2025
FAK inhibition combined with the RAF-MEK clamp avutometinib overcomes resistance to targeted and immune therapies in BRAF V600E melanoma
Lubrano S, Cervantes-Villagrana R, Faraji F, Ramirez S, Sato K, Adame-Garcia S, Officer A, Arang N, Rigiracciolo D, Anguiano Quiroz P, Martini C, Wang Y, Ferguson F, Bacchiocchi A, Halaban R, Coma S, Holmen S, Pachter J, Aplin A, Gutkind J. FAK inhibition combined with the RAF-MEK clamp avutometinib overcomes resistance to targeted and immune therapies in BRAF V600E melanoma. Cancer Cell 2025, 43: 428-445.e6. PMID: 40020669, PMCID: PMC11903146, DOI: 10.1016/j.ccell.2025.02.001.Peer-Reviewed Original ResearchConceptsBRAF V600E melanomaFocal adhesion kinaseV600E melanomaFAK inhibitorActivated focal adhesion kinaseFocal adhesion kinase inhibitionRaf-MEKActivation of focal adhesion signalingFocal adhesion kinase inhibitorResistance to BRAFiSyngeneic mouse modelMAPK pathway inhibitionFocal adhesion signalingPro-apoptotic activityMelanoma patientsAdhesion signalingImmune therapyBRAF mutationsBRAFiTranscriptome analysisMelanomaMouse modelPathway inhibitionBRAFMelanoma cells
2024
Ultra-sensitive molecular residual disease detection through whole genome sequencing with single-read error correction
Li X, Liu T, Bacchiocchi A, Li M, Cheng W, Wittkop T, Mendez F, Wang Y, Tang P, Yao Q, Bosenberg M, Sznol M, Yan Q, Faham M, Weng L, Halaban R, Jin H, Hu Z. Ultra-sensitive molecular residual disease detection through whole genome sequencing with single-read error correction. EMBO Molecular Medicine 2024, 16: 2188-2209. PMID: 39164471, PMCID: PMC11393307, DOI: 10.1038/s44321-024-00115-0.Peer-Reviewed Original ResearchMolecular residual diseaseCirculating tumor DNAWhole-genome sequencingCell-free DNAGenome sequenceDetection of molecular residual diseaseCirculating tumor DNA detectionResidual disease detectionConsistent with clinical outcomesVariant allele frequencyResidual diseaseMelanoma patientsMonitoring immunotherapyTumor DNAEsophageal cancerClinical outcomesColorectal cancerWGS technologiesAllele frequenciesCancerDNAAnalytical sensitivitySequenceImmunotherapyRelapseChemical complementarity of tumor resident, T-cell receptor CDR3s and renalase-1 correlates with increased melanoma survival
Zaman S, Gorelick F, Chrobrutskiy A, Chobrutskiy B, Desir G, Blanck G. Chemical complementarity of tumor resident, T-cell receptor CDR3s and renalase-1 correlates with increased melanoma survival. Oncotarget 2024, 15: 550-561. PMID: 39102218, PMCID: PMC11299663, DOI: 10.18632/oncotarget.28633.Peer-Reviewed Original ResearchConceptsT cell receptorOverall survivalT cellsAssociated with improved overall survivalT-cell receptor CDR3sPromote T cell activationImproved overall survivalSurvival of melanomaPancreatic cancer patientsT cell activationT cell receptor recognitionTumor-residentTumor rejectionMelanoma patientsMelanoma growthMelanoma survivalImmune signature genesSurvival associationsCancer patientsMelanomaSignature genesAmino acid sequenceSurvivalPatientsExpression levelsSpatially 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 dataTumour necrosis is a valuable histopathological prognostic parameter in melanomas of the vulva and vagina
Roy S, Baig J, DeCoste R, Finch S, Sennik S, Kakadekar A, Sade S, Micevic G, Chergui M, Rahimi K, Flaman A, Trinh V, Osmond A. Tumour necrosis is a valuable histopathological prognostic parameter in melanomas of the vulva and vagina. Pathology 2024, 56: 854-864. PMID: 38906758, DOI: 10.1016/j.pathol.2024.03.008.Peer-Reviewed Original ResearchTumor necrosisVaginal melanomaPrognostic factorsDisease-specific mortalitySurvival outcomesKaplan-Meier log-rankAssociated with disease-specific mortalityKaplan-Meier survival analysisPositive lymph nodesHistopathological prognostic parametersMedian follow-upMetastasis-free survivalNon-metastatic patientsMultivariate Cox regressionTime to metastasisFollow-up dataTertiary Canadian hospitalProgression-freeTumor ulcerationMelanoma patientsPrognostic parametersLymph nodesAggressive malignancyImmunohistochemical markersLog-rankCombined BET and MEK Inhibition synergistically suppresses melanoma by targeting YAP1
