Establishment and Validation of a Risk Scoring Model Based on Autophagy Subcluster-related Modular Genes for Prognostic Prediction in Osteosarcoma.

Abstract

Aims: This study aims to determine the clinical significance of autophagy in OS prognosis and explore the potential molecular mechanisms between it and tumour-infiltrating immune cells.

Materials and methods: Autophagy-associated gene (AAG) expression data were retrieved from The Cancer Genome Atlas to construct an AAG expression matrix for osteosarcoma (OS). Using univariate Cox and LASSO regression analyses, three key prognostic AAGs (CCL2, DDN and GJA5) were identified. Based on these genes, we calculated individual risk scores and established an autophagy-associated prognostic model. OS patients were stratified into high- and low-risk groups according to autophagy-related risk scores to explore prognosis-associated mechanisms. Gene enrichment analyses were conducted to investigate the involved biological pathways, a nomogram integrating clinical parameters was developed, and the tumour immune infiltration landscape was assessed. Furthermore, the differential expression of the three AAGs was experimentally validated by quantitative real-time polymerase chain reaction (qRT-PCR) in a normal osteoblast cell line (hFOB1.19) and OS cell lines (143B, MG63 and U2OS), supporting the predicted transcriptional trends.

Results: We integrated three autophagy-related prognostic genes to construct a nomogram, which demonstrated high predictive accuracy and robustness as evidenced by calibration curves and survival analyses. These AAGs exhibited dual functions in immune regulation and were implicated in multiple cytokine signalling pathways. Tumour immune infiltration analysis revealed distinct immune landscapes between risk groups, consistent with findings from pathway enrichment analysis. Furthermore, qRT-PCR validation in normal osteoblasts (hFOB1.19) and osteosarcoma cell lines (143B, MG63 and U2OS) confirmed that DDN was significantly upregulated, whereas CCL2 and GJA5 were downregulated in tumour cells, aligning with the transcriptional trends predicted by the model.

Conclusion: Our findings suggest that excessive autophagy is closely associated with poor prognosis and altered immune cell infiltration, particularly involving macrophages, in osteosarcoma. These results highlight the dual roles of autophagy in tumour progression and immune regulation. However, macrophage-related autophagy in OS remains poorly understood, warranting further mechanistic studies and experimental validation.