Oral health-related quality of life in patients with osteoarthritis of the temporomandibular joint-Results of a systematic review.

OBJECTIVES: The aim of this systematic review was to assess the oral health-related quality of life (OHRQoL) of patients with osteoarthritis (OA) of the temporomandibular joint (TMJ). METHODS: This systematic literature search applied the search terms "oral health-related quality of life AND osteoarthritis of jaw OR arthritis of temporomandibular joint AND oral health-related quality of life" in PubMed, Medline, Web of Science and Scopus. Eligibility criteria were publication until 31 August 2021, examination of children or adults with OA of TMJ, reporting of any OHRQoL measurement and a full text in English language. Two different, independent and experienced reviewers performed this systematic literature search. The analysis of respective data was qualitative. For quality appraisal, the available checklist from the Agency for Healthcare Research and Quality (AHRQ) was applied. RESULTS: Out of 102 findings, eight studies were included in qualitative analysis. Seven clinical investigations were performed in adults aged between 34 and 43 years. The other included study was performed on children. The quality of two studies was moderate, and six studies were evaluated as of high quality. Most studies applied the 14-item short form of the oral health impact profile (OHIP 14) for assessment of OHRQoL. OHIP 14 ranged between 9.24 and 38.86 points in means of sum score. Comparison with healthy individuals revealed worse OHRQoL of OA patients in two studies. Associations between OHRQoL with either oral health, general quality of life or disease-related parameters were rarely reported and heterogeneous. Five of the included studies reported subscales of OHIP 14, showing an impairment in all subscales. CONCLUSIONS: There are hints that patients with OA of the TMJ show a reduced OHRQoL. More studies are needed, especially regarding oral health, disease-related parameters and pain intensity and its potential influence on OHRQoL.

Evaluation of ICAM-1 and VCAM-1 Gene Polymorphisms in Patients with Periodontal Disease.

BACKGROUND We aimed to investigate the potential genetic relationships between the polymorphisms of gene rs5498 ICAM-1 and rs1041163 VCAM-1 and chronic periodontitis in a Chinese population within Heilongjiang. MATERIAL AND METHODS Genomic DNA was extracted from oral mucosa cells of 584 periodontal patients and 182 healthy individuals. Genotyping of the rs5498 ICAM-1 and rs1041163 VCAM-1 gene polymorphisms was performed with the Multiplex SNaPshot technique. RESULTS Statistically significant associations were identified between the chronic periodontal patients and the controls in the gene polymorphisms of rs5498 ICAM-1 (P=0.007) and rs1041163 VCAM-1 (P=0.029). The distribution of rs5498 (P=0.029) and rs1041163 (P=0.049) differed significantly across the mild, moderate, and severe groups of periodontitis. CONCLUSIONS Our findings indicate that ICAM-1 rs5498 and VCAM-1 rs1041163 polymorphisms contribute to chronic periodontitis, and ICAM-1 rs5498 and VCAM-1 rs1041163 gene polymorphisms might be associated with periodontitis severity in the Heilongjiang Chinese population. Further studies should be conducted to determine whether these polymorphisms could be used as biomarkers of periodontitis.

The antitumor effects of herbal medicine Triphala on oral cancer by inactivating PI3K/Akt signaling pathway: based on the network pharmacology, molecular docking, in vitro and in vivo experimental validation.

