulating phenotypic changes in breast cancer cells. Bioscience Reports 2015, 35: e00178. PMID: 25643809, PMCID: PMC4370098, DOI: 10.1042/bsr20140172.Peer-Reviewed Original ResearchConceptsCell fate decisionsATP-citrate lyaseFate decisionsPhenotypic changesBreast cancer cellsEpidermal growth factorCell fate decision processesCancer cellsLipid accumulationIrreversible phenotypic changesPhosphoinositide-3 kinaseSimilar cellular responsesPI3K pathwayGrowth factorRapamycin complexKinase pathwayNegative regulatorMolecular mechanismsCellular responsesMetabolic pathwaysMammalian targetK pathwayCitrate lyaseLipogenic pathwayCell proliferationNetwork-based identification of feedback modules that control RhoA activity and cell migration
Kim TH, Monsefi N, Song JH, von Kriegsheim A, Vandamme D, Pertz O, Kholodenko BN, Kolch W, Cho KH. Network-based identification of feedback modules that control RhoA activity and cell migration. Journal Of Molecular Cell Biology 2015, 7: 242-252. PMID: 25780058, DOI: 10.1093/jmcb/mjv017.Peer-Reviewed Original ResearchConceptsRho family GTPasesCancer cell migrationCell migrationRhoA activityControl cell migrationBoolean network modelNetwork-based identificationPotential new targetsRho activationGTPasesSrc inhibitionGenetic backgroundCsk inhibitionMost cancer deathsActivation stateNew targetsNew insightsMigrationCskSrcFAKRewiringInhibitionEGFProtrusion
2013
Systems biology‐embedded target validation: improving efficacy in drug discovery
Vandamme D, Minke BA, Fitzmaurice W, Kholodenko BN, Kolch W. Systems biology‐embedded target validation: improving efficacy in drug discovery. WIREs Mechanisms Of Disease 2013, 6: 1-11. PMID: 24214316, DOI: 10.1002/wsbm.1253.Peer-Reviewed Original ResearchConceptsSystems biology approachBiology approachDrug discoveryPotential drug targetsOmics technologiesMolecular mechanismsMultidrug treatmentDrug targetsMedical treatmentNovel targetDrug pipelineDrug developmentEfficacyAttrition ratesTreatmentDiscoveryGreater personalizationReductionist modelPatientsSystems medicine: helping us understand the complexity of disease
Vandamme D, Fitzmaurice W, Kholodenko B, Kolch W. Systems medicine: helping us understand the complexity of disease. QJM 2013, 106: 891-895. PMID: 23904523, DOI: 10.1093/qjmed/hct163.Peer-Reviewed Original Research