An 11-lncRNA expression could be potential prognostic biomarkers in head and neck squamous cell carcinoma

The aim of our study is to construct the competing endogenous RNA (ceRNA) network of head and neck squamous cell carcinoma (HNSCC) and identify key long noncoding RNAs (lncRNAs) to predict prognosis. The genes whose expression were differentially in HNSCC and normal tissues were explored by the Cancer Genome Atlas database. The ceRNA network was constructed by the Cytoscape software. The lncRNAs which could estimate the overall survival were explored from Cox proportional hazards regression. There are 1997, 589, and 82 mRNAs, lncRNAs, and miRNAs whose expression were statistically significant different, respectively. Then, the network between miRNA and mRNA or miRNA and lncRNA was constructed by miRcode, miRDB, TargetScan, and miRanda. Five mRNAs, 10 lncRNAs, and 3 miRNAs were associated with overall survival. Then, 11-lncRNAs were found to be prognostic factors. Therefore, our research analyzed the potential signature of novel 11-lncRNA as candidate prognostic biomarker from the ceRNA network for patients with HNSCC.     

Integrated analysis of co‐expression and ceRNA network identifies five lncRNAs as prognostic markers for breast cancer

Long non‐coding RNAs (lncRNAs), which competitively bind miRNAs to regulate target mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for breast cancer. LncRNA, mRNA and miRNA expression profiles of breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all miRNAs to perform weighted gene co‐expression network analysis. The correlation between modules and clinical information of breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a ceRNA network of breast cancer. Additionally, the standard Kaplan‐Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and miRNAs co‐expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of miRNAs, our constructed ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2‐AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of breast cancer and provided novel insights into the use of breast cancer drugs and prognosis.     

Identification and development of long non‐coding RNA‐associated regulatory network in colorectal cancer

Colorectal cancer (CRC) is one of the leading causes of cancer‐associated death globally. Long non‐coding RNAs (lncRNAs) have been identified as micro RNA (miRNA) sponges in a competing endogenous RNA (ceRNA) network and are involved in the regulation of mRNA expression. This study aims to construct a lncRNA‐associated ceRNA network and investigate the prognostic biomarkers in CRC. A total of 38 differentially expressed (DE) lncRNAs, 23 DEmiRNAs and 27 DEmRNAs were identified by analysing the expression profiles of CRC obtained from The Cancer Genome Atlas (TCGA). These RNAs were chosen to develop a ceRNA regulatory network of CRC, which comprised 125 edges. Survival analysis showed that four lncRNAs, six miRNAs and five mRNAs were significantly associated with overall survival. A potential regulatory axis of ADAMTS9‐AS2/miR‐32/PHLPP2 was identified from the network. Experimental validation was performed using clinical samples by quantitative real‐time PCR (qRT‐PCR), which showed that expression of the genes in the axis was associated with clinicopathological features and the correlation among them perfectly conformed to the ‘ceRNA theory’. Overexpression of ADAMTS9‐AS2 in colon cancer cell lines significantly inhibited the miR‐32 expression and promoted PHLPP2 expression, while ADAMTS9‐AS2 knockdown had the opposite effects. The constructed novel ceRNA network may provide a comprehensive understanding of the mechanisms of CRC carcinogenesis. The ADAMTS9‐AS2/miR‐32/PHLPP2 regulatory axis may serve as a potential therapeutic target for CRC.     

Comprehensive analysis of a ceRNA network reveals potential prognostic cytoplasmic lncRNAs involved in HCC progression

The aberrant expression of long noncoding RNAs (lncRNAs) has drawn increasing attention in the field of hepatocellular carcinoma (HCC) biology. In the present study, we obtained the expression profiles of lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) in 371 HCC tissues and 50 normal tissues from The Cancer Genome Atlas (TCGA) and identified hepatocarcinogenesis-specific differentially expressed genes (DEGs, log fold change ≥ 2, FDR < 0.01), including 753 lncRNAs, 97 miRNAs, and 1,535 mRNAs. Because the specific functions of lncRNAs are closely related to their intracellular localizations and because the cytoplasm is the main location for competitive endogenous RNA (ceRNA) action, we analyzed not only the interactions among these DEGs but also the distributions of lncRNAs (cytoplasmic, nuclear or both). Then, an HCC-associated deregulated ceRNA network consisting of 37 lncRNAs, 10 miRNAs, and 26 mRNAs was constructed after excluding those lncRNAs located only in the nucleus. Survival analysis of this network demonstrated that 15 lncRNAs, 3 miRNAs, and 16 mRNAs were significantly correlated with the overall survival of HCC patients (p < 0.01). Through multivariate Cox regression and lasso analysis, a risk score system based on 13 lncRNAs was constructed, which showed good discrimination and predictive ability for HCC patient survival time. This ceRNA network-construction approach, based on lncRNA distribution, not only narrowed the scope of target lncRNAs but also provided specific candidate molecular biomarkers for evaluating the prognosis of HCC, which will help expand our understanding of the ceRNA mechanisms involved in the early development of HCC.     

