A novel anoikis-resistance related signature predicts pulmonary metastasis in osteosarcoma

Pulmonary metastasis remains the leading cause of mortality in patients with osteosarcoma (OS). Anoikis functions as a physiological barrier to metastasis by eliminating detached cells. Tumor cells with high anoikis resistance can survive detachment and circulation, facilitating pulmonary metastasis. However, the prognostic significance and biological role of anoikis-related genes (ARGs) in osteosarcoma remain largely unexplored. Transcriptomic profiles and clinical information of osteosarcoma patients were obtained from the TCGA database ( n = 90) and used as the training cohort. Anoikis-related genes were retrieved from the GeneCards database. Differential expression analysis was performed between metastatic and non-metastatic osteosarcoma samples, and candidate ARGs were identified by intersecting differentially expressed genes with ARGs. A prognostic signature was established using univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox analysis. Kaplan–Meier survival analysis, receiver operating characteristic (ROC) curves, multivariate Cox regression, and nomogram analysis were performed to evaluate the predictive performance of the model. Two independent GEO datasets (GSE87624, n = 52 ; GSE220538, n = 38) were used for external validation. Tumor microenvironment characteristics were assessed using immune cell deconvolution with the immunedeconv package and immune infiltration analyses. Furthermore, single-cell RNA sequencing data (GSE152048, n = 11; GSE250015, n = 2) were analyzed to validate the cellular distribution and biological relevance of the risk signature. A total of seven metastasis-associated ARGs were identified, among which five genes (UCHL1, ST3GAL1, NTF3, NGFR, and CRABP2) were incorporated into the final anoikis-resistance related gene signature(AR-Score). Patients in the high-risk group exhibited significantly worse metastasis-free survival (MFS) than those in the low-risk group ( P < 0.001). Multivariate Cox regression demonstrated that the risk score was an independent prognostic factor for osteosarcoma (HR = 6.53, 95% CI: 2.87–14.90, P < 0.001). A prognostic nomogram integrating the AR-Score and clinical characteristics showed predictive performance, with area under the curve (AUC) values of 0.90, 0.92, and 0.93 for 1-, 3-, and 5-year MFS prediction, respectively. External validation in two independent GEO cohorts confirmed the performance of the model. Tumor microenvironment analysis revealed significantly higher immune scores in high-AR-Score patients, suggesting that anoikis resistance may contribute to the formation of a metastasis-promoting immune microenvironment. Single-cell transcriptomic analysis further demonstrated that metastatic osteosarcoma samples exhibited elevated anoikis-related risk scores compared with primary tumors, supporting the involvement of anoikis resistance in metastatic progression. We developed and validated a novel anoikis-associated prognostic signature that effectively predicts pulmonary metastasis risk in osteosarcoma. These findings provide a promising tool for risk stratification and offer potential therapeutic targets for preventing metastatic dissemination in osteosarcoma.