Abstract
Objective
Delayed fracture healing (DFH) is a major clinical challenge, and sensitive molecular biomarkers remain lacking. This study focused on the regulatory roles of lncRNA DLX6-AS1 and miR-141-3p in DFH.
Methods
A total of 192 patients were enrolled and classified into normal fracture healing (NFH) and DFH groups. Serum samples were analyzed for DLX6-AS1 and miR-141-3p levels via qRT-PCR. Diagnostic value and risk associations were assessed using ROC curves and logistic regression. Human bone marrow mesenchymal stem cells (hBMSCs) were induced to undergo chondrogenic differentiation. Cellular activity including proliferation and apoptosis was measured. Dual-luciferase and rescue assays explored interactions among DLX6-AS1, miR-141-3p, and VEGFA.
Results
DLX6-AS1 expression was notably reduced, whereas miR-141-3p was elevated in DFH patients. Both were identified as independent risk factors for DFH. The combined detection of two RNAs demonstrated excellent diagnostic performance. Functional assays revealed that DLX6-AS1 promoted, while miR-141-3p suppressed, hBMSCs proliferation, survival, and chondrogenic differentiation. DLX6-AS1 bound miR-141-3p through a sponging mechanism. miR-141-3p directly targeted VEGFA, which was reduced in DFH and inversely correlated with miR-141-3p abundance. Mechanistic analysis confirmed that the DLX6-AS1/miR-141-3p/VEGFA axis regulates hBMSCs proliferation, apoptosis, and chondrogenic differentiation of fracture healing.
Conclusion
DLX6-AS1 and miR-141-3p emerge as independent risk indicators and potential diagnostic biomarkers for DFH. By modulating the miR-141-3p/VEGFA axis, DLX6-AS1 influences chondrocyte differentiation and fracture repair, highlighting this pathway as a viable target.
Supplementary Information
The online version contains supplementary material available at 10.1186/s13018-025-06478-5.
Keywords: DLX6-AS1, miR-141-3p, VEGFA, Chondrogenic differentiation, Delayed fracture healing
Introduction
With the increasing prevalence of clinical risk factors such as aging, obesity, and diabetes, the number of fracture patients continues to rise annually [1]. Despite advances in treatment, approximately 5%-10% of fractures fail to heal properly, resulting in nonunion or delayed fracture healing (DFH) [2, 3]. DFH is generally referred to as a fracture that does not heal within nine months after injury or fails to show signs of progression within the preceding three months [4]. Fracture repair is a complex and highly orchestrated event that involves four overlapping phases: the early inflammatory phase, soft and hard callus formation, and bone remodeling [5, 6]. Among these, chondrocyte differentiation plays a pivotal role by stabilizing the fracture site through soft callus formation, which serves as a scaffold for subsequent endochondral ossification and bone regeneration [7]. Although various strategies—such as surgical interventions, biophysical stimulation, and osteoinductive factors—have been employed to promote fracture repair, consensus regarding the optimal treatment remains lacking [8–10]. Moreover, non-surgical approaches, including cell-based therapy, molecular therapy, and gene therapy, though promising, are still under development [11–14]. Importantly, the diagnosis of DFH often requires prolonged observation, and reliable early predictive biomarkers are lacking. This delay not only hampers timely intervention but also imposes significant financial and psychological burdens on patients and their families [4, 15]. Therefore, identifying early diagnostic markers and elucidating the molecular mechanisms underlying DFH are of great clinical significance [16].
Advances in next-generation sequencing have revealed that only ~ 2% encodes proteins, illustrating the widespread regulatory role of noncoding RNAs [17–19]. lncRNAs and miRNAs have emerged as key regulators of diverse biological processes [20–22]. LncRNAs interact with miRNAs to form intricate regulatory networks that influence cellular homeostasis and disease progression [23, 24]. Their involvement in stem cell biology is well documented. For instance, ADAMTS9-AS2 regulates cartilage differentiation of mesenchymal stem cells (MSCs) during cartilage repair [25], while LINC00963 promotes osteogenic differentiation of bone marrow-derived MSCs in osteoporosis by targeting miR-760 [26].
DLX6-AS1, located on chromosome 7q21.3, has recently been identified as a potential regulator in multiple diseases. RNA-seq data and WGCNA analysis implicated DLX6-AS1 in pathways related to cartilage differentiation and formation [27]. Furthermore, DLX6-AS1 expression is upregulated during chondrocyte differentiation using public datasets analysis [28]. However, its function in fracture healing remains unexplored. Our previous bioinformatics analysis predicted a direct binding interaction between DLX6-AS1 and miR-141-3p, a miRNA that has been reported to negatively regulate bone health [29]. Based on these findings, it is hypothesized that DLX6-AS1 may influence chondrocyte differentiation during fracture healing by modulating miR-141-3p.