Construction of a paclitaxel-related competitive endogenous RNA network and identification of a potential regulatory axis in pancreatic cancer

BackgroundIncreasing numbers of studies have elucidated the role of competitive endogenous RNA (ceRNA) networks in carcinogenesis. However, the potential role of the paclitaxel-related ceRNA network in the innate mechanism and prognosis of pancreatic cancer has not been identified.MethodsComprehensive bioinformatics analyses were performed to identify drug-related miRNAs (DRmiRNAs), drug-related mRNAs (DRmRNAs) and drug-related lncRNAs (DRlncRNAs) and construct a ceRNA network. The ssGSEA and CIBERSORT algorithms were utilized for immune cell infiltration analysis. Additionally, we validated our paclitaxel-related ceRNA regulatory axis at the gene expression level; functional experiments were conducted to explore the biological functions of the key genes.ResultsA total of 182 mRNAs, 13 miRNAs, and 53 lncRNAs were confirmed in the paclitaxel-related ceRNA network. In total, 6 mRNAs, 4 miRNAs, and 6 lncRNAs were identified to establish a risk signature and exhibited optimal prognostic effects. The mRNA signature can predict the abundance of immune cell infiltration and the sensitivity of different chemotherapeutic drugs and may also have a guiding effect in immune checkpoint therapy. A potential PART1/hsa-mir-21/SCRN1 axis was confirmed according to the ceRNA theory and was verified by qPCR. The results indicated that PART1 knockdown markedly increased hsa-mir-21 expression but inhibited SCRN1 expression, weakening the proliferation and migration abilities.ConclusionsWe hypothesized that the paclitaxel-related ceRNA network strongly influences the innate mechanism, prognosis, and immune infiltration of pancreatic cancer. Our risk signatures can accurately predict survival outcomes and provide a clinical basis.     

Comprehensive analysis of lncRNA–miRNA–mRNA during proliferative phase of rat liver regeneration

This study aims to reveal the regulatory mechanism of lncRNAs–miRNAs–mRNAs network during the proliferative phase of liver regeneration (LR). High-throughput sequencing technology was performed, and a total of 1,738 differentially expressed lncRNAs (DE lncRNAs), 167 known differentially expressed miRNAs (DE miRNAs), and 2,727 differentially expressed mRNAs were identified. Then, the target DE lncRNAs and DE mRNAs regulated by the same miRNAs were screened and a ceRNA regulatory network containing 32 miRNAs, 107 lncRNAs, and 270 mRNAs was constructed. Insulin signaling pathway, pyrimidine metabolism, axon guidance, carbohydrate digestion and absorption, and pyruvate metabolism were significantly enriched in the network. Through literature review and the regulatory relationship between lncRNAs and miRNAs, nine core lncRNAs were identified, which might play important roles during the proliferative phase of rat LR. This study analyzed lncRNA–miRNA–mRNA regulatory network for the first time during the proliferative phase of rat LR, providing clues for exploring the mechanism of LR and the treatment of liver diseases.     

A comprehensive study of construction and analysis of competitive endogenous RNA networks in lung adenocarcinoma

