An integrated analysis for long noncoding RNAs and microRNAs with the mediated competing endogenous RNA network in papillary renal cell carcinoma

A Differential Transcriptional Regulome Approach to Unpack Cancer Biology: Insights on Renal Cell Carcinoma Subtypes

Cancer research calls for new approaches that account for the regulatory complexities of biology. We present, in this study, the differential transcriptional regulome (DIFFREG) approach for the identification and prioritization of key transcriptional regulators and apply it to the case of renal cell carcinoma (RCC) biology. Of note, RCC has a poor prognosis and the biomarker and drug discovery studies to date have tended to focus on gene expression independent from mutations and/or post-translational modifications. DIFFREG focuses on the differential regulation between transcription factors (TFs) and their target genes rather than differential gene expression and integrates transcriptome profiling with the human transcriptional regulatory network to analyze differential gene regulation between healthy and RCC cases. In this study, RNA-seq tissue samples (n = 1020) from the Cancer Genome Atlas (TCGA), including healthy and tumor subjects, were integrated with a comprehensive human TF-gene interactome dataset (1122603 interactions between 1289 TFs and 25177 genes). Comparative analysis of DIFFREG profiles, consisting of perturbed TF-gene interactions, from three common subtypes (clear cell RCC, papillary RCC and chromophobe RCC) revealed subtype-specific alterations, supporting the hypothesis that these signatures in the transcriptional regulome profiles may be considered potential biomarkers that may play an important role in elucidating the molecular mechanisms of RCC development and translating knowledge about the genetic basis of RCC into the clinic. In addition, these indicators may help oncologists make the best decisions for diagnosis and prognosis management.

lncRNA PVT1 in the Pathogenesis and Clinical Management of Renal Cell Carcinoma

LncRNA PVT1 (plasmacytoma variant translocation 1) has become a staple of the lncRNA profile in patients with renal cell carcinoma (RCC). Common dysregulation in renal tumors outlines the essential role of PVT1 in the development of RCC. There is already a plethora of publications trying to uncover the cellular mechanisms of PVT1-mediated regulation and its potential exploitation in management of RCC. In this review, we summarize the literature focused on PVT1 in RCC and aim to synthesize the current knowledge on its role in the cells of the kidney. Further, we provide an overview of the lncRNA profiling studies that have identified a more or less significant association of PVT1 with the clinical behavior of RCC. Based on our search, we analyzed the 17 scientific papers discussed in this review that provide robust support for the indispensable role of PVT1 in RCC development and future personalized therapy.

Development of an Autophagy Score Signature for Predicting Overall Survival in Papillary Renal Cell Carcinoma

Background

Autophagy is considered to be closely associated with cancer, functioning as either an anticancer or procancer mechanism depending on the cancer stage. However, the prognostic value of autophagy on papillary renal cell carcinoma (pRCC) remains unclear. In this study, our purpose was to determine the autophagy-related mRNA signature to predict the overall survival of patients with pRCC.

Materials and Methods

A total of 284 patients with pathologic confirmed pRCC in The Cancer Genome Atlas (TCGA) dataset were recruited and included. We choose patients who have smoked less than 15 years but staging 3 or 4 (including nontobacco exposure) vs. more than 15 years but staging 1 or 2. Fourteen differentially expressed mRNAs were found with fold change > 2 and P value < 0.001 through limma package after making a pair between nontobacco exposure or less than 15 years and tobacco exposure more than 15 years by matchIt package.

Results

Six mRNAs were identified to be significantly associated with overall survival. Then, using a risk score based on the signature of these six mRNAs, we divided the patients into low-risk and high-risk groups with significantly different OS. Further multivariate Cox regression analyses revealed that the 6-mRNA signature was independent of age, TNM stage, and tumor type. In the present study, a novel 6-mRNA signature that is useful in survival prediction in pRCC patients was developed. If validated, this mRNA signature might assist in selecting high-risk subpopulation that needs more aggressive therapeutic intervention. The risk score involved in several cancer-related pathways was identified using gene set enrichment analysis.

Conclusion

We initially generated a six autophagy-related genes' signature, which correlates with AJCC N stage, tumor type, and pathological stage and independently predicts OS.

Comprehensive analysis of competing endogenous RNA network in Wilms tumor based on the TARGET database

Background

Wilms tumor (WT) was the most common malignant tumor of urinary system in children. With the advances in gene sequencing, research of molecular mechanism of WT tumor was gradually increasing. However, few studies have explored the influence of competing endogenous RNA (ceRNA) in WT. Accordingly, we aimed to explore the mechanisms of ceRNA co-expression network in WT.

