Circulating Genomic Determinants of Treatment Failure in Hodgkin Lymphoma
Project Number5R01CA257655-05
Contact PI/Project LeaderALIZADEH, ASH ARASH Other PIs
Awardee OrganizationSTANFORD UNIVERSITY
Description
Abstract Text
PROJECT SUMMARY/ABSTRACT
PIs: Ash Alizadeh, M.D./Ph.D. & Maximilian Diehn, M.D./Ph.D.
Classical Hodgkin lymphoma (HL) is among the most curable human malignancies. However,
strategies to personalize HL therapies and to minimize long-term attendant toxicities of
chemotherapy are currently limited to baseline risk factors and imaging. This is due to our
incomplete understanding of targetable pathways and lack of good biomarkers. Because of the
low fraction of malignant cells in tumor tissue and consecutive technical challenges, the
landscape of HL is not well-defined.
Our long-term goal is to study the ability of baseline and dynamic risk factors, including genetic
mutations, circulating tumor DNA (ctDNA) and imaging studies (PET), to accurately predict
treatment outcomes in HL patients, and to provide a basis for individualized precision medicine.
Our central hypothesis is that clinical and biological heterogeneity in HL reflects distinct
genomic features that are noninvasively measurable using ultrasensitive ctDNA techniques, and
that refining early response assessment integrating interim PET and blood based methods
improves prognostication. We will test our hypotheses via three specific aims: (1) To
noninvasively define the genomic landscape of somatic variations in HL, and to determine the
relationship of genomic variants with biological heterogeneity at initial disease presentation, (2)
To associate molecular features at baseline and molecular response with ultimate therapeutic
outcome, and to integrate clinical and molecular biomarkers in a personalized dynamic risk
model for predicting HL outcomes, and (3) To functionally characterize novel mutations in
Interleukin-4 receptor (IL4R) resulting in gain-of-function IL4/STAT6 signaling, and to test the
utility of precision therapeutic targeting of these mutations.
If successful, our project will lead to novel ways to select better therapies for patients at highest
risk of failure, and to minimize toxicity for the majority of patients responding well to standard
therapy. Our innovative approach, in which we will combine blood-based methods for
genotyping and disease monitoring with imaging studies, will provide the basis for a
personalized treatment approach in HL.
Public Health Relevance Statement
PROJECT NARRATIVE
PIs: Ash Alizadeh, M.D./Ph.D. & Maximilian Diehn, M.D./Ph.D.
In this study, we will use liquid biopsy to identify genetic subtypes in classical Hodgkin
lymphoma. We will combine serial liquid biopsy measurements and imaging methods to refine
prediction of how patients with classical Hodgkin lymphoma will respond to treatment. This work
is relevant to public health because precision medicine has the potential to improve clinical
outcomes of cancer patients and reduce sequelae.
NIH Spending Category
No NIH Spending Category available.
Project Terms
Antibody-drug conjugatesBiological AssayBiological MarkersBiotechnologyBloodCancer PatientCellsClinicalCytotoxic ChemotherapyDNA Sequence AlterationDependenceDevelopmentDiagnosisDiseaseDisease remissionDoctor of MedicineDoctor of PhilosophyEventFailureFrequenciesGeneticGenomicsGenotypeGoalsHeterogeneityHodgkin DiseaseHumanHuman Herpesvirus 4IL4 geneImageIndividualInterleukin 4 ReceptorMalignant NeoplasmsMeasurableMeasurementMeasuresMetabolicMethodsModelingMolecularMonitorMutationNatureOutcomePathologicPathway interactionsPatientsPhenotypePlasmaPositron-Emission TomographyPrecision therapeuticsPrediction of Response to TherapyPropertyPublic HealthRecurrenceRegimenRiskRisk FactorsSTAT6 geneSignal TransductionSomatic MutationStereotypingTechniquesTestingTherapeuticTherapeutically TargetableToxic effectToxicity due to chemotherapyTreatment EfficacyTreatment FailureTreatment outcomeTumor TissueTumor VolumeVariantViral GenomeWorkbiological heterogeneitycancer cellcancer imagingclinical biomarkersclinical heterogeneitycohortcytokinedisorder riskexomeexperimental studygain of functiongenetic varianthigh riskimaging modalityimaging studyimmune checkpoint blockadeimprovedindexinginduced pluripotent stem cellinnovationinsightintegration siteliquid biopsymolecular markerneoplastic cellnovelnovel therapeutic interventionoutcome predictionpersonalized medicinepersonalized risk predictionpre-clinicalprecision medicineprognosticationresponseresponse biomarkerrisk predictionrisk prediction modeltargeted treatmenttherapeutic targettherapy outcometumortumor DNA
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