BackgroundLong noncoding RNAs (lncRNAs) have gain increasing attention in lung adenocarcinoma. In this study, we aimed at constructing and analyzing the lncRNAs and the related proteins based competitive endogenous RNA (ceRNA) network.MethodsRNA expression data of lung adenocarcinoma were extracted from the TCGA database. Differentially expressed (DE) lncRNAs, messenger RNAs (mRNAs) and microRNAs (miRNAs) were identified and then a DElncRNA-DEmiRNA-DEmRNA ceRNA network was constructed for lung adenocarcinoma. We also analyzed the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the DEgenes. Kaplan-Meier survival curves were also been further utilized for exploring the prognostic factors.ResultsAfter compared and calculated lncRNA, mRNA and miRNA expression profiles between lung adenocarcinoma and normal samples, 1709 differential expressed lncRNAs, 2554 differential expressed mRNAs and 116 differential expressed miRNAs were finally identified. Afterwards, a lncRNA mediated ceRNA network was constructed, according to the interactions among 544 pairs of DElncRNA-DEmiRNA relationships and 47 pairs of DEmiRNA-DEmRNA relationships. As for the survival analyses, we found 10 DElncRNAs, 25 DEmRNAs and 7 miRNAs have statistically prognostic significance for overall survival, respectively.ConclusionsThis study provides meaningful information for deeper understanding the underlying molecular mechanism of lung adenocarcinoma and for evaluating prognosis, which could monitor recurrence, guide clinical treatment drugs and subsequent related researches.     

Construction of lncRNA-associated ceRNA networks to identify prognostic lncRNA biomarkers for glioblastoma

Long noncoding RNAs (lncRNAs) serve as competitive endogenous RNAs (ceRNAs) that play significant regulatory roles in the pathogenesis of tumors. However, the role of lncRNAs, especially the lncRNA-related ceRNA regulatory network, in glioblastoma (GBM) has not been fully elucidated. The goal of the current study was to construct lncRNA-microRNA-mRNA-related ceRNA networks for further investigation of their mechanism of action in GBM. We downloaded data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases and identified differential lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) associated with GBM. A ceRNA network was constructed and analyzed to examine the relationship between lncRNAs and patients’ overall survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGGs) were used to analyze the related mRNAs to indirectly explain the mechanism of action of lncRNAs. The potential effective drugs for the treatment of GBM were identified using the connectivity map (CMap). After integrated analysis, we obtained a total of 210 differentially expressed lncRNAs, 90 differentially expressed miRNAs, and 2508 differentially expressed mRNAs (DEmRNAs) from the TCGA and GEO databases. Using these differential genes, we constructed a lncRNA-associated ceRNA network. Six lncRNAs in the ceRNA network were associated with the overall survival of patients with GBM. Through KEGG analysis, it was found that the DEmRNAs involved in the network are related to cancer-associated pathways, for instance, mitogen-activated protein kinase and Ras signaling pathways. CMap analysis revealed four small-molecule compounds that could be used as drugs for the treatment of GBM. In this study, a multi-database joint analysis was used to construct a lncRNA-related ceRNA network to help identify the regulatory functions of lncRNAs in the pathogenesis of GBM.     

Genome-wide identification of a competing endogenous RNA network in cholangiocarcinoma

Cholangiocarcinoma (CCA) is the second widespread liver tumor with relatively poor survival. Increasing evidence in recent studies showed long noncoding RNAs (lncRNAs) exert a crucial impact on the development and progression of CCA based on the mechanism of competing endogenous RNAs (ceRNAs). However, functional roles and regulatory mechanisms of lncRNA-regulated ceRNA in CCA, are only partially understood. The expression profile of messenger RNAs (mRNAs), lncRNAs, and microRNAs (miRNAs) downloaded from The Cancer Genome Atlas were comprehensively investigated. Differential expression of these three types of RNA between CCA and corresponding precancerous tissues were screened out for further analysis. On the basis of interactive information generated from miRDB, miRTarBase, TargetScan, and miRcode public databases, we then constructed an mRNA-miRNA-lncRNA regulatory network. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were conducted to identify the biological function of the ceRNA network involved in CCA. As a result, 2883 mRNAs, 136 miRNAs, and 993 lncRNAs were screened out as differentially expressed RNAs in CCA. In addition, a ceRNA network in CCA was constructed, composing of 50 up and 27 downregulated lncRNAs, 14 up and 7 downregulated miRNAs, 29 up and 25 downregulated mRNAs. Finally, gene set enrichment and pathway analysis indicated our CCA-specific ceRNA network was related with cancer-related pathway and molecular function. In conclusion, our research identified a novel lncRNA-related ceRNA network in CCA, which might act as a potential therapeutic target for patients with CCA.     

