Osteosarcoma (OS) is the most common primary malignant bone tumor in adolescents. The molecular mechanism behind OS progression and metastasis remains poorly understood, which limits the effectiveness of current therapies. RNA N⁶-methyladenosine (m⁶A) modification plays a critical role in influencing RNA fate. However, the biological significance of m⁶A modification and its potential regulatory mechanisms in the development of OS remain unclear. Liquid chromatography-tandem mass spectrometry (LC-MS/MS), dot blotting, and colorimetric ELISA were used to detect m⁶A levels. Western blotting, quantitative real-time PCR (RT-qPCR) and immunohistochemistry (IHC) were used to investigate METTL14 expression levels. Methylated RNA immunoprecipitation sequencing (MeRIP-seq) and transcriptomic RNA sequencing (RNA-seq) were used to screen the target genes of METTL14. RNA pull-down and RNA immunoprecipitation (RIP) assays were conducted to explore the specific binding of target genes and relevant m⁶A “readers”. RNA stability and polysome analysis assays were used to detect the half-lives and translation efficiencies of the downstream genes of METTL14. IHC and clinical data were applied to explore the clinical correlations of METTL14 and its downstream target genes with the prognosis of OS. We observed the abundance of m⁶A modifications in OS and revealed that METTL14 plays an oncogenic role in facilitating OS progression. MeRIP-seq and RNA-seq revealed that MN1 is a downstream gene of METTL14. MN1 contributes to tumor progression and all-trans-retinoic acid (ATRA) chemotherapy resistance in OS. Mechanistically, MN1 is methylated by METTL14, specifically in the coding sequence (CDS) regions, and this modification is recognized by the specific m⁶A reader insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) to prevent MN1 mRNA degradation and promote it translation efficiency. IHC showed that MN1 expression was positively correlated with METTL14 and IGF2BP2 expression in OS tissues. The METTL14-IGF2BP2-MN1 panel demonstrated more promising prognostic value for OS patients than any of these molecules individually. Our study revealed that METTL14 contributes to OS progression and ATRA resistance as an m⁶A RNA methylase by regulating the stability and translation efficiency of MN1 and thus provides both an underlying biomarker panel for prognosis prediction in OS patients. This work was supported by the National Natural Science Foundation of China (Grants 81972510 and 81772864).

Despite advances in treatment, the prognosis of patients with osteosarcoma remains unsatisfactory, and searching for potential targets is imperative. Here, we identify N4-acetylcytidine (ac4C) acetyltransferase 10 (NAT10) as a candidate therapeutic target in osteosarcoma through functional screening. NAT10 overexpression is correlated with a poor prognosis, and NAT10 knockout inhibits osteosarcoma progression. Mechanistically, NAT10 enhances mRNA stability of activating transcription factor 4 (ATF4) through ac4C modification. ATF4 induces the transcription of asparagine synthetase (ASNS), which catalyzes asparagine (Asn) biosynthesis, facilitating osteosarcoma progression. Utilizing virtual screening, we identify paliperidone and AG-401 as potential NAT10 inhibitors, and both inhibitors are found to bind to NAT10 proteins. Inhibiting NAT10 suppresses osteosarcoma progression in vivo. Combined treatment using paliperidone and AG-401 produces synergistic inhibition for osteosarcoma in patient-derived xenograft (PDX) models. Our findings demonstrate that NAT10 facilitates osteosarcoma progression through the ATF4/ASNS/Asn axis, and pharmacological inhibition of NAT10 may be a feasible therapeutic approach for osteosarcoma.

Background: Patients with advanced soft tissue sarcomas (STS) have a dismal prognosis with few effective therapeutic options. A defect in the homologous recombination repair (HRR) pathway can accumulate DNA repair errors and gene mutations, which can lead to tumorigenesis. BRCAness describes tumors with an HRR deficiency (HRD) in the absence of a germline BRCA1/2 mutation. However, the characteristics of BRCAness in STS remain largely unknown. Thus, this study aimed to explore the genomic and molecular landscape of BRCAness using whole exome sequencing (WES) in STS, aiming to find a potential target for STS treatment.

