2023
More than bad luck: Cancer and aging are linked to replication-driven changes to the epigenome
Minteer C, Thrush K, Gonzalez J, Niimi P, Rozenblit M, Rozowsky J, Liu J, Frank M, McCabe T, Sehgal R, Higgins-Chen A, Hofstatter E, Pusztai L, Beckman K, Gerstein M, Levine M. More than bad luck: Cancer and aging are linked to replication-driven changes to the epigenome. Science Advances 2023, 9: eadf4163. PMID: 37467337, PMCID: PMC10355820, DOI: 10.1126/sciadv.adf4163.Peer-Reviewed Original ResearchConceptsStem cell divisionImmortalized human cellsTissue-specific cancer riskTumorigenic stateCell divisionDNA methylationEpigenetic changesAge-related accumulationHuman cellsMultiple tissuesSomatic mutationsClinical tissuesTissue differencesEpigenomeCellsTissueNormal tissuesMethylationMutationsReplicationNormal breast tissueSignaturesVitroAccumulationDivision
2022
Intratumour heterogeneity, from hypothesis to the clinic
Shan NL, Kahn A, Pusztai L. Intratumour heterogeneity, from hypothesis to the clinic. British Journal Of Cancer 2022, 128: 459-460. PMID: 36216884, PMCID: PMC9938204, DOI: 10.1038/s41416-022-02008-w.Commentaries, Editorials and LettersRisk-adapted modulation through de-intensification of cancer treatments: an ESMO classification
Trapani D, Franzoi M, Burstein H, Carey L, Delaloge S, Harbeck N, Hayes D, Kalinsky K, Pusztai L, Regan M, Sestak I, Spanic T, Sparano J, Jezdic S, Cherny N, Curigliano G, Andre F. Risk-adapted modulation through de-intensification of cancer treatments: an ESMO classification. Annals Of Oncology 2022, 33: 702-712. PMID: 35550723, DOI: 10.1016/j.annonc.2022.03.273.Peer-Reviewed Original ResearchConceptsNon-inferiority clinical trialClinical trialsESMO classificationCancer treatmentPrecision Medicine Working GroupSingle-arm studyHealth system burdenOngoing clinical trialsShorter treatment durationLevel of evidenceEvidence-based criteriaQuality of lifePublic health expertsMedicine Working GroupStandard regimensCohort investigationWorking GroupCumulative doseTreatment modalitiesTreatment modulationPatient representativesTreatment durationIntermittent scheduleFinancial toxicityEvidence of reductionCancer Relevance of Human Genes
Qing T, Mohsen H, Cannataro VL, Marczyk M, Rozenblit M, Foldi J, Murray M, Townsend J, Kluger Y, Gerstein M, Pusztai L. Cancer Relevance of Human Genes. Journal Of The National Cancer Institute 2022, 114: 988-995. PMID: 35417011, PMCID: PMC9275765, DOI: 10.1093/jnci/djac068.Peer-Reviewed Original ResearchConceptsCore cancer genesHuman genesFunctional importanceSomatic mutation frequencySelection pressureGene/protein networksCancer genesHigher somatic mutation frequencyNegative selection pressureGene-gene interaction networksMutation frequencyProtein-truncating variantsGenomic contextCell viabilityGenes decreasesCancer Genome AtlasInteraction networksProtein networkCancer relevanceCancer cell viabilityCell survivalGenesCancer biologyGenome AtlasSearch tools
2021
Data augmentation based on waterfall plots to increase value of response data generated by small single arm Phase II trials
Han G, Pusztai L, Hatzis C. Data augmentation based on waterfall plots to increase value of response data generated by small single arm Phase II trials. Contemporary Clinical Trials 2021, 110: 106589. PMID: 34634476, DOI: 10.1016/j.cct.2021.106589.Peer-Reviewed Original ResearchNetwork propagation-based prioritization of long tail genes in 17 cancer types
Mohsen H, Gunasekharan V, Qing T, Seay M, Surovtseva Y, Negahban S, Szallasi Z, Pusztai L, Gerstein MB. Network propagation-based prioritization of long tail genes in 17 cancer types. Genome Biology 2021, 22: 287. PMID: 34620211, PMCID: PMC8496153, DOI: 10.1186/s13059-021-02504-x.Peer-Reviewed Original ResearchConceptsCancer-relevant genesTail genesMobility genesNetwork propagation approachGenome-wide RNAiNetwork propagation methodCancer developmentPotential functional impactCancer cell survivalNew genesUnreported genesFunctional screeningCancer typesFunctional importanceCancer genesNovel potential therapeutic targetDriver genesCell survivalGenesMutational distributionsBiological interactionsPotential therapeutic targetFunctional impactGenomic alterationsInfrequent mutationsOptimal Management for Residual Disease Following Neoadjuvant Systemic Therapy
