Identification and Validation of a Potent Multi-miRNA Signature for Prediction of Prognosis of Osteosarcoma Patients

A glycometabolic gene signature associating with immune infiltration and chemosensitivity and predicting the prognosis of patients with osteosarcoma

Background

Accumulating evidence has suggested that glycometabolism plays an important role in the pathogenesis of tumorigenesis. However, few studies have investigated the prognostic values of glycometabolic genes in patients with osteosarcoma (OS). This study aimed to recognize and establish a glycometabolic gene signature to forecast the prognosis, and provide therapeutic options for patients with OS.

Methods

Univariate and multivariate Cox regression, LASSO Cox regression, overall survival analysis, receiver operating characteristic curve, and nomogram were adopted to develop the glycometabolic gene signature, and further evaluate the prognostic values of this signature. Functional analyses including Gene Ontology (GO), kyoto encyclopedia of genes and genomes analyses (KEGG), gene set enrichment analysis, single-sample gene set enrichment analysis (ssGSEA), and competing endogenous RNA (ceRNA) network, were used to explore the molecular mechanisms of OS and the correlation between immune infiltration and gene signature. Moreover, these prognostic genes were further validated by immunohistochemical staining.

Results

A total of four genes including PRKACB, SEPHS2, GPX7, and PFKFB3 were identified for constructing a glycometabolic gene signature which had a favorable performance in predicting the prognosis of patients with OS. Univariate and multivariate Cox regression analyses revealed that the risk score was an independent prognostic factor. Functional analyses indicated that multiple immune associated biological processes and pathways were enriched in the low-risk group, while 26 immunocytes were down-regulated in the high-risk group. The patients in high-risk group showed elevated sensitivity to doxorubicin. Furthermore, these prognostic genes could directly or indirectly interact with other 50 genes. A ceRNA regulatory network based on these prognostic genes was also constructed. The results of immunohistochemical staining showed that SEPHS2, GPX7, and PFKFB3 were differentially expressed between OS tissues and adjacent normal tissues.

Conclusion

The preset study constructed and validated a novel glycometabolic gene signature which could predict the prognosis of patients with OS, identify the degree of immune infiltration in tumor microenvironment, and provide guidance for the selection of chemotherapeutic drugs. These findings may shed new light on the investigation of molecular mechanisms and comprehensive treatments for OS.

Silencing circular RNA hsa_circABCC1 inhibits osteosarcoma progression through down-regulating HDAC4 via sponging miR-591

BACKGROUND

Circular RNA (circRNA) has been shown to play an important regulatory role in the development of various cancers, including osteosarcoma (OS). However, the role of circRNA ABCC1 (circABCC1) in OS was still poorly understood. The aim of our study was to investigate the role of circABCC1 in OS progression and its potential molecular mechanisms.

METHODS

The expression of circABCC1, microRNA-591 (miR-591) and histone deacetylase 4 (HDAC4) in OS tissues or cells was detected by quantitative real-time polymerase chain reaction (qRT-PCR) and western blot (WB) analyses. In vitro experiments, the viability, proliferation, apoptosis, migration, invasion and autophagy of U2OS and HOS cells were assessed in vitro using cell counting kit-8 (CCK-8) assay, 5-ethynyl-29-deoxyuridine (EdU) assay, flow cytometry (FCM) assay, transwell migration and invasion assays (transwell) and WB assay, respectively. Interactions between circABCC1 and miR-591, miR-591 and HDAC4 were confirmed using a dual luciferase reporter gene assay system. The oncogenic role of circABCC1 in OS in vivo was examined by establishing a tumor xenograft model.

