Abstract
Aims
The present study investigated receptor activator of nuclear factor kappa-Β ligand (RANKL), osteoprotegerin (OPG), and Runt-related transcription factor 2 (RUNX2) gene expressions in giant cell tumour of bone (GCTB) patients in relationship with tumour recurrence. We also aimed to investigate the influence of CpG methylation on the transcriptional levels of RANKL and OPG.
Methods
A total of 32 GCTB tissue samples were analyzed, and the expression of RANKL, OPG, and RUNX2 was evaluated by quantitative polymerase chain reaction (qPCR). The methylation status of RANKL and OPG was also evaluated by quantitative methylation-specific polymerase chain reaction (qMSP).
Results
We found that RANKL and RUNX2 gene expression was upregulated more in recurrent than in non-recurrent GCTB tissues, while OPG gene expression was downregulated more in recurrent than in non-recurrent GCTB tissues. Additionally, we proved that changes in DNA methylation contribute to upregulating the expression of RANKL and downregulating the expression of OPG, which are critical for bone homeostasis and GCTB development.
Conclusion
Our results suggest that the overexpression of RANKL/RUNX2 and the lower expression of OPG are associated with recurrence in GCTB patients.
Cite this article: Bone Joint Res 2024;13(2):84–91.
Article focus
-
The overexpression of receptor activator of nuclear factor kappa-Β ligand (RANKL)/Runt-related transcription factor 2 (RUNX2) and the lower expression of osteoprotegerin (OPG) are associated with tumour recurrence in giant cell tumour of bone (GCTB) patients.
Key messages
-
RANKL, RUNX2, and OPG have a crucial role in the recurrence and aggressive behaviour of GCTB.
Strengths and limitations
-
Our results indicate the upregulation of RANKL and RUNX2 and downregulation of OPG genes in recurrent GCTB cases compared with non-recurrent cases. This finding underlines their involvement and crucial role in GCTB recurrence.
-
We proved that changes in DNA methylation contribute to regulating the expression of OPG and RANKL genes, which are critical for bone homeostasis and GCTB development.
-
A small sample size was used, although we plan to increase the number of patients in future research.
Introduction
Giant cell tumour of bone (GCTB) is a relatively uncommon intermediate tumour. It is painful, with a high tendency to recur locally, and in rare cases it can undergo transformation to a malignant form.1 According to the most recent World Health Organization (WHO) classification,2 these tumours fall into the category of lesions with intermediate behaviour and locoregional aggressiveness, and in exceptional cases develop distant metastases.3 Tumour recurrence is a major problem: it is an enormous challenge encountered during the clinical treatment of GCTB,4 with incidence rates of 0% to 65%.5,6 Recurrence of GCTB is not fatal in most cases, but can lead to disability and poor quality of life as a result of repeated and radical operations, loss of bone stock, and secondary arthritis of the joints.7
The identification of risk factors influencing recurrence in GCTB is still under-developed. A previous study has reported that recurrence is influenced by clinical features, such as sex, age, location, tumour size, and surgery method.8 Moreover, certain factors were proposed as predictors of recurrence and aggressiveness markers in GCTB. Indeed, the overexpression of interleukin-17A (IL-17A) and β-catenin is closely associated with GCTB progression and recurrence.9
Moreover, the receptor activator of nuclear factor kappa-Β (RANK) pathway is often reported to be involved in the recurrence of GCTB. It is a key signalling system of bone remodelling that plays a critical role in the differentiation of precursors into multinucleated osteoclasts, which are responsible for bone resorption. The lack of RANK ligand (RANKL)-RANK-osteoprotegerin (OPG) signalling balance induces dysregulation of bone remodelling, which leads to changes in bone mass. This can be explained by an increase in bone destruction, bone metastasis, and the development of skeletal tumours.10 Previous reviews have focused on the association of this pathway in the pathogenesis and progression of GCTB, as well as discussing the possible therapeutic strategies by targeting this pathway.10,11 According to the Food and Drug Administration (FDA), some humanized monoclonal antibodies such as denosumab, which target the RANKL (RANKL inhibitor), have been employed in the treatment of GCTB when surgery is not possible, or is likely to result in severe morbidity.12 Recent studies have shown an elevated incidence of recurrence and sarcomatous transformation in patients with GCTB following denosumab therapy.13,14 Therefore, a new potential drug target is needed for GCTB.
