SFXN1 expression analysis in oral squamous cell carcinoma and its association with the PI3K-AKT-mTOR pathway and immune cell infiltration

PRELP inhibits the progression of oral squamous cell carcinoma via inactivation of the NF-κB pathway

Background: HOXD13, a member of the homeobox gene family, plays a critical role in developmental processes and has been implicated in various malignancies, including pancreatic cancer and glioma. However, its role in oral squamous cell carcinoma (OSCC) remains poorly understood. This study aimed to elucidate the potential of HOXD13 as a diagnostic biomarker and therapeutic target for OSCC. Methods: We conducted a comprehensive analysis of OSCC samples from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA)-head and neck squamous cell carcinoma (HNSCC) databases. Differentially expressed genes (DEGs) with upregulated expression were identified using Venn diagrams. Functional annotation was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. A protein-protein interaction (PPI) network was constructed, and 10 key hub genes were identified using the cytoNCA method in Cytoscape. Subsequently, these hub genes were validated using quantitative real-time PCR (qRT-PCR) in tissue samples and cell lines. The impact of HOXD13 knockdown on OSCC cell proliferation and migration was assessed through lentiviral transduction followed by Cell Counting Kit-8 (CCk-8), 5-Ethynyl-2'-deoxyuridine (EdU), wound healing, and Transwell assays. Additionally, proteomic sequencing was performed to explore the effects on lipid metabolism-related pathways. Result: Bioinformatic analysis revealed 121 upregulated DEGs in OSCC. Among these, 10 hub genes (FOXM1, CSF2, FN1, HOXD13, MMP9, SPP1, BIRC5, CXCL11, CXCL9, and FOXA2) were identified using the PPI network and Cytoscape analysis. HOXD13 was notably upregulated in OSCC tissues and cell lines, showing high diagnostic potential with an area under the receiver operating characteristics (ROC) curve (AUC) of 0.9. Immune infiltration analysis indicated significant differences in the tumor microenvironment associated with HOXD13 expression levels. Stable knockdown of HOXD13 in OSCC cell lines resulted in a marked reduction in cell proliferation and migration. Proteomic analysis post-HOXD13 knockdown highlighted alterations in fatty acid degradation pathways and increased expression of related metabolic enzymes. Conclusion: HOXD13 is significantly upregulated in OSCC, and its inhibition reduces OSCC cell proliferation and migration. Additionally, HOXD13 affects fatty acid metabolism in OSCC, suggesting its potential as a therapeutic target and biomarker.

Previous studies have shown that asthma is a risk factor for lung cancer, while the mechanisms involved remain unclear. We attempted to further explore the association between asthma and non-small cell lung cancer (NSCLC) via bioinformatics analysis. We obtained GSE143303 and GSE18842 from the GEO database. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) groups were downloaded from the TCGA database. Based on the results of differentially expressed genes (DEGs) between asthma and NSCLC, we determined common DEGs by constructing a Venn diagram. Enrichment analysis was used to explore the common pathways of asthma and NSCLC. A protein-protein interaction (PPI) network was constructed to screen hub genes. KM survival analysis was performed to screen prognostic genes in the LUAD and LUSC groups. A Cox model was constructed based on hub genes and validated internally and externally. Tumor Immune Estimation Resource (TIMER) was used to evaluate the association of prognostic gene models with the tumor microenvironment (TME) and immune cell infiltration. Nomogram model was constructed by combining prognostic genes and clinical features. 114 common DEGs were obtained based on asthma and NSCLC data, and enrichment analysis showed that significant enrichment pathways mainly focused on inflammatory pathways. Screening of 5 hub genes as a key prognostic gene model for asthma progression to LUAD, and internal and external validation led to consistent conclusions. In addition, the risk score of the 5 hub genes could be used as a tool to assess the TME and immune cell infiltration. The nomogram model constructed by combining the 5 hub genes with clinical features was accurate for LUAD. Five-hub genes enrich our understanding of the potential mechanisms by which asthma contributes to the increased risk of lung cancer.

