Search

Long non-coding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs) to regulate mRNA expression through sponging microRNA in tumorigenesis and progression. However, following the discovery of new RNA interaction, the differentially expressed RNAs and ceRNA regulatory network are required to update. Our study comprehensively analyzed the differentially expressed RNA and corresponding ceRNA network and thus constructed a potentially predictive tool for prognosis. “DESeq2” was used to perform differential expression analysis. Two hundred and six differentially expressed (DE) lncRNAs, 222 DE miRNAs, and 2,463 DE mRNAs were found in this study. The lncRNA-mRNA interactions in the miRcode database and the miRNA-mRNA interactions in the starBase, miRcode, and mirTarBase databases were searched, and a competing endogenous RNA (ceRNA) network with 186 nodes and 836 interactions was subsequently constructed. Aberrant expression patterns of lncRNA NR2F1-AS1 and lncRNA AC010168.2 were evaluated in two datasets (GSE89006, GSE31684), and real-time polymerase chain reaction was also performed to validate the expression pattern. Furthermore, we found that these two lncRNAs were independent prognostic biomarkers to generate a prognostic lncRNA signature by univariate and multivariate Cox analyses. According to the lncRNA signature, patients in the high-risk group were associated with a poor prognosis and validated by an external dataset. A novel genomic-clinicopathologic nomogram to improve prognosis prediction of bladder cancer was further plotted and calibrated. Our study deepens the understanding of the regulatory ceRNA network and provides an easy-to-do genomic-clinicopathological nomogram to predict the prognosis in patients with bladder cancer.

Abnormal metabolism, including abnormal fatty acid metabolism, is an emerging hallmark of cancer. The current study sought to investigate the potential prognostic value of fatty acid metabolism-related long noncoding RNAs (lncRNAs) in colorectal cancer (CRC). To this end, we obtained the gene expression data and clinical data of patients with CRC from The Cancer Genome Atlas (TCGA) database. Through gene set variation analysis (GSVA), we found that the fatty acid metabolism pathway was related to the clinical stage and prognosis of patients with CRC. After screening differentially expressed RNAs, we constructed a fatty acid metabolism-related competing endogenous RNA (ceRNA) network based on the miRTarBase, miRDB, TargetScan, and StarBase databases. Next, eight fatty acid metabolism-related lncRNAs included in the ceRNA network were identified to build a prognostic signature with Cox and least absolute shrinkage and selection operator (LASSO) regression analyses, and a nomogram was established based on the lncRNA signature and clinical variables. The signature and nomogram were further validated by Kaplan–Meier survival analysis, Cox regression analysis, calibration plots, receiver operating characteristic (ROC) curves, decision curve analysis (DCA). Besides, the TCGA internal and the quantitative real-time polymerase chain reaction (qRT-PCR) external cohorts were applied to successfully validate the robustness of the signature and nomogram. Finally, in vitro assays showed that knockdown of prognostic lncRNA TSPEAR-AS2 decreased the triglyceride (TG) content and the expressions of fatty acid synthase (FASN) and acetyl-CoA carboxylase 1 (ACC1) in CRC cells, which indicated the important role of lncRNA TSPEAR-AS2 in modulating fatty acid metabolism of CRC. The result of Oil Red O staining showed that the lipid content in lncRNA TSPEAR-AS2 high expression group was higher than that in lncRNA TSPEAR-AS2 low expression group. Our study may provide helpful information for fatty acid metabolism targeting therapies in CRC.

BackgroundA detailed means of prognostic stratification in patients with non-small cell lung cancer (NSCLC) is urgently needed to support individualized treatment plans. Recently, microRNAs (miRNAs) have been used as biomarkers due to their previously reported prognostic roles in cancer. This study aimed to construct an immune-related miRNA signature that effectively predicts NSCLC patient prognosis.MethodsThe miRNAs and mRNA expression and mutation data of NSCLC was obtained from The Cancer Genome Atlas (TCGA). Immune-associated miRNAs were identified using immune scores calculated by the ESTIMATE algorithm. LASSO-penalized multivariate survival models were using for development of a tumor immune-related miRNA signature (TIM-Sig), which was evaluated in several public cohorts from the Gene Expression Omnibus (GEO) and the CellMiner database. The miRTarBase was used for constructing the miRNA-target interactions.ResultsThe TIM-Sig, including 10 immune-related miRNAs, was constructed and successfully predicted overall survival (OS) in the validation cohorts. TIM-Sig score negatively correlated with CD8+ T cell infiltration, IFN-γ expression, CYT activity, and tumor mutation burden. The correlation between TIM-Sig score and genomic mutation and cancer chemotherapeutics was also evaluated. A miRNA-target network of 10 miRNAs in TIM-Sig was constructed. Further analysis revealed that these target genes showed prognostic value in both lung squamous cell carcinoma and adenocarcinoma.ConclusionsWe concluded that the immune-related miRNAs demonstrated a potential value in clinical prognosis.

