1. Introduction
Multiple myeloma (MM) is a plasma cell disorder with increasing incidence worldwide in recent decades [ 1 ]. It accounts for about 10% of all hematologic malignancies [ 2 ]. The uncontrolled proliferation of abnormal monoclonal plasma cells (MPCs) in bone marrow (BM) impels the development of myeloma related bone disease (MBD). At diagnosis, up to 80% of patients present with osteolytic bone lesions [ 3 ] and are at increased risk of skeletal-related events (SRE) such as pathological fractures and spinal cord compression. Bone complications lead to a significant reduction of quality of life and place a substantial additional burden on patients and healthcare systems [ 4 ]. Complex interactions between MPCs, stromal cells, and the BM microenvironment play a critical role in the pathogenesis of MBD [ 5 , 6 ]. Many signaling pathways including Notch signaling, Wnt/β-Catenin signaling, RANKL/RANK/OPG (receptor activator of nuclear factor kappa-Β ligand/receptor activator of NF-κB, osteoprotegerin) axis are activated [ 7 , 8 ]. Bone remodeling is severely dysregulated, manifested by increased osteoclast activity and suppressed osteoblast activity resulting in osteolytic lesions and bone destruction [ 9 ].
RANKL/RANK signaling is vital for osteoclastogenesis. As a membrane protein, RANKL is highly expressed in osteoblasts, osteocytes, and activated T lymphocytes [ 10 ]. The soluble form of the protein (sRANKL) is generated by either proteolytic processing by matrix metalloproteases or alternative mRNA splicing [ 11 ]. RANKL binds to RANK on the surface of osteoclasts and osteoclast precursors, leading to their differentiation and activation [ 12 , 13 ]. In the 5T2MM mouse model of multiple myeloma, MPCs overexpress RANKL, which directly promotes the formation of osteoclasts and osteolytic lesions [ 14 ]. Terpos et al. first reported elevated serum levels of sRANKL in MM patients and suggested that RANKL/OPG system is essential for the development of MBD [ 15 ]. The early involvement of RANKL signaling was observed in patients with monoclonal gammopathy of undetermined significance (MGUS), where circulating sRANKL levels were higher than in controls but still lower than in patients with symptomatic MM [ 16 ]. Serum RANKL was significantly increased in advanced clinical stages and high grade MBD of MM patients [ 17 , 18 ]. Therefore, inhibition of the RANK/RANKL pathway is an important target for the prevention of SRE in MM. Denosumab, a fully human monoclonal anti-RANKL antibody, has been in use for more than ten years in clinical practice [ 19 ].
Another protein associated with bone metabolism is the extracellular matrix (ECM) protein periostin, which is produced primarily by stromal mesenchymal cells and is mainly expressed in the periosteum [ 20 , 21 ]. In addition to its structural role in the bone matrix, under physiological conditions, periostin stimulates osteoblastic function and bone formation activating the Wnt/β-catenin signaling pathway [ 22 ]. Under pathological conditions, high serum periostin is associated with an increased risk of fractures in postmenopausal women [ 23 , 24 ], and in ankylosing spondylitis [ 25 ]. Many studies have reported elevated periostin expression in primary tumors and metastatic lesions, e.g., colorectal cancer and liver metastatic lesions [ 26 , 27 , 28 , 29 , 30 , 31 ]. There are very scarce data concerning periostin implication in MM. Terpos et al. first demonstrated high periostin in the supernatant of six myeloma cell lines. Beside the experimental data, the authors investigated periostin in clinical settings and found the progressive elevation of its levels as the disease evolves from MGUS, SMM (smoldering multiple myeloma), and symptomatic MM [ 32 ]. Revealing the role of periostin in the pathogenesis of MBD, target therapy with anti-periostin antibodies might be a promising new treatment strategy.
Another abundant non-collagenous ECM protein that is an important component of the BM microenvironment is osteopontin (OPN) [ 33 ]. It is expressed by a wide variety of cell types such as bone cells, neurons, epithelial cells, pericytes, fibroblasts, hepatocytes, tubular cells, vascular smooth muscle cells, and immune cells [ 34 ]. It is involved in a number of physiological and pathological processes, including bone remodeling, angiogenesis, immune-regulation, inflammation, wound healing, atherosclerosis, and tumor progression [ 33 , 35 , 36 , 37 , 38 ]. In models with human MM cell lines, Abe et al. demonstrated a cell–cell contact-mediated mechanism of OC induced MPC growth and survival, partially dependent on IL-6 and OPN. A vicious cycle is supposed to be formed, in which the production of OPN along with IL-6 from OCs recruited around MPCs contribute to extensive bone destruction and MPC expansion [ 39 ]. Various studies have found significantly elevated plasma OPN levels in symptomatic MM patients compared to MGUS patients, patients in remission and healthy controls [ 40 , 41 , 42 ]. OCs-derived osteopontin and VEGF from MPCs cooperatively enhance angiogenesis and also induce osteoclastogenic activity by vascular endothelial cells [ 43 ].
The aim of the present study was to explore circulating levels of sRANKL, periostin, and osteopontin in newly diagnosed MM (NDMM) patients at diagnosis and in the course of their treatment, including autologous stem cell transplantation (ASCT), and to assess possible correlations with laboratory data, disease stage, and MBD.
2. Materials and Methods
2.1. Study Population and Study Design
A total of 41 NDMM patients were enrolled in this single-center non-interventional prospective study, carried out between June 2021 and December 2022. Selected patients met the following inclusion criteria: 18 to 80 years of age; and diagnosed according to the Revised International Myeloma Working Group criteria [ 44 ]. Patients with autoimmune or other malignant diseases and treated with bone affecting drugs during the last six months were excluded from the study. The disease stage was determined according to the International Staging System, ISS [ 45 ]. The study design was explained in detail in [ 46 ]. In brief, whole-body low-dose computed tomography (WBLDCT) imaging was used for the assessment of MBD, defined by osteolytic lesions, pathological fractures, vertebral collapse, and soft-tissue involvement. All patients were treated using the standard VCD chemotherapeutic protocol. In addition, patients with a glomerular filtration rate of more than 30 mL/min/1.73 m 2 received biphosphonates. International Myeloma Working Group (IMWG) consensus criteria for response were used to evaluate response to treatment [ 47 ]. After they completed four cycles of VCD treatment, the patients were divided into two groups: patients below 65 years and with a complete response (CR) and very good partial response (VGPR) proceeded to ASCT; patients with stable disease (SD) or partial response (PR) continued with another four cycles of VCD. Patients with progressive disease in the course of treatment dropped out from the study. Four time points for the evaluation of the variations in the tested biochemical markers were selected: before treatment (time point T0); after four cycles of VCD treatment (time point T1); after eight cycles of VCD treatment (time point T2); three months after ASCT (time point TA).
