Featured Publications
Control of cell state transitions
Rukhlenko O, Halasz M, Rauch N, Zhernovkov V, Prince T, Wynne K, Maher S, Kashdan E, MacLeod K, Carragher N, Kolch W, Kholodenko B. Control of cell state transitions. Nature 2022, 609: 975-985. PMID: 36104561, PMCID: PMC9644236, DOI: 10.1038/s41586-022-05194-y.Peer-Reviewed Original ResearchConceptsCell state transitionsCell fateCell statesCell fate transitionsCell fate decisionsSingle-cell dataNew biological insightsFate transitionsMovement of cellsFate decisionsWaddington landscapePhenotypic dataBiological insightsOmics datasetsOmics dataCellular modelMechanistic modelLandscape1FateCellsDevelopment pathwaysLandscapeBiologyState transitionsTherapeutic interventionsA 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 dosesGrb2Untangling the wires: A strategy to trace functional interactions in signaling and gene networks
Kholodenko BN, Kiyatkin A, Bruggeman FJ, Sontag E, Westerhoff HV, Hoek JB. Untangling the wires: A strategy to trace functional interactions in signaling and gene networks. Proceedings Of The National Academy Of Sciences Of The United States Of America 2002, 99: 12841-12846. PMID: 12242336, PMCID: PMC130547, DOI: 10.1073/pnas.192442699.Peer-Reviewed Original ResearchConceptsGene networksFunctional interactionMitogen-activated protein kinase cascadeProtein kinase cascadeProteomic data setsKinase cascadeCellular signalingLarge genomicsUnidentified elementsMechanistic levelCellular networkingSignalingCell systemGenomicsInteractionInteraction routesCascadeComputer-generated responsesNetwork responseCurrent methodologiesResponse
2025
cSTAR analysis identifies endothelial cell cycle as a key regulator of flow-dependent artery remodeling
Deng H, Rukhlenko O, Joshi D, Hu X, Junk P, Tuliakova A, Kholodenko B, Schwartz M. cSTAR analysis identifies endothelial cell cycle as a key regulator of flow-dependent artery remodeling. Science Advances 2025, 11: eado9970. PMID: 39752487, PMCID: PMC11698091, DOI: 10.1126/sciadv.ado9970.Peer-Reviewed Original Research
2024
Using Structure-Based Modeling to Identify Effective Drug Combinations in RAS-Mutant Acute Myeloid Leukemia
Jones L, Rukhlenko O, Dias T, Carmody C, Wynne K, Kholodenko B, Bond J. Using Structure-Based Modeling to Identify Effective Drug Combinations in RAS-Mutant Acute Myeloid Leukemia. Blood 2024, 144: 4161-4161. DOI: 10.1182/blood-2024-207308.Peer-Reviewed Original ResearchAcute myeloid leukemiaPatient-derived xenograftsCombination-treated miceInhibitor combinationsPeripheral bloodPhosphorylated ERKBone marrowRAS pathway activationSpleen weightMyeloid leukemiaAML patient-derived xenograftDrug combinationsVehicle controlSingle agentHuman CD45+ cellsPre-clinical mouse modelPediatric acute myeloid leukemiaAssociated with poor outcomesHigh-risk patient groupsMedian spleen weightSB-treated micePreclinical in vivo modelsCD45+ cellsLateral tail veinPathway activationEV017/#1282 GLP-1 analogues reduce the incidence of endometrial cancer in an animal model
Wilkinson M, Mulligan K, Moran B, Rukhlenko O, Kashdan E, Kholodenko B, Fabre A, Mccormack J, Docherty N, Roux C, Brennan D. EV017/#1282 GLP-1 analogues reduce the incidence of endometrial cancer in an animal model. 2024, a92.1-a92. DOI: 10.1136/ijgc-2024-igcs.136.Peer-Reviewed Original ResearchCell-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 sensitivityCell State Transition Models Stratify Breast Cancer Cell Phenotypes and Reveal New Therapeutic Targets
Rukhlenko O, Imoto H, Tambde A, McGillycuddy A, Junk P, Tuliakova A, Kolch W, Kholodenko B. Cell State Transition Models Stratify Breast Cancer Cell Phenotypes and Reveal New Therapeutic Targets. Cancers 2024, 16: 2354. PMID: 39001416, PMCID: PMC11240448, DOI: 10.3390/cancers16132354.Peer-Reviewed Original ResearchControl of cell movementCell linesCell statesLuminal BC cellsControl cell phenotypeWaddington landscapeTissue-derived cell linesCell movementOncogenic transformationSmall molecule inhibitorsSignaling nodeBC cell linesExpression profilesPerturbation datasetsNormal cell stateMolecule inhibitorsBC cellsCell phenotypeBasal BCBC subtypesBreast cancerOncogenic driversCellsCurrent biologicsBreast tissue cells
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
2021
Can Systems Biology Advance Clinical Precision Oncology?
