Adjunct faculty typically have an academic or research appointment at another institution and contribute or collaborate with one or more School of Medicine faculty members or programs.
Adjunct rank detailsMichal Marczyk, PhD
Assistant Professor AdjunctAbout
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Titles
Assistant Professor Adjunct
Biography
Michal Marczyk defended his PhD in biocybernetics and biomedical engineering in 2013 (Silesian University of Technology). His area of research interests focuses on bioinformatics and exploratory analysis of biological and medical data in cancer research. As part of his doctoral thesis, he created tools for analysis of DNA microarrays and MALDI-ToF mass spectra. Then he worked on new techniques for processing, detection and modeling of protein spots on 2D electrophoresis gels, and he was involved in the analysis of clinical data of patients with various cancers in terms of seeking disease biomarkers or negative effects of therapy. Currently, he is working on the analysis of data from sequencing of human genome (ATAC-seq, Bisulfite seq., whole genome seq.) and transcriptome (RNA-seq, single-cell RNA-seq) in translational research in oncology to search for drug candidates and improve cancer therapies.
Michal Marczyk is a co-author of 21 papers published in impact factor journals, 17 publications in other journals and over 60 conference abstracts mainly on international meetings. Michal Marczyk is currently receiving a scholarship from the Minister of Science and Higher Education of Poland for outstanding young scientists. He was also awarded the DoktoRIS scholarship from the program for an innovative Silesia co-financed by the EU. During doctoral studies he received a scholarship for the best PhD students.
Appointments
Medical Oncology and Hematology
Assistant Professor AdjunctPrimary
Other Departments & Organizations
- Internal Medicine
- Medical Oncology and Hematology
- Pusztai Lab
Education & Training
- Assistant Professor
- Slesian University of Technology (2017)
- Research Assistant
- Silesian University of Technology (2014)
- Young specialist in biostatistics
- Medical University of Gdansk (2013)
- PhD
- Silesian University of Technology (2013)
- MSc
- Silesian University of Technology (2008)
Research
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Overview
Medical Research Interests
ORCID
0000-0003-2508-5736
Research at a Glance
Yale Co-Authors
Publications Timeline
Research Interests
Lajos Pusztai, MD, DPhil
Kim Blenman, PhD, MS
Andrea Silber, MD
David Rimm, MD, PhD
Mariya Rozenblit, MD
Naing Lin Shan, MBBS, PhD, MS
Algorithms
Computational Biology
Publications
2025
A comprehensive evaluation of diversity measures for TCR repertoire profiling
Mika J, Polanska A, Blenman K, Pusztai L, Polanska J, Candéias S, Marczyk M. A comprehensive evaluation of diversity measures for TCR repertoire profiling. BMC Biology 2025, 23: 133. PMID: 40369611, PMCID: PMC12080070, DOI: 10.1186/s12915-025-02236-5.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsHSPA2 influences the differentiation and production of immunomodulatory mediators in human immortalized epidermal keratinocyte lines