In this study, the DLX6-AS1/miR-141-3p regulatory axis in DFH was investigated. We examined the expression levels and diagnostic performance of DLX6-AS1 and miR-141-3p in DFH and constructed an in vitro BMSC-derived chondrocyte differentiation model to explore their functional interplay. The targeting relationship between RNAs and the effects of the regulatory axis on chondrogenic differentiation, cell proliferation, and apoptosis were assessed. These results offer new understanding of the molecular mechanisms driving DFH and establish a theoretical foundation for future diagnostic and therapeutic strategies.
Materials and methods
Study subjects
192 patients with tibial fractures admitted to the Huanggang Central Hospital between 2020 and 2022 were enrolled in this study, including 96 patients with DFH and 96 patients with normal fracture healing (NFH). DFH was defined as the presence of minimal or absent callus formation, a persistent fracture line, or a distinct fracture gap on X-ray examination three months after treatment and follow-up. All patients had a history of trauma, and fractures were confirmed radiographically. Patients with incomplete clinical data, abnormal cardiac, renal, or hepatic function, immune disorders, infectious diseases, osteoporosis, or other metabolic bone diseases affecting bone metabolism were excluded.
Written informed consent was obtained from all participants. The study protocol was reviewed and approved by the Ethics Committee of Huanggang Central Hospital and conducted in accordance with the Declaration of Helsinki.
For each patient, 5 mL of fasting peripheral venous blood was collected on the day following admission. Samples were centrifuged (3000 rpm, 10 min) at 4 °C to obtain serum, which was aliquoted and stored at − 80 °C.
Cell culture and transfection
Human bone marrow mesenchymal stem cells (hBMSCs) were obtained from ATCC (USA). Cells were cultured in DMEM (Gibco, USA) supplemented with 10% FBS (Gibco). To induce chondrogenic differentiation, hBMSCs were seeded in differentiation medium containing transforming growth factor-β3 (TGF-β3, 10 ng/mL; PeproTech, USA), with medium replaced every 2–3 days.
Small interfering RNA targeting DLX6-AS1 (si-DLX6-AS1), negative control siRNA (si-NC), miR-mimic, miR-inhibitor, corresponding controls (miR-NC), and VEGFA overexpression plasmid (oe-VEGFA) were synthesized by GenePharma (Shanghai, China). Transfections were performed using Lipofectamine 3000 (Invitrogen, USA).
qRT-PCR
RNA was extracted from serum or cultured cells using TRIzol (Invitrogen, USA). The concentration and purity were assessed spectrophotometrically (Thermo Fisher Scientific, USA). cDNA was synthesized using the PrimeScript RT Reagent Kit and Mir-X miRNA First-Strand Synthesis Kit (Takara, Japan). qRT-PCR was performed with SYBR Premix Ex Taq II (Takara). GAPDH and U6 were used as internal controls. Relative expression was quantified using the 2–ΔΔCt method. The qRT-PCR primer sequences used in this study have now been summarized in Supplementary Table S1.
Dual-luciferase reporter assay
The predicted target sites between DLX6-AS1 and miR-141-3p, as well as between miR-141-3p and VEGFA, were identified by bioinformatics databases (starBase). Wild-type (WT) and mutant-type (MUT) sequences of DLX6-AS1 or VEGFA 3′UTR were cloned into the pmirGLO luciferase reporter vector (Promega, USA). Cells were co-transfected with WT or MUT constructs and either miR-mimic or miR-NC using Lipofectamine 3000. After 48 h, luciferase activity was measured.
Cell proliferation
Cell proliferation was assessed using CCK-8 (Dojindo, Japan). Transfected hBMSCs were seeded in 96-well plates (2 × 103 cells/well). At different cultured time points (0, 24, 48, and 72 h), 10 μL of CCK-8 reagent was added and incubated for 2 h. Absorbance at 450 nm was measured.
Cell apoptosis
Cell apoptosis was detected using the Annexin V-FITC/PI Apoptosis Detection Kit (BD Biosciences, USA). Briefly, transfected hBMSCs were harvested, washed with cold PBS, and resuspended in binding buffer. Cells were stained with Annexin V-FITC and PI for 15 min in the dark at room temperature and analyzed by flow cytometry (BD FACSCanto II, BD Biosciences). Data were processed using FlowJo software.
