Comprehensive Analyses Revealed Eight Immune Related Signatures Correlated With Aberrant Methylations as Prognosis and Diagnosis Biomarkers for Kidney Renal Papillary Cell Carcinoma.

BACKGROUND: Kidney renal papillary cell carcinoma (KIRP) is a common type of renal cell carcinoma. DNA methylation plays an important role in the development of several cancers. The aim of our study was to identify differentially expressed genes associated with abnormal DNA methylation as biomarkers for predicting the outcome of KIRP. METHOD: We downloaded KIRP methylation data, RNA sequencing (RNAseq) data, and their corresponding clinical information from the Cancer Genome Atlas (TCGA) database. ChAMP and DEGseq2 packages in R software were used to screen differentially methylated probes (DMPs) and differentially expressed genes (DEGs). Univariate and multivariate Cox regression analyses were used to identify suitable immune related genes correlated with aberrant methylations as prognosis biomarkers. RESULTS: We identified 8 DEGs (Cysteine And Glycine Rich Protein 1 [CSRP1], major histocompatibility complex, Class II, DM Beta [HLA-DMB], LIF Receptor Subunit Alpha [LIFR], Leukotriene B4 receptor 2 [LTB4R2], Mitogen-Activated Protein Kinase Kinase Kinase 14 [MAP3K14], Nuclear Receptor Subfamily 2 Group F Member 1 [NR2F1], Secreted And Transmembrane 1 [SECTM1], and Vimentin [VIM]) that were independently associated with the overall survival (months) (OS) of KIRP. The time dependent area under the curve (AUC) for each receiver operating characteristic (ROC) of the risk assessment model at 1, 3, 5, and 10-years reached 0.8415, 0.8131, 0.7873, and 0.7667. The risk assessment model was correlated with several immune cells and factors. The AUC value of the diagnosis model using those 8 DEGs reached 0.99. CONCLUSIONS: The risk assessment model constructed by those 8 DEGs was well able to predict the prognosis and diagnose of KIRP. However, whether the prognosis and diagnosis model could be applied in clinical practice requires further study.

CCDC26 rs4295627 polymorphisms associated with an increased risk of glioma: A meta-analysis.

BACKGROUND: Gliomas are the most common primary brain tumor in adults. Many studies have revealed associations between the rs4295627 polymorphism in the coiled-coil domain containing 26 (CCDC26) gene and the risk of glioma. However, the conclusions are still unclear because some studies have reported inconsistent results. OBJECTIVES: The aim of the present meta-analysis was to determine the relationship and quantitatively evaluate the effect of the rs4295627 polymorphism on the risk of glioma. MATERIAL AND METHODS: Data was extracted from PubMed, EMBASE and Google Scholar, with the most recent search up to December, 2015. Odds ratios (OR) and their 95% CIs were used to evaluate the effect of CCDC26 rs4295627 polymorphisms on glioma. A test of heterogeneity and an assessment of publication bias were also performed. RESULTS: A total of 11 studies (8292 cases and 12,419 controls) were selected for this meta-analysis. Significant associations were observed in all genetic analysis models (G vs T: OR = 1.26, 95% CI = 1.12-1.43; GG vs TT: OR = 1.72, 95% CI = 1.24-2.39; GT vs TT: OR = 1.33, 95% CI = 1.24-1.42; GG + GT vs TT: OR = 1.36, 95% CI = 1.20-1.53; GG vs GT + TT: OR = 1.65, 95% CI = 1.18-2.29, respectively). CONCLUSION: The results of the present study clearly show that the G allele of the rs4295627 polymorphism significantly increases the risk of glioma. Nevertheless, well-designed large-scale studies are needed to further evaluate the effect of the rs4295627 polymorphism on different types or degrees of glioma in different ethnic groups as well as to measure the combined effects on glioma risk.