Gogler A, Wilk A, Sojka D, Adamiec-Organiściok M, Matysiak N, Kania D, Wiecha K, Małusecka E, Cortez A, Zamojski D, Marczyk M, Mazurek A, Oziębło S, Scieglinska D. HSPA2 influences the differentiation and production of immunomodulatory mediators in human immortalized epidermal keratinocyte lines. Cell Death & Disease 2025, 16: 344. PMID: 40287440, PMCID: PMC12033329, DOI: 10.1038/s41419-025-07565-5.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsChaperone proteinsKeratinocyte differentiationCell type-specific expression patternsHomologous chaperone proteinsEpidermal keratinocyte differentiationInterferon-mediated signalingInterferon-stimulated genesControl proteostasisExtracellular secretionTranscriptome analysisMolecular machineryKeratinocyte differentiation markersHSPA2Upper epidermal layersDifferentiation defectsExpression patternsSomatic cellsMolecular networksPro-inflammatory IL-6 cytokinePotential therapeutic targetFunctional analysisSecretion of IL-6Keratinocyte linePathogenic factorsReduced levelsEPIIC: Edge-Preserving Method Increasing Nuclei Clarity for Compression Artifacts Removal in Whole-Slide Histopathological Images
Merta J, Marczyk M. EPIIC: Edge-Preserving Method Increasing Nuclei Clarity for Compression Artifacts Removal in Whole-Slide Histopathological Images. Applied Sciences 2025, 15: 4450. DOI: 10.3390/app15084450.Peer-Reviewed Original ResearchConceptsEdge-preserving filtering methodCompression artifact removalCompression artifactsArtifact removalHistopathological imagesDeep learning-based solutionsCompression quality factorNatural image datasetsLearning-based solutionLossy compression methodsNuclei segmentation taskImage quality measuresFiltering methodImage qualityWhole-slide histopathology imagesJPEG algorithmPixel blocksNatural imagesSegmentation taskImage datasetsImage enhancementMap estimationNeural networkSegmentation resultsCompression methodSearching for the Ideal Recipe for Preparing Synthetic Data in the Multi-Object Detection Problem
Staniszewski M, Kempski A, Marczyk M, Socha M, Foszner P, Cebula M, Labus A, Cogiel M, Golba D. Searching for the Ideal Recipe for Preparing Synthetic Data in the Multi-Object Detection Problem. Applied Sciences 2025, 15: 354. DOI: 10.3390/app15010354.Peer-Reviewed Original ResearchCitationsConceptsSynthetic dataUtilization of synthetic dataSynthetic data generation methodAdvancement of deep learning methodsSynthetic data generation techniquesReal-world datasetsLevel of photorealismDeep learning methodsDetection methodData generation techniquesData generation methodEnhanced detection methodNetwork trainingClassification qualityDetection metricsDetection problemLearning methodsTraining datasetTraining processGeneration methodData quantityGeneration techniqueMulti-objectiveTraining methodsDatasetPost-Processing of Thresholding or Deep Learning Methods for Enhanced Tissue Segmentation of Whole-Slide Histopathological Images
Marczyk M, Wrobel A, Merta J, Polanska J. Post-Processing of Thresholding or Deep Learning Methods for Enhanced Tissue Segmentation of Whole-Slide Histopathological Images. 2025, 229-238. DOI: 10.5220/0013174700003911.Peer-Reviewed Original ResearchCitationsGenomic alterations in normal breast tissues preceding breast cancer diagnosis
Dai J, Rozenblit M, Li X, Shan N, Wang Y, Mane S, Marczyk M, Pusztai L. Genomic alterations in normal breast tissues preceding breast cancer diagnosis. Breast Cancer Research 2025, 27: 60. PMID: 40264151, PMCID: PMC12013151, DOI: 10.1186/s13058-025-02018-5.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsHistologically normal breast tissueSomatic mutationsNormal breast tissueGenomic alterationsBreast tissuePre-DiagnosisMethodsWhole exome sequencingCancer diagnosisCancer predisposition genesCOSMIC signature 3Breast cancerCancer hallmark genesBreast tissue of womenBreast cancer diagnosisEvading growth suppressorsVariant burdenMutational signature analysisRegulatory genesAffected genesExome sequencingGermline variantsTissue of womenTissues adjacent to cancerDNA repairGenomic instability
2024
Hormone Receptor-Positive HER2-Negative/MammaPrint High-2 Breast Cancers Closely Resemble Triple-Negative Breast Cancers.