Statistical analysis
GraphPad Prism 9.0 (GraphPad Software, USA) and R software (version 4.4.0) were used. all experiments were performed with at least three independent biological replicates, and results are presented as mean ± standard deviation (SD). Student’s t-test, chi-square test, and one-way ANOVA followed by Bonferroni’s test were applied. Pearson correlation analysis assessed associations between variables. Receiver operating characteristic (ROC) curves were used to evaluate diagnostic performance, and logistic regression was performed to identify risk factors for DFH. A p-value < 0.05 was statistically significant.
Results
Baseline characteristics
Patient baseline characteristics for the NFH and DFH groups are listed in Table 1. No statistically significant differences were detected in age, BMI, gender, smoking, drinking, hypertension, hyperlipidemia, or disease severity (P > 0.05, Table 1). Although patients with diabetes tended to have a higher likelihood of developing DFH, the difference failed to achieve statistical significance (P = 0.083, Table 1).
Table 1.
Baseline characteristics
| Parameters | NFH (n = 96) | DFH (n = 96) | P-value |
|---|---|---|---|
| Age, years | 50.98 ± 12.03 | 50.73 ± 11.34 | 0.882 |
| BMI | 22.44 ± 2.48 | 22.92 ± 2.43 | 0.173 |
| Gender | 1.000 | ||
| Female | 42 | 43 | |
| Male | 54 | 53 | |
| Smoking | 0.654 | ||
| No | 38 | 34 | |
| Yes | 58 | 62 | |
| Drinking | 0.878 | ||
| No | 33 | 31 | |
| Yes | 63 | 65 | |
| Hypertension | 0.310 | ||
| No | 48 | 40 | |
| Yes | 48 | 56 | |
| Hyperlipidemia | 0.659 | ||
| No | 59 | 55 | |
| Yes | 37 | 41 | |
| Diabetes | 0.083 | ||
| No | 80 | 69 | |
| Yes | 16 | 27 | |
| Severity | 0.293 | ||
| Incomplete fracture | 39 | 31 | |
| Complete fracture | 57 | 65 | |
BMI, Body mass index; DFH, Delayed fracture healing; NFH, Normal fracture healing
Clinical significance of DLX6-AS1 and miR-141-3p
DLX6-AS1 levels were significantly downregulated in DFH patients (P < 0.05, Fig. 1A), whereas miR-141-3p expression was markedly increased compared with NFH controls (P < 0.05, Fig. 1B). Logistic regression identified DLX6-AS1 and miR-141-3p as independent predictors of DFH (P < 0.05, Fig. 1C). ROC analysis further demonstrated robust diagnostic performance, with area under the curve (AUC) exceeding 0.8 for each biomarker alone. Notably, their combined application yielded an AUC of 0.950, with a sensitivity of 0.822 and specificity of 0.958 (Fig. 1D).
Fig. 1.
Expression patterns and diagnostic value of DLX6-AS1 and miR-141-3p in DFH. A, B DLX6-AS1 A and miR-141-3p B levels in NFH (n = 96) and DFH (n = 96) patients. C Logistic regression analysis identifying risk factors for DFH. D ROC curves evaluating the diagnostic performance. NFH, normal fracture healing; DFH, delayed fracture healing. ***P < 0.001
Interaction and expression of DLX6-AS1/miR-141-3p in hBMSCs
Bioinformatic prediction suggested complementary binding sites between DLX6-AS1 and miR-141-3p (Fig. 2A), which were experimentally confirmed. Luciferase activity was downregulated in the wild-type DLX6-AS1 construct, but not with the mutant construct (P < 0.05, Fig. 2B). A significant inverse correlation was detected between their serum levels (P < 0.05, Fig. 2C). During hBMSC chondrogenic differentiation, expression of SOX9, COL2A1, and ACAN progressively increased over days 0, 7, and 14 (P < 0.05, Fig. 2D), accompanied by elevated DLX6-AS1 and reduced miR-141-3p abundance (P < 0.05, Fig. 2E).
Fig. 2.
Interaction between DLX6-AS1 and miR-141-3p. A Predicted target sites. B Dual-luciferase reporter validation of the interaction. C Correlation analysis of serum DLX6-AS1 and miR-141-3p levels. D, E Expression of chondrogenic differentiation markers D, DLX6-AS1, and miR-141-3p E during hBMSCs chondrogenic differentiation. Data are presented as mean ± SD. Statistical analysis was performed using Student’s t-test or one-way ANOVA (n = 3). hBMSCs, Human bone marrow mesenchymal stem cells. *P < 0.05, **P < 0.01, ***P < 0.001
Silencing DLX6-AS1 significantly decreased its expression while elevating miR-141-3p levels (P < 0.05, Fig. 3A). Co-transfection with miR-inhibitor partially restored miR-141-3p suppression without affecting DLX6-AS1 expression (P < 0.05, Fig. 3A). Functionally, si-DLX6-AS1 promoted hBMSCs proliferation and inhibited apoptosis, whereas inhibition of target miRNA partially reversed these influences (P < 0.05, Fig. 3B, C). Furthermore, DLX6-AS1 silencing upregulated chondrogenic markers SOX9, COL2A1, and ACAN, an effect again attenuated by miR-inhibition (P < 0.05, Fig. 3D).
