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 benefitsPatientsCD68
2023
New 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 patternsDigital 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
Quantitative 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 NSCLCQuantitative assessment of Siglec-15 expression in lung, breast, head, and neck squamous cell carcinoma and bladder cancer
Shafi S, Aung TN, Xirou V, Gavrielatou N, Vathiotis IA, Fernandez A, Moutafi M, Yaghoobi V, Herbst RS, Liu LN, Langermann S, Rimm DL. 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: 35581307, PMCID: PMC10211373, 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 heterogeneityDiscovery of Biomarkers of Resistance to Immune Checkpoint Blockade in NSCLC Using High-Plex Digital Spatial Profiling
Moutafi M, Martinez-Morilla S, Divakar P, Vathiotis I, Gavrielatou N, Aung TN, Yaghoobi V, Fernandez AI, Zugazagoitia J, Herbst R, Schalper KA, Rimm DL. Discovery of Biomarkers of Resistance to Immune Checkpoint Blockade in NSCLC Using High-Plex Digital Spatial Profiling. Journal Of Thoracic Oncology 2022, 17: 991-1001. PMID: 35490853, PMCID: PMC9356986, DOI: 10.1016/j.jtho.2022.04.009.Peer-Reviewed Original ResearchConceptsImmune checkpoint inhibitorsICI resistanceDigital spatial profilingICI therapyOverall survivalPretreatment samplesQuantitative immunofluorescenceImmune checkpoint blockadeRole of neutrophilsShorter overall survivalCandidate biomarker proteinsCandidate protein biomarkersCohort validationOperable NSCLCUntreated NSCLCCheckpoint inhibitorsCheckpoint blockadeCD66b expressionAdditional patientsClinical efficacyPoor outcomeDiscovery of biomarkersUnivariate analysisNSCLCPatientsDevelopment of an immunohistochemical assay for Siglec-15
Shafi S, Aung TN, Robbins C, Zugazagoitia J, Vathiotis I, Gavrielatou N, Yaghoobi V, Fernandez A, Niu S, Liu LN, Cusumano ZT, Leelatian N, Cole K, Wang H, Homer R, Herbst RS, Langermann S, Rimm DL. Development of an immunohistochemical assay for Siglec-15. Laboratory Investigation 2022, 102: 771-778. PMID: 35459795, PMCID: PMC9253057, DOI: 10.1038/s41374-022-00785-9.Peer-Reviewed Original ResearchConceptsSiglec-15IHC assaysPD-L1PD-1/PD-L1 inhibitionPD-L1 blockadePD-L1 inhibitionHigh expressionFuture clinical trialsImmunoglobulin-type lectinsSiglec-15 expressionCompanion diagnostic assayPromising new targetTumor histologyImmunotherapeutic targetLung cancerImmune cellsClinical trialsNovel recombinant antibodiesCancer histologyImmunohistochemical assaysMyeloid cellsTumor typesScoring systemNew targetsHigh concordanceAssociation of PD-1/PD-L1 Co-location with Immunotherapy Outcomes in Non-Small Cell Lung Cancer
Gavrielatou N, Liu Y, Vathiotis I, Zugazagoitia J, Aung TN, Shafi S, Fernandez A, Schalper K, Psyrri A, Rimm DL. Association of PD-1/PD-L1 Co-location with Immunotherapy Outcomes in Non-Small Cell Lung Cancer. Clinical Cancer Research 2022, 28: clincanres.2649.2021. PMID: 34686497, PMCID: PMC8776595, DOI: 10.1158/1078-0432.ccr-21-2649.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerBest overall responsePD-L1 tumor proportion scorePD-1/PD-L1Immune checkpoint inhibitorsProgression-free survivalTumor proportion scoreCell lung cancerPD-L1Immunotherapy outcomesCheckpoint inhibitorsOverall survivalQuantitative immunofluorescenceLung cancerProportion scoreAdvanced non-small cell lung cancerLocal T cell responsesCell death protein 1Immunotherapy-treated patientsMultiplexed quantitative immunofluorescencePD-1 expressionPD-L1 expressionDeath protein 1Selection of patientsT cell responses
