Next generation pan-cancer blood proteome pro�ling using proximity extension assay

Cancer is a highly heterogeneous disease in need of accurate and non-invasive diagnostic tools. Here, we describe a novel strategy to explore the proteome signature by comprehensive analysis of protein levels using a pan-cancer approach of patients representing the major cancer types. Plasma pro�les of 1,463 proteins from more than 1,400 cancer patients representing altogether 12 common cancer types were measured in minute amounts of blood plasma collected at the time of diagnosis and before treatment. AI-based disease prediction models allowed for the identi�cation of a set of proteins associated with each of the analyzed cancers. By combining the results from all cancer types, a panel of proteins suitable for the identi�cation of all individual cancer types was de�ned. The results are presented in a new open access Human Disease Blood Atlas. The implication for cancer precision medicine of next generation plasma pro�ling is discussed.

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