Fig. 3.
Effect of DLX6-AS1/miR-141-3p on hBMSCs functions. A qRT-PCR analysis of DLX6-AS1 and miR-141-3p after si-DLX6-AS1 treatment with or without miR-inhibition. B Proliferation level. C Apoptosis rate. D Expression of chondrogenic differentiation markers SOX9, COL2A1, and ACAN. Data are presented as mean ± SD. Statistical analysis was performed using Student’s t-test or one-way ANOVA (n = 3). hBMSCs, Human bone marrow mesenchymal stem cells. *P < 0.05, **P < 0.01, ***P < 0.001
The functional impact of miR-141-3p/VEGFA
StarBase analysis identified a putative binding site between miR-141-3p and VEGFA (Fig. 4A). miR-mimics suppressed luciferase activity of WT-VEGFA but not MUT-VEGFA (P < 0.05, Fig. 4B). qRT-PCR further showed VEGFA was significantly downregulated in DFH compared with NFH (P < 0.05, Fig. 4C). An inverse relationship between VEGFA and miR-141-3p, while VEGFA was directly correlated with DLX6-AS1 (P < 0.05, Fig. 4D, E).
Fig. 4.
VEGFA is a binding target of miR-141-3p. A Predicted binding sequence. B Dual-luciferase assay validation. C VEGFA expression levels in NFH (n = 96) vs DFH (n = 96) patients. D, E Correlation analyses between VEGFA and miR-141-3p or DLX6-AS1 (n = 96). Data are presented as mean ± SD. Statistical analysis was performed using Student’s t-test or one-way ANOVA. hBMSCs, Human bone marrow mesenchymal stem cells. NFH, normal fracture healing; DFH, delayed fracture healing. **P < 0.01, ***P < 0.001
Upregulation of miR-141-3p enhanced its abundance while markedly reducing VEGFA expression; co-treatment with oe-VEGFA rescued VEGFA expression but did not alter miR-141-3p (P < 0.05, Fig. 5A). Functionally, miR-141-3p overexpression suppressed cell proliferation and enhanced apoptosis, effects that were partially reversed by VEGFA restoration (P < 0.05, Fig. 5B, C). Moreover, miR-mimic reduced SOX9, COL2A1, and ACAN expression, whereas VEGFA overexpression mitigated this suppression (P < 0.05, Fig. 5D).
Fig. 5.
Functional role of the miR-141-3p/VEGFA axis in hBMSCs. A miR-141-3p and VEGFA abundance after transfection. B Proliferation assessed. C Apoptosis analysis. D Expression of chondrogenic differentiation markers after indicated treatments. Data are presented as mean ± SD. Statistical analysis was performed using Student’s t-test or one-way ANOVA (n = 3). hBMSCs, Human bone marrow mesenchymal stem cells. *P < 0.05, **P < 0.01, ***P < 0.001
Discussion
Fractures are among the most common traumatic injuries, and both their incidence and the rate of poor healing are rising [30–32]. Currently, no molecular markers with sufficient sensitivity and stable dynamic detectability are available for the clinical diagnosis of delayed fracture healing [15, 33]. Radiographically, DFH is characterized by visible fracture lines, lack of sclerosis or resorption at fracture ends, and minimal or discontinuous callus formation [34]. DFH is influenced by both endogenous and exogenous factors. Diabetes has been reported as a risk factor for impaired fracture repair [35], and the findings are consistent with this trend, showing a higher likelihood of DFH in diabetic patients, although not reaching statistical significance. More importantly, DLX6-AS1 and miR-141-3p were recognized as risk factors for DFH. Their altered expression profiles, significant diagnostic performance, and robust ROC values-particularly when analyzed in combination-highlight their promise as potential biomarkers for DFH.