Background: Osteosarcoma is a highly aggressive cancer, and the efficacy of existing therapies has plateaued. Multiomics integration analysis can identify novel therapeutic targets for various cancers and therefore shows potential toward osteosarcoma treatment. This study aimed to leverage multiomics integration to develop a new risk model, characterizing the immune features of osteosarcoma to uncover novel therapeutic targets. Methods: Metabolomics profiling was conducted to identify key metabolites in osteosarcoma. Transcriptomic sequencing datasets were analyzed to identify prognostic genes related to key metabolic pathways and develop a prognostic risk model. Patients were then divided into high-risk and low-risk groups with distinct clinical outcomes based on the risk model. The single-sample gene set enrichment analysis, Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm, and xCell algorithms were used to evaluate the immune cell infiltration and activity. Single-cell RNA sequencing was used to explore cell-to-cell interactions within the tumor microenvironment. In vitro coculture functional assays were performed to validate the role of macrophage migration inhibitory factor (MIF) in macrophage polarization and chemotaxis. In vivo studies were used to evaluate the effectiveness of MIF inhibition in combination with immune checkpoint blockade in murine models. Results: Elevated lactate levels in osteosarcoma patients correlated with poorer overall survival. We identified SLC7A7 and CYP27A1 as prognostic lactate metabolism genes and developed a risk model to stratify patients into high-risk and low-risk groups with distinct outcomes. Bioinformatics analyses highlighted the differences in immune infiltration patterns and activity between the groups. Notably, the infiltration and phenotype of macrophages varied significantly between the groups, and MIF was identified as a critical mediator in this process. In osteosarcoma cells, lactate regulated MIF expression through histone H3K9 lactylation. Combining the MIF inhibitor 4-IPP with a programmed cell death 1 (PD-1) monoclonal antibody treatment demonstrated a significant antitumor effect. Conclusion: MIF acts as a novel therapeutic target by regulating macrophage polarization and chemotaxis. Lactate regulated MIF expression through histone lactylation. Targeting MIF holds promise for enhancing the efficacy of anti-PD-1 treatment.

Osteosarcoma is the most common malignant bone tumor in children and adolescents, characterized by high disability and mortality rates. Over the past three decades, therapeutic outcomes have plateaued, underscoring the critical need for innovative therapeutic targets. Solute carrier (SLC) family transporters have been implicated in the malignant progression of a variety of tumors, however, their specific role in osteosarcoma remains poorly understood. The single-cell sequencing data from GSE152048 and GSE162454, along with RNA-seq from the TARGET and GSE21257 cohorts, were utilized for the analysis in this study. LASSO regression analysis was conducted to identify prognostic genes and construct an SLC-related prognostic signature. Survival analysis and ROC analysis evaluated the validity of the prognostic signature. The ESTIMATE and CIBERSORT Packages were utilized to assess the immune infiltration status. Pseudotime and CellChat analyses were performed to investigate the relationship between SLC7A1, malignant phenotypes, and the immune microenvironment. CCK8 assays, EdU staining, colony formation assays, Transwell assays, and co-culture systems were used to assess the effects of SLC7A1 on cell proliferation, metastasis, and macrophage polarization. Finally, virtual docking identified potential drugs targeting SLC7A1. SLCs displayed distinct expression patterns across various cell types within the osteosarcoma microenvironment, with myeloid cells exhibiting a preference for amino acid uptake. A prognostic model comprising nine genes was constructed via LASSO regression, with SLC7A1 showing the highest hazard ratio. Multiple analytical algorithms indicated that SLCs were associated with immune cell infiltration and immune checkpoint gene expression. Single-cell analysis indicated that SLC7A1 was predominantly expressed in osteosarcoma cells and correlated with various malignant tumor characteristics. SLC7A1 also regulate interactions between tumor cells and macrophages, as well as modulate macrophage function through multiple pathways. In vitro assays and survival analysis demonstrated that inhibition of SLC7A1 suppressed the malignant phenotype of osteosarcoma cells, with SLC7A1 expression correlating with poor prognosis. Co-culture models confirmed the involvement of SLC7A1 in macrophage polarization. Finally, virtual screening and CETSA identified Cepharanthine as potential inhibitors of SLC7A1. SLC-related prognostic signatures can be utilized for the prognostic evaluation of osteosarcoma. Pharmacological inhibition of SLC7A1 may be a feasible therapeutic approach for osteosarcoma.