Diagnostic and prognostic value of bone metabolism biomarkers in newly diagnosed plasma cell myeloma

Diagnostic and prognostic value of bone metabolism biomarkers in newly diagnosed plasma cell myeloma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Diagnostic and prognostic value of bone metabolism biomarkers in newly diagnosed plasma cell myeloma Maciej Korpysz, Alicja Bogdanowicz-Żeleźniak, Anna Kowalska-Kępczyńska, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8388907/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Plasma cell myeloma (PCM) is the second most common type of haematological cancer. Lytic lesions and bone pain are among the most common symptoms of PCM. The study aimed to evaluated the diagnostic and prognostic value of markers of bone metabolism, i.e. activin A, Dkk-1, GDF-15, β-CTX and sclerostin in patients with PCM. The study involved 76 patients with PCM and 25 healthy volunteers. The concentration of above markers was determined by ELISA method. Patients showed significantly higher pretreatment concentration of activin A, Dkk-1, GDF-15 and β-CTX compared to the control. The number of bone lesions (based on X-ray) showed a significant correlation with the concentration of activin A (rho = 0.276), Dkk-1 (rho = 0.598), GDF-15 (rho = 0.489), and β-CTX (rho = 0.381). The ROC curves analyses revealed that the determination of Dkk-1 was characterized by the highest diagnostic utility in the detection of osteolytic lesions (AUC = 0.81). Moreover the high levels of Dkk-1 were significantly associated with poor PFS (HR = 1.75) and OS (HR = 3.04). The assessment of Dkk-1 concentration may become a new biomarker useful in the detection and monitoring of bone lesions and may indicate an unfavourable prognosis in PCM. Health sciences/Biomarkers Biological sciences/Cancer Health sciences/Diseases Health sciences/Medical research bone markers diagnosis dickkopf-1 (Dkk-1) plasma cell myeloma prognosis Figures Figure 1 Figure 2 Figure 3 Introduction Plasma cell myeloma (PCM) is the second most common hematological malignancy, accounting for 1% of all cancers, with a high incidence (≥ 4/100,000/year) and mortality (1.8/100,000/year) [ 1 ]. Typical symptoms include hypercalcemia (C), renal dysfunction (R), anemia (A), and lytic lesions with bone pain (B) - collectively known as CRAB [ 2 ]. Myeloma bone disease (MBD) affects approximately 80% of patients, often leading to pathological fractures or spinal cord compression. PCM cells interact with bone marrow stromal cells to increase expression of receptor activator of nuclear factor κB ligand (RANKL), stimulating osteoclast activity, while reducing osteoprotegerin (OPG), a natural RANKL inhibitor [ 3 ]. Additionally, osteoblast function is inhibited due to secretion of Wnt pathway antagonists like dickkopf-related protein 1 (Dkk-1) and secreted frizzled-related protein 2 (sFRP2) by myeloma cells, disrupting bone formation and remodeling [ 4 ]. This results in an imbalance between excessive bone resorption and impaired formation [ 5 ], along with a reduced number of healthy osteocytes correlated with disease stage. Bone turnover markers (BTMs), such as C-, N-terminal telopeptides of type I collagen (CTX, NTX) and bone alkaline phosphatase (bALP), osteocalcin, are commonly used to assess bone metabolism [ 6 ]. Recent studies highlight new molecules that may serve as BTMs in PCM. Growth differentiation factor 15 (GDF-15) negatively correlates with bone formation markers like alkaline phosphatase, indicating its involvement in impaired bone mass homeostasis [ 7 ]. Activin A, elevated in both serum and bone marrow of patients with lytic lesions, inhibits bone morphogenetic protein (BMP) signaling [ 3 ]. Dkk-1 and sclerostin levels also correlate with the presence and severity of bone lesions according to the International Staging System (ISS), making them promising markers [ 8 ]. The aim of this study was to evaluate the usefulness of activin A, Dkk-1, GDF-15, β-CTX, and sclerostin as potential biomarkers of bone lesions and prognostic factors in PCM. Materials and Methods Study group The study group consisted of 76 patients with newly diagnosed PCM, treated between April 2014 and April 2017at the Department of Hematooncology and Bone Marrow Transplantation of the Independent Public Clinical Hospital No. 1 in Lublin. Patients were diagnosed according the International Myeloma Working Group (IMWG). Plasma cell infiltration in the bone marrow was marked as positive when more than 10% of plasma cells in the bone marrow sample were noted. Inclusion criteria: newly diagnosed PCM based on IMWG recommendations; patients of both sexes over the age of 18; patients who gave their written informed consent to participate after having read the information about the study; patients who had undergone an X-ray examination at the time of diagnosis to assess the extent of osteolytic lesions in the bones. Exclusion criteria: coexistence of another malignant disease; genetic or endocrine - related metabolic bone diseases; general poor condition of the patient; high creatinine concentration (> 3 mg/dl); previous antimyeloma treatment. Patients diagnosed with PCM were treated with various therapeutic regimens, most of which were based on thalidomide, bortezomib or contained both thalidomide and bortezomib. Patients with a satisfactory response to the treatment and eligible for autologous hematopoietic stem cell transplantation (aHSCT) underwent the procedure (Table 1 ) . The median follow-up time of the patients from the time of inclusion in the study was 43 months. In 81.6% of the patients, disease progression was observed during follow-up, while 56.6% of the patients died. Control group The control group consisted of 25 healthy volunteers, who were matched in age and gender to the study group. Before the blood was taken, the participants were asked to complete a questionnaire about their individual health condition. Based on the survey results, participants who did not take medication affecting bone metabolism, had not suffered any fractures recently, and had not been diagnosed with osteoporosis or other skeletal disorders were qualified for the control group. Methods Assessment of cytogenetic changes cIg-FISH analysis Adverse cytogenetic abnormalities characteristic of PCM were assessed by simultaneous staining of cytoplasmic immunoglobulins and fluorescense in situ hybridization (cIg-FISH) method according to the protocol described previously [9]. The following commercially available FISH probes were used: Vysis TP53/CEP 17 FISH Probe Kit, Vysis IGH/FGFR3 DF FISH Probe Kit and Vysis IGH/MAF DF FISH Probe Kit (Abbott GmBH, Wiesbaden, Germany). The analysis was performed on Olympus BX51 microscope (Olympus Europe, Hamburg, Germany) by counting 100 AMCA-positive plasma cells to determine the frequency of each aberration. Cut-off levels were 20% for deletion probes and 10% for dual fusion probes, according to the European Myeloma Network recommendations. Assessment of laboratory parameters including bone metabolism regulatory biomarkers The study material was venous blood (10 ml) collected before the start of treatment from patients included in the study and the control group into tubes without anticoagulant. After the blood had clotted (20–30 min.), the sample was centrifuged (10 min. at 2500 rpm), and then the serum obtained was stored at -80°C until the analyses were performed. Activin A, Dkk-1 and GDF-15 concentrations were measured using enzyme-linked immunosorbent assay (ELISA) kits from R&D Systems (catalog numbers: DAC00B, DKK100B and DGD150, respectively), while sclerostin using kit from TECOmedical Group (catalog number: TE1023-HS). All measurements were carried out according to the manufacturer's test protocols. The absorbance was read at the appropriate wavelength using a spectrophotometric reader, model 800 TS (BioTek, Winooski, USA). The β-CTX concentration was determined by electrochemiluminescence immunoassay (ECLIA) using a Cobas e411 analyzer (Roche Diagnostics, Mannheim, Germany) and a suitable Roche β CrossLaps/serum reagent kit. Assessment of treatment response The treatment response was assessed according to the current IMWG criteria [10]. In a group of 25 patients with at least a very good treatment response (14 patients with VGPR and 11 with CR, respectively) after 4–6 cycles of therapy, the indicators of bone metabolism regulation were re-measured. Assessment of bone lesions In order to assess bone lesions, a radiological examination (X-ray) was performed in all patients (cervical, thoracic, lumbar spine, femurs, humerus, skull and pelvis). A general overview of the chest and the other body parts where the patient reported pain was also applied. The study group was divided into 3 subgroups depending on the number of bone lesions. Group I consisted of patients with no bone lesions, group II consisted of patients with limited lesions in 1–3 bones, while group III consisted of patients with extensive bone lesions in more than three bones or with pathological fractures. All experiments were conducted in accordance with applicable guidelines and regulations. Informed consent was obtained from all study participants and/or their legal guardians. The Bioethics Committee at the Medical University of Lublin granted approval for the study under No. KE-0254/111/2014. Statistical analysis The statistical analysis was performed using MedCalc software version 15.8 PL and GraphPad Prism. The D'Agostino-Pearson test was used to assess whether the studied variables showed a normal distribution. The distributions of the analyzed continuous variables were not normal, therefore non-parametric tests were used to compare the obtained data (Mann-Whitney U test for independent groups and Wilcoxon test for dependent groups). The Kruskal-Wallis ANOVA test was used to compare several independent groups, and if significant differences were found, the data were further analyzed using an appropriate post-hoc test. The correlation between the studied biomarkers and the number of bone lesions was performed using Spearman's rank correlation. ROC (receiver operating characteristic) curves