BACKGROUND: This research aimed to investigate the anti-tumor effects and underlying genetic mechanisms of herbal medicine Triphala (TRP) in oral squamous cell carcinoma (OSCC). METHODS: The target genes of Triphala (TRP) in oral squamous cell carcinoma (OSCC) were identified, and subsequent functional enrichment analysis was conducted to determine the enriched signaling pathways. Based on these genes, a protein-protein interaction network was constructed to identify the top 10 genes with the highest degree. Genes deregulated in OSCC tumor samples were identified to be hub genes among the top 10 genes. In vitro experiments were performed to investigate the influence of TRP extracts on the cell metabolic activity, migration, invasion, apoptosis, and proliferation of two OSCC cell lines (CAL-27 and SCC-9). The functional rescue assay was conducted to investigate the effect of applying the inhibitor and activator of an enriched pathway on the phenotypes of cancer cells. In addition, the zebrafish xenograft tumor model was established to investigate the influence of TRP extracts on tumor growth and metastasis in vivo. RESULTS: The target genes of TRP in OSCC were prominently enriched in the PI3K-Akt signaling pathway, with the identification of five hub genes (JUN, EGFR, ESR1, RELA, and AKT1). TRP extracts significantly inhibited cell metabolic activity, migration, invasion, and proliferation and promoted cell apoptosis in OSCC cells. Notably, the application of TRP extracts exhibited the capacity to downregulate mRNA and phosphorylated protein levels of AKT1 and ESR1, while concomitantly inducing upregulation of mRNA and phosphorylated protein levels in the remaining three hub genes (EGFR, JUN, and RELA). The functional rescue assay demonstrated that the co-administration of TRP and the PI3K activator 740Y-P effectively reversed the impact of TRP on the phenotypes of OSCC cells. Conversely, the combination of TRP and the PI3K inhibitor LY294002 further enhanced the effect of TRP on the phenotypes of OSCC cells. Remarkably, treatment with TRP in zebrafish xenograft models demonstrated a significant reduction in both tumor growth and metastatic spread. CONCLUSIONS: Triphala exerted significant inhibitory effects on cell metabolic activity, migration, invasion, and proliferation in OSCC cell lines, accompanied by the induction of apoptosis, which was mediated through the inactivation of the PI3K/Akt pathway.

Combined computational analysis and cytology show limited depth osteogenic effect on bone defects in negative pressure wound therapy.

Background: The treatment of bone defects remains a clinical challenge. The effect of negative pressure wound therapy (NPWT) on osteogenesis in bone defects has been recognized; however, bone marrow fluid dynamics under negative pressure (NP) remain unknown. In this study, we aimed to examine the marrow fluid mechanics within trabeculae by computational fluid dynamics (CFD), and to verify osteogenic gene expression, osteogenic differentiation to investigate the osteogenic depth under NP. Methods: The human femoral head is scanned using micro-CT to segment the volume of interest (VOI) trabeculae. The VOI trabeculae CFD model simulating the bone marrow cavity is developed by combining the Hypermesh and ANSYS software. The effect of trabecular anisotropy is investigated, and bone regeneration effects are simulated under NP scales of -80, -120, -160, and -200 mmHg. The working distance (WD) is proposed to describe the suction depth of the NP. Finally, gene sequence analysis, cytological experiments including bone mesenchymal stem cells (BMSCs) proliferation and osteogenic differentiation are conducted after the BMSCs are cultured under the same NP scale. Results: The pressure, shear stress on trabeculae, and marrow fluid velocity decrease exponentially with an increase in WD. The hydromechanics of fluid at any WD inside the marrow cavity can be theoretically quantified. The NP scale significantly affects the fluid properties, especially those fluid close to the NP source; however, the effect of the NP scale become marginal as WD deepens. Anisotropy of trabecular structure coupled with the anisotropic hydrodynamic behavior of bone marrow; An NP of -120 mmHg demonstrates the majority of bone formation-related genes, as well as the most effective proliferation and osteogenic differentiation of BMSCs compared to the other NP scales. Conclusion: An NP of -120 mmHg may have the optimal activated ability to promote osteogenesis, but the effective WD may be limited to a certain depth. These findings help improve the understanding of fluid mechanisms behind NPWT in treating bone defects.

Identification of Key Pyroptosis-Related Genes and Distinct Pyroptosis-Related Clusters in Periodontitis.