Additionally, recent studies have identified that RANKL is bound to RANK on the surface of osteoblasts and transmits signals to increase the expression of downstream Runt-related transcription factor 2 (RUNX2), thereby promoting the differentiation and maturation of osteoblasts.15RUNX2, also known as core-binding factor α1 (Cbfa1), is a member of the Runt homology domain family of transcription factors, essential for osteoblast differentiation and bone formation. It is expressed in multipotent mesenchymal cells, osteoblast lineage cells, and chondrocytes.16
Several investigations have addressed the role of the trio RANKL/OPG/RUNX2 in GCTB aggressiveness.17,18 However, the identification of risk factors influencing recurrence, and the relationship between RANKL/OPG/RUNX2 expression and recurrence, are still not well explored. Moreover, others have confirmed that DNA methylation influenced the transcriptional expression of OPG and RANKL, which probably take on a ‘main switch’ role in the pathogenesis of bone diseases.19 Thus, for the first time, we aimed to explore the role of the ‘RUNX2/RANKL/OPG’ trio in GCTB recurrence. Our primary objectives were to identify and characterize the expression of the RANKL/OPG/RUNX2 trio in GCTB tissues using quantitative polymerase chain reaction (qPCR), and to examine their expression in relation to tumour recurrence. Additionally, we sought to investigate the impact of CpG-rich region methylation on the transcriptional messenger RNA (mRNA) levels of RANKL and OPG.
Methods
Patients and tissue samples
A total of 32 patients diagnosed with GCTB were enrolled in this study. Recruitment took place between 2018 and 2020 at our institution. All of the patients underwent their surgical procedures at our institution, and the tissue obtained during surgery underwent pathological examination reviewed by pathologists. All procedures performed in studies involving human participants were in accordance with the ethical standards of the National Committee of Medical Ethics, Tunisia.
Patients were scheduled for follow-up, which was defined as the time that elapsed from the confirmed diagnosis to the most recent follow-up date. These patients underwent their initial surgery for primary GCTB and were subsequently monitored for a maximum duration of 24 months. Based on their clinical status (recurrent or non-recurrent), we categorized the patients into two groups: recurrent GCTB and non-recurrent GCTB.
Ten control patients, comprising six females and four males, were included in the study. These controls were hospitalized due to fractures that occurred in healthy bones, which were non-tumoural, non-infectious, and not associated with any structural bone pathology. Samples were gathered from the cleaning products used during the fracture treatment process, without causing any harm or disruption to the patients’ treatment, as these were typically discarded bone debris. We collected these debris fragments to use them as references, since they consisted of fragments of healthy bone (patients consented beforehand to the collection of their bone samples).
Molecular analysis
RNA extraction and cDNA synthesis: TRIzol reagent (Invitrogen; Thermo Fisher Scientific, USA) was used to extract RNA from specimens according to the manufacturer’s protocol followed by quantification with NanoDropND-1000 (Thermo Fisher Scientific). A quantity of 300 ng of RNA served as a template for complementary DNA (cDNA) synthesis using hexamer primers (50 nmol) and a dNTP mix (10 nmol). This step was followed by ten-minute incubation at 70°C. Next, buffer, DTT (0.2 μmol), and SuperScriptM II RTase (200 units) were added. The reaction was then incubated for 12 minutes at 25°C followed by 50 minutes at 42°C, and a final incubation at 70°C for 15 minutes.
Quantitative polymerase chain reaction: qPCR was performed using SYBR green master mix (Bio-Rad, USA). Primer sequences and annealing temperature (T°) are described in Table I. The reaction was performed in a volume of 10 μl using the following protocol: denaturation at 95°C for five seconds, annealing at 58°C for 15 seconds, and extension at 72°C for 20 seconds, for 40 cycles. The relative amount of gene expression was calculated using the 2−ΔΔCt method, which was expressed by the mean (standard error). Experiments were performed in triplicate. The mean Ct values were calculated from triplicate PCRs for RANKL, OPG, RUNX2, and glyceraldehyde 3-phosphate dehydrogenase (GAPDH), and the ΔCt value for each specimen was obtained by subtracting these two values. Then the relative amount of RANKL, OPG, and RUNX2 expressions were calculated by the 2−ΔΔCt method.
Table I.
