Deficient bone regeneration causes bone defects or nonunion in a substantial proportion of trauma patients that urges for novel therapies. To develop a reliable therapy, we investigated the effect of negative pressure wound therapy (NPWT) on bone regeneration in vivo in a rat calvarial defect model. Negative pressure (NP) treatment in vitro was mimicked to test its effect on osteoblast differentiation in rat mesenchymal stem cells (MSCs) and MC3T3-E1 cells. Transcriptomic analyses, pharmaceutical interventions, and shRNA knockdowns were conducted to explore the underlying mechanism and their clinical relevance was investigated in samples from patients with nonunion. The potential application of a combined therapy of MSCs in hydrogels with negative pressure was tested in the rat critical-size calvarial defect model. We found that NPWT promoted bone regeneration in vivo and NP treatment induced osteoblast differentiation in vitro. NP induced osteogenesis via activating macroautophagy/autophagy by AMPK-ULK1 signaling that was impaired in clinical samples from patients with nonunion. More importantly, the combined therapy involving MSCs in hydrogels with negative pressure significantly improved bone regeneration in rat critical-size calvarial defect model. Thus, our study identifies a novel AMPK-ULK1-autophagy axis by which negative pressure promotes osteoblast differentiation of MSCs and bone regeneration. NPWT treatment can potentially be adopted for therapy of bone defects. Abbreviations: ADP, adenosine diphosphate; AICAR/Aic, acadesine; ALP, alkaline phosphatase; ALPL, alkaline phosphatase, biomineralization associated; AMP, adenosine monophosphate; AMPK, AMP-activated protein kinase; ARS, alizarin red S staining; ATG7, autophagy related 7; ATP, adenosine triphosphate; BA1, bafilomycin A₁; BGLAP/OCN, bone gamma-carboxyglutamate protein; BL, BL-918; BS, bone surface; BS/TV, bone surface per tissue volume; BV/TV, bone volume per tissue volume; C.C, compound C; CCN1, cellular communication network factor 1; COL1A1, collagen type I alpha 1 chain; COL4A3, collagen type IV alpha 3 chain; COL4A4, collagen type IV alpha 4 chain; COL18A1, collagen type XVIII alpha 1 chain; CQ, chloroquine; GelMA, gelatin methacryloyl hydrogel; GO, Gene Ontology; GSEA, gene set enrichment analysis; HIF1A, hypoxia inducible factor 1 subunit alpha; HPLC, high-performance liquid chromatography; ITGAM/CD11B, integrin subunit alpha M; ITGAX/CD11C, integrin subunit alpha X; ITGB1/CdD9, integrin subunit beta 1; KEGG, Kyoto Encyclopedia of Genes and Genomes; MAP1LC3B/LC3B, microtubule associated protein 1 light chain 3 beta; micro-CT, microcomputed tomography; MSCs, mesenchymal stem cells; MTOR, mechanistic target of rapamycin kinase; NP, negative pressure; NPWT, negative pressure wound therapy; PRKAA1/AMPKα1, protein kinase AMP-activated catalytic subunit alpha 1; PRKAA2, protein kinase AMP-activated catalytic subunit alpha 2; PTPRC/CD45, protein tyrosine phosphatase receptor type C; ROS, reactive oxygen species; RUNX2, RUNX family transcription factor 2; SBI, SBI-0206965; SPP1/OPN, secreted phosphoprotein 1; THY1/CD90, Thy-1 cell surface antigen; SQSTM1, sequestosome 1; TGFB3, transforming growth factor beta 3; ULK1/Atg1, unc-51 like autophagy activating kinase 1.

