Journal of Bone Oncology最新文献

{"title":"Feasibility of ADC histogram analysis for predicting of postoperative recurrence in aggressive spinal tumors","authors":"Qizheng Wang ,&nbsp;Yongye Chen ,&nbsp;Guangjin Zhou ,&nbsp;Tongyu Wang ,&nbsp;Jingchao Fang ,&nbsp;Ke Liu ,&nbsp;Siyuan Qin ,&nbsp;Weili Zhao ,&nbsp;Dapeng Hao ,&nbsp;Ning Lang","doi":"10.1016/j.jbo.2025.100666","DOIUrl":"10.1016/j.jbo.2025.100666","url":null,"abstract":"<div><h3>Background</h3><div>Risk stratification of spinal tumors is a major unmet clinical need for personalized therapy.</div></div><div><h3>Purpose</h3><div>To explore the feasibility of pretreatment whole-lesion apparent diffusion coefficient (ADC) histogram in predicting local recurrence of aggressive spinal tumors.</div></div><div><h3>Methods</h3><div>119 aggressive spinal tumor patients (median age, 40; range, 13–74  years) confirmed by pathological findings with a mean follow-up of 36 months were enrolled and divided into the recurrence and non-recurrence group. The histogram metrics of whole-lesion, including the maximum, mean, kurtosis, skewness, entropy, and percentiles (10th, 25th, 50th, 75th, 95th) ADC values, were evaluated and take the average. Fractal dimension (FD) was assessed in the three orthogonal directions and take maximum. Clinical and general imaging features were used to construct an alternative prognostic model for comparison. Variables with statistical differences would be included in stepwise logistic regression analysis.</div></div><div><h3>Results</h3><div>As for the clinical model, Enneking staging (odds ratio [OR]: 3.572; <em>P</em> = 0.04) and vertebral compression (OR: 4.302; <em>P</em> = 0.002) were independent predictors of recurrence. There was no statistical difference in FD between the two groups (<em>P</em> = 0.623). Among the ADC histogram parameters compared, skewness, maximum, and mean ADC values were independent risk factors and constructed ADC histogram prediction models. The ADC histogram model (AUC = 0.871) and the combined model (AUC = 0.884) performed better than the clinical prediction model (AUC = 0.704) with <em>P</em>-values of 0.004 and 0.001, respectively.</div></div><div><h3>Conclusion</h3><div>Prediction models based on the ADC histogram analysis might represent serviceable instruments for the aggressive spinal tumors.</div></div>","PeriodicalId":48806,"journal":{"name":"Journal of Bone Oncology","volume":"51 ","pages":"Article 100666"},"PeriodicalIF":3.4,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative analysis of aggressiveness in giant cell tumor of bone between upper and lower extremities: A systematic review and meta-analysis","authors":"Rhyan Darma Saputra ,&nbsp;Dita Anggara Kusuma ,&nbsp;Fathih Kaldani ,&nbsp;Khoirul Fahmi","doi":"10.1016/j.jbo.2025.100663","DOIUrl":"10.1016/j.jbo.2025.100663","url":null,"abstract":"<div><h3>Background and Objective</h3><div>Giant cell tumor of bone (GCTB) is among the most prevalent benign primary bone tumors, characterized by its potential for aggressive local recurrence, soft tissue invasion, and, though rare, lung metastasis. Emerging evidence suggests unique behavioral patterns of GCTB in extremities. This study seeks to rigorously compare the aggressiveness of GCTB in the upper versus lower extremities, centering on recurrence rates.</div></div><div><h3>Method</h3><div>This systematic review and meta-analysis, conducted in accordance with PRISMA guidelines, sourced data from MEDLINE/PubMed, Cochrane, Scopus, CINAHL/EBSCO, and reference lists of pertinent studies. Two independent reviewers screened studies, with discrepancies resolved by discussion. Eligible studies included a minimum of 10 participants. Data extraction and analysis were performed by an additional team of two researchers.