Abstract
ObjectivesThis 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.MethodsGene 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.Results10 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.ConclusionsThis 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.
Highlights
Osteosarcoma (OS), one of the most common malignant neoplasm, accounts for 20–40% of all bone cancers, which is characterized by the direct formation of osteoid tissue, osteoid- and spindle-shaped matrix cell in immature bones [1]
Results showed that the median expression value of each dataset were on a straight line, and gene expression value accorded with normal distribution, indicating that the data processed in this study could be analyzed for further investigation
We made principle component analysis (PCA) on the processed matrix to observe the difference between different phenotypes, and results illustrated that normal samples could be distinguished from tumor samples on PCA1 axis (Additional file 3: Figure S3D)
Summary
Osteosarcoma (OS), one of the most common malignant neoplasm, accounts for 20–40% of all bone cancers, which is characterized by the direct formation of osteoid tissue, osteoid- and spindle-shaped matrix cell in immature bones [1]. The main clinical treatment for patients with OS included surgery, radiotherapy, and chemotherapy. JNJ0966, GS-5745, two chemotherapy drugs, were selective inhibitors regarding matrix metalloproteinase-9 (MMP-9), had shown prospective view in treatment of encephalomyelitis, ulcerative colitis and gastric cancer [11, 12]. Researches based on MMP9 inhibitors regarding osteosarcoma had hardly been reported before, which could make significance in targeted chemotherapy regarding osteosarcoma. Based on the fact that poor prognosis and lack of effective targeted therapies as well as tumor-related biomarkers in OS, there is an urgent need to explore novel predictive and prognostic biomarkers as well as discover lead compound inhibitors regarding OS, in order to make a comprehensive understanding of oncogene and eventually improve the prognosis of patients
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