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Multi-cohort high-dimensional proteomics reveals early risk markers for lymphoid cancer subtypes
Multi-cohort high-dimensional proteomics reveals early risk markers for lymphoid cancer subtypes
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Multi-cohort high-dimensional proteomics reveals early risk markers for lymphoid cancer subtypes
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Multi-cohort high-dimensional proteomics reveals early risk markers for lymphoid cancer subtypes
Multi-cohort high-dimensional proteomics reveals early risk markers for lymphoid cancer subtypes

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Multi-cohort high-dimensional proteomics reveals early risk markers for lymphoid cancer subtypes
Multi-cohort high-dimensional proteomics reveals early risk markers for lymphoid cancer subtypes
Journal Article

Multi-cohort high-dimensional proteomics reveals early risk markers for lymphoid cancer subtypes

2025
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Overview
This study aims to investigate the early stages of lymphoid malignancy pathogenesis and identify pre-diagnostic proteomic markers for lymphoma. Using the SomaScan-7K platform, we analyze 6412 unique plasma proteins in a case-cohort study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, comprising 4565 participants (484 incident lymphoid malignancy cases, median follow-up 9 years). We identify over 500 unique protein-lymphoid malignancy associations. Enriched pathways include viral protein interactions, cytokine signaling, B-cell receptor signaling, and NF-κB activation, reflecting key mechanisms in lymphoma pathogenesis. Cross-cohort validation of the top 20 FDR-significant proteins reveals concordant nominal significance for 70%-95% of the associations in the UK Biobank (Olink) and ARIC (SomaScan) studies. Time-stratified analyses reveals that a subset of these protein-lymphoma associations is evident over a decade before diagnosis. These findings highlight the potential of circulating proteomic markers in risk stratification, early diagnosis, and targeted prevention strategies for lymphoid malignancies. A comprehensive characterisation of the proteomic landscape of lymphoid malignancies remains elusive. Here, high-throughput proteomic profiling of 6,412 circulating proteins identifies potential risk stratification markers.