Quantitative characterization of tumor heterogeneity using habitat imaging for the prediction of patient outcome in triple negative breast cancer
Project Number1K99CA293004-01
Contact PI/Project LeaderKAZEROUNI, ANUM SYED
Awardee OrganizationUNIVERSITY OF WASHINGTON
Description
Abstract Text
PROJECT SUMMARY
The overall goal of this training proposal is to employ quantitative imaging to noninvasively characterize tumor
microenvironmental heterogeneity in triple negative breast cancer (TNBC) for the prediction of treatment
response and outcome. TNBC is an aggressive breast cancer subtype with notable diversity in disease biology
and clinical presentation. Recently-approved immunotherapies introduce exciting new avenues for neoadjuvant
treatment of TNBC; however, response to immunotherapy is variable and treatment can entail significant adverse
effects and financial cost. Variable response to therapy can be attributed in-part to heterogeneity of the tumor
microenvironment, affecting therapeutic delivery and efficacy. Through an innovative approach known as “habitat
imaging”, multiparametric magnetic resonance imaging (mpMRI) can be used to spatially resolve local
microenvironments within a lesion into distinct tumor subregions, or habitats. For the research component of this
proposal, we propose to use quantitative breast imaging and informatics techniques to identify tumor habitats
and whole-lesion habitat signatures for TNBC patient stratification. We hypothesize that imaging-derived habitat
signatures identified prior to treatment can aid in stratifying TNBC patients with increased probability of achieving
pCR and/or decreased risk of recurrence. We will test this hypothesis through the following specific aims: Aim 1
(K99) To retrospectively identify tumor habitat signatures from pretreatment mpMRI to stratify TNBC patients
and predict treatment outcome; Aim 2 (R00) To prospectively employ habitat imaging using hybrid positron
emission tomography (PET)/MRI for improved TNBC patient stratification. Successful completion of my research
aims will provide a clinically-translatable methodology for improved understanding of an individual’s lesion
physiology that could guide personalized treatment strategies for optimal patient outcome. To provide me with
the necessary training to successfully carry out these research aims, this proposal outlines a mentored-training
plan with three areas of focus: 1) strengthen my expertise in clinical breast cancer research, 2) receive additional
training in computational pathology, and 3) obtain educational training and hands-on experience with PET/MRI
to prepare for research in the independent R00 phase and beyond. This training program will be executed under
the direct mentorship of NIH-funded researchers and clinicians specializing in medical oncology, nuclear
medicine, pathology and radiology, and take place within the well-equipped and established cancer research
environment at the University of Washington and Fred Hutch Cancer Center. As outlined in my career
development plan, funding from this proposal will be used to dedicate time for educational workshops and training
seminars, along with regular meetings with my mentorship team. Together, this training and research proposal
will ensure that I am well-prepared to achieve my career goal to become an independent investigator focused
on the translation of innovative imaging techniques to clinical practice to further personalize breast cancer care.
Public Health Relevance Statement
PROJECT NARRATIVE
Despite recognized intertumoral diversity, current treatment strategies for triple negative breast
cancer remain generalized due to lack of reliable biomarkers. This proposal seeks to quantitatively
characterize TNBC heterogeneity using novel habitat signatures and elucidate interpatient
differences to aid in stratifying patients with increased probability of response to neoadjuvant
therapy. Successful whole-tumor habitat characterizations will yield greater understanding of an
individual’s tumor physiology and provide an avenue to further personalize breast cancer care.
NIH Spending Category
No NIH Spending Category available.
Project Terms
Adverse effectsAffectAreaAwardBiologicalBiological MarkersBiologyBiopsyBiopsy SpecimenBlood VesselsBreast Cancer ModelBreast Cancer PatientBreast Cancer TreatmentBreast Magnetic Resonance ImagingCancer CenterCellsCellularityClinicalComputer AnalysisDataDedicationsDevelopment PlansDiagnosticDiscipline of Nuclear MedicineDiseaseDisease-Free SurvivalDrug Delivery SystemsEducational workshopEmerging TechnologiesEnsureEnvironmentFinancial costFunctional ImagingFundingGenotypeGlucoseGoalsHabitatsHeterogeneityHistopathologyHybridsImageImaging TechniquesImmunohistochemistryImmunotherapyIn complete remissionIndividualInformaticsInstitutionLesionMagnetic Resonance ImagingMalignant Breast NeoplasmMeasurementMeasuresMedical OncologyMentorsMentorshipMetabolicMetabolismMethodologyMethodsMolecular TargetNeoadjuvant TherapyOperative Surgical ProceduresOxygenPathologicPathologyPatient-Focused OutcomesPatientsPhasePhenotypePhysiologicalPhysiologyPositron-Emission TomographyPrediction of Response to TherapyProbabilityRadiology SpecialtyRecurrenceResearchResearch PersonnelResearch ProposalsRiskSelection for TreatmentsStratificationTechniquesTestingTherapeuticTimeTissuesTrainingTraining ProgramsTraining and EducationTranslatingTranslationsTreatment ProtocolsTreatment outcomeTumor BurdenTumor VolumeTumor-Infiltrating LymphocytesUnited States National Institutes of HealthUniversitiesWashingtonadvanced diseaseaggressive breast canceranatomic imaginganti-cancer researchbreast imagingcancer carecancer heterogeneitycancer imagingcancer subtypescareercareer developmentchemotherapyclinical practiceclinical translationdrug efficacyexperiencefinancial toxicityfluorodeoxyglucose positron emission tomographyglucose uptakeimprovedin vivoinnovationmeetingsmolecular imagingmouse modelnovelpatient populationpatient stratificationpersonalized medicineprospectivequantitative imagingresponsetreatment responsetreatment strategytriple-negative invasive breast carcinomatumortumor heterogeneitytumor microenvironmenttumor-immune system interactions
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