The premetastatic niche (PMN) contributes to lung-specific metastatic tropism in osteosarcoma. However, the crosstalk between primary tumor cells and lung stromal cells is not clearly defined. Here, we dissect the composition of immune cells in the lung PMN and identify granulocytic myeloid-derived suppressor cell (gMDSC) infiltration as positively associated with immunosuppressive PMN formation and tumor cell colonization. Osteosarcoma-cell-derived extracellular vesicles (EVs) activate lung interstitial macrophages to initiate the influx of gMDSCs via secretion of the chemokine CXCL2. Proteomic profiling of EVs reveals that EV-packaged S100A11 stimulates the Janus kinase 2/signal transducer and activator of transcription 3 signaling pathway in macrophages by interacting with USP9X. High level of S100A11 expression or circulating gMDSCs correlates with the presentation of lung metastasis and poor prognosis in osteosarcoma patients. In summary, we identify a key role of tumor-derived EVs in lung PMN formation, providing potential strategies for monitoring or preventing lung metastasis in osteosarcoma.

The high heterogeneity and severe side effects of chemotherapy are major factors contributing to the failure of osteosarcoma treatment. Herein, a comprehensive genomic analysis is conducted, and identified two prominent characteristics of osteosarcoma: significant cyclin‐dependent kinases 4 (CDK4) amplification and homologous recombination repair deficiency. Based on these findings, a co‐delivery system loaded with CDK4/6 inhibitors and poly ADP‐ribose polymerase (PARP) inhibitors is designed. By employing metal–organic frameworks (MOFs) as carriers, issue of drug insolubility is effectively addressed, while also enabling controlled release in response to the tumor microenvironment. To enhance targeting capability and biocompatibility, the MOFs are further coated with a bio‐membrane targeting B7H3. This targeted biomimetic co‐delivery system possesses several key features: 1) it can precisely target osteosarcoma with high B7H3 expression; 2) the combination of CDK4/6 inhibitors and PARP inhibitors exhibits synergistic effects, significantly impairing tumor's DNA repair capacity; and 3) the system has the potential for combination with photodynamic therapy, amplifying DNA repair defects to maximize tumor cell eradication. Furthermore, it is observed that this co‐delivery system can activate immune microenvironment, increasing CD8⁺ T cell infiltration and converting osteosarcoma from an immune‐cold to an immune‐hot tumor. In summary, the co‐delivery system is an effective therapeutic strategy and holds promise as a novel approach for osteosarcoma treatment.

The risk of osteoporosis in breast cancer patients is higher than that in healthy populations. The fracture and death rates increase after patients are diagnosed with osteoporosis. We aimed to develop machine learning-based models to predict the risk of osteoporosis as well as the relative fracture occurrence and prognosis. We selected 749 breast cancer patients from two independent Chinese centers and applied six different methods of machine learning to develop osteoporosis, fracture and survival risk assessment models. The performance of the models was compared with that of current models, such as FRAX, OSTA and TNM, by applying ROC, DCA curve analysis, and the calculation of accuracy and sensitivity in both internal and independent external cohorts. Three models were developed. The XGB model demonstrated the best discriminatory performance among the models. Internal and external validation revealed that the AUCs of the osteoporosis model were 0.86 and 0.87, compared with the FRAX model (0.84 and 0.72)/OSTA model (0.77 and 0.66), respectively. The fracture model had high AUCs in the internal and external cohorts of 0.93 and 0.92, which were higher than those of the FRAX model (0.89 and 0.86). The survival model was also assessed and showed high reliability via internal and external validation (AUC of 0.96 and 0.95), which was better than that of the TNM model (AUCs of 0.87 and 0.87). Our models offer a solid approach to help improve decision making.

Nuclear condensates have been shown to regulate cell fate control, but its role in oncogenic transformation remains largely unknown. Here we show acquisition of oncogenic potential by nuclear condensate remodeling. The proto-oncogene SS18 and its oncogenic fusion SS18-SSX1 can both form condensates, but with drastically different properties and impact on 3D genome architecture. The oncogenic condensates, not wild type ones, readily exclude HDAC1 and 2 complexes, thus, allowing aberrant accumulation of H3K27ac on chromatin loci, leading to oncogenic expression of key target genes. These results provide the first case for condensate remodeling as a transforming event to generate oncogene and such condensates can be targeted for therapy. One sentence summary: Expulsion of HDACs complexes leads to oncogenic transformation.

Purpose: To explore the efficacy and safety of lenvatinib, either as a monotherapy or in combination with programmed death-1 (PD-1) blockades, as re-challenging treatment in patients with metastatic osteosarcoma following treatment failure with previous tyrosine kinase inhibitors (TKIs). Patients and Methods: We retrospectively reviewed the data of 26 patients with metastatic osteosarcoma who received rechallenge treatment with lenvatinib monotherapy or lenvatinib plus PD-1 blockades after failure of the initial TKI treatment from January 2020 to June 2024 in our center. The primary endpoint was progression-free survival (PFS). Secondary endpoints included objective response rate (ORR), clinical benefit rate (CBR), and safety. Results: Of the 26 patients, ORR and CBR were 11.5% and 61.5%, respectively. The median duration of follow-up was 15 months (range, 4.3– 25.6) with a median PFS of 7.2 months (95% CI: 1.9– 12.5). A total of 14 patients received lenvatinib as a monotherapy, and 12 received a combination therapy of lenvatinib and PD-1 blockade. No significant differences were observed in ORR (0 vs 25%) and CBR (57.1 vs 66.7%) between the two groups. Additionally, the combination cohort exhibited a significantly longer PFS compared to the monotherapy cohort (8.6 [95% CI: 5.0– 12.1] vs 4.0 months [95% CI: 1.0– 7.0], p = 0.022). 96.2% of patients experienced grade 1 or more adverse events (AEs). Grade 3 adverse events occurred in 6 (23.1%) patients. The safety profiles of the lenvatinib and PD-1 blockade combination group were found to be comparable to those of the lenvatinib monotherapy group. Conclusion: Our data indicated that patients with metastatic osteosarcoma could potentially benefit from lenvatinib rechallenge after progress with initial TKI treatment. The combination of lenvatinib and PD-1 blockade therapy demonstrated promising survival outcomes in patients with metastatic osteosarcoma, accompanied by a manageable toxicity profile.