Analysis of competing endogenous RNA network identifies a poorly differentiated cancer-specific RNA signature for hepatocellular carcinoma

Plenty of evidence has suggested that long noncoding RNAs (lncRNAs) play a vital role in competing endogenous RNA (ceRNA) networks. Poorly differentiated hepatocellular carcinoma (PDHCC) is a malignant phenotype. This paper aimed to explore the effect and the underlying regulatory mechanism of lncRNAs on PDHCC as a kind of ceRNA. Additionally, prognosis prediction was assessed. A total of 943 messenger RNAs (mRNAs), 86 miRNAs, and 468 lncRNAs that were differentially expressed between 137 PDHCCs and 235 well-differentiated HCCs were identified. Thereafter, a ceRNA network related to the dysregulated lncRNAs was established according to bioinformatic analysis and included 29 lncRNAs, 9 miRNAs, and 96 mRNAs. RNA-related overall survival (OS) curves were determined using the Kaplan-Meier method. The lncRNA ARHGEF7-AS2 was markedly correlated with OS in HCC (P = .041). Moreover, Cox regression analysis revealed that patients with low ARHGEF7-AS2 expression were associated with notably shorter survival time (P = .038). In addition, the area under the curve values of the lncRNA signature for 1-, 3-, and 5-year survival were 0.806, 0.741, and 0.701, respectively. Furthermore, a lncRNA nomogram was established, and the C-index of the internal validation was 0.717. In vitro experiments were performed to demonstrate that silencing ARHGEF7-AS2 expression significantly promoted HCC cell proliferation and migration. Taken together, our findings shed more light on the ceRNA network related to lncRNAs in PDHCC, and ARHGEF7-AS2 may be used as an independent biomarker to predict the prognosis of HCC.     

Integrated analysis of ceRNA network and tumor-infiltrating immune cells in esophageal cancer

Background: Esophageal cancer (ESCA) is one of the most commonly diagnosed cancers in the world. Tumor immune microenvironment is closely related to tumor prognosis. The present study aimed at analyzing the competing endogenous RNA (ceRNA) network and tumor-infiltrating immune cells in ESCA.Methods: The expression profiles of mRNAs, lncRNAs, and miRNAs were downloaded from the Cancer Genome Atlas database. A ceRNA network was established based on the differentially expressed RNAs by Cytoscape. CIBERSORT was applied to estimate the proportion of immune cells in ESCA. Prognosis-associated genes and immune cells were applied to establish prognostic models basing on Lasso and multivariate Cox analyses. The survival curves were constructed with Kaplan–Meier method. The predictive efficacy of the prognostic models was evaluated by the receiver operating characteristic (ROC) curves.Results: The differentially expressed mRNAs, lncRNAs, and miRNAs were identified. We constructed the ceRNA network including 23 lncRNAs, 19 miRNAs, and 147 mRNAs. Five key molecules (HMGB3, HOXC8, HSPA1B, KLHL15, and RUNX3) were identified from the ceRNA network and five significant immune cells (plasma cells, T cells follicular helper, monocytes, dendritic cells activated, and neutrophils) were selected via CIBERSORT. The ROC curves based on key genes and significant immune cells all showed good sensitivity (AUC of 3-year survival: 0.739, AUC of 5-year survival: 0.899, AUC of 3-year survival: 0.824, AUC of 5-year survival: 0.876). There was certain correlation between five immune cells and five key molecules.Conclusion: The present study provides an effective bioinformatics basis for exploring the potential biomarkers of ESCA and predicting its prognosis.     

Integrative analysis of competing endogenous RNA networks reveals the functional lncRNAs in heart failure

Heart failure has become one of the top causes of death worldwide. It is increasing evidence that lncRNAs play important roles in the pathology processes of multiple cardiovascular diseases. Additionally, lncRNAs can function as ceRNAs by sponging miRNAs to affect the expression level of mRNAs, implicating in numerous biological processes. However, the functional roles and regulatory mechanisms of lncRNAs in heart failure are still unclear. In our study, we constructed a heart failure‐related lncRNA‐mRNA network by integrating probe re‐annotation pipeline and miRNA‐target interactions. Firstly, some lncRNAs that had the central topological features were found in the heart failure‐related lncRNA‐mRNA network. Then, the lncRNA‐associated functional modules were identified from the network, using bidirectional hierarchical clustering. Some lncRNAs that involved in modules were demonstrated to be enriched in many heart failure‐related pathways. To investigate the role of lncRNA‐associated ceRNA crosstalks in certain disease or physiological status, we further identified the lncRNA‐associated dysregulated ceRNA interactions. And we also performed a random walk algorithm to identify more heart failure‐related lncRNAs. All these lncRNAs were verified to show a strong diagnosis power for heart failure. These results will help us to understand the mechanism of lncRNAs in heart failure and provide novel lncRNAs as candidate diagnostic biomarkers or potential therapeutic targets.     