Aim: This study aims to identify pyroptosis-related genes (PRGs), their functional immune characteristics, and distinct pyroptosis-related clusters in periodontitis. Methods: Differentially expressed (DE)-PRGs were determined by merging the expression profiles of GSE10334, GSE16134, and PRGs obtained from previous literatures and Molecular Signatures Database (MSigDB). Least absolute shrinkage and selection operator (LASSO) regression was applied to screen the prognostic PRGs and develop a prognostic model. Consensus clustering was applied to determine the pyroptosis-related clusters. Functional analysis and single-sample gene set enrichment analysis (ssGSEA) were performed to explore the biological characteristics and immune activities of the clusters. The hub pyroptosis-related modules were defined using weighted correlation network analysis (WGCNA). Results: Of the 26 periodontitis-related DE-PRGs, the highest positive relevance was for High-Mobility Group Box 1 (HMGB1) and SR-Related CTD Associated Factor 11 (SCAF11). A 14-PRG-based signature was developed through the LASSO model. In addition, three pyroptosis-related clusters were obtained based on the 14 prognostic PRGs. Caspase 3 (CASP3), Granzyme B (GZMB), Interleukin 1 Alpha (IL1A), IL1Beta (B), IL6, Phospholipase C Gamma 1 (PLCG1) and PYD And CARD Domain Containing (PYCARD) were dysregulated in the three clusters. Distinct biological functions and immune activities, including human leukocyte antigen (HLA) gene expression, immune cell infiltration, and immune pathway activities, were identified in the three pyroptosis-related clusters of periodontitis. Furthermore, the pink module associated with endoplasmic stress-related functions was found to be correlated with cluster 2 and was suggested as the hub pyroptosis-related module. Conclusion: The study identified 14 key pyroptosis-related genes, three distinct pyroptosis-related clusters, and one pyroptosis-related gene module describing several molecular aspects of pyroptosis in the pathogenesis and immune micro-environment regulation of periodontitis and also highlighted functional heterogeneity in pyroptosis-related mechanisms.

Implications of Human Antimicrobial Peptide Defensin Beta-1 in Clinical Oral Squamous Cell Carcinoma Patients via an Integrated Bioinformatics Approach.

BACKGROUND: The human antimicrobial peptide defensin beta 1 (DEFB1) has been found to play antimicrobial and anti-inflammatory roles in oral diseases; however, its tumor-regulating role in oral squamous cell carcinoma (OSCC) has not yet been researched by using an integrative bioinformatics approach. OBJECTIVE: To investigate the regulating mechanisms of the DEFB1 gene in OSCC in terms of its expression patterns, prognostic values, biological functions, and implication for tumor immunity. METHODS: The DEFB1 gene expression pattern and regulatory involvement in OSCC were investigated using publically accessible data from TCGA database. R software tools and public web servers were utilized to conduct statistical analysis of data from cancer and noncancerous samples. RESULTS: DEFB1 was found to be significantly downregulated in OSCC tumor samples compared with healthy control oral samples. The DEFB1 gene was found associated with the prognostic outcomes of OSCC, and its upregulation represented better survival outcome. Gene set enrichment analysis (GSEA) results showed that DEFB1-significantly correlated genes were mainly enriched in four signaling pathways mediating the antitumor role of DEFB1 in OSCC, including extracellular matrix-related pathway, RTK/PI3K/AKT/mTOR pathway, keratinization, and cytokine-related pathway. The gene-gene interaction network showed that DEFB1 was closely correlated with several genes, for example, CCR6 (C-C motif chemokine receptor 6), CXCL1 (C-X-C motif chemokine ligand 1), MAP4K2 (mitogen-activated protein kinase kinase kinase kinase 2), PTGER3 (prostaglandin E receptor 3), and MMP7 (matrix metallopeptidase 7). Moreover, DEFB1 was found to be involved in the tumor immunity of OSCC by regulating the function of tumor macrophage cells, mast cells, T cells, and NK cells. CONCLUSIONS: Given the dysregulation, prognostic value, and tumor progression-related biological pathway alteration, indicating the tumor immune-modulatory role of DEFB1 in OSCC, the DEFB1 gene should be regarded as a potential therapeutic target for treating oral cancer.

Identifying crosstalk genetic biomarkers linking a neurodegenerative disease, Parkinson's disease, and periodontitis using integrated bioinformatics analyses.