Hu R, Hou H, Li Y, Zhang M, Li X, Chen Y, Guo Y, Sun H, Zhao S, Liao M, Cao D, Yan Q, Chen X, Yin M. Combined BET and MEK Inhibition synergistically suppresses melanoma by targeting YAP1. Theranostics 2024, 14: 593-607. PMID: 38169595, PMCID: PMC10758063, DOI: 10.7150/thno.85437.Peer-Reviewed Original ResearchConceptsMEK inhibitor resistanceMEK inhibitor trametinibTrametinib treatmentInhibitor resistanceInhibitor trametinibMelanoma patientsYAP1 expressionMEK inhibitionBRAF-mutant melanoma patientsResistance to MEK inhibitionYAP1 inhibitionResistance to trametinibMelanoma growth <i>inInhibition of BRD4Trametinib resistanceAntitumor effectMelanoma growthTrametinibNHWD-870YAP1 inhibitorDrug resistanceMelanomaMelanoma samplesMelanoma cellsBRD4 depletion
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 therapeuticsPatientsDigital spatial profiling of melanoma shows CD95 expression in immune cells is associated with resistance to immunotherapy
Martinez-Morilla S, Moutafi M, Fernandez A, Jessel S, Divakar P, Wong P, Garcia-Milian R, Schalper K, Kluger H, Rimm D. Digital spatial profiling of melanoma shows CD95 expression in immune cells is associated with resistance to immunotherapy. OncoImmunology 2023, 12: 2260618. PMID: 37781235, PMCID: PMC10540659, DOI: 10.1080/2162402x.2023.2260618.Peer-Reviewed Original ResearchConceptsDigital spatial profilingImmune checkpoint inhibitor therapyShorter progression-free survivalQuantitative immunofluorescenceCheckpoint inhibitor therapyProgression-free survivalMetastatic melanoma patientsPre-treatment specimensIndependent validation cohortMetastatic melanoma casesAdjuvant settingNanoString GeoMxMultivariable adjustmentAdverse eventsImmunotherapy cohortInhibitor therapyPD-L1Immune markersMelanoma patientsUnivariable analysisValidation cohortImmune cellsMelanoma casesMultiplex immunofluorescenceCD95 expressionLeptomeningeal disease in melanoma: An update on the developments in pathophysiology and clinical care
Smalley I, Boire A, Brastianos P, Kluger H, Hernando‐Monge E, Forsyth P, Ahmed K, Smalley K, Ferguson S, Davies M, Oliva I. Leptomeningeal disease in melanoma: An update on the developments in pathophysiology and clinical care. Pigment Cell & Melanoma Research 2023, 37: 51-67. PMID: 37622466, DOI: 10.1111/pcmr.13116.Peer-Reviewed Original ResearchA subset of neutrophils as a predictive biomarker for immunotherapy response in patients with non–small-cell lung cancer and melanoma.
Shaked Y, Benguigui M, Halaban R, Bacchiocchi A, Kamer I, Bar J, Lotem M, Shen-Orr S, Sznol M, Cooper T. A subset of neutrophils as a predictive biomarker for immunotherapy response in patients with non–small-cell lung cancer and melanoma. Journal Of Clinical Oncology 2023, 41: 2557-2557. DOI: 10.1200/jco.2023.41.16_suppl.2557.Peer-Reviewed Original ResearchPeripheral blood mononuclear cellsCell lung cancerImmunotherapy outcomesImmunotherapy responseMelanoma patientsCancer patientsLung cancerT cellsImmune checkpoint inhibitor-based therapyNew biomarkersNon-small cell lung cancerAdvanced metastatic NSCLCAnti-PD1 responseImmunotherapy-treated patientsMyeloid cell compositionPDL-1 expressionSubset of neutrophilsAnti-PD1 therapyMalignant melanoma patientsBlood mononuclear cellsInhibitor-based therapyPre-clinical modelsRenal cell carcinomaBlood-borne biomarkersSuccessful clinical trialsDynamic changes of circulating soluble PD-1/PD-L1 and its association with patient survival in immune checkpoint blockade-treated melanoma
Lu L, Risch E, Halaban R, Zhen P, Bacchiocchi A, Risch H. Dynamic changes of circulating soluble PD-1/PD-L1 and its association with patient survival in immune checkpoint blockade-treated melanoma. International Immunopharmacology 2023, 118: 110092. PMID: 37004344, DOI: 10.1016/j.intimp.2023.110092.Peer-Reviewed Original ResearchConceptsImmune checkpoint blockadeSoluble PD-L1 (sPD-L1) levelsPD-L1 ratioPD-L1 levelsSoluble PD-1Soluble PD-L1PD-L1PD-1Patient survivalSurvival statusPD-1/PD-L1Immune checkpoints PD-1T cell exhaustionPatients' survival statusSolid tumor typesInitial immunotherapyCheckpoint blockadeMelanoma patientsPoor prognosisRetrospective studyPatient responseCell exhaustionTumor typesMelanomaSurvival