Rocca A, Kholodenko B. Can Systems Biology Advance Clinical Precision Oncology? Cancers 2021, 13: 6312. PMID: 34944932, PMCID: PMC8699328, DOI: 10.3390/cancers13246312.Peer-Reviewed Original ResearchSignal transduction networksSystems biology studiesGenotype-phenotype relationshipsTransduction networksSystems biology modelsSystems biologyBiological processesEnvironmental perturbationsBiology studiesCancer mutationsNetwork reconstructionPrecision oncologyBiology modelsTumor molecular alterationsBiological systemsArray of techniquesMolecular alterationsIndividual cancer patientsOncological researchBiologyValuable toolMutationsTherapeutic treatmentRelationship Between Dimensionality and Convergence of Optimization Algorithms: A Comparison Between Data-Driven Normalization and Scaling Factor-Based Methods Using PEPSSBI
Degasperi A, Nguyen L, Fey D, Kholodenko B. Relationship Between Dimensionality and Convergence of Optimization Algorithms: A Comparison Between Data-Driven Normalization and Scaling Factor-Based Methods Using PEPSSBI. Methods In Molecular Biology 2021, 2385: 91-115. PMID: 34888717, PMCID: PMC9446379, DOI: 10.1007/978-1-0716-1767-0_5.Peer-Reviewed Original ResearchConceptsUnknown parametersOrdinary differential equation modelDifferential equation modelMulti-CPU clusterObjective function constructionModel importParameter estimation softwareParameter identifiabilityOptimization algorithmDNS approachPersonal computerFirst softwareConvergence timeEstimation softwareFunction constructionFactor-based methodsDynamic modelAdditional parametersBiological dataData normalizationAlgorithmSoftwareScaling factorsDNSSimulationsModeling the Nonlinear Dynamics of Intracellular Signaling Networks
Rukhlenko O, Kholodenko B. Modeling the Nonlinear Dynamics of Intracellular Signaling Networks. Bio-protocol 2021, 11: e4089. PMID: 34395728, PMCID: PMC8329461, DOI: 10.21769/bioprotoc.4089.Peer-Reviewed Original ResearchOrdinary differential equationsPartial differential equation systemDifferential equation systemDifferent dynamical regimesBasins of attractionMain qualitative featuresDifferential equationsState trajectoriesEquation systemSystem trajectoriesDynamical regimesNonlinear dynamicsStable steady stateSteady stateBifurcation analysisParameter spaceLimit cyclesMultiple attractorsConstant parametersParametric planePoint dynamicsStandard optimizationIntracellular signaling networksSpatial pointsMultiple steady statesChanneling macrophage polarization by rocaglates increases macrophage resistance to Mycobacterium tuberculosis
Chatterjee S, Yabaji S, Rukhlenko O, Bhattacharya B, Waligurski E, Vallavoju N, Ray S, Kholodenko B, Brown L, Beeler A, Ivanov A, Kobzik L, Porco J, Kramnik I. Channeling macrophage polarization by rocaglates increases macrophage resistance to Mycobacterium tuberculosis. IScience 2021, 24: 102845. PMID: 34381970, PMCID: PMC8333345, DOI: 10.1016/j.isci.2021.102845.Peer-Reviewed Original ResearchMacrophage polarizationAlternative activation programChronic unresolved inflammationType 2 immunityCytokine IFN-gammaM1-like macrophagesM1-like phenotypeChronic bacterial infectionM2-like phenotypeUnresolved inflammationInfectious granulomasIL-4IFN-gammaPhagosome-lysosome fusionIntracellular mycobacteriaReparative microenvironmentHost immunityMacrophage phenotypeSolid tumorsTumor growthBacterial infectionsCertain tumorsTumor progressionType 1Primary macrophagesReengineering protein-phosphorylation switches
Kholodenko B, Okada M. Reengineering protein-phosphorylation switches. Science 2021, 373: 25-26. PMID: 34210865, PMCID: PMC8327301, DOI: 10.1126/science.abj5028.Peer-Reviewed Original Research
2020
Inhaled multi-walled carbon nanotubes differently modulate global gene and protein expression in rat lungs
Seidel C, Zhernovkov V, Cassidy H, Kholodenko B, Matallanas D, Cosnier F, Gaté L. Inhaled multi-walled carbon nanotubes differently modulate global gene and protein expression in rat lungs. Nanotoxicology 2020, 15: 238-256. PMID: 33332178, DOI: 10.1080/17435390.2020.1851418.Peer-Reviewed Original ResearchConceptsNM-401Bronchoalveolar lavage fluidLong-term health effectsWeeks of inhalationDose-dependent increasePost-exposure timeLung inflammationLavage fluidWhole lungRat lungInhalationHealth effectsProtein expressionRecovery periodMechanisms of toxicityMWCNT exposureDifferent toxicological profilesLungToxicological profileDaysToxicological effectsPersistent effectsToxicityAnimalsToxicogenomic approachSystems 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