Abstract 1889: Proteomic profiling using high-dimensional multiplex platforms to identify prospective risk factors for lymphoid malignancies across multiple cohorts

Abstract Introduction: Circulating proteins play a central role in the development of lymphoid malignancies and the immune system’s response to these cancers. Methods: In this study, we measured 6, 412 unique proteins in prediagnostic plasma samples using the SomaScan 7K panel from a total of 4, 565 participants of a case-cohort study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC)—484 who later developed a lymphoid malignancy (median follow-up 9 years) and 4, 081 who did not. 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: We observed significantly altered plasma levels prior to NHL diagnosis for 147 unique proteins (161 aptamers), of which 131 were upregulated and 16 were downregulated. Increased plasma levels of members of several major immunomodulatory protein families, including the FC-receptor family and the semaphorin family, were associated with increased risk of NHL. Alongside established biomarkers such as sCD23 for CLL, CXCL13 for DLBCL, and sBCMA for MM, we identified potent novel markers, including FCMR and FDCSP for NHL. Time-stratified analyses revealed that a subset of these protein-lymphoma associations are evident over a decade 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. In total, 2136 out of 6412 proteins measured in our current study overlapped with those measured in a recent UK biobank study. The significant protein-cancer associations observed in our current analyses within EPIC showed high concordance in the UK biobank in terms of both FDR-adjusted significance (58%-82%) and the direction of the association (89%-92%), meaning positively or negatively associated with cancer risk. Conclusion: In conclusion, we identified hundreds of proteins associated with lymphoid malignancy risk, revealing a robust set of markers detectable many years prior to diagnosis, and advancing our understanding of lymphoid malignancy pathogenesis. Citation Format: Pieter Martijn Kolijn, Karl Smith-Byrne, Vivian Viallon, Matthew Lee, Keren Papier, Anton W. Langerak, Florentin Späth, Arjan Diepstra, Raul Zamora-Ros, Alessandra Macciotta, Amaia Aizpurua, Rosario Tumino, Ruth C. Travis, Elio Riboli, Marc J. Gunter, James McKay, Roel C. Vermeulen. Proteomic profiling using high-dimensional multiplex platforms to identify prospective risk factors for lymphoid malignancies across multiple cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1889.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-1889
Primary Topic
Advanced Biosensing Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 1889: Proteomic profiling using high-dimensional multiplex platforms to identify prospective risk factors for lymphoid malignancies across multiple cohorts

Amaia Aizpurua, Alessandra Macciotta, Matthew A. Lee, Roel C.H. Vermeulen et al.
Cancer Research
Advanced Biosensing Techniques and Applications
article

Abstract 1889: Proteomic profiling using high-dimensional multiplex platforms to identify prospective risk factors for lymphoid malignancies across multiple cohorts

Amaia Aizpurua, Alessandra Macciotta, Matthew A. Lee, Roel C.H. Vermeulen, Ruth C. Travis, ­Rosario ­Tumino, Karl Smith-Byrne, Florentin Späth, P. Martijn Kolijn, Elio Ríboli, Marc J. Gunter, Anton W. Langerak, Raúl Zamora‐Ros, Arjan Diepstra, James McKay, Keren Papier, Vivian Viallon
article en

Abstract

Abstract Introduction: Circulating proteins play a central role in the development of lymphoid malignancies and the immune system’s response to these cancers. Methods: In this study, we measured 6, 412 unique proteins in prediagnostic plasma samples using the SomaScan 7K panel from a total of 4, 565 participants of a case-cohort study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC)—484 who later developed a lymphoid malignancy (median follow-up 9 years) and 4, 081 who did not. 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: We observed significantly altered plasma levels prior to NHL diagnosis for 147 unique proteins (161 aptamers), of which 131 were upregulated and 16 were downregulated. Increased plasma levels of members of several major immunomodulatory protein families, including the FC-receptor family and the semaphorin family, were associated with increased risk of NHL. Alongside established biomarkers such as sCD23 for CLL, CXCL13 for DLBCL, and sBCMA for MM, we identified potent novel markers, including FCMR and FDCSP for NHL. Time-stratified analyses revealed that a subset of these protein-lymphoma associations are evident over a decade 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. In total, 2136 out of 6412 proteins measured in our current study overlapped with those measured in a recent UK biobank study. The significant protein-cancer associations observed in our current analyses within EPIC showed high concordance in the UK biobank in terms of both FDR-adjusted significance (58%-82%) and the direction of the association (89%-92%), meaning positively or negatively associated with cancer risk. Conclusion: In conclusion, we identified hundreds of proteins associated with lymphoid malignancy risk, revealing a robust set of markers detectable many years prior to diagnosis, and advancing our understanding of lymphoid malignancy pathogenesis. Citation Format: Pieter Martijn Kolijn, Karl Smith-Byrne, Vivian Viallon, Matthew Lee, Keren Papier, Anton W. Langerak, Florentin Späth, Arjan Diepstra, Raul Zamora-Ros, Alessandra Macciotta, Amaia Aizpurua, Rosario Tumino, Ruth C. Travis, Elio Riboli, Marc J. Gunter, James McKay, Roel C. Vermeulen. Proteomic profiling using high-dimensional multiplex platforms to identify prospective risk factors for lymphoid malignancies across multiple cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1889.

Cancer ResearchVol. 85(8_Supplement_1)
University of Groningen (NL), Utrecht University (NL), University of Bristol (GB), University of Oxford (GB), Institut d'Investigació Biomédica de Bellvitge (ES), Sint Franciscus Gasthuis (NL), Biogipuzkoa Health Research Institute (ES), Italian Association for Cancer Research (IT), The London College (GB), Centre international de recherche sur le cancer (FR), Imperial College London (GB), University of Turin (IT), Umeå University (SE)
Openalex Percentile: Top 93%
Advanced Biosensing Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.