Thirty-three healthy age- and gender-matched control subjects without any chronic inflammatory, autoimmune, or neoplastic disease or bisphosphonate and other bone-affecting drug medication six months before starting the survey were included in the study.
2.2. Methods
Serum sRANKL, periostin, and osteopontin were assayed by commercial ELISA (Sunredbio, Shanghai, China), strictly following the manufacturer’s instructions. Hematological and biochemical parameters as well as morphological evaluations of bone marrow aspirate smears were routinely monitored.
2.3. Statistical Analysis
Results were presented as the mean ± standard deviation (SD), median, and interquartile range (IQR: 25–75-th percentile), or number ( n ) and percentage (%), as appropriate. Descriptive statistics, the unpaired Student’s t -test, and the Mann–Whitney U-test for comparison of Gausian or non-Gausian distributed interval data were used. Chi-square analysis was used to evaluate the frequency distribution according to gender. The relationship between continuous variables was evaluated by Spearman’s correlation analysis, and if a significant relation was found, a linear regression analysis was applied to test the associations of sRANKL, periostin, and osteopontin with routine laboratory parameters. Receiver operating characteristic (ROC) analysis was performed for evaluation the predictive power of serum sRANKL, periostin, and osteopontin. All statistical analyses were two-tailed and statistical significance was considered at p < 0.05. Data analysis was performed using GraphPad Prism v. 8.0.1, San Diego, CA, USA.
3. Results
The baseline demographic and clinical characteristics, as well some results from the routine laboratory testing of MM patients enrolled in the study are provided in detail in [ 46 ] and in Supplementary Table S1 .
3.1. Baseline Serum Levels of sRANKL, Periostin, and Osteopontin in Newly Diagnosed Multiple Myeloma Patients
The median serum levels and IQR for sRANKL, periostin, and osteopontin in NDMM patients at baseline (T0) were: 9.59 pg/mL (8.03–10.92), 648.4 pg/mL (594.4–809.9), and 596.0 ng/mL (479.7–793.8), respectively, significantly higher than those in controls: 5.67 pg/mL (5.15–6.44) for sRANKL, 396.9 pg/mL (308.6–471.9) for periostin, and 387.0 ng/mL (335.9–441.9) for osteopontin ( Figure 1 ).
The serum levels of sRANKL, periostin, and osteopontin gradually increased with the disease stage. The median and IQR for sRANKL in patients in ISS-I, ISS-II, and ISS-III were 8.03 pg/mL (6.97–9.94), 9.09 pg/mL (8.02–10.92), and 10.55 pg/mL (9.36–12.89), respectively. The same phenomenon was observed for periostin: the medians and their IQR for ISS-I, ISS-II, and ISS-III were 563.2 pg/mL (432.8–620.6), 669.0 pg/mL (632.3–761.4), and 807.6 pg/mL (719.6–860.5), respectively, as well as for osteopontin: 480.0 ng/mL (442.8–562.0) in ISS-I stage, 526.2 ng/mL (477.7–715.0) in ISS-II stage and 715.0 ng/mL (596.0–920.1) in ISS-III stage. A statistical difference was reached between ISS-I and ISS-III for all three parameters: for sRANKL— p = 0.0013, for periostin— p < 0.0001, and for osteopontin— p = 0.0003. A significant difference between ISS-I and ISS-II was detected only for periostin ( p = 0.0012), as well for osteopontin between ISS-II and ISS-III— p = 0.0505 ( Figure 2 ).
Lytic bone lesions (≥5 mm) on WBLDCT have been integrated into the diagnostic criteria of the IMWG [ 48 ]. According to the number of bone lesions the patients were divided into two groups: G1—patients with 0 to 3 osteolytic lesions, and G2—patients with more than three lesions and/or bone fractures. The serum levels of the assessed proteins were significantly higher in the G2 group: sRANKL 9.76 pg/mL (IQR 8.90–11.04); periostin 706.8 pg/mL (IQR 624.0–833.6); osteopontin 669.8 ng/mL (IQR 535.6–843.1), compared to G1 group: sRANKL 7.75 pg/mL (IQR 6.44–9.29); periostin 463.8 pg/mL (IQR 431.0–596.4); osteopontin 669.8 ng/mL (IQR 535.6–843.1); 460.0 ng/mL (IQR 419.1–494.8) ( Figure 3 ).
The impact of tumor burden on sRANKL, periostin, and osteopontin serum levels was evaluated by dividing the patients into two groups according to the BMI by MPCs using a cut-off of 60% [ 49 ]. Twenty-four NDMM patients (58.54%) were with BMI ≥ 60% MPCs and their serum levels of sRANKL (median 9.63 pg/mL, IQR 8.90–11.73), periostin (median 726.9 pg/mL, IQR 639.9–855.1), and osteopontin (median 676.7 ng/mL, IQR 517.7–834.3) were significantly higher than the corresponding values in patients with BMI < 60% MPCs: 8.03 pg/mL (IQR 6.96–10.55) for sRANKL, 585.6 pg/mL (IQR 436.3–660.1) for periostin, and 521.2 ng/mL (IQR 453.9–646.5) for osteopontin ( Figure 4 ).
Spearman correlation analysis was performed to evaluate the relationship between the tested bone markers and some routine laboratory parameters. A statistically significant ( p < 0.0001) strong positive correlation with B2MG was found for periostin (r = 0.779), osteopontin (r = 0.697), and for sRANKL (r = 0.576). Bone marrow infiltration (BMI) by MPCs correlates significantly with sRANKL (r = 0.330, p = 0.0349) and periostin (r = 0.417, p = 0.0067) serum levels, while for osteopontin we did not find such a significant relation (r = 0.261, p = 0.0997). Spearman’s correlation analysis with creatinine was also performed to evaluate a possible relationship between the tested bone parameters and the renal function of MM patients. A significant positive correlation was found for the tested three parameters, stronger for periostin and osteopontin. Only periostin revealed a significant positive correlation with total protein. A significant negative association with albumin, as well with hemoglobin was found for all examined parameters ( Figure 5 and Supplementary Table S2 ).