were also plotted and the area under the curves (AUC) was calculated to assess the diagnostic usefulness of studied biomarkers in differentiating the lack or presence of bone lesions. The progression-free survival (PFS) was defined as the time between diagnosis and the occurrence of progression or the most recent follow-up. Overall survival (OS) was defined as the time between diagnosis and death or the most recent follow-up. A univariate analysis of the impact of the examined variables on PFS and OS was performed using the log-rank test. Kaplan-Meier estimation method was used to generate survival curves. In the multivariate analysis of the impact of the examined variables on survival, Cox's proportional hazard models were used (variables that remained significant after the use of the backward elimination method - were included in multivariable models). In all of the statistical analysis, a value of p ≤ 0.05 was considered to be statistically significant. Results Comparison of the concentration of bone metabolism regulatory biomarkers in the study and control groups Statistical analysis showed significantly higher activin A, Dkk-1, GDF-15 and β-CTX in the study group compared to the control. However, in the case of sclerostin, observed differences were not significant ( Supplementary Table S1 ). Assessment of the relationship between bone metabolism regulatory biomarkers and the number of bone lesions A significantly higher Dkk-1 concentrations were observed in patients with multiple bone lesions compared to those with a limited number or no lesions. Moreover, significantly higher Dkk-1 concentrations were noted in patients with a limited number of bone lesions compared to those with no lesions. Significantly higher GDF-15 and β-CTX concentrations were found in patients with multiple bone lesions compared to those with a limited number or no lesions. Detailed data regarding the relationship between bone metabolism regulatory biomarkers and the number of bone lesions are included in Table 2. Assessment of the diagnostic value of bone metabolism regulatory biomarkers in the detection of bone lesions Supplementary Figure S1 shows a comparison of the AUC values describing the diagnostic usefulness of the studied indicators of bone metabolism in the detection of bone lesions, while Fig. 1 shows the ROC curves for the parameters of metabolism, significantly differentiating patients with current bone lesions from those with no lesions. The highest diagnostic accuracy in detecting bone lesions was obtained for Dkk-1 measurements (AUC = 0.81; cut off: >2046), and the lowest for sclerostin (AUC = 0.54; cut off: ≤0.489) ( Supplementary Table S2 ). A description of the other combinations can be found with Supplementary Table S3 . Comparison of the concentration of bone metabolism regulatory biomarkers before and after treatment The measurements were carried out in a group of 25 patients with at least VGPR who had previously undergone therapy with regimens containing thalidomide (48%), bortezomib (40%) or both drugs (12%). After treatment, a significant decrease was observed in Dkk-1, β-CTX and sclerostin concentration. However, no such differences were found for activin A and GDF-15. Figure 2 and Supplementary Table S4 show a comparison of the concentrations of bone metabolism regulatory biomarkers before and after treatment. Survival Detailed data on survival analysis are presented in Table 3. Progression-free survival Among the variables studied, the following had a significant effect on shortening PFS: older age, higher ISS stage (2 or 3), presence of cytogenetic changes, presence of plasma cell infiltration in the bone marrow (> 25%), high β2-microglobulin, high calcium, high Dkk-1 (13 vs 26 months; HR = 1.94; Fig. 3A), and high GDF-15 (13 vs 21 months; HR = 1.81). An increase in PFS was observed in patients with a satisfactory response to treatment (sCR or CR or VGPR). On the basis of multifactorial models, it was observed that the independent factors related to PFS shortening include: high Dkk-1 (HR = 1.75), the presence of plasma cell infiltration in the bone marrow (> 25%) and the presence of adverse cytogenetic changes. On the other hand, an independent factor related to longer PFS was a satisfactory response to treatment (sCR or CR or VGPR). Overall survival Among the studied variables, the following factors were significantly related to OS shortening: higher (2 and 3) stage of advancement according to ISS, high monoclonal/polyclonal FLC ratio, high β2-microglobulin, high LDH concentration, low albumin, high calcium, low hemoglobin, high Dkk-1 (21 months vs. NR; HR = 3.58; Fig. 3B) and GDF-15 level (21 months vs NR; HR = 2.61), presence of cytogenetic changes, presence of bone lesions, plasma cell infiltration in the bone marrow (> 25%). Furthermore, OS was significantly longer in case of a satisfactory treatment response. The multivariable analysis confirmed the independent, unfavorable prognostic value of high LDH, low albumin, high Dkk-1 (HR = 3.04) and the presence of plasma cell infiltration in the bone marrow (> 25%). Detailed data are presented in Table 3. Discussion Despite the enormous progress in understanding the molecular aspects of bone metabolism, many studies are still being conducted to identify new biomarkers contributing to bone resorption in the course of PCM. There are relatively few reports in the available literature evaluating changes of various markers in blood serum and describing their possible diagnostic and prognostic usefulness in monitoring bone disease in the course of PCM. In this study, a higher serum concentration of Dkk-1 was found in PCM patients as compared to control, which is reflected in the work of other authors [ 11 – 13 ]. The study by Ng et al. showed a higher concentration of Dkk-1 in the serum of patients with monoclonal gammopathy of undetermined significance (MGUS) compared to control [ 14 ]. In turn, Kristensen et al. proved increased expression of the DKK- 1 gene in the bone marrow microenvironment of patients with MGUS compared to control. The results obtained in the MGUS group suggest that Dkk-1 is involved in modulating osteoblast function already in the precancerous stage, and may also indicate the involvement of the Dkk-1 molecule in disease progression [ 15 ]. Interestingly, Palma et al. observed higher levels of Dkk-1 in the bone marrow of smoldering multiple myeloma (SMM) patients who later progressed to PCM. Subsequent analyses by the same authors showed that Dkk-1 concentration in the bone marrow was one of the independent factors of disease progression [ 16 ]. The role of Dkk-1 in this process seems to be explained by the results of the study by D'Amico et al., who found that Dkk-1 significantly influences the generation of more myeloid-derived suppressor cells (MDSCs), weakening the immune response against tumor cells [ 17 ]. Furthermore, researchers agree on a higher concentration of Dkk-1 in the serum of patients with PCM compared to MGUS [ 11 , 18 – 19 ]. The literature contains a limited number of studies on other markers of bone metabolism in patients with PCM. Study by Wang L. et al., showed that the concentration of activin A is significantly higher in PCM patients at each successive stage according to the R-ISS [ 20 ]. In this analysis, no such observations were made due to the lack of cytogenetic tests in some patients included in the R-ISS classification criteria. However, the GDF-15 results obtained by Westhrin et al. indicate that the concentration of this marker is significantly higher in patients with PCM than in control, which may result from the enhancement of the potential to initiate tumor development and self-renewal of altered plasma cells [ 21 ]. Similarly, in our study, a higher concentration of GDF-15 was found in the serum of patients than in the control. On the other hand, the study by Banaszkiewicz et al. showed that the level of GDF-15 positively correlates with the stage of advancement according to ISS [ 22 ]. Analyses by Mohammed A. et al., Ting KR. et al. and Auzina D. et al. showed that the β-CTX concentration in patients with PCM was significantly elevated compared to the control, as in our own work [ 23 – 25 ]. However, in our study, as well as that conducted by Brunetti G. et al., no significant differences were found in the serum concentration of sclerostin measured in PCM patients compared to control [ 26 ]. Literature reports describe a clear relationship between Dkk-1 gene expression and the concentration of this protein in serum or bone marrow and the degree of bone disease, as assessed by imaging tests [ 13 , 18 – 19 , 27 – 28 ]. Particularly interesting are the results in which the level of Dkk-1 in the bone marrow showed a close relationship with the number of lesions detected on MRI [ 28 ]. In contrast to the study by Palma et al., the serum Dkk-1 concentration was correlated with the changes detected in the X-ray in the present study. The Dkk-1 values were significantly higher in the group of patients with multiple lesions compared to patients with no or only a few lesions. On the other hand, Terpos E. et al. observed a significantly higher concentration of activin A in patients with increased bone resorption determined based on elevated β-CTX and extensive bone disease assessed on the base of the number of bone lesions or pathological fractures [ 29 ]. This correlation was also demonstrated in our study, as the level of activin A was significantly elevated in patients with multiple bone lesions. Also, as in the study by Westhrin et al., a higher level of GDF-15 was observed in patients with advanced osteolytic bone disease (> 3 bone lesions) compared to patients without bone lesions at the time of treatment, which confirms the thesis that GDF-15 may play an important role in the development of MBD [ 21 ]. The analysis of AUC showed that the best diagnostic utility was demonstrated by Dkk-1 measurements (AUC = 0.81). In addition, in our study, a significantly higher AUC was found for Dkk-1 than for activin A and β-CTX ( Supplementary Table S2 ). This indicates the limited diagnostic usefulness of the commonly