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RASSF4, a member of the RASSF family, is broadly expressed in normal tissues but often inactivated in human cancers. Despite various studies on RASSF4, its role in osteosarcoma remains unclear. Therefore, in this study, we investigated the effects of RASSF4 expression on osteosarcoma cells and explored the underlying mechanism. The results of our study showed that RASSF4 was lowly expressed in osteosarcoma tissues and cells. RASSF4 overexpression significantly inhibited proliferation, migration, and invasion as well as the EMT process in osteosarcoma cells. Meanwhile, we found that RASSF4 overexpression markedly decreased the protein expression of β-catenin, cyclin D1, and c-Myc in osteosarcoma cells. In conclusion, our findings showed that RASSF4 overexpression inhibits proliferation, invasion, EMT, and Wnt signaling pathway in osteosarcoma cells. Thus, RASSF4 may be considered a novel target for osteosarcoma treatment.

Background: This study aims to identify a predictive model to predict survival outcomes of osteosarcoma (OS) patients.Methods: A RNA sequencing dataset (the training set) and a microarray dataset (the validation set) were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, respectively. Differentially expressed genes (DEGs) between metastatic and non-metastatic OS samples were identified in training set. Prognosis-related DEGs were screened and optimized by support vector machine (SVM) recursive feature elimination. A SVM classifier was built to classify metastatic and non-metastatic OS samples. Independent prognosic genes were extracted by multivariate regression analysis to build a risk score model followed by performance evaluation in two datasets by Kaplan-Meier (KM) analysis. Independent clinical prognostic indicators were identified followed by nomogram analysis. Finally, functional analyses of survival-related genes were conducted.Result: Totally, 345 DEGs and 45 prognosis-related genes were screened. A SVM classifier could distinguish metastatic and non-metastatic OS samples. An eight-gene signature was an independent prognostic marker and used for constructing a risk score model. The risk score model could separate OS samples into high and low risk groups in two datasets (training set: log-rank p < 0.01, C-index = 0.805; validation set: log-rank p < 0.01, C-index = 0.797). Tumor metastasis and RS model status were independent prognostic factors and nomogram model exhibited accurate survival prediction for OS. Additionally, functional analyses of survival-related genes indicated they were closely associated with immune responses and cytokine-cytokine receptor interaction pathway.Conclusion: An eight-gene predictive model and nomogram were developed to predict OS prognosis. [ABSTRACT FROM AUTHOR]

The study objects were to explore the correlation between the biological role of clock genes and clinical indicators in patients with osteosarcoma (OS). We acquired the clinical information and RNA sequencing data of OS samples from the TARGET database. The protein-protein interaction (PPI) network and expression correlation analysis of clock genes were performed. Then, the functional enrichment analysis of clock genes was analyzed. The survival analysis of clock genes in patients of OS was carried out by univariate cox regression, Kaplan-Meier (KM) curve and multivariate cox regression methods. Moreover, the spearmen correlation analysis was performed to explore the correlation between clock genes and DNA repair genes in patients with OS. The PPI network and expression correlation analysis of clock genes indicated that the clock genes were highly correlated with each other. The survival analysis of clock genes found that clock gene ARNTL is a protective factor for the prognosis of patients with OS. We found that ARNTL was positively related to DNA repair genes and was involved in the biological process of DNA damage repair in patients with OS. ARNTL may affect the prognosis and chemotherapy response of patients with OS by regulating DNA repair pathways. • The clock genes were highly correlated with each other. • The clock gene ARNTL is a protective factor for the prognosis of patients with OS. • ARNTL was involved in the biological process of DNA damage repair in patients with OS. [ABSTRACT FROM AUTHOR]