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 samples
2021
Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma
Johannet P, Coudray N, Donnelly DM, Jour G, Illa-Bochaca I, Xia Y, Johnson DB, Wheless L, Patrinely JR, Nomikou S, Rimm DL, Pavlick AC, Weber JS, Zhong J, Tsirigos A, Osman I. Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma. Clinical Cancer Research 2021, 27: 131-140. PMID: 33208341, PMCID: PMC7785656, DOI: 10.1158/1078-0432.ccr-20-2415.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedDisease ProgressionDrug Resistance, NeoplasmFemaleFollow-Up StudiesHumansImage Processing, Computer-AssistedImmune Checkpoint InhibitorsMachine LearningMaleMelanomaMiddle AgedNeoplasm StagingPrognosisProgression-Free SurvivalProspective StudiesRisk AssessmentROC CurveSkinSkin NeoplasmsConceptsProgression-free survivalImmune checkpoint inhibitorsLower riskClinicodemographic characteristicsAdvanced melanomaClinical dataWorse progression-free survivalICI treatment outcomesKaplan-Meier curvesBiomarkers of responseStandard of careCheckpoint inhibitorsICI responseImmunotherapy responseValidation cohortTraining cohortDisease progressionProspective validationTreatment outcomesHigh riskClinical practicePatientsROC curveProgressionRisk
2018
Immunological differences between primary and metastatic breast cancer
Szekely B, Bossuyt V, Li X, Wali VB, Patwardhan GA, Frederick C, Silber A, Park T, Harigopal M, Pelekanou V, Zhang M, Yan Q, Rimm DL, Bianchini G, Hatzis C, Pusztai L. Immunological differences between primary and metastatic breast cancer. Annals Of Oncology 2018, 29: 2232-2239. PMID: 30203045, DOI: 10.1093/annonc/mdy399.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAntineoplastic Agents, ImmunologicalB7-H1 AntigenBiomarkers, TumorBiopsyBreast NeoplasmsDisease ProgressionDrug Resistance, NeoplasmFemaleGene Expression RegulationHumansImmunologic SurveillanceLymphocyte CountLymphocytes, Tumor-InfiltratingMiddle AgedMutation RateTumor EscapeTumor MicroenvironmentYoung AdultConceptsMetastatic breast cancerBreast cancerTherapeutic targetToll-like receptor pathway genesImmuno-oncology therapeutic targetsBreast cancer evolvesImmune proteasome expressionPD-L1 positivityCorresponding primary tumorsPotential therapeutic targetMHC class IImmune-related genesMetastatic cancer samplesLigand/receptor pairLymphocyte countT helperT-regsPD-L1Immune microenvironmentCytotoxic TPrimary tumorMastoid cellsDisease progressionTherapeutic combinationsMacrophage markers
2016
miR-34a Silences c-SRC to Attenuate Tumor Growth in Triple-Negative Breast Cancer
Adams BD, Wali VB, Cheng CJ, Inukai S, Booth CJ, Agarwal S, Rimm DL, Győrffy B, Santarpia L, Pusztai L, Saltzman WM, Slack FJ. miR-34a Silences c-SRC to Attenuate Tumor Growth in Triple-Negative Breast Cancer. Cancer Research 2016, 76: 927-939. PMID: 26676753, PMCID: PMC4755913, DOI: 10.1158/0008-5472.can-15-2321.Peer-Reviewed Original ResearchConceptsTriple-negative breast cancerBreast cancerTumor growthMiR-34a replacement therapyTNBC cell linesDifferent TNBC subtypesPromising therapeutic strategyAttenuates tumor growthHuman clinical trialsMiRNA-profiling studiesMiR-34a levelsCell linesPotent antitumorigenic effectsMiR-34a targetsHuman tumor specimensC-SrcReplacement therapyTNBC subtypesAggressive subtypeTreatment optionsClinical trialsDisease progressionEffective therapyPatient outcomesC-Src inhibitor
2014
Induction cetuximab, paclitaxel, and carboplatin followed by chemoradiation with cetuximab, paclitaxel, and carboplatin for stage III/IV head and neck squamous cancer: a phase II ECOG-ACRIN trial (E2303)
Wanebo HJ, Lee J, Burtness BA, Ridge JA, Ghebremichael M, Spencer SA, Psyrri D, Pectasides E, Rimm D, Rosen FR, Hancock MR, Tolba KA, Forastiere AA. Induction cetuximab, paclitaxel, and carboplatin followed by chemoradiation with cetuximab, paclitaxel, and carboplatin for stage III/IV head and neck squamous cancer: a phase II ECOG-ACRIN trial (E2303). Annals Of Oncology 2014, 25: 2036-2041. PMID: 25009013, PMCID: PMC4176450, DOI: 10.1093/annonc/mdu248.Peer-Reviewed Original ResearchConceptsEvent-free survivalStage III/IV headResponse/survivalInduction therapyComplete responseStage III/IV HNSCCNeck squamous cell carcinomaPrimary site biopsiesTreatment-related deathsPathologic complete responseNeck squamous cancerSquamous cell carcinomaProtein expression statusEligible patientsSite biopsiesOverall survivalCell carcinomaPromising survivalSquamous cancerDisease progressionChemoradiationRadiation therapyPatientsWeek 9Cetuximab
2005
Translational Crossroads for Biomarkers
Bast RC, Lilja H, Urban N, Rimm DL, Fritsche H, Gray J, Veltri R, Klee G, Allen A, Kim N, Gutman S, Rubin MA, Hruszkewycz A. Translational Crossroads for Biomarkers. Clinical Cancer Research 2005, 11: 6103-6108. PMID: 16144908, DOI: 10.1158/1078-0432.ccr-04-2213.Peer-Reviewed Original ResearchConceptsNational Cancer InstituteBiomarker developmentCancer InstituteClinical needAccurate pretreatment stagingUseful laboratory testPrediction of responsePretreatment stagingCancer careDisease progressionOvarian cancerProstate cancerBreast cancerGroups of investigatorsEarly cancer detectionDrug AdministrationTumor typesPromising markerTissue specimensClinical paradigmSpecific markersBiomarkersCancerMultiple biomarkersNew markers
2003
JAKs and STATs as Biomarkers of Disease
Dolled-Filhart M, Rimm D. JAKs and STATs as Biomarkers of Disease. 2003, 697-720. DOI: 10.1007/978-94-017-3000-6_44.Peer-Reviewed Original ResearchClinical practice todayPathways of tumorigenesisPrecise disease classificationPrognosticate outcomesClinical trialsDisease progressionDisease outcomeLarge cohortTumor specimensBiomarkers of diseaseSmall studyNew biomarkersPredictive valueBiomarker expressionHuman malignanciesPatient samplesLevel of expressionTherapeutic agentsTumor biomarkersTherapyProtein expressionBiomarkersPatientsOutcomesDisease