Esophageal squamous cell carcinoma (ESCC) is a prevalent aggressive malignant tumor with poor prognosis. Investigations into the molecular changes that occur as a result of the disease, as well as identification of novel biomarkers for its diagnosis and prognosis, are urgently required. Long non-coding RNAs (lncRNAs) have been reported to play a critical role in tumor progression. The present study performed data mining analyses for ESCC via an integrated study of accumulated datasets and identification of the differentially expressed lncRNAs from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The identified intersection of differentially expressed genes (lncRNAs, miRNAs and mRNAs) in ESCC tissues between the GEO and TCGA datasets was investigated. Based on these intersected lncRNAs, the present study constructed a competitive endogenous RNA (ceRNA) network of lncRNAs in ESCC. A total of 81 intersection lncRNAs were identified; 67 of these were included in the ceRNA network. Functional analyses revealed that these 67 key lncRNAs primarily dominated cellular biological processes. The present study then analyzed the associations between the expression levels of these 67 key lncRNAs and the clinicopathological characteristics of the ESCC patients, as well as their survival time using TCGA. The results revealed that 31 of these lncRNAs were associated with tumor grade, tumor-node-metastasis (TNM) stage and lymphatic metastasis status (P<0.05). In addition, 15 key lncRNAs were demonstrated to be associated with survival time (P<0.05). Finally, 5 key lncRNAs were selected for validation of their expression levels in 30 patients newly diagnosed with ESCC via reverse transcription-quantitative PCR (RT-qPCR). The results suggested that the fold changes in the trends of up- and downregulation between GEO, TCGA and RT-qPCR were consistent. In addition, it was also demonstrated that a select few of these 5 key lncRNAs were significantly associated with TNM stage and lymph node metastasis (P<0.05). The results of the clinically relevant analysis and the aforementioned bioinformatics were similar, hence proving that the bioinformatics analysis used in the present study is credible. Overall, the results from the present study may provide further insight into the functional characteristics of lncRNAs in ESCC through bioinformatics integrative analysis of the GEO and TCGA datasets, and reveal potential diagnostic and prognostic biomarkers for ESCC.

/pdf/integrated-analysis-highlights-multiple-long-non-coding-rnas-53rq2y2kp4.pdf

Integrated analysis highlights multiple long non‑coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma

Neuroblastoma (NBL) is the most frequently encountered extracranial solid neoplasm and impacts significantly on the survival of patients, especially in cases of advanced tumor stage or relapse. A long noncoding RNA (lncRNA) signature to predict the survival of patients with NBL is proposed in this paper. Differentially expressed lncRNA (DElncRNA) was selected using the Limma plus Voom package in R based on the RNA-sequencing data downloaded from the Therapeutically Applicable Research To Generate Effective Treatments database and Genotype-Tissue Expression database. Univariate cox regression analysis, least absolute shrinkage and selection operator regression analysis, and multivariate cox regression analysis were conducted to identify candidate DElncRNAs for the risk signature. Consequently, 10 DElncRNAs were designated as candidate DElncRNAs for the risk signature. Time-dependent receiver operating characteristic curves and Kapan-Meier survival curves confirmed the efficacy of the risk signature in predicting the survival of patients with NBL (area under the curve = 0.941; p ≤ .001). One of the DElncRNA constituent subparts (LINC01010) was significantly associated with the survival outcome of patients with NBL in GSE62564 (p = .004). Thus, a risk signature comprising 10 DElncRNAs was identified as effective for individual risk stratification and the survival prediction outcomes of patients with NBL.

A novel risk signature that combines 10 long noncoding RNAs to predict neuroblastoma prognosis.