Primer sequences for quantitative polymerase chain reaction.
| Gene | F or R | Primer sequences (5’-3’) | Annealing T, °C |
|---|---|---|---|
| RANKL | Forward | 5’-CAA CAT ATC GTT GGA TCA CAG CA-3’ | 60 |
| Reverse | 5’-GAC AGA CTC ACT TTA TGG GAA CC-3’ | ||
| OPG | Forward | 5’-CAC AAA TTG CAG TGT CTT TGG TC-3’ | 60 |
| Reverse | 5’-TCT GCG TTT ACT TTG GTG CCA-3’ | ||
| GAPDH | Forward | 5’-GCTCTCTGCTCCTCCTGTTC-3’ | 60 |
| Reverse | 5’-CGCCCAATACGACCAAATCC-3’ | ||
| RUNX2 | Forward | 5’-CGGAATGCCTCTGCTGTTAT-3’ | 60 |
| Reverse | 5’-AGCTTCTGTCTGTGCCTTCT-3’ |
-
GAPDH, glyceraldehyde 3-phosphate dehydrogenase; OPG, osteoprotegerin; RANKL, receptor activator of nuclear factor kappa-Β ligand; RUNX2, Runt-related transcription factor 2; T, temperature.
Methylation analysis by qMSP
Genomic DNA was isolated with phenol-chloroform: isoamyl alcohol (15593031; Invitrogen). A volume of 1 μg of genomic DNA was modified by bisulfite treatment for 12 hours using EZ DNA Methylation kit (D5005; Zymo Research) according to the manufacturer’s instructions. After bisulfite conversion, the DNA was bound to a Zymo spin column and desulfonated. The bisulfite converted DNA was eluted from the column in 10 μl of elution buffer. This treatment deaminates unmethylated cytosines into uracil but does not affect 5-methylcytosines. DNA samples were subjected to quantitative methylation-specific polymerase chain reaction (qMSP) analysis.
qMSP is based on the amplification of bisulfite-converted DNA. Sodium bisulfite converts unmethylated cytosines to uracils, while methylated cytosines remain unaffected. Thus, it enables distinction between methylated and unmethylated DNA. Primers, which targeted CpG-rich regions within the RANKL and OPG promoter regions, were designed with Methyl Primer Express software (Applied Biosystems, USA). For each region, a pair of primers was selected: one specifically recognized the bisulfite-treated methylated DNA, and the other recognized only unmethylated bisulfite-treated DNA.20
Statistical analysis
All statistical analysis was performed with SPSS 20.0 (IBM, USA). Data are expressed as mean (standard deviation (SD)). The normality of distribution was checked using the Shapiro-Wilk test. Levene's test was performed to verify the homogeneity of variances. The independent-samples t-test was used to test the two groups of data. Analysis of variance (ANOVA) was used to test whether multiple sets of data were statistically significant. We used Mann-Whitney U test to determine if there was a significant difference between two groups (recurrent and non-recurrent patients). Pearson’s chi-squared test was used to determine if there was a significant association between two categorical variables (e.g. age, recurrence, gender). Pearson correlation coefficient to correlate the two study groups.
After performing qPCR and qMSP, the relative expression levels for each gene were determined using the 2−ΔΔCt method, normalized to the expression level of the housekeeping gene GAPDH. Statistical significance was set at p < 0.05.
Results
Clinicopathological characteristics of GCTB patients
The clinical and pathological features of 32 GCTB cases (11 male and 21 female) are summarized in Table II. Their ages ranged between 12 and 74 years, with a majority between 20 and 40 years (56.2%, n = 18). Tumours were mainly located in the radius (n = 10, 31%), tibia (n = 9, 28%), femur (n = 7, 22%), fibula (n = 3, 9.5%), and other rare locations (n = 3, 9.5%). The local recurrence rates were 47% overall, and 15/32 developed a recurrent tumour after surgery. Time of recurrence ranged from six to 24 months. The mean duration of follow-up from the time of diagnosis of GCTB was ten months (SD 5,154).
Table II.
Clinicopathological characteristics of giant cell tumour of bone patients.
