2021
Genomic features of rapid versus late relapse in triple negative breast cancer
Zhang Y, Asad S, Weber Z, Tallman D, Nock W, Wyse M, Bey JF, Dean KL, Adams EJ, Stockard S, Singh J, Winer EP, Lin NU, Jiang YZ, Ma D, Wang P, Shi L, Huang W, Shao ZM, Cherian M, Lustberg MB, Ramaswamy B, Sardesai S, VanDeusen J, Williams N, Wesolowski R, Obeng-Gyasi S, Sizemore GM, Sizemore ST, Verschraegen C, Stover DG. Genomic features of rapid versus late relapse in triple negative breast cancer. BMC Cancer 2021, 21: 568. PMID: 34006255, PMCID: PMC8130400, DOI: 10.1186/s12885-021-08320-7.Peer-Reviewed Original ResearchMeSH KeywordsAdultBiomarkers, TumorChemotherapy, AdjuvantDatasets as TopicDisease-Free SurvivalDNA Copy Number VariationsFemaleFollow-Up StudiesGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLogistic ModelsMastectomyMiddle AgedModels, GeneticMutationNeoadjuvant TherapyNeoplasm Recurrence, LocalPrognosisRisk AssessmentTime FactorsTriple Negative Breast NeoplasmsConceptsLate relapseRapid relapseImmune signaturesBreast cancerAnti-tumor CD8 T cellsBackgroundTriple-negative breast cancerTriple-negative breast cancerCD8 T cellsTumor mutation burdenIndependent validation cohortNegative breast cancerFisher's exact testPearson's chi-squared testChi-squared testLogistic regression modelsLuminal signaturePrimary TNBCTNBC subsetImmune subsetsClinical featuresValidation cohortWhole-genome copy numberPrimary tumorM1 macrophagesT cellsTriple-negative breast cancer: promising prognostic biomarkers currently in development
Sukumar J, Gast K, Quiroga D, Lustberg M, Williams N. Triple-negative breast cancer: promising prognostic biomarkers currently in development. Expert Review Of Anticancer Therapy 2021, 21: 135-148. PMID: 33198517, PMCID: PMC8174647, DOI: 10.1080/14737140.2021.1840984.Peer-Reviewed Original ResearchConceptsTriple-negative breast cancerHuman epidermal growth factor receptor 2Vascular endothelial growth factorHomologous recombination deficiencyBreast cancerEpidermal growth factor receptorGrowth factor receptorPredictive biomarkersTreatment optionsFibroblast growth factor receptorManagement of TNBCEpidermal growth factor receptor 2Factor receptorGrowth factor receptor 2PI3K/Akt/mTORLimited treatment optionsNTRK gene fusionsFactor receptor 2Akt/mTOREndothelial growth factorCell-free DNAAntibody-drug conjugatesClinical outcomesImmune biomarkersPoor prognosis
2018
An Evaluation of Factors Predicting Diet Quality among Cancer Patients
Kane K, Ilic S, Paden H, Lustberg M, Grenade C, Bhatt A, Diaz D, Beery A, Hatsu I. An Evaluation of Factors Predicting Diet Quality among Cancer Patients. Nutrients 2018, 10: 1019. PMID: 30081543, PMCID: PMC6116020, DOI: 10.3390/nu10081019.Peer-Reviewed Original ResearchConceptsHealthy Eating Index 2010Higher HEI scoresCancer patientsHEI scoresDiet qualityMean HEI scoreLower HEI scoresDisease-related factorsDisease-related characteristicsOverall HEI scoreHigher diet qualityTypes of cancerGeneral education diplomaPredictive factorsCancer mortalityPoor-quality dietLower riskPatientsHealthcare providersSpecific demographic characteristicsHigh school degreeDemographic characteristicsOne-way ANOVAScoresCancer
2017
Genomic risk prediction of aromatase inhibitor‐related arthralgia in patients with breast cancer using a novel machine‐learning algorithm
Reinbolt R, Sonis S, Timmers C, Fernández‐Martínez J, Cernea A, de Andrés‐Galiana E, Hashemi S, Miller K, Pilarski R, Lustberg M. Genomic risk prediction of aromatase inhibitor‐related arthralgia in patients with breast cancer using a novel machine‐learning algorithm. Cancer Medicine 2017, 7: 240-253. PMID: 29168353, PMCID: PMC5773952, DOI: 10.1002/cam4.1256.Peer-Reviewed Original Research
2015
Gene expression patterns through oral squamous cell carcinoma development: PD-L1 expression in primary tumor and circulating tumor cells