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 stainingImmune Checkpoint Inhibitor-Induced Hypophysitis and Patterns of Loss of Pituitary Function
Jessel S, Weiss SA, Austin M, Mahajan A, Etts K, Zhang L, Aizenbud L, Perdigoto AL, Hurwitz M, Sznol M, Herold KC, Kluger HM. Immune Checkpoint Inhibitor-Induced Hypophysitis and Patterns of Loss of Pituitary Function. Frontiers In Oncology 2022, 12: 836859. PMID: 35350573, PMCID: PMC8958012, DOI: 10.3389/fonc.2022.836859.Peer-Reviewed Original ResearchImmune checkpoint inhibitorsRenal cell carcinomaCombination immune checkpoint inhibitorsCell carcinomaClinical experienceSelect casesIncidence of hypophysitisInstitution's clinical experienceYale Cancer CenterObjective response rateAdrenal axis hormonesFree testosterone levelsMerkel cell carcinomaHigh rateMultiple tumor typesCheckpoint inhibitorsPituitary axesReal-world practiceFree testosteroneMedian timeMelanoma patientsOverall incidencePituitary functionTreatment delayAxis hormonesTumor MHC Class I Expression Associates with Intralesional IL2 Response in Melanoma
Pourmaleki M, Jones C, Ariyan C, Zeng Z, Pirun M, Navarrete D, Li Y, Zhang M, Nandakumar S, Campos C, Nadeem S, Klimstra D, Temple-Oberle C, Brenn T, Lipson E, Schenk K, Stein J, Taube J, White M, Traweek R, Wargo J, Kirkwood J, Gasmi B, Goff S, Corwin A, McDonough E, Ginty F, Callahan M, Schietinger A, Socci N, Mellinghoff I, Hollmann T. Tumor MHC Class I Expression Associates with Intralesional IL2 Response in Melanoma. Cancer Immunology Research 2022, 10: 303-313. PMID: 35013003, PMCID: PMC8898286, DOI: 10.1158/2326-6066.cir-21-1083.Peer-Reviewed Original ResearchConceptsCD8+ T cellsT cellsUntreated lesionsTumor cellsCohort of metastatic melanoma patientsProliferating CD8+ T cellsPredictive biomarkers of treatment responseExpression of PD-1MHC class I expressionBiomarkers of treatment responseMetastatic melanoma patientsB cell aggregatesResponse to IL2Class I expressionExpression of IFNGIL2 therapyPD-1Cancer immunotherapyTumor regressionMelanoma patientsLAG-3Tim-3IL2 responsivenessInjected lesionsPredictive biomarkers
2021
389 Phase II of CD40 agonistic antibody sotigalimab (APX005M) in combination with nivolumab in subjects with metastatic melanoma with confirmed disease progression on anti-PD-1 therapy
Weiss S, Sznol M, Shaheen M, Berciano-Guerrero M, Felip E, Rodríguez-Abreu D, Arance A, Boni V, Linette G, Schuchter L, Gonzalez-Cao M, Iannotti N, Ganti A, Hauke R, Berrocal A, Filbert E, Kluger H. 389 Phase II of CD40 agonistic antibody sotigalimab (APX005M) in combination with nivolumab in subjects with metastatic melanoma with confirmed disease progression on anti-PD-1 therapy. Journal For ImmunoTherapy Of Cancer 2021, 9: a422-a422. DOI: 10.1136/jitc-2021-sitc2021.389.Peer-Reviewed Original ResearchAnti-PD-1 therapyMelanoma patientsMetastatic melanomaTumor PD-L1 expressionEffective anti-tumor immunityArm phase II trialCD40 agonist antibodyRefractory melanoma patientsRefractory metastatic melanomaAdvanced melanoma patientsPD-1 blockadePD-L1 expressionPhase II trialAnti-tumor immunitySubset of patientsOverall safety profileMajority of AEsOptimal therapeutic applicationReceptor binding profileInstitutional review boardClinical study teamNebraska Medical CenterOpen labelII trialTolerability profileIdentifying treatment options for BRAFV600 wild-type metastatic melanoma: A SU2C/MRA genomics-enabled clinical trial