ABSTRACT This study explored the mechanism that ADAMTS9-AS2/miR-196b-5p/PPP1R12B/cell cycle pathway axis in inhibiting the malignant progression of esophageal cancer (EC), providing a new idea for targeted molecular therapy of EC. The expression data of EC tissue were acquired from TCGA database. The target lncRNA, downstream miRNA and its target gene were determined by bioinformatics analysis. ADAMTS9-AS2, miR-196b-5p and PPP1R12B levels in EC tissue and cells were assayed through qRT-PCR. Western blot was applied to assess protein level of PPP1R12B in cells and tissues, as well as protein expression of CDK1, cyclin A2, cyclin B1 and Plk1 in EC cells. Cell proliferation was assayed via CCK-8 assay. Cell cycle distribution was analyzed by flow cytometry. Cell migratory and invasive abilities were measured through scratch healing and transwell assays. Pearson correlation analysis was utilized to analyze relationship among ADAMTS9-AS2, miR-196b-5p and PPP1R12B. RIP was introduced to assess binding among the three. Dual-luciferase assay was utilized to verify targeted binding sites. The tumor formation in nude mice assay was utilized to detect tumorigenesis of EC cells in vivo. ADAMTS9-AS2 was significantly lowly expressed while miR-196b-5p was increased in EC tissue and cells. ADAMTS9-AS2 bound to miR-196b-5p and constrained its expression. Overexpressed ADAMTS9-AS2 inhibited EC cell malignant progression via downregulating miR-196b-5p, while overexpressed miR-196b-5p reversed this inhibitory effect. ADAMTS9-AS2 modulated PPP1R12B level by competitively inhibiting miR-196b-5p. PPP1R12B played a modulatory role in EC by inhibiting cell cycle pathway. Overexpressed ADAMTS9-AS2 regulated the tumor-forming ability of EC cells in vivo through miR-196b-5p/PPP1R12B/cell cycle signaling pathway axis. ADAMTS9-AS2 downregulated PPP1R12B by adsorbing miR-196b-5p, so as to regulate the cell cycle signaling pathway to inhibit EC malignant progression.

ADAMTS9-AS2 regulates PPP1R12B by adsorbing miR-196b-5p and affects cell cycle-related signaling pathways inhibiting the malignant process of esophageal cancer

Objective Long non-coding RNA (lncRNA) is closely associated with cancer occurrence and tumor development. However, the biological function of lncRNA ZNFX1-AS1 has not yet been reported in bladder cancer. The present study aimed to study the function of ZNFX1-AS1 in bladder cancer cells and the mechanism involved. Patients and methods The expression of ZNFX1-AS1 in bladder cancer tumor tissues and cell lines was examined by qRT-PCR. The effects of ZNFX1-AS1 knockdown on cell proliferation, cell cycle, cell migration, and invasion were assessed by Cell Counting Kit-8, flow cytometry (FCM), and transwell assays. Bioinformatics analyses and Luciferase reporter assays were performed to explore the mechanism by which ZNFX1-AS1 exerted its oncogenesis role in bladder cancer. The anti-tumor effect of ZNFX1-AS1 silencing on bladder cancer in vivo was also evaluated. Results ZNFX1-AS1 was over-expressed in bladder cancer tumor tissues and cell lines. ZNFX1-AS1 expression was found to be associated with tumor size and advanced clinical stage in patients with bladder cancer. Downregulation of ZNFX1-AS1 inhibited cell proliferation, cell clone formation, migration, and invasion of bladder cancer cells. ZNFX1-AS1 was found to interact with miR-193a-3p/Syndecan 1 (SDC1). ZNFX1-AS1 expression was negatively correlated with miR-193a-3p expression, but positively correlated with SDC1 expression in bladder cancer samples. ZNFX1-AS1 knockdown also effectively suppressed tumor growth in an in vivo xenograft model. Conclusions ZNFX1-AS1 regulated bladder cancer progression by targeting the miR-193a-3p/SDC1 axis. Our study may provide novel insights for bladder cancer prognosis and therapy.

LncRNA ZNFX1-AS1 targeting miR-193a-3p/SDC1 regulates cell proliferation, migration and invasion of bladder cancer cells.

