2024
Phosphoenolpyruvate carboxykinase-2 (PCK2) is a therapeutic target in triple-negative breast cancer
Gunasekharan V, Lin H, Marczyk M, Rios-Hoyo A, Campos G, Shan N, Ahmed M, Umlauf S, Gareiss P, Raaisa R, Williams R, Cardone R, Siebel S, Kibbey R, Surovtseva Y, Pusztai L. Phosphoenolpyruvate carboxykinase-2 (PCK2) is a therapeutic target in triple-negative breast cancer. Breast Cancer Research And Treatment 2024, 1-15. PMID: 39177932, DOI: 10.1007/s10549-024-07462-z.Peer-Reviewed Original ResearchMetabolic fluxTriple-negative breast cancerReduced metabolic fluxMDA-MB-231 cellsCell growth in vitroEnzyme assays in vitroMDA-MB-231Potential small molecule inhibitorsPyruvate carboxylaseGrowth in vitroSmall molecule inhibitorsIn silico screeningEnzyme assaysAssay in vitroEnzymatic assayCell lines in vitroEnzyme activityGrowth inhibitory activityBT-549Breast cancerIn vitro screeningBreast cell lines in vitroPhosphoenolpyruvateSignificant growth inhibitory activityLines in vitroPassenger Location Estimation in Public Transport: Evaluating Methods and Camera Placement Impact
Marczyk M, Kempski A, Socha M, Cogiel M, Foszner P, Staniszewski M. Passenger Location Estimation in Public Transport: Evaluating Methods and Camera Placement Impact. IEEE Transactions On Intelligent Transportation Systems 2024, PP: 1-10. DOI: 10.1109/tits.2024.3434746.Peer-Reviewed Original ResearchPublic transportCase of public transportMachine learningHuman head detectionML modelsSpecialized hardware devicesDistance estimation methodPassenger bodyPassengerPerformance of ML modelsHead detectionHardware devicesOcclusion problemLocation estimationCrowd densityML methodsComputation timePlacement impactCameraDistance estimationEvaluation methodTransportEstimation methodMinibusImage analysis methodPeripheral blood immune parameters, response, and adverse events after neoadjuvant chemotherapy plus durvalumab in early-stage triple-negative breast cancer
Foldi J, Blenman K, Marczyk M, Gunasekharan V, Polanska A, Gee R, Davis M, Kahn A, Silber A, Pusztai L. Peripheral blood immune parameters, response, and adverse events after neoadjuvant chemotherapy plus durvalumab in early-stage triple-negative breast cancer. Breast Cancer Research And Treatment 2024, 1-9. PMID: 39002068, DOI: 10.1007/s10549-024-07426-3.Peer-Reviewed Original ResearchImmune-related adverse eventsTriple-negative breast cancerAssociated with pathological responsePathological complete responseNeoadjuvant chemotherapyCytokine levelsPathological responseAdverse eventsBreast cancerEarly-stage triple-negative breast cancerPatients treated with immune checkpoint inhibitorsB cell clonal expansionMeasured serum cytokine levelsImmune checkpoint inhibitorsGM-CSF levelsPeripheral blood cytokine levelsBlood cytokine levelsSerum cytokine levelsB cell receptorMagnetic bead panelBenjamini-Hochberg correctionSample of patientsImmunoSEQ platformCheckpoint inhibitorsComplete responseCorrelation of hormone receptor positive HER2-negative/MammaPrint high-2 breast cancer with triple negative breast cancer: Results from gene expression data from the ISPY2 trial.
