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Abstract Objectives This study aimed to identify novel targets in the carcinogenesis, therapy and prognosis of osteosarcoma from genomic level, together with screening ideal lead compounds with potential inhibition regarding MMP-9. Methods Gene expression profiles from GSE12865, GSE14359, GSE33382, GSE36001 and GSE99671 were obtained respectively from GEO database. Differentially expressed genes were identified, and functional enrichment analysis, such as GO, KEGG, GSEA, PPI were performed to make a comprehensive understanding of the hub genes. Next, a series of high-precision computational techniques were conducted to screen potential lead compounds targeting MMP9, including virtual screening, ADME, toxicity prediction, and accurate docking analysis. Results 10 genes, MMP9, CD74, SPP1, CXCL12, TYROBP, FCER1G, HCLS1, ARHGDIB, LAPTM5 and IGF1R were identified as hub genes in the initiation of osteosarcoma. Machine learning, multivariate Cox analysis, ssGSEA and survival analysis demonstrated that these genes had values in prognosis, immune-correlation and targeted treatment. Tow novel compounds, ZINC000072131515 and ZINC000004228235, were screened as potential inhibitor regarding MMP9, and they could bind to MMP9 with favorable interaction energy and high binding affinity. Meanwhile, they were precited to be efficient and safe drugs with low-ames mutagenicity, none weight evidence of carcinogenicity, as well as non-toxic with liver. Conclusions This study revealed the significance of 10-gene signature in the development of osteosarcoma. Besides, drug candidates identified in this study provided a solid basis on MMP9 inhibitors’ development.

Objectives: This study aimed to identify novel targets in the carcinogenesis, therapy and prognosis of osteosarcoma from genomic level, together with screening ideal lead compounds with potential inhibition regarding MMP-9. Methods: Gene expression profiles from GSE12865, GSE14359, GSE33382, GSE36001 and GSE99671 were obtained respectively from GEO database. Differentially expressed genes were identified, and functional enrichment analysis, such as GO, KEGG, GSEA, PPI were performed to make a comprehensive understanding of the hub genes. Next, a series of high-precision computational techniques were conducted to screen potential lead compounds targeting MMP9, including virtual screening, ADME, toxicity prediction, and accurate docking analysis. Results: 10 genes, MMP9, CD74, SPP1, CXCL12, TYROBP, FCER1G, HCLS1, ARHGDIB, LAPTM5 and IGF1R were identified as hub genes in the initiation of osteosarcoma. Machine learning, multivariate Cox analysis, ssGSEA and survival analysis demonstrated that these genes had values in prognosis, immune-correlation and targeted treatment. Tow novel compounds, ZINC000072131515 and ZINC000004228235, were screened as potential inhibitor regarding MMP9, and they could bind to MMP9 with favorable interaction energy and high binding affinity. Meanwhile, they were precited to be efficient and safe drugs with low-ames mutagenicity, none weight evidence of carcinogenicity, as well as non-toxic with liver. Conclusions: This study revealed the significance of 10-gene signature in the development of osteosarcoma. Besides, drug candidates identified in this study provided a solid basis on MMP9 inhibitors' development. [ABSTRACT FROM AUTHOR]