Foldi J, Rozenblit M, Park TS, Knowlton CA, Golshan M, Moran M, Pusztai L. Optimal Management for Residual Disease Following Neoadjuvant Systemic Therapy. Current Treatment Options In Oncology 2021, 22: 79. PMID: 34213636, DOI: 10.1007/s11864-021-00879-4.Peer-Reviewed Original ResearchConceptsPathologic complete responseResidual cancerClinical trialsAdjuvant therapyExcellent long-term disease-free survivalLong-term disease-free survivalAxillary lymph node dissectionHuman epidermal growth factor receptor 2Early-stage breast cancerEpidermal growth factor receptor 2Post-mastectomy breastSystemic adjuvant therapyInternal mammary nodesLymph node dissectionNeoadjuvant systemic therapyDisease-free survivalGrowth factor receptor 2Minimal residual disease monitoringRecurrence-free survivalType of surgeryPivotal clinical trialsOngoing clinical trialsFactor receptor 2Residual disease monitoringAccurate prognostic estimatesThe Way of the Future: Personalizing Treatment Plans Through Technology.
Liefaard MC, Lips EH, Wesseling J, Hylton NM, Lou B, Mansi T, Pusztai L. The Way of the Future: Personalizing Treatment Plans Through Technology. American Society Of Clinical Oncology Educational Book 2021, 41: 1-12. PMID: 33793316, DOI: 10.1200/edbk_320593.Peer-Reviewed Original ResearchConceptsComputer-aided solutionDiverse immune response of DNA damage repair-deficient tumors
Qing T, Jun T, Lindblad KE, Lujambio A, Marczyk M, Pusztai L, Huang KL. Diverse immune response of DNA damage repair-deficient tumors. Cell Reports Medicine 2021, 2: 100276. PMID: 34095878, PMCID: PMC8149377, DOI: 10.1016/j.xcrm.2021.100276.Peer-Reviewed Original ResearchConceptsCancer typesDDR-deficient tumorsImmune checkpoint inhibitorsHigh neoantigen loadDifferent immune phenotypesDiverse immune responsesAdaptive immune markersRepair-deficient tumorsDDR deficiencyCheckpoint inhibitorsImmunotherapy outcomesDNA damage repair deficiencyImmune infiltratesImmune markersNeoantigen loadSurvival outcomesImmune phenotypeTumor neoantigensImmune responseAnimal modelsGenomic biomarkersGermline mutationsPathway mutationsTumorsRepair deficiencyTargeted RNAseq assay incorporating unique molecular identifiers for improved quantification of gene expression signatures and transcribed mutation fraction in fixed tumor samples
Fu C, Marczyk M, Samuels M, Trevarton AJ, Qu J, Lau R, Du L, Pappas T, Sinn BV, Gould RE, Pusztai L, Hatzis C, Symmans WF. Targeted RNAseq assay incorporating unique molecular identifiers for improved quantification of gene expression signatures and transcribed mutation fraction in fixed tumor samples. BMC Cancer 2021, 21: 114. PMID: 33541297, PMCID: PMC7860187, DOI: 10.1186/s12885-021-07814-8.Peer-Reviewed Original ResearchConceptsPolymerase chain reactionParaffin-embedded tumor tissue samplesConcordance correlation coefficientFresh frozenFFPE samplesPrimary breast cancerMulti-gene signatureTumor tissue samplesActivating point mutationMutant allele fractionReverse transcriptionKey breast cancer genesGene expression signaturesBreast cancer genesPIK3CA mutationsBackgroundOur objectiveBreast cancerWhole transcriptome RNAseqTumor samplesLin's concordance correlation coefficientHormone receptorsFF samplesTissue samplesExpression signaturesChain reactionExpected Medium- and Long-Term Impact of the COVID-19 Outbreak in Oncology