Rios-Hoyo A, Xiong K, Marczyk M, García-Millán R, Wolf D, Huppert L, Nanda R, Yau C, Hirst G, van 't Veer L, Esserman L, Pusztai L. Correlation of hormone receptor positive HER2-negative/MammaPrint high-2 breast cancer with triple negative breast cancer: Results from gene expression data from the ISPY2 trial. Journal Of Clinical Oncology 2024, 42: 573-573. DOI: 10.1200/jco.2024.42.16_suppl.573.Peer-Reviewed Original ResearchGene expression dataGene expression analysisExpression dataExpressed genesExpression analysisTriple-negativeDistance analysisPathway analysisDifferential gene expression analysisCell cycle pathwayGene set enrichment analysisBreast cancerIngenuity Pathway AnalysisRate of pathological complete responseHigh-risk stage IIGlucocorticoid receptor signalingTriple negative breast cancerCycle pathwayPathological complete responseDNA repairEnrichment analysisOptimal treatment strategyNegative breast cancerI-SPY2 trialGenes
2023
Combining Low-Dose Computer-Tomography-Based Radiomics and Serum Metabolomics for Diagnosis of Malignant Nodules in Participants of Lung Cancer Screening Studies
Zyla J, Marczyk M, Prazuch W, Sitkiewicz M, Durawa A, Jelitto M, Dziadziuszko K, Jelonek K, Kurczyk A, Szurowska E, Rzyman W, Widłak P, Polanska J. Combining Low-Dose Computer-Tomography-Based Radiomics and Serum Metabolomics for Diagnosis of Malignant Nodules in Participants of Lung Cancer Screening Studies. Biomolecules 2023, 14: 44. PMID: 38254644, PMCID: PMC10813699, DOI: 10.3390/biom14010044.Peer-Reviewed Original ResearchSerum metabolomicsComputed tomography lung cancer screeningLow-dose computed tomography (LDCT) lung cancer screeningLung cancer screening studyTomography lung cancer screeningLung cancer screeningCancer screening studyLung cancer diagnosisCollected cohortCancer screeningLung cancerSerum metabolomeBenign lesionsPulmonary nodulesMetabolomic evaluationAuxiliary biomarkerLogistic regressionDiagnosisCancer diagnosisLung nodulesMalignant nodulesScreening studyPatientsRadiomicsMolecular featuresShort- and long-term effects of radiation exposure at low dose and low dose rate in normal human VH10 fibroblasts
Akuwudike P, López-Riego M, Marczyk M, Kocibalova Z, Brückner F, Polańska J, Wojcik A, Lundholm L. Short- and long-term effects of radiation exposure at low dose and low dose rate in normal human VH10 fibroblasts. Frontiers In Public Health 2023, 11: 1297942. PMID: 38162630, PMCID: PMC10755029, DOI: 10.3389/fpubh.2023.1297942.Peer-Reviewed Original ResearchConceptsLong-term effectsLow dosesDose-rate effectiveness factorLow dose rateSignificant early effectsColony forming assaysDays post irradiationEarly time pointsPooled cohortValidation cohortStrong cytotoxic effectEpidemiological dataLow doseGy/minCell growth curveSample cohortCohortThird cohortCell viability assaysRadiation exposureEarly effectsTime pointsCytotoxic effectsGene expression changesConsistent upregulationmiR-122 and miR-21 are Stable Components of miRNA Signatures of Early Lung Cancer after Validation in Three Independent Cohorts
Zyla J, Dziadziuszko R, Marczyk M, Sitkiewicz M, Szczepanowska M, Bottoni E, Veronesi G, Rzyman W, Polanska J, Widlak P. miR-122 and miR-21 are Stable Components of miRNA Signatures of Early Lung Cancer after Validation in Three Independent Cohorts. Journal Of Molecular Diagnostics 2023, 26: 37-48. PMID: 37865291, DOI: 10.1016/j.jmoldx.2023.09.010.Peer-Reviewed Original ResearchConceptsEarly lung cancerLung cancerLung cancer screening studyMiR-122MiR-21MiRNA signatureCancer screening studyLung cancer developmentPlasma miRNA signatureScreening studyIndependent cohortDiagnostic biomarkersPotential biomarkersCancer typesCohortCancer developmentCancerHealthy participantsMiR-144MiRNA panelDiagnostic potentialBiomarkersAdenocarcinomaDifferent cohortsMiRNAsEvaluation of zero counts to better understand the discrepancies between bulk and single-cell RNA-Seq platforms