| Categories | With recurrence | Without recurrence | Total | p-value* |
|---|---|---|---|---|
| Cases, n (%) | 15 (47) | 17 (53) | 32 | |
| Sex, n (%) | 0.061 | |||
| Male | 3 (20) | 8 (47.1) | 11 (34.4) | |
| Female | 12 (80) | 9 (52.9) | 21 (65.6) | |
| Age group, n (%) | 0.072 | |||
| < 20 yrs | 1 (6.7) | 3 (17.6) | 4 (12.5) | |
| 20 to 39 yrs | 10 (66.7) | 8 (47.1) | 18 (56.2) | |
| ≥ 40 yrs | 4 (26.7) | 6 (35.3) | 10 (31.2) | |
| Location, n (%) | 0.091 | |||
| Femur | 2 (13.3) | 5 (29.4) | 7 (21.9) | |
| Tibia | 4 (26.7) | 5 (29.4) | 9 ((28.1) | |
| Radius | 7 (46.7) | 3 (17.6) | 10 (31.2) | |
| Fibula | 1 (6.7) | 2 (11.8) | 3 (9.4) | |
| Other locations | 1 (6.7) | 2 (11.8) | 3 (9.4) | |
| Surgical method, n (%) | 0.031 | |||
| Biopsy | 0 (0.0) | 4 (23.5) | 4 (12.5) | |
| Intralesional curettage | 13 (86.7) | 8 (47.1) | 21 (65.6) | |
| Wide resection | 2 (13.3) | 5 (29.4) | 7 (21.9) |
-
*
Chi-squared test.
Curettage generally has a significantly higher recurrence rate than wide resection.21 Indeed, 21 of the total patients underwent curettage as a treatment. In addition, the present study revealed that the type of surgery is significantly associated with recurrence (p = 0.031, chi-squared test). In fact, 13 of 21 patients treated with curettage had a recurrence, while this occured in only two of the seven patients treated with wide resection. Therefore, there was no significant correlation between the location of the tumour, age, sex, and recurrence (p = 0.091, p = 0.072, p = 0.061, chi-squared test) (Table II).
Gene expression in recurrent GCTB disease
The expression levels of RANKL and OPG were investigated in 32 GCTB cases, and in ten normal bone tissues. The level of RANKL was significantly higher in GCTB tissues than in normal bone tissues (p = 0.01, chi-squared test). By contrast, the expression level of OPG was slightly, although still significantly, lower in GCTB tissues compared to normal bone tissues (p = 0.010, chi-squared test) (Figure 1).
Fig. 1
Expression levels of receptor activator of nuclear factor kappa-Β ligand (RANKL) and osteoprotegerin (OPG) in giant cell tumour of bone (GCTB) tissues and in normal tissues. ***p < 0.05.
Additionally, as demonstrated in Figure 2, Runx2 was highly expressed in GCTB tissues compared to normal bone tissues (p = 0.010, chi-squared test).
Fig. 2
Expression level of Runt-related transcription factor 2 (RUNX2) in giant cell tumour of bone (GCTB) tissues and in normal bone tissues. ***p < 0.05.
Furthermore, as shown in Figure 3, the expression status of RANKL and RUNX2 was significantly associated with sex (p = 0.011), age (p = 0.011), and the method of surgery (p = 0.011), while it was not correlated with the location of GCTB (p = 0.010, all chi-squared test). In fact, their expressions were associated specifically with female sex, higher age, and curettage. Moreover, the expression of OPG was only correlated with the method of surgery (p = 0.011, chi-squared test) (Figure 3).
Fig. 3
Correlation of receptor activator of nuclear factor kappa-Β ligand (RANKL), osteoprotegerin (OPG), and Runt-related transcription factor 2 (RUNX2) expressions with clinical data (Pearson correlation coefficient (r)).
Interestingly, RANKL and RUNX2 were strongly expressed in recurrent GCTB (p = 0.030, Pearson correlation coefficient). Fold change (Fc) values of 1.26 and 1.37 for RANKL and RUNX2, respectively, suggest that the expression of RANKL and RUNX2 was 26% and 37% higher in the recurrent group compared to the non-recurrent group, respectively (Table III). A significant association between the overexpression of RANKL/RUNX2 and recurrence was observed in all GCTB cases (p = 0.020, chi-squared test). More importantly, we confirmed the involvement of RANKL and RUNX2 in GCTB recurrence.
Table III.
Comparison of receptor activator of nuclear factor kappa-Β ligand and Runt-related transcription factor 2 expression levels in non-recurrent giant cell tumour of bone (GCTB) patients versus recurrent GCTB patients.
| Group | RANKL | RUNX2 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Mean | Fc | SD | SE | p-value* | Mean | Fc | SD | SE | p-value* | |
| Non-recurrent patients (n = 17) | 30.059 | 1.26 | 0.67 | 0.16 | 0.010 | 29.147 | 1.37 | 0.988 | 0.239 | 0.010 |
| Recurrent patients (n = 15) | 37.951 | 0.7 | 1.68 | 0.43 | 39.94 | 0.7 | 0.72 | 0.18 | ||
-
*
Independent-samples t-test.
