Niels J. Rupp

This study uses AI-based image analysis and multi-omics profiling to link morphological features with molecular changes in ccRCC, identifying unique molecular profiles in aggressive rhabdoid tumors.

This paper shows that ASC controls AA amyloidosis by interacting with SAA and that anti-ASC antibodies reduce amyloid loads in mice.

The paper investigates how genomic alterations affect molecular networks in prostate cancer by integrating genomic, transcriptomic, and proteomic data from 105 samples, identifying a sub-network predictive of tumor aggressiveness and recurrence.

This study develops a deep learning model to automate Gleason grading of prostate cancer tissue microarrays, achieving agreement with pathologists and expert-level patient stratification.

This study quantifies spatial proteome heterogeneity in prostate tissues using multi-region analysis and identifies biomarker variability across benign and malignant tissues.