3.2. Variation of sRANKL, Periostin, and Osteopontin Serum Levels in the Course of Treatment and According to the Response to Therapy
The medians and corresponding IQR of sRANKL, periostin, and osteopontin serum levels at different time points in the course of treatment are given in Supplementary Table S3 . Serum levels for sRANKL, periostin, and osteopontin gradually decreased in the course of treatment. A significant reduction in periostin was already observed at time point T1, while sRANKL and osteopontin were non-significantly lower than the baseline values (T0). For patients, not eligible for transplantation, the periostin levels continued to decrease and remained significantly lower at time point T2 compared to the T0 values ( p = 0.0024), while the sRANKL and osteopontin changes continued to not show any significant reduction. Patients who underwent ASCT, showed the lowest values for all measured proteins at TA, significantly different from those in T0 and T1 ( Figure 6 ).
Examining the tested parameter changes in the course of treatment in relation to the control values, we found significantly higher serum periostin at T1 ( p = 0.0005), while at T2 and TA it almost reached the control levels ( p = 0.1899 and p > 0.9999, respectively). The same phenomenon was observed for sRANKL and osteopontin only at the TA time point ( p = 0.5614 and p = 0.0996, respectively).
The response to therapy at all treatment points is summarized in Table 1 .
Table 2 represents the changes of sRANKL, periostin, and osteopontin serum levels depending on treatment response.
Patients with a CR and VGPR revealed significantly lower levels for the tested parameters vs. baseline levels (T0). In addition, periostin and osteopontin almost reached the control values, while sRANKL remained significantly higher ( p = 0.0036). On the other hand, sRANKL and osteopontin remained unchanged compared to T0 in PR and SD patients, while periostin was significantly decreased. Regarding the controls, the patients from this group revealed significantly higher values for all measured proteins ( Figure 7 ).
3.3. Predicting Power of sRANKL, Periostin, and Osteopontin
ROC analysis was performed to evaluate the diagnostic utility of the tested parameters for MBD assessment in NDMM patients ( Table 3 and Figure 8 ).
The area under the ROC curve for each of the tested parameters is above 0.85 ( p < 0.0001), revealing a relatively high distinguishing capacity between positive and negative cases of MBD in NDMM patients. All tested proteins revealed high diagnostic sensitivity and specificity at the most appropriate cut-off value.
Multiple linear regression analysis was used to estimate the relationship between each one of tested parameters as a dependent variable and several independent variables with which a significant correlation was established. For sRANKL linear regression was calculated with B2M, BMI, Hb, albumin, and creatinine. The regression model was statistically valid with F = 5.546, p = 0.0007 and adjusted R2 = 0.3624. Between the independent variables, only B2M revealed significant association (β = 0.5538, p = 0.0017) with sRANKL. The regression model performed for periostin included B2M, BMI, Hb, albumin, and creatinine and was also statistically significant (F = 12.27, p < 0.0001 and adjusted R2 = 0.5849). B2M, BMI, and albumin revealed significant associations (β = 25.04, p = 0.0164; β = 1.585, p = 0.0248 and β = −7.562, p = 0.0145, respectively). A statistically significant regression model was constructed for osteopontin and B2M, Hb, and creatinine (F = 10.73, p < 0.0001 and adjusted R2 = 0.4218). Only B2M revealed a significant association (β = 3.706, p = 0.0007) with osteopontin.
4. Discussion
The pathogenesis of MBD is multifactorial. Interactions of MPCs with various cell types such as lymphocytes, endothelial and stromal cells, as well as components of the extracellular bone marrow microenvironment play a crucial role in the development of MBD. In the last two decades, several cytokines and ECM proteins have been evaluated as biomarkers for the assessment of MBD. We analyzed the serum levels of sRANKL, periostin, and osteopontin in NDMM patients depending on the clinical stage and grade of MBD and their variations in the course of therapy to evaluate their potential as additional biomarkers for the assessment of MBD.
4.1. Baseline Serum Levels of sRANKL, Periostin, and Osteopontin in Newly Diagnosed Multiple Myeloma Patients
The role of sRANKL as a potent osteoclast activating factor is well established in animal and in vitro models [ 14 , 50 , 51 , 52 ]. mRNA and soluble RANKL have been observed in samples from MM patients, but not in chronic lymphocytic leukemia, indicating a unique requirement for RANKL in multiple myeloma [ 53 ]. In our study the sRANKL serum levels in NDMM patients at baseline were significantly higher than those in controls. In agreement with our results are the findings of most previous studies, which have demonstrated significantly higher values for sRANKL in NDMM patients vs. control subjects [ 15 , 16 , 17 , 54 ]. A few reports did not find a statistical difference in the serum levels of sRANKL in NDMM patients compared to controls, and no differences were observed with respect to disease stage and bone lesions [ 55 , 56 ]. The inconsistency of the abovementioned results could be explained by the different ELISA kits used for sRANKL determination. It is not surprising that RANKL, as a potent osteoclast activator, increases with osteoclast bone lesions as well as with the disease stage. In our study lower RANKL levels were associated with a small number of osteolytic lesions (<3, G1), whereas higher RANKL was related to advanced bone disease (G2). Similar relationships were observed for circulating RANKL and disease stage, increased in ISS-2 and ISS-3, and lower in ISS-1. Our findings agree with other studies reporting a significant increase of serum RANKL with advanced disease stage, grade of bone disease, and factors of disease activity such as B2MG and BMI [ 15 , 16 , 17 , 18 , 54 , 57 ].
