Introduction: Current blood-based biomarkers for predicting progression from monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM), such as monoclonal protein levels, the free light-chain ratio, and the suppression of uninvolved immunoglobulins, are insufficient to accurately determine individual MM progression risk. Emerging evidence suggests that blood immune markers may improve prediction of MM progression. Previous studies have associated MM risk with low blood levels of monocyte chemotactic protein-3 (MCP-3), macrophage inflammatory protein-1 alpha (MIP-1α), fibroblast growth factor-2 (FGF-2), vascular endothelial growth factor (VEGF), fractalkine, and transforming growth factor-alpha (TGF-α) (Vermeulen et al. International Journal of Cancer 2018, Späth et al. Haematologica 2019). Declining levels of these markers closer to MM diagnosis were reported, possibly indicating MM progression (Späth et al. Haematologica 2019). However, these studies were small or only included one sample per participant, limiting their accuracy in evaluating marker-disease associations and marker changes over time. To address these limitations, we performed a large prospective longitudinal study to examine the associations between blood levels of these markers and future MM risk and progression.
Methods: From the Janus Serum Bank in Norway (with >300,000 participants), we identified 293 future MM cases and 293 matched cancer-free controls. For MM cases, we selected the pre-diagnostic serum sample that most closely preceded the myeloma diagnosis (first sample), and one additional sample that most closely preceded the first sample (additional sample). Controls were matched to cases' first samples on sex, age (+/- 6 months), and date of blood draw (+/- 3 months). Immune marker levels were quantified in duplicate by Luminex multiplex assays (Merck Millipore) in all samples (n=879). Markers detected in >60% of the measurements (MIP-1α, VEGF, and TGF-α) were analyzed, with missing data handled using multiple imputation. We used conditional logistic regression to investigate continuous immune marker levels and MM risk, and linear mixed effects modeling to study immune marker changes over time. Analyses were performed in R v4.2.3 (R Foundation, Vienna, Austria).
Results: All MM cases were diagnosed between 1978 and 2016. Prospective serum samples, collected within the Janus Serum Bank, were obtained at a median of 20 years (first sample) and 26 years (additional sample) before MM diagnosis. We observed no associations between MM risk and levels of MIP-1α, VEGF, and TGF-α in samples 20 years (median) before diagnosis. Time-stratified analyses suggested inverse but not statistically significant relations of MM risk with TGF-α and MIP-1α levels in samples obtained closer (<8 years) to diagnosis. Notably, TGF-α levels decreased significantly closer to diagnosis in MM cases (p<0.0001), while VEGF and MIP-1α levels did not change. In cancer-free controls, serum levels of MIP-1α, VEGF, and TGF-α remained stable over time. Age did not affect immune marker levels (all p>0.48).
Conclusion: No associations were found between MM risk and levels of MIP-1α, VEGF, and TGF-α in samples obtained 20 years before diagnosis, indicating these markers are not indicative of early MM development. However, the significant decline in TGF-α levels closer to diagnosis supports previous findings (Späth et al. Haematologica 2019) in a large, independent cohort. This decline could reflect microenvironmental changes related to MM progression, potentially aiding in early MM prediction. This warrants further investigation.
No relevant conflicts of interest to declare.
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