used biochemical indicator of bone resorption - β-CTX, which is contrary to the results of the study by Auzina et al. based on which it was concluded that β-CTX is a very good indicator of bone disease in PCM patients (AUC = 0.91) [ 25 ]. Issues related to bone markers were also addressed by Pop et al., who noted that β-CTX concentration is reduced in patients with PCM without bone lesions, while higher values are observed in the presence of bone lesions. In addition, the β-CTX level may correlate with the extent of bone involvement by plasma cells [ 30 ]. Furthermore, the study by Gerov et al. indicated that significantly higher concentrations of Dkk-1 and sclerostin were found in patients with PCM who had at least three bone lesions or bone fractures compared to patients with single bone lesions [ 8 ]. However, there was no significant difference in sclerostin levels between patients with one or more bone lesions. The research aim of this study also included the evaluation of the concentration of selected markers (Dkk-1, sclerostin, activin A, GDF-15 and β-CTX) after treatment. Among the molecules studied, the concentration of Dkk-1 was significantly reduced, accompanied by a reduction in the level of the resorption marker β-CTX. The results obtained in this study therefore confirm the usefulness of β-CTX determinations as a marker for assessing the effectiveness of bone disease treatment in patients with PCM [ 24 – 25 ]. In recent years, scientists have focused more on the evaluation of bone formation markers and selected molecules that regulate bone metabolism, including Dkk-1. The aforementioned panel of tests usually included patients treated with regimens containing bortezomib, which, in addition to its anti-myeloma effect, had a positive effect on osteoblasts [ 31 – 33 ]. In most published studies using bortezomib, the authors unanimously demonstrated a decrease in Dkk-1 concentration and an increase in bone formation markers (bALP, OC) in patients who responded well to the applied treatment [ 12 , 34 – 36 ]. In contrast, therapy with lenalidomide did not lead to a decrease in Dkk-1 concentration or an increase in parameters reflecting osteoblast activity [ 37 ]. On the other hand, the analysis carried out by Terpos et al. also showed a significant effect of daratumumab therapy on the decrease in Dkk-1 and sclerostin levels at specific intervals after the end of therapy [ 38 ]. We obtained similar results after conducting analyzes in a group of patients with relapsed/refractory PCM (RRMM). It was shown that daratumumab therapy significantly reduces the level of Dkk-1 and β-CTX compared to the initial concentration before the start of treatment. In contrast, no significant differences were found in sclerostin before and after treatment with daratumumab [ 39 ]. In our study, it was difficult to accurately assess the direct impact of the bortezomib-containing regimen on the reduction of Dkk-1 levels and other markers because the group of 25 patients also included 12 patients treated with a thalidomide-based regimen. In the available literature, few authors have conducted studies evaluating Dkk-1 concentration in PCM patients taking into account different therapeutic regimens. However, the work of Heider et al. is noteworthy, in which it was stated that the decrease in Dkk-1 concentration primarily determines the depth of the clinical response to treatment obtained, and not the type of regimen used, which seems to be consistent with the results of our own research [ 40 ]. It should be noted that, in addition to the Dkk-1, other factors present in the bone marrow microenvironment are also involved in the inhibition of osteoblast function. The above observations indicate that the decrease in Dkk-1 level after treatment is related to the reduction in the number of tumor plasmacytes producing the molecule and probably contributes to the restoration of balance in the bone metabolism of patients with PCM. The evaluation of the Dkk-1 in serum can among other parameters provide information on the effectiveness of the therapy and reflect its impact on bone metabolism. In addition, in a published paper, Mabille et al. showed that an increase in serum Dkk-1 concentration preceded the clinical recurrence of the disease by several months [ 41 ]. However, with regard to other markers of bone metabolism, only a limited number of reports with a similar comparative analysis of the treatment of patients with PCM have been published to date. The aim of the study conducted by Terpos E. et al. was to investigate the effect of lenalidomide treatment on activin A levels in patients with PCM. In patients who responded to the treatment, the concentration of activin A did not decrease, and in patients who did not respond to the treatment, there was a statistically insignificant increase in the level of activin A [ 29 ]. However, the above results cannot be applied to the present work, as the authors' own observation included patients treated with regimens without the use of lenalidomide. Furthermore, Terpos E. et al. observed that bortezomib monotherapy leads to a reduction in sclerostin concentration by about half in patients with PCM who respond to and do not respond to the treatment [ 34 ]. The prognostic value of bone metabolism markers and laboratory and clinical parameters in a group of PCM patients was also analysed. Among others, it was shown that a high concentration of the Dkk-1 worsened the prognosis in the study group. It is also noteworthy that an abnormal X-ray result was not a significant factor for OS in the multivariable analysis compared to the Dkk-1 level. The results obtained by Feng et al. also indicate that the median OS was significantly longer (by 23 months) in myeloma patients with low Dkk-1 concentrations compared to patients with high concentrations of this marker [ 42 ]. Furthermore, when considering the results obtained in patients with prostate and breast cancer, high Dkk-1 levels were significantly associated with shorter OS [ 43 , 44 ]. It is also worth noting that Dkk-1 concentration correlate with the number of bone metastases in patients with non-small cell lung cancer, and high levels also significantly worsen the prognosis [ 45 ]. Therefore, it can be assumed that the Dkk-1 level in serum not only reflects disturbed bone metabolism, but also has prognostic significance in the mentioned patient groups. Moreover, the above-mentioned studies proved that Dkk-1 concentration was an independent prognostic factor [ 43 , 44 ]. Similar observations were made in this study. On the other hand, the study by Wang L. et al. indicates that the median OS in patients with an activin A level ≥ 156 ng/l respectively was 61 months, and with a concentration < 156 ng/l the median OS was not reached [ 20 ]. The analysis by Banaszkiewicz M. et al. showed that the GDF-15 parameter was not significantly statistically related to OS, neither in the univariable nor in the multivariable analysis taking into account, among others, ISS or treatment response status [ 22 ]. On the other hand, Huang L. et al. observed that a high concentration of β-CTX in patients with PCM is significantly associated with worse OS (median OS: 25.67 vs. NR months) [ 46 ]. In our work, the relationship between bone metabolism regulatory parameters and PFS was also analyzed, and it was shown that a high level of Dkk-1 was associated with a shortening of PFS, while no such relationship was observed for the other markers evaluated in the multivariate analysis. Moreover, there are individual studies in the world literature that would describe similar relationships related to PCM, therefore it is crucial to conduct further research in this aspect [ 16 , 21 , 41 , 47 ]. The limitations of our study include the relatively small sample size, the lack of complete data for all variables related to cytogenetic studies, and the heterogeneity of the treatment used in patients. Conclusion In summary, the concentrations of selected markers of bone metabolism regulation show a correlation with the number of changes observed in the X-ray. The Dkk-1 level is most promising indicator with the highest diagnostic utility in detecting bone lesions in patients with PCM. The Dkk-1 concentration is significantly reduced after treatment, which means that this molecule can be an interesting biochemical marker useful in monitoring bone metabolism in PCM patients. In addition, the close relationship between Dkk-1 concentration and the result of the imaging test suggests that the determination of this parameter will provide additional information to routinely used imaging tests. Furthermore, the obtained results suggest that Dkk-1 concentration accurately reflects disease activity, which results in its prognostic value. High Dkk-1 level is one of the independent predictors of progression and prognosis in patients with PCM. Declarations Contribution statement: M.K. contributed to the study design, data acquisition and wrote the paper. M. K. and A. K-K. collected samples and performed the ELISA. A.B-Ż contributed to data analysis and wrote the paper. S.C. collected samples and performed cytogenetic analysis. A.S-S., M.M., J.S. provided clinical data and patients. R.M. contributed to data analysis and interpretation. K.G., M.H., R.M contributed to supervision and project administration. All authors participated in revising the manuscript and approved the final version for submission. Conflict of interest statement: The authors declare no conflict of interest. Ethics statement: The study protocol was approved by the ethics committee of the Medical University of Lublin, obtaining consent for its implementation by resolution No. KE-0254/111/2014 Funding information: This work was supported by Medical University of Lublin, Poland [No MNmb10, No DS17]. Author Contribution M.K. contributed to the study design, data acquisition and wrote the paper. M. K. and A. K-K. collected samples and performed the ELISA. A.B-Ż contributed to data analysis and wrote the paper. S.C. collected samples and performed cytogenetic analysis. A.S-S., M.M., J.S. provided clinical data and patients. R.M. contributed to data analysis and interpretation. K.G., M.H., R.M contributed to supervision and project administration. All authors participated in revising the manuscript and approved the final version for submission. Acknowledgements : The authors wish to express their gratitude to the team at the Center for Scientific and Educational Innovation, Medical University of Lublin, for their assistance with translation and language editing. Data Availability The data generated in this study are not publicly available due to the privacy protection of patients of the Independent Public Clinical Hospital No. 1 in Lublin. The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request. References Mafra, A. et al. The global multiple myeloma incidence and mortality burden in 2022 and predictions for 2045. J. Natl. Cancer Inst. 117 , 907–914 (2025). Bird, S. A. & Boyd, K. Multiple myeloma: an overview of management. Palliat. Care Soc. Pract. 