</div></div><div><h3>Results</h3><div>Out of 1,283 studies spanning from 1984 to 2023, 30 met eligibility, encompassing 2,672 participants. The mean age was 32.77 ± 12.99 years, with an average follow-up of 75.53 ± 65.88 months. GCTB predominantly affected the lower extremities, accounting for 1,937 cases. Notably, comparisons of aggressiveness between upper and lower extremity GCTB revealed no statistically significant difference (OR = 1.10, p = 0.56 for Surgery Group; OR = 1.16, p = 0.45 for Local Adjuvant Group; and OR = 1.71, p = 0.32 for Drug/Denosumab Group).</div></div><div><h3>Conclusion</h3><div>This analysis underscores the lower extremities as the primary site for GCTB but finds no significant difference in aggressiveness between upper and lower extremities. These findings challenge assumptions about GCTB behavior based on tumor location and highlight the need for further investigation to fully elucidate the complex biology of extremity GCTB.</div></div>","PeriodicalId":48806,"journal":{"name":"Journal of Bone Oncology","volume":"51 ","pages":"Article 100663"},"PeriodicalIF":3.4,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Naringenin induces ferroptosis in osteosarcoma cells through the STAT3-MGST2 signaling pathway","authors":"Yingang Li ,&nbsp;Xizhuang Bai","doi":"10.1016/j.jbo.2024.100657","DOIUrl":"10.1016/j.jbo.2024.100657","url":null,"abstract":"<div><div>Osteosarcoma is a common malignant tumor found in adolescents, characterized by a high metastatic potential and poor prognosis, but it is sensitive to radiotherapy and chemotherapy. Ferroptosis is a novel form of regulated cell death induced by excessive iron accumulation, leading to lipid peroxidation that results in cellular dysfunction and death. Naringenin is a flavonoid known for its anti-cancer properties, yet its role in osteosarcoma has not been thoroughly studied. In this study, we found that naringenin significantly reduced the viability of osteosarcoma cells while increasing the accumulation of reactive oxygen species (ROS), iron overload, and the excessive expression of malondialdehyde (MDA). Bioinformatics analysis revealed that microsomal glutathione S-transferase 2 (MGST2) is highly expressed in osteosarcoma cells. Silencing MGST2 decreased the proliferation, migration, and invasion of these cells and enhanced their sensitivity to ferroptosis. Mechanistically, signal transducer and activator of transcription 3 (STAT3) binds to the MGST2 promoter, promoting its transcription. Naringenin inhibits STAT3, blocking the expression of MGST2, while the STAT3 agonist Colivelin reverses this effect. In vivo experiments further confirmed that naringenin inhibited tumor growth in subcutaneous xenograft models and exhibited good biosafety. In summary, our study demonstrates that naringenin induces ferroptosis in osteosarcoma cells through the STAT3-MGST2 signaling pathway, providing a promising strategy for osteosarcoma treatment.</div></div>","PeriodicalId":48806,"journal":{"name":"Journal of Bone Oncology","volume":"50 ","pages":"Article 100657"},"PeriodicalIF":3.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11743371/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143014503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medication related osteonecrosis (MRONJ) in the management of CTIBL in breast and prostate cancer patients. Joint report by SIPMO AND SIOMMMS","authors":"Francesco Bertoldo ,&nbsp;Cristina Eller-Vainicher ,&nbsp;Vittorio Fusco ,&nbsp;Rodolfo Mauceri ,&nbsp;Jessica Pepe ,&nbsp;Alberto Bedogni ,&nbsp;Andrea Palermo ,&nbsp;Umberto Romeo ,&nbsp;Giuseppe Guglielmi ,&nbsp;Giuseppina Campisi","doi":"10.1016/j.jbo.2024.100656","DOIUrl":"10.1016/j.jbo.2024.100656","url":null,"abstract":"<div><h3>Background</h3><div>Low-doses of bone modifying agents (LD-BMAs) compared to those used to treat bone metastases are used in breast or prostate cancer patients on adjuvant endocrine therapy to prevent Cancer Treatment Induced Bone Loss (CTIBL). Their use is associated with an increased risk of developing Medication-Related Osteonecrosis of the Jaw (MRONJ). However, there is not clarity about strategies aimed to minimize the MRONJ risk in cancer patients at different conditions as low- vs high-doses of BMA. This joint report from the Italian Societies of Oral Pathology and Medicine (SIPMO) and of Italian Society of Osteoporosis, Mineral Metabolism and Skeletal Diseases (SIOMMMS) aims to define the dental management of breast and prostate cancer patients with CTIBL under LD-BMAs, to reduce their risk to develop MRONJ.