2024
High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC)
Moutafi M, Bates K, Aung T, Milian R, Xirou V, Vathiotis I, Gavrielatou N, Angelakis A, Schalper K, Salichos L, Rimm D. High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC). Journal For ImmunoTherapy Of Cancer 2024, 12: e009039. PMID: 38857914, PMCID: PMC11168162, DOI: 10.1136/jitc-2024-009039.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerImmune checkpoint inhibitorsProgrammed cell death protein 1Associated with OSCell lung cancerTissue microarray spotsTissue microarrayValidation cohortLung cancerNon-small cell lung cancer treated with immune checkpoint inhibitorsAssociated with resistance to immunotherapyCell death protein 1Resistance to immunotherapyAssociated with PFSProgression-free survivalSecreted frizzled-related protein 2Cox proportional-hazards model analysisCheckpoint inhibitorsImmunotherapy strategiesTumor compartmentsRetrospective cohortDiscovery cohortLong-term benefitsPatientsCD68Spatially Informed Gene Signatures for Response to Immunotherapy in Melanoma.
Aung T, Warrell J, Martinez-Morilla S, Gavrielatou N, Vathiotis I, Yaghoobi V, Kluger H, Gerstein M, Rimm D. Spatially Informed Gene Signatures for Response to Immunotherapy in Melanoma. Clinical Cancer Research 2024, 30: 3520-3532. PMID: 38837895, PMCID: PMC11326985, DOI: 10.1158/1078-0432.ccr-23-3932.Peer-Reviewed Original ResearchGene signatureResistance to immunotherapyResponse to immunotherapyPrediction of treatment outcomeResistant to treatmentAccurate prediction of treatment outcomePredictive of responseImmunotherapy outcomesMelanoma patientsMelanoma specimensValidation cohortPatient stratificationDiscovery cohortTreatment outcomesImmunotherapyMelanomaTumorPatientsCohortS100BOutcomesGene expression dataGenesCD68+macrophagesExpression dataCorrelation of eTILs with recurrence free survival (RFS) in stage IIB-IIIA melanoma and use as biomarker for stratification for clinical trials.
Aung T, Zhang C, Espinoza G, Leung L, Moon J, Horst B, Ferringer T, Nastiuk K, Rimm D, Saenger Y. Correlation of eTILs with recurrence free survival (RFS) in stage IIB-IIIA melanoma and use as biomarker for stratification for clinical trials. Journal Of Clinical Oncology 2024, 42: 9567-9567. DOI: 10.1200/jco.2024.42.16_suppl.9567.Peer-Reviewed Original ResearchTumor-infiltrating lymphocytesRecurrence free survivalAmerican Joint Committee on CancerFree survivalInfiltrating lymphocytesRetrospective cohortClinical trialsQuantify tumor-infiltrating lymphocytesStage II-III melanomaTumor-infiltrating lymphocytes groupDiagnostic slidesIIb-IIIaRoswell Park Comprehensive Cancer CenterEarly-stage melanoma patientsCox modelStage IIB-IIICAdjuvant clinical trialsKaplan-Meier curvesMultivariate Cox modelUnivariate Cox modelCox proportional hazards modelsClinical pathological featuresGeisinger Medical CenterProportional hazards modelClinical trial designHigh-Plex Assessment of Biomarkers in Tumors
Aung T, Bates K, Rimm D. High-Plex Assessment of Biomarkers in Tumors. Modern Pathology 2024, 37: 100425. PMID: 38219953, DOI: 10.1016/j.modpat.2024.100425.Peer-Reviewed Original Research
2023
B-cell infiltration is associated with survival outcomes following programmed cell death protein 1 inhibition in head and neck squamous cell carcinoma
Gavrielatou N, Fortis E, Spathis A, Anastasiou M, Economopoulou P, Foukas G, Lelegiannis I, Rusakiewicz S, Vathiotis I, Aung T, Tissot S, Kastrinou A, Kotsantis I, Vagia E, Panayiotides I, Rimm D, Coukos G, Homicsko K, Foukas P, Psyrri A. B-cell infiltration is associated with survival outcomes following programmed cell death protein 1 inhibition in head and neck squamous cell carcinoma. Annals Of Oncology 2023, 35: 340-350. PMID: 38159908, DOI: 10.1016/j.annonc.2023.12.011.Peer-Reviewed Original ResearchProlonged progression-free survivalTertiary lymphoid structuresPD-L1 expressionB cellsM HNSCCCell death protein 1 inhibitionPD-1-based immunotherapyNeck squamous cell cancerNeck squamous cell carcinomaHigher B cell countsIncreased B cellsB cell infiltrationB-cell countsPD-L1 positivityProgression-free survivalTreatment of recurrentSquamous cell cancerBlood immune cell compositionSquamous cell carcinomaBiomarkers of responseImmune cell compositionB-cell-associated genesProtein 1 inhibitionCell death proteinMetastatic headNew Therapies in Melanoma: Current Trends, Evolving Paradigms, and Future Perspectives.
