Comprehensive biobanking strategy with clinical impact at the European Cancer Moonshot Lund Center

Henriett Oskolas, Fábio C N Nogueira, Gilberto B Domont, Kun-Hsing Yu, Yevgeniy R Semenov, Peter Sorger, Erik Steinfelder, Les Corps, Lesley Schulz, Elisabet Wieslander, David Fenyö, Sarolta Kárpáti, Péter Holló, Lajos V Kemény, Balazs Döme, Zsolt Megyesfalvi, Krzysztof Pawłowski, Toshihide Nishimura, HoJeong Kwon, Sergio Encarnación-GuevaraA Marcell Szasz, Zoltán Veréb, Rolland Gyulai, István Balázs Németh, Roger Appelqvist, Melinda Rezeli, Bo Baldetorp, Peter Horvatovich, Johan Malmström, Indira Pla, Aniel Sanchez, Beatrice Knudsen, András Kiss, Johan Malm, György Marko-Varga, Jeovanis Gil

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Abstract

This white paper presents a comprehensive biobanking framework developed at the European Cancer Moonshot Lund Center that merges rigorous sample handling, advanced automation, and multi-omic analyses to accelerate precision oncology. Tumor and blood-based workflows, supported by automated fractionation systems and standardized protocols, ensure the collection of high-quality biospecimens suitable for proteomic, genomic, and metabolic studies. A robust informatics infrastructure, integrating LIMS, barcoding, and REDCap, supports end-to-end traceability and realtime data synchronization, thereby enriching each sample with critical clinical metadata. Proteogenomic integration lies at the core of this initiative, uncovering tumor- and blood-based molecular profiles that inform cancer heterogeneity, metastasis, and therapeutic resistance. Machine learning and AI-driven models further enhance these datasets by stratifying patient populations, predicting therapeutic responses, and expediting the discovery of actionable targets and companion biomarkers. This synergy between technology, automation, and high-dimensional data analytics enables individualized treatment strategies in melanoma, lung, and other cancer types. Aligned with international programs such as the Cancer Moonshot and the ICPC, the Lund Center's approach fosters open collaboration and data sharing on a global scale. This scalable, patient-centric biobanking paradigm provides an adaptable model for institutions aiming to unify clinical, molecular, and computational resources for transformative cancer research.

Original languageEnglish
Article number105442
Number of pages15
JournalJournal of proteomics
Volume316
DOIs
Publication statusPublished - 30-May-2025

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