Molecular characterization of lung cancer: A two-miRNA prognostic signature based on cancer stem-like cells related genes

Lung cancer is one of the deadliest cancers worldwide. To increase the survival rate of lung cancer, it is necessary to explore specific prognosis markers. More and more evidence finds that noncoding RNA is closely associated with the survival of lung cancer, and cancer stem cells (CSCs) also play a significant role in the progress of lung cancer. The objective of this study is to find CSLCs genes that affect the prognosis of lung cancer. The differential expression of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), messenger RNAs (mRNAs) in the Cancer Genome Atlas (TCGA) database and differential expression data from microarray of CD326⁺ and CD326⁻ A549 cell are intersected to identify stable and consistent expression genes (2 lncRNAs, 15 miRNAs, and 134 mRNAs). The intersection of lncRNAs and miRNAs is analyzed by univariate and multivariate Cox regression to obtained prognostic genes. Two miRNAs (miR-30b-5p and miR-29c-3p) are significantly correlated with the overall survival rate. Then using these two miRNAs to construct a risk score model as a prognosis signature of lung cancer. Subsequently, we analyzed the association between two miRNAs and clinical information of lung cancer patients, of which T stage, Neoplasm cancer and risk score (P < .05) can be used as independent prognostic indicators of lung cancer. Finally, target genes of 2 miRNAs and 134 mRNAs were annotated with Gene Ontology and analyzed with Kyoto Encyclopedia of Genes and Genomes pathway, and verified with the GEO database. In summary, this study illustrates the role of miRNAs in the promotion of lung cancer by CSCs, which is important to find molecular biomarkers of lung cancer.     

The exploration of new therapeutic targets for HPV-negative head and neck squamous cell cancer through the construction of a ceRNA network and immune microenvironment analysis

Previous studies have shown that human papillomavirus (HPV)-negative patients with head and neck squamous cell cancer (HNSCC) suffer from an unsatisfactory prognosis. Long noncoding RNAs (lncRNAs) have been verified to participate in many biological processes, including regulating gene expression as competing endogenous RNAs (ceRNAs), while few studies focused the ceRNA network regulation mechanism in patients with HPV-negative HNSCC tumor. Meanwhile, the immune microenvironment may be critical in the development and prognosis of HPV-negative tumors. Our study aimed to further investigate the pathogenesis and potential biomarkers for the diagnosis, therapy and prognosis of HPV-negative HNSCC through a ceRNA network. Comprehensively analyzing the sequencing data of lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) in The Cancer Genome Atlas HNSCC dataset, we constructed a differentially expressed ceRNA network containing 131 lncRNAs, 35 miRNAs and 162 mRNAs. Then, survival analysis in the network was cited to explore the prognostic biomarkers. Eight mRNAs, nine lncRNAs, and one miRNA were identified to be associated with prognosis. Neuropilin (NRP) binding function, retinoid X receptor (RXR) binding, and the vascular endothelial growth factor (VEGF) signaling pathway were associated with the enrichment analysis, and they also related to the immune microenvironment. Combined with the analysis of the immune microenvironment differences, we obtained new targeted therapies using an RXR agonist, or a combination of the VEGF monoclonal antibody and an NRP antagonist, which may provide a promising future for HPV-negative HNSCC patients.     

