17 DHC 2025
22 - 24 January 2025
Lymphoid Abstracts (3)
Abstract
Proteomic Profiling Using High-dimensional Multiplex Platforms
23 January
10:45 11:00
Martijn Kolijn
Paper

Proteomic Profiling Using High-dimensional Multiplex Platforms to Identify Prospective Risk Factors for Lymphoid Malignancies Across Multiple Cohorts

Pieter Martijn Kolijn (1,2), Karl Smith-Byrne (3), Vivian Viallon (4), Bertrand Hémon (4), Matthew Lee (4,5), Anton W. :Langerak (2), Florentin Späth (6), Arjan Diepstra (7), Ruth C. Travis (3), Elio Riboli (8), Marc J. Gunter (3,8), James McKay (4), Roel C.H. Vermeulen (1)
(1) University Utrecht, Population Health Sciences, Utrecht, (2) Erasmus MC, Immunology, Rotterdam, (3) University of Oxford, Cancer Epidemiology Unit, Nuffield Department of Population Health, Oxford, UK, (4) International Agency for Research on Cancer (IARC) - World Health Organization, Lyon, France, (5) University of Bristol, Population Health Sciences, Bristol, (6) Umeå University, Department of Diagnostics and Intervention, Umeå, (7) University of Groningen, University Medical Center Groningen, Pathology and Medical Biology, Groningen, (8) Imperial College London, Department of Epidemiology and Biostatistics, London, UK
No potential conflicts of interest
Introduction

Circulating proteins play a central role in the development of lymphoid malignancies and the immune system’s response to these cancers. Proteomic studies in serum and plasma offer a promising source of biomarkers for early detection, progression, recurrence and prognosis.

Methods

In this study, we measured 6,412 unique proteins in prediagnostic plasma samples from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort using the SomaScan assay from 4,564 participants—484 who later developed lymphoma (median follow-up 9 years)  and 4,081 who did not. Results were compared with proteomic datasets from the Atherosclerosis Risk in Communities (ARIC) study (SomaScan) and the UK Biobank (OLINK).Given the heterogeneity of lymphoid malignancies, we conducted subtype-specific analyses for non-Hodgkin lymphoma (NHL, n=348), chronic lymphocytic leukemia (CLL, n=80), multiple myeloma (MM, n=116), diffuse large B-cell lymphoma (DLBCL, n=80), follicular lymphoma (FL, n=51) and Hodgkin lymphoma (HL, n=20) using Prentice-weighted Cox regression with Benjamini-Hochberg correction for multiple testing.

Results

Alongside established biomarkers such as sCD23 for CLL, CXCL13 for DLBCL, and sBCMA for MM, we identified novel potent markers, including FCMR and FDCSP for NHL. Our data indicate that these protein changes are evident more than 15 years before diagnosis, underscoring the protracted preclinical phase of lymphoid malignancies. Pathway analyses revealed dysregulation in immune modulation, epigenetic regulation, cytokine and chemokine signaling, B-cell receptor signaling, the NF-κB signaling pathway, alternative splicing and N-glycan biosynthesis. Time-stratified analyses revealed a sharp increase in the number of dysregulated proteins in cases within 5 years of diagnosis. Interestingly, the top enriched pathways in participants within 5 years of diagnosis reflected pathways recurrently mutated in lymphoid malignancy, such as the MAPK pathway for MM and the spliceosome for CLL.

Conclusion

In conclusion, we identified multiple proteomic signatures associated with lymphoid malignancy risk, revealing a robust set of early-detection markers detectable many years prior to diagnosis, advancing our understanding of lymphoid malignancy pathogenesis.

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