Accumulating studies demonstrated that hydroxyapatite nanoparticles (HANPs) showed a selective anti-tumor effect, making them a good candidate for osteosarcoma (OS) treatment. However, the capacity of HANPs with different aspect ratios to regulate tumor immune microenvironment (TIM) was scarcely reported before. To explore it, the three HANPs with aspect ratios from 1.86 to 6.25 were prepared by wet chemical method. After a 24 or 72 h-exposure of OS UMR106 cells or macrophages to the nanoparticles, the tumor cells exhibited immunogenic cell death (ICD) indicated by the increased production of calreticulin (CRT), adenosine triphosphate (ATP) and high mobility group box 1 (HMGB1), and macrophages were activated with the release of pro-inflammatory cytokines. Next, the beneficial crosstalk between tumor cells and macrophages generated in the presence of HANPs for improved anti-tumor immunity activation. In the OS-bearing cognate rat model, HANPs inhibited OS growth, which was positively correlated with CRT and HMGB1 expression, and macrophage polarization in the tumor tissues. Additionally, HANPs promoted CD8⁺ T cell infiltration into the tumor and systemic dendritic cell maturation. Particularly, HANPs bearing the highest aspect ratio exhibited the strongest immunomodulatory and anti-tumor function. This study suggested the potential of HANPs to be a safe and effective drug-free nanomaterial to control the TIM for OS therapy. STATEMENT OF SIGNIFICANCE: : Emerging studies demonstrated that hydroxyapatite nanoparticles (HANPs) inhibited tumor cell proliferation and tumor growth. However, the underlying anti-tumor mechanism still remains unclear, and the capacity of HANPs without any other additive to regulate tumor immune microenvironment (TIM) was scarcely reported before. Herein, we demonstrated that HANPs, in an aspect ratio-dependent manner, showed the potential to delay the growth of osteosarcoma (OS) and to regulate TIM by promoting the invasion of CD8+ T cells and F4/80+ macrophages, and inducing immunogenic cell death (ICD) in tumors. This work revealed the new molecular mechanism for HANPs against OS, and suggested HANPs might be a novel ICD inducer for OS treatment.

Bone defects that are congenital or the result of infection, malignancy, or trauma represent a challenge to the global healthcare system. To address this issue, multiple research groups have been developing novel cell sheet technology (CST)-based approaches to promote bone regeneration. These methods hold promise for use in regenerative medicine because they preserve cell-cell contacts, cell-extracellular matrix interactions, and the protein makeup of cell membranes. This review introduces the concept and preparation system of the cell sheet (CS), explores the application of CST in bone regeneration, highlights the current states of the bone regeneration via CST, and offers perspectives on the challenges and future research direction of translating current knowledge from the lab to the clinic.

Background: The lung immune prognostic index (LIPI), composed of serum lactate dehydrogenase (LDH) and the derived neutrophil to lymphocyte ratio (dNLR), is a novel prognostic factor of lung cancer. The prognostic effect of the LIPI has never been verified in osteosarcoma.Methods: We retrospectively reviewed the osteosarcoma patients with metachronous metastasis from January 2016 to January 2021 in West China Hospital. We collected and analyzed the clinical data and constructed the LIPI for osteosarcoma. The correlation between the LIPI and metastasis was analyzed according to the Kaplan–Meier method and Cox regression analysis with hazard ratios (HRs) and 95% confidence intervals (CIs). Univariate analysis and multivariate analysis were conducted to clarify the independent risk factors of metastasis. The nomogram model was established by R software, version 4.1.0.Results: The area under the curve (AUC) and best cutoff value were 0.535 and 91, 0.519, and 5.02, 0.594 and 2.77, 0.569 and 227.14, 0.59 and 158, and 0.607 and 2.05 for ALP, LMR, NLR, PLR, LDH, and dNLR, respectively. The LIPI was composed of LDH and dNLR and showed a larger AUC than other hematological factors in the time-dependent operator curve (t-ROC). In total, 184 patients, 42 (22.8%), 96 (52.2%), and 46 (25.0%) patients had LIPIs of good, moderate, and poor, respectively (P < 0.0001). Univariate analysis revealed that pathological fracture, the initial CT report of suspicious nodule, and the NLR, PLR, ALP, and the LIPI were significantly associated with metastasis, and multivariate analysis showed that the initial CT report of suspicious nodule and the PLR, ALP, and LIPI were dependent risk factors for metastasis. Metastatic predictive factors were selected and incorporated into the nomogram construction, including the LIPI, ALP, PLR, initial CT report, and pathological fracture. The C-index of our model was 0.71. According to the calibration plot, this predictive nomogram could accurately predict 3- and 5-year metachronous metastasis. Based on the result of decision curve and clinical impact curve, this predictive nomogram could also help patients obtain significant net benefits.Conclusion: We first demonstrated the metastatic predictive effect of the LIPI on osteosarcoma. This LIPI-based model is useful for clinicians to predict metastasis in osteosarcoma patients and could help conduct timely intervention and facilitate personalized management of osteosarcoma patients.

Osteosarcoma is the most common primary malignant bone tumor with a high metastatic potential. Nowadays, there is a lack of new markers to identify prognosis of osteosarcoma patients with response to medical treatment. Recent studies have shown that hematological markers can reflect to some extent the microenvironment of an individual with the potential to predict patient prognosis. However, most of the previous studies have studied the prognostic value of a single hematological index, and it is difficult to comprehensively reflect the tumor microenvironment of patients. Here, we comprehensively collected 16 hematological markers and constructed a hematological prognostic scoring system (HPSS) using LASSO cox regression analysis. HPSS contains many indicators such as immunity, inflammation, coagulation and nutrition. Our results suggest that HPSS is an independent prognostic factor for overall survival in osteosarcoma patients and is an optimal addition to clinical characteristics and well suited to further identify high-risk patients from clinically low-risk patients. HPSS-based nomograms have good predictive ability. Finally, HPSS also has some hints for immunotherapy response in osteosarcoma patients.