Methods

A total of 6 non-tumor controls and 127 WT patients’ RNA-seq data combined with clinical data was acquired from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Differentially expressed lncRNA, miRNA and mRNA between WT tissues and normal tissues were analyzed using “edgeR” package in R software. Weighted gene co-expression network analysis (WGCNA) was utilized to construct the ceRNA co-expression network while Molecular Complex Detection (MCODE) algorithm was used to extract the pivotal sub-network. Function annotation of mRNA was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Survival analysis was then conducted based on long-rank test and Kaplan-Meier curves using the survival package.

Results

By applying the “edgeR” package in R, the transcriptome expression data of 127 WT tissues with 6 normal tissues were normalized. Moreover, 146 DElncRNAs, 62 DEmiRNAs, 287 DEmRNAs of them were involved in ceRNA network after applying WGCNA. According to MCODE, we identified that the interactions between LINC002253 (lncRNA) and TRIM71 (mRNA) was mediated by hsa-mir-301a and hsa-mir-301b (miRNA). Furthermore, we detected 13 DElncRNAs which were significantly associated with the progression of WT.

Conclusions

We used WGCNA method to construct the WT ceRNA network for the first time. TRIM71 was identified to be the most closely related genes involved in hub sub-network by MCDOE, suggesting it might act as a new drug target and prognostic factor based on our comprehensive results.

Identification of biomarkers in common chronic lung diseases by co-expression networks and drug-target interactions analysis

Background

asthma, chronic obstructive pulmonary disease (COPD), and idiopathic pulmonary fibrosis (IPF) are three serious pulmonary diseases that contain common and unique characteristics. Therefore, the identification of biomarkers that differentiate these diseases is of importance for preventing misdiagnosis. In this regard, the present study aimed to identify the disorders at the early stages, based on lung transcriptomics data and drug-target interactions.

Methods

To this end, the differentially expressed genes were found in each disease. Then, WGCNA was utilized to find specific and consensus gene modules among the three diseases. Finally, the disease-disease similarity was analyzed, followed by determining candidate drug-target interactions.

Results

The results confirmed that the asthma lung transcriptome was more similar to COPD than IPF. In addition, the biomarkers were found in each disease and thus were proposed for further clinical validations. These genes included RBM42, STX5, and TRIM41 in asthma, CYP27A1, GM2A, LGALS9, SPI1, and NLRC4 in COPD, ATF3, PPP1R15A, ZFP36, SOCS3, NAMPT, and GADD45B in IPF, LRRC48 and CETN2 in asthma-COPD, COL15A1, GIMAP6, and JAM2 in asthma-IPF and LMO7, TSPAN13, LAMA3, and ANXA3 in COPD-IPF. Finally, analyzing drug-target networks suggested anti-inflammatory candidate drugs for treating the above mentioned diseases.

Conclusion

In general, the results revealed the unique and common biomarkers among three chronic lung diseases. Eventually, some drugs were suggested for treatment purposes.

A cluster of long non-coding RNAs exhibit diagnostic and prognostic values in renal cell carcinoma

Kidney cancer ranked in the top 10 for both men and women in the estimated numbers of new cancer cases in the United States in 2018. Targeted therapies have recently been administered to patients with clear cell renal cell carcinoma (ccRCC), but the overall survival of patients at the terminal stage of the disease has not been as good as expected. It is therefore necessary to uncover efficient biomarkers for early diagnosis, and to clarify the molecular mechanisms underlying ccRCC progression and metastasis. Increased evidence has shown that long non-coding RNAs (lncRNAs) play important roles during tumor progression. In this study, 10 candidate lncRNAs with diagnostic and prognostic values in ccRCC were identified: IGFL2-AS1, AC023043.1, AP000439.2, AC124854.1, AL355102.4, TMEM246-AS1, AL133467.3, ZNF582-AS1, LINC01510 and PSMG3-AS1. Enrichment analysis revealed metabolic and functional pathways, which may be closely associated with kidney cancer tumorigenesis. Six representative processes were summarized, namely glycolysis, amino acid metabolism, lipid synthesis, reductive carboxylation, nucleotide metabolism, transmembrane transport and signal transduction. In combination, the present results provided prognostic and diagnostic biomarkers for ccRCC and might pave the way for targeted intervention and molecular therapies in the future.