During fracture repair, MSCs are recruited to the injury site and predominantly differentiate into chondrocytes [36, 37]. These chondrocytes secrete type II collagen and proteoglycans to form a soft callus, which provides initial stability and a framework for endochondral ossification [38]. In this study, hBMSCs were used to induce chondrogenic differentiation, a biologically relevant model of fracture healing [39]. SOX9, COL2A1, and ACAN-markers of early chondrogenesis significantly upregulated, confirming successful differentiation. SOX9 functions as a master transcription factor, directing MSCs toward the chondrocyte lineage and regulating COL2A1 and ACAN, which encode structural proteins and proteoglycans essential for cartilage callus formation [40, 41]. Notably, DLX6-AS1 expression increased, while miR-141-3p expression decreased during chondrogenic induction, implicating their involvement in this process. Cell proliferation and apoptosis are key indicators of cellular growth potential and overall health, and are widely used to assess changes in physiological function. For instance, disruption of IHH signaling has been shown to suppress chondrocyte proliferation [42], thereby impairing endochondral osteoblast development. Activation of UCHL1 can inhibit apoptosis and preserve mitochondrial function in chondrocytes [43]. Functional assays further demonstrated that DLX6-AS1 knockdown or miR-141-3p overexpression impaired cell viability and promoted apoptosis, underscoring their regulatory role in chondrogenesis.
Mechanistically, lncRNAs frequently function as ceRNAs that sponge miRNAs to modulate downstream targets [44–46]. Several precedents exist: LINC00665 regulates BMSC viability and chondrogenesis via miR-214-3p [47], while MEG3 influences chondrogenic differentiation through the miR-129-5p/RUNX1 axis [48]. In line with this paradigm, DLX6-AS1 directly binds miR-141-3p was confirmed. Enhanced miR-141-3p expression reversed DLX6-AS1-mediated effects on chondrogenesis, supporting their antagonistic interaction. Since miRNAs bind to target mRNAs, they can induce mRNA degradation or inhibit translation, thereby regulating target gene function [49]. The downstream of miR-141-3p target, VEGFA, was screened. VEGFA, a known pro-angiogenic factor critical in fracture healing. Previous studies have shown that VEGFA expression is upregulated during bone repair in animal models [50], while this study demonstrated suppressed VEGFA expression in DFH. Importantly, restoring VEGFA expression reversed the suppressive influence of miR-141-3p on cell activity and chondrogenic differentiation. Chondrocytes represent one of the major sources of VEGFA. As a potent angiogenic factor, VEGFA promotes the ingrowth of new blood vessels into the cartilage callus, thereby facilitating endochondral ossification [51]. VEGFA has also been reported to increase during osteogenic differentiation [52], further supporting its protective role in bone regeneration. In glucocorticoid-induced bone microvascular endothelial cell injury models, VEGFA has been shown to be closely associated with the activation of the PI3K/AKT signaling pathway [53]. In pharmacological studies, Tubiechong treatment was found to promote tibial fracture healing in rats through the VEGF/ERK1/2 signaling pathway [54]. Similarly, Osteoking exerts its therapeutic effects on bone fracture repair by modulating VEGFA and the EGF/EGFR/Wnt signaling axis [55]. Collectively, these findings indicate that VEGFA serves as a key molecular hub connecting multiple signaling pathways involved in bone repair and regeneration. Although this study primarily focused on the miR-141-3p/VEGFA regulatory relationship, future work should further investigate these downstream mechanisms to clarify how VEGFA exerts its effects on chondrogenesis. Collectively, our findings suggest that DLX6-AS1 regulates chondrogenesis through the miR-141-3p/VEGFA axis, thereby influencing fracture healing.
This study has limitations. All functional experiments in this study were conducted in vitro using osteoblast-related cell models. Although these findings provide mechanistic insights into fracture healing, the in vitro system cannot fully represent the complex in vivo environment. Future studies employing animal fracture models are warranted to verify whether the identified molecular mechanisms contribute to bone regeneration in vivo. Future studies should also investigate additional molecular targets and signaling pathways to further clarify the regulatory networks involved in impaired fracture healing. Furthermore, despite the high AUC values observed, the absence of an external validation cohort limits the generalizability of the ROC results, and potential overfitting cannot be completely excluded. While internal validation was performed using the existing dataset, future studies with larger, multicenter cohorts are needed to further confirm the diagnostic value and generalizability of the model. Additionally, expanding the sample size and incorporating independent validation datasets will enhance the robustness and clinical applicability of the findings.
Conclusion
In summary, DLX6-AS1 and miR-141-3p were found to be independent risk factors for DFH with strong diagnostic value. Mechanistically, DLX6-AS regulates the miR-141-3p/VEGFA axis to influence proliferation, apoptosis, and chondrogenic differentiation of hBMSCs. Given their diagnostic potential and regulatory roles in bone repair, the DLX6-AS1/miR-141-3p/VEGFA axis may serve as both a diagnostic biomarker and a therapeutic target for DFH.