The role of periostin in the pathogenesis of MM is poorly understood. In an experimental study it was suggested that fibroblast-like cells from the BM microenvironment are implicated in ECM remodeling and lead to the upregulation of various matrix proteins, including periostin, thus creating a favorable environment for MPC development. The upregulation takes place already at the level of MGUS and is more pronounced in MM [ 58 ]. Data from clinical studies regarding periostin are really scarce. Terpos et al. were the first to show significantly increased serum levels of periostin in NDMM and relapsed patients compared not only to healthy subjects, but also to MGUS and SMM patients. The authors found that serum periostin strongly correlated with B2MG and ISS-stages. The established correlations of periostin (positive with CTX, a bone resorption marker, and negative with bone alkaline phosphatase, a bone formation marker) suggest the role of periostin in the development of MBD. Moreover, patients with pathological fractures had markedly elevated periostin both in serum and BM plasma in comparison with all others. Patients with osteolytic lesions had significantly higher periostin in BM, but not in serum compared to those without osteolytic lesions [ 32 ]. Consistent with these data are our results which demonstrate a significant increase in serum periostin levels in NDMM patients vs. controls. We also established that periostin levels progressively increased both with the disease stages and the severity of bone involvement. In contrast with the finding of Terpos et al. we found significant differences in periostin serum levels in the G2 group vs. G1 group. The discordance may be due to the fact that patients with pathological fractures were also included in the G2 group. Also findings a moderate to strong positive correlation of serum periostin with B2MG, BMI, creatinine, and TP, as well as a negative correlation with albumin and Hb, all of which are associated with disease progression, we suggest the important role of periostin for MPC invasion in the BM and for MBD.
OPN, as the most abundant non-collagenous protein in the bone ECM, is an integral part of the BM microenvironment, where it regulates matrix interactions and cell adhesion [ 59 ]. For bone resorption, OPN-mediated attachment of OCs to the bone surface represents a crucial step. The role of OPN in MM is better studied than that of periostin, but different results have been reported. In most studies, the baseline OPN levels in symptomatic patients were significantly higher than those of controls [ 40 , 41 , 42 , 60 , 61 ]. We have also obtained similar results. On the contrary, Kang et al. did not find a significant difference in OPN levels between MM patients and healthy controls [ 62 ]. Moreover, in a recent study, even significantly lower OPN levels were found in stage I MM patients [ 63 ]. This discrepancy is probably due to the small patient sample, poorly defined patients’ disease stages, and the ELISA method used for osteopontin determination. Our data revealing statistically higher levels in ISS-III patients compared to ISS-I patients, as well in the G2 vs. G1 group, confirm the results of several studies that OPN levels reflect the progression of MM and MBD well [ 42 , 61 , 64 ]. In addition, we proved that patients with BMI ≥ 60% MPCs had significantly higher levels of OPN than those with BMI < 60% MPCs. OPN is produced not only by osteoclasts, but also by MPCs and in turn elevated OPN stimulates MPCs proliferation and exerts a proangiogenic effect on BM blood vessels [ 39 , 65 , 66 ], thus forming a vicious cycle of the self-maintenance and progression of the tumor process. Sfiridaki et al. reported a significant correlation between serum OPN and disease infiltration, as well with serum vascular endothelial growth factor (VEGF) and BM microvessel density (MVD) as markers of BM neovascularization [ 64 ]. In an Interesting in vitro study Robbiani et al. showed that high OPN expression correlates inversely with bone disease, explained by presence of maf translocations [ 67 ]. In the present study, the association of OPN with tumor burden was also proven by a strong positive correlation with B2MG and a weak negative correlation with albumin and hemoglobin. Similar results were reported by other researchers [ 41 , 60 , 61 , 64 ].
4.2. Variation of sRANKL, Periostin, and Osteopontin Serum Levels in the Course of Treatment and According to the Response to Therapy
Bortezomib-based regimens are most frequently used for MM [ 68 ]. In addition to an antimyeloma effect, Bortezomib (Velcade) induces mesenchyme stem cells to preferentially undergo osteoblastic differentiation and suppresses osteoclasts, ultimately leading to bone formation [ 69 , 70 ].
In the first clinical study concerning the effect of Bortezomib administration on bone remodeling markers, Terpos et al. have shown significantly reduced serum levels of sRANKL, DKK-1, CTX, and TRACP-5b after four cycles of therapy, irrespective of treatment response, thus leading to the normalization of bone remodeling in relapsed myeloma patients [ 71 ]. In several other clinical studies bortezomib-based therapies also have led to a significant reduction of serum RANKL [ 64 , 69 ]. Our results are consistent with the abovementioned findings showing a gradual decrease of sRANKL in the course of treatment. Moreover, we found significantly lower levels of this cytokine in NDMM patients with a CR and VGPR vs. those with a PR and SD.
In our study, circulating periostin showed a strong association with the course of treatment. In the different time points of chemotherapy or after transplantation, its serum levels were significantly lower than those at diagnosis. Moreover, the patients with a CR and VGPR revealed significantly lower periostin levels compared to those with a PR and in stable disease. To our knowledge, we are the first to demonstrate that circulating periostin reflects the effectiveness of therapy.
In comparison with sRANKL, considerably less data are available in the literature regarding the effect of therapy on serum OPN levels. Sfiridaki et al. have shown significantly lower OPN after chemotherapy [ 64 ]. Minarik et al. found not only lower post-chemotherapeutic OPN levels, but also significantly lower levels in patients with a deep response in comparison with initial OPN levels [ 42 ]. In our study, we examined OPN level variations in the course of treatment and found a gradual decrease with the lowest levels achieved 3 months after ASCT.
According to the ROC analysis, the three biomarkers show similar diagnostic reliability (AUC approximately 0.9, p < 0.0001). Depending on the ISS-stage, serum periostin and osteopontin differentiate the intermediate ISS-II, which was not observed for sRANKL ( Figure 2 ). According to treatment response, periostin most adequately reflects the treatment effect. In patients with a CR + VGPR, periostin serum levels decrease and almost reach control levels. In patients with a PR + SD, they remain elevated vs. the controls and a CR + VGPR but are lower than baseline levels. Based on these findings, we could hypothesize that serum periostin might be the most sensitive indicator among the tested parameters. Further studies involving larger cohorts should be conducted to confirm this hypothesis.
As these ECM proteins have been very scarcely studied in clinical settings, we consider the monitoring of OPN, PON, and RANKL serum levels in NDMM patients and the effect of therapy on their serum levels to constitute the strengths of our study. There are also some limitations in our study. One limitation is the small number of studied patients. Another is that we did not examine the changes in osteoprotegerin (OPG) levels in NDMM patients and its interrelations with the proteins that we tested, especially with sRANKL.
5. Conclusions
MBD has a significant impact on patient quality of life. The discovery and validation of sensitive serum bone markers would aid in the prediction of skeletal complications and their early treatment, improving patient outcomes and reducing the burden on healthcare systems. The present study demonstrates activated osteoclastogenesis, evident by elevated levels of bone resorption cytokines sRANKL, periostin, and osteopontin in NDMM. Moreover, their increased levels strongly correlate with the MM stage and the grade of MBD. Studying the dynamics of these proteins, we demonstrated a significant decrease during treatment, more pronounced after ASCT. In the context of these findings, sRANKL, periostin, and osteopontin could be promising markers for monitoring MBD in MM and the effect of treatment.