Current Concepts of Non-Coding RNAs in the Pathogenesis of Non-Clear Cell Renal Cell Carcinoma

Renal cell carcinoma (RCC) is a relatively rare malignancy of the urinary tract system. RCC is a heterogenous disease in terms of underlying histology and its associated underlying pathobiology, prognosis and treatment schedule. The most prevalent histological RCC subtype is clear-cell renal cell carcinoma (ccRCC), accounting for about 70-80% of all RCCs. Though the pathobiology and treatment schedule for ccRCC are well-established, non-ccRCC subtypes account for 20%-30% of RCC altogether, and their underlying molecular biology and treatment options are poorly defined. The class of non-coding RNAs-molecules that are generally not translated into proteins-are new cancer drivers and suppressors in all types of cancer. Of these, small non-coding microRNAs (miRNAs) contribute to carcinogenesis by regulating posttranscriptional gene silencing. Additionally, a growing body of evidence supports the role of long non-coding RNAs (lncRNAs) in cancer development and progression. Most studies on non-coding RNAs in RCC focus on clear-cell histology, and there is a relatively limited number of studies on non-ccRCC subtypes. The aim of this review is to give an overview of the current knowledge regarding the role of non-coding RNAs (including short and long non-coding RNAs) in non-ccRCC and to highlight possible implications as diagnostic, prognostic and predictive biomarkers.

Investigation of miRNA- and lncRNA-mediated competing endogenous RNA network in cholangiocarcinoma

Cholangiocarcinoma (CCA) is a biliary malignancy which is prone to lymphatic metastasis and has a high mortality rate. This disease lacks effective therapeutic targets and prognostic molecular biomarkers. The aim of the current study was to investigate differentially expressed genes and elucidate their association with CCA and the underlying mechanisms of action. mRNAs, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) obtained from 36 CCA samples and nine normal samples from The Cancer Genome Atlas were integrated. Subsequently, 1,095 differentially expressed (DE) mRNAs and 75 DE miRNAs were identified using a threshold of |log2 fold change|>2 and an adjusted P<0.01. Weighted gene co-expression network analysis was used to identify the DEmRNAs that could be key target genes in CCA. A total of 12 hub DEmRNAs were identified as targetable genes. Furthermore, the hub DEmRNAs-DElncRNAs pairs were identified using the miRTarBase and miRcode databases. Cytoscape software was used to construct and visualize the protein-protein interactions and the competing endogenous RNA network. Survival time analysis and correlation analysis were used to further evaluate the hub genes. The results obtained in the current study suggested that spalt like transcription factor 3 and OPCML intronic transcript 1 may serve an important role in the development and progression of CCA.

Construction and integrated analysis of crosstalking ceRNAs networks in laryngeal squamous cell carcinoma

Background

Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumours of the head and neck. Recent evidence has demonstrated that lncRNAs play important roles in tumour progression and could be used as biomarkers for early diagnosis, prognosis, and potential therapeutic targets. The "competitive endogenous RNA (ceRNA)" hypothesis states that lncRNAs competitively bind to miRNAs through their intramolecular miRNA reaction elements (MREs) to construct a wide range of ceRNA regulatory networks. This study aims to predict the role of ceRNA network in LSCC, for advancing the understanding of underlying mechanisms of tumorigenesis.

Material and Methods

In this study, the functions of lncRNAs as ceRNAs in LSCC and their prognostic significance were investigated via comprehensive integrated expression profiles data of lncRNAs, mRNAs, and miRNAs obtained from The Cancer Genome Atlas (TCGA). Protein-protein interaction, gene ontology, pathway, and Kaplan-Meier curves analysis were used to profile the expression and function of altered RNAs in LSCC.

Results

As a result, 889 lncRNAs, 55 miRNAs and 1946 mRNAs were found to be differentially expressed in LSCC. These altered mRNAs were mainly involved in extracellular matrix organization, calcium signaling, and metabolic pathways. To study the regulatory function of lncRNAs, an lncRNA-mediated ceRNA network was constructed. This ceRNA network included 61 lncRNAs, seven miRNAs and seven target mRNAs. Of these RNAs, lncRNAs (TSPEAR-AS, CASK-AS1, MIR137HG, PART1, LSAMP-AS1), miRNA (has-mir-210) and mRNAs (HOXC13, STC2, DIO1, FOXD4L1) had a significant effect on the prognosis of LSCC.

Conclusion

The results of this study broaden the understanding of the mechanisms by which lncRNAs are involved in tumorigenesis. Furthermore, five lncRNAs (TSPEAR-AS, CASK-AS1, MIR137HG, PART1, LSAMP-AS1) were identified as potential prognostic biomarkers and therapeutic targets for LSCC. These results provide a basis for further experimental and clinical research.