13 , 1178224219868235 (2019). Terpos, E., Ntanasis-Stathopoulos, I., Gavriatopoulou, M. & Dimopoulos, M. A. Pathogenesis of bone disease in multiple myeloma: from bench to bedside. 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Al-Janabi, M. A. A., Momeni, A. & Jasim Obaid Al-Harbi, H. R. Association between CTX-1 and Fibulin-1 Serum Levels with Pathogenesis of Multiple Myeloma Cancer. Asian Pac. J. Cancer Prev. 25 , 1599–1605 (2024). Ting, K. R. et al. Clinical utility of C-terminal telopeptide of type 1 collagen in multiple myeloma. Br. J. Haematol. 173 , 82–88 (2016). Auzina, D., Erts, R. & Lejniece, S. Prognostic value of the bone turnover markers in multiple myeloma. Exp. Oncol. 39 , 53–56 (2017). Brunetti, G. et al. Sclerostin is overexpressed by plasma cells from multiple myeloma patients. Ann. N Y Acad. Sci. 1237 , 19–23 (2017). Tian, E. et al. The role of the Wnt-signaling antagonist DKK1 in the development of osteolytic lesions in multiple myeloma. N Engl. J. Med. 349 , 2483–2494 (2003). Palma, B. D. et al. Osteolytic lesions, cytogenetic features and bone marrow levels of cytokines and chemokines in multiple myeloma patients: Role of chemokine (C-C motif) ligand 20. Leukemia 30 , 409–416 (2016). Terpos, E. et al. Circulating activin-A is elevated in patients with advanced multiple myeloma and correlates with extensive bone involvement and inferior survival; no alterations post-lenalidomide and dexamethasone therapy. Ann. Oncol. 23 , 2681–2686 (2012). Pop, V. S. et al. The Impact of Modern Bone Markers in Multiple Myeloma: Prospective Analyses Pre and Post-First Line Treatment. Curr. Issues. Mol. Biol. 46 , 9330–9341 (2024). Giuliani, N. et al. The proteasome inhibitor bortezomib affects osteoblast differentiation in vitro and in vivo in multiple myeloma patients. Blood 110 , 334–338 (2007). Qiang, Y. W. et al. Bortezomib induces osteoblast differentiation via Wnt-independent activation of beta-catenin/TCF signaling. Blood 113 , 4319–4330 (2009). Kaiser, M. F. et al. The proteasome inhibitor bortezomib stimulates osteoblastic differentiation of human osteoblast precursors via upregulation of vitamin D receptor signalling. Eur. J. Haematol. 90 , 263–272 (2013). Terpos, E. et al. Elevated circulating sclerostin correlates with advanced disease features and abnormal bone remodeling in symptomatic myeloma: reduction post-bortezomib monotherapy. Int. J. Cancer . 131 , 1466–1471 (2012). Eom, K. S. et al. Changes in osteoblastic activity in patient who received bortezomib as second line treatment for plasma cell myeloma: a prospective multicenter study. Biomed Res Int. 245247 (2014). (2014). Delforge, M. et al. Fewer bone disease events, improvement in bone remodeling, and evidence of bone healing with bortezomib plus melphalan-prednisone vs. melphalan-prednisone in the phase III VISTA trial in multiple myeloma. Eur. J. Haematol. 86 , 372–384 (2011). Terpos, E. et al. The combination of lenalidomide and dexamethasone reduces bone resorption in responding patients with relapsed/refractory multiple myeloma but has no effect on bone formation: final results on 205 patients of the Greek myeloma study group. Am. J. Hematol. 89 , 34–40 (2014). Terpos, E. et al. Daratumumab Improves Bone Turnover in Relapsed/Refractory Multiple Myeloma; Phase 2 Study REBUILD. Cancers (Basel) . 14 , 2768 (2022). Korpysz, M. et al. The effect of daratumumab treatment on bone metabolism in patients with multiple myeloma. XXVIII Congress of the Polish Society of Hematologists and Transfusionists. Łódź, Abstract; s. 30 (2019). Heider, U. et al. Serum concentrations of DKK-1 decrease in patients with multiple myeloma responding to anti-myeloma treatment. Eur. J. Haematol. 82 , 31–38 (2009). Mabille, C. et al. DKK1 and sclerostin are early markers of relapse in multiple myeloma. Bone 113 , 114–117 (2018). Feng, Y., Zhang, Y., Wei, X. & Zhang, Q. Correlations of DKK1 with pathogenesis and prognosis of human multiple myeloma. Cancer Biomark. 24 , 195–201 (2019). Rachner, T. D. et al. High serum levels of Dickkopf-1 are associated with a poor prognosis in prostate cancer patients. BMC Cancer . 14 , 649 (2014). Zhou, S. J., Zhuo, S. R., Yang, X. Q., Qin, C. X. & Wang, Z. L. Serum Dickkopf-1 expression level positively correlates with a poor prognosis in breast cancer. Diagn. Pathol. 9 , 161 (2014). Qiao, R. et al. Serum dickkopf-1 as a clinical and prognostic factor in non-small cell lung cancer patients with bone metastases. Oncotarget 8 , 79469–79479 (2017). Huang, L. et al. The correlation between serum bone metabolism indexes and bone disease and survival in newly diagnosed multiple myeloma patients. Cancer Biol. Ther. 25 , 2403205 (2024). Vallet, S. et al. Activin A promotes multiple myeloma-induced osteolysis and is a promising target for myeloma bone disease. Proc. Natl. Acad. Sci. U S A . 107 , 5124–5129 (2010). Tables Tables are available in the Supplementary Files section. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8388907","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":617724168,"identity":"f24ba72a-558c-414d-a4aa-21d324074442","order_by":0,"name":"Maciej Korpysz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFklEQVRIie3QsUrEMBjA8a+c1OU7XVN69whCpBCHFp+lodBbxFWHGyqFcyne6ku4dk4JnEu1q+JyIjg5dKxQxOboCUJbHQXzh4QQ8iMkADrdH00AAm3XHsAumM1ipEb0GxKqw1ti9BLVlsifycGlfBblBJx9+25lVXXBb2Jkazh3eWRfdBKWhzS7RmDW1WloIz7xVOIRhXzGo0nWTcQJSETwaI7MBrIhjBgLySPCu0nxBrJuiVXR+5Z8DJCH5pbmx5giBH3RkmiIvNIsQeJYyV7gogicVJpn1F/NnEXfW4rgpXxPvMMljrPHqj6eprdxui7n7nRpx6KLbDIS0sy4Q752/GaYpO+8qlITjsrvu4NEp9Pp/lGfJClhMHNdLOAAAAAASUVORK5CYII=","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":true,"prefix":"","firstName":"Maciej","middleName":"","lastName":"Korpysz","suffix":""},{"id":617724169,"identity":"6580ea36-eb34-4124-94a1-235392979ed0","order_by":1,"name":"Alicja Bogdanowicz-Żeleźniak","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Alicja","middleName":"","lastName":"Bogdanowicz-Żeleźniak","suffix":""},{"id":617724170,"identity":"a39f1a59-b8c8-4a17-9db1-b28e9e7cf409","order_by":2,"name":"Anna Kowalska-Kępczyńska","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Kowalska-Kępczyńska","suffix":""},{"id":617724171,"identity":"364d6ffa-f6eb-4b90-9e36-82bb30be92ea","order_by":3,"name":"Aneta Szudy-Szczyrek","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Aneta","middleName":"","lastName":"Szudy-Szczyrek","suffix":""},{"id":617724172,"identity":"a48571f8-8f53-48b7-9c9f-116c519b27af","order_by":4,"name":"Sylwia Chocholska","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Sylwia","middleName":"","lastName":"Chocholska","suffix":""},{"id":617724173,"identity":"1b150641-21f7-48ef-9223-270e20a97e00","order_by":5,"name":"Marta Morawska","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Marta","middleName":"","lastName":"Morawska","suffix":""},{"id":617724174,"identity":"ea3a196c-1893-4dcb-8956-bb812a4378ce","order_by":6,"name":"Jan Siwiec","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"","lastName":"Siwiec","suffix":""},{"id":617724175,"identity":"57c1b81d-5307-409c-b14c-2377fd225c3d","order_by":7,"name":"Marek Hus","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Marek","middleName":"","lastName":"Hus","suffix":""},{"id":617724177,"identity":"4d478f89-5c5e-4a14-88d1-b0342d1732bf","order_by":8,"name":"Krzysztof Giannopoulos","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Krzysztof","middleName":"","lastName":"Giannopoulos","suffix":""},{"id":617724179,"identity":"bd48e183-3a12-4706-b33b-1815d0bbbe15","order_by":9,"name":"Radosław Mlak","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Radosław","middleName":"","lastName":"Mlak","suffix":""}],"badges":[],"createdAt":"2025-12-17 20:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8388907/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8388907/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106381929,"identity":"38d6a195-d828-4df7-a005-ed107c3a3f64","added_by":"auto","created_at":"2026-04-08 05:25:24","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":243864,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves showing the diagnostic usefulness of bone metabolism regulatory biomarkers in the detection of bone lesions in PCM patients. Abbreviations: Dkk-1, dickkopf-related protein 1; GDF-15, growth differentiation factor 15; β-CTX, β-C-terminal telopeptid\u003c/p\u003e","description":"","filename":"Figure1withlabelpage0001.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8388907/v1/35a33429470863c86283d0a5.jpg"},{"id":106382208,"identity":"93301294-ff66-48fe-ab29-26e51882953f","added_by":"auto","created_at":"2026-04-08 05:25:55","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":409070,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the concentration of bone metabolism regulatory biomarkers before and after treatment. Abbreviations: Dkk-1, dickkopf-related protein 1; GDF-15, growth differentiation factor 15; β-CTX, β-C-terminal telopeptid\u003c/p\u003e","description":"","filename":"Figure2withlabel.page0001.