</div></div><div><h3>Methods</h3><div>This interdisciplinary SIPMO-SIOMMMS Expert Italian Panel reviewed the available international scientific literature and developed a set of recommendations to implement strategies of MRONJ prevention in breast (BC) and prostate cancer (PC) patients undertaking LD-BMAs to prevent CTIBL.</div></div><div><h3>Results</h3><div>The Expert Panel, after addressing some introductive topics (i.e., CTIBL and its management, pharmacology and pharmacodynamics of BMAs, definition and diagnosis of MRONJ), developed a joint report on the following five issues: a) prevention and dental management in cancer patients candidates to LD-BMAs, or under LD-BMAs; b) prophylactic drug holiday; c) MRONJ treatment; d) LD-BMAs therapeutic drug holiday;<!--> <!-->and e) restart of LD-BMA treatment after successful healing of MRONJ.</div><div>Finally, ten key questions with answers were prepared and placed at the end of the document.</div></div><div><h3>Conclusions</h3><div>Despite obvious weaknesses of the available international literature, the Expert Panel recognized the need to tailor separate MRONJ preventive approach for breast and prostate cancer patients on adjuvant endocrine therapy who begin low-dose BMA therapy to prevent CTIBL and provided this practical guidance for bone specialists and oral healthcare providers. In view of a MRONJ risk for BC and PC patients receiving low-dose BMAs, which approximates that of patients with osteoporosis and other non-malignant diseases undergoing similar treatment schedules, the SIPMO-SIOMMMS Expert Panel recognizes the need for less stringent preventive strategies than those already developed for BC or PC patients with bone metastases taking HD-BMAs.</div></div>","PeriodicalId":48806,"journal":{"name":"Journal of Bone Oncology","volume":"50 ","pages":"Article 100656"},"PeriodicalIF":3.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11728904/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142980197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mixed reality infrastructure based on deep learning medical image segmentation and 3D visualization for bone tumors using DCU-Net","authors":"Kun Wang ,&nbsp;Yong Han ,&nbsp;Yuguang Ye ,&nbsp;Yusi Chen ,&nbsp;Daxin Zhu ,&nbsp;Yifeng Huang ,&nbsp;Ying Huang ,&nbsp;Yijie Chen ,&nbsp;Jianshe Shi ,&nbsp;Bijiao Ding ,&nbsp;Jianlong Huang","doi":"10.1016/j.jbo.2024.100654","DOIUrl":"10.1016/j.jbo.2024.100654","url":null,"abstract":"<div><h3>Objective</h3><div>Segmenting and reconstructing 3D models of bone tumors from 2D image data is of great significance for assisting disease diagnosis and treatment. However, due to the low distinguishability of tumors and surrounding tissues in images, existing methods lack accuracy and stability. This study proposes a U-Net model based on double dimensionality reduction and channel attention gating mechanism, namely the DCU-Net model for oncological image segmentation. After realizing automatic segmentation and 3D reconstruction of osteosarcoma by optimizing feature extraction and improving target space clustering capabilities, we built a mixed reality (MR) infrastructure and explored the application prospects of the infrastructure combining deep learning-based medical image segmentation and mixed reality in the diagnosis and treatment of bone tumors.