Molecular epidemiology approach : nested case-control studies in glioma and lymphoid malignancies

• Main Author: Späth, Florentin
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: Umeå universitet, Onkologi 2019
• Subjects: 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; Cancer and Oncology; Cancer och onkologi; Northern Sweden
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-156421

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 ...