Extracorporeal membrane oxygenation (ECMO) is an important clinical treatment for acute myocardial infarction (AMI) combined with cardiogenic shock, but the role of programmed cell death (PCD)-related genes in prognostication has not yet been investigated. Therefore, we explored the key prognostic biomarkers and immune infiltration in ECMO treatment in AMI combined with cardiogenic shock. The GSE93101 dataset was analyzed from the Gene Expression Omnibus (GEO) database, and the expression levels of PCD-related genes in AMI under ECMO were identified. Differentially expressed PCD-related genes between successful and failed treatment samples were analyzed, and Least absolute shrinkage and selection operator (LASSO) logistic regression and random forest were used to screen PCD-related molecular markers for ECMO treatment in AMI combined with cardiogenic shock. Co-expressed regulatory network and enrichment functions of the hub PCD-related genes were performed. In addition, the single-sample gene set enrichment analysis (ssGSEA) algorithm was used to calculate the immune cell infiltration of the ECMO treatment samples. A total of 115 differentially expressed genes were identified from the GSE93101 dataset, and 76 genes were associated with PCD. Then, two hub PCD-related genes, Cell division cycle associated 7 (CDCA7), ankyrin repeat and SOCS box containing 13 (ASB13) were identified as prognostic markers of ECMO treatment in AMI combined with cardiogenic shock. The most significant Gene Ontology (GO) enriched terms of the co-expressed protein of ASB13 are related to post-translational protein modification, cullin-RING ubiquitin ligase complex, and cullin family protein binding, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that ubiquitin mediated proteolysis is the most enriched pathway. The results of GO and KEGG analysis in CDCA7 were mainly involved in DNA and cell cycle related activities and pathways. Moreover, we found that the successful treatment samples contained a lower proportion of nature killer T cells using immune infiltration analysis. Immune cell infiltration analysis revealed that ASB13 was positively correlated with natural killer cell (r = 0.591, p = 0.026), monocyte (r = 0.586, p = 0.028), and gamma delta T cell (r = 0.562, p = 0.036). The results of this study showed that ASB13 and CDCA7 may contribute to the occurrence and progression of AMI with cardiogenic shock under ECMO.

Oral squamous cell carcinoma (OSCC) is a globally prevalent cancer with significant mortality rates. OSCC a predominant subtype of head and neck squamous cell carcinoma (HNSCC), poses a substantial health burden. Despite advancements in diagnosis and therapy, OSCC prognosis remains poor. The 26S proteasome, a cellular protein degradation complex, is associated with cancer, including PSMA1, a proteasomal subunit, which is upregulated in various cancers. We analyzed PSMA1 expression using TCGA data, validated it in OSCC samples using real-time PCR, and explored its role through various databases. Tumor and adjacent normal tissues from OSCC patients were examined, and PSMA1 expression was analyzed. Survival analysis assessed the impact of PSMA1 on patient outcomes, while immune infiltration was examined using the TIMER database. GeneMANIA, STRING, and Metascape were utilized for gene interaction and pathway analysis. PSMA1 was significantly upregulated in OSCC and HNSCC. Its overexpression correlated with advanced clinicopathological features and poorer prognosis in HNSCC patients. PSMA1 expression is also related to immune cell infiltration. Gene interaction analysis revealed PSMA1 involvement in proteolysis regulation, suggesting its potential as a therapeutic target. PSMA1 upregulation in HNSCC association with adverse clinicopathological features and prognosis underscores its potential significance. Further research is warranted to elucidate its molecular mechanisms and therapeutic potential in OSCC management.

Alteration in PNMA1 expression is associated with poor prognosis and tumor immune infiltration in head and neck squamous cell carcinoma

Laryngeal cancer (LC) is a malignant tumor that occurs in the head and neck. Laryngeal cancer is one of the most common cancers of the neck and head, and its prognosis has always been poor. The incidence of LC increased gradually and showed an early rising trend. Laryngeal cancer is rarely studied in relation to immunity, Malignant tumors will change the state of the human body in various ways to adapt to their own survival and avoid the immune system. This study aims to explore the immune molecular mechanism of laryngeal cancer through bioinformatics analysis. The gene expression data was downloaded for 3 microarray datasets: GSE27020, GSE59102, and GSE51985. CIBERSORT algorithm was performed to evaluate immune cell infiltration in tissues between LC and healthy control (HC). Differentially expressed genes (DEGs) were screened. Functional correlation of DEGs were analyzed by Gene Ontology, Gene Set Enrichment Analysis and Kyoto encyclopedia of genes and genomes. Candidate biomarkers were identified by cytoHubba of Cytoscape. Spearman correlations between the above biomarkers and infiltrating immune cells were explored using R software analysis. The immune cell types of LC and HC were significantly different. Twenty-one DEGs were obtained by cross-screening. The function of DEGs is closely related to the number of immune cells. Five central genes (TNNT3, TNNI2, Desmin, matrix metallopeptidase 9 and cytotoxic T lymphocyte antigen 4) were screened. The HUB gene was demonstrated to have the ability to diagnose LC and HC with good specificity and sensitivity. The correlation between immune cells and biomarkers showed that hub gene was positively correlated with macrophages and dendritic cells, and negatively correlated with CD4 + T cell. TNNT3, TNNI2, Desmin, matrix metallopeptidase 9 and cytotoxic T lymphocyte antigen 4 can be used as diagnostic biomarker for LC. Macrophages, dendritic cells and CD4 + T cell may participate in the occurrence and development of LC.