-
Fc, fold change; RANKL, receptor activator of nuclear factor kappa-Β ligand; RUNX2, Runt-related transcription factor 2; SD, standard deviation; SE, standard error.
However, minimal amounts of OPG mRNA were detected in recurrent GCTB patients compared to non-recurrent GCTB patients. Indeed, a significant association was found between the lower expression of OPG and recurrence in GCTB patients (p = 0.041, chi-squared test) (Figure 4).
Fig. 4
Expression levels of receptor activator of nuclear factor kappa-Β ligand (RANKL), osteoprotegerin (OPG), and Runt-related transcription factor 2 (RUNX2) in non-recurrent and recurrent giant cell tumour of bone (GCTB) tissues and in controls. Association of the expression levels of RANKL and OPG with recurrence in GCTB. Correlations were tested using the non-parametric Mann-Whitney U test. **p < 0.05.
Accordingly, the identification of suitable molecular markers of malignancy, such as RANKL and RUNX2, would facilitate further exploration of the biological behaviour of GCTB, and identification of effective angiogenesis inhibitors.
Influence of DNA methylation on the expression of OPG/RANKL in GCTB
Previous bioinformatics analysis revealed two CpG islands in the RANKL gene: the upstream one (18 CpG sites), located at -14,415 bp from the transcription start site of isoform I (TSS I), the major RANKL transcript; and the downstream one (59 CpG sites), which spans from -260 bp to +615 bp of the TSS I. In this study, chose the downstream RANKL CpG region because the upstream one does not play an important role in the regulation of gene expression.20
We explored the methylation degree of the CpG-rich regions of the RANKL gene in GCTB tissues and in normal bone tissues. qMSP analysis showed that GCTB tissues, which expressed higher amounts of RANKL, showed lower methylation levels in the CpG island compared to normal tissues. RANKL’s lower methylation was correlated with higher transcriptional levels (p = 0.023, chi-squared test).
In terms of OPG gene expression and methylation, one island was found in the OPG gene (56 CpG sites), spanning from -402 to +850 bp of the TSS I. We explored the methylation degree of the CpG-rich regions of the OPG gene via qMSP in GCTB tissues and in controls. Then, GCTB tissues, which expressed lower amounts of OPG, showed higher methylation in the CpG island compared to control tissues. OPG aberrant methylation was correlated with transcriptional silencing.
Relationship between RANKL and OPG gene expression and their methylation degree
The inverse relationship observed between methylation status and mRNA expression of OPG and RANKL genes suggests that DNA methylation plays an important role in the regulation of gene expression during development. Methyl moieties at CpG residues suppress transcription by disrupting DNA-protein interactions, thus altering the accessibility of genes to trans-acting factors in the cell. Indeed, in GCTB tissues, RANKL overexpression correlates with a lower degree of methylation in the CpG regions. Conversely, lower expression of OPG correlates with hypermethylation in its promoter region (p < 0.01, Mann-Whitney U test).
To summarize, we revealed that the hypermethylation of the CpG-rich regions of OPG induced a decrease in OPG gene expression in GCTB tissues than in control tissues. However, lower methylation of the CpG regions of RANKL induced an increase in RANKL gene expression in the GCTB tissues, but not in the controls.
Discussion
The local recurrence rate in GCTB varies from 0% to 65% (4/19). There is a risk of pulmonary metastasis development in advanced or recurrent GCTB patients, with approximately 3% of cases metastasizing to the lungs.22 In this study, we aimed to investigate RANKL, OPG, and RUNX2 gene expressions in a cohort of GCTB patients in relation to tumour recurrence. We also aimed to investigate the influence of CpG methylation on the transcriptional levels of RANKL and OPG.