BackgroundApigenin, as a natural flavonoid, has low intrinsic toxicity and has potential pharmacological effects against hepatocellular carcinoma (HCC). However, the molecular mechanisms involving microRNAs (miRNAs) and their target genes regulated by apigenin in the treatment of HCC have not been addressed.ObjectiveIn this study, the molecular mechanisms of apigenin involved in the prevention and treatment of HCC were explored in vivo and in vitro using miRNA transcriptomic sequencing to determine the basis for the clinical applications of apigenin in the treatment of HCC.MethodsThe effects of apigenin on the proliferation, cell cycle progression, apoptosis, and invasion of human hepatoma cell line Huh7 and Hep3B were studied in vitro, and the effects on the tumorigenicity of Huh7 cells were assessed in vivo. Then, a differential expression analysis of miRNAs regulated by apigenin in Huh7 cells was performed using next-generation RNA sequencing and further validated by qRT-PCR. The potential genes targeted by the differentially expressed miRNAs were identified using a curated miRTarBase miRNA database and their molecular functions were predicted using Gene Ontology and KEGG signaling pathway analysis.ResultsCompared with the control treatment group, apigenin significantly inhibited Huh7 cell proliferation, cell cycle, colony formation, and cell invasion in a concentration-dependent manner. Moreover, apigenin reduced tumor growth, promoted tumor cell necrosis, reduced the expression of Ki67, and increased the expression of Bax and Bcl-2 in the xenograft tumors of Huh7 cells. Bioinformatics analysis of the miRNA transcriptome showed that hsa-miR-24, hsa-miR-6769b-3p, hsa-miR-6836-3p, hsa-miR-199a-3p, hsa-miR-663a, hsa-miR-4739, hsa-miR-6892-3p, hsa-miR-7107-5p, hsa-miR-1273g-3p, hsa-miR-1343, and hsa-miR-6089 were the most significantly up-regulated miRNAs, and their key gene targets were MAPK1, PIK3CD, HRAS, CCND1, CDKN1A, E2F2, etc. The core regulatory pathways of the up-regulated miRNAs were associated with the hepatocellular carcinoma pathway. The down-regulated miRNAs were hsa-miR-181a-5p and hsa-miR-148a-3p, and the key target genes were MAPK1, HRAS, STAT3, FOS, BCL2, SMAD2, PPP3CA, IFNG, MET, and VAV2, with the core regulatory pathways identified as proteoglycans in cancer pathway.ConclusionApigenin can inhibit the growth of HCC cells, which may be mediated by up-regulation or down-regulation of miRNA molecules and their related target genes.

Background: Leptomeningeal metastasis (LM) has frequently been observed in patients with lung adenocarcinoma. So far, its diagnosis and disease course monitoring are still extremely difficult. Moreover, there is no effective treatment regimen for LM due to a lack knowledge on the molecular mechanism of LM. This study aimed to identify LM-related cerebrospinal fluid (CSF) miRNAs, which have potential value for diagnosing and monitoring LM and exploring the molecular mechanism. Methods: CSF miRNAs were screened and verified by microarray analysis and quantitative real-time PCR (qRT-PCR) in LM patients with lung adenocarcinoma and non-LM controls, and the diagnostic performance of candidate miRNAs was evaluated. Then, candidate miRNAs in matched CSF samples from LM patients at diagnosis, after initial therapy, at relapse, and after salvage therapy, were analyzed to assess the relationship between CSF miRNAs and LM disease course. The effect of candidate miRNAs on proliferation, invasion, and migration of lung adenocarcinoma cell lines was assessed. The targeted genes of the candidate miRNA were predicted by TargetScan, miRDB, and miRTarbase online analysis tools. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the functional categories of predicted target genes. Results: CSF miR-7975, miR-7977, and miR-7641 were screened and verified to be statistically significantly up-regulated in LM patients compared to non-LM controls. The three miRNAs, when combined, exhibited optimal diagnostic performance. Longitudinal data of CSF miR-7975 and miR-7977 correlated well with clinical courses of LM. Overexpression of miR-7977 promoted proliferation, migration, and invasion of lung adenocarcinoma cells. Moreover, 385 targeted genes of miR-7977 were predicted and were involved in various pathways related to cancer metastasis. Conclusions: This study offers insights for future research of CSF miRNAs as robust tools for diagnosing and monitoring LM. It also reveals a novel pathway for exploration of underlying mechanisms of LM.

Although huge progress has been made in therapeutics against hepatocellular carcinoma (HCC) over the decades, the prognosis of this lethal disease remains poor. To find out risk factors for HCC-related outcome and better predict the prognosis, there is an unmet need to identify novel biomarkers of HCC. Accumulating evidence suggests that circRNAs play pivotal roles in carcinogenesis of several malignancies. In this study, we analyzed two datasets (GSE 94508 and GSE 97332) to examine differentially expressed circRNAs markedly related to HCC pathogenesis. Using Limma package in R and WGCNA analysis, hsa_circ_0000517 was significantly up-regulated in HCC (adjusted P < 0.01). Thereafter, a hsa_circ_0000517-related regulatory network was built based on application of databases including CSCD, TargetScan, miRDB, and miRTarBase. We uncovered the potential function of hsa_circ_0000517 through bioinformatics approaches, such as PPI network, GO, and KEGG pathway analyses. Specifically, functional analysis unveiled that hsa_circ_0000517 was likely to regulate the MAPK and Ras pathway through sponging several miRNAs and having an impact on the expression of TP53, MYC, and AKT1. To verify our initial finding, the expression of hsa_circ_0000517 in 60 HCC patients was detected by qRT-PCR and the expression in cancer tissues was higher compared with the paracarcinoma tissues. Survival analysis suggests high hsa_circ_0000517 expression was associated with adverse prognosis in HCC patients. Furthermore, this circRNA was significantly up-regulated in worse TNM stage, consistent with the progressive-stage-specific characteristic of circRNAs. A prognostic nomogram built on AFP and has_circ_0000517 showed significant diagnostic value. In all, we concluded that hsa_circ_0000517, a promising molecular in underlying mechanism of HCC, is a potent valuable biomarker for prognosis prediction.