2024
Spatially 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 data
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 therapeuticsPatients
2022
Objective 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 staining