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8388907/v1/64f05e971b225a7577bf9dc1.jpg"},{"id":106381899,"identity":"5309523a-4920-41c5-acf2-146467484ec8","added_by":"auto","created_at":"2026-04-08 05:25:09","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":241658,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier curve showing the probability of progression [A] or death [B] depending on Dkk-1 concentration. Abbreviations: mPFS/OS, median progression-free survival/overall survival; mo, months\u003c/p\u003e","description":"","filename":"Figure3withlabel.page0001.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8388907/v1/135fcb01c2c33035b6ba5b77.jpg"},{"id":106959386,"identity":"5a732273-dcdd-480a-b54c-895caab7a58f","added_by":"auto","created_at":"2026-04-15 09:07:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1929356,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8388907/v1/b6b7be53-a939-417b-89ef-6f80859b7baa.pdf"},{"id":106382316,"identity":"16984667-6a99-44b1-81dc-0da4405ecca4","added_by":"auto","created_at":"2026-04-08 05:26:30","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":28960,"visible":true,"origin":"","legend":"","description":"","filename":"Tablefile.docx","url":"https://assets-eu.researchsquare.com/files/rs-8388907/v1/538814ad1b184b6aaebe7861.docx"},{"id":106381898,"identity":"90ce00af-713c-4b17-8dff-3122ab948acb","added_by":"auto","created_at":"2026-04-08 05:25:08","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":53448,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTablesandFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-8388907/v1/e1550afd94025abe6187559f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Diagnostic and prognostic value of bone metabolism biomarkers in newly diagnosed plasma cell myeloma","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePlasma cell myeloma (PCM) is the second most common hematological malignancy, accounting for 1% of all cancers, with a high incidence (\u0026ge;\u0026thinsp;4/100,000/year) and mortality (1.8/100,000/year) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Typical symptoms include hypercalcemia (C), renal dysfunction (R), anemia (A), and lytic lesions with bone pain (B) - collectively known as CRAB [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Myeloma bone disease (MBD) affects approximately 80% of patients, often leading to pathological fractures or spinal cord compression. PCM cells interact with bone marrow stromal cells to increase expression of receptor activator of nuclear factor κB ligand (RANKL), stimulating osteoclast activity, while reducing osteoprotegerin (OPG), a natural RANKL inhibitor [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Additionally, osteoblast function is inhibited due to secretion of Wnt pathway antagonists like dickkopf-related protein 1 (Dkk-1) and secreted frizzled-related protein 2 (sFRP2) by myeloma cells, disrupting bone formation and remodeling [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This results in an imbalance between excessive bone resorption and impaired formation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], along with a reduced number of healthy osteocytes correlated with disease stage. Bone turnover markers (BTMs), such as C-, N-terminal telopeptides of type I collagen (CTX, NTX) and bone alkaline phosphatase (bALP), osteocalcin, are commonly used to assess bone metabolism [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Recent studies highlight new molecules that may serve as BTMs in PCM. Growth differentiation factor 15 (GDF-15) negatively correlates with bone formation markers like alkaline phosphatase, indicating its involvement in impaired bone mass homeostasis [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Activin A, elevated in both serum and bone marrow of patients with lytic lesions, inhibits bone morphogenetic protein (BMP) signaling [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Dkk-1 and sclerostin levels also correlate with the presence and severity of bone lesions according to the International Staging System (ISS), making them promising markers [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The aim of this study was to evaluate the usefulness of activin A, Dkk-1, GDF-15, β-CTX, and sclerostin as potential biomarkers of bone lesions and prognostic factors in PCM.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003eStudy group\u003c/h2\u003e\n \u003cp\u003eThe study group consisted of 76 patients with newly diagnosed PCM, treated between April 2014 and April 2017at the Department of Hematooncology and Bone Marrow Transplantation of the Independent Public Clinical Hospital No. 1 in Lublin. Patients were diagnosed according the International Myeloma Working Group (IMWG). Plasma cell infiltration in the bone marrow was marked as positive when more than 10% of plasma cells in the bone marrow sample were noted.\u003c/p\u003e\n \u003cp\u003eInclusion criteria:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003enewly diagnosed PCM based on IMWG recommendations;\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003epatients of both sexes over the age of 18;\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003epatients who gave their written informed consent to participate after having read the information about the study;\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003epatients who had undergone an X-ray examination at the time of diagnosis to assess the extent of osteolytic lesions in the bones.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003eExclusion criteria:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003ecoexistence of another malignant disease;\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003egenetic or endocrine - related metabolic bone diseases;\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003egeneral poor condition of the patient;\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003ehigh creatinine concentration (\u0026gt;\u0026thinsp;3 mg/dl);\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eprevious antimyeloma treatment.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003ePatients diagnosed with PCM were treated with various therapeutic regimens, most of which were based on thalidomide, bortezomib or contained both thalidomide and bortezomib. Patients with a satisfactory response to the treatment and eligible for autologous hematopoietic stem cell transplantation (aHSCT) underwent the procedure (Table\u0026nbsp;1\u003cstrong\u003e)\u003c/strong\u003e. The median follow-up time of the patients from the time of inclusion in the study was 43 months. In 81.6% of the patients, disease progression was observed during follow-up, while 56.6% of the patients died.\u003c/p\u003e\n \u003cdiv\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eControl group\u003c/h3\u003e\n\u003cp\u003eThe control group consisted of 25 healthy volunteers, who were matched in age and gender to the study group. Before the blood was taken, the participants were asked to complete a questionnaire about their individual health condition. Based on the survey results, participants who did not take medication affecting bone metabolism, had not suffered any fractures recently, and had not been diagnosed with osteoporosis or other skeletal disorders were qualified for the control group.\u003c/p\u003e\n\u003ch3\u003eMethods\u003c/h3\u003e\n\u003cdiv id=\"Sec6\"\u003e\n \u003ch2\u003e\u003cem\u003eAssessment of cytogenetic changes cIg-FISH analysis\u003c/em\u003e\u003c/h2\u003e\n \u003cp\u003eAdverse cytogenetic abnormalities characteristic of PCM were assessed by simultaneous staining of cytoplasmic immunoglobulins and fluorescense in situ hybridization (cIg-FISH) method according to the protocol described previously [9]. The following commercially available FISH probes were used: Vysis TP53/CEP 17 FISH Probe Kit, Vysis IGH/FGFR3 DF FISH Probe Kit and Vysis IGH/MAF DF FISH Probe Kit (Abbott GmBH, Wiesbaden, Germany). The analysis was performed on Olympus BX51 microscope (Olympus Europe, Hamburg, Germany) by counting 100 AMCA-positive plasma cells to determine the frequency of each aberration. Cut-off levels were 20% for deletion probes and 10% for dual fusion probes, according to the European Myeloma Network recommendations.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eAssessment of laboratory parameters including bone metabolism regulatory biomarkers\u003c/h3\u003e\n\u003cp\u003eThe study material was venous blood (10 ml) collected before the start of treatment from patients included in the study and the control group into tubes without anticoagulant. After the blood had clotted (20\u0026ndash;30 min.), the sample was centrifuged (10 min. at 2500 rpm), and then the serum obtained was stored at -80\u0026deg;C until the analyses were performed.\u003c/p\u003e\n\u003cp\u003eActivin A, Dkk-1 and GDF-15 concentrations were measured using enzyme-linked immunosorbent assay (ELISA) kits from R\u0026amp;D Systems (catalog numbers: DAC00B, DKK100B and DGD150, respectively), while sclerostin using kit from TECOmedical Group (catalog number: TE1023-HS). All measurements were carried out according to the manufacturer\u0026apos;s test protocols. The absorbance was read at the appropriate wavelength using a spectrophotometric reader, model 800 TS (BioTek, Winooski, USA).\u003c/p\u003e\n\u003cp\u003eThe \u0026beta;-CTX concentration was determined by electrochemiluminescence immunoassay (ECLIA) using a Cobas e411 analyzer (Roche Diagnostics, Mannheim, Germany) and a suitable Roche \u0026beta; CrossLaps/serum reagent kit.\u003c/p\u003e\n\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003eAssessment of treatment response\u003c/h2\u003e\n \u003cp\u003eThe treatment response was assessed according to the current IMWG criteria [10]. In a group of 25 patients with at least a very good treatment response (14 patients with VGPR and 11 with CR, respectively) after 4\u0026ndash;6 cycles of therapy, the indicators of bone metabolism regulation were re-measured.