Author

Antti Sakari Rannikko

University of HelsinkiORCID 0000-0002-4261-3484Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Vilja M. PietiäineniD· 3 shared Erika Romppanen· 2 shared Michaela FeodoroffiD· 2 shared Minna Malmstedt· 2 shared Minttu PolsoiD· 2 shared Olli KallioniemiiD· 2 shared Petrus JärvineniD· 2 shared Piia MikkoneniD· 2 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersCancer Biology

Vilja M. PietiäinenORCID

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Author profile →

3 papers

Recent·Most cited

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, Minttu Polso, Patrick Penttilä, Minna Malmstedt, Piia Mikkonen, Lauren J. Gerber, Ruusu‐Maaria Merivirta, Mariliina Arjama, Erika Romppanen, Matilda Roos-Mattila, Pauliina Kallio, Swapnil Potdar, Mikaela Grönholm, , 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.

bioRxiv · Jul 9, 2026 · PreprintCancer Biology

Pathway-centric multi-omics and functional precision medicine reveal shared drug vulnerabilities in heterogeneous adult Wilms tumor

Minttu Polso, Romika Kumari, Tamara J. Luck, Piia Mikkonen, Katja Välimäki, Ruusu‐Maaria Merivirta, Minna Malmstedt, Johanna Lehtonen, Erika Romppanen, Sara Kuusela, Antti Hassinen, Janna Saarela, Teijo S. Pellinen, Panu Jaakkola, Pia Suonpää, , Vilja M. Pietiäinen

This study identifies shared drug vulnerabilities in adult Wilms tumor through multi-omics and functional assays, showing pathway-level dependencies predict drug responses better than single-gene biomarkers.

bioRxiv · Jun 25, 2026 · PreprintCancer Biology

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

Isabel Mogollón, Michaela Feodoroff, Anna Serafia Nylund, Alba Montedeoca, Gantugs Atarsaikhan, Pedro Neto, Péter Horváth, Antti Sakari Rannikko, Vincenzo Cerullo, Vilja Pietiäinen, 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.

bioRxiv · Sep 8, 2024 · PreprintCancer Biology