</div></div><div><h3>Methods</h3><div>We conducted experiments using a hospital dataset for bone tumor segmentation, used the optimized DCU-Net and 3D reconstruction technology to generate bone tumor models, and used set similarity (DSC), recall (R), precision (P), and 3D vertex distance error (VDE) to evaluate segmentation performance and 3D reconstruction effects. Then, two surgeons conducted clinical examination experiments on patients using two different methods, viewing 2D images and virtual reality infrastructure, and used the Likert scale (LS) to compare the effectiveness of surgical plans of the two methods.</div></div><div><h3>Results</h3><div>The DSC, R and P values of the model introduced in this paper all exceed 90%, which has significant advantages compared with methods such as U-Net and Attention-Uet. Furthermore, LS showed that clinicians in the DCU-Net-based MR group had better spatial awareness of tumor preoperative planning.</div></div><div><h3>Conclusion</h3><div>The deep learning DCU-Net algorithm model can improve the performance of tumor CT image segmentation, and the reconstructed fine model can better reflect the actual situation of individual tumors; the MR system constructed based on this model enhances clinicians’ understanding of tumor morphology and spatial relationships. The MR system based on deep learning and three-dimensional visualization technology has great potential in the diagnosis and treatment of bone tumors, and is expected to promote clinical practice and improve efficacy.</div></div>","PeriodicalId":48806,"journal":{"name":"Journal of Bone Oncology","volume":"50 ","pages":"Article 100654"},"PeriodicalIF":3.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11745962/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143014498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using β-Elemene to reduce stemness and drug resistance in osteosarcoma: A focus on the AKT/FOXO1 signaling pathway and immune modulation","authors":"Shaochun Zhang ,&nbsp;Zhijie Xing ,&nbsp;Jing Ke","doi":"10.1016/j.jbo.2024.100655","DOIUrl":"10.1016/j.jbo.2024.100655","url":null,"abstract":"<div><h3>Objective</h3><div>Osteosarcoma, a highly malignant bone tumor, poses significant treatment challenges due to its propensity for stemness and drug resistance, particularly against doxorubicin (DOX). This study aims to investigate the mechanism by which β-elemene reduces the stemness of osteosarcoma stem cells and ultimately decreases DOX resistance by inhibiting the Akt/FoxO1 signaling pathway and activating a macrophage-mediated inflammatory microenvironment.</div></div><div><h3>Methods</h3><div>Osteosarcoma stem cells were isolated and induced for DOX resistance. <em>In vitro</em> and <em>in vivo</em> models were employed to assess β-elemene’s impact on cell viability, stemness, and drug resistance. Bioinformatics analysis, flow cytometry, and immunofluorescence staining were used to evaluate signaling pathway activity and macrophage polarization. Additionally, an osteosarcoma xenograft mouse model was established to confirm the therapeutic effects of β-elemene.</div></div><div><h3>Results</h3><div><em>In vivo</em> animal experiments demonstrated that β-elemene reduces osteosarcoma resistance. Bioinformatics analysis revealed that AKT1 is a key core gene in osteosarcoma progression, acting through the FOXO signaling pathway. Additionally, AKT inhibits immune cell infiltration in osteosarcoma and suppresses immune responses during osteosarcoma progression. β-elemene may influence osteosarcoma progression by mediating TP53 to regulate PTEN and subsequently AKT1. <em>In vitro</em> experiments showed that β-elemene promotes M1 macrophage activation by inhibiting the Akt/FoxO1 signaling axis, thereby reducing the stemness of osteosarcoma stem cells. Finally, <em>in vivo</em> animal experiments confirmed that β-elemene reduces osteosarcoma resistance by promoting M1 macrophage activation through inhibition of the Akt/FoxO1 signaling axis.