Within our cohort, no significant correlation was found between sex, age, location, and recurrence. However, some studies have reported a positive association between sex, age, and recurrence,23,24 whereas others have reported that location in the radius and proximal tibia was more frequently associated with tumour recurrence.25
RUNX2 is a multifunctional transcription factor and is considered to be one of the most important markers in the process of osteoblast differentiation and maturation.26 In this study, we found that the mRNA levels of RANKL and RUNX2 in tumours were significantly overexpressed more often in GCTB tissues than in normal bone tissues. Furthermore, OPG was upregulated more often in GCTB tissues than in controls. Indeed, RANK, which is secreted from the maturing osteoclasts, binds osteoblastic RANKL and promotes bone formation by triggering RANKL reverse signalling, which activates RUNX2.15RUNX2 is the most upstream transcription factor, essential for osteoblast differentiation. It regulates the expression of Sp7, the protein of which is a crucial transcription factor for osteoblast differentiation, as well as regulating the expression of bone matrix genes including Spp1, Ibsp, and Bglap2.27RUNX2, which is a vital factor in the RANKL-RANK pathway, is a key target for the regulation of bone destruction and is known to be associated with cell proliferation.28 Here, we have demonstrated the positive correlation between RUNX2 and RANKL expression and recurrence; this result suggests that, despite the multinuclear giant cells demonstrating bone absorption, the pivotal aspects of this process involve the recruitment and induction of osteoclast cells. These results would suggest that, during the development of GCTB, RUNX2 promotes osteoblast maturation through regulating RANKL and OPG, and this trio has a crucial role in the development and differentiation of GCTB.
Since we found an epigenetic modulation of RANKL and OPG gene expression levels, we explored whether differential levels of DNA methylation could explain the differences in gene transcription between non-recurrent GCTB tissues, recurrent GCTB tissues, and controls. It has previously been reported that epigenetic mechanisms, particularly DNA methylation, are known to be a principal contributor to gene transcription in many tissues, as extensively studied in neoplastic disorders including bone tumours.29,30 DNA methylation tends to block gene expression by mechanisms that are not well known, including the interference of the binding of transcription factors to the regulatory sites in DNA.31 Although there are some indications for the role of DNA methylation of the RANKL/OPG genes in murine models and cancer cells,32 it is still unknown whether DNA methylation regulates the expression of these genes in human bone. Therefore, we have studied the methylation profile of the RANKL downstream CpG-rich region, and the OPG CpG region in GCTB tissues and normal bone tissues. As a result, GCTB tissues that expressed higher amounts of RANKL, showed lower methylation in the CpG island than the control tissues. Meanwhile, for OPG, GCTB tissues that expressed lower amounts of OPG showed higher methylation in the CpG island than the control tissues. We can speculate that DNA methylation represents an on/off regulator of RANKL/OPG gene expression.
In our study, we identified an inverse relationship between DNA methylation levels and gene expression, which is consistent with findings from a previous study that have also confirmed this association.33 Thus, the CpG-rich regions of GCTB tissues, which highly expressed RANKL transcripts, were hypomethylated, whereas the CpG-rich regions of GCTB tissues, which hardly expressed OPG, were hypermethylated. A previously published study confirmed that changes in DNA methylation contribute to regulating the expression of RANKL and OPG genes, which are critical for bone homeostasis.19 In addition, another study demonstrated that DNA methylation influenced the transcriptional expression of OPG and RANKL, which probably took on a ‘main switch’ role in the pathogenesis of primary osteoporosis.20
In conclusion, this study unveiled a more pronounced upregulation of RANKL and RUNX2 genes and a more significant downregulation of OPG genes in GCTB tissues compared to controls. Intriguingly, this pattern was even more prominent in recurrent cases than in non-recurrent cases. This finding underlines the involvement of RANKL, RUNX2, and OPG and their role in GCTB recurrence. Moreover, we demonstrated that changes in DNA methylation contribute to regulating the expression of OPG and RANKL genes, which are critical for bone homeostasis and GCTB development.