Objective: To identify the genetic linkage mechanisms underlying Parkinson's disease (PD) and periodontitis, and explore the role of immunology in the crosstalk between both these diseases. Methods: The gene expression omnibus (GEO) datasets associated with whole blood tissue of PD patients and gingival tissue of periodontitis patients were obtained. Then, differential expression analysis was performed to identify the differentially expressed genes (DEGs) deregulated in both diseases, which were defined as crosstalk genes. Inflammatory response-related genes (IRRGs) were downloaded from the MSigDB database and used for dividing case samples of both diseases into different clusters using k-means cluster analysis. Feature selection was performed using the LASSO model. Thus, the hub crosstalk genes were identified. Next, the crosstalk IRRGs were selected and Pearson correlation coefficient analysis was applied to investigate the correlation between hub crosstalk genes and hub IRRGs. Additionally, immune infiltration analysis was performed to examine the enrichment of immune cells in both diseases. The correlation between hub crosstalk genes and highly enriched immune cells was also investigated. Results: Overall, 37 crosstalk genes were found to be overlapping between the PD-associated DEGs and periodontitis-associated DEGs. Using clustering analysis, the most optimal clustering effects were obtained for periodontitis and PD when k = 2 and k = 3, respectively. Using the LASSO feature selection, five hub crosstalk genes, namely, FMNL1, MANSC1, PLAUR, RNASE6, and TCIRG1, were identified. In periodontitis, MANSC1 was negatively correlated and the other four hub crosstalk genes (FMNL1, PLAUR, RNASE6, and TCIRG1) were positively correlated with five hub IRRGs, namely, AQP9, C5AR1, CD14, CSF3R, and PLAUR. In PD, all five hub crosstalk genes were positively correlated with all five hub IRRGs. Additionally, RNASE6 was highly correlated with myeloid-derived suppressor cells (MDSCs) in periodontitis, and MANSC1 was highly correlated with plasmacytoid dendritic cells in PD. Conclusion: Five genes (i.e., FMNL1, MANSC1, PLAUR, RNASE6, and TCIRG1) were identified as crosstalk biomarkers linking PD and periodontitis. The significant correlation between these crosstalk genes and immune cells strongly suggests the involvement of immunology in linking both diseases.

Role of enhancer of zeste homolog 2 in osteoclast formation and periodontitis development by downregulating microRNA-101-regulated VCAM-1.

The enhancer of zeste homolog 2 (EZH2) represents a potential target for periodontitis treatment; however, its role in the development of periodontitis remains unclear. The current study aimed to elucidate the role of EZH2 in osteoclasts (OCs) growth as well as the mechanism underpinning the related process. The potential interaction among EZH2, microRNA-101 (miR-101), and vascular cell adhesion molecule 1 (VCAM-1) was evaluated using chromatin immunoprecipitation and dual-luciferase reporter gene assay. The expressions of EZH2 and miR-101 in OCs were examined by Western blot analysis and reverse transcription squantitative polymerase chain reaction. Loss- and gain-function assays were then performed to determine the role of EZH2/miR-101/VCAM-1 in periodontitis and OCs proliferation, followed by OC growth and proliferation detected using tartrate resistant acid phosphatase (TRAP) and 5-ethynyl-2'-deoxyuridine staining. Enzyme-linked immunoassay was conducted to determine the expression of interleukin 1ß (IL-1ß) and tumor necrosis factor-α (TNF-α). A periodontitis rat model was established to investigate the effect of EZH2 and VCAM-1 in vivo. EZH2 was overexpressed, while miR-101 was downregulated in the OCs of periodontitis. Silencing of EZH2, VCAM-1 repression, or miR-101 elevation suppressed the growth and proliferation of OC while acting to encumber the release of IL-1ß and TNF-α. EZH2 negatively targeted miR-101, while miR-101 negatively targeted VCAM-1. Moreover, silencing of EZH2 or VCAM-1 was observed to attenuate periodontitis which was evidenced by an increase in BMD, BV/TV, and BS/BV as well as reduction in TRAP and cathepsin K in vivo. Taken together, the key findings of the current study demonstrate that EZH2 knockdown inhibited OC formation by elevating the expression of miR-101 via suppression of VCAM-1, ultimately attenuating periodontitis.