</div></div><div><h3>Conclusion</h3><div>β-Elemene demonstrates promising potential in reducing osteosarcoma stemness and drug resistance via dual mechanisms: targeting the AKT/FOXO1 pathway and modulating the tumor immune microenvironment. These findings suggest β-elemene as a potential adjunct therapy for osteosarcoma, providing novel therapeutic strategies to overcome chemotherapy resistance and improve patient outcomes.</div></div>","PeriodicalId":48806,"journal":{"name":"Journal of Bone Oncology","volume":"50 ","pages":"Article 100655"},"PeriodicalIF":3.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11755076/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143029469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT","authors":"Hao-Nan Zhu ,&nbsp;Yi-Fan Guo ,&nbsp;YingMin Lin ,&nbsp;Zhi-Chao Sun ,&nbsp;Xi Zhu ,&nbsp;YuanZhe Li","doi":"10.1016/j.jbo.2024.100653","DOIUrl":"10.1016/j.jbo.2024.100653","url":null,"abstract":"<div><h3>Background</h3><div>Bone metastasis from breast cancer significantly elevates patient morbidity and mortality, making early detection crucial for improving outcomes. This study utilizes radiomics to analyze changes in the thoracic vertebral bone marrow microenvironment from chest computerized tomography (CT) images prior to bone metastasis in breast cancer, and constructs a model to predict metastasis. Methods: This study retrospectively gathered data from breast cancer patients who were diagnosed and continuously monitored for five years from January 2013 to September 2023. Radiomic features were extracted from the bone marrow of thoracic vertebrae on non-contrast chest CT scans. Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. The effectiveness of this combined model was assessed through receiver operating characteristic (ROC) analysis as well as decision curve analysis (DCA). Results: The study included a total of 106 patients diagnosed with breast cancer, among whom 37 developed bone metastases within five years. The radiomics model’s area under the curve (AUC) for the test set, calculated using logistic regression, is 0.929, demonstrating superior predictive performance compared to alternative machine learning models. Furthermore, DCA demonstrated the potential of radiomics models in clinical application, with a greater clinical benefit in predicting bone metastasis than clinical model and nomogram. Conclusion: CT-based radiomics can capture subtle changes in the thoracic vertebral bone marrow before breast cancer bone metastasis, offering a predictive tool for early detection of bone metastasis in breast cancer.</div></div>","PeriodicalId":48806,"journal":{"name":"Journal of Bone Oncology","volume":"50 ","pages":"Article 100653"},"PeriodicalIF":3.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11655691/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142878439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Out with the old (not so!) and in with the new","authors":"Rob Coleman (Editor in Chief)","doi":"10.1016/j.jbo.2024.100658","DOIUrl":"10.1016/j.jbo.2024.100658","url":null,"abstract":"","PeriodicalId":48806,"journal":{"name":"Journal of Bone Oncology","volume":"50 ","pages":"Article 100658"},"PeriodicalIF":3.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11786014/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143081457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multicenter, randomized, double-blind trial comparing LY01011, a biosimilar, with denosumab (Xgeva®) in patients with bone metastasis from solid tumors","authors":"Mingchuan Zhao ,&nbsp;Xichun Hu ,&nbsp;Pengpeng Zhuang ,&nbsp;Aiping Zeng ,&nbsp;Yan Yu ,&nbsp;Zhendong Chen ,&nbsp;Hongmei Sun ,&nbsp;Weihua Yang ,&nbsp;Lili Sheng ,&nbsp;Peijian Peng ,&nbsp;Jingfen Wang ,&nbsp;Tienan Yi ,&nbsp;Minghong Bi ,&nbsp;Huaqiu Shi ,&nbsp;Mingli Ni ,&nbsp;Xiumei Dai ,&nbsp;Changlu Hu ,&nbsp;Hongjie Xu ,&nbsp;Dongqing Lv ,&nbsp;Qingshan Li ,&nbsp;Changlin Dou","doi":"10.1016/j.jbo.2025.100661","DOIUrl":"10.1016/j.jbo.2025.100661","url":null,"abstract":"<div><h3>Introduction</h3><div>Denosumab (Xgeva®) is a standard treatment for the prevention of skeletal-related events (SREs) in patients with bone metastases (BM). This trial was designed to assess the equivalence of LY01011 to denosumab in terms of efficacy and safety.