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Predicting multiple myeloma disease activity by analyzing natural calcium isotopic composition

Leukemia volume 28, pages 2112–2115 (2014)Cite this article

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We propose that measurements of naturally occurring calcium (Ca) isotopes can serve as an accurate near-real-time detector of bone metabolism for patients with multiple myeloma (MM), a neoplasm characterized by clonal proliferation of plasma cells and their production of a monoclonal immunoglobulin.1, 2 Bone destruction is a hallmark of MM, manifested in the form of lytic lesions, osteoporosis and fractures. Bone involvement is diagnosed with imaging studies or reported pain. Patient management would improve with better diagnosis and monitoring of bone metabolism.1, 2

Lytic bone lesions are present in ∼80% of MM patients at diagnosis.3 Lesions cause major morbidity for patients, increase treatment costs, and lower quality of life and overall patient survival.4, 5 Imaging detects past damage, not currently active disease. Skeletal surveys are routinely used in the clinic, but they underestimate bone disease; radiographs do not demonstrate abnormalities until ⩾30% of trabecular bone has been lost, and provide no information about ongoing bone remodeling.6, 7 Dual energy X-ray absorpitometry scans (DEXA) are ineffective in evaluation of MM bone disease due to diminished osteoblast activity.8 Because of the heterogeneity of bone involvement in patients with MM, and the variability of bone mineral density response, sequential bone density scans are not recommended.9

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Acknowledgements

This work was funded by an ASU-Mayo Clinic Seed Grant. Dr Fonseca is a Clinical Investigator of the Damon Runyon Cancer Research Fund. His work is supported by grants R01 CA83724, ECOG CA 21115T, Predolin Foundation, Mayo Clinic Cancer Center and the Mayo Foundation. The authors thank Dr Jennifer Morgan for catalyzing the collaboration between Dr Fonseca and the ASU team. The work of Drs Anbar, Gordon, and Skulan was partially supported by NASA Human Research Program Grants NNX08AQ36G and 12-12_NASA_2-0046. Dr Channon's work was supported by the Bisgrove Scholars Program of Science Foundation Arizona. This work was funded in part by Arizona's Technology Research Initiative Fund, a voter-approved program that is supported by state sales tax and administered through the Arizona Board of Regents. Dr Anbar thanks Dr Michael Anbar for inspiring him to pursue the use of natural isotope variations in clinical medicine.

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Author notes

  1. G W Gordon and J Monge: These authors are co-first authors.

Authors and Affiliations

  1. School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA

    G W Gordon, M B Channon & A D Anbar

  2. Division of Hematology and Oncology, Mayo Clinic in Arizona, Scottsdale, AZ, USA

    J Monge & R Fonseca

  3. Division of Health Sciences Research, Mayo Clinic in Arizona, Scottsdale, AZ, USA

    Q Wu

  4. Department of Chemistry and Biochemistry, Arizona State University, Tempe, AZ, USA

    J L Skulan & A D Anbar

  5. Department of Medicine, Mayo Clinic in Arizona, Scottsdale, AZ, USA

    R Fonseca

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  1. G W Gordon
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Correspondence to R Fonseca.

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Competing interests

Drs Gordon, Skulan and Anbar have pending patent applications for ‘Isotopic biomarkers for rapid assessment of bone mineral balance in biomedical applications’ (US Application #PCT/US2011/039780; AzTE reference number M10-102L) and ‘Application of Ca isotope analysis to the early detection of metastatic cancer’ (AzTE reference number M13-117) from ASU and AZTE. Dr Fonseca has a patent for ‘Prognostication of MM based on genetic categorization of the disease’ and has received consulting fees from Medtronic, Otsuka, Celgene, Genzyme, BMS, Lilly, Onyx, Binding Site, Millennium and AMGEN; and has sponsored research from Cylene and Onyx.

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Author Contributions

GWG performed laboratory work with assistance from MBC. JM analyzed patient records and wrote the paper. QW performed statistical analysis. JLS, GWG, ADA and RF designed the study and provided substantial revisions to the paper. RF arranged access to samples.

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Gordon, G., Monge, J., Channon, M. et al. Predicting multiple myeloma disease activity by analyzing natural calcium isotopic composition. Leukemia 28, 2112–2115 (2014). https://doi.org/10.1038/leu.2014.193

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