One of the most common oral carcinomas is oral squamous cell carcinoma (OSCC), bringing a heavy burden to global health. Although progresses have been made in the intervention of OSCC, 5 years survival of patients suffering from OSCC is poor like before regarding to the high invasiveness of OSCC, which causes metastasis and recurrence of the tumor. The relationship between pyroptosis and OSCC remains to be further investigated as pyroptosis in carcinomas has gained much attention. Herein, the key pyroptosis-related genes were identified according to The Cancer Genome Atlas (TCGA) dataset. Additionally, a prognostic model was constructed based upon three key genes (CTLA4, CD5, and IL12RB2) through least absolute shrinkage and selection operator (LASSO) analyses, as well as univariate and multivariate COX regression in OSCC. It was discovered that the high expression of these three genes was associated with the low-risk group. We also identified LAIR2 as a hub gene, whose expression negatively correlated with the risk score and the different immune cell infiltration. Finally, we proved that these three genes were independent prognostic factors linked to overall survival (OS), and reliable consequences could be predicted by this model. Our study revealed the relationship between pyroptosis and OSCC, providing insights into new treatment targets for preventing and treating OSCC.

BACKGROUND: The aim of this study was to investigate the common gene signatures and potential molecular mechanisms of bladder urothelial carcinoma (BLCA) and metabolic syndrome (MS).
METHODS: Transcriptome data for BLCA and MS were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was utilized to identify co-expression networks associated with BLCA and MS, and five hub genes were further screened and validated using logistic least absolute shrinkage and selection operator (LASSO) regression models and receiver operating characteristic (ROC) curve, and external dataset for validation. The relationship between the hub genes and the clinicopathological characteristics and prognosis of BLCA patients was explored in the GEO and The Cancer Genome Atlas (TCGA)-BLCA cohorts, respectively. Differences in the immune microenvironment of BLCA and MS were analyzed using the database CIBERSORT and the R package \"ssGSEA\", and the correlation between hub genes and tumor microenvironment, immune score and targeted drugs was analyzed with the help of the TCGA-BLCA cohort. Finally, BLCA single-cell RNA (scRNA) data were used to analyze the expression levels of the hub genes in various cell types of BLCA and molecular mechanisms.
RESULTS: Five hub genes were screened by WGCNA and LASSO regression analysis, namely AP2-associated protein kinase 1 (AAK1), ATP-binding cassette subfamily F member 2 (ABCF2), Mitochondrial ribosomal protein L42 (MRPL42), La-related protein 3 (SSB) and TATA-box binding protein-associated factor 10 (TAF10). Analyzed in the GEO and TCGA-BLCA cohorts, we found that the hub genes (TAF10 and ABCF2) were closely associated with the clinicopathological characteristics and prognosis of BLCA patients. In CIBERSORT, we discovered that the hub genes are closely linked to the immune microenvironment, immune score, and especially with dendritic cells (DCs). In the single-cell RNA sequencing (scRNA-seq) analysis of BLCA, we identified that SSB was significantly differentially expressed in BLCA and normal bladder tissues and that it plays an important role in the development of BLCA.
CONCLUSIONS: The interaction of BLCA with MS may be associated with several cancer pathways being activated and identified TAF10 and ABCF2 as potential biomarkers and therapeutic targets for patients with BLCA and MS.

Complex diseases have heterogeneous underlying molecular mechanisms. In order to improve the diagnosis and treatment of disease, it is vital to stratify patients into homogeneous subgroups that share a similar disease etiology. In this study, we performed gene-level subtyping analysis on two independent Rheumatoid Arthritis gene expression cohorts from different ethnic groups to discover the possible disease mechanisms associated with each subtype. Also, a novel pathway-level analysis is proposed to increase the subtyping robustness and facilitate biological interpretation. This approach could stratify RA patients into two robust and homogeneous groups with differing activation of central signal transduction pathways and pro-inflammatory cytokines in the pathogenesis of RA. Such a methodology can help understand disease mechanisms at play in different patient sub-populations and also potentially explain why some patients don\'t respond to anti-TNF treatment.

ALDH16A1 is a novel member of the ALDH superfamily that is enzymatically-inactive and highly expressed in the kidney. Recent studies identified an association between a rare missense single nucleotide variant (SNV) in the ALDH16A1 gene and elevated serum uric acid levels and gout. The present study explores the mechanisms by which ALDH16A1 influences uric acid homeostasis in the kidney. We generated and validated a mouse line with global disruption of the Aldh16a1 gene through gene targeting and performed RNA-seq analyses in the kidney of wild-type (WT) and Aldh16a1 knockout (KO) mice, along with plasma metabolomics. We found that ALDH16A1 is expressed in proximal and distal convoluted tubule cells in the cortex of the kidney and in zone 3 hepatocytes. RNA-seq and gene ontology enrichment analyses showed that cellular lipid and lipid metabolic processes are up-regulated. Three transporters localized in the apical membrane of the proximal convoluted tubule of the kidney known to influence urate/uric acid homeostasis were found to be up-regulated (Abcc4, Slc16a9) or down-regulated (Slc17a3). An initial metabolomics analysis in plasma revealed an altered lipid profile in KO mice that is in agreement with our RNA-seq analysis. This is the first study demonstrating a functional role of ALDH16A1 in the kidney.