</div></div><div><h3>Materials and methods</h3><div>Eligible patients with BM from solid tumors were randomized at a 1:1 ratio to receive 120 mg of LY01011 or 120 mg of denosumab subcutaneously every four weeks during a 12-week double-blind treatment period, and then all enrolled patients continued to receive LY01011 until week 53. The primary endpoint was the natural logarithm of change of the urinary N-terminal crosslinked telopeptide of type I collagen level normalized to the urine creatinine level (uNTX/uCr) at week 13 from baseline. Other endpoints included the uNTX/uCr ratio, serum bone-specific alkaline phosphatase level alteration, status of anti-drug antibodies and neutralizing antibodies, adverse events and SREs.</div></div><div><h3>Results</h3><div>850 eligible patients were randomized into the LY01011 group (n = 424) or the denosumab group (n = 426). The least-squares means (SEs) of the natural logarithms of the changes in the uNTX/uCr ratios at week 13 from baseline were −1.810 (0.0404) in the LY01011 group and −1.791 (0.0406) in the denosumab group. The LSM difference [90 % CI] between two arms was −0.019 [-0.110, 0.073] within the equivalence margins (−0.135, 0.135) and met the predetermined primary endpoint. The AEs, ADAs and the PK data showed no statistically significant difference.</div></div><div><h3>Conclusions</h3><div>This study demonstrated the equivalent efficacy and safety of LY01011 to denosumab in patients with BM.</div></div>","PeriodicalId":48806,"journal":{"name":"Journal of Bone Oncology","volume":"51 ","pages":"Article 100661"},"PeriodicalIF":3.4,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143332852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lipid metabolic reprogramming and associated ferroptosis in osteosarcoma: From molecular mechanisms to potential targets","authors":"Zhiyang Yin ,&nbsp;Guanlu Shen ,&nbsp;Minjie Fan ,&nbsp;Pengfei Zheng","doi":"10.1016/j.jbo.2025.100660","DOIUrl":"10.1016/j.jbo.2025.100660","url":null,"abstract":"<div><div>Osteosarcoma is a common bone tumor in adolescents, which is characterized by lipid metabolism disorders and plays a key role in tumorigenesis and disease progression. Ferroptosis is an iron-dependent form of programmed cell death associated with lipid peroxidation. This review provides an in-depth analysis of the complex relationship between lipid metabolic reprogramming and associated ferroptosis in OS from the perspective of metabolic enzymes and metabolites. We discussed the molecular basis of lipid uptake, synthesis, storage, lipolysis, and the tumor microenvironment, as well as their significance in OS development. Key enzymes such as adenosine triphosphate-citrate lyase (ACLY), acetyl-CoA synthetase 2 (ACSS2), fatty acid synthase (FASN) and stearoyl-CoA desaturase-1 (SCD1) are overexpressed in OS and associated with poor prognosis.</div><div>Based on specific changes in metabolic processes, this review highlights potential therapeutic targets in the lipid metabolism and ferroptosis pathways, and in particular the HMG-CoA reductase inhibitor simvastatin has shown potential in inducing apoptosis and inhibiting OS metastasis. Targeting these pathways provides new strategies for the treatment of OS. However, challenges such as the complexity of drug development and metabolic interactions must be overcome. A comprehensive understanding of the interplay between dysregulation of lipid metabolism and ferroptosis is essential for the development of innovative and effective therapies for OS, with the ultimate goal of improving patient outcomes.</div></div>","PeriodicalId":48806,"journal":{"name":"Journal of Bone Oncology","volume":"51 ","pages":"Article 100660"},"PeriodicalIF":3.4,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143103134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}