Vilja M. Pietiäinen

This study identifies SUMOylation as a therapeutic target in high-risk neuroblastoma, showing that SUMO pathway inhibitors like TAK-981 reduce tumor growth and are effective in combination with other therapies.

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.

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.

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

The paper develops Blood Cell Painting (BCP) to profile immune cell morphology in healthy donors, identifying genetic and clinical associations with immune cell features.

The paper introduces Regression Plane, a tool for continuous phenotypic analysis using machine learning without requiring class labels.