Onesti CE, Tagliamento M, Curigliano G, Harbeck N, Bartsch R, Wildiers H, Tjan-Heijnen V, Martin M, Rottey S, Generali D, Campone M, Cristofanilli M, Pusztai L, Peeters M, Berchem G, Cortes J, Ruhstaller T, Ciruelos E, Rugo HS, Jerusalem G. Expected Medium- and Long-Term Impact of the COVID-19 Outbreak in Oncology. JCO Global Oncology 2021, 7: go.20.00589. PMID: 33529077, PMCID: PMC8081548, DOI: 10.1200/go.20.00589.Peer-Reviewed Original ResearchConceptsMedical oncologistsCOVID-19 positive patientsCOVID-19 outbreakUse of telemedicineClinical trial activityAffected modalityPalliative treatmentOncology unitLong-term impactNational registryPostacute phaseClinical activityMultidisciplinary meetingOncologic activityLocal registryHealthcare staffTreatment adaptationPatientsEarly cessationTrial activityHealthcare systemCOVID-19 pandemicOncologistsRegistrySignificant reduction
2020
Germline variant burden in cancer genes correlates with age at diagnosis and somatic mutation burden
Qing T, Mohsen H, Marczyk M, Ye Y, O’Meara T, Zhao H, Townsend JP, Gerstein M, Hatzis C, Kluger Y, Pusztai L. Germline variant burden in cancer genes correlates with age at diagnosis and somatic mutation burden. Nature Communications 2020, 11: 2438. PMID: 32415133, PMCID: PMC7228928, DOI: 10.1038/s41467-020-16293-7.Peer-Reviewed Original ResearchConceptsAge groupsGermline variantsSomatic mutationsLate-onset cancerEarly-onset cancersCancer hallmark genesSomatic mutation burdenMutation burdenMalignant transformationCancer genesYounger ageGermline alterationsCancerVariant burdenBurdenAverage numberHallmark genesAgeNegative correlationStrong negative correlationMutationsPatientsGroup
2018
TQuest, A Web-Based Platform to Enable Precision Medicine by Linking a Tumor’s Genetic Defects to Therapeutic Options
Gershkovich P, Platt J, Knopf J, Tasoulis MK, Shi W, Pusztai L, Hatzis C. TQuest, A Web-Based Platform to Enable Precision Medicine by Linking a Tumor’s Genetic Defects to Therapeutic Options. JCO Clinical Cancer Informatics 2018, 2: 1-13. PMID: 30652574, DOI: 10.1200/cci.17.00120.Peer-Reviewed Original ResearchConceptsData acquisition layerFull-text indexAcquisition layerUser interfaceData layersPrototype web applicationWeb-based platformWeb applicationRelevance scoresSearch enginesSource codeSoftware toolsSearch resultsInterventional clinical trialsLabel dataClinical trialsTherapeutic optionsPlatformUS FoodMolecular abnormalitiesMetastatic breast cancerPotential therapeutic optionPotential treatment optionTumor DNA sequencingWeb-based modulesReliability of Whole-Exome Sequencing for Assessing Intratumor Genetic Heterogeneity
Shi W, Ng CKY, Lim RS, Jiang T, Kumar S, Li X, Wali VB, Piscuoglio S, Gerstein MB, Chagpar AB, Weigelt B, Pusztai L, Reis-Filho JS, Hatzis C. Reliability of Whole-Exome Sequencing for Assessing Intratumor Genetic Heterogeneity. Cell Reports 2018, 25: 1446-1457. PMID: 30404001, PMCID: PMC6261536, DOI: 10.1016/j.celrep.2018.10.046.Peer-Reviewed Original ResearchA framework to rank genomic alterations as targets for cancer precision medicine: the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT)
Mateo J, Chakravarty D, Dienstmann R, Jezdic S, Gonzalez-Perez A, Lopez-Bigas N, Ng CKY, Bedard PL, Tortora G, Douillard J, Van Allen EM, Schultz N, Swanton C, André F, Pusztai L. A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT). Annals Of Oncology 2018, 29: 1895-1902. PMID: 30137196, PMCID: PMC6158764, DOI: 10.1093/annonc/mdy263.Peer-Reviewed Original ResearchConceptsESMO ScaleMolecular targetsClinical actionabilityPrecision Medicine Working GroupGenomic alterationsPrecision medicineRoutine clinical decisionEvidence-based criteriaMedicine Working GroupLack of evidencePreclinical evidenceClinical benefitClinical evidencePatient populationClassification systemClinical managementCancer precision medicineInvestigational targetsPatient managementMolecular aberrationsTumor typesClinical decisionClinical targetsAvailable evidenceEuropean Society
2017
Structural insights into POT1-TPP1 interaction and POT1 C-terminal mutations in human cancer