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Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers15235562/s1 . Table S1: Patients’ demographic and clinical characteristics at baseline. Table S2: Correlations of sRANKL, periostin and osteopontin with some laboratory parameters; Table S3: Serum values of sRANKL, Periostin and Osteopontin, measured at different time points.
Click here for additional data file.
Author Contributions
Conceptualization, D.G., V.G. and B.G.; methodology, D.G., B.G., I.M. and V.G.; validation, V.G., M.N., N.N. and M.P.; formal analysis, V.G. and D.G.; investigation, V.G., M.N., N.N. and M.P.; resources, V.G., M.N., N.N. and M.P.; data curation, V.G.; writing—original draft preparation, V.G. and D.G.; writing—review and editing, D.G., B.G. and I.M.; visualization, V.G. and D.G.; supervision, I.M. and B.G.; project administration, D.G. and B.G.; funding acquisition, B.G. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of the Medical University of Varna (protocol No 94/25.06.2020).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data presented in this study are available in this article.
Conflicts of Interest
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.
References
1. Padala S.A. Barsouk A. Barsouk A. Rawla P. Vakiti A. Kolhe R. Kota V. Ajebo G.H. Epidemiology, Staging, and Management of Multiple Myeloma Med. Sci. 2021 9 3 10.3390/medsci9010003 33498356 PMC7838784
2. Rajkumar S.V. Multiple Myeloma: Every Year a New Standard? Hematol. Oncol. 2019 37 62 65 10.1002/hon.2586 31187526 PMC6570407
3. Terpos E. Ntanasis-Stathopoulos I. Gavriatopoulou M. Pathogenesis of Bone Disease in Multiple Myeloma: From Bench to Bedside Blood Cancer J. 2018 8 7 10.1038/s41408-017-0037-4 29330358 PMC5802524
4. Hagiwara M. Panjabi S. Delea T. Yucel E. Fonseca R. Burden of Disease Progression in Patients with Multiple Myeloma in the US Leuk. Lymphoma 2020 61 47 55 10.1080/10428194.2019.1648802 31389283
5. Kumar R. Godavarthy P.S. Krause D.S. The Bone Marrow Microenvironment in Health and Disease at a Glance J. Cell Sci. 2018 131 jcs201707 10.1242/jcs.201707 29472498
6. Bernstein Z.S. Kim E.B. Raje N. Bone Disease in Multiple Myeloma: Biologic and Clinical Implications Cells 2022 11 2308 10.3390/cells11152308 35954151 PMC9367243
7. Mukkamalla S.K.R. Malipeddi D. Myeloma Bone Disease: A Comprehensive Review Int. J. Mol. Sci. 2021 22 6208 10.3390/ijms22126208 34201396 PMC8227693
8. Gau Y.-C. Yeh T.-J. Hsu C.-M. Hsiao S.Y. Hsiao H.-H. Pathogenesis and Treatment of Myeloma-Related Bone Disease Int. J. Mol. Sci. 2022 23 3112 10.3390/ijms23063112 35328533 PMC8951013
9. Mansour A. Wakkach A. Blin-Wakkach C. Emerging Roles of Osteoclasts in the Modulation of Bone Microenvironment and Immune Suppression in Multiple Myeloma Front. Immunol. 2017 8 954 10.3389/fimmu.2017.00954 28848556 PMC5554508
10. Kim J.-M. Lin C. Stavre Z. Greenblatt M.B. Shim J.-H. Osteoblast-Osteoclast Communication and Bone Homeostasis Cells 2020 9 2073 10.3390/cells9092073 32927921 PMC7564526
11. Tobeiha M. Moghadasian M.H. Amin N. Jafarnejad S. RANKL/RANK/OPG Pathway: A Mechanism Involved in Exercise-Induced Bone Remodeling BioMed Res. Int. 2020 2020 6910312 10.1155/2020/6910312 32149122 PMC7053481
12. Raje N.S. Bhatta S. Terpos E. Role of the RANK/RANKL Pathway in Multiple Myeloma Clin. Cancer Res. 2019 25 12 20 10.1158/1078-0432.CCR-18-1537 30093448
13. Wu X. Li F. Dang L. Liang C. Lu A. Zhang G. RANKL/RANK System-Based Mechanism for Breast Cancer Bone Metastasis and Related Therapeutic Strategies Front. Cell Dev. Biol. 2020 8 76 10.3389/fcell.2020.00076 32117996 PMC7026132
14. Buckle C.H. De Leenheer E. Lawson M.A. Yong K. Rabin N. Perry M. Vanderkerken K. Croucher P.I. Soluble Rank Ligand Produced by Myeloma Cells Causes Generalised Bone Loss in Multiple Myeloma PLoS ONE 2012 7 e41127 10.1371/journal.pone.0041127 22952578 PMC3430669
15. Terpos E. Szydlo R. Apperley J.F. Hatjiharissi E. Politou M. Meletis J. Viniou N. Yataganas X. Goldman J.M. Rahemtulla A. Soluble Receptor Activator of Nuclear Factor κB Ligand–Osteoprotegerin Ratio Predicts Survival in Multiple Myeloma: Proposal for a Novel Prognostic Index Blood 2003 102 1064 1069 10.1182/blood-2003-02-0380 12689925
16. Politou M. Terpos E. Anagnostopoulos A. Szydlo R. Laffan M. Layton M. Apperley J.F. Dimopoulos M. Rahemtulla A. Role of Receptor Activator of Nuclear Factor-kappa B Ligand (RANKL), Osteoprotegerin and Macrophage Protein 1-alpha (MIP-1a) in Monoclonal Gammopathy of Undetermined Significance (MGUS) Br. J. Haematol. 2004 126 686 689 10.1111/j.1365-2141.2004.05092.x 15327520
17. Goranova-Marinova V. Goranov S. Pavlov P. Tzvetkova T. Serum Levels of OPG, RANKL and RANKL/OPG Ratios in Newly-Diagnosed Patients with Multiple Myeloma. Clinical Correlations Haematologica 2007 92 1000 1001 10.3324/haematol.10943 17606458
