Radioimmunogenomic Habitat Phenotypes to Predict Efficacy of Neoadjuvant Immunotherapies in Non-Small Cell Lung Cancer
Radioimmunogenomic Habitat Phenotypes to Predict Efficacy of Neoadjuvant Immunotherapies in Non-Small Cell Lung Cancer
批准号:
10685447
负责人:
Tina Cascone
金额:
$65.82万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-16 至 2026-08-31
关键词:
AddressAdjuvantAdjuvant StudyAdjuvant TherapyAlgorithmsBiologicalBiological MarkersCancer EtiologyCharacteristicsClinicalClinical TrialsClinical effectivenessControl GroupsCurative SurgeryDataData ScienceData SetDevelopmentDiseaseDisease ProgressionEvaluationEvolutionGoalsHabitatsImageImmuneImmune checkpoint inhibitorImmuno-ChemotherapyImmunocompetentImmunogenomicsImmunologic MemoryImmunologicsImmunotherapyKnowledgeLeadLungLymph Node InvolvementMalignant NeoplasmsMalignant neoplasm of lungMapsMeta-AnalysisMetastatic Neoplasm to the LungMicrometastasisModelingMusNeoadjuvant StudyNeoadjuvant TherapyNeoplasm MetastasisNodalNon-Small-Cell Lung CarcinomaOperative Surgical ProceduresOutcomePET/CT scanPathologicPatient CarePatientsPerformancePhasePhenotypePhysiologicalPositioning AttributePositron-Emission TomographyPostoperative PeriodPre-Clinical ModelPrimary NeoplasmRadioRadiogenomicsRandomizedRecurrent tumorReportingResectableRiskRoleSpatial DistributionStructure of parenchyma of lungSurrogate EndpointTestingThoracic OncologyTissuesToxic effectTrainingTranslatingTreatment EfficacyTumor TissueTumor-infiltrating immune cellsUnited StatesUnresectableX-Ray Computed Tomographybiomarker validationcancer immunobiologyclinical efficacyclinical investigationclinical practiceclinical predictorsclinically relevantcohortcomparative efficacycomputational pipelinescomputerized toolsdesigndisorder riskefficacy evaluationfluorodeoxyglucose positron emission tomographyimaging biomarkerimmunotherapy trialsimproved outcomelymph nodesmolecular markermortalitymouse modelmultiple omicsnovelnovel therapeuticspatient stratificationperipheral bloodpersonalized managementphase 2 studypre-clinicalpredictive modelingpreventquantitative imagingradiological imagingradiomicsrandomized trialresearch clinical testingresponseserial imagingstandard of caresurvival outcometreatment responsetreatment stratificationtumortumor heterogeneitytumor microenvironmenttumor-immune system interactions
中文摘要
摘要
英文摘要
ABSTRACT
Lung cancer is the leading cause of cancer-related mortality in the United States and worldwide. The efficacy of
immune checkpoint inhibitors (ICIs) in patients with metastatic non-small lung cancer (NSCLC) prompted the
clinical investigation of these agents in the early-stage operable setting. Several theoretical advantages exist
when we administer ICIs before surgery (neoadjuvant) rather than postoperatively (adjuvant), including an
opportunity to address micrometastases early in the course of treatment, and may impart immunologic memory
to prevent tumor recurrence. Indeed, the results from our preclinical models of resectable NSCLC demonstrated
that combined neoadjuvant ICIs resulted in fewer lung metastases, greater immune infiltration of tumors, and
longer overall survival compared with mice treated with monotherapy or adjuvant combined ICIs. Those results
informed the first reported randomized phase 2 study testing neoadjuvant ICI combinations in patients with
resectable NSCLC using major pathologic response (MPR, ≤10% viable tumor) as a surrogate endpoint for
clinical efficacy (NEOSTAR, PI: Cascone). Neoadjuvant chemoimmunotherapy has been shown to be highly
promising for resectable NSCLC, and is now being tested in one of the phase 3 randomized studies in patients
with operable NSCLC (CheckMate-77T, Lead PI: Cascone). However, a major shortcoming of all of the
neoadjuvant trials, is that no validated biomarker exists that can be used to stratify patients. Consequently, many
of these patients on these trials do not achieve an MPR at surgery, indicating that limited benefit may be gained
from induction ICIs. By delaying surgery in patients who may not benefit, the risks of disease progression and of
eliminating a chance to offer potentially curative surgery upfront occur. The ongoing evaluation of molecular
biomarkers of clinical benefit to ICIs has proved disappointing as evidenced by the significant intertrial variability,
possibly related to intratumor heterogeneity. By contrast, radiologic imaging provides a holistic view of tumor
characteristics and interactions with the adjacent tissue. Built on our promising preliminary data, we propose to
spearhead radiographic and radiogenomics strategies to address this unmet clinical need. We hypothesize that
imaging phenotypes reflect tumor microenvironment, and quantitative imaging phenotyping will shed light on our
understanding of the mechanisms of response to ICIs and yield surrogates of clinical efficacy. We will leverage
the parallel assessment of well-curated data from unique clinical trials and immunocompetent mouse models to
develop new imaging biomarkers and validate their clinical and biological relevance. The strength of this proposal
is our interdisciplinary team with the requisite expertise and ability to treat patients, obtain and analyze high-
quality, longitudinal imaging and biospecimens and rapidly evaluate putative imaging biomarkers for therapeutic
response and clinical outcomes. The advent of imaging biomarkers will: 1) identify those patients most likely to
benefit from neoadjuvant ICIs, 2) maximize the clinical effectiveness, and 3) lead to the development of new
therapies that will improve outcomes for a greater number of patients with resectable NSCLC.
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Radioimmunogenomic Habitat Phenotypes to Predict Efficacy of Neoadjuvant Immunotherapies in Non-Small Cell Lung Cancer
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批准号:10278410
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项目类别:
-
资助金额:$62.45万
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财政年份:2021
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负责人:Tina Cascone
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依托单位:
海外基金