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. 2023 Nov 24;15(23):5562.
doi: 10.3390/cancers15235562.

Circulating sRANKL, Periostin, and Osteopontin as Biomarkers for the Assessment of Activated Osteoclastogenesis in Myeloma Related Bone Disease

Vladimir Gerov  1 , Daniela Gerova  2 , Ilina Micheva  1   3 , Miglena Nikolova  4 , Milena Pasheva  4 , Neshe Nazifova  4 , Bistra Galunska  4
Affiliations

Circulating sRANKL, Periostin, and Osteopontin as Biomarkers for the Assessment of Activated Osteoclastogenesis in Myeloma Related Bone Disease

Vladimir Gerov et al. Cancers (Basel). .

Abstract

The hallmark of multiple myeloma is myeloma related bone disease. Interactions between myeloma plasma cells (MPCs), stromal cells, and the bone marrow (BM) microenvironment play a critical role in the pathogenesis of MBD. Bone remodeling is severely dysregulated with the prevalence of osteoclast activity. We aimed to assess circulating levels of sRANKL, periostin, and osteopontin as osteoclast activators in NDMM patients at diagnosis and in the course of treatment, correlations with clinical and laboratory data, and to evaluate their potential as additional biomarkers for the assessment of MBD. The current study involved 74 subjects (41 NDMM patients, 33 controls). MBD was assessed by whole-body low-dose computed tomography. sRANKL, periostin, and osteopontin were assayed by commercial ELISA kits. At diagnosis, all tested parameters were significantly higher in NDMM patients compared to the controls (p < 0.0001), correlating with disease stage, MBD grade, and BM infiltration by MPCs. During therapy, the serum levels of all tested proteins decrease, most prominently after autologous stem cell transplantation (p < 0.0001). A significant reduction was established in patients achieving complete and very-good partial response compared to all others (p < 0.05). In conclusion, sRANKL, periostin, and osteopontin reflect MBD severity and could be promising markers for MBD monitoring and the effect of myeloma treatment.

Keywords: biomarkers; myeloma bone disease; osteopontin; periostin; sRANKL.

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Conflict of interest statement

The authors declare no conflict of interest. The funder had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Serum levels of sRANKL, periostin, and osteopontin in controls and patients at baseline. Data are presented as medians and minimal and maximal values. Statistical significance was indicated at p < 0.05.
Figure 2
Figure 2
Comparison of sRANKL, periostin, and osteopontin serum levels in NDMM patients at baseline (T0) and stratified according to the ISS staging system. Data are presented as medians and minimal and maximal values. Statistical significance was indicated at p < 0.05.
Figure 3
Figure 3
Serum levels of sRANKL, periostin and osteopontin in NDMM patients, stratified by the number of bone lesions. Data are presented as medians and minimal and maximal values. Statistical significance was indicated at p < 0.05.
Figure 4
Figure 4
Serum levels of sRANKL, periostin, and osteopontin in NDMM patients, stratified according to BMI by MPCs. Data are presented as medians and minimal and maximal values. Statistical significance was indicated at p < 0.05.
Figure 5
Figure 5
Spearman correlations of sRANKL, periostin, and osteopontin with B2MG, BMI, albumin, and Hb. Β2MG—β2 microglobulin, BMI—bone marrow infiltration by MPCs, Alb—albumin, Hb—hemoglobin. Statistical significance was indicated at p < 0.05.
Figure 6
Figure 6
sRANKL, periostin, and osteopontin assessed at different time points.
Figure 7
Figure 7
sRANKL, periostin, and osteopontin according to the treatment response. Data are presented as medians and minimal and maximal values. Statistical significance was indicated at p < 0.05.
Figure 8
Figure 8
Diagnostic performance of sRANKL, periostin, and osteopontin assessed by ROC curve analysis. ROC curve—receiver operating characteristic curve, AUC—area under the curve. The green dotted line represents the settings for finding the optimal diagnostic cut-off values of the tested parameters. Statistical significance was indicated at p < 0.05.
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