18. Jakob C. Goerke A. Terpos E. Sterz J. Heider U. Kühnhardt D. Ziefle S. Kleeberg L. Mieth M. Von Metzler I. Serum Levels of Total-RANKL in Multiple Myeloma Clin. Lymphoma Myeloma 2009 9 430 435 10.3816/CLM.2009.n.085 19951882
19. Cadieux B. Coleman R. Jafarinasabian P. Lipton A. Orlowski R.Z. Saad F. Scagliotti G.V. Shimizu K. Stopeck A. Experience with Denosumab (XGEVA ® ) for Prevention of Skeletal-Related Events in the 10 Years after Approval J. Bone Oncol. 2022 33 100416 10.1016/j.jbo.2022.100416 35242510 PMC8857591
20. Wang Z. An J. Zhu D. Chen H. Lin A. Kang J. Liu W. Kang X. Periostin: An Emerging Activator of Multiple Signaling Pathways J. Cell Commun. Signal. 2022 16 515 530 10.1007/s12079-022-00674-2 35412260 PMC9733775
21. Cobo T. Viloria C.G. Solares L. Fontanil T. González-Chamorro E. De Carlos F. Cobo J. Cal S. Obaya A.J. Role of Periostin in Adhesion and Migration of Bone Remodeling Cells PLoS ONE 2016 11 e0147837 10.1371/journal.pone.0147837 26809067 PMC4725750
22. Bonnet N. Garnero P. Ferrari S. Periostin Action in Bone Mol. Cell. Endocrinol. 2016 432 75 82 10.1016/j.mce.2015.12.014 26721738
23. Kim B.-J. Lee S.H. Koh J.-M. Potential Biomarkers to Improve the Prediction of Osteoporotic Fractures Endocrinol. Metab. 2020 35 55 63 10.3803/EnM.2020.35.1.55 32207264 PMC7090300
24. Rousseau J.C. Sornay-Rendu E. Bertholon C. Chapurlat R. Garnero P. Serum Periostin Is Associated With Fracture Risk in Postmenopausal Women: A 7-Year Prospective Analysis of the OFELY Study J. Clin. Endocrinol. Metab. 2014 99 2533 2539 10.1210/jc.2013-3893 24628551
25. Sakellariou G.T. Anastasilakis A.D. Bisbinas I. Oikonomou D. Gerou S. Polyzos S.A. Sayegh F.E. Circulating Periostin Levels in Patients with AS: Association with Clinical and Radiographic Variables, Inflammatory Markers and Molecules Involved in Bone Formation Rheumatology 2015 54 908 914 10.1093/rheumatology/keu425 25349442
26. Kapoor S. Periostin and Its Emerging Role in Systemic Carcinogenesis Osteoporos. Int. 2014 25 1423 1424 10.1007/s00198-013-2614-0 24477553
27. Underwood T.J. Hayden A.L. Derouet M. Garcia E. Noble F. White M.J. Thirdborough S. Mead A. Clemons N. Mellone M. Cancer-associated Fibroblasts Predict Poor Outcome and Promote Periostin-dependent Invasion in Oesophageal Adenocarcinoma J. Pathol. 2015 235 466 477 10.1002/path.4467 25345775 PMC4312957
28. Wu G. Wang X. Zhang X. Clinical Implications of Periostin in the Liver Metastasis of Colorectal Cancer Cancer Biother. Radiopharm. 2013 28 298 302 10.1089/cbr.2012.1374 23347152
29. Kim G.-E. Lee J.S. Park M.H. Yoon J.H. Epithelial Periostin Expression Is Correlated with Poor Survival in Patients with Invasive Breast Carcinoma PLoS ONE 2017 12 e0187635 10.1371/journal.pone.0187635 29161296 PMC5697858
30. Tilman G. Mattiussi M. Brasseur F. Van Baren N. Decottignies A. Human Periostin Gene Expression in Normal Tissues, Tumors and Melanoma: Evidences for Periostin Production by Both Stromal and Melanoma Cells Mol. Cancer 2007 6 80 10.1186/1476-4598-6-80 18086302 PMC2222651
31. Sasaki H. Auclair D. Kaji M. Fukai I. Kiriyama M. Yamakawa Y. Fujii Y. Chen L.B. Serum Level of the Periostin, a Homologue of an Insect Cell Adhesion Molecule, in Thymoma Patients Cancer Lett. 2001 172 37 42 10.1016/S0304-3835(01)00633-4 11595127
32. Terpos E. Christoulas D. Kastritis E. Bagratuni T. Gavriatopoulou M. Roussou M. Papatheodorou A. Eleutherakis-Papaiakovou E. Kanellias N. Liakou C. High Levels of Periostin Correlate with Increased Fracture Rate, Diffuse MRI Pattern, Abnormal Bone Remodeling and Advanced Disease Stage in Patients with Newly Diagnosed Symptomatic Multiple Myeloma Blood Cancer J. 2016 6 e482 10.1038/bcj.2016.90 27716740 PMC5098262
33. Wai P.Y. Kuo P.C. Osteopontin: Regulation in Tumor Metastasis Cancer Metastasis Rev. 2008 27 103 118 10.1007/s10555-007-9104-9 18049863
34. Kaleta B. Boguska A. Sildenafil, a Phosphodiesterase Type 5 Inhibitor, Downregulates Osteopontin in Human Peripheral Blood Mononuclear Cells Arch. Immunol. Ther. Exp. 2017 65 347 353 10.1007/s00005-017-0455-9 28210757 PMC5511304
35. Denhardt D.T. Mistretta D. Chambers A.F. Krishna S. Porter J.F. Raghuram S. Rittling S.R. Transcriptional Regulation of Osteopontin and the Metastatic Phenotype: Evidence for a Ras-Activated Enhancer in the Human OPN Promoter Clin. Exp. Metastasis 2003 20 77 84 10.1023/A:1022550721404 12650610
36. Cho H.-J. Cho H.-J. Kim H.-S. Osteopontin: A Multifunctional Protein at the Crossroads of Inflammation, Atherosclerosis, and Vascular Calcification Curr. Atheroscler. Rep. 2009 11 206 213 10.1007/s11883-009-0032-8 19361352
