Exosomes miR-92a-3p from human exfoliated deciduous teeth inhibits periodontitis progression via the KLF4/PI3K/AKT pathway.

BACKGROUND: Periodontitis is a chronic inflammatory disease mediated by dysbiosis of the oral microflora, resulting in the destruction of periodontal tissue. Increasing evidence suggested that mesenchymal stem cell (MSCs) and exosomes derived from MSCs play a critical role in periodontal tissue regeneration. However, whether stem cells from exfoliated deciduous teeth (SHED)-secreted exosomes can improve the therapeutic potential of periodontitis is largely unknown. OBJECTIVE: Here, we aim to evaluate the effect of SHED-exosomes on inflammation, apoptosis and osteogenic differentiation in periodontitis. METHODS: The periodontitis cell model was constructed by stimulating periodontal ligament stem cells (PDLSCs) with lipopolysaccharide (LPS), and the periodontitis rats were established by ligation. RESULTS: First, we isolated exosomes from the SHED, and we figured out that exosomes secreted by SHED were enriched in miR-92a-3p and the exosomes enhanced proliferation and osteogenic differentiation and reduced apoptosis and inflammatory responses in PDLSCs. In addition, we found that SHED-exosomes alleviated inflammatory effect and elevated the expression of osteogenic-related genes in periodontitis rat model. Moreover, miR-92a-3p targeted downstream Krüppel-Like Transcription Factor 4 (KLF4) and regulated the PI3K/AKT pathway. Finally, our data indicated that upregulation of KLF4 or activation of PI3K/AKT by 740Y-P counteracted the inhibitory effect of SHED-exosomes on periodontitis progression. CONCLUSION: Taken together, our finding revealed that exosomal miR-92a-3p derived from SHED contributed to the alleviation of periodontitis development and progression through inactivating the KLF4/PI3K/AKT signaling pathway, which may provide a potential target for the treatment of periodontitis.

Neuropeptides as the Shared Genetic Crosstalks Linking Periodontitis and Major Depression Disorder.

BACKGROUND: The aim of this study was at investigating the association between major depressive disorder (MDD) and periodontitis based on crosstalk genes and neuropeptides. METHODS: Datasets for periodontitis (GSE10334, GSE16134, and GSE23586) and MDD (GSE38206 and GSE39653) were downloaded from GEO. Following batch correction, a differential expression analysis was applied (MDD: ∣log2FC | >0 and periodontitis ∣log2FC | ≥0.5, p < 0.05). The neuropeptide data were downloaded from NeuroPep and NeuroPedia. Intersected genes were potential crosstalk genes. The correlation between neuropeptides and crosstalk genes in MDD and periodontitis was analyzed with Pearson correlation coefficient. Subsequently, regression analysis was performed to calculate the differentially regulated link. Cytoscape was used to map the pathways of crosstalk genes and neuropeptides and to construct the protein-protein interaction network. Lasso regression was applied to screen neuropeptides, whereby boxplots were created, and receiver operating curve (ROC) analysis was conducted. RESULTS: The MDD dataset contained 30 case and 33 control samples, and the periodontitis dataset contained 430 case and 139 control samples. 35 crosstalk genes were obtained. A total of 102 neuropeptides were extracted from the database, which were not differentially expressed in MDD and periodontitis and had no intersection with crosstalk genes. Through lasso regression, 9 neuropeptides in MDD and 43 neuropeptides in periodontitis were obtained. Four intersected neuropeptide genes were obtained, i.e., ADM, IGF2, PDYN, and RETN. The results of ROC analysis showed that IGF2 was highly predictive in MDD and periodontitis. ADM was better than the other three genes in predicting MDD disease. A total of 13 crosstalk genes were differentially coexpressed with four neuropeptides, whereby FOSB was highly expressed in MDD and periodontitis. CONCLUSION: The neuropeptide genes ADM, IGF2, PDYN, and RETN were intersected between periodontitis and MDD, and FOSB was a crosstalk gene related to these neuropeptides on the transcriptomic level. These results are a basis for future research in the field, needing further validation.

Ferroptosis-Related Long Non-Coding RNA Signature Contributes to the Prediction of Prognosis Outcomes in Head and Neck Squamous Cell Carcinomas.

Background: Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor, which makes the prognosis prediction challenging. Ferroptosis is an iron-dependent form of non-apoptotic regulated cell death, which could affect cancer development. However, the prognostic value of ferroptosis-related long non-coding RNA (lncRNA) in HNSCC is still limited. Methods: In the current study, we employed the DESeq2 method to characterize the differentially expressed ferroptosis-related genes (FEGs) between cancer and normal samples. Next, the FEG-related lncRNAs (FElncRNAs) were identified using Spearman's correlation analysis and multiple permutation hypotheses. Subsequently, LASSO and stepwise multivariate Cox regression analyses were undertaken to recognize the prognosis-related FElncRNA signature (PFLS) and risk scores. Results: Herein, we first identified 60 dysregulated FEGs and their co-expressed FElncRNAs in HNSCC. Then, we recognized a set of six FElncRNAs PFLS (SLCO4A1-AS1, C1RL-AS1, PCED1B-AS1, HOXB-AS3, MIR9-3HG, and SFTA1P) for predicting patients' prognostic risks and survival outcomes. We also assessed the efficiency of PFLS in the test set and an external validation cohort. Further parsing of the tumor immune microenvironment showed the PFLS was closely associated with immune cell infiltration abundances. Notably, the low-risk group of the PFLS showed a higher MHC score and cytolytic activity (CYT) score than the high-risk group, implying the low-risk group may have greater tumor surveillance and killing ability. In addition, we observed that the expression levels of two immune checkpoints (ICPs), i.e., programmed cell death protein 1 (PD-1) and programmed cell death 1 ligand 1 (PD-L1), showed significant associations with patients' risk score, prompting the role of the PFLS in ICP blockade therapy. Finally, we also constructed a drug-PFLS network to reinforce the clinical utilities of the PFLS. Conclusion: In summary, our study indicated that FElncRNAs played an important role in HNSCC survival prediction. Identification of PFLS will contribute to the development of novel anticancer therapeutic strategies.