Zyla J, Papiez A, Zhao J, Qu R, Li X, Kluger Y, Polanska J, Hatzis C, Pusztai L, Marczyk M. Evaluation of zero counts to better understand the discrepancies between bulk and single-cell RNA-Seq platforms. Computational And Structural Biotechnology Journal 2023, 21: 4663-4674. PMID: 37841335, PMCID: PMC10568495, DOI: 10.1016/j.csbj.2023.09.035.Peer-Reviewed Original ResearchSingle-cell RNA-seq platformsSingle-cell RNA sequencingBulk RNA-seq dataRNA-seq platformsNumber of transcriptsLow-expression genesRNA-seq dataSingle-cell dataExpression levelsLow sequencing depthDiscordant genesRNA sequencingSequencing technologiesExpression shiftsPathway levelBiological pathwaysGene levelSequencing depthTranscriptomic platformsGenesIndividual cellsSingle cellsRNA integrityPathwayCellsPre‐analytical effects on whole transcriptome and targeted RNA sequencing analysis in cytology: The effects of prolonged time in storage of effusion specimens prior to preservation
Sura G, Tran K, Fu C, Du L, Marczyk M, Gould R, Chen E, Tasto A, Tinnirello A, Symmans W. Pre‐analytical effects on whole transcriptome and targeted RNA sequencing analysis in cytology: The effects of prolonged time in storage of effusion specimens prior to preservation. Cytopathology 2023, 34: 551-561. PMID: 37712171, PMCID: PMC10592006, DOI: 10.1111/cyt.13304.Peer-Reviewed Original ResearchPathological changes or technical artefacts? The problem of the heterogenous databases in COVID-19 CXR image analysis
Socha M, Prażuch W, Suwalska A, Foszner P, Tobiasz J, Jaroszewicz J, Gruszczynska K, Sliwinska M, Nowak M, Gizycka B, Zapolska G, Popiela T, Przybylski G, Fiedor P, Pawlowska M, Flisiak R, Simon K, Walecki J, Cieszanowski A, Szurowska E, Marczyk M, Polanska J, Polanska J, Marczyk M, Prazuch W, Suwalska A, Socha M, Foszner P, Tobiasz J, Nowak M, Fiedor P, Cieszanowski A, Oronowicz-Jaskowiak A, Golebiewski B, Simon K, Sliwinska M, Rataj M, Chmielarz P, Tur A, Drabik G, Popiela T, Kozub J, Przybylski G, Kozanecka A, Szurowska E, Hildebrandt S, Krutul-Walenciej K, Baron J, Gruszczynska K, Jaroszewicz J, Piotrowski D, Walecki J, Wasilewski P, Mazur S, Flisiak R, Zapolska G, Klaude K, Rataj K, Golebiewski B, Pawlowska M, Rabiko P, Rajewski P, Gizycka B, Blewaska P, Sznajder K, Plesniak R. Pathological changes or technical artefacts? The problem of the heterogenous databases in COVID-19 CXR image analysis. Computer Methods And Programs In Biomedicine 2023, 240: 107684. PMID: 37356354, PMCID: PMC10278898, DOI: 10.1016/j.cmpb.2023.107684.Peer-Reviewed Original ResearchConceptsChest X-ray imagesNeural networkClassification neural networkDeep neural networksSuper-resolution networkImage resolutionHeterogenous databasesDiagnostic algorithm developmentSet of artifactsX-ray imagesBias discoveryNetwork architecturePoor generalizationNetwork decisionsImage dataScientific research areasAI developmentTypes of dataAlgorithm developmentImage propertiesMedical imagingNetworkResearch areaImage analysisHigh accuracyPOLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020–2021)
