grant

Liquid biopsy approaches to inform neuroblastoma prognosis and disease monitoring

Organization UNIVERSITY OF CHICAGOLocation CHICAGO, UNITED STATESPosted 11 Apr 2022Deadline 31 Mar 2027
NIHUS FederalResearch GrantFY20260-11 years oldAutomobile DrivingBiologicalBiological MarkersBiologyBiopsyBlood SampleBlood specimenCRISPRCRISPR/Cas systemCancersChildChild YouthChildren (0-21)Children's Oncology GroupClinicalClinical EvaluationClinical TestingClinical TrialsClinical assessmentsClustered Regularly Interspaced Short Palindromic RepeatsComplexCopy Number PolymorphismCytosineDNADNA MarkersDNA biomarkersDNA mutationDataDeoxyribonucleic AcidDepositDepositionDetectable Residual DiseaseDetection of Minimal Residual DiseaseDiagnosisDiagnosticDiseaseDisease ResistanceDisorderDisparateEarly DiagnosisEarly InterventionEarly treatmentElasticityEnrollmentEpigeneticEpigenetic ChangeEpigenetic MechanismEpigenetic ProcessExtracellular Signal-Regulated Kinase GeneGene TranscriptionGeneralized GrowthGenesGenetic ChangeGenetic TranscriptionGenetic defectGenetic mutationGoalsGrowthIn VitroInduction TherapyKnock-outKnockoutLong-Term SurvivorsMAP Kinase GeneMAPKMalignant CellMalignant NeoplasmsMalignant TumorMethodologyMethodsMethylationMinimal Residual DiseaseMitogen-Activated Protein Kinase GeneModificationMonitorMutationNEOADJNeoadjuvantNeoadjuvant TherapyNeoadjuvant TreatmentNeuroblastomaNewly DiagnosedNorth AmericaPatient outcomePatient-Centered OutcomesPatient-Focused OutcomesPatientsPediatric Oncology GroupPhase III studyPrimary NeoplasmPrimary TumorPrognosisRNA ExpressionRecurrenceRecurrentRecurrent diseaseRefractory DiseaseRelapseRelapsed DiseaseResidual NeoplasmResidual TumorsRetrospective cohortRiskSamplingSpecificityTherapeuticTherapeutic InterventionTissue GrowthTrainingTranscriptionTumor Suppressor ProteinsValidationWorkbio-markersbiologicbiologic markerbiomarkerbiomarker validationburden of diseaseburden of illnesscancer cellcancer typecandidate identificationcell free DNAcell free circulating DNAchemotherapyclinical testcopy number variantcopy number variationdiagnostic biomarkerdiagnostic markerdisease burdendrivingearly detectionearly therapyenrollentire genomeepigeneticallyfull genomegene networkgenome mutationhigh riskhigh risk grouphigh risk individualhigh risk peoplehigh risk populationimprovedimproved outcomeinduction therapiesintervention therapyinventionkidsliquid biopsymachine learning based methodmachine learning methodmachine learning methodologiesmalignancymarker validationnanoneoplasm/cancernew drug treatmentsnew drugsnew pharmacological therapeuticnew therapeuticsnew therapynext generation therapeuticsnovelnovel drug treatmentsnovel drugsnovel pharmaco-therapeuticnovel pharmacological therapeuticnovel therapeuticsnovel therapyontogenyparticipant enrollmentpatient enrollmentpatient oriented outcomespatient profileperipheral bloodphase 3 studypredictive biological markerpredictive biomarkerspredictive markerpredictive molecular biomarkerprofiles in patientsprognosticprognostic assaysprognostic testprognosticationprospectiverelapse predictionrelapse riskresearch clinical testingresidual diseaseresistance to diseaseresistance to therapyresistant diseaseresistant to diseaseresistant to therapyresponseresponse biomarkerresponse markersresponse to therapyresponse to treatmentrisk stratificationscreeningscreeningssealstratify risksuccesstherapeutic resistancetherapeutic responsetherapy resistanttherapy responsetreatment resistancetreatment responsetreatment responsivenesstumortumor DNAtumor cell DNAtumor suppressortumor-specific DNAvalidationswhole genomeyoungster
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Full Description

Abstract
Fewer than half of all children with high-risk neuroblastoma become long-term survivors. Currently, it is not

possible to predict if a child will be cured with standard therapy or is destined to relapse. Furthermore, standard

clinical evaluations lack sensitivity to detect minimal residual disease (MRD) that ultimately leads to recurrence.

Thus, there is a critical challenge and an unmet need to develop new precision biomarkers to identify patients

who will ultimately have a poor response to the high-intensity therapy and may benefit from alternate approaches.

We will develop new biomarkers to guide treatment decisions using cell-free DNA (cfDNA) and a novel,

epigenetic-based methodology that will identify underlying biology driving aggressive neuroblastoma. In many

cancer types, analysis of cfDNA isolated from peripheral blood has shown promise, revealing biomarkers for

diagnosis, prognostication, and tumor surveillance. Cytosines in DNA can either be unmodified, methylated (5-

methylcytosine, 5mC), or contain an oxidized form of 5mC, 5-hydroxymethylcytosine (5hmC). Unlike 5mC,

elevated 5hmC deposition across a gene body marks active transcription. In this proposal, we will use nano-

hmC-seal, a whole-genome methodology for analyzing 5hmC modifications in cfDNA. Recently, we evaluated

5hmC in cfDNA collected serially from children with neuroblastoma and demonstrated that 5hmC profiles

correlated with disease burden and patient outcome. Importantly, we also found a cfDNA 5hmC derived

biomarker can distinguish patients with superior response to treatment from those at high risk for relapse. 5hmC

profiles from cfDNA compared to diagnostic high-risk primary tumors demonstrated cfDNA is derived from

clinically aggressive, malignant cells with activation of networks common in relapsed tumors. To prospectively

determine the prognostic strength of 5hmC-based cfDNA biomarkers, we will use nano-hmC-seal to generate

5hmC profiles from clinically annotated serial blood samples (liquid biopsies) collected from 400 patients enrolled

on the ongoing Children’s Oncology Group High-Risk Neuroblastoma Phase III study (ANBL1531,

NCT03126916). We hypothesize that cfDNA 5hmC profiles from children with neuroblastoma will serve as

superior biomarkers for response and survival compared to current clinical methods and will reveal transcriptional

networks driving relapse. The specific aims are: 1) Evolve and validate biomarkers of poor response at diagnosis;

2) Prospectively identify minimal residual disease (MRD) and predict relapse from serial cfDNA 5hmC profiles;

3) Experimentally confirm candidate networks enriched in cfDNA at relapse. The success of this proposal will

lead to: 1) unprecedented diagnostic biomarkers to improve therapeutic decisions; 2) early detection and

interventions for patients with relapse causing MRD; 3) identification of epigenetic mechanisms which drive

relapse. This work will have a transformative impact by to identifying patients who benefit from early introduction

of alternate therapy, improving outcomes for those with aggressive disease.

Grant Number: 5R37CA262781-05
NIH Institute/Center: NIH

Principal Investigator: Mark Applebaum

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