References
1. Basu Mallick A , Chawla SP . Giant cell tumor of bone: an update . Curr Oncol Rep . 2021 ; 23 ( 5 ): 1 – 6 . Crossref PubMed Google Scholar
2. Larousserie F , Audard V , Burns R , de Pinieux G . Giant-cell tumor of bone in 2022 . Ann Pathol . 2022 ; 42 ( 3 ): 214 – 226. (Article in French) Crossref PubMed Google Scholar
3. Metovic J , Annaratone L , Linari A , et al. Prognostic role of PD-L1 and immune-related gene expression profiles in giant cell tumors of bone . Cancer Immunol Immunother . 2020 ; 69 ( 9 ): 1905 – 1916 . Crossref PubMed Google Scholar
4. Singh AS , Chawla NS , Chawla SP . Giant-cell tumor of bone: treatment options and role of denosumab . Biologics . 2015 ; 9 : 69 – 74 . Crossref PubMed Google Scholar
5. Klenke FM , Wenger DE , Inwards CY , Rose PS , Sim FH . Giant cell tumor of bone: risk factors for recurrence . Clin Orthop Relat Res . 2011 ; 469 ( 2 ): 591 – 599 . Crossref PubMed Google Scholar
6. Becker WT , Dohle J , Bernd L , et al. Local recurrence of giant cell tumor of bone after intralesional treatment with and without adjuvant therapy . J Bone Joint Surg Am . 2008 ; 90-A ( 5 ): 1060 – 1067 . Crossref PubMed Google Scholar
7. Szendröi M . Giant-cell tumour of bone . J Bone Joint Surg Br . 2004 ; 86-B ( 1 ): 5 – 12 . PubMed Google Scholar
8. Cheng D , Hu T , Zhang H , Huang J , Yang Q . Factors affecting the recurrence of giant cell tumor of bone after surgery: a clinicopathological study of 80 cases from a single center . Cell Physiol Biochem . 2015 ; 36 ( 5 ): 1961 – 1970 . Crossref PubMed Google Scholar
9. Matsubayashi S , Nakashima M , Kumagai K , et al. Immunohistochemical analyses of beta-catenin and cyclin D1 expression in giant cell tumor of bone (GCTB): a possible role of Wnt pathway in GCTB tumorigenesis . Pathol Res Pract . 2009 ; 205 ( 9 ): 626 – 633 . Crossref PubMed Google Scholar
10. Boyce BF , Xing L . Functions of RANKL/RANK/OPG in bone modeling and remodeling . Arch Biochem Biophys . 2008 ; 473 ( 2 ): 139 – 146 . Crossref PubMed Google Scholar
11. Wu P-F , Tang J , Li K . RANK pathway in giant cell tumor of bone: pathogenesis and therapeutic aspects . Tumour Biol . 2015 ; 36 ( 2 ): 495 – 501 . Crossref PubMed Google Scholar
12. Trovarelli G , Pala E , Angelini A , Ruggieri P . A systematic review of multicentric giant cell tumour with the presentation of three cases at long-term follow-up . Bone Joint J . 2022 ; 104-B ( 12 ): 1352 – 1361 . Crossref PubMed Google Scholar
13. Errani C , Tsukamoto S , Leone G , et al. Denosumab may increase the risk of local recurrence in patients with giant-cell tumor of bone treated with curettage . J Bone Joint Surg Am . 2018 ; 100-A ( 6 ): 496 – 504 . Crossref PubMed Google Scholar
14. Agarwal MG , Gundavda MK , Gupta R , Reddy R . Does denosumab change the giant cell tumor treatment strategy? Lessons learned from early experience . Clin Orthop Relat Res . 2018 ; 476 ( 9 ): 1773 – 1782 . Crossref PubMed Google Scholar
15. Ikebuchi Y , Aoki S , Honma M , et al. Coupling of bone resorption and formation by RANKL reverse signalling . Nature . 2018 ; 561 ( 7722 ): 195 – 200 . Crossref PubMed Google Scholar
16. Jin Y-H , Zhang J , Zhu H , Fan G-T , Zhou G-X . Functions of exogenous RUNX2 in giant cell tumor of bone in vitro . Orthop Surg . 2020 ; 12 ( 2 ): 668 – 678 . Crossref PubMed Google Scholar
17. De Vita A , Vanni S , Miserocchi G , et al. A rationale for the activity of bone target therapy and tyrosine kinase inhibitor combination in giant cell tumor of bone and desmoplastic fibroma: translational evidences . Biomedicines . 2022 ; 10 ( 2 ): 372 . Crossref PubMed Google Scholar
18. Komori T . Molecular mechanism of Runx2-dependent bone development . Mol Cells . 2020 ; 43 ( 2 ): 168 – 175 . Crossref PubMed Google Scholar
19. Lu T-Y , Kao C-F , Lin C-T , et al. DNA methylation and histone modification regulate silencing of OPG during tumor progression . J Cell Biochem . 2009 ; 108 ( 1 ): 315 – 325 . Crossref PubMed Google Scholar
20. Delgado-Calle J , Sañudo C , Fernández AF , García-Renedo R , Fraga MF , Riancho JA . Role of DNA methylation in the regulation of the RANKL-OPG system in human bone . Epigenetics . 2012 ; 7 ( 1 ): 83 – 91 . Crossref PubMed Google Scholar