Suwalska A, Tobiasz J, Prazuch W, Socha M, Foszner P, Piotrowski D, Gruszczynska K, Sliwinska M, Walecki J, Popiela T, Przybylski G, Nowak M, Fiedor P, Pawlowska M, Flisiak R, Simon K, Zapolska G, Gizycka B, Szurowska E, Marczyk M, Cieszanowski A, Polanska J. POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020–2021). Scientific Data 2023, 10: 348. PMID: 37268643, PMCID: PMC10236395, DOI: 10.1038/s41597-023-02229-5.Peer-Reviewed Original ResearchConceptsLung maskChest X-ray databaseChest X-ray imagesArtificial intelligence toolsCOVID-19 detectionX-ray databaseImage collectionImage databaseX-ray imagesIntelligence toolsSegmentation solutionSegmentation modelDiagnosis methodOriginal radiographsDatasetImagesCOVID-19 diagnosisDatabaseHealthcare systemMaskMedical assistanceSmall numberLung areaSetToolAssessment of stained direct cytology smears of breast cancer for whole transcriptome and targeted messenger RNA sequencing
Marczyk M, Fu C, Lau R, Du L, Trevarton A, Sinn B, Gould R, Pusztai L, Hatzis C, Symmans W. Assessment of stained direct cytology smears of breast cancer for whole transcriptome and targeted messenger RNA sequencing. Cancer Cytopathology 2023, 131: 289-299. PMID: 36650408, PMCID: PMC10614161, DOI: 10.1002/cncy.22679.Peer-Reviewed Original ResearchConceptsCytology smearsBreast cancerConcordance correlation coefficientTumor tissue samplesParaffin-embedded sectionsClinical diagnostic proceduresSurgical resectionRNA sequencingTumor stromaCytologic specimensDiagnostic proceduresLin's concordance correlation coefficientPapanicolaou stainCancerTissue samplesDNA mutation testingSmearsSimilar concordanceTranscriptome RNA-SeqDiagnostic cytologyAllele fractionExpression levelsRNA-seqExpression of genesGene expression levelsChapter 3 Single-cell transcriptomics
Marczyk M, Kujawa T, Papiez A, Polanska J. Chapter 3 Single-cell transcriptomics. 2023, 67-84. DOI: 10.1016/b978-0-323-91810-7.00015-7.ChaptersSingle-cell transcriptomicsSingle-cell technologiesCell trajectory inferenceGene expression dataSimilar cell typesTranscriptional signalsCancer cell line dataRNAseq dataGene expressionCellular heterogeneitySequencing platformsBreast cancer cell line dataExpression dataCell line dataGroups of cellsTrajectory inferenceCell typesIndividual cellsMolecular characteristicsProper processingCellsTranscriptomicsGenesExpressionCertain steps
2022
Molecular differences between younger versus older ER-positive and HER2-negative breast cancers
Qing T, Karn T, Rozenblit M, Foldi J, Marczyk M, Shan N, Blenman K, Holtrich U, Kalinsky K, Meric-Bernstam F, Pusztai L. Molecular differences between younger versus older ER-positive and HER2-negative breast cancers. Npj Breast Cancer 2022, 8: 119. PMID: 36344517, PMCID: PMC9640562, DOI: 10.1038/s41523-022-00492-0.Peer-Reviewed Original ResearchBreast cancerYounger patientsHER2-negative breast cancerNode-positive breast cancerNode-negative diseaseSame clinical featuresHigh mutation burdenLower mRNA expressionAdjuvant chemotherapyMicroarray cohortTAILORx trialOvarian suppressionOlder patientsPatient ageClinical featuresProliferation-related gene expressionScore 0Mutation burdenCopy number gainsOlder womenGATA3 mutationsAge groupsGene signatureMRNA expressionChemotherapyInfluence of single-cell RNA sequencing data integration on the performance of differential gene expression analysis
Kujawa T, Marczyk M, Polanska J. Influence of single-cell RNA sequencing data integration on the performance of differential gene expression analysis. Frontiers In Genetics 2022, 13: 1009316. PMID: 36386846, PMCID: PMC9663917, DOI: 10.3389/fgene.2022.1009316.Peer-Reviewed Original ResearchMolecular testing opportunities on cytology effusion specimens: the pre-analytic effects of various body fluid cytology preparation methods on RNA extraction quality and targeted sequencing
