grant
Unraveling nonsense-mediated mRNA decay mechanisms in cancer
Organization UNIVERSITY OF SOUTHERN CALIFORNIALocation Los Angeles, UNITED STATESPosted 15 May 2026Deadline 30 Apr 2031
NIHUS FederalResearch GrantFY2026AccelerationAddressAffectAntioncogene Protein p53Atlas of Cancer Mortality in the United StatesCancer BiologyCancer MapsCancer PatientCancer TreatmentCancer cell lineCancersCell Cycle ControlCell Cycle RegulationCellular Tumor Antigen P53ComprehensionComputer ModelsComputerized ModelsComputing MethodologiesDNA mutationDataData CollectionDependenceDevelopmentDiseaseDisorderEpistasisEpistatic DeviationGene ExpressionGene variantGenesGeneticGenetic ChangeGenetic EpistasisGenetic defectGenetic mutationGenomicsHealthIndividualInteraction DeviationKnowledgeLinkMalignant Neoplasm TherapyMalignant Neoplasm TreatmentMalignant NeoplasmsMalignant TumorMapsMediatingMessenger RNAMissionModelingMultiomic DataMutationNational Institutes of HealthNormal TissueNormal tissue morphologyOncogenesisOncoprotein p53OutcomeP53Pathway interactionsPhosphoprotein P53Phosphoprotein pp53PositionPositioning AttributePost-Transcriptional ControlPost-Transcriptional RegulationPrediction of Response to TherapyProbabilistic ModelsProbability ModelsProtein TP53Protein TruncationPublic HealthQTLQuality ControlQuantitative Trait LociRegulationResearchResearch ResourcesResidualResidual stateResourcesRoleSamplingStatistical MethodsStatistical ModelsStop CodonTCGATP53TP53 geneTRP53Termination CodonTerminator CodonThe Cancer Genome AtlasTherapeuticTranscriptTranslation Stop SignalTreesTumor CellTumor Protein p53Tumor Protein p53 GeneUnited States National Institutes of HealthVariantVariationallelic variantanti-cancer researchanti-cancer therapyburden of diseaseburden of illnesscancer progressioncancer researchcancer riskcancer therapycancer typecancer-directed therapyclinical relevanceclinically relevantcomputational methodologycomputational methodscomputational modelingcomputational modelscomputer based methodcomputer based modelscomputer methodscomputerized modelingcomputing methoddeep learning based modeldeep learning modeldesigndesigningdevelopmentaldisease burdeneffective therapyeffective treatmentepistatic interactionepistatic relationshipfitnessgene x gene interactiongenetic epistasesgenetic variantgenome mutationgenomic datagenomic datasetgenomic variantindividualized cancer therapyinnovateinnovationinnovativeinsightmRNAmRNA DecaymRNA Surveillancemalignancymultiple omic dataneoplasm progressionneoplasm/cancerneoplastic cellneoplastic progressionnovelp53 Antigenp53 Genesp53 Tumor Suppressorpathwaypatient responsepatient specific responsepersonalized cancer therapypersonalized cancer treatmentpost-transcriptional gene regulationposttranscriptionalpredict therapeutic responsepredict therapy responseprematureprematuritypreventpreventingprotein p53responseresponse to therapyresponse to treatmentresponsive patientsecondary analysissocial rolestatistic methodsstatistical linear mixed modelsstatistical linear modelstherapeutic responsetherapy predictiontherapy responsetranscriptomicstreatment predictiontreatment responsetreatment response predictiontreatment responsivenesstumortumor progressiontumorigenesis
Description preview
PROJECT SUMMARY
Our project delves into the multifaceted role of nonsense-mediated mRNA decay (NMD) in cancer, extending
beyond its conventional function of degrading faulty mRNA transcripts. We hypothesize that understanding
NMD's regulatory functions in cancer, particularly their interaction with the surveillance mechanisms of NMD,
holds…
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