2021
Quantitative assessment of the immune microenvironment in African American Triple Negative Breast Cancer: a case–control study
Yaghoobi V, Moutafi M, Aung TN, Pelekanou V, Yaghoubi S, Blenman K, Ibrahim E, Vathiotis IA, Shafi S, Sharma A, O’Meara T, Fernandez AI, Pusztai L, Rimm DL. Quantitative assessment of the immune microenvironment in African American Triple Negative Breast Cancer: a case–control study. Breast Cancer Research 2021, 23: 113. PMID: 34906209, PMCID: PMC8670126, DOI: 10.1186/s13058-021-01493-w.Peer-Reviewed Original ResearchConceptsNegative breast cancerT cellsTumor microenvironmentAA patientsImmune cellsAA tumorsBreast cancerPurposeTriple-negative breast cancerAfrican AmericansTriple-negative breast cancerCase-control studySignificant differencesActivated T cellsImmunologic biomarkersPD-L1Lymphocytic infiltrationLymphoid infiltrationImmune microenvironmentControl cohortTNBC tumorsMyeloid markersQuantitative immunofluorescenceMean expression levelPatientsTNBCAlpha-smooth muscle actin expression in the stroma predicts resistance to trastuzumab in patients with early-stage HER2-positive breast cancer
Vathiotis IA, Moutafi MK, Divakar P, Aung TN, Qing T, Fernandez A, Yaghoobi V, El-Abed S, Wang Y, Guillaume S, Nuciforo P, Huober J, Di Cosimo S, Kim SB, Harbeck N, Gomez H, Shafi S, Syrigos KN, Fountzilas G, Sotiriou C, Pusztai L, Warren S, Rimm DL. Alpha-smooth muscle actin expression in the stroma predicts resistance to trastuzumab in patients with early-stage HER2-positive breast cancer. Clinical Cancer Research 2021, 27: 6156-6163. PMID: 34465600, PMCID: PMC8595766, DOI: 10.1158/1078-0432.ccr-21-2103.Peer-Reviewed Original ResearchConceptsDisease-free survivalHER2-positive breast cancerShorter disease-free survivalBreast cancerQuantitative immunofluorescenceEarly-stage HER2-positive breast cancerAlpha-smooth muscle actin expressionAlpha-smooth muscle actinProgesterone receptor statusHigh α-SMA expressionDigital Spatial ProfilerΑ-SMA expressionPromising candidate biomarkerCompanion diagnostic testsMuscle actin expressionDigital spatial profilingCohort validationNeoadjuvant lapatinibAdjuvant trastuzumabReceptor statusClinical trialsUnivariate analysisEstrogen receptorMAIN OUTCOMEΑ-SMASTING enhances cell death through regulation of reactive oxygen species and DNA damage
Hayman TJ, Baro M, MacNeil T, Phoomak C, Aung TN, Cui W, Leach K, Iyer R, Challa S, Sandoval-Schaefer T, Burtness BA, Rimm DL, Contessa JN. STING enhances cell death through regulation of reactive oxygen species and DNA damage. Nature Communications 2021, 12: 2327. PMID: 33875663, PMCID: PMC8055995, DOI: 10.1038/s41467-021-22572-8.Peer-Reviewed Original ResearchA new tool for technical standardization of the Ki67 immunohistochemical assay
Aung TN, Acs B, Warrell J, Bai Y, Gaule P, Martinez-Morilla S, Vathiotis I, Shafi S, Moutafi M, Gerstein M, Freiberg B, Fulton R, Rimm DL. A new tool for technical standardization of the Ki67 immunohistochemical assay. Modern Pathology 2021, 34: 1261-1270. PMID: 33536573, PMCID: PMC8222064, DOI: 10.1038/s41379-021-00745-6.Peer-Reviewed Original Research