37. Kim J.-M. Kim M.Y. Lee K. Jeong D. Distinctive and Selective Route of PI3K/PKCα-PKCδ/RhoA-Rac1 Signaling in Osteoclastic Cell Migration Mol. Cell. Endocrinol. 2016 437 261 267 10.1016/j.mce.2016.08.042 27576187
38. Walker C.G. Dangaria S. Ito Y. Luan X. Diekwisch T.G.H. Osteopontin Is Required for Unloading-Induced Osteoclast Recruitment and Modulation of RANKL Expression during Tooth Drift-Associated Bone Remodeling, but Not for Super-Eruption Bone 2010 47 1020 1029 10.1016/j.bone.2010.08.025 20828639 PMC2970729
39. Abe M. Hiura K. Wilde J. Shioyasono A. Moriyama K. Hashimoto T. Kido S. Oshima T. Shibata H. Ozaki S. Osteoclasts Enhance Myeloma Cell Growth and Survival via Cell-Cell Contact: A Vicious Cycle between Bone Destruction and Myeloma Expansion Blood 2004 104 2484 2491 10.1182/blood-2003-11-3839 15187021
40. Saeki Mima Y.T. Ishii T. Ogata A. Kobayashi H. Ohshima S. Ishida T. Tabunoki Y. Kitayama H. Mizuki M. Katada Y. Enhanced Production of Osteopontin in Multiple Myeloma: Clinical and Pathogenic Implications Br. J. Haematol. 2003 123 263 270 10.1046/j.1365-2141.2003.04589.x 14531907
41. Standal T. Hjorth-Hansen H. Rasmussen T. Dahl I.M.S. Lenhoff S. Brenne A.-T. Seidel C. Baykov V. Waage A. Børset M. Osteopontin Is an Adhesive Factor for Myeloma Cells and Is Found in Increased Levels in Plasma from Patients with Multiple Myeloma Haematologica 2004 89 174 182 15003892
42. Minarik J. Pika T. Bacovsky J. Petrova P. Langova K. Scudla V. Prognostic Value of Hepatocyte Growth Factor, Syndecan-1, and Osteopontin in Multiple Myeloma and Monoclonal Gammopathy of Undetermined Significance Sci. World J. 2012 2012 356128 10.1100/2012/356128 22629140 PMC3351092
43. Tanaka Y. Abe M. Hiasa M. Oda A. Amou H. Nakano A. Takeuchi K. Kitazoe K. Kido S. Inoue D. Myeloma Cell-Osteoclast Interaction Enhances Angiogenesis Together with Bone Resorption: A Role for Vascular Endothelial Cell Growth Factor and Osteopontin Clin. Cancer Res. 2007 13 816 823 10.1158/1078-0432.CCR-06-2258 17289872
44. Rajkumar S.V. Updated Diagnostic Criteria and Staging System for Multiple Myeloma Am. Soc. Clin. Oncol. Educ. Book 2016 36 e418 e423 10.1200/EDBK_159009 27249749
45. Greipp P.R. Miguel J.S. Durie B.G.M. Crowley J.J. Barlogie B. Bladé J. Boccadoro M. Child J.A. Avet-Loiseau H. Kyle R.A. International Staging System for Multiple Myeloma J. Clin. Oncol. 2005 23 3412 3420 10.1200/JCO.2005.04.242 15809451
46. Gerov V. Gerova D. Micheva I. Nikolova M. Mihaylova G. Galunska B. Dynamics of Bone Disease Biomarkers Dickkopf-1 and Sclerostin in Patients with Multiple Myeloma JCM 2023 12 4440 10.3390/jcm12134440 37445475 PMC10342782
47. Kumar S. Paiva B. Anderson K.C. Durie B. Landgren O. Moreau P. Munshi N. Lonial S. Bladé J. Mateos M.-V. International Myeloma Working Group Consensus Criteria for Response and Minimal Residual Disease Assessment in Multiple Myeloma Lancet Oncol. 2016 17 e328 e346 10.1016/S1470-2045(16)30206-6 27511158
48. Rajkumar S.V. Dimopoulos M.A. Palumbo A. Blade J. Merlini G. Mateos M.-V. Kumar S. Hillengass J. Kastritis E. Richardson P. International Myeloma Working Group Updated Criteria for the Diagnosis of Multiple Myeloma Lancet Oncol. 2014 15 e538 e548 10.1016/S1470-2045(14)70442-5 25439696
49. Al Saleh A.S. Parmar H.V. Visram A. Muchtar E. Buadi F.K. Go R.S. Dispenzieri A. Kapoor P. Warsame R. Lacy M.Q. Increased Bone Marrow Plasma-Cell Percentage Predicts Outcomes in Newly Diagnosed Multiple Myeloma Patients Clin. Lymphoma Myeloma Leuk. 2020 20 596 601 10.1016/j.clml.2020.03.012 32360276 PMC7484262
50. Pearse R.N. Sordillo E.M. Yaccoby S. Wong B.R. Liau D.F. Colman N. Michaeli J. Epstein J. Choi Y. Multiple Myeloma Disrupts the TRANCE/ Osteoprotegerin Cytokine Axis to Trigger Bone Destruction and Promote Tumor Progression Proc. Natl. Acad. Sci. USA 2001 98 11581 11586 10.1073/pnas.201394498 11562486 PMC58772
51. Sordillo E.M. Pearse R.N. RANK-Fc: A Therapeutic Antagonist for RANK-L in Myeloma Cancer 2003 97 802 812 10.1002/cncr.11134 12548579
52. Deleenheer E. Evidence of a Role for RANKL in the Development of Myeloma Bone Disease Curr. Opin. Pharmacol. 2004 4 340 346 10.1016/j.coph.2004.03.011 15251126
53. Schmiedel B.J. Scheible C.A. Nuebling T. Kopp H.-G. Wirths S. Azuma M. Schneider P. Jung G. Grosse-Hovest L. Salih H.R. RANKL Expression, Function, and Therapeutic Targeting in Multiple Myeloma and Chronic Lymphocytic Leukemia Cancer Res. 2013 73 683 694 10.1158/0008-5472.CAN-12-2280 23139212
54. Sfiridaki K. Pappa C.A. Tsirakis G. Kanellou P. Kaparou M. Stratinaki M. Sakellaris G. Kontakis G. Alexandrakis M.G. Angiogenesis-Related Cytokines, RANKL, and Osteoprotegerin in Multiple Myeloma Patients in Relation to Clinical Features and Response to Treatment Mediators Inflamm. 2011 2011 867576 10.1155/2011/867576 21941412 PMC3175728
