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Predictive Imaging Biomarkers for GBM Therapeutic Response and Recurrence

Predictive Imaging Biomarkers for GBM Therapeutic Response and Recurrence
GBM 治疗反应和复发的预测成像生物标志物
批准号:
8510988
负责人:
THOMAS L CHENEVERT
金额:
$34.31万
依托单位国家:
美国
项目类别:
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-09-05 至 2018-06-30
关键词:
AccountingAddressAmerican College of Radiology Imaging NetworkAnimalsBiological MarkersBiologyBiopsy SpecimenBrain NeoplasmsCaringClinicalClinical ManagementClinical TrialsClinical Trials DesignComputer softwareDataData SetDetectionDiffusionDiffusion Magnetic Resonance ImagingDiseaseEarly DiagnosisEarly treatmentEnrollmentExcisionFoundationsFundingGenetically Engineered MouseGenomicsGlioblastomaGliomaGoalsHarvestHealthcare SystemsHereditary DiseaseHumanImageIndividualInstitutionInstructionInterobserver VariabilityIonizing radiationKnowledgeLeadMRI ScansMagnetic Resonance ImagingMalignant GliomaMapsMedicineMethodsMetricModelingMolecular GeneticsMultivariate AnalysisMutationNewly DiagnosedOperative Surgical ProceduresOutcomePatientsPatternPerfusionPhasePhase II Clinical TrialsPhase III Clinical TrialsPoly(ADP-ribose) PolymerasesPropertyProtocols documentationRadiationRadiation Therapy Oncology GroupRadiation therapyRecurrenceRecurrent tumorResearchResearch PersonnelScanningSignal TransductionSolutionsSourceStratificationTechnologyTestingThe Cancer Genome AtlasTherapeuticTimeTissuesTranslatingTreatment EfficacyTreatment outcomeTumor BiologyValidationWorkXenograft procedurebasebevacizumabchemotherapyclinical applicationclinical careclinical practicecostdesigndrug efficacyefficacy trialgenome sequencinghemodynamicsimprovedindustry partnerinhibitor/antagonistinsightneurosurgerynoveloutcome forecastpatient populationresponsestandard of caretemozolomidetherapy resistanttranscriptomicstreatment responsetumortumor progression

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英文摘要
Primary GBM, accounting for over 90% of human GBMs, develops rapidly or de novo with no prior clinical disease. Large-scale genomic analyses have contributed greatly to the definition of the overall glioma landscape and datasets (TCGA) have enabled the division of GBMs into subclasses based on their genomic, transcriptomic, and signal transduction patterns. Sadly, despite these insights into the genetics of the disease and advances in neurosurgery, radiation and chemotherapy, its dismal prognosis has not changed significantly. The current paradigm for glioblastoma (GBM) therapy is based on the concept that each patient is treated with the standard of care consisting of temozolomide and ionizing radiation (TMZ/IR) with no upfront knowledge if they will benefit from first-line therapy. Following completion of treatment, a month delay (or more) is needed to assess outcome. Patients found nonresponsive are assigned to a second-line treatment and so on. Care of GBM patients is sub-optimal in the current era wherein the technology for whole genome sequencing is a reality and thus enabling personalized medicine using targeted agents based on genetic alterations of each patient is possible. This Project will establish the accuracy of voxel-based quantitative MRI-derived metrics for detection of early treatment response and tumor recurrence during TMZ/IR treatment and during administration of molecularly targeted therapies. Specific Aim 1 will conduct a multi-center validation of the parametric response map (PRM) as a voxel-based imaging biomarker of early response in standard of care treatment of newly diagnosed glioblastoma. Tumors harvested at the time of initial surgical excision will be genetically profiled by Project 1 for stratification with responsiveness. Specific Aim 2 will evaluate PRM early response imaging metrics in Phase II (MCC-15412/ABTC-0703) and Phase 1 (RTOG-0825/ACR1N-6686) clinical trials of molecularly targeted agents in patients with newly diagnosed malignant glioma. Specific Aim 3 will develop and evaluate a novel PRM approach for automated and objective detection and spatial depiction of early GBM progression prior to detection by currently available conventional MRI-based criteria. Overall, this Project is designed to advance the clinical application and utility of novel MRI-based biomarker metrics as quantitative and predictive surrogates of patient tumor status. These approaches will provide for significant improvements in how imaging can be integrated into clinical trials as well as in improving clinical management and care of GBM patients. Overall, this effort is anticipated to lead to improved outcome for this patient population.
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University of Michigan Quantitative Co-Clinical Imaging Research Resource
University of Michigan Quantitative Co-Clinical Imaging Research Resource
University of Michigan Quantitative Co-Clinical Imaging Research Resource
University of Michigan Quantitative Co-Clinical Imaging Research Resource
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