Characterization of the gut microbiota and fecal metabolome in the osteosarcoma mouse model.

Previous studies have reported the correlation between gut microbiota (GM), GM-derived metabolites, and various intestinal and extra-intestinal cancers. However, limited studies have investigated the correlation between GM, GM-derived metabolites, and osteosarcoma (OS). This study successfully established a female BALB/c nude mouse model of OS. Mice (n = 14) were divided into the following two groups (n = 7/group): OS group named OG, injected with Saos-2 OS cells; normal control group named NCG, injected with Matrigel. The GM composition and metabolites were characterized using 16S rDNA sequencing and untargeted metabolomics, respectively. Bioinformatics analysis revealed that amino acid metabolism was dysregulated in OS. The abundances of bone metabolism-related genera Alloprevotella, Rikenellaceae_RC9_gut_group, and Muribaculum were correlated with amino acid metabolism, especially histidine metabolism. These findings suggest the correlation between GM, GM-derived metabolites, and OS pathogenesis. Clinical significance: The currently used standard therapeutic strategies for OS, including surgery, chemotherapy, and radiation, are not efficacious. The findings of this study provided novel insights for developing therapeutic, diagnostic, and prognostic strategies for OS.

MiR-134-5p inhibits the malignant phenotypes of osteosarcoma via ITGB1/MMP2/PI3K/Akt pathway.

Micro RNAs (miRs) have been implicated in various tumorigenic processes. Osteosarcoma (OS) is a primary bone malignancy seen in adolescents. However, the mechanism of miRs in OS has not been fully demonstrated yet. Here, miR-134-5p was found to inhibit OS progression and was also expressed at significantly lower levels in OS tissues and cells relative to normal controls. miR-134-5p was found to reduce vasculogenic mimicry, proliferation, invasion, and migration of OS cells, with miR-134-5p knockdown having the opposite effects. Mechanistically, miR-134-5p inhibited expression of the ITGB1/MMP2/PI3K/Akt axis, thus reducing the malignant features of OS cells. In summary, miR-134-5p reduced OS tumorigenesis by modulation of the ITGB1/MMP2/PI3K/Akt axis, suggesting the potential for using miR-134-5p as a target for treating OS.

Cisplatin and doxorubicin chemotherapy alters gut microbiota in a murine osteosarcoma model.

The gut microbiota is closely associated with tumor progression and treatment in a variety of cancers. However, the alteration of the gut microbiota during the progression and chemotherapy of osteosarcoma remains poorly understood. This study aimed to explore the relationship between dysbiosis in the gut microbiota during osteosarcoma growth and chemotherapy treatment. We used BALB/c nude mice to establish osteosarcoma xenograft tumor models and administered cisplatin (CDDP) or doxorubicin (DOX) intraperitonially once every 2 days for a total of 5 times to establish effective chemotherapy models. Fecal samples were collected and processed for 16S rRNA sequencing to analyze the composition of the gut microbiota. We observed that the abundances of Colidextribacter, Lachnospiraceae_NK4A136_group, Lachnospiraceae_UCG-010, Lachnospiraceae_UCG-006, and Lachnoclostridium decreased, and the abundances of Alloprevotella and Enterorhabdus increased in the osteosarcoma mouse model group compared to those in the control group. In addition, genera, such as Lachnoclostridium and Faecalibacterium were more abundant in chemotherapy-treated mice than those in saline-treated mice. Additionally, we observed that alterations in some genera, including Lachnoclostridium and Colidextribacter in the osteosarcoma animal model group returned to normal after CDDP or DOX treatment. Furthermore, the function of the gut microbiota was inferred through PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), which indicated that metabolism-related microbiota was highly enriched and significantly different in each group. These results indicate correlations between dysbiosis of the gut microbiota and osteosarcoma growth and chemotherapy treatment with CDDP or DOX and may provide novel avenues for the development of potential adjuvant therapies.

Transcriptomics and metabolomics reveal changes in the regulatory mechanisms of osteosarcoma under different culture methods in vitro.