55. Kraj M. Owczarska K. Sokołowska U. Centkowski P. Pogłód R. Kruk B. Correlation of Osteoprotegerin and sRANKL Concentrations in Serum and Bone Marrow of Multiple Myeloma Patients Arch. Immunol. Ther. Exp. 2005 53 454 464 16314829
56. Schütt P. Rebmann V. Brandhorst D. Wiefelspütz J. Ebeling P. Opalka B. Seeber S. Nowrousian M.R. Moritz T. Grosse-Wilde H. The Clinical Significance of Soluble Human Leukocyte Antitgen Class-I, ICTP, and RANKL Molecules in Multiple Myeloma Patients Hum. Immunol. 2008 69 79 87 10.1016/j.humimm.2008.01.006 18361931
57. Heider U. Langelotz C. Jakob C. Zavrski I. Fleissner C. Eucker J. Possinger K. Hofbauer L.C. Sezer O. Expression of Receptor Activator of Nuclear Factor kappaB Ligand on Bone Marrow Plasma Cells Correlates with Osteolytic Bone Disease in Patients with Multiple Myeloma Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2003 9 1436 1440 12684416
58. Slany A. Haudek-Prinz V. Meshcheryakova A. Bileck A. Lamm W. Zielinski C. Gerner C. Drach J. Extracellular Matrix Remodeling by Bone Marrow Fibroblast-like Cells Correlates with Disease Progression in Multiple Myeloma J. Proteome Res. 2014 13 844 854 10.1021/pr400881p 24256566
59. Lamort A.-S. Giopanou I. Psallidas I. Stathopoulos G.T. Osteopontin as a Link between Inflammation and Cancer: The Thorax in the Spotlight Cells 2019 8 815 10.3390/cells8080815 31382483 PMC6721491
60. Dizdar O. Barista I. Kalyoncu U. Karadag O. Hascelik G. Cila A. Pinar A. Celik I. Kars A. Tekuzman G. Biochemical Markers of Bone Turnover in Diagnosis of Myeloma Bone Disease Am. J. Hematol. 2007 82 185 191 10.1002/ajh.20794 17022050
61. Valković T. Babarović E. Lučin K. Štifter S. Aralica M. Pećanić S. Seili-Bekafigo I. Duletić-Načinović A. Nemet D. Jonjić N. Plasma Levels of Osteopontin and Vascular Endothelial Growth Factor in Association with Clinical Features and Parameters of Tumor Burden in Patients with Multiple Myeloma BioMed Res. Int. 2014 2014 513170 10.1155/2014/513170 24995304 PMC4065766
62. Kang S.Y. Lee J.J. Lee W.I. Clinical Significance of Serum Osteopontin in Patients with Multiple Myeloma Ann. Lab. Med. 2007 27 400 405 10.3343/kjlm.2007.27.6.400 18160829
63. Maaroufi A. Khadem-Ansari M.-H. Khalkhali H.-R. Rasmi Y. Serum Levels of Bone Sialoprotein, Osteopontin, and Β2-Microglobulin in Stage I of Multiple Myeloma J. Cancer Res. Ther. 2020 16 98 101 10.4103/jcrt.JCRT_666_16 32362616
64. Sfiridaki A. Miyakis S. Pappa C. Tsirakis G. Alegakis A. Kotsis V. Stathopoulos E. Alexandrakis M. Circulating Osteopontin: A Dual Marker of Bone Destruction and Angiogenesis in Patients with Multiple Myeloma J. Hematol. Oncol. 2011 4 22 10.1186/1756-8722-4-22 21548993 PMC3102033
65. Colla S. Morandi F. Lazzaretti M. Rizzato R. Lunghi P. Bonomini S. Mancini C. Pedrazzoni M. Crugnola M. Rizzoli V. Human Myeloma Cells Express the Bone Regulating Gene Runx2/Cbfa1 and Produce Osteopontin That Is Involved in Angiogenesis in Multiple Myeloma Patients Leukemia 2005 19 2166 2176 10.1038/sj.leu.2403976 16208410
66. Babarović E. Valković T. Budisavljević I. Balen I. Štifter S. Duletić-Načinović A. Lučin K. Jonjić N. The Expression of Osteopontin and Vascular Endothelial Growth Factor in Correlation with Angiogenesis in Monoclonal Gammopathy of Undetermined Significance and Multiple Myeloma Pathol.-Res. Pract. 2016 212 509 516 10.1016/j.prp.2015.11.021 26997492
67. Robbiani D.F. Colon K. Ely S. Ely S. Chesi M. Bergsagel P.L. Osteopontin Dysregulation and Lytic Bone Lesions in Multiple Myeloma Hematol. Oncol. 2007 25 16 20 10.1002/hon.803 17044113
68. Liu Z. Zeng Q. Xiang B. Bortezomib-Based Regimens Improve the Prognosis of Newly Diagnosed MM Patients with Chromosomal Aberrations except for Del(17q13): A Retrospective Study from a Single Center Medicine 2021 100 e25834 10.1097/MD.0000000000025834 33950994 PMC8104214
69. Eom K.-S. Kim S.J. Lee J.-J. Suh C. Kim J.S. Yoon S.-S. Kim B.S. Kang H.J. Choi Y.J. Kim C.S. Changes in Osteoblastic Activity in Patient Who Received Bortezomib as Second Line Treatment for Plasma Cell Myeloma: A Prospective Multicenter Study BioMed Res. Int. 2014 2014 245247 10.1155/2014/245247 25050331 PMC4094867
70. Lin L. Chen D. Xiang Z.-F. Pei R.-Z. Zhang P.-S. Liu X.-H. Du X.-H. Lu Y. Bortezomib Could Down-Regulate the Expression of RANKL, Inhibit Cell Proliferation and Induce Cell Apoptosis in the Human Myeloma Cell Line RPMI 8226 by Activating Casepase-3 Cancer Biomark. 2017 20 217 224 10.3233/CBM-170584 28869453
71. Terpos E. Heath D.J. Rahemtulla A. Zervas K. Chantry A. Anagnostopoulos A. Pouli A. Katodritou E. Verrou E. Vervessou E.-C. Bortezomib Reduces Serum Dickkopf-1 and Receptor Activator of Nuclear Factor-? B Ligand Concentrations and Normalises Indices of Bone Remodelling in Patients with Relapsed Multiple Myeloma Br. J. Haematol. 2006 135 688 692 10.1111/j.1365-2141.2006.06356.x 17107351