Learn more about Covaris Proteomics Workflows ➜
Speak to an AFA® Solution Expert ➜
Watch On-Demand: Optimizing Melanoma Therapy Through AI-Enhanced Digital Pathology and Molecular Profiling in Large Scale Biobanks
Peter Horvatovich, PhD
Professor, Computational Proteomics, University of Groningen, The Netherlands
An international consortium led by Lund University is building patient digital twins for melanoma precision treatment, drawing on a biobank of more than 5,000 FFPE tissue samples. In this presentation, Peter Horvatovich of the University of Groningen details how FFPE proteomics melanoma subtypes profiling on the Covaris R230 enabled untargeted proteomic analysis across all four melanoma subtypes: superficial spreading, nodular, lentigo maligna, and the rare acral lentiginous form.
After optimizing sample preparation protocols and reducing processing time to just five minutes, the workflow identified up to 5,000 proteins per sample with improved reproducibility compared to standard methods. Differential expression analysis using this FFPE proteomics melanoma subtypes approach revealed distinct molecular signatures for acral lentiginous melanoma, including upregulated extracellular matrix remodeling and protein synthesis pathways, alongside downregulated lipid metabolism and chromatin remodeling. Notably, the team identified reduced expression of ATP5 inhibitory factor 1, a regulator of mitochondrial complex V linked to the Warburg effect, distinguishing this aggressive, non-UV-associated melanoma subtype from the others. The pilot study is now scaling to the full 5,000+ sample biobank to support multi-omic digital twin development for personalized melanoma treatment.