Shafi S, Challa B, Parwani A, Aung T. New Therapies in Melanoma: Current Trends, Evolving Paradigms, and Future Perspectives. Cutis 2023, 112: e32-e39. PMID: 38091429, DOI: 10.12788/cutis.0911.Peer-Reviewed Original ResearchConceptsImmune checkpoint inhibitorsLymphocyte-activating gene-3Early phase clinical trialsPrimary treatment failureAggressive skin cancerNew therapeutic agentsICI therapyCheckpoint inhibitorsNovel immunotherapiesMelanoma patientsTreatment failureMetastatic melanomaPredictive biomarkersLong-term benefitsClinical trialsClinical careNew therapiesTherapeutic strategiesAlternative treatmentSkin cancerTherapy outcomeTherapeutic agentsNovel targetNovel therapeuticsPatientsAutomated scoring of tumor-infiltrating lymphocytes informs risk of death from thin melanoma: A nested case-case study
Tan S, Aung T, Claeson M, Acs B, Zhou C, Brown S, Lambie D, Baade P, Pandeya N, Soyer H, Smithers B, Whiteman D, Rimm D, Khosrotehrani K. Automated scoring of tumor-infiltrating lymphocytes informs risk of death from thin melanoma: A nested case-case study. Journal Of The American Academy Of Dermatology 2023, 90: 179-182. PMID: 37730017, DOI: 10.1016/j.jaad.2023.09.026.Peer-Reviewed Original ResearchPhase II window study of olaparib alone or with cisplatin or durvalumab in operable Head and Neck Cancer
Moutafi M, Koliou G, Papaxoinis G, Economopoulou P, Kotsantis I, Gkotzamanidou M, Anastasiou M, Pectasides D, Kyrodimos E, Delides A, Giotakis E, Papadimitriou N, Panayiotides I, Perisanidis C, Fernandez A, Xirou V, Poulios C, Gagari E, Yaghoobi V, Gavrielatou N, Shafi S, Aung T, Kougioumtzopoulou A, Kouloulias V, Palialexis K, Gkolfinopoulos S, Strati A, Lianidou E, Fountzilas G, Rimm D, Foukas P, Psyrri A. Phase II window study of olaparib alone or with cisplatin or durvalumab in operable Head and Neck Cancer. Cancer Research Communications 2023, 3: 1514-1523. PMID: 37575280, PMCID: PMC10414130, DOI: 10.1158/2767-9764.crc-23-0051.Peer-Reviewed Original ResearchConceptsObjective response rateTumor microenvironmentPD-L1Operable headResponse rateDeath ligand 1 (PD-L1) levelsPathologic complete response ratePhase II window studyNeck squamous cell carcinomaPD-L1 CPSComplete response rateSerious adverse eventsPercentage of patientsInhibitor-based treatmentSquamous cell carcinomaEffective antitumor responseImmunosuppressive tumor microenvironmentInflammatory tumor microenvironmentTumor cell proliferationColony-stimulating factor 1 receptor (CSF1R) genePrimary endpointSecondary endpointsAdverse eventsOpportunity trialAntitumor responseIntegrative deep learning analysis improves colon adenocarcinoma patient stratification at risk for mortality