Head and neck squamous cell carcinoma (HNSCC) is one of the few malignant tumors that respond well to immunotherapy. We aimed to investigate the immune-related genes and immune cell infiltration of HNSCC and construct a predictive model for its prognosis. We calculated the stromal/immune scores of patients with HNSCC from The Cancer Genome Atlas using the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm and investigated the relationship between the scores and patients' prognosis. Three machine learning algorithms (LASSO, Random Forest, and Rbsurv) were performed to screen key immune-related genes and constructed a predictive model. The immune cell infiltrating was calculated by the Tumor Immune Estimation Resource algorithm. The stromal and immune scores significantly correlated with prognosis. A 6-gene signature was selected and displayed a robust predictive effect. The expressions of key genes were associated with immune infiltrating. GSE65858 validated the results. Our study comprehensively analyzed the tumor microenvironment of HNSCC and constructed a robust predictive model, providing a basis for further investigation of therapy.

HPV Associated Oral and Oropharyngeal Cancer

DYNC1I1 acts as a promising prognostic biomarker and is correlated with immune infiltration in head and neck squamous cell carcinoma

The prognostic value of TMB and the relationship between TMB and immune infiltration in head and neck squamous cell carcinoma: A gene expression-based study.

Introduction: The morbidity and mortality of acute kidney injury (AKI) are increasing. Epigenetic regulation and immune cell infiltration are thought to be involved in AKI. However, the relationship between epigenetic regulation and immune cell infiltration in AKI has not been elucidated. This study was conducted to identify the differentially expressed genes (DEGs), differentially expressed RNA methylation genes (DEMGs), and infiltrated immune cells in the kidneys of ischemia-reperfusion induced-acute kidney injury (IRI-AKI) models and further explore their relationships in IRI-AKI. Methods: This is a bioinformatic analysis using R programming language in 3 selected IRI-AKI datasets from the Gene Expression Omnibus (GEO) database, including 16 IRI-AKI kidney tissues and 10 normal kidney tissues. The DEGs were screened, and enrichment pathways were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The DEMGs and core DEMGs were identified using the R package. The ROC curve was plotted to predict disease occurrence of 7 core DEMGs. The correlation of 7 core DEMGs and other genes was analyzed using Pearson’s correlation test. The gene set enrichment analysis (GSEA) of each DEMG was conducted using the R package. The upstream miRNAs and transcript factors of 7 core DEMGs were predicted based on the RegNetwork database and Cytoscape software. The STITCH database was used to predict the possible binding compounds of the 7 core DEMGs. Immune cell infiltration in kidney tissues between the IRI-AKI group and control group was evaluated using the R package. Results: A total of 2,367 DEGs were obtained, including 1,180 upregulated and 1,187 downregulated genes in IRI-AKI kidney associated with the cell structure, proliferation, molecule binding/interaction, and signaling pathways such as the leukocyte migration and chemokine signaling pathways. Ten DEMGs were identified, with Ythdf1, Rbm15, Trmt6, Hnrnpc, and Dnmt1 being significantly upregulated, while Lrpprc, Cyfip2, Mettl3, Ncbp2, and Nudt7 were significantly downregulated in IRI-AKI tissues. The molecules interacting with 7 core DEMGs were identified. Significant changes in the infiltration of 8 types of immune cells were observed in IRI-AKI kidneys compared to normal controls. The significant correlation between 6 core DEMGs and the infiltration of immune cells was observed. Conclusion: IRI may induce AKI through RNA methylation to regulate the expression of genes involved in immune cell infiltration.

