Author

Vincenzo Cerullo

University of HelsinkiORCID 0000-0003-4901-3796Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:bulk RNA-seq· 2 Approach:deep learning· 2 Research Focus:drug response / drug discovery· 2 Assay:imaging· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1

Frequent Co-Authors

Antti Sakari RannikkoiD· 2 shared Michaela FeodoroffiD· 2 shared Mikaela GrönholmiD· 2 shared Vilja M. PietiäineniD· 2 shared Ada JunqueraiD· 1 shared Alba MontedeocaiD· 1 shared Aleksandra ShabanovaiD· 1 shared Anna Serafia NylundiD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 23 mutual co-author links

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2 shared papersCancer Biology

Antti Sakari RannikkoORCID

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3 papers

Recent·Most cited

Cancer BiologybioRxivPreprintJul 9, 2026

Site-Dependent Decoupling of Drug-Biomarker Associations in Clear Cell Renal Cell Carcinoma Revealed by Functional Profiling of Patient-Derived Cell Models

Michaela Feodoroff, Tamara J. Luck, Romika Kumari…·Vilja M. Pietiäinen

The paper identifies site-dependent drug-biomarker associations in ccRCC using patient-derived models and multi-omic data, revealing discrepancies between genomic predictions and functional drug responses.

2 citations

humanbulk RNA-seq

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Cancer BiologyCancer DiscoveryPeer-reviewedFeb 9, 2026

✦ In-depth digest

Single-cell spatial atlas of high-grade serous ovarian cancer unveils MHC class II as a key driver of spatial tumor ecosystems and clinical outcomes

Fernando Pérez‐Villatoro, Aleksandra Shabanova, Lilian van Wagensveld…·Anniina Färkkilä

Cyclic immunofluorescence of 265 high-grade serous ovarian carcinomas and random-forest feature ranking identify cancer-cell MHC-II as an adjusted predictor of longer survival marking immune-activated tumor-stroma hotspots.

10 citationstop 1%

humanimaging

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Cancer BiologybioRxivPreprintSep 8, 2024

MorphoNavigator-3D: Generalizable single-cell phenotyping of cancer spheroids using Bayesian-optimized deep-learning workflows

Isabel Mogollón, Michaela Feodoroff, Anna Serafia Nylund…·Lassi Paavolainen

MorphoNavigator-3D enables automated, annotation-free single-cell analysis of 3D tumor-immune co-cultures, revealing drug-induced phenotypes and their biological relevance.

1 citation

humanimaging

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