Gastric cancer (GC) is one of the most common lethal malignancies worldwide. The molecular mechanisms underlying GC early detection are poorly understood. Identifying potential coding and non-coding markers and related pathways in the GC progression is essential. Some Long non-coding RNAs (lncRNAs) reportedly play vital roles during gastric GC development. However, the clinical significance and biological function of LINC00332 in GC remain largely unclear.The gene expression patterns of GC from an RNAseq dataset (GSE122401) were retrieved from the Gene Expression Omnibus (GEO) database to recognize differentially expressed genes (DEGs) and lncRNAs (DELs) between normal and GC samples through several bioinformatic analysis. The expression of LINC00332 and MMP-13 as a target gene was quantified in fresh frozen tissues obtained from GC patients. In addition, we investigated the potential function of LINC00332 in silico and in vitro.The expressions of LINC00332 and MMP-13 were significantly downregulated and upregulated in GC tissues, respectively. A significant inverse correlation between LINC00332 and MMP-13 mRNA expression was observed in tumor samples. The mRNA expression level of mesenchymal markers, stem cell factors, and MMP genes were significantly decreased after the LINC00332 ectopic expression, while epithelial markers expression was significantly increased. The LINC00332 overexpression markedly repressed proliferation, migration, and invasion and did not induce apoptosis in AGS cells. In addition, LINC00332 overexpression notably promoted the E-cadherin protein expression. Moreover, LINC00332 significantly decreased the cisplatin resistance.Our findings indicated that LINC00332 may be a critical anti-EMT factor and provided a new efficient therapeutic strategy for GC treatment. 

Inhibitory role of LINC00332 in gastric cancer progression through regulating cell EMT and stemness.

Background ceRNAs have emerged as pivotal players in the regulation of gene expression and play a crucial role in the physiology and development of various cancers. Nevertheless, the function and underlying mechanisms of ceRNAs in esophageal cancer (EC) are still largely unknown. Methods In this study, profiles of DEmRNAs, DElncRNAs, and DEmiRNAs between normal and EC tumor tissue samples were obtained from the Cancer Genome Atlas database using the DESeq package in R by setting the adjusted P 2 as the cutoff. The ceRNA network (ceRNet) was initially constructed to reveal the interaction of these ceRNAs during carcinogenesis based on the bioinformatics of miRcode, miRDB, miRTarBase, and TargetScan. Then, independent microarray data of GSE6188, GSE89102, and GSE92396 and correlation analysis were used to validate molecular biomarkers in the initial ceRNet. Finally, a least absolute shrinkage and selection operator logistic regression model was built using an oncogenic ceRNet to diagnose EC more accurately. Results We successfully constructed an oncogenic ceRNet of EC, crosstalk of hsa-miR372-centered CADM2-ADAMTS9-AS2 and hsa-miR145-centered SERPINE1-PVT1. In addition, the risk-score model -0.0053*log2(CADM2)+0.0168*log2(SERPINE1)-0.0073*log2(ADAMTS9-AS2)+0.0905*log2(PVT1)+0.0047*log2(hsa-miR372)-0.0193*log2(hsa-miR145), (log2[gene count]) could improve diagnosis of EC with an AUC of 0.988. Conclusion We identified two novel pairs of ceRNAs in EC and its role of diagnosis. The pairs of hsa-miR372-centered CADM2-ADAMTS9-AS2 and hsa-miR145-centered SERPINE1-PVT1 were likely potential carcinogenic mechanisms of EC, and their joint detection could improve diagnostic accuracy.

/pdf/robust-analysis-of-novel-mrna-lncrna-cross-talk-based-on-4ibbywxiow.pdf

Robust analysis of novel mRNA-lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer.

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Robust analysis of novel mRNA-lncRNA cross talk based on ceRNA hypothesis uncovers carcinogenic mechanism and promotes diagnostic accuracy in esophageal cancer.