Supplementary Information
Below is the link to the electronic supplementary material.
Author contributions
All authors designed this study.MD Z, G C, Y R and JX Z conducted the experiment and analyzed the data. MD Z and G C wrote the manuscript. JX Z revised the manuscript. All authors reviewed and approved for publication.
Funding
Not applicable.
Data availability
All data generated or analyzed during this study are included in this article and its supplementary material files. Further enquiries can be directed to the corresponding author.
Declarations
Ethics approval and consent to participate
The study protocol was approved by The Ethics Committee of Huanggang Central Hospital. All procedures performed in studies involving human participants were in accordance with the 1964 Helsinki Declaration and later versions.
Consent for publication
All patients provided written informed consent.
Competing interests
There is no conflict of interest in this study.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Mingdong Zhang and Gong Chen have made equal contributions to this article.
References
- 1.Clynes MA, Harvey NC, Curtis EM, Fuggle NR, Dennison EM, Cooper C. The epidemiology of osteoporosis. Br Med Bull. 2020;133(1):105–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Steppe L, Megafu M, Tschaffon-Müller MEA, Ignatius A, Haffner-Luntzer M. Fracture healing research: recent insights. Bone Rep. 2023;19:101686. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Ji X, Zhao D, Xin Z, Feng H, Huang Z. The predictive value of stress-induced hyperglycemia parameters for delayed healing after tibial fracture post-surgery. J Orthop Surg Res. 2024;19(1):666. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Nicholson JA, Yapp LZ, Keating JF, Simpson AHRW. Monitoring of fracture healing. Update on current and future imaging modalities to predict union. Injury. 2021;52(Suppl 2):S29–34. [DOI] [PubMed] [Google Scholar]
- 5.Ghiasi MS, Chen JE, Rodriguez EK, Vaziri A, Nazarian A. Computational modeling of human bone fracture healing affected by different conditions of initial healing stage. BMC Musculoskelet Disord. 2019;20(1):562. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Gargano G, Oliviero A, Oliva F, Maffulli N. Small interfering RNAs in tendon homeostasis. Br Med Bull. 2021;138(1):58–67. [DOI] [PubMed] [Google Scholar]
- 7.Wong SA, Rivera KO, Miclau T, Alsberg E, Marcucio RS, Bahney CS. Microenvironmental regulation of chondrocyte plasticity in endochondral repair-a new frontier for developmental engineering. Front Bioeng Biotechnol. 2018;6:58. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Migliorini F, Cocconi F, Vecchio G, Schäefer L, Koettnitz J, Maffulli N. Pharmacological agents for bone fracture healing: talking points from recent clinical trials. Expert Opin Investig Drugs. 2023;32(9):855–65. [DOI] [PubMed] [Google Scholar]
- 9.Khanna A, Gougoulias N, Maffulli N. Intermittent pneumatic compression in fracture and soft-tissue injuries healing. Br Med Bull. 2008;88(1):147–56. [DOI] [PubMed] [Google Scholar]
- 10.Liu J, Liu T-T, Zhang H-C, Li C, Wei W, Chao A-J. Effects of Jintiange on the healing of osteoporotic fractures in aged rats. J Orthop Surg Res. 2024;19(1):828. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Ganse B. Methods to accelerate fracture healing - a narrative review from a clinical perspective. Front Immunol. 2024;15:1384783. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Gargano G, Oliva F, Oliviero A, Maffulli N. Small interfering RNAs in the management of human rheumatoid arthritis. Br Med Bull. 2022;142(1):34–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Gargano G, Asparago G, Spiezia F, Oliva F, Maffulli N. Small interfering RNAs in the management of human osteoporosis. Br Med Bull. 2023;148(1):58–69. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Martinez de Albornoz P, Khanna A, Longo UG, Forriol F, Maffulli N. The evidence of low-intensity pulsed ultrasound for in vitro, animal and human fracture healing. Br Med Bull. 2011;100:39–57. [DOI] [PubMed] [Google Scholar]
- 15.Lee C, Copp J. Future modalities to assess fracture healing. OTA Int. 2022;5(1 Suppl):e161. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Yang X, Yin P, Yao X, Zhang J. Micrornas in the diagnosis of osteoarthritis: a systematic review and meta-analysis of observational studies. J Orthop Surg Res. 2025;20(1):654. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Gargano G, Pagano SM, Maffulli N. Circular RNAs in the management of human osteoporosis. Br Med Bull. 2025;153(1). 10.1093/bmb/ldae024. [DOI] [PubMed] [Google Scholar]
