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Immune marker changes and risk of multiple myeloma: a nested case-control study using repeated prediagnostic blood samples
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology. (Melin)ORCID iD: 0000-0002-0711-0830
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology. (Melin)
Utrecht University.
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Biomarkers reliably predicting progression to multiple myeloma (MM) are lacking. Myeloma risk has been associated with low blood levels of monocyte chemotactic protein-3 (MCP-3), macrophage inflammatory protein-1 alpha (MIP-1α), vascular endothelial growth factor (VEGF), fibroblast growth factor-2 (FGF-2), fractalkine, and transforming growth factor alpha (TGF-α). In this study, we aimed to replicate these findings and also study the individual dynamics of each marker in a prospective longitudinal cohort, thereby examining their potential as markers of myeloma progression. For this purpose, we identified 65 myeloma cases within the Northern Sweden Health and Disease Study as well as 65 individually matched controls, each with two donated blood samples. Samples from myeloma cases were donated in median 13 and 4 years prior to myeloma diagnosis. Known risk factors of progression were determined by protein-, and immunofixation electrophoresis, and free light chain assays. We observed lower levels of MCP-3, VEGF, FGF-2, fractalkine, and TGF-α in myeloma patients than in controls, consistent with previous data. We also observed that these markers decreased among future myeloma patients while remaining stable in controls. Decreasing trajectories were marked for TGF-α (P = 2.5 x 10-4) indicating progression to MM. Investigating this, we found that low levels of TGF-α assessed at time of the repeated sample were independently associated with risk of progression in a multivariable model (hazard ratio = 3.5; P = 0.003). TGF-α can potentially improve early detection of MM.

Keywords [en]
prospective longitudinal study, multiple myeloma risk, progression, marker trajectories
National Category
Clinical Medicine
Research subject
Oncology; Cancer Epidemiology
Identifiers
URN: urn:nbn:se:umu:diva-156420OAI: oai:DiVA.org:umu-156420DiVA, id: diva2:1288937
Funder
Swedish Research CouncilSwedish Cancer SocietyAvailable from: 2019-02-14 Created: 2019-02-14 Last updated: 2019-05-10
In thesis
1. Molecular epidemiology approach: nested case-control studies in glioma and lymphoid malignancies
Open this publication in new window or tab >>Molecular epidemiology approach: nested case-control studies in glioma and lymphoid malignancies
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

BACKGROUND: Nested case-control studies aim to link molecular markers with a certain outcome. Repeated prediagnostic samples may improve the evaluation of marker-disease associations. However, data regarding the benefit of repeated samples in such studies are sparse. We aimed to assess the relationship between blood levels of various proteins and risk of glioma, B cell lymphoma, and multiple myeloma to gain further understanding of disease etiology and to evaluate the clinical relevance of the studied markers. To this end, marker-disease associations were evaluated considering the natural history of the studied disease and the time between blood sample collection and diagnosis using both single (I-II) and repeated prediagnostic blood samples (III-IV).

PATIENTS AND METHODS: We conducted four nested case-control studies and one meta-analysis using samples from three prospective cohorts: the Janus Serum Bank, the Northern Sweden Health and Disease study, and the European Prospective Investigation into Cancer and Nutrition study. The following studied endpoints and relationships were included: I) glioma risk and the association with the receptor tyrosine kinases (soluble) sEGFR and sERBB2; II) B cell lymphoma risk and the association with the immune markers sCD27 and sCD30; III) B cell lymphoma risk and the association with immune markers (CXCL13, sTNF-R1, sCD23, sCD27, and sCD30) and their trends over time; and IV) multiple myeloma risk and the association  with ten immune markers and growth factors (MCP-3, MIP-1α, MIP-1β, VEGF, FGF-2, fractalkine, TGF-α, IL-13, TNF-α, and IL-10) and their trends over time.

RESULTS: Risk of developing I) glioma was weakly associated with high blood levels of sERBB2. In addition, high levels of both sEGFR and sERBB2 assessed 15 years before diagnosis were associated with glioblastoma risk.

Risk of II) B cell lymphoma was associated with high levels of sCD30, whereas high levels of sCD27 were particularly associated with risk of chronic lymphocytic leukemia. Meta-analyses showed consistent results for sCD30 across cohorts and lymphoma subtypes, whereas results for sCD27 were less consistent across cohorts and subtypes.

In addition, III) B cell lymphoma risk was associated with levels of CXCL13, sCD23, sCD27, and sCD30 assessed in samples collected 17 years before diagnosis. Marker levels increased in cases closer to diagnosis, particularly for indolent lymphoma with a marked association for chronic lymphocytic leukemia and sCD23. Increasing marker levels closer to diagnosis were also observed for CXCL13 in future diffuse large B cell lymphoma patients.

Risk of IV) multiple myeloma was associated with low levels of MCP-3, VEGF, FGF-2, fractalkine, and TGF-α. Levels of these markers decreased in myeloma cases over time, especially for TGF-α. TGF-α assessed at time of the prediagnostic repeated sample seemed to help predict progression to multiple myeloma.

CONCLUSIONS: Both the natural history of the studied disease and the time between sample collection and diagnosis are crucial for the evaluation of marker-disease associations. Using repeated blood samples improves the understanding of marker-disease associations and might help to identify useful biomarker candidates.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2019. p. 53
Series
Umeå University medical dissertations, ISSN 0346-6612 ; 2016
Keywords
Glioma, B cell lymphoma, multiple myeloma, risk, repeated samples, prospective longitudinal study, nested case-control study, circulating sEGFR and sERBB2, circulating immune markers and growth factors, marker disease association, disease progression, NSHDS, Janus, linear mixed modeling
National Category
Cancer and Oncology
Research subject
Epidemiology; Oncology
Identifiers
urn:nbn:se:umu:diva-156421 (URN)978-91-7855-025-8 (ISBN)
Public defence
2019-03-22, Bergasalen, byggnad 27, Norrlands universitetssjukhus, Umeå, 09:00 (English)
Opponent
Supervisors
Available from: 2019-02-22 Created: 2019-02-14 Last updated: 2019-02-21Bibliographically approved

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Späth, FlorentinWibom, CarlJohansson, Ann SofieBergdahl, IngvarHultdin, JohanMelin, Beatrice S.

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