BACKGROUND: Recently, increasing attention has been drawn to the impact of the tumor microenvironment (TME) on the occurrence and progression of malignant tumors. A variety of 3D culture techniques have been used to simulate TME in vitro. The purpose of this study was to reveal the differences in transcriptional and metabolic levels between osteosarcoma (OS) 2D cells, 3D cells, 3D cell-printed tissue, isolated tissue, and transplanted tumor tissue in vivo. METHODS: We cultured the OS Saos-2 cell line under different culture methods as 2D cells, 3D cells, 3D cell-printed tissue and isolated tissue for 14 days and transplanted tumors in vivo as a control group. Through transcriptomic and metabonomic analyses, we determined the changes in gene expression and metabolites in OS tissues under different culture methods. RESULTS: At the transcriptional level, 166 differentially expressed genes were found, including the SMAD family, ID family, BMP family and other related genes, and they were enriched in the TGF-ß signaling pathway, complement and coagulation cascades, signaling pathways regulating pluripotency of stem cells, Hippo signaling pathway, ferroptosis, cGMP-PKG signaling pathway and other pathways. At the metabolic level, 362 metabolites were significantly changed and enriched in metabolic pathways such as the Fc Epsilon RI signaling pathway, histidine metabolism, primary bile acid biosynthesis, steroid biosynthesis, protein digestion and absorption, ferroptosis, and arachidonic acid metabolism. After integrating the transcriptome and metabolomics data, it was found that 44 metabolic pathways were changed, and the significantly enriched pathways were ferroptosis and pyrimidine metabolism. CONCLUSION: Different culture methods affect the gene expression and metabolite generation of OS Saos-2 cells. Moreover, the cell and tissue culture method in vitro cannot completely simulate TME in vivo, and the ferroptosis and pyrimidine metabolism pathways mediate the functional changes of OS Saos-2 cells in different microenvironments.

Periostin promotes the proliferation and metastasis of osteosarcoma by increasing cell survival and activates the PI3K/Akt pathway.

BACKGROUND: Silencing of the periostin gene (POSTN) can inhibit the biological process of several different cancers, and this inhibition may be related to down-regulation of PI3K/AKT signaling. However, the effect of POSTN on the progression, proliferation, and invasion of osteosarcoma (OS) remain unclear. METHODS: We used the Gene Expression Omnibus (GEO) database to screen datasets on in situ OS and lung metastases to identify core genes and potential pathways. We used additional bioinformatics tools to identify protein-protein interactions (PPIs) and gene networks, and selected the top seven genes whose expression had the strongest correlations with other genes. RESULTS: The results indicated that POSTN was a major hub gene. Subsequent analysis of gene expression profiles showed that POSTN was highly expressed in 262 cases with sarcoma and expression was closely related to poor prognosis. We also performed enrichment analysis to identify differentially expressed genes and used real-time PCR, western blotting, and immunohistochemistry analyses to measure POSTN expression in cells and tissues. Transfection of a POSTN-shRNA plasmid into cultured OS cells (Saos-2) effectively inhibited the proliferation, invasion, and migration of these cells. Taken together, our results suggest that POSTN may play a role in promoting the proliferation and metastasis of OS by activation of the PI3K/Akt signaling pathway. CONCLUSIONS: Our results provide a preliminary characterization of the mechanism by which POSTN may regulate the migration and invasion of OS cells and also provide a theoretical basis for identifying biomarkers that have potential use for the diagnosis and treatment of OS.

A metabolism-related gene signature for predicting the prognosis in thyroid carcinoma.

Metabolic reprogramming is one of the cancer hallmarks, important for the survival of malignant cells. We investigated the prognostic value of genes associated with metabolism in thyroid carcinoma (THCA). A prognostic risk model of metabolism-related genes (MRGs) was built and tested based on datasets in The Cancer Genome Atlas (TCGA), with univariate Cox regression analysis, LASSO, and multivariate Cox regression analysis. We used Kaplan-Meier (KM) curves, time-dependent receiver operating characteristic curves (ROC), a nomogram, concordance index (C-index) and restricted mean survival (RMS) to assess the performance of the risk model, indicating the splendid predictive performance. We established a three-gene risk model related to metabolism, consisting of PAPSS2, ITPKA, and CYP1A1. The correlation analysis in patients with different risk statuses involved immune infiltration, mutation and therapeutic reaction. We also performed pan-cancer analyses of model genes to predict the mutational value in various cancers. Our metabolism-related risk model had a powerful predictive capability in the prognosis of THCA. This research will provide the fundamental data for further development of prognostic markers and individualized therapy in THCA.