Oral Health-Related Quality of Life in Patients With Chronic Respiratory Diseases-Results of a Systematic Review.

Background: This systematic review evaluates the oral health-related quality of life (OHRQoL) of patients with chronic respiratory diseases. Methods: A systematic literature search was performed based on the PubMed, Medline, Web of Science, and Scopus, using the search terms: "oral health-related quality of life" and "respiratory disease" or "lung" and "oral health-related quality of life." Full-text articles published until June 30, 2021 and reporting any OHRQoL measurement in children or adults with a chronic respiratory disease or condition were included and analyzed qualitatively. Results: A total of seven out of 44 studies were included, of which four studies examined adults and three studies investigated children. The respective diseases were chronic obstructive pulmonary disease (COPD) (n = 2), sleep apnea (n = 2), severe asthma (n = 1), cystic fibrosis (n = 1), and lung transplantation (n = 1). Four studies confirmed a worse OHRQoL in the respiratory diseased group compared to healthy controls. The overall OHRQoL was reduced in the included studies. Oral health, health-related quality of life, and disease-related parameters were rarely examined with regard to OHRQoL. Conclusion: Patients with chronic respiratory diseases show a reduced OHRQoL. Oral health should be fostered in these individuals to support their OHRQoL.

Deep Learning Reveals Key Immunosuppression Genes and Distinct Immunotypes in Periodontitis.

BACKGROUND: Periodontitis is a chronic immuno-inflammatory disease characterized by inflammatory destruction of tooth-supporting tissues. Its pathogenesis involves a dysregulated local host immune response that is ineffective in combating microbial challenges. An integrated investigation of genes involved in mediating immune response suppression in periodontitis, based on multiple studies, can reveal genes pivotal to periodontitis pathogenesis. Here, we aimed to apply a deep learning (DL)-based autoencoder (AE) for predicting immunosuppression genes involved in periodontitis by integrating multiples omics datasets. METHODS: Two periodontitis-related GEO transcriptomic datasets (GSE16134 and GSE10334) and immunosuppression genes identified from DisGeNET and HisgAtlas were included. Immunosuppression genes related to periodontitis in GSE16134 were used as input to build an AE, to identify the top disease-representative immunosuppression gene features. Using K-means clustering and ANOVA, immune subtype labels were assigned to disease samples and a support vector machine (SVM) classifier was constructed. This classifier was applied to a validation set (Immunosuppression genes related to periodontitis in GSE10334) for predicting sample labels, evaluating the accuracy of the AE. In addition, differentially expressed genes (DEGs), signaling pathways, and transcription factors (TFs) involved in immunosuppression and periodontitis were determined with an array of bioinformatics analysis. Shared DEGs common to DEGs differentiating periodontitis from controls and those differentiating the immune subtypes were considered as the key immunosuppression genes in periodontitis. RESULTS: We produced representative molecular features and identified two immune subtypes in periodontitis using an AE. Two subtypes were also predicted in the validation set with the SVM classifier. Three "master" immunosuppression genes, PECAM1, FCGR3A, and FOS were identified as candidates pivotal to immunosuppressive mechanisms in periodontitis. Six transcription factors, NFKB1, FOS, JUN, HIF1A, STAT5B, and STAT4, were identified as central to the TFs-DEGs interaction network. The two immune subtypes were distinct in terms of their regulating pathways. CONCLUSION: This study applied a DL-based AE for the first time to identify immune subtypes of periodontitis and pivotal immunosuppression genes that discriminated periodontitis from the healthy. Key signaling pathways and TF-target DEGs that putatively mediate immune suppression in periodontitis were identified. PECAM1, FCGR3A, and FOS emerged as high-value biomarkers and candidate therapeutic targets for periodontitis.

The Genetic and Epigenetic Mechanisms Involved in Irreversible Pulp Neural Inflammation.