BackgroundTumor immune infiltrate has been explored in oral squamous cell carcinoma (OSCC), but studies on simultaneous characterization of multiple immune cell subtypes separately in stromal and intraepithelial tumor compartments are limited.ObjectivesWe aimed to investigate the immune cell infiltrate in OSCC by using immunohistochemistry (IHC) for a panel of inflammatory cells in stromal and epithelial tumor compartments for a better characterization of the tumors.MethodsThirty‐six OSCC lesions and nine normal oral mucosa (NOM) samples from patients attending Khartoum Dental Teaching Hospital, Sudan were investigated for presence of tumor infiltrating lymphocytes, tumor‐associated macrophages, tumor‐associated neutrophils, and PD‐L1 positive cells in the inflammatory infiltrate by single and double IHC. Digital quantitative analysis (Aperio Technologies Inc.) was performed separately for stromal and epithelial compartments.ResultsOSCC cases displayed a higher inflammatory infiltrate in the associated stroma, but not in the epithelial compartment when compared to NOM. The immunosuppressive type of inflammatory infiltrate, that is, T regulatory cells (FoxP3+ cells) was identified to be significantly higher in the epithelial compartment of tumors with advanced clinical state. An immunoscore developed by combining intraepithelial FoxP3+ and CD4+ cells was found significantly higher in lesions from elderly patients, localized at toombak dipping‐related sites, poorly differentiated OSCCs, or with loco‐regional lymph node spreading.ConclusionsDespite heavy immune cell infiltration in tumor‐associated stroma, the majority of OSCCs in this cohort displayed a low intraepithelial immune infiltration. An immunoscore based on combined CD4 and FoxP3 intraepithelial expression may serve as an indicator of advanced tumor progression and should be further investigated for its use as potential prognostic biomarker in OSCC.

Comparison of combined positive score, Salgado TIL score, immunofluorescence and single cell RNA sequencing for predicting response to therapy

IntroductionSalivary statherin, encoded by the STATH gene, maintains enamel integrity and oral microbial balance. Its downregulation has been linked to oral diseases, but its transcriptomic behavior in head and neck squamous cell carcinoma (HNSCC) remains largely unexplored. This study aimed to assess STATH as a diagnostic and prognostic biomarker in HNSCC and explore its potential biological role.Materials and methodsThe expression of STATH across 33 cancer types was analyzed via TIMER (Tumor Immune Estimation Resource), GEPIA (Gene Expression Profiling Interactive Analysis), and UALCAN (University of Alabama at Birmingham Cancer Data Analysis Portal), and promoter methylation and clinical correlations were explored in HNSCC. Prognostic significance was evaluated via Kaplan-Meier survival analysis (log-rank p<0.05). Immune cell infiltration was assessed by human papilloma virus (HPV) status via TIMER. Mutation data (n=674) were analyzed via cBioPortal. The findings were validated via the GEO GSE6631 dataset (n=22 paired samples). Co-expression and pathway enrichment analyses were conducted via UALCAN and Enrichr. Protein-protein interaction (PPI) networks were constructed via Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database.ResultsSTATH was significantly downregulated in HNSCC tissues compared with normal tissues according to TIMER (p<0.001) and GEPIA (p<0.01), with slightly reduced promoter methylation (median β=0.611; p=0.006) and rare genetic alterations (<1%). Higher STATH expression was associated with better overall survival (hazard ratio (HR)=0.914; log-rank p=0.033), especially in HPV-positive patients (HR=0.822; log-rank p=0.039). STATH expression was correlated with immune infiltration, particularly B cells, in HPV-positive tumors (r=0.355; p=0.001). STATH downregulation was validated (adjusted p=0.004). Co-expression analysis revealed enrichment in immune and oral health-associated pathways, including salivary protein's role in periodontitis (p=0.007; OR=118.8; LYZ, LTF) and dental caries (p=0.007; OR=59.36; LYZ, CCL28). PPIs interact with histatins and mucins.ConclusionSTATH is consistently downregulated in HNSCC, independent of promoter methylation or genetic mutations. Its suppression likely reflects tumor-driven remodeling of the salivary microenvironment, weakening host defenses and promoting disease progression. STATH has potential as a noninvasive diagnostic and prognostic biomarker.