Rios-Hoyo A, Xiong K, Dai J, Yau C, Marczyk M, Garcia-Milian R, Wolf D, Huppert L, Nanda R, Hirst G, Cobain E, van 't Veer L, Esserman L, Pusztai L. Hormone Receptor-Positive HER2-Negative/MammaPrint High-2 Breast Cancers Closely Resemble Triple-Negative Breast Cancers. Clinical Cancer Research 2024, 31: 403-413. PMID: 39561272, PMCID: PMC11747811, DOI: 10.1158/1078-0432.ccr-24-1553.Peer-Reviewed Original ResearchCitationsAltmetricConceptsPathological complete responseEvent-free survivalBreast cancerHER2 negative breast cancerHormone receptor-positive/HER2-negativePathologic complete response ratePrognostic risk categoriesTN breast cancerNegative breast cancerGene set analysisExpression of cell cycleGene expression dataLow-risk subgroupsHigh-risk groupMammaPrint assayNeoadjuvant trialsComplete responseER statusResidual cancerPrognostic groupsClinical featuresI-SPY2Prognostic assaysExpression dataTreatment strategiesMolecular adaptation to neoadjuvant immunotherapy in triple-negative breast cancer
Denkert C, Schneeweiss A, Rey J, Karn T, Hattesohl A, Weber K, Rachakonda S, Braun M, Huober J, Jank P, Sinn H, Zahm D, Felder B, Hanusch C, Teply-Szymanski J, Marmé F, Fehm T, Thomalla J, Sinn B, Stiewe T, Marczyk M, Blohmer J, van Mackelenbergh M, Schem C, Staib P, Link T, Müller V, Stickeler E, Stover D, Solbach C, Metzger-Filho O, Jackisch C, Geyer C, Fasching P, Pusztai L, Nekljudova V, Untch M, Loibl S. Molecular adaptation to neoadjuvant immunotherapy in triple-negative breast cancer. Cell Reports Medicine 2024, 5: 101825. PMID: 39566464, PMCID: PMC11604547, DOI: 10.1016/j.xcrm.2024.101825.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsTriple-negative breast cancerPositive prognostic factorPrognostic factorsBreast cancerCombination of durvalumabImmune-suppressive microenvironmentResistance to immunotherapyCombination of immunotherapyProliferation-related gene expressionAnti-angiogenic therapyClinical trial cohortPoor therapy responseGene expressionStromal gene expressionDurvalumab armNeoadjuvant immunotherapyImmunotherapy resistanceTumor biopsiesImmunotherapy responseTherapy responseAlteration of gene expressionImmunotherapyDurvalumabTrial cohortStromal reorganizationComparative analysis of Ficoll-Hypaque and CytoLyt techniques for blood removal in breast cancer malignant effusions: effects on RNA quality and sequencing outcomes
Sura G, Tran K, Trevarton A, Marczyk M, Fu C, Du L, Qu J, Lau R, Tasto A, Gould R, Tinnirello A, Sinn B, Pusztai L, Hatzis C, Symmans W. Comparative analysis of Ficoll-Hypaque and CytoLyt techniques for blood removal in breast cancer malignant effusions: effects on RNA quality and sequencing outcomes. Journal Of The American Society Of Cytopathology 2024, 14: 91-101. PMID: 39668068, DOI: 10.1016/j.jasc.2024.11.001.Peer-Reviewed Original ResearchAltmetricConceptsRNA integrity numberRNA qualityRNA-seqMeasurement of gene expressionRNA-seq analysisMetastatic breast cancerFicoll-Hypaque methodDensity gradient enrichmentSequence dataRead-basedVariant detectionMalignant effusionsCytospin slidesFresh frozen samplesRNA fragmentsTranscript abundanceSequencing outcomesSequencing methodsBreast cancerRNA sequencingFicoll-HypaqueUMI-basedGene expressionRNAMalignant effusion specimensTrends in breast cancer–specific death by clinical stage at diagnoses between 2000 and 2017
Marczyk M, Kahn A, Silber A, Rosenblit M, Digiovanna M, Lustberg M, Pusztai L. Trends in breast cancer–specific death by clinical stage at diagnoses between 2000 and 2017. Journal Of The National Cancer Institute 2024, 117: 287-295. PMID: 39348186, DOI: 10.1093/jnci/djae241.Peer-Reviewed Original ResearchCitationsAltmetricConceptsBreast cancer-specific deathCancer-specific deathBreast cancerStage IAll-Cause MortalityTemporal trendsStage I/II breast cancerHormone receptor-positiveNode-negative cancersPrimary tumor typeStage I/II diseaseMetastatic breast cancerStage II cancerBilateral cancerIV cancerFemale sexIV diseaseReceptor-positiveExcellent prognosisII cancerClinical stageTumor typesTreated patientsStage IIICancer
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- November 08, 2022
Biomarkers could determine the need for chemotherapy in young patients with ER+ breast cancer
- August 11, 2022
Discoveries & Impact (August 2022)
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