Sura G, Tran K, Fu C, Du L, Marczyk M, Martinez Y, Tinnirello A, Gould R, Lau R, Symmans W. Molecular testing opportunities on cytology effusion specimens: the pre-analytic effects of various body fluid cytology preparation methods on RNA extraction quality and targeted sequencing. Journal Of The American Society Of Cytopathology 2022, 12: 10-19. PMID: 36270909, PMCID: PMC10644714, DOI: 10.1016/j.jasc.2022.09.003.Peer-Reviewed Original ResearchConceptsCell blocksCarnoy's solutionDiff-QuikFF samplesCytology laboratoryFFPE cell blocksMultigene expression signaturesConcordance correlation coefficientCell block sectionsParaffin-embedded sectionsMalignant effusionsEffusion specimensMolecular subtypesSurePath samplesCytospin preparationsCytologic methodsCytologic samplesSurePath preparationsDiagnostic approachClinical researchRNA sequencing analysisExpression signaturesHigh concordanceBlock sectionsFrozen cell pelletsTumor immune microenvironment of self-identified African American and non-African American triple negative breast cancer
Marczyk M, Qing T, O’Meara T, Yagahoobi V, Pelekanou V, Bai Y, Reisenbichler E, Cole KS, Li X, Gunasekharan V, Ibrahim E, Fanucci K, Wei W, Rimm DL, Pusztai L, Blenman KRM. Tumor immune microenvironment of self-identified African American and non-African American triple negative breast cancer. Npj Breast Cancer 2022, 8: 88. PMID: 35869114, PMCID: PMC9307813, DOI: 10.1038/s41523-022-00449-3.Peer-Reviewed Original ResearchTumor immune microenvironmentImmune microenvironmentTriple-negative breast cancer tissuesTriple-negative breast cancerAfrican AmericansImmune checkpoint inhibitorsTumor mutation burdenNegative breast cancerBreast cancer tissuesImmune-related pathwaysStromal TILsCheckpoint inhibitorsImmune exclusionClinical outcomesPD-L1Self-identified African AmericansCancer patientsImmune infiltrationBreast cancerMutation burdenCancer tissuesPredictive signatureMRNA expressionTherapeutic agentsPatientsQuantifying Spatial Heterogeneity of Tumor-Infiltrating Lymphocytes to Predict Survival of Individual Cancer Patients
Suwalska A, Zientek L, Polanska J, Marczyk M. Quantifying Spatial Heterogeneity of Tumor-Infiltrating Lymphocytes to Predict Survival of Individual Cancer Patients. Journal Of Personalized Medicine 2022, 12: 1113. PMID: 35887610, PMCID: PMC9317291, DOI: 10.3390/jpm12071113.Peer-Reviewed Original ResearchInvestigating Sources of Zeros in 10× Single-Cell RNAseq Data
Slowik H, Zyla J, Marczyk M. Investigating Sources of Zeros in 10× Single-Cell RNAseq Data. Lecture Notes In Computer Science 2022, 13347: 71-80. DOI: 10.1007/978-3-031-07802-6_6.Peer-Reviewed Original ResearchSingle-cell levelSingle-cell RNA sequencingSingle-cell RNAseq dataNumber of transcriptsMulti-omics dataGene expression estimatesRibosomal genesRNA sequencingExpression profilingEnrichment analysisRNAseq dataBiological pathwaysSequencing platformsExpression dataGenesExpression estimatesIndividual cellsBreast cancer cell linesCancer cell linesCell linesSingle experimentLow mappabilityTranscriptsSequencingProfilingFinding Significantly Enriched Cells in Single-Cell RNA Sequencing by Single-Sample Approaches
Mrukwa A, Marczyk M, Zyla J. Finding Significantly Enriched Cells in Single-Cell RNA Sequencing by Single-Sample Approaches. Lecture Notes In Computer Science 2022, 13347: 33-44. DOI: 10.1007/978-3-031-07802-6_3.Peer-Reviewed Original Research