Aim: To analyze the m6A methylome of osteosarcoma stem cells (OSCs). Materials & methods: Chemoresistant OSCs were enriched by doxorubicin treatment. Expression of m6A-related enzymes was detected ...

Background: Osteosarcoma (OSA) presents a clinical challenge and has a low 5‐year survival rate. Currently, the lack of advanced stratification models makes personalized therapy difficult. This study aims to identify novel biomarkers to stratify high‐risk OSA patients and guide treatment.Methods: We combined 10 machine‐learning algorithms into 101 combinations, from which the optimal model was established for predicting overall survival based on transcriptomic profiles for 254 samples. Alterations in transcriptomic, genomic and epigenomic landscapes were assessed to elucidate mechanisms driving poor prognosis. Single‐cell RNA sequencing (scRNA‐seq) unveiled genes overexpressed in OSA cells as potential therapeutic targets, one of which was validated via tissue staining, knockdown and pharmacological inhibition. We characterized changes in multiple phenotypes, including proliferation, colony formation, migration, invasion, apoptosis, chemosensitivity and in vivo tumourigenicity. RNA‐seq and Western blotting elucidated the impact of squalene epoxidase (SQLE) suppression on signalling pathways.Results: The artificial intelligence‐derived prognostic index (AIDPI), generated by our model, was an independent prognostic biomarker, outperforming clinicopathological factors and previously published signatures. Incorporating the AIDPI with clinical factors into a nomogram improved predictive accuracy. For user convenience, both the model and nomogram are accessible online. Patients in the high‐AIDPI group exhibited chemoresistance, coupled with overexpression of MYC and SQLE, increased mTORC1 signalling, disrupted PI3K–Akt signalling, and diminished immune infiltration. ScRNA‐seq revealed high expression of MYC and SQLE in OSA cells. Elevated SQLE expression correlated with chemoresistance and worse outcomes in OSA patients. Therapeutically, silencing SQLE suppressed OSA malignancy and enhanced chemosensitivity, mediated by cholesterol depletion and suppression of the FAK/PI3K/Akt/mTOR pathway. Furthermore, the SQLE‐specific inhibitor FR194738 demonstrated anti‐OSA effects in vivo and exhibited synergistic effects with chemotherapeutic agents.Conclusions: AIDPI is a robust biomarker for identifying the high‐risk subset of OSA patients. The SQLE protein emerges as a metabolic vulnerability in these patients, providing a target with translational potential.

Panax notoginseng, an important Chinese medicinal herb, can be mainly cultivated in two planting patterns, cropland planting (DT) and understory planting (LX). We speculate that the rhizosphere microbiome may vary in DT and LX and may play an important role in promoting the growth and health of P. notoginseng. In the present study, culture-independent Illumina HiSeq was employed to investigate the rhizosphere bacteria and fungi under DT and LX planting patterns. Predominant phyla include Proteobacteria, Acidobacteria, Actinobacteria, Gemmatimonadetes, and Ascomycota in the two planting patterns. DT has higher alpha diversity index than LX. The predominant LX-core genera include Bradyrhizobium, Streptomyces, and Actinomadura, and the predominant DT-core genera include Sphingomonas, Variovorax, and Novosphingobium. Total relative abundance of the disease-suppression phylum (Proteobacteria, Firmicutes, and Actinobacteria) and the potential plant growth-promoting rhizobacteria (PGPR) were both significantly higher in LX than in DT. We also identified over-presented microbial functional traits mediating plant–microbe and microbe–microbe interactions, nutrition acquisition, and plant growth promotion in P. notoginseng rhizosphere. Our findings provide a valuable reference for studying beneficial microbes and pathogens of P. notoginseng planted in DT and LX.

Giant cell tumor (GCT) of bone is an aggressive skeletal tumor characterized by localized bone resorption. MicroRNA-16-5p (miR-16-5p) has been reported to be downregulated in lesions of patients with GCT, but little is known about its role in GCT. To explore the underlying function of miR-16-5p in GCT, we first detected its expression in patients with GCT. The results showed that osteoclast formation increased, whereas miR-16-5p expression considerably decreased with the severity of bone destruction. Furthermore, we found that miR-16-5p expression considerably decreased with the progression of receptor activator of nuclear factor-κB ligand- (RANKL-) induced osteoclastogenesis. Functionally, miR-16-5p mimics significantly reduced RANKL-induced osteoclast formation. However, treatment with an inhibitor of miR-16-5p significantly promoted osteoclastogenesis. These findings reveal that miR-16-5p inhibits osteoclastogenesis and that it may represent a therapeutic target for giant cell tumor of bone.