Zhou J, pour A, Deirawan H, Daaboul F, Aung T, Beydoun R, Ahmed F, Chuang J. Integrative deep learning analysis improves colon adenocarcinoma patient stratification at risk for mortality. EBioMedicine 2023, 94: 104726. PMID: 37499603, PMCID: PMC10388166, DOI: 10.1016/j.ebiom.2023.104726.Peer-Reviewed Original ResearchConceptsModerate-risk patientsClinical variablesPatient stratificationOverall survivalAdenocarcinoma patientsTCGA-COADLow-risk patientsColorectal cancer patientsEnrollment of patientsRectal adenocarcinoma patientsRisk of mortalityColon adenocarcinoma patientsLow immune infiltrationNational Cancer InstituteMutation signaturesNumber of deathsCancer Genome AtlasColorectal cancerPathological featuresCancer patientsImmune infiltrationImproved stratificationClinical trialsPatient riskCancer InstituteSubsets 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 patterns202 Automated assessment of tumor infiltrating lymphocytes informs mortality in thin melanoma
Tan S, Aung T, Claeson M, Zhou C, Brown S, Acs B, Lambie D, Baade P, Pandeya N, Soyer H, Smithers B, Whiteman D, Rimm D, Khosrotehrani K. 202 Automated assessment of tumor infiltrating lymphocytes informs mortality in thin melanoma. Journal Of Investigative Dermatology 2023, 143: s34. DOI: 10.1016/j.jid.2023.03.204.Peer-Reviewed Original ResearchDigital spatial profiling links beta-2-microglobulin expression with immune checkpoint blockade outcomes in head and neck squamous cell carcinoma
Gavrielatou N, Vathiotis I, Aung T, Shafi S, Burela S, Fernandez A, Moutafi M, Burtness B, Economopoulou P, Anastasiou M, Foukas P, Psyrri A, Rimm D. Digital spatial profiling links beta-2-microglobulin expression with immune checkpoint blockade outcomes in head and neck squamous cell carcinoma. Cancer Research Communications 2023, 3: 558-563. PMID: 37057033, PMCID: PMC10088911, DOI: 10.1158/2767-9764.crc-22-0299.Peer-Reviewed Original ResearchConceptsDigital spatial profilingB2M expressionOverall survivalM HNSCCImmunotherapy outcomesNeck squamous cell carcinoma (HNSCC) treatmentHigh beta-2 microglobulinSquamous cell carcinoma treatmentCell death protein 1Neck squamous cell carcinomaM expressionPretreatment biopsy samplesImmune checkpoint inhibitorsPD-L1 expressionImmune checkpoint markersDeath protein 1Squamous cell carcinomaB2MBeta-2-microglobulinBeta 2 microglobulin expressionImproved PFSCheckpoint inhibitorsMetastatic headCheckpoint markersImproved survivalQuantitative, Spatially Defined Expression of Leukocyte Associated Immunoglobulin-like Receptor (LAIR-1) in Non-Small Cell Lung Cancer
Aung T, Gavrielatou N, Vathiotis I, Fernandez A, Shafi S, Yaghoobi V, Burela S, MacNeil T, Ahmed F, Myint H, Flies D, Langermann S, Rimm D. Quantitative, Spatially Defined Expression of Leukocyte Associated Immunoglobulin-like Receptor (LAIR-1) in Non-Small Cell Lung Cancer. Cancer Research Communications 2023, 3: 471-482. PMID: 36960400, PMCID: PMC10029762, DOI: 10.1158/2767-9764.crc-22-0334.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerLeukocyte-associated immunoglobulin-like receptor-1LAIR-1 expressionMultiplexed quantitative immunofluorescenceCell lung cancerLung adenocarcinomaLung cancerPD-L1Anti-PD-1/PD-L1Anti-PD-1 resistanceSquamous cell carcinoma subtypeImmunoglobulin-like receptor-1Cancer immunotherapeutic strategiesDeath-1 blockadeResistant lung tumorsImmunoglobulin-like receptorsCell typesAntitumor immunityImmunotherapeutic strategiesHistologic subtypePrognostic valueCombination therapyLung tumorsCarcinoma subtypesLAIR-2Spatial characterization and quantification of CD40 expression across cancer types
