Background: This study sought to identify potential key genes for osteosarcoma metastasis and analyze their immune infiltration patterns using bioinformatic methods.Methods: We obtained transcriptomic data related to osteosarcoma and osteosarcoma with metastasis from the Therapeutically Applicable Research to Generate Effective Treatment (TARGET) and The Gene Expression Omnibus (GEO) databases and identified the differentially expressed genes (DEGs). We also identified potential key genes for osteosarcoma metastasis by a protein-protein interaction network analysis, and we conducted a Gene Ontology (GO) functional annotation analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify the core genes for prognosis, immune cell infiltration, and drug sensitivity, and the risk prediction and prognosis models of metastasis were constructed.Results: By comparing the transcriptome data of osteosarcomas without metastasis and those with metastasis, a total of 19 core DEGs were identified, and the GO and KEGG analyses revealed an association between these DEGs and the regulation of cell division, secretory granule lumen, the Ras-associated protein 1 (Rap1) signaling pathway, and the mitogen-activated protein kinase (MAPK) signaling pathway. Compared with other immune cells, macrophage infiltration was predominant in osteosarcoma samples with metastatic osteosarcoma, and insulin-like growth factors-1 (IGF1) and myelocytomatosis protein 2 (MYC2) genes were predicted to more than 50 targeted therapeutic agents. A metastasis prediction model with 5 genes [i.e., ecotropic viral integration site 2B (EVI2B), CCAAT/enhancer binding protein (CEBPA), lymphocyte cytosolic protein 2 (LCP2), selectin L (SELL), and Niemann-Pick disease, type C2A (NPC2A)], and a prognostic model with 4 genes [i.e., insulin-like growth factors-2 (IGF2), cathepsin O (CTSO), Niemann-Pick disease, type C2 (NPC2), and amyloid beta (A4) precursor protein-binding, family B, member 1 interacting protein (APBB1IP)] were developed. Conclusions:We constructed a metastasis prediction model with 5 genes (i.e., EVI2B, CEBPA, LCP2, SELL, and NPC2A), and a prognostic model with 4 genes (i.e., IGF2, CTSO, NPC2, and APBB1IP) that may be potential biomarkers for osteosarcoma metastasis. Macrophages are the predominant immune infiltrating cells in osteosarcoma metastasis and may provide a new direction for the treatment of osteosarcoma.
Background: The immune microenvironment plays an essential role in osteosarcoma (OSs); however, differences in immune-related long non-coding ribonucleic acids (irlncRNAs) in children with localized OSs and metastatic OSs have not yet been investigated. Methods:The clinical data and the transcriptome of OSs were obtained from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, and the immune-related genes were derived from the imported dataset. The correlations between immune-related genes and lncRNAs were examined.Next, the differential expressions of the irlncRNA pairs (IRLPs) in localized OSs and distant metastatic OSs were analyzed, and a prognostic model was constructed based on the significant differentially expressed IRLPs.We also analyzed the association between the IRLPs' signature risk score and the infiltration of the immune cells. Finally, we investigated the correlation between risk score and drug resistance.Results: Thirty upregulated and 22 downregulated lncRNAs were identified in the localized and metastatic OSs samples. Univariate and multivariate cox regression analyses were undertaken to select 6 lncRNA pairs to establish the prognostic signature, the model was valuable in predicting OSs prognosis. Further, the expression of the finally selected irlncRNAs indicated that VPS9D1-AS1 (P=0.
Objective: This research aims to explore the clinical curative effect for the treatment peripheral nerve injury growth factor of Mecobalamin combined with nerve. Methods: 150 cases of patients with peripheral nerve injury treated in the hospital in July were selected from 2011 to 2013. Those patients were randomly divided into three groups according to the types of injured nerve and the undergoing treatment order. 50 cases are for each group. Patients in group A were injected with 0.5 mg Mecobalamin by intravenous injection. It lasted for once a day, for 10 days. Later, 0.5 mg Mecobalamin was changed to be taken orally, three times a day, a course of treatment. And a course is 3 to 6 weeks. 50 patients in group B were injected with nerve growth factor for 30 micrograms by intramuscular injection, once a day, a course of treatment. And a course is 3 to 6 weeks. While in group C, 50 patients were treated with Mecobalamin (0.5 mg, intravenous injection, once a day) combined with nerve growth factor (30 mg, intramuscular injection, once a day). A course lasted 3 to 6 weeks. The purpose is to observe the therapeutic effect of two different drugs on patients with peripheral nerve injury. Results: The curative effect of Mecobalamin combined with nerve growth factors for the treatment of peripheral nerve injury in group C is more significant than the single drug treatment in group A and group B. Peripheral nerve injury after sensorimotor function rating evaluation of curative effect made by The British Medical Research Institute of Neurotrauma Society was applied in this research. The comparison of the results of 3 groups after treatment is showed as follows. As to the sensory recovery above level II, the curative * The first author. # Contribute equally as the first author and corresponding author. C. K. Huang et al.76 effect in C group is generally better than in group A and group B, the approximate chi square test H = 13.6573, P = 0.0011. About motion recovery situation, there is a statistical significance in group A and group C which recovered V level X 2 = 3.8431, P = 0.0499, while there is no obvious difference in group B (P > 0.05). Conclusion: Some certain curative effect is presented of Mecobalamin combined with nerve growth factor in the treatment of peripheral nerve injury, which has an important clinical significance. Therefore, it is worth taking into application.
Background: Osteoarthritis (OA) is one of the most common diseases in elderly people; however, the correlation between molecular alterations and the occurrence and progression of OA are still not well understood. We conducted this study to investigate the molecular changes in OA via the competing endogenous ribonucleic acid (ceRNA) network. Methods:We downloaded the messenger RNA (mRNA) data set, GSE48556, the microRNA (miRNA) data set, GSE105027, and the long non-coding (lncRNA) data set, GSE126963 from the Gene Expression Omnibus (GEO) database, and examined the differentially expressed genes (DEGs) in these data sets.Further, we constructed a ceRNA network of the differentially expressed miRNAs, mRNAs, and lncRNAs.To determine the biological functions of the ceRNA network, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses. Finally, we conducted an immune cell infiltration analysisusing single-sample gene set enrichment analysis to examine the abundance of immune cells in healthy and OA patients, and compared the infiltration of 28 immune cells between the healthy and OA samples. We also analyzed the relationship between the abundance of immune cells and mRNA expression levels in the ceRNA network.Results: Ultimately hsa-mir-425-3p, dual specificity phosphatase 1, and 24 lncRNAs were identified in the ceRNA network. The functional enrichment analyses showed that these lncRNAs, miRNAs, and mRNAs are involved in various significant biological process, such as the regulation of leukocyte migration, Mitogen-Activated Protein (MAP) kinase tyrosine/serine/threonine phosphatase activity, the interleukin-17 signaling pathway, the tumor necrosis factor signaling pathway, and osteoclast differentiation, and can also have a strong effect on immune cell infiltration. Conclusions:The dual-specificity phosphatase 1-specific ceRNA network can be used as a diagnostic tool to assess the progression of OA patients.
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