Background: The difficulty of assessment of neoadjuvant chemotherapeutic response preoperatively may hinder personalized-medicine strategies that depend on the results from pathological examination. Methods: A total of 191 patients with high-grade osteosarcoma (HOS) were enrolled retrospectively from November 2013 to November 2017 and received neoadjuvant chemotherapy (NCT). A cutoff time of November 2016 was used to divide the training set and validation set. All patients underwent diagnostic CTs before and after chemotherapy. By quantifying the tumor regions on the CT images before and after NCT, 540 delta-radiomic features were calculated. The interclass correlation coefficients for segmentations of inter/intra-observers and feature pair-wise correlation coefficients (Pearson) were used for robust feature selection. A delta-radiomics signature was constructed using the lasso algorithm based on the training set. Radiomics signatures built from single-phase CT were constructed for comparison purpose. A radiomics nomogram was then developed from the multivariate logistic regression model by combining independent clinical factors and the delta-radiomics signature. The prediction performance was assessed using area under the ROC curve (AUC), calibration curves and decision curve analysis (DCA). Results:The delta-radiomics signature showed higher AUC than single-CT based radiomics signatures in both training and validation cohorts. The delta-radiomics signature, consisting of 8 selected features, showed significant differences between the pathologic good response (pGR) (necrosis fraction ≥90%) group and the non-pGR (necrosis fraction < 90%) group (P < 0.0001, in both training and validation sets). The delta-radiomics nomogram, which consisted of the delta-radiomics signature and new pulmonary metastasis during chemotherapy showed good calibration and great discrimination capacity with AUC 0.871 (95% CI, 0.804 to 0.923) in the training cohort, and 0.843 (95% CI, 0.718 to 0.927) in the validation cohort. The DCA confirmed the clinical utility of the radiomics model. Conclusion:The delta-radiomics nomogram incorporating the radiomics signature and clinical factors in this study could be used for individualized pathologic response evaluation after chemotherapy preoperatively and help tailor appropriate chemotherapy and further treatment plans.

The mechanism by which osteosarcomas metastasize is elusive, and challenges remain regarding its treatment with modalities including immunotherapy. CXCL12 is deeply involved in the process of tumor metastasis and T-cell homing, which is driven by a chemokine gradient, but healthy bones are supposed to preferentially express CXCL12. Here, we show for the first time that osteosarcomas epigenetically downregulate CXCL12 expression via DNA methyltransferase 1 (DNMT1) and consequently acquire the ability to metastasize and to impair cytotoxic T-cell homing to the tumor site. Analysis of human osteosarcoma cases further revealed that CXCL12 expression strongly correlated with overall survival. Evaluations on fresh human chemotherapy-free osteosarcoma samples also showed a positive correlation between CXCL12 concentration and the number of intratumoral lymphocytes. Critically, treatment targeting DNMT1 in immunocompetent mouse models significantly elevated expression of CXCL12 in tumors, resulting in a robust immune response and consequently eradicating early lung metastases in addition to suppressing subcutaneous tumor growth. These antitumor effects were abrogated by CXCL12-CXCR4 blockade or CD8 T-cell depletion. Collectively, our data show that CXCL12 regulation plays a significant role in both tumor progression and immune response, and targeting CXCL12 is promising for therapeutics against osteosarcoma. Epigenetic regulation of CXCL12 controls metastasis and immune response in osteosarcoma, suggesting epigenetic therapies or therapies targeting CXCL12 have potential for therapeutic intervention in osteosarcoma. .

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Iodine has been known as an effective disinfectant with broad‐spectrum antimicrobial potency yet without drug resistance risk when used in clinic. However, the exploration of iodine for antibacterial therapy in orthopedics remains sparse due to its volatile nature and poor solubility. Herein, leveraging the superior absorption capability of metal–organic frameworks (MOFs) and their inherent photocatalytic properties, iodine‐loaded MOF surface is presented to realize responsive iodine release along with intracellular reactive oxygen species(ROS) oxidation under near‐infrared (NIR) exposure to achieve synergistic antibacterial effect. Iodine is successfully loaded using vapor deposition process onto zeolitic imidazolate framework‐8(ZIF‐8), which is immobilized onto micro arc oxidized titanium via a hydrothermal approach. The combination of NIR‐triggered iodine release and ZIF‐8 mediated ROS oxidative stress substantially augments the antibacterial efficacy of this approach both in vitro and in vivo. Furthermore, this composite coating also supported osteogenic differentiation of bone marrow stromal cells, as well as improved osseointegration of coated implants using an intramedullary rat model, suggesting improvement of antibacterial efficacy does not impair osteogenic potential of the implants. Altogether, immobilization of iodine via MOF on orthopedic implants with synergistic antibacterial effect can be a promising strategy to combat bacterial infections.