Background Bone mesenchymal stem cells (BMSCs) have good osteogenic differentiation potential and have become ideal seed cells in bone tissue engineering. However, the osteogenic differentiation ability of BMSCs gradually weakens with age, and the regulatory mechanism is unclear. Method We conducted a bioinformatics analysis, dual-luciferase reporter (DLR) experiment, and RNA binding protein immunoprecipitation (RIP) to explore the hub genes that may affect BMSC functions. Results The expression level of long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (Malat1) was significantly higher in the BMSCs from elderly than younger mice, while miR-129-5p showed the opposite trend. The results of alkaline phosphatase staining, quantitative reverse transcription PCR and western blot experiments indicated that inhibiting the expression of Malat1 inhibits the osteogenic differentiation of BMSCs. This effect can be reversed by reducing the expression of miR-129-5p. Additionally, DLR and RIP experiments confirmed that Malat1 acts as a sponge for miR-129-5p. Conclusion Overall, our study findings indicated that lncRNA Malat1 may play a critical role in maintaining the osteoblast differentiation potential of BMSCs by sponging miR-129-5p.

Background: Autophagy, is a metabolic pathway that occurs in eukaryotic cells and regulated by autophagy-related genes (ARGs).The occurrence and development of many diseases are caused by abnormal autophagy. The purpose of this article is to explore the relationship between autophagy and prognosis of oral cancer, hoping to provide a new way for early diagnosis and guide doctors to make subsequent treatment decisions.Methods: Download the RNA seq and clinical features of 305 oral cancer and 30 non-tumor patients from The Cancer Genome Atlas (TCGA) dataset. Filtered out differential expression autophagy-related genes (ARGs),and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyzed these ARGs. Cox regression analysis filtered out the prognostic ARGs and constructed a risk score models for overall survival (OS) .Divided patients into high-risk and low-risk groups based on median risk score. Kaplan-Meier analyzed the overall survival (OS). Next, receiver operating characteristic (ROC) curve verified the predictive accuracy of the model. Furthermore, we performed stratification analyses to explore the relationship between the prognostic signature and clinicopathological variables. Lastly, we used another date set to verify the model. All data was processed by R (version 3.6.0) and perl (version5.18.4).Results: The K-M plot showed the overall survival rate of the high-risk group was lower than the low-risk group’s (P=2.216e−10). And Cox regression analysis suggested that the autophagy prognostic index was an independent prognostic factor. Further more, the ARGs prognostic model was confirmed in dataset of GSE65858.Conclusion: This study constructed an autophagy-related signature of oral cancer, which can foresee the prognosis of patients. It will open up new prospects for fight against oral cancer.

Background: Oral squamous cell carcinoma (OSCC) is a life-threatening disease that emerged as a major international health concern, associated with poor prognosis and the absence of specific biomarkers. Studies have shown that the ferroptosis-related genes (FRGs) can be used as tumor prognostic markers. However, FRGs’ prognostic value in OSCC needs further exploration. Our aim was to construct a novel FRG signature for overall survival (OS) prediction in OSCC patients and explore its role in immunotherapy.Methods: In our study, gene expression profile and clinical data of OSCC patients were collected from a public domain. FRGs were available from the FerrDb database. We performed univariate and multivariate Cox regression analyses to construct a multigene signature. The Kaplan-Meier (K-M) and receiver operating characteristic (ROC) methods were utilized to test the effectiveness of the FRG signature. A differential gene expression analysis was performed by the limma R package, followed by functional enrichment analyses. CIBERSORT was applied to analyze the tumor microenvironment (TME). Finally, the expression of human leukocyte antigen (HLA) and immune checkpoint molecules were analyzed to confirm the sensitivity of immunotherapy.Results: A total of 103 FRGs, expressed in OSCC (FRGs-OSCC), were identified from the two datasets by the Venn analysis. The Cox regression analysis identified 5 FRGs-OSCC that were associated with overall survival (all P < 0.01). The FRGs-OSCC risk model was established to classify patients into high risk and low risk groups. Compared with the low risk group, the survival time of the high-risk group was significantly reduced (P < 0.001). According to the multivariate Cox regression analyses, the risk score acted as an independent predictor for OS (HR > 1, P < 0.001). The accuracy of the FRGs-OSCC risk predictive model was confirmed by ROC curve analysis. The results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed significant enrichment of immune-related pathways, and a difference in tumor microenvironment between the two groups. The low risk group had the characteristics of higher expression of HLA and immune checkpoints (IDO1, LAG3, PDCD1 and TIGHT), a lower tumor purity and a higher infiltration of immune cells, indicating a more sensitive response to immunotherapy.Conclusions: The novel FRGs-OSCC risk score system can be used to predict OSCC prognosis. Ferroptosis targeting may be a therapeutic option for OSCC.