21. Li D , Zhang J , Li Y , et al. Surgery methods and soft tissue extension are the potential risk factors of local recurrence in giant cell tumor of bone . World J Surg Oncol . 2016 ; 14 : 114 . Crossref PubMed Google Scholar
22. Amri R , Charfi S , Jemaà M , et al. Significance of EGFR/HER2 expression and PIK3CA mutations in giant cell tumour of bone development . BioMed Research International . 2020 ; 2020 : 1 – 11 . Crossref Google Scholar
23. Chan CM , Adler Z , Reith JD , Gibbs CP Jr . Risk factors for pulmonary metastases from giant cell tumor of bone . J Bone Joint Surg Am . 2015 ; 97-A ( 5 ): 420 – 428 . Crossref PubMed Google Scholar
24. Amelio JM , Rockberg J , Hernandez RK , et al. Population-based study of giant cell tumor of bone in Sweden (1983-2011) . Cancer Epidemiol . 2016 ; 42 : 82 – 89 . Crossref PubMed Google Scholar
25. Hu P , Zhao L , Zhang H , et al. Recurrence rates and risk factors for primary giant cell tumors around the knee: a multicentre retrospective study in China . Sci Rep . 2016 ; 6 ( 1 ): 36332 . Crossref PubMed Google Scholar
26. Siddiqui MA , Seng C , Tan MH . Risk factors for recurrence of giant cell tumours of bone . J Orthop Surg (Hong Kong) . 2014 ; 22 ( 1 ): 108 – 110 . Crossref PubMed Google Scholar
27. Komori T . Roles of Runx2 in Skeletal Development . Adv Exp Med Biol . 2017 ; 962 : 83 – 93 . Crossref PubMed Google Scholar
28. Esteller M . Epigenetics in cancer . N Engl J Med . 2008 ; 358 ( 11 ): 1148 – 1159 . Crossref PubMed Google Scholar
29. Ulaner GA , Vu TH , Li T , et al. Loss of imprinting of IGF2 and H19 in osteosarcoma is accompanied by reciprocal methylation changes of a CTCF-binding site . Hum Mol Genet . 2003 ; 12 ( 5 ): 535 – 549 . Crossref PubMed Google Scholar
30. Klose RJ , Bird AP . Genomic DNA methylation: the mark and its mediators . Trends Biochem Sci . 2006 ; 31 ( 2 ): 89 – 97 . Crossref PubMed Google Scholar
31. Kitazawa R , Kitazawa S . Methylation status of a single CpG locus 3 bases upstream of TATA-box of receptor activator of nuclear factor-kappaB ligand (RANKL) gene promoter modulates cell- and tissue-specific RANKL expression and osteoclastogenesis . Mol Endocrinol . 2007 ; 21 ( 1 ): 148 – 158 . Crossref PubMed Google Scholar
32. Turner DC , Gorski PP , Maasar MF , et al. DNA methylation across the genome in aged human skeletal muscle tissue and muscle-derived cells: the role of HOX genes and physical activity . Sci Rep . 2020 ; 10 ( 1 ): 15360 . Crossref PubMed Google Scholar
33. Huan T , Mendelson M , Joehanes R , et al. Epigenome-wide association study of DNA methylation and microRNA expression highlights novel pathways for human complex traits . Epigenetics . 2020 ; 15 ( 1–2 ): 183 – 198 . Crossref PubMed Google Scholar
Author contributions
R. Amri: Funding acquisition, Formal analysis.
A. Chelly: Formal analysis.
M. Ayedi: Formal analysis.
M. A. Rebaii: Writing – review & editing.
S. Aifa: Writing – review & editing.
S Masmoudi: revised the paper
H. Keskes: Writing – review & editing.
Funding statement
The authors disclose receipt of the following financial or material support for the research, authorship, and/or publication of this article: this work was funded by the Tunisian Ministry of Higher Education and Scientific Research.
Data sharing
The data that support the findings for this study are available to other researchers from the corresponding author upon reasonable request.
Acknowledgements
The authors thank the patients and their families for their cooperation in the present study. They also express their sincere gratitude to the following pathologists, whose expertise and invaluable contributions greatly enriched this project: Dr Slim Charfi, Dr Boudawara Tahia (Department of Pathology, Habib Bourguiba Hospital, Road El Ain, 3029 Sfax, Tunisia).
Ethical review statement
All procedures performed in studies involving human participants were in accordance with the ethical standards of the National Committee of Medical Ethics, Tunisia.
Open access funding
The authors report that the open access funding for their manuscript was self-funded.
© 2024 Amri et al. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (CC BY-NC-ND 4.0) licence, which permits the copying and redistribution of the work only, and provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc-nd/4.0/