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eAssessment of bone lesions\u003c/h3\u003e\n\u003cp\u003eIn order to assess bone lesions, a radiological examination (X-ray) was performed in all patients (cervical, thoracic, lumbar spine, femurs, humerus, skull and pelvis). A general overview of the chest and the other body parts where the patient reported pain was also applied. The study group was divided into 3 subgroups depending on the number of bone lesions. Group I consisted of patients with no bone lesions, group II consisted of patients with limited lesions in 1\u0026ndash;3 bones, while group III consisted of patients with extensive bone lesions in more than three bones or with pathological fractures.\u003c/p\u003e\n\u003cp\u003eAll experiments were conducted in accordance with applicable guidelines and regulations. Informed consent was obtained from all study participants and/or their legal guardians. The Bioethics Committee at the Medical University of Lublin granted approval for the study under No. KE-0254/111/2014.\u003c/p\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eThe statistical analysis was performed using MedCalc software version 15.8 PL and GraphPad Prism. The D\u0026apos;Agostino-Pearson test was used to assess whether the studied variables showed a normal distribution. The distributions of the analyzed continuous variables were not normal, therefore non-parametric tests were used to compare the obtained data (Mann-Whitney U test for independent groups and Wilcoxon test for dependent groups). The Kruskal-Wallis ANOVA test was used to compare several independent groups, and if significant differences were found, the data were further analyzed using an appropriate post-hoc test. The correlation between the studied biomarkers and the number of bone lesions was performed using Spearman\u0026apos;s rank correlation. ROC (receiver operating characteristic) curves were also plotted and the area under the curves (AUC) was calculated to assess the diagnostic usefulness of studied biomarkers in differentiating the lack or presence of bone lesions. The progression-free survival (PFS) was defined as the time between diagnosis and the occurrence of progression or the most recent follow-up. Overall survival (OS) was defined as the time between diagnosis and death or the most recent follow-up. A univariate analysis of the impact of the examined variables on PFS and OS was performed using the log-rank test. Kaplan-Meier estimation method was used to generate survival curves. In the multivariate analysis of the impact of the examined variables on survival, Cox\u0026apos;s proportional hazard models were used (variables that remained significant after the use of the backward elimination method - were included in multivariable models). In all of the statistical analysis, a value of p\u0026thinsp;\u0026le;\u0026thinsp;0.05 was considered to be statistically significant.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003e\u003cstrong\u003eComparison of the concentration of bone metabolism regulatory biomarkers in the study and control groups\u003c/strong\u003e\u003c/h2\u003e\n \u003cp\u003eStatistical analysis showed significantly higher activin A, Dkk-1, GDF-15 and \u0026beta;-CTX in the study group compared to the control. However, in the case of sclerostin, observed differences were not significant (\u003cstrong\u003eSupplementary Table S1\u003c/strong\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003eAssessment of the relationship between bone metabolism regulatory biomarkers and the number of bone lesions\u003c/h2\u003e\n \u003cp\u003eA significantly higher Dkk-1 concentrations were observed in patients with multiple bone lesions compared to those with a limited number or no lesions. Moreover, significantly higher Dkk-1 concentrations were noted in patients with a limited number of bone lesions compared to those with no lesions. Significantly higher GDF-15 and \u0026beta;-CTX concentrations were found in patients with multiple bone lesions compared to those with a limited number or no lesions. Detailed data regarding the relationship between bone metabolism regulatory biomarkers and the number of bone lesions are included in Table\u0026nbsp;2.\u003c/p\u003e\n \u003cdiv\u003e\u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eAssessment of the diagnostic value of bone metabolism regulatory biomarkers in the detection of bone lesions\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSupplementary Figure S1\u003c/strong\u003e shows a comparison of the AUC values describing the diagnostic usefulness of the studied indicators of bone metabolism in the detection of bone lesions, while Fig.\u0026nbsp;1 shows the ROC curves for the parameters of metabolism, significantly differentiating patients with current bone lesions from those with no lesions.\u003c/p\u003e\n \u003cp\u003eThe highest diagnostic accuracy in detecting bone lesions was obtained for Dkk-1 measurements (AUC\u0026thinsp;=\u0026thinsp;0.81; cut off: \u0026gt;2046), and the lowest for sclerostin (AUC\u0026thinsp;=\u0026thinsp;0.54; cut off: \u0026le;0.489) (\u003cstrong\u003eSupplementary Table S2\u003c/strong\u003e). A description of the other combinations can be found with \u003cstrong\u003eSupplementary Table S3\u003c/strong\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eComparison of the concentration of bone metabolism regulatory biomarkers before and after treatment\u003c/h2\u003e\n \u003cp\u003eThe measurements were carried out in a group of 25 patients with at least VGPR who had previously undergone therapy with regimens containing thalidomide (48%), bortezomib (40%) or both drugs (12%). After treatment, a significant decrease was observed in Dkk-1, \u0026beta;-CTX and sclerostin concentration. However, no such differences were found for activin A and GDF-15. Figure\u0026nbsp;2 and \u003cstrong\u003eSupplementary Table S4\u003c/strong\u003e show a comparison of the concentrations of bone metabolism regulatory biomarkers before and after treatment.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003eSurvival\u003c/h2\u003e\n \u003cp\u003eDetailed data on survival analysis are presented in Table\u0026nbsp;3.\u003c/p\u003e\n \u003cdiv\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\"\u003e\n \u003ch2\u003eProgression-free survival\u003c/h2\u003e\n \u003cp\u003eAmong the variables studied, the following had a significant effect on shortening PFS: older age, higher ISS stage (2 or 3), presence of cytogenetic changes, presence of plasma cell infiltration in the bone marrow (\u0026gt;\u0026thinsp;25%), high \u0026beta;2-microglobulin, high calcium, high Dkk-1 (13 vs 26 months; HR\u0026thinsp;=\u0026thinsp;1.94; Fig.\u0026nbsp;3A), and high GDF-15 (13 vs 21 months; HR\u0026thinsp;=\u0026thinsp;1.81). An increase in PFS was observed in patients with a satisfactory response to treatment (sCR or CR or VGPR).\u003c/p\u003e\n \u003cp\u003eOn the basis of multifactorial models, it was observed that the independent factors related to PFS shortening include: high Dkk-1 (HR\u0026thinsp;=\u0026thinsp;1.75), the presence of plasma cell infiltration in the bone marrow (\u0026gt;\u0026thinsp;25%) and the presence of adverse cytogenetic changes. On the other hand, an independent factor related to longer PFS was a satisfactory response to treatment (sCR or CR or VGPR).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\"\u003e\n \u003ch2\u003eOverall survival\u003c/h2\u003e\n \u003cp\u003eAmong the studied variables, the following factors were significantly related to OS shortening: higher (2 and 3) stage of advancement according to ISS, high monoclonal/polyclonal FLC ratio, high \u0026beta;2-microglobulin, high LDH concentration, low albumin, high calcium, low hemoglobin, high Dkk-1 (21 months vs. NR; HR\u0026thinsp;=\u0026thinsp;3.58; Fig.\u0026nbsp;3B) and GDF-15 level (21 months vs NR; HR\u0026thinsp;=\u0026thinsp;2.61), presence of cytogenetic changes, presence of bone lesions, plasma cell infiltration in the bone marrow (\u0026gt;\u0026thinsp;25%). Furthermore, OS was significantly longer in case of a satisfactory treatment response.\u003c/p\u003e\n \u003cp\u003eThe multivariable analysis confirmed the independent, unfavorable prognostic value of high LDH, low albumin, high Dkk-1 (HR\u0026thinsp;=\u0026thinsp;3.04) and the presence of plasma cell infiltration in the bone marrow (\u0026gt;\u0026thinsp;25%). Detailed data are presented in Table\u0026nbsp;3.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDespite the enormous progress in understanding the molecular aspects of bone metabolism, many studies are still being conducted to identify new biomarkers contributing to bone resorption in the course of PCM. There are relatively few reports in the available literature evaluating changes of various markers in blood serum and describing their possible diagnostic and prognostic usefulness in monitoring bone disease in the course of PCM.