RESULTS

CircABCC1 was significantly elevated in OS tissues (about 3.1-folds) and cells (U2OS (about 2.1-folds) and HOS (about 2.8-folds)) compared with the control (p < .05). Silencing of circABCC1 significantly reduced the viability and proliferation, promoted apoptosis, impaired migration and invasion, and increased autophagy of U2OS and HOS cells (p < .05). In addition, miR-591 was confirmed to be a target of circABCC1, exerting an opposite effect to circABCC1 (p < .05). MiR-591 attenuation in U2OS and HOS cells was able to reply to the inhibition of cell proliferation, migration and invasion as well as promotion of cell apoptosis and autophagy mediated by silencing circABCC1 (p < .05). HDAC4 was verified to be the target gene of miR-591 in U2OS and HOS cells and was regulated by the circABCC1/miR-591 axis (p < .05), and restoration of HDAC4 levels in U2OS and HOS cells was able to restore the altered cellular function caused by silencing circABCC1 (p < .05). In addition, knockdown of circABCC1 attenuated tumor growth in vivo (p < .05).

CONCLUSION

Silencing of circABCC1 inhibits osteosarcoma progression by attenuating HDAC4 expression through sponging miR-591.

Comprehensive analysis of a glycolysis and cholesterol synthesis-related genes signature for predicting prognosis and immune landscape in osteosarcoma

Background

Glycolysis and cholesterol synthesis are crucial in cancer metabolic reprogramming. The aim of this study was to identify a glycolysis and cholesterol synthesis-related genes (GCSRGs) signature for effective prognostic assessments of osteosarcoma patients.

Methods

Gene expression data and clinical information were obtained from GSE21257 and TARGET-OS datasets. Consistent clustering method was used to identify the GCSRGs-related subtypes. Univariate Cox regression and LASSO Cox regression analyses were used to construct the GCSRGs signature. The ssGSEA method was used to analyze the differences in immune cells infiltration. The pRRophetic R package was utilized to assess the drug sensitivity of different groups. Western blotting, cell viability assay, scratch assay and Transwell assay were used to perform cytological validation.

Results

Through bioinformatics analysis, patients diagnosed with osteosarcoma were classified into one of 4 subtypes (quiescent, glycolysis, cholesterol, and mixed subtypes), which differed significantly in terms of prognosis and tumor microenvironment. Weighted gene co-expression network analysis revealed that the modules strongly correlated with glycolysis and cholesterol synthesis were the midnight blue and the yellow modules, respectively. Both univariate and LASSO Cox regression analyses were conducted on screened module genes to identify 5 GCSRGs (RPS28, MCAM, EN1, TRAM2, and VEGFA) constituting a prognostic signature for osteosarcoma patients. The signature was an effective prognostic predictor, independent of clinical characteristics, as verified further via Kaplan-Meier analysis, ROC curve analysis, univariate and multivariate Cox regression analysis. Additionally, GCSRGs signature had strong correlation with drug sensitivity, immune checkpoints and immune cells infiltration. In cytological experiments, we selected TRAM2 as a representative gene to validate the validity of GCSRGs signature, which found that TRAM2 promoted the progression of osteosarcoma cells. Finally, at the pan-cancer level, TRAM2 had been correlated with overall survival, progression free survival, disease specific survival, tumor mutational burden, microsatellite instability, immune checkpoints and immune cells infiltration.

Conclusion

Therefore, we constructed a GCSRGs signature that efficiently predicted osteosarcoma patient prognosis and guided therapy.

Role of MicroRNAs in Human Osteosarcoma: Future Perspectives

Osteosarcoma (OS) is a rare form of cancer with high death rate but is one of the most frequent forms of bone cancer in children and adolescents. MiRNAs are small endogenous RNAs that regulate gene expression post-transcriptionally. The discovery of miRNAs could allow us to obtain an earlier diagnosis, predict prognosis and chemoresistance, and lead to the discovery of new treatments in different types of tumors, including OS. Despite the fact that there is currently only one clinical trial being carried out on a single miRNA for solid tumors, it is very probable that the number of clinical trials including miRNAs as prognostic and diagnostic biomarkers, as well as potential therapeutic targets, will increase in the near future. This review summarizes the different miRNAs related to OS and their possible therapeutic application.