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Immune marker changes and risk of multiple myeloma: a nested case-control study using repeated prediagnostic blood samples
Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi. (Melin)ORCID-id: 0000-0002-0711-0830
Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi. (Melin)
Utrecht University.
Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
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2019 (Engelska)Ingår i: Haematologica, ISSN 0390-6078, E-ISSN 1592-8721, Vol. 104, nr 12, s. 2456-2464Artikel i tidskrift (Refereegranskat) Published
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-1 alpha), vascular endothelial growth factor (VEGF), fibroblast growth factor-2 (FGF-2), fractalkine, and transforming growth factor-alpha (TGF-alpha). In this study, we aimed to replicate these findings and 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 and 65 matched cancer-free controls each with two donated blood samples within the Northern Sweden Health and Disease Study. The first and repeated samples from myeloma cases were donated at a median 13 and 4 years, respectively, before the myeloma was diagnosed. Known risk factors for progression were determined by protein-, and immunofixation electrophoresis, and free light chain assays. We observed lower levels of MCP-3, VEGF, FGF-2, and TGF-alpha 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 noted for TGF-alpha (P=2.5 x 10(-4)) indicating progression to MM. Investigating this, we found that low levels of TGF-alpha assessed at the time of the repeated sample were independently associated with risk of progression in a multivariable model (hazard ratio = 3.5; P=0.003). TGF-alpha can potentially improve early detection of MM.

Ort, förlag, år, upplaga, sidor
Ferrata Storti Foundation, 2019. Vol. 104, nr 12, s. 2456-2464
Nyckelord [en]
prospective longitudinal study, multiple myeloma risk, progression, marker trajectories
Nationell ämneskategori
Klinisk medicin
Forskningsämne
onkologi; cancerepidemiologi
Identifikatorer
URN: urn:nbn:se:umu:diva-156420DOI: 10.3324/haematol.2019.216895ISI: 000499687600030PubMedID: 30948485Scopus ID: 2-s2.0-85075958352OAI: oai:DiVA.org:umu-156420DiVA, id: diva2:1288937
Forskningsfinansiär
VetenskapsrådetCancerfonden
Anmärkning

Originally included in thesis in manuscript form

Tillgänglig från: 2019-02-14 Skapad: 2019-02-14 Senast uppdaterad: 2020-01-07Bibliografiskt granskad
Ingår i avhandling
1. Molecular epidemiology approach: nested case-control studies in glioma and lymphoid malignancies
Öppna denna publikation i ny flik eller fönster >>Molecular epidemiology approach: nested case-control studies in glioma and lymphoid malignancies
2019 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Umeå: Umeå universitet, 2019. s. 53
Serie
Umeå University medical dissertations, ISSN 0346-6612 ; 2016
Nyckelord
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
Nationell ämneskategori
Cancer och onkologi
Forskningsämne
epidemiologi; onkologi
Identifikatorer
urn:nbn:se:umu:diva-156421 (URN)978-91-7855-025-8 (ISBN)
Disputation
2019-03-22, Bergasalen, byggnad 27, Norrlands universitetssjukhus, Umeå, 09:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2019-02-22 Skapad: 2019-02-14 Senast uppdaterad: 2019-02-21Bibliografiskt granskad

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