Chen C, Gu P, Wu J, Chen X, Niu S, Sun H, Wu L, Li N, Peng J, Shi S, Fan C, Huang M, Wong CC, Gong Q, Kumar-Sinha C, Zhang R, Pusztai L, Rai R, Chang S, Lei M. Structural insights into POT1-TPP1 interaction and POT1 C-terminal mutations in human cancer. Nature Communications 2017, 8: 14929. PMID: 28393832, PMCID: PMC5394241, DOI: 10.1038/ncomms14929.Peer-Reviewed Original ResearchMeSH KeywordsAmino Acid SequenceAnimalsConserved SequenceDNA DamageDNA Mutational AnalysisDNA RepairGenomic InstabilityHumansMiceModels, MolecularMolecular ChaperonesMutationNeoplasmsPhosphoproteinsProstaglandin-E SynthasesProtein BindingProtein Structure, SecondaryScattering, Small AngleShelterin ComplexStructure-Activity RelationshipTelomere-Binding ProteinsX-Ray DiffractionConceptsTelomerase-mediated telomere extensionHuman cancersDNA damage responseC-terminal mutationsOB foldsHuman POT1Chromosome endsGenome instabilityPOT1-TPP1Telomere extensionDamage responseStable heterodimerA-NHEJStructural insightsC-terminusInappropriate repairTPP1POT1Heart-shaped structureMissense mutationsTerminal portionMutationsDomainMutantsTelomeres
2016
Testing Violations of the Exponential Assumption in Cancer Clinical Trials with Survival Endpoints
Han G, Schell MJ, Zhang H, Zelterman D, Pusztai L, Adelson K, Hatzis C. Testing Violations of the Exponential Assumption in Cancer Clinical Trials with Survival Endpoints. Biometrics 2016, 73: 687-695. PMID: 27669414, PMCID: PMC6093291, DOI: 10.1111/biom.12590.Peer-Reviewed Original ResearchPatient preferences regarding incidental genomic findings discovered during tumor profiling
Yushak ML, Han G, Bouberhan S, Epstein L, DiGiovanna MP, Mougalian SS, Sanft TB, Abu-Khalaf MM, Chung GG, Stein SM, Goldberg SB, Pusztai L, Hofstatter EW. Patient preferences regarding incidental genomic findings discovered during tumor profiling. Cancer 2016, 122: 1588-1597. PMID: 26970385, DOI: 10.1002/cncr.29951.Peer-Reviewed Original ResearchConceptsIncidental findingTumor profilingGermline variantsAmbulatory oncology clinicsMajority of patientsStandard of careTumor profiling testsOncology clinicPreventable diseaseFamily historyPatient tumorsInformation patientsPreventable illnessPatientsDisease variablesUnpreventable diseaseUncertain significanceDisclosure preferencesCancerFrequent concernTumorsIllnessProfiling testsDiseaseCurrent studyAssessing cost-utility of predictive biomarkers in oncology: a streamlined approach
Safonov A, Wang S, Gross CP, Agarwal D, Bianchini G, Pusztai L, Hatzis C. Assessing cost-utility of predictive biomarkers in oncology: a streamlined approach. Breast Cancer Research And Treatment 2016, 155: 223-234. PMID: 26749360, PMCID: PMC5990969, DOI: 10.1007/s10549-016-3677-3.Peer-Reviewed Original ResearchConceptsQuality-adjusted life yearsCost-effectiveness analysisPredictive biomarkersBiomarker-guided treatmentIncremental cost-effectiveness ratioHealth-related qualityTreatment costsCost-effectiveness ratioClinical outcomesClinical efficacyPrognostic biomarkerTraditional cost-effectiveness analysisBiomarker useLife yearsBiomarker valuesBiomarker prevalenceClinical literatureBiomarkersTreatmentState transition modelDecision analytic approachMedical utilityDecision analytic toolsCrizotinibHER2
2015
Tumor profiling and the incidentalome: patient decisions and risks
Hofstatter E, Mehra K, Yushak M, Pusztai L. Tumor profiling and the incidentalome: patient decisions and risks. Future Oncology 2015, 11: 3299-3305. PMID: 26562094, DOI: 10.2217/fon.15.260.BooksConceptsTumor profilingField of oncologyTumor DNA sequencesOncology patientsIncidental discoveryPatient educationPatient's perspectivePatient decisionOncology communityClinical implicationsPatient healthGermline mutationsCancer medicineGenetic sequencingCancer therapyTherapyPotential riskRiskHealthPatientsIncidentalomeMainstayDiseaseOncologyProfiling