\u003c/p\u003e \u003cp\u003eIn this study, a higher serum concentration of Dkk-1 was found in PCM patients as compared to control, which is reflected in the work of other authors [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The study by Ng et al. showed a higher concentration of Dkk-1 in the serum of patients with monoclonal gammopathy of undetermined significance (MGUS) compared to control [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In turn, Kristensen et al. proved increased expression of the \u003cem\u003eDKK-\u003c/em\u003e1 gene in the bone marrow microenvironment of patients with MGUS compared to control. The results obtained in the MGUS group suggest that Dkk-1 is involved in modulating osteoblast function already in the precancerous stage, and may also indicate the involvement of the Dkk-1 molecule in disease progression [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Interestingly, Palma et al. observed higher levels of Dkk-1 in the bone marrow of smoldering multiple myeloma (SMM) patients who later progressed to PCM. Subsequent analyses by the same authors showed that Dkk-1 concentration in the bone marrow was one of the independent factors of disease progression [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The role of Dkk-1 in this process seems to be explained by the results of the study by D'Amico et al., who found that Dkk-1 significantly influences the generation of more myeloid-derived suppressor cells (MDSCs), weakening the immune response against tumor cells [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Furthermore, researchers agree on a higher concentration of Dkk-1 in the serum of patients with PCM compared to MGUS [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The literature contains a limited number of studies on other markers of bone metabolism in patients with PCM. Study by Wang L. et al., showed that the concentration of activin A is significantly higher in PCM patients at each successive stage according to the R-ISS [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In this analysis, no such observations were made due to the lack of cytogenetic tests in some patients included in the R-ISS classification criteria. However, the GDF-15 results obtained by Westhrin et al. indicate that the concentration of this marker is significantly higher in patients with PCM than in control, which may result from the enhancement of the potential to initiate tumor development and self-renewal of altered plasma cells [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Similarly, in our study, a higher concentration of GDF-15 was found in the serum of patients than in the control. On the other hand, the study by Banaszkiewicz et al. showed that the level of GDF-15 positively correlates with the stage of advancement according to ISS [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Analyses by Mohammed A. et al., Ting KR. et al. and Auzina D. et al. showed that the β-CTX concentration in patients with PCM was significantly elevated compared to the control, as in our own work [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, in our study, as well as that conducted by Brunetti G. et al., no significant differences were found in the serum concentration of sclerostin measured in PCM patients compared to control [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLiterature reports describe a clear relationship between \u003cem\u003eDkk-1\u003c/em\u003e gene expression and the concentration of this protein in serum or bone marrow and the degree of bone disease, as assessed by imaging tests [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Particularly interesting are the results in which the level of Dkk-1 in the bone marrow showed a close relationship with the number of lesions detected on MRI [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In contrast to the study by Palma et al., the serum Dkk-1 concentration was correlated with the changes detected in the X-ray in the present study. The Dkk-1 values were significantly higher in the group of patients with multiple lesions compared to patients with no or only a few lesions. On the other hand, Terpos E. et al. observed a significantly higher concentration of activin A in patients with increased bone resorption determined based on elevated β-CTX and extensive bone disease assessed on the base of the number of bone lesions or pathological fractures [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This correlation was also demonstrated in our study, as the level of activin A was significantly elevated in patients with multiple bone lesions. Also, as in the study by Westhrin et al., a higher level of GDF-15 was observed in patients with advanced osteolytic bone disease (\u0026gt;\u0026thinsp;3 bone lesions) compared to patients without bone lesions at the time of treatment, which confirms the thesis that GDF-15 may play an important role in the development of MBD [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The analysis of AUC showed that the best diagnostic utility was demonstrated by Dkk-1 measurements (AUC\u0026thinsp;=\u0026thinsp;0.81). In addition, in our study, a significantly higher AUC was found for Dkk-1 than for activin A and β-CTX (\u003cb\u003eSupplementary Table S2\u003c/b\u003e). This indicates the limited diagnostic usefulness of the commonly used biochemical indicator of bone resorption - β-CTX, which is contrary to the results of the study by Auzina et al. based on which it was concluded that β-CTX is a very good indicator of bone disease in PCM patients (AUC\u0026thinsp;=\u0026thinsp;0.91) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Issues related to bone markers were also addressed by Pop et al., who noted that β-CTX concentration is reduced in patients with PCM without bone lesions, while higher values are observed in the presence of bone lesions. In addition, the β-CTX level may correlate with the extent of bone involvement by plasma cells [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Furthermore, the study by Gerov et al. indicated that significantly higher concentrations of Dkk-1 and sclerostin were found in patients with PCM who had at least three bone lesions or bone fractures compared to patients with single bone lesions [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, there was no significant difference in sclerostin levels between patients with one or more bone lesions.\u003c/p\u003e \u003cp\u003eThe research aim of this study also included the evaluation of the concentration of selected markers (Dkk-1, sclerostin, activin A, GDF-15 and β-CTX) after treatment. Among the molecules studied, the concentration of Dkk-1 was significantly reduced, accompanied by a reduction in the level of the resorption marker β-CTX. The results obtained in this study therefore confirm the usefulness of β-CTX determinations as a marker for assessing the effectiveness of bone disease treatment in patients with PCM [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In recent years, scientists have focused more on the evaluation of bone formation markers and selected molecules that regulate bone metabolism, including Dkk-1. The aforementioned panel of tests usually included patients treated with regimens containing bortezomib, which, in addition to its anti-myeloma effect, had a positive effect on osteoblasts [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In most published studies using bortezomib, the authors unanimously demonstrated a decrease in Dkk-1 concentration and an increase in bone formation markers (bALP, OC) in patients who responded well to the applied treatment [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In contrast, therapy with lenalidomide did not lead to a decrease in Dkk-1 concentration or an increase in parameters reflecting osteoblast activity [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. On the other hand, the analysis carried out by Terpos et al. also showed a significant effect of daratumumab therapy on the decrease in Dkk-1 and sclerostin levels at specific intervals after the end of therapy [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. We obtained similar results after conducting analyzes in a group of patients with relapsed/refractory PCM (RRMM). It was shown that daratumumab therapy significantly reduces the level of Dkk-1 and β-CTX compared to the initial concentration before the start of treatment. In contrast, no significant differences were found in sclerostin before and after treatment with daratumumab [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In our study, it was difficult to accurately assess the direct impact of the bortezomib-containing regimen on the reduction of Dkk-1 levels and other markers because the group of 25 patients also included 12 patients treated with a thalidomide-based regimen. In the available literature, few authors have conducted studies evaluating Dkk-1 concentration in PCM patients taking into account different therapeutic regimens. However, the work of Heider et al. is noteworthy, in which it was stated that the decrease in Dkk-1 concentration primarily determines the depth of the clinical response to treatment obtained, and not the type of regimen used, which seems to be consistent with the results of our own research [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. It should be noted that, in addition to the Dkk-1, other factors present in the bone marrow microenvironment are also involved in the inhibition of osteoblast function. The above observations indicate that the decrease in Dkk-1 level after treatment is related to the reduction in the number of tumor plasmacytes producing the molecule and probably contributes to the restoration of balance in the bone metabolism of patients with PCM. The evaluation of the Dkk-1 in serum can among other parameters provide information on the effectiveness of the therapy and reflect its impact on bone metabolism. In addition, in a published paper, Mabille et al. showed that an increase in serum Dkk-1 concentration preceded the clinical recurrence of the disease by several months [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, with regard to other markers of bone metabolism, only a limited number of reports with a similar comparative analysis of the treatment of patients with PCM have been published to date. The aim of the study conducted by Terpos E. et al. was to investigate the effect of lenalidomide treatment on activin A levels in patients with PCM. In patients who responded to the treatment, the concentration of activin A did not decrease, and in patients who did not respond to the treatment, there was a statistically insignificant increase in the level of activin A [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, the above results cannot be applied to the present work, as the authors' own observation included patients treated with regimens without the use of lenalidomide. Furthermore, Terpos E. et al. observed that bortezomib monotherapy leads to a reduction in sclerostin concentration by about half in patients with PCM who respond to and do not respond to the treatment [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe prognostic value of bone metabolism markers and laboratory and clinical parameters in a group of PCM patients was also analysed. Among others, it was shown that a high concentration of the Dkk-1 worsened the prognosis in the study group. It is also noteworthy that an abnormal X-ray result was not a significant factor for OS in the multivariable analysis compared to the Dkk-1 level. The results obtained