- 18.Li Y, Sun Y, Ma K, Wang S, Wang Z, Huang L. Functional mechanism and clinical implications of LINC00339 in delayed fracture healing. J Orthop Surg Res. 2024;19(1):511. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Yang X, Jin Q, Guo L. Mir-217 participates in the progression of postmenopausal osteoporosis by regulating the OPG/RANKL/RANK pathway. J Orthop Surg Res. 2025;20(1):600. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Zhu S, Wang J, He Y, Meng N, Yan G-R. Peptides/proteins encoded by non-coding RNA: a novel resource bank for drug targets and biomarkers. Front Pharmacol. 2018;9:1295. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Kaikkonen MU, Lam MTY, Glass CK. Non-coding RNAs as regulators of gene expression and epigenetics. Cardiovasc Res. 2011;90(3):430–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Giordano L, Porta GD, Peretti GM, Maffulli N. Therapeutic potential of microRNA in tendon injuries. Br Med Bull. 2020;133(1):79–94. [DOI] [PubMed] [Google Scholar]
- 23.Statello L, Guo C-J, Chen L-L, Huarte M. Gene regulation by long non-coding RNAs and its biological functions. Nat Rev Mol Cell Biol. 2021;22(2):96–118. 10.1038/s41580-020-00315-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Oliviero A, Della Porta G, Peretti GM, Maffulli N. Microrna in osteoarthritis: physiopathology, diagnosis and therapeutic challenge. Br Med Bull. 2019;130(1):137–47. [DOI] [PubMed] [Google Scholar]
- 25.Huang M-J, Zhao J-Y, Xu J-J, Li J, Zhuang Y-F, Zhang X-L. LncRNA ADAMTS9-AS2 controls human mesenchymal stem cell chondrogenic differentiation and functions as a ceRNA. Mol Ther Nucleic Acids. 2019;18:533–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Ren L, Guo L, Kou N, Lv J, Wang Z, Yang K. LncRNA LINC00963 promotes osteogenic differentiation of hBMSCs and alleviates osteoporosis progression by targeting miRNA-760/ETS1 axis. Autoimmunity. 2021;54(6):313–25. [DOI] [PubMed] [Google Scholar]
- 27.Huynh NPT, Zhang B, Guilak F. High-depth transcriptomic profiling reveals the temporal gene signature of human mesenchymal stem cells during chondrogenesis. FASEB J. 2019;33(1):358–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Chen Y, Sha W, Zhang Y, Kou W, Yang L, Guo R, et al. Irisin-regulated lncRNAs and their potential regulatory functions in chondrogenic differentiation of human mesenchymal stem cells. Open Med. 2024;19(1):20241073. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Vyavahare S, Kumar S, Smith K, Mendhe B, Zhong R, Cooley MA, et al. Inhibiting MicroRNA-141-3p improves musculoskeletal health in aged mice. Aging Dis. 2023;14(6):2303–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Global, regional, and national burden of bone fractures in 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019. Lancet Healthy Longev. 2021;2(9):e580-e92. [DOI] [PMC free article] [PubMed]
- 31.Zhao C, Li Q, Shen C. Therapeutic potential of miR-204-5p in intervertebral disc degeneration: targeting the SSRP1/NF-κB pathway to inhibit apoptosis. J Orthop Surg Res. 2025;20(1):586. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Liu X, Zhang X, Cen M. Dysregulation of miR-106a-5p/PTEN axis associated with progression and diagnostic of postmenopausal osteoporosis. J Orthop Surg Res. 2025;20(1):456. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Li Y, Ye S, Han Z, Wei C, Huang Y. LncRNA CRNDE ameliorates bone fracture by regulating cell viability and apoptosis of osteoblasts. J Orthop Surg Res. 2025;20(1):521. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Bowers KM, Anderson DE. Delayed union and nonunion: current concepts, prevention, and correction: a review. Bioengineering. 2024;11(6):525. 10.3390/bioengineering11060525. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Jiao H, Xiao E, Graves DT. Diabetes and its effect on bone and fracture healing. Curr Osteoporos Rep. 2015;13(5):327–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Knight MN, Hankenson KD. Mesenchymal stem cells in bone regeneration. Adv Wound Care. 2013;2(6):306–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Wang X, Wang Y, Gou W, Lu Q, Peng J, Lu S. Role of mesenchymal stem cells in bone regeneration and fracture repair: a review. Int Orthop. 