Bates K, Vathiotis I, MacNeil T, Ahmed F, Aung T, Katlinskaya Y, Bhattacharya S, Psyrri A, Yea S, Parkes A, Sadraei N, Roychoudhury S, Rimm D, Gavrielatou N. Spatial characterization and quantification of CD40 expression across cancer types. BMC Cancer 2023, 23: 220. PMID: 36894898, PMCID: PMC9996913, DOI: 10.1186/s12885-023-10650-7.Peer-Reviewed Original ResearchConceptsCD40 expressionSolid tumorsTumor cellsQuantitative immunofluorescencePatient cohortPancreatic cancerCancer typesExpression of CD40Large patient cohortOvarian cancer populationTissue microarray formatDifferent solid tumorsInnate immune responseTNF receptor family membersAvailable patient cohortNSCLC populationOverall survivalPrognostic impactReceptor family membersCancer populationAdenocarcinoma populationImmune cellsOvarian cancerPancreatic adenocarcinomaPositivity rate
2022
Baseline gene expression profiling determines long-term benefit to programmed cell death protein 1 axis blockade
Vathiotis I, Salichos L, Martinez-Morilla S, Gavrielatou N, Aung T, Shafi S, Wong P, Jessel S, Kluger H, Syrigos K, Warren S, Gerstein M, Rimm D. Baseline gene expression profiling determines long-term benefit to programmed cell death protein 1 axis blockade. Npj Precision Oncology 2022, 6: 92. PMID: 36522538, PMCID: PMC9755314, DOI: 10.1038/s41698-022-00330-3.Peer-Reviewed Original ResearchProgression-free survivalLong-term benefitsPredictive valueAnti-PD-1 therapyCell death protein 1Baseline tumor samplesImmune checkpoint inhibitorsAntitumor immune responseCohort of patientsDeath protein 1Gene expression profilesAdvanced diseaseCheckpoint inhibitorsAdvanced melanomaAxis blockadeImmunotherapy outcomesTreatment initiationEarly outcomesDisease progressionMalignant melanomaBaseline gene expressionImmune responseBaseline gene expression profilesExpression profilesTumor samples127 Spatial-specific gene signatures outperform bulk-mRNA signatures to define resistance to immunotherapy in melanoma patients
Aung T, Warrell J, Martinez-Morilla S, Gavrielatou N, Vathiotis L, Chan N, Kluger H, Rimm D. 127 Spatial-specific gene signatures outperform bulk-mRNA signatures to define resistance to immunotherapy in melanoma patients. 2022, a140-a140. DOI: 10.1136/jitc-2022-sitc2022.0127.Peer-Reviewed Original Research133 Spatially defined gene signatures uncover the association of extracellular matrix genes with immunotherapy resistance in head and neck squamous cell carcinoma
Gavrielatou N, Warrell J, Aung T, Vathiotis L, Economopoulou P, Burtness B, Psyrri A, Rimm D. 133 Spatially defined gene signatures uncover the association of extracellular matrix genes with immunotherapy resistance in head and neck squamous cell carcinoma. 2022, a146-a146. DOI: 10.1136/jitc-2022-sitc2022.0133.Peer-Reviewed Original ResearchQuantitative assessment of Siglec-15 expression in lung, breast, head, and neck squamous cell carcinoma and bladder cancer.