by Feng et al. also indicate that the median OS was significantly longer (by 23 months) in myeloma patients with low Dkk-1 concentrations compared to patients with high concentrations of this marker [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, when considering the results obtained in patients with prostate and breast cancer, high Dkk-1 levels were significantly associated with shorter OS [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. It is also worth noting that Dkk-1 concentration correlate with the number of bone metastases in patients with non-small cell lung cancer, and high levels also significantly worsen the prognosis [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Therefore, it can be assumed that the Dkk-1 level in serum not only reflects disturbed bone metabolism, but also has prognostic significance in the mentioned patient groups. Moreover, the above-mentioned studies proved that Dkk-1 concentration was an independent prognostic factor [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Similar observations were made in this study. On the other hand, the study by Wang L. et al. indicates that the median OS in patients with an activin A level\u0026thinsp;\u0026ge;\u0026thinsp;156 ng/l respectively was 61 months, and with a concentration\u0026thinsp;\u0026lt;\u0026thinsp;156 ng/l the median OS was not reached [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The analysis by Banaszkiewicz M. et al. showed that the GDF-15 parameter was not significantly statistically related to OS, neither in the univariable nor in the multivariable analysis taking into account, among others, ISS or treatment response status [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. On the other hand, Huang L. et al. observed that a high concentration of β-CTX in patients with PCM is significantly associated with worse OS (median OS: 25.67 vs. NR months) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. In our work, the relationship between bone metabolism regulatory parameters and PFS was also analyzed, and it was shown that a high level of Dkk-1 was associated with a shortening of PFS, while no such relationship was observed for the other markers evaluated in the multivariate analysis. Moreover, there are individual studies in the world literature that would describe similar relationships related to PCM, therefore it is crucial to conduct further research in this aspect [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe limitations of our study include the relatively small sample size, the lack of complete data for all variables related to cytogenetic studies, and the heterogeneity of the treatment used in patients.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, the concentrations of selected markers of bone metabolism regulation show a correlation with the number of changes observed in the X-ray. The Dkk-1 level is most promising indicator with the highest diagnostic utility in detecting bone lesions in patients with PCM. The Dkk-1 concentration is significantly reduced after treatment, which means that this molecule can be an interesting biochemical marker useful in monitoring bone metabolism in PCM patients. In addition, the close relationship between Dkk-1 concentration and the result of the imaging test suggests that the determination of this parameter will provide additional information to routinely used imaging tests. Furthermore, the obtained results suggest that Dkk-1 concentration accurately reflects disease activity, which results in its prognostic value. High Dkk-1 level is one of the independent predictors of progression and prognosis in patients with PCM.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eContribution statement:\u003c/h2\u003e \u003cp\u003eM.K. contributed to the study design, data acquisition and wrote the paper. M. K. and A. K-K. collected samples and performed the ELISA. A.B-Ż contributed to data analysis and wrote the paper. S.C. collected samples and performed cytogenetic analysis. A.S-S., M.M., J.S. provided clinical data and patients. R.M. contributed to data analysis and interpretation. K.G., M.H., R.M contributed to supervision and project administration. All authors participated in revising the manuscript and approved the final version for submission.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConflict of interest statement:\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthics statement:\u003c/h2\u003e \u003cp\u003eThe study protocol was approved by the ethics committee of the Medical University of Lublin, obtaining consent for its implementation by resolution No. KE-0254/111/2014\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding information:\u003c/h2\u003e \u003cp\u003eThis work was supported by Medical University of Lublin, Poland [No MNmb10, No DS17].\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eM.K. contributed to the study design, data acquisition and wrote the paper. M. K. and A. K-K. collected samples and performed the ELISA. A.B-Ż contributed to data analysis and wrote the paper. S.C. collected samples and performed cytogenetic analysis. A.S-S., M.M., J.S. provided clinical data and patients. R.M. contributed to data analysis and interpretation. K.G., M.H., R.M contributed to supervision and project administration. All authors participated in revising the manuscript and approved the final version for submission.\u003c/p\u003e\u003ch2\u003e \u003cb\u003eAcknowledgements\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eThe authors wish to express their gratitude to the team at the Center for Scientific and Educational Innovation, Medical University of Lublin, for their assistance with translation and language editing.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data generated in this study are not publicly available due to the privacy protection of patients of the Independent Public Clinical Hospital No. 1 in Lublin. The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMafra, A. et al. The global multiple myeloma incidence and mortality burden in 2022 and predictions for 2045. \u003cem\u003eJ. Natl. Cancer Inst.\u003c/em\u003e \u003cb\u003e117\u003c/b\u003e, 907\u0026ndash;914 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBird, S. A. \u0026amp; Boyd, K. Multiple myeloma: an overview of management. \u003cem\u003ePalliat. Care Soc. Pract.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e, 1178224219868235 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTerpos, E., Ntanasis-Stathopoulos, I., Gavriatopoulou, M. \u0026amp; Dimopoulos, M. A. 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U S A\u003c/em\u003e. \u003cb\u003e107\u003c/b\u003e, 5124\u0026ndash;5129 (2010).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"bone markers, diagnosis, dickkopf-1 (Dkk-1), plasma cell myeloma, prognosis","lastPublishedDoi":"10.21203/rs.3.rs-8388907/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8388907/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePlasma cell myeloma (PCM) is the second most common type of haematological cancer. Lytic lesions and bone pain are among the most common symptoms of PCM. The study aimed to evaluated the diagnostic and prognostic value of markers of bone metabolism, i.e. activin A, Dkk-1, GDF-15, β-CTX and sclerostin in patients with PCM. The study involved 76 patients with PCM and 25 healthy volunteers. The concentration of above markers was determined by ELISA method. Patients showed significantly higher pretreatment concentration of activin A, Dkk-1, GDF-15 and β-CTX compared to the control. The number of bone lesions (based on X-ray) showed a significant correlation with the concentration of activin A (rho\u0026thinsp;=\u0026thinsp;0.276), Dkk-1 (rho\u0026thinsp;=\u0026thinsp;0.598), GDF-15 (rho\u0026thinsp;=\u0026thinsp;0.489), and β-CTX (rho\u0026thinsp;=\u0026thinsp;0.381). The ROC curves analyses revealed that the determination of Dkk-1 was characterized by the highest diagnostic utility in the detection of osteolytic lesions (AUC\u0026thinsp;=\u0026thinsp;0.81). Moreover the high levels of Dkk-1 were significantly associated with poor PFS (HR\u0026thinsp;=\u0026thinsp;1.75) and OS (HR\u0026thinsp;=\u0026thinsp;3.04). The assessment of Dkk-1 concentration may become a new biomarker useful in the detection and monitoring of bone lesions and may indicate an unfavourable prognosis in PCM.\u003c/p\u003e","manuscriptTitle":"Diagnostic and prognostic value of bone metabolism biomarkers in newly diagnosed plasma cell myeloma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-08 05:23:24","doi":"10.21203/rs.3.rs-8388907/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-20T02:02:46+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-13T15:03:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"82421922846290861778810635622569632196","date":"2026-04-09T12:22:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-08T13:13:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"219065021168574646953388762852104558850","date":"2026-04-02T01:10:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81492871161398091625576602331494172522","date":"2026-04-01T16:54:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-01T16:44:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-23T19:02:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-23T11:13:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-22T12:29:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-12-22T12:14:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4c971a05-8c72-42f8-8710-56a19372d9c9","owner":[],"postedDate":"April 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":65740163,"name":"Health sciences/Biomarkers"},{"id":65740164,"name":"Biological sciences/Cancer"},{"id":65740165,"name":"Health sciences/Diseases"},{"id":65740166,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-05-04T12:09:32+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-08 05:23:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8388907","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8388907","identity":"rs-8388907","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}