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Inorganic arsenic (iAs) is a recognized environment-related factor for bladder cancer (BCa). Arsenic (+3 oxidation state) methyltransferase (AS3MT) gene might influence BCa by regulating iAs metabolism. The aim of the present study was to explore whether AS3MT polymorphisms could affect BCa susceptibility. We systematically reviewed eligible case-control studies about AS3MT polymorphisms and BCa and to further compare the genotype distribution and allele distribution between BCa patients and controls by meta-analysis for humans. Besides, to clarify the effects of AS3MT expression on BCa clinical outcomes and survival time, we also conducted a series of analyses based on The Cancer Genome Atlas dataset. Databases were systematically retrieved and we applied Stata software to perform meta-analysis. The registration of this study protocol is at PROSPERO and ID is CRD42019133947. Five articles were recruited and pooled results demonstrated that rs3740393 and rs11191438 polymorphisms were related to BCa risk in overall population (p  < .05) in the overall population. In addition, GG and GC genotypes in rs3740393 and GG genotype in rs11191438 might be the susceptibility genotypes for BCa. Results based on 168 BCa samples from TGCA indicated that patients with higher expression of AS3MT had poor overall survival time and AS3MT expression is an independent indicator for BCa survival. This study identified that AS3MT polymorphisms could affect BCa risk and AS3MT expression was pivotal in prognosis of BCa. [ABSTRACT FROM AUTHOR]

Background. The incidence of lung cancer is the highest of all cancers, and it has the highest death rate. Lung adenocarcinoma (LUAD) is a major type of lung cancer. This study is aimed at identifying the prognostic value of immune-related long noncoding RNAs (lncRNAs) in LUAD. Materials and Methods. Gene expression profiles and the corresponding clinicopathological features of LUAD patients were obtained from The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was performed on the prognostic immune-related lncRNAs to calculate the risk scores, and a risk signature was constructed. Survival analysis was performed to assess the prognostic value of the risk signature. A nomogram was also constructed based on the clinicopathological features and risk signature. Results. A total of 437 LUAD patients with gene expression data and clinicopathological features were obtained in this study, which was considered the combination set. They were randomly and equally divided into a training set and a validation set. Seven immune-related lncRNAs (AC092794.1, AL034397.3, AC069023.1, AP000695.1, AC091057.1, HLA-DQB1-AS1, and HSPC324) were identified and used to construct a risk signature. The patients were divided into the low- and high-risk groups based on the median risk score of -0.04074. Survival analysis suggested that patients in the low-risk group had a longer overall survival (OS) than those in the high-risk group (p = 1.478 e − 02). A nomogram was built that could predict the 1-, 3-, and 5-year survival rates of LUAD patients (C-index of the nomogram was 0.755, and the AUCs for the 1-, 3-, and 5-year survivals were 0.826, 0.719, and 0.724, respectively). The validation and combination sets confirmed these results. Conclusion. Our study identified seven novel immune-related lncRNAs and generated a risk signature, as well as a nomogram, that could predict the prognosis of LUAD patients. [ABSTRACT FROM AUTHOR]

Background. Lung cancer is the most common cancer and the most common cause of cancer-related death worldwide. However, the molecular mechanism of its development is unclear. It is imperative to identify more novel biomarkers. Methods. Two datasets (GSE70880 and GSE113852) were downloaded from the Gene Expression Omnibus (GEO) database and used to identify the differentially expressed genes (DEGs) between lung cancer tissues and normal tissues. Then, we constructed a competing endogenous RNA (ceRNA) network and a protein-protein interaction (PPI) network and performed gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and survival analyses to identify potential biomarkers that are related to the diagnosis and prognosis of lung cancer. Results. A total of 41 lncRNAs and 805 mRNAs were differentially expressed in lung cancer. The ceRNA network contained four lncRNAs (CLDN10-AS1, SFTA1P, SRGAP3-AS2, and ADAMTS9-AS2), 21 miRNAs, and 48 mRNAs. Functional analyses revealed that the genes in the ceRNA network were mainly enriched in cell migration, transmembrane receptor, and protein kinase activity. mRNAs DLGAP5, E2F7, MCM7, RACGAP1, and RRM2 had the highest connectivity in the PPI network. Immunohistochemistry (IHC) demonstrated that mRNAs DLGAP5, MCM7, RACGAP1, and RRM2 were upregulated in lung adenocarcinoma (LUAD). Survival analyses showed that lncRNAs CLDN10-AS1, SFTA1P, and ADAMTS9-AS2 were associated with the prognosis of LUAD. Conclusion. lncRNAs CLDN10-AS1, SFTA1P, and ADAMTS9-AS2 might be the biomarkers of LUAD. For the first time, we confirmed the important role of lncRNA CLDN10-AS1 in LUAD. [ABSTRACT FROM AUTHOR]