Shafi S, Aung T, Xirou V, Gavrielatou N, Vathiotis I, Fernandez A, Moutafi M, Yaghoobi V, Herbst R, Liu L, Langermann S, Rimm D. Quantitative assessment of Siglec-15 expression in lung, breast, head, and neck squamous cell carcinoma and bladder cancer. Laboratory Investigation 2022, 102: 1143-1149. PMID: 36775354, DOI: 10.1038/s41374-022-00796-6.Peer-Reviewed Original ResearchConceptsSiglec-15 expressionNon-small cell lung cancerNeck squamous cell carcinomaProgression-free survivalSquamous cell carcinomaCancer typesOverall survivalCell carcinomaBladder cancerImmune cellsSiglec-15PD-1/PD-L1 blockadePotential future clinical trialsQuantitative immunofluorescencePD-L1 blockadeStromal immune cellsImmune checkpoint blockadeCell lung cancerFuture clinical trialsNew potential targetsCheckpoint blockadePD-L1Lung cancerClinical trialsIntra-tumoral heterogeneityObjective assessment of tumor infiltrating lymphocytes as a prognostic marker in melanoma using machine learning algorithms
Aung TN, Shafi S, Wilmott JS, Nourmohammadi S, Vathiotis I, Gavrielatou N, Fernandez A, Yaghoobi V, Sinnberg T, Amaral T, Ikenberg K, Khosrotehrani K, Osman I, Acs B, Bai Y, Martinez-Morilla S, Moutafi M, Thompson JF, Scolyer RA, Rimm DL. Objective assessment of tumor infiltrating lymphocytes as a prognostic marker in melanoma using machine learning algorithms. EBioMedicine 2022, 82: 104143. PMID: 35810563, PMCID: PMC9272337, DOI: 10.1016/j.ebiom.2022.104143.Peer-Reviewed Original ResearchConceptsTumor-infiltrating lymphocytesMelanoma patientsPrognostic valuePrognostic markerPrimary melanoma patientsRobust prognostic markerStage II patientsSpecific molecular subtypesTIL phenotypeAdjuvant therapyOverall survivalSurgical treatmentTIL scoreII patientsSurvival outcomesLung cancerClinical trialsPrimary melanomaClinical impactT cellsMolecular subtypesHigh riskIndependent cohortLower riskEosin stainingProgrammed Death-Ligand 1 and Programmed Death-Ligand 2 mRNAs Measured Using Closed-System Quantitative Real-Time Polymerase Chain Reaction Are Associated With Outcome and High Negative Predictive Value in Immunotherapy-Treated NSCLC
Fernandez AI, Gavrielatou N, McCann L, Shafi S, Moutafi MK, Martinez-Morilla S, Vathiotis IA, Aung TN, Yaghoobi V, Bai Y, Chan YG, Weidler J, Herbst R, Bates M, Rimm DL. Programmed Death-Ligand 1 and Programmed Death-Ligand 2 mRNAs Measured Using Closed-System Quantitative Real-Time Polymerase Chain Reaction Are Associated With Outcome and High Negative Predictive Value in Immunotherapy-Treated NSCLC. Journal Of Thoracic Oncology 2022, 17: 1078-1085. PMID: 35764237, DOI: 10.1016/j.jtho.2022.06.007.Peer-Reviewed Original ResearchConceptsImmune checkpoint inhibitorsHigh negative predictive valueLow stage patientsICI therapyPD-L1Negative predictive valueAdjuvant settingLong-term benefitsPredictive valueProgrammed Death Ligand 1PD-L1 mRNA levelsCurrent predictive biomarkersHigh PD-L1Death ligand 1Lung cancer managementPD-L1 mRNAUseful objective methodReal-time reverse transcription-polymerase chain reactionMRNA levelsStandard of careReverse transcription-polymerase chain reactionQuantitative real-time reverse transcription-polymerase chain reactionTranscription-polymerase chain reactionMRNA expression levelsAdvanced NSCLC