Oliveira-Costa J, de Carvalho A, da Silveira G, Amaya P, Wu Y, Park K, Gigliola M, Lustberg M, Buim M, Ferreira E, Kowalski L, Chalmers J, Soares F, Carraro D, Ribeiro-Silva A. Gene expression patterns through oral squamous cell carcinoma development: PD-L1 expression in primary tumor and circulating tumor cells. Oncotarget 2015, 6: 20902-20920. PMID: 26041877, PMCID: PMC4673238, DOI: 10.18632/oncotarget.3939.Peer-Reviewed Original ResearchMeSH KeywordsAdaptor Proteins, Signal TransducingAdultAgedAged, 80 and overAutoimmune DiseasesB7-H1 AntigenBiomarkers, TumorCarcinoma, Squamous CellCohort StudiesCytoplasmDNA-Binding ProteinsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHomeodomain ProteinsHumansKaplan-Meier EstimateLymphatic MetastasisMaleMiddle AgedMouth NeoplasmsNeoplastic Cells, CirculatingOligonucleotide Array Sequence AnalysisPrognosisProportional Hazards ModelsTissue BanksTreatment OutcomeConceptsOral squamous cell carcinomaPD-L1Tumor sizePerineural invasionPrimary tumorAdvanced oral squamous cell carcinomaTumor cellsSquamous cell carcinoma developmentStrong cytoplasmatic expressionPD-L1 positivityDisease-specific survivalOral squamous cell carcinoma developmentPD-L1 expressionIndependent prognostic factorLymph node metastasisT cell activitySquamous cell carcinomaSub-classify patientsSpecific survivalNode metastasisPD-1Prognostic factorsPoor prognosisAutoimmune diseasesCell carcinoma
2014
Heterogeneous atypical cell populations are present in blood of metastatic breast cancer patients
Lustberg M, Balasubramanian P, Miller B, Garcia-Villa A, Deighan C, Wu Y, Carothers S, Berger M, Ramaswamy B, Macrae E, Wesolowski R, Layman R, Mrozek E, Pan X, Summers T, Shapiro C, Chalmers J. Heterogeneous atypical cell populations are present in blood of metastatic breast cancer patients. Breast Cancer Research 2014, 16: r23. PMID: 24602188, PMCID: PMC4053256, DOI: 10.1186/bcr3622.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAntigens, CDAntigens, Differentiation, MyelomonocyticAntigens, NeoplasmBiomarkers, TumorBreast NeoplasmsCell Adhesion MoleculesCell Line, TumorEpithelial Cell Adhesion MoleculeErbB ReceptorsFemaleFlow CytometryHumansImmunohistochemistryKeratin-18Keratin-19Keratin-8Leukocyte Common AntigensMCF-7 CellsMicroscopy, ConfocalMiddle AgedNeoplasm MetastasisNeoplastic Cells, CirculatingPrognosisProspective StudiesVimentinConceptsMetastatic breast cancerBreast cancer patientsBlood samplesCancer patientsBreast cancerMetastatic breast cancer patientsPatient samplesMultiparametric flow cytometry analysisAtypical cell populationNumber of CKPresent prospective trialWorse overall survivalTumor-associated macrophagesCell populationsPan-hematopoietic marker CD45Confocal microscopyEpidermal growth factor receptorEpithelial cell adhesion moleculeNormal control samplesCell surface markersRole of EpCAMFlow cytometry analysisGrowth factor receptorOverall survivalProspective trial
2012
Microcirculatory fraction (MCFI) as a potential imaging marker for tumor heterogeneity in breast cancer
Yang X, Mrozek E, Lustberg M, Jia G, Sammet S, Sammet C, Shapiro C, Knopp M. Microcirculatory fraction (MCFI) as a potential imaging marker for tumor heterogeneity in breast cancer. Magnetic Resonance Imaging 2012, 30: 1059-1067. PMID: 22884756, PMCID: PMC3645932, DOI: 10.1016/j.mri.2012.04.026.Peer-Reviewed Original ResearchConceptsPotential imaging markerPathologic responseBreast cancerTumor heterogeneityImaging markerHER-2 negative breast cancerImaging biomarkersVolumetric biomarkersCombination neoadjuvant chemotherapyCurrent imaging studiesGood predictive biomarkerNegative breast cancerTherapeutic response assessmentNovel imaging biomarkersNeoadjuvant chemotherapyRetrospective studyPredictive biomarkersNovel biomarkersResponse assessmentHeterogeneous diseaseEarly changesImaging studiesBiomarkersCancerCellular composition