急性髓系白血病mRNA与非编码RNA差异表达谱及CeRNA调控网络分析

利用GEO数据库(gene expression omnibus database)通过生物信息学分析方法探讨急性髓系白血病(acute myelogenous leukemia,AML)的发病机制。检索GEO数据库中AML相关芯片数据集GSE142698、GSE142699和GSE96535。利用GEO2R分析得到差异mRNAs、miRNAs以及差异lncRNAs。利用在线生物信息学分析工具DAVID对差异mRNAs进行GO富集分析和KEGG通路分析。利用miRWalk数据库预测AML相关miRNAs的靶向mRNAs,利用Spongescan数据库预测AML相关miRNAs的靶向lncRNAs,构建lncRNA-miRNA-mRNA竞争性内源RNA （competing endogenous RNA,ceRNA）调控网络。共筛选出29个显著差异mRNAs、70个显著差异miRNAs和20 005个显著差异lncRNAs。GO富集分析和KEGG通路分析显示,差异表达基因主要涉及蛋白磷酸化、细胞分裂、细胞增殖的负调控、基因表达的正向调节、周期蛋白依赖的丝氨酸/苏氨酸激酶活性的调节等生物过程以及细胞周期、细胞衰老、癌症通路、PI3K-Akt通路等信号通路。将miRWalk数据库预测的靶向mRNAs与差异mRNAs取交集,Spongescan数据库预测的靶向lncRNAs与差异lncRNAs取交集,分别确定了25个mRNAs、6个lncRNAs参与AML相关ceRNA调控网络的构建。结果表明,lncRNAs可能作为关键的ceRNA,通过调控miRNA和相关靶基因参与AML的发生与发展,研究结果为AML诊断和治疗的分子生物学研究提供了新的依据。     

竞争性内源RNA:一种全新的基因表达调控模式

竞争性内源RNA(ceRNA)假说是一种全新的基因表达调控模式:mRNA、假基因转录物和长链非编码RNA等转录物通过microRNA应答元件竞争结合相同的microRNA来调控各自的表达水平,从而影响细胞的功能.迄今为止,多家实验室已从生物信息学、细胞生物学和动物实验等层面验证了该假说.本文追溯了ceRNA假说提出的历程,讨论了ceRNA调控网络的影响因素,并提出了一些有待进一步完善的内容.ceRNA假说大大拓展了人类基因组中功能遗传信息的范畴,也为解析一些人类疾病发生的机制提供了新线索.     

Evaluation of serum exosomal LncRNA‐based biomarker panel for diagnosis and recurrence prediction of bladder cancer

Exosomes are small membrane vesicles released by many cells. These vesicles can mediate cellular communications by transmitting active molecules including long non‐coding RNAs (lncRNAs). In this study, our aim was to identify a panel of lncRNAs in serum exosomes for the diagnosis and recurrence prediction of bladder cancer (BC). The expressions of 11 candidate lncRNAs in exosome were investigated in training set (n = 200) and an independent validation set (n = 320) via quantitative real‐time PCR. A three‐lncRNA panel (PCAT‐1, UBC1 and SNHG16) was finally identified by multivariate logistic regression model to provide high diagnostic accuracy for BC with an area under the receiver‐operating characteristic curve (AUC) of 0.857 and 0.826 in training set and validation set, respectively, which was significantly higher than that of urine cytology. The corresponding AUCs of this panel for patients with Ta, T1 and T2‐T4 were 0.760, 0.827 and 0.878, respectively. In addition, Kaplan‐Meier analysis showed that non‐muscle‐invasive BC (NMIBC) patients with high UBC1 expression had significantly lower recurrence‐free survival (P = 0.01). Multivariate Cox analysis demonstrated that UBC1 was independently associated with tumour recurrence of NMIBC (P = 0.018). Our study suggested that lncRNAs in serum exosomes may serve as considerable diagnostic and prognostic biomarkers of BC.     

Competing endogenous RNA network and prognostic nomograms for hepatocellular carcinoma patients who underwent R0 resection

The prognosis of hepatocellular carcinoma (HCC) after R0 resection is unsatisfactory due to the high rate of recurrence. In this study, we investigated the recurrence-related RNAs and the underlying mechanism. The long noncoding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) expression data and clinical information of 247 patients who underwent R0 resection patients with HCC were obtained from The Cancer Genome Atlas. Comparing the 1-year recurrence group (n = 56) with the nonrecurrence group (n = 60), we detected 34 differentially expressed lncRNAs (DElncRNAs), five DEmiRNAs, and 216 DEmRNAs. Of these, three DElncRNAs, hsa-mir-150-5p, and 11 DEmRNAs were selected for constructing the competing endogenous RNA (ceRNA) network. Next, two nomogram models were constructed based separately on the lncRNAs and mRNAs that were further selected by Cox and least absolute shrinkage and selection operator regression analysis. The two nomogram models that showed a high prediction accuracy for disease-free survival with the concordance indexes at 0.725 and 0.639. Further functional enrichment analysis of DEmRNAs showed that the mRNAs in the ceRNA network and nomogram models were associated with immune pathways. Hence, we constructed a hsa-mir-150-5p-centric ceRNA network and two effective nomogram prognostic models, and the related RNAs may be useful as potential biomarkers for predicting recurrence in patients with HCC.