LoRusso PM, Sekulic A, Sosman JA, Liang WS, Carpten J, Craig DW, Solit DB, Bryce AH, Kiefer JA, Aldrich J, Nasser S, Halperin R, Byron SA, Pilat MJ, Boerner SA, Durecki D, Hendricks WPD, Enriquez D, Izatt T, Keats J, Legendre C, Markovic SN, Weise A, Naveed F, Schmidt J, Basu GD, Sekar S, Adkins J, Tassone E, Sivaprakasam K, Zismann V, Calvert VS, Petricoin EF, Fecher LA, Lao C, Eder JP, Vogelzang NJ, Perlmutter J, Gorman M, Manica B, Fox L, Schork N, Zelterman D, DeVeaux M, Joseph RW, Cowey CL, Trent JM. Identifying treatment options for BRAFV600 wild-type metastatic melanoma: A SU2C/MRA genomics-enabled clinical trial. PLOS ONE 2021, 16: e0248097. PMID: 33826614, PMCID: PMC8026051, DOI: 10.1371/journal.pone.0248097.Peer-Reviewed Original ResearchConceptsMetastatic melanomaAlternate treatment armResponse-evaluable patientsMetastatic melanoma patientsComprehensive genomic profilingAdditional drug classesCutaneous metastatic melanomaLack of responseCombination BRAFStable diseaseTwo-stage optimal designPartial responseProgressive diseaseCare therapyMelanoma patientsMelanoma TrialTreatment armsTreatment optionsBRAFV600 mutationsClinical trialsDrug classesResponse ratePatientsDrug selectionMelanomaTreatment Contraindications Based on Comorbidity Status in Patients With Melanoma in the United States
Boczar D, BAGARIA SP, SPAULDING AC, HUAYLLANI MT, AVILA FR, Guliyeva G, Lu X, RINKER BD, FORTE AJ. Treatment Contraindications Based on Comorbidity Status in Patients With Melanoma in the United States. Anticancer Research 2021, 41: 2067-2070. PMID: 33813415, DOI: 10.21873/anticanres.14976.Peer-Reviewed Original ResearchConceptsNational Cancer DatabaseMultivariate logistic regressionComorbid conditionsTreatment contraindicationsGovernment insuranceLogistic regressionUnknown treatment statusMost patientsPatient demographicsComorbidity statusCurative treatmentMelanoma patientsCancer DatabaseIndependent associationOncological patientsMelanoma incidenceTreatment decisionsInclusion criteriaHigher oddsMelanoma treatmentTreatment statusPatientsPoor candidatesPatient treatmentPrivate insuranceResident and circulating memory T cells persist for years in melanoma patients with durable responses to immunotherapy
Han J, Zhao Y, Shirai K, Molodtsov A, Kolling FW, Fisher JL, Zhang P, Yan S, Searles TG, Bader JM, Gui J, Cheng C, Ernstoff MS, Turk MJ, Angeles CV. Resident and circulating memory T cells persist for years in melanoma patients with durable responses to immunotherapy. Nature Cancer 2021, 2: 300-311. PMID: 34179824, PMCID: PMC8223731, DOI: 10.1038/s43018-021-00180-1.Peer-Reviewed Original ResearchConceptsT cell responsesMemory T cellsT cellsEffector memory T cellsResident memory T cellsMetastatic melanoma survivorsT cells persistStrong prognostic valueT cell receptorDurable responsesMemory CD8Melanoma patientsCancer survivorsPrognostic valueCancer immunotherapyMelanoma survivorsCells persistClonal repertoireSingle-cell RNA sequencingImmunotherapyTumorsExceptional responsePatient's skinClonotypesBloodValidation of the Data Quality of a Tumor Board Registry Through Assessment of Clinicopathologic Survival Outcomes in Melanoma Patients.
Ligtenberg KG, Chartash D, Bosenberg M, Brandt C. Validation of the Data Quality of a Tumor Board Registry Through Assessment of Clinicopathologic Survival Outcomes in Melanoma Patients. AMIA Annual Symposium Proceedings 2021, 2020: 747-755. PMID: 33936449, PMCID: PMC8075482.Peer-Reviewed Original Research
2020
Quantitative analysis of CMTM6 expression in tumor microenvironment in metastatic melanoma and association with outcome on immunotherapy
Martinez-Morilla S, Zugazagoitia J, Wong PF, Kluger HM, Rimm DL. Quantitative analysis of CMTM6 expression in tumor microenvironment in metastatic melanoma and association with outcome on immunotherapy. OncoImmunology 2020, 10: 1864909. PMID: 33457084, PMCID: PMC7781756, DOI: 10.1080/2162402x.2020.1864909.Peer-Reviewed Original ResearchConceptsImmune checkpoint inhibitorsPD-L1CMTM6 expressionControl patientsLonger survivalTissue microarrayQuantitative immunofluorescenceEffectiveness of immunotherapyMetastatic melanoma patientsDeath ligand 1Like MARVEL transmembrane domainCancer Genome Atlas (TCGA) databaseExpression of CMTM6MARVEL transmembrane domainExpression of mRNAChemokine-like factorICI treatmentCheckpoint inhibitorsPretreatment biopsiesCD68 markersImmune compartmentMultivariable analysisMelanoma patientsImmune-related proteinsPredictive factors
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