Author

Katarina Mišura

Medical University of ViennaORCID 0000-0003-4914-0410Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Organism:mouse· 2 Assay:bulk RNA-seq· 1 Research Focus:cancer & tumor microenvironment· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Gerda EggeriD· 3 shared Anna MalzeriD· 2 shared Carlos Uziel Pérez MallaiD· 2 shared Gabriel WasingeriD· 2 shared Jessica KallaiD· 2 shared Kristina DraganićiD· 2 shared Raheleh Sheibani‐TezerjiiD· 2 shared Ana‐Iris SchieferiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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3 shared papersCancer Biology

Gerda EggerORCID

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3 papers

Recent·Most cited

Cancer BiologyCell Reports MethodsPeer-reviewedMar 30, 2026

Biobank of genetically defined murine prostate cancer tumoroids uncovers oncogenic pathways and drug vulnerabilities driven by PTEN-loss

Jessica Kalla, Thomas Dillinger, Zlata Pavlovicova…·Gerda Egger

This study establishes a murine tumoroid biobank to identify oncogenic pathways and drug vulnerabilities in prostate cancer, finding that PTEN loss drives cancer pathways and that specific compounds inhibit tumor growth.

1 citation

mouseorganoid / primary culture

𝕏 PostBluesky

Cancer BiologyLeukemiaPeer-reviewedApr 2, 2025

HDAC1 acts as tumor suppressor in ALK-positive anaplastic large-cell lymphoma: Implications for HDAC inhibitor therapy

Maša Zrimšek, Kristina Draganić, Anna Malzer…·Gerda Egger

This study shows HDAC1 suppresses ALK-positive lymphoma growth, but systemic HDAC inhibition can still be therapeutic.

8 citations

mouseexperimental assay

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BioinformaticsbioRxivPreprintMar 2, 2023

Identification of Biomarkers and Trajectories of Prostate Cancer Progression: A Bioinformatics Fusion of Weighted Correlation Network Analysis and Machine Learning

Raheleh Sheibani‐Tezerji, Carlos Uziel Pérez Malla, Gabriel Wasinger…·Gerda Egger

This study identifies biomarkers and trajectories of prostate cancer progression using bioinformatics fusion of weighted correlation network analysis and machine learning, finding the EZH2-TROAP axis as a key trajectory and 58 validated biomarkers.

1 citation

humanbulk RNA-seq

𝕏 PostBluesky