2023
Immune dysfunction revealed by digital spatial profiling of immuno-oncology markers in progressive stages of renal cell carcinoma and in brain metastases
Schoenfeld D, Moutafi M, Martinez S, Djureinovic D, Merkin R, Adeniran A, Braun D, Signoretti S, Choueiri T, Parisi F, Hurwitz M, Rimm D, Wei W, Jilaveanu L, Kluger H. Immune dysfunction revealed by digital spatial profiling of immuno-oncology markers in progressive stages of renal cell carcinoma and in brain metastases. Journal For ImmunoTherapy Of Cancer 2023, 11: e007240. PMID: 37586773, PMCID: PMC10432651, DOI: 10.1136/jitc-2023-007240.Peer-Reviewed Original ResearchConceptsRenal cell carcinomaBrain metastasesPrimary tumorTumor microenvironmentDigital spatial profilingCell carcinomaActivation protein expressionInflammatory macrophage markersRCC brain metastasesInnate immune activatorsNormal kidney samplesProgressive stagesExtracranial metastasesTim-3Immune checkpointsImmune dysfunctionImmune activationRCC metastasisLonger survivalImmune activatorsMacrophage markersTreatment responseSeparate cohortTissue microarrayMetastatic samplesSubsets of IFN Signaling Predict Response to Immune Checkpoint Blockade in Patients with Melanoma.
Horowitch B, Lee D, Ding M, Martinez-Morilla S, Aung T, Ouerghi F, Wang X, Wei W, Damsky W, Sznol M, Kluger H, Rimm D, Ishizuka J. Subsets of IFN Signaling Predict Response to Immune Checkpoint Blockade in Patients with Melanoma. Clinical Cancer Research 2023, 29: 2908-2918. PMID: 37233452, PMCID: PMC10524955, DOI: 10.1158/1078-0432.ccr-23-0215.Peer-Reviewed Original ResearchConceptsImmune checkpoint inhibitorsHuman melanoma cell linesMelanoma cell linesPD-L1Validation cohortYale-New Haven HospitalCombination of ipilimumabPD-L1 markersImmune checkpoint blockadePD-L1 biomarkerNew Haven HospitalSTAT1 levelsCell linesWestern blot analysisCheckpoint inhibitorsCheckpoint blockadeClinical responseOverall survivalImproved survivalResistance of cancersMetastatic melanomaMelanoma responsePredict responseTreatment responseDistinct patterns
2021
Deep learning trained on hematoxylin and eosin tumor region of Interest predicts HER2 status and trastuzumab treatment response in HER2+ breast cancer
Farahmand S, Fernandez AI, Ahmed FS, Rimm DL, Chuang JH, Reisenbichler E, Zarringhalam K. Deep learning trained on hematoxylin and eosin tumor region of Interest predicts HER2 status and trastuzumab treatment response in HER2+ breast cancer. Modern Pathology 2021, 35: 44-51. PMID: 34493825, PMCID: PMC10221954, DOI: 10.1038/s41379-021-00911-w.Peer-Reviewed Original ResearchConceptsHER2 statusBreast cancerTreatment responseHER2-positive breast cancerAnti-HER2 agentsPre-treatment samplesNeoadjuvant chemotherapyTrastuzumab therapyClinical outcomesClinical evaluationProtein immunohistochemistryHER2 amplificationTrastuzumab responseTumor stainTreatment selectionTCGA testPathology teamTumor regionCancer featuresCancerPatientsHER2Current standardImmunohistochemistryHematoxylin
2017
Quantitative spatial profiling of PD-1/PD-L1 interaction and HLA-DR/IDO1 to predict outcomes to anti-PD-1 in metastatic melanoma (MM).
Johnson D, Bordeaux J, Kim J, Vaupel C, Rimm D, Ho T, Joseph R, Daud A, Conry R, Gaughan E, Dimou A, Balko J, Smithy J, Witte J, McKee S, Dominiak N, Dabbas B, Hall J, Dakappagari N. Quantitative spatial profiling of PD-1/PD-L1 interaction and HLA-DR/IDO1 to predict outcomes to anti-PD-1 in metastatic melanoma (MM). Journal Of Clinical Oncology 2017, 35: 9517-9517. DOI: 10.1200/jco.2017.35.15_suppl.9517.Peer-Reviewed Original ResearchHLA-DRValidation cohortMetastatic melanomaPD-1/PD-L1Anti-PD-1 therapyPD-1/L1Pre-treatment tumor biopsiesPD-1/PD-L1 interactionPD-1 monotherapyPD-L1 expressionProgression-free survivalBiomarkers of responseFuture clinical trialsMultiple immune markersPD-L1 interactionImmune suppression mechanismsPrior therapyFree survivalDurable responsesOverall survivalPD-L1Immune markersClinical trialsTreatment responseTumor biopsies
2016
Copy Number Changes Are Associated with Response to Treatment with Carboplatin, Paclitaxel, and Sorafenib in Melanoma
Wilson MA, Zhao F, Khare S, Roszik J, Woodman SE, D'Andrea K, Wubbenhorst B, Rimm DL, Kirkwood JM, Kluger HM, Schuchter LM, Lee SJ, Flaherty KT, Nathanson KL. Copy Number Changes Are Associated with Response to Treatment with Carboplatin, Paclitaxel, and Sorafenib in Melanoma. Clinical Cancer Research 2016, 22: 374-382. PMID: 26307133, PMCID: PMC4821426, DOI: 10.1158/1078-0432.ccr-15-1162.Peer-Reviewed Original ResearchMeSH KeywordsAntineoplastic Combined Chemotherapy ProtocolsCarboplatinDisease-Free SurvivalDNA Copy Number VariationsDNA Mutational AnalysisDouble-Blind MethodGenes, rasHumansMelanomaMutationNeoplasm StagingNiacinamidePaclitaxelPhenylurea CompoundsProto-Oncogene Proteins B-rafProto-Oncogene Proteins c-metSorafenibTreatment OutcomeConceptsProgression-free survivalGene copy gainOverall survivalImproved progression-free survivalCopy gainImproved overall survivalGenomic alterationsCancer Genome Atlas (TCGA) datasetImproved treatment responseClinical outcomesMET amplificationV600KCCND1 amplificationTreatment responseMelanoma pathogenesisV600E mutationCurrent FDAPretreatment samplesBRAF geneTumor samplesPatientsSorafenibTherapyTumorsAtlas dataset