AIM: To identify the critical genetic and epigenetic biomarkers by constructing the long noncoding RNA- (lncRNA-) related competing endogenous RNA (ceRNA) network involved in irreversible pulp neural inflammation (pulpitis). MATERIALS AND METHODS: The public datasets regarding irreversible pulpitis were downloaded from the gene expression omnibus (GEO) database. The differential expression analysis was performed to identify the differentially expressed genes (DEGs) and DElncRNAs. Functional enrichment analysis was performed to explore the biological processes and signaling pathways enriched by DEGs. By performing a weighted gene coexpression network analysis (WGCNA), the significant gene modules in each dataset were identified. Most importantly, DElncRNA-DEmRNA regulatory network and DElncRNA-associated ceRNA network were constructed. A transcription factor- (TF-) DEmRNA network was built to identify the critical TFs involved in pulpitis. RESULT: Two datasets (GSE92681 and GSE77459) were selected for analysis. DEGs involved in pulpitis were significantly enriched in seven signaling pathways (i.e., NOD-like receptor (NLR), Toll-like receptor (TLR), NF-kappa B, tumor necrosis factor (TNF), cell adhesion molecules (CAMs), chemokine, and cytokine-cytokine receptor interaction pathways). The ceRNA regulatory relationships were established consisting of three genes (i.e., LCP1, EZH2, and NR4A1), five miRNAs (i.e., miR-340-5p, miR-4731-5p, miR-27a-3p, miR-34a-5p, and miR-766-5p), and three lncRNAs (i.e., XIST, MIR155HG, and LINC00630). Six transcription factors (i.e., GATA2, ETS1, FOXP3, STAT1, FOS, and JUN) were identified to play pivotal roles in pulpitis. CONCLUSION: This paper demonstrates the genetic and epigenetic mechanisms of irreversible pulpitis by revealing the ceRNA network. The biomarkers identified could provide research direction for the application of genetically modified stem cells in endodontic regeneration.

Protective Effect of Triphala against Oxidative Stress-Induced Neurotoxicity.

BACKGROUND: Oxidative stress is implicated in the progression of many neurological diseases, which could be induced by various chemicals, such as hydrogen peroxide (H2O2) and acrylamide. Triphala is a well-recognized Ayurvedic medicine that possesses different therapeutic properties (e.g., antihistamine, antioxidant, anticancer, anti-inflammatory, antibacterial, and anticariogenic effects). However, little information is available regarding the neuroprotective effect of Triphala on oxidative stress. MATERIALS AND METHODS: An in vitro H2O2-induced SH-SY5Y cell model and an in vivo acrylamide-induced zebrafish model were established. Cell viability, apoptosis, and proliferation were examined by MTT assay, ELISA, and flow cytometric analysis, respectively. The molecular mechanism underlying the antioxidant activity of Triphala against H2O2 was investigated dose dependently by Western blotting. The in vivo neuroprotective effect of Triphala on acrylamide-induced oxidative injury in Danio rerio was determined using immunofluorescence staining. RESULTS: The results indicated that Triphala plays a neuroprotective role against H2O2 toxicity in inhibiting cell apoptosis and promoting cell proliferation. Furthermore, Triphala pretreatment suppressed the phosphorylation of the mitogen-activated protein kinase (MARK) signal pathway (p-Erk1/2, p-JNK1/2, and p-p38), whereas it restored the activities of antioxidant enzymes (superoxide dismutase 1 (SOD1) and catalase) in the H2O2-treated SH-SY5Y cells. Consistently, similar protective effects of Triphala were observed in declining neuroapoptosis and scavenging free radicals in the zebrafish central neural system, possessing a critical neuroprotective property against acrylamide-induced oxidative stress. CONCLUSION: In summary, Triphala is a promising neuroprotective agent against oxidative stress in SH-SY5Y cells and zebrafishes with significant antiapoptosis and antioxidant activities.

Molecular Subtypes of Oral Squamous Cell Carcinoma Based on Immunosuppression Genes Using a Deep Learning Approach.

