Spinal cord injury (SCI) is a debilitating neurological condition that severely impacts motor, sensory, and autonomic functions, leading to significant challenges in patient quality of life and imposing substantial economic burdens on society. PANoptosis is an emerging concept in programmed cell death that combines three key processes: pyroptosis, apoptosis, and necroptosis. Research has demonstrated the significant roles of apoptosis, necroptosis, and pyroptosis in the progression of SCI. As such, targeting PANoptosis-related genes may offer new therapeutic targets and clinically relevant treatment strategies. This study seeks to identify distinct molecular subtypes of SCI and potential drugs for its treatment, based on the mechanisms of PANoptosis. We acquired RNA sequencing data from the Gene Expression Omnibus (GEO) datasets GSE151371 and performed Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA) analysis to delineate differential biological functions between SCI patients and healthy controls. We identified a total of 1138 significant differentially expressed genes (DEGs), comprising 431 downregulated and 707 upregulated genes. We intersected DEGs with PANoptosis gene sets and identified 23 common genes. 23 PANoptosis-related genes were subjected to functional enrichment analysis and PANoptosis scores calculation. PANoptosis score in SCI samples was significantly higher than in HC samples. Additionally, a protein-protein interaction (PPI) network was established to identify hub genes, and 8 machine learning algorithms were used to narrowed down hub genes. BMX and CASP5 were consistently identified across all algorithms. Immune cell infiltration analysis revealed significant correlations between BMX and several immune cell types, highlighting its involvement in the inflammatory response after SCI. Through additional ROC curve analysis, we confirmed the promising diagnostic potential of BMX, with an AUC value of 0.987. Moreover, we predicted potential therapeutic agents and key regulatory factors interacting with BMX. We performed single-gene GSEA analysis to explore the biological functions and pathways associated with BMX. Finally, we created a rat model of SCI to experimentally confirm the elevated expression of BMX in the SCI group by quantitative real-time PCR (qRT-PCR), western blot (WB) and immunohistochemistry (IHC). In conclusion, our findings provide valuable insights into the molecular mechanisms underlying SCI, highlighting BMX, a PANoptosis-related gene, as a potential therapeutic target. These results underscore the necessity for future studies to explore these targets in clinical applications.