2013;37(12):2491–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Sophia Fox AJ, Bedi A, Rodeo SA. The basic science of articular cartilage: structure, composition, and function. Sports Health. 2009;1(6):461–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Somoza RA, Welter JF, Correa D, Caplan AI. Chondrogenic differentiation of mesenchymal stem cells: challenges and unfulfilled expectations. Tissue Eng Part B Rev. 2014;20(6):596–608. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Lefebvre V, Dvir-Ginzberg M. SOX9 and the many facets of its regulation in the chondrocyte lineage. Connect Tissue Res. 2017;58(1):2–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Zhang Q, Ji Q, Wang X, Kang L, Fu Y, Yin Y, et al. SOX9 is a regulator of ADAMTSs-induced cartilage degeneration at the early stage of human osteoarthritis. Osteoarthritis Cartilage. 2015;23(12):2259–68. [DOI] [PubMed] [Google Scholar]
- 42.St-Jacques B, Hammerschmidt M, McMahon AP. Indian hedgehog signaling regulates proliferation and differentiation of chondrocytes and is essential for bone formation. Genes Dev. 1999;13(16):2072–86. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Yan Q, Shi S, Ge Y, Wan S, Li M, Li M. UCHL1 alleviates apoptosis in chondrocytes via upregulation of HIF-1α-mediated mitophagy. Int J Mol Med. 2023;52(4):99. 10.3892/ijmm.2023.5302. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Wu X, Shen T, Ji W, Huang M, Sima J, Li J, et al. LncRNA CASC11 regulates the progress of delayed fracture healing via sponging miR-150-3p. J Orthop Surg Res. 2024;19(1):757. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Zhang Z, Wang L, Zhang F, Jing S, Cen M. Functional mechanism and clinical implications of miR-1271-5p in pilon fracture healing processes. J Orthop Surg Res. 2024;19(1):782. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Li F, Tan H, Zhang X, Zhao X, Li X, Chen G. LncRNA HCG18 regulates the progression of spinal tuberculosis by modulating the hsa-miR-146a-5p/TGF-β1/SMADs pathway. J Orthop Surg Res. 2025;20(1):484. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Chen S, Liu H, Wang Y, Wang S, Yang B, Sun D, et al. Overexpression of lncRNA LINC00665 inhibits the proliferation and chondroblast differentiation of bone marrow mesenchymal stem cells by targeting miR-214-3p. J Orthop Surg Res. 2024;19(1):2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Zhu J, Fu Q, Shao J, Peng J, Qian Q, Zhou Y, et al. Over-expression of MEG3 promotes differentiation of bone marrow mesenchymal stem cells into chondrocytes by regulating miR-129-5p/RUNX1 axis. Cell Cycle. 2021;20(1):96–111. 10.1080/15384101.2020.1863043. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.O’Brien J, Hayder H, Zayed Y, Peng C. Overview of microrna biogenesis, mechanisms of actions, and circulation. Front Endocrinol (Lausanne). 2018;9:402. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Lai J-C, Li H-P, Chang GR-L, Lan Y-W, Chen Y-H, Tseng Y-S, et al. Kefir peptides promote osteogenic differentiation to enhance bone fracture healing in rats. Life Sci. 2022;310:121090. [DOI] [PubMed] [Google Scholar]
- 51.Hankenson KD, Dishowitz M, Gray C, Schenker M. Angiogenesis in bone regeneration. Injury. 2011;42(6):556–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Li Y, Yao X, Lin Y, Xing Y, Liu C, Xu J, et al. Identification and validation of autophagy-related genes during osteogenic differentiation of bone marrow mesenchymal stem cells. Iran J Basic Med Sci. 2022;25(11):1364–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Huang X, Jie S, Li W, Liu C. Chrdl2 activates the PI3K/AKT pathway to ameliorate glucocorticoid-induced damages to bone microvascular endothelial cells (BMECs). Heliyon. 2024;10(13):e33867. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Wei X, Wang J, Deng Y-Y, Shao B-H, Zhang Z-F, Wang H-H, et al. Tubiechong patching promotes tibia fracture healing in rats by regulating angiogenesis through the VEGF/ERK1/2 signaling pathway. J Ethnopharmacol. 2022;301:115851. [DOI] [PubMed] [Google Scholar]
- 55.Zhang S, Chen L, Zhang C, Gong C, He X, Zhong H, et al. Osteoking exerts pro-osteogenic and anti-adipogenic effects in promoting bone fracture healing via EGF/EGFR/HDAC1/Wnt/β-catenin signaling. Int J Mol Med. 2025;55(5):75. 10.3892/ijmm.2025.5516. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data generated or analyzed during this study are included in this article and its supplementary material files. Further enquiries can be directed to the corresponding author.