Background: The mechanisms through which immunosuppressed patients bear increased risk and worse survival in oral squamous cell carcinoma (OSCC) are unclear. Here, we used deep learning to investigate the genetic mechanisms underlying immunosuppression in the survival of OSCC patients, especially from the aspect of various survival-related subtypes. Materials and methods: OSCC samples data were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and OSCC-related genetic datasets with survival data in the National Center for Biotechnology Information (NCBI). Immunosuppression genes (ISGs) were obtained from the HisgAtlas and DisGeNET databases. Survival analyses were performed to identify the ISGs with significant prognostic values in OSCC. A deep learning (DL)-based model was established for robustly differentiating the survival subpopulations of OSCC samples. In order to understand the characteristics of the different survival-risk subtypes of OSCC samples, differential expression analysis and functional enrichment analysis were performed. Results: A total of 317 OSCC samples were divided into one inferring cohort (TCGA) and four confirmation cohorts (ICGC set, GSE41613, GSE42743, and GSE75538). Eleven ISGs (i.e., BGLAP, CALCA, CTLA4, CXCL8, FGFR3, HPRT1, IL22, ORMDL3, TLR3, SPHK1, and INHBB) showed prognostic value in OSCC. The DL-based model provided two optimal subgroups of TCGA-OSCC samples with significant differences (p = 4.91E-22) and good model fitness [concordance index (C-index) = 0.77]. The DL model was validated by using four external confirmation cohorts: ICGC cohort (n = 40, C-index = 0.39), GSE41613 dataset (n = 97, C-index = 0.86), GSE42743 dataset (n = 71, C-index = 0.87), and GSE75538 dataset (n = 14, C-index = 0.48). Importantly, subtype Sub1 demonstrated a lower probability of survival and thus a more aggressive nature compared with subtype Sub2. ISGs in subtype Sub1 were enriched in the tumor-infiltrating immune cells-related pathways and cancer progression-related pathways, while those in subtype Sub2 were enriched in the metabolism-related pathways. Conclusion: The two survival subtypes of OSCC identified by deep learning can benefit clinical practitioners to divide immunocompromised patients with oral cancer into two subpopulations and give them target drugs and thus might be helpful for improving the survival of these patients and providing novel therapeutic strategies in the precision medicine area.

Shared Molecular Mechanisms between Atherosclerosis and Periodontitis by Analyzing the Transcriptomic Alterations of Peripheral Blood Monocytes.

OBJECTIVE: This study investigated the nature of shared transcriptomic alterations in PBMs from periodontitis and atherosclerosis to unravel molecular mechanisms underpinning their association. METHODS: Gene expression data from PBMs from patients with periodontitis and those with atherosclerosis were each downloaded from the GEO database. Differentially expressed genes (DEGs) in periodontitis and atherosclerosis were identified through differential gene expression analysis. The disease-related known genes related to periodontitis and atherosclerosis each were downloaded from the DisGeNET database. A Venn diagram was constructed to identify crosstalk genes from four categories: DEGs expressed in periodontitis, periodontitis-related known genes, DEGs expressed in atherosclerosis, and atherosclerosis-related known genes. A weighted gene coexpression network analysis (WGCNA) was performed to identify significant coexpression modules, and then, coexpressed gene interaction networks belonging to each significant module were constructed to identify the core crosstalk genes. RESULTS: Functional enrichment analysis of significant modules obtained by WGCNA analysis showed that several pathways might play the critical crosstalk role in linking both diseases, including bacterial invasion of epithelial cells, platelet activation, and Mitogen-Activated Protein Kinases (MAPK) signaling. By constructing the gene interaction network of significant modules, the core crosstalk genes in each module were identified and included: for GSE23746 dataset, RASGRP2 in the blue module and VAMP7 and SNX3 in the green module, as well as HMGB1 and SUMO1 in the turquoise module were identified; for GSE61490 dataset, SEC61G, PSMB2, SELPLG, and FIBP in the turquoise module were identified. CONCLUSION: Exploration of available transcriptomic datasets revealed core crosstalk genes (RASGRP2, VAMP7, SNX3, HMGB1, SUMO1, SEC61G, PSMB2, SELPLG, and FIBP) and significant pathways (bacterial invasion of epithelial cells, platelet activation, and MAPK signaling) as top candidate molecular linkage mechanisms between atherosclerosis and periodontitis.