Construction and analysis of a prognostic model for osteosarcoma based on lactate metabolism-related genes

Background Lactic acid metabolism plays a significant role in tumor development, potentially resulting in alterations in the immune microenvironment. However, further research is necessary to investigate the link between lactic acid metabolism and osteosarcoma. Methods We obtained sequencing data and clinical information for osteosarcoma RNA from TCGA and GEO databases. Prognosis-related LMRGs were identified using Cox regression, enabling the construction of risk scores for patients. Model predictive ability was assessed using various methods. Drug sensitivity for high and low-risk groups was evaluated using the oncoPredict algorithm, and model genes were validated in a single-cell dataset. Besides, we verified the biological function of NHLRC2 using in vitro assays. Results We identified 256 differential LMRGs, of which 137 were associated with prognosis. After applying Lasso regression, we selected 5 LMRGs for our prognostic risk score model. The log-rank test showed significant survival differences between high-risk and low-risk groups. Multi-factor Cox analysis confirmed the independence of the prognostic risk score as a robust prognostic factor. In vitro experiments confirmed that NHLRC2 could promote the proliferation and invasion of OS. Conclusion We successfully developed and validated an osteosarcoma risk identification score using five LMRGs. Notably, one of these genes holds significant implications for the exploration of potential therapeutic targets in osteosarcoma research.