The ideal tissue engineering scaffold should facilitate rapid cell infiltration and provide an optimal immune microenvironment during interactions with the host. Electrospinning can produce two-dimensional (2D) membranes mimicking the extracellular matrix. However, their dense structure hinders cell penetration, and their thin form restricts scaffold utility. In this study, latticed hydrogels were three-dimensional (3D) printed onto electrospun membranes. This technique allowed for layer-by-layer assembly of the membranes into 3D scaffolds, which maintained their resilience impressively under both dry and wet conditions. We assessed the cellular and host responses of these 3D nanofiber scaffolds by comparing random membranes and mesh-like membranes with three different mesh sizes (250, 500, and 750 μm). It was found that scaffolds with a mesh size of 500 μm were superior for M2 macrophage phenotype polarization, vascularization, and matrix deposition. Furthermore, it was confirmed by subsequent experiments such as RNA sequencing that the mesh-like topology may promote polarization to the M2 phenotype by affecting the PI3K/AKT pathway. In conclusion, our work offers a novel method for transforming 2D nanofiber membranes into 3D scaffolds. This method boasts flexibility, allowing for the use of varied electrospun membranes and hydrogels in terms of structure and composition. It has vast potential in tissue repair and regeneration.

The complex genomics, immunosuppressive tumor microenvironment (TME), and chemotherapeutic resistance of osteosarcoma (OS) have resulted in limited therapeutic effects in the clinic. Ferroptosis is involved in tumor progression and is regulated mainly by glutathione peroxidase 4 (GPX4). Small interfering RNA (siRNA)-based RNA interference (RNAi) can precisely target any gene. However, achieving effective siRNA delivery is highly challenging. Here, we fabricated a TME-responsive metal-organic framework (MOF)-based biomimetic nanosystem (mFeP@si) with siGPX4 delivery and sonodynamic therapy (SDT) to treat OS by targeting ferroptosis. Under ultrasound (US) irradiation, mFeP@si achieves lysosomal escape via singlet oxygen (¹O₂)-mediated lysosomal membrane disruption and then accelerates ROS generation and glutathione (GSH) depletion. Meanwhile, siGPX4 silences GPX4 expression by binding to GPX4 mRNA and leads to the accumulation of toxic phospholipid hydroperoxides (PL-OOH), further magnifying the ROS storm and triggering ferroptosis. Notably, synergistic therapy remarkably enhances antitumor effects, improves the immunosuppressive TME by inducing potent immunogenic cell death (ICD), and increases the sensitivity of chemotherapy-resistant OS cells to cisplatin. Overall, this novel nanosystem, which targets ferroptosis by integrating RNAi and SDT, exhibits strong antitumor effects both in vitro and in vivo, providing new insights for treating OS.

Construction and Validation of a Macrophage-Associated Risk Model for Predicting the Prognosis of Osteosarcoma: Background. Osteosarcoma is one of the most common bone tumors among children. Tumor-associated macrophages have been found to interact with tumor cells, secreting a variety of cytokines about tumor growth, metastasis, and prognosis. This study aimed to identify macrophage-associated genes (MAGs) signatures to predict the prognosis of osteosarcoma. Methods. Totally 384 MAGs were collected from GSEA software C7: immunologic signature gene sets. Differential gene expression (DGE) analysis was performed between normal bone samples and osteosarcoma samples in GSE99671. Kaplan–Meier survival analysis was performed to identify prognostic MAGs in TARGET-OS. Decision curve analysis (DCA), nomogram, receiver operating characteristic (ROC), and survival curve analysis were further used to assess our risk model. All genes from TARGET-OS were used for gene set enrichment analysis (GSEA). Immune infiltration of osteosarcoma sample was calculated using CIBERSORT and ESTIMATE packages. The independent test data set GSE21257 from gene expression omnibus (GEO) was used to validate our risk model. Results. 5 MAGs (MAP3K5, PML, WDR1, BAMBI, and GNPDA2) were screened based on protein-protein interaction (PPI), DGE, and survival analysis. A novel macrophage-associated risk model was constructed to predict a risk score based on multivariate Cox regression analysis. The high-risk group showed a worse prognosis of osteosarcoma ( < 0.001) while the low-risk group had higher immune and stromal scores. The risk score was identified as an independent prognostic factor for osteosarcoma. MAGs model for diagnosis of osteosarcoma had a better net clinical benefit based on DCA. The nomogram and ROC curve also effectively predicted the prognosis of osteosarcoma. Besides, the validation result was consistent with the result of TARGET-OS. Conclusions. A novel macrophage-associated risk score to differentiate low- and high-risk groups of osteosarcoma was constructed based on integrative bioinformatics analysis. Macrophages might affect the prognosis of osteosarcoma through macrophage differentiation pathways and bring novel sights for the progression and prognosis of osteosarcoma.