Identifying pyroptosis- and inflammation-related genes in intracranial aneurysms based on bioinformatics analysis.

BACKGROUND: Intracranial aneurysm (IA) is the most common cerebrovascular disease, and subarachnoid hemorrhage caused by its rupture can seriously impede nerve function. Pyroptosis is an inflammatory mode of cell death whose underlying mechanisms involving the occurrence and rupture of IAs remain unclear. In this study, using bioinformatics analysis, we identified the potential pyroptosis-related genes (PRGs) and performed their inflammatory response mechanisms in IAs. METHODS: The mRNA expression matrix of the IA tissue was obtained from the Gene Expression Omnibus database, and 51 PRGs were obtained from previous articles collected from PubMed. The differentially expressed PRGs (DEPRGs) were performed using R software. Subsequently, we performed enrichment analysis, constructed a protein-protein interaction network, performed weighted gene coexpression network analysis (WGCNA) and external validation using another dataset, and identified a correlation between hub genes and immune cell infiltration. Finally, the expression and tissue distribution of these hub genes in IA tissues were detected using Western blotting and immunohistochemical (IHC) staining. RESULTS: In total, 12 DEPRGs associated with IA were identified in our analysis, which included 11 up-regulated and one down-regulated genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that the DEPRGs were mostly enriched in the NOD-like receptor signaling pathway, interleukin-1 beta production, and the inflammasome complex. Three hub genes, NLRP3, IL1B and IL18, were identified using Cytoscape software and the WGCNA correlation module, and external validation revealed statistically significant differences between the expression of these hub genes in the ruptured and unruptured aneurysm groups (p < 0.05). Furthermore, all AUC values were > 0.75. Immune cell infiltration analysis suggested that the hub genes are related to CD8 T cell, macrophages and mast cells. Finally, IHC staining revealed that the protein levels of these hub genes were higher in ruptured and unruptured IA tissues than in normal tissues (p < 0.05). CONCLUSION: The results of bioinformatics analysis showed that pyroptosis is closely related to the formation and rupture of IA, and identified three potential hub genes involved in the pyroptosis and infiltration ofcells. Our findings may improve the understanding of the mechanisms underlying pyroptosis in IA.

Identification of potential biomarkers and survival analysis for oral squamous cell carcinoma: A transcriptomic study.

OBJECTIVE: Oral squamous cell carcinoma (OSCC) is one of the most common neoplasms worldwide. The current study aimed to identify potential biomarkers associated with OSCC survival. MATERIALS AND METHODS: Differentially expressed genes (DEGs) in atypical OSCC cases were identified using two public datasets: The Cancer Genome Atlas and the Gene Expression Omnibus database. Receiver operating characteristic (ROC) analysis was performed to identify the cutoff, and the candidate DEGs related to survival. Kaplan-Meier and Cox regression analysis using the categorized genes were employed to identify genes that impact the overall survival in OSCC. RESULTS: A total of 263 OSCC samples and 105 healthy tissues were used to identify 295 upregulated and 131 downregulated genes expressed only in non-smokers. ROC analyses identified 25 candidate genes associated with death. Survival analyses demonstrated that the following DEGs, namely CSTA, FGFR2, MMP19, OLR1, PCSK1, RAMP2, and CGB5, are potential OSCC prognostic factors. CONCLUSION: We found that CSTA, FGFR2, MMP19, OLR1, PCSK1, RAMP2, and CGB5 are associated with a low survival rate in OSCC. However, further studies are needed to validate our findings and facilitate the development of these factors as potential biomarkers for OSCC survival.

Primary Breast Angiosarcoma: Comparative Transcriptome Analysis.

Primary breast angiosarcoma, with de novo appearance and not associated with exposure to radiation or lymphedema, is a rare pathology representing less than 0.05% of the neoplasms related to this organ. The pathology is characterized by its aggressiveness, poor prognosis, and difficulties in its differential diagnosis. This article reports the case of a 55-year-old white woman with no family history of cancer, with a rapidly growing mass in the left mammary gland that ulcerates and bleeds. It is confirmed as primary breast angiosarcoma by immunostaining in the tumor tissue for CD31, CD34, and FLI-1. In addition, a sample of neoplastic and healthy tissues is collected from the patient for RNA sequencing; the results are contrasted with a tissue sample from a patient with Luminal A subtype of breast cancer, as well as data from other cases of angiosarcoma available in public databases. These findings revealed a genetic profile associated with the immune and inflammatory response in the patient's sample when compared to available angiosarcoma data; these molecular patterns are consistent with other recent studies. Due to the rarity of the disease, the studies carried out on each patient contribute to the expanding knowledge of the etiology and molecular pathways that are still partially known and continue to be the subject of research. Aside from a comparative transcriptome study, this article aims to provide an update on the state of knowledge about this disease.

Genetic and in silico analysis show a role of SMAD3 on recurrent pregnancy loss.

Recurrent pregnancy loss (RPL) is one of the most common reproductive failures affecting 1-5% of couples. Smad3 is an effector of signalling of the Transforming Growth Factors-ß superfamily (TGF-ß), regulating the transcription of several target genes of these cytokines. The objective of this study was to evaluate the influence of a variant on SMAD3 (rs17293443) in RPL. A case-control study was carried out with 149 women who experienced RPL and 159 controls, as well as bioinformatics tools to determine the role of this variant in this condition. Our study showed an allelic (p = 0.023) and genotypic (p < 0.01) association of this variant with the RPL. Our functional in silico predictions suggest that this variant causes a change in SMAD3 expression levels. Alterations in the expression of this gene can directly compromise the Smad3-dependent signalling pathway that is fundamental for key processes for gestation such as steroid hormone regulation and implantation, as demonstrated by ontologies analyses performed and the literature. Our findings regarding the involvement of Smad3 on RPL are a novelty in this field, and they seem to be promising to the clinical management of this condition.

Reanalysis and integration of public microarray datasets reveals novel host genes modulated in leprosy.

Due to multiple hypothesis testing with often limited sample size, microarrays and other-omics technologies can sometimes produce irreproducible findings. Complementary to better experimental design, reanalysis and integration of gene expression datasets may help overcome reproducibility issues by identifying consistent differentially expressed genes from independent studies. In this work, after a systematic search, nine microarray datasets evaluating host gene expression in leprosy were reanalyzed and the information was integrated to strengthen evidence of differential expression for several genes. Our results are relevant in prioritizing genes and pathways for further investigation, whether in functional studies or in biomarker discovery. Reanalysis of individual datasets revealed several differentially expressed genes (DEGs) in accordance with original reports. Then, five integration methods (P value and effect size based) were tested. In the end, random-effects model and ratio association were selected as the main methods to pinpoint DEGs. Overall, classic pathways were found corroborating previous findings and validating this approach. Also, we identified some novel DEG involved especially with skin development processes (AQP3, AKR1C3, CYP27B1, LTB, VDR) and keratinocyte biology (CSTA, DSG1, KRT14, KRT5, PKP1, IVL), both still poorly understood in leprosy context. In addition, here we provide aggregated evidence towards some gene candidates that should be prioritized in further leprosy research, as they are likely important in immunopathogenesis. Altogether, these data are useful in better understanding host responses to the disease and, at the same time, provide a list of potential host biomarkers that could be useful in complementing leprosy diagnosis based on transcriptional levels.