Calcium Isotopic Composition and Its Association With Multiple Myeloma Disease Activity

Multiple myeloma (MM) is characterized by clonal proliferation of a neoplastic plasma cell and its production of a monoclonal immunoglobulin; evolving from an asymptomatic pre-malignant stage named monoclonal gammopathy of undetermined significance (MGUS). At the time of diagnosis with MM, lytic lesions are present in approximately 70-80% of patients. Lytic lesions increase the risk for skeletal related events as well as treatment costs, while lowering quality of life and overall survival. Metastatic bone surveys underestimate bone disease since plain radiographs demonstrate abnormalities until at least 30% of trabecular bone has been lost and cannot provide information about ongoing bone remodeling. Bone scintigraphy lacks usefulness in following bone disease due to decreased osteoblast activity in MM, while Dual-energy X-ray absorptiometry scans produce heterogeneous local bone mineral density changes and are not recommended to evaluate bone disease in these patients. Biomarkers ( eg, N- and C-terminal telopeptides of type I collagen) have been used to assess bone metabolism balance (BMB; ie, the difference between bone formation and resorption) in MM prior and subsequent to specific therapies, however, consensus is still lacking and their clinical utility is uncertain. Calcium in nature consists of six isotopes, and the relative abundance of the isotopes varies measurably. The strength of molecular bonds depends on atomic weight of the participating atoms. Calcium (Ca) containing compounds react at different rates depending on atomic mass. Bone formation favors lighter isotopes of Ca, depleting soft tissue of light Ca isotopes, while bone resorption releases this isotopically light Ca back into soft tissue with little or no selectivity. As a result of this difference in isotope fractionation, Ca isotopic composition in soft tissue should shift to heavier Ca isotope values in positive BMB and lighter values in negative BMB. In order to identify whether Ca isotopic composition can be used as a marker of myeloma-induced bone disease, we first set out to determine its association with MM disease activity. Using multiple collector inductively coupled plasma mass spectrometry, we determined the Ca isotopic composition in 108 peripheral blood samples from 54 patients with monoclonal gammopathies. Ca isotopic composition was determined as the ratio between the naturally occurring 44 Ca and 42 Ca isotopes (δ 44/42 Ca) relative to a standard in parts per ten thousand units, as previously described by Morgan et al. Disease activity was determined at the time of δ 44/42 Ca determination by assessing disease status and response to treatment, as described by the International Myeloma Working Group uniform response criteria, defining progressive or relapsed disease as active disease, and stable or responsive disease as non-active. Categorical variables were analyzed using chi squared or Fisher’s exact test, interval variables were analyzed using a one-tailed t-test. A repeated measures logistic regression model was developed using a cross-sectional time-series generalized estimating equation. All statistical analysis was done using Stata/SE 12.0. Fifty-four adult patients (61% male) diagnosed with monoclonal gammopathy, ranging from MGUS (n=1) to SMM (n=4) to MM (n=49), were assessed at different time points, with 7 patients being assessed once, 41 were assessed twice, 5 were assessed 3 times, while 1 patient was assessed 4 times. Mean age at the time of first assessment was 66, ranging from 45 to 84. Mean δ 44/42 Ca was statistically lower in the active disease group as compared to the non-active group (-0.7536 vs -0.6564, p=0.0466). In a statistically significant repeated measurement logistic regression model (p= 0.0239), δ 44/42 Ca is associated with active disease (OR=0. 054, p=0.031, 95% CI=0.004-0.765) after adjusting for age, gender, presence of anemia, serum creatinine, free light chain ratio, current bisphosphonate and current anti-myeloma therapy. A lower δ 44/42 Ca in the active disease group might suggest a link between a more intense level of bone resorption and myeloma activity. Ca isotopic composition can become part of the clinician’s arsenal to determine disease status in a patient with MM. In order to further characterize δ 44/42 Ca to specifically infer myeloma-induced bone disease activity, further studies that include serum biomarkers and dynamic imaging should be performed. Disclosures: Gordon: Arizona State University: “Application of Ca isotope analysis to the early detection of metastatic cancer” (AzTE reference number M13-117) Patents & Royalties; Arizona State University: “Isotopic biomarkers for rapid assessment of bone mineral balance in biomedical applications” (US Application #PCT/US2011/039780; AzTE reference number M10-102L), “Isotopic biomarkers for rapid assessment of bone mineral balance in biomedical applications” (US Application #PCT/US2011/039780; AzTE reference number M10-102L) Patents & Royalties. Skulan: AZTE: “Application of Ca isotope analysis to the early detection of metastatic cancer” (AzTE reference number M13-117) Patents & Royalties; AZTE: “Isotopic biomarkers for rapid assessment of bone mineral balance in biomedical applications” (US Application #PCT/US2011/039780; AzTE reference number M10-102L), “Isotopic biomarkers for rapid assessment of bone mineral balance in biomedical applications” (US Application #PCT/US2011/039780; AzTE reference number M10-102L) Patents & Royalties. Anbar: Arizona State University: “Isotopic biomarkers for rapid assessment of bone mineral balance in biomedical applications” (US Application #PCT/US2011/039780; AzTE reference number M10-102L), “Isotopic biomarkers for rapid assessment of bone mineral balance in biomedical applications” (US Application #PCT/US2011/039780; AzTE reference number M10-102L) Patents & Royalties; Arizona State University: “Application of Ca isotope analysis to the early detection of metastatic cancer” (AzTE reference number M13-117) Patents & Royalties. Fonseca: AMGEN: Consultancy; Millennium: Consultancy; Binding Site: Consultancy; Onyx: Consultancy, Research Funding; Lilly: Consultancy; BMS: Consultancy; Genzyme: Consultancy; Celgene: Consultancy; Medtronic: Consultancy; Otsuka: Consultancy; Cylene: Research Funding; Prognostication of MM based on genetic categorization of the disease: Patents & Royalties.