XIST/miR-376c-5p/OPN axis modulates the influence of proinflammatory M1 macrophages on osteoarthritis chondrocyte apoptosis

The inflammatory microenvironment in the joints is one of the critical issues during osteoarthritis (OA) and also the main factor that may aggravate symptoms. Under inflammatory microenvironment, M1 macrophages are activated and produce large numbers of proinflammatory mediators, leading to the production of degradative enzymes, the disturbance of chondrocyte apoptosis and cartilage catabolic processes, and finally the deterioration of OA. In the present study, we reveal that the overexpression of osteopontin (OPN), a cytokine, and a matrix protein involved in arthritis and chondrocyte apoptosis in OA, could exacerbate the inflammatory microenvironment in OA via promoting the production of proinflammation cytokines and the levels of degradative enzymes in M1 macrophages, therefore, enhancing the cytotoxicity of M1 macrophage on chondrocytes. XIST expression significantly increases in OA tissue specimens. XIST serves as a competing endogenous RNA for miR-376c-5p to compete with OPN for miR-376c-5p binding, thus counteracting miR-376c-5p-mediated OPN suppression. XIST knockdown could improve the inflammatory microenvironment in OA via acting on M1 macrophages, subsequently affecting the apoptosis of cocultured chondrocytes. miR-376c-5p inhibition exerts an opposing effect on M1 macrophages and cocultured chondrocytes, as well as significantly reverses the effect of XIST knockdown. As a further confirmation, XIST and OPN mRNA expression significantly increased in OA tissues and was positively correlated in tissue samples. In summary, we provide a novel mechanism of macrophages and the inflammatory microenvironment affecting chondrocyte apoptosis. XIST and OPN might be potential targets for OA treatment, which needs further in vivo experimental confirmation.

Identification of a universal 6-lncRNA prognostic signature for three pathologic subtypes of renal cell carcinoma

Renal cell carcinoma (RCC) is the most common adult renal epithelial cancer susceptible to metastasis and patients with irresectable RCC always have a poor prognosis. Long noncoding RNAs (lncRNAs) have recently been documented as having critical roles in the etiology of RCC. Nevertheless, the prognostic significance of lncRNA-based signature for outcome prediction in patients with RCC has not been well investigated. Therefore, it is essential to identify a lncRNA-based signature for predicting RCC prognosis. In the current study, we comprehensively analyzed the RNA sequencing data of the three main pathological subtypes of RCC (kidney renal clear cell carcinoma [KIRC], kidney renal papillary cell carcinoma [KIRP], and kidney chromophobe carcinoma [KICH]) from The Cancer Genome Atlas (TCGA) database, and identified a 6-lncRNA prognostic signature with the help of a step-wise multivariate Cox regression model. The 6-lncRNA signature stratified the patients into low- and high-risk groups with significantly different prognosis. Multivariate Cox regression analysis showed that predictive value of the 6-lncRNA signature was independent of other clinical or pathological factors in the entire cohort and in each cohort of RCC subtypes. In addition, the three independent prognostic clinical factors (including age, pathologic stage III, and stage IV) was also stratified into low- and high-risk groups basis on the risk score, and the stratification analyses demonstrated that the high-risk score was a poor prognostic factor. In conclusion, these findings indicate that the 6-lncRNA signature is a novel prognostic biomarker for all three subtypes of RCC, and can increase the accuracy of predicting overall survival.

The construction and analysis of the aberrant lncRNA-miRNA-mRNA network in non-small cell lung cancer

Background

Non-small cell lung cancer (NSCLC) is the most common cancer and the pathogenesis remain unclear. According to the competing endogenous RNA (ceRNA) theory, long noncoding RNA (lncRNA) have a competition with mRNAs for the connecting with miRNAs that affecting the level of mRNA. In this work, the ceRNA network and the important genes to predict the survival prognosis were explored.

Methods

In the study, we recognized differently expressed genes (mRNAs, lncRNAs and miRNAs) between NSCLC and normal tissues from The Cancer Genome Atlas database (fold change >2, P<0.01) using edgeR. Then, the interaction between lncRNA and miRNA or mRNA and miRNA was explored by miRcode, miRDB, TargetScan, and miRanda. Furthermore, the functions and KEGG pathway were analyzed with DAVID and KOBAS. The connections of these mRNAs were explored by STRING online database. The relation between genes in the network and survival time were further explored by survival package in R.

Results

By bioinformatics tools, we explored 155 lncRNAs, 30 miRNAs and 68 mRNAs and constructed ceRNA network. The functions and KEGG pathway of 68 mRNAs were further analyzed. AQP2, EGF, SLC12A1, TRPV5 and AVPR2 was in the center of network and may play key roles in the development of NSCLC. And mRNA (CCNB1, COL1A1, E2F7, EGLN3, FOXG1 and PFKP), miRNA (miR-31, miR-144 and miR-192) and lncRNA (AC080129.1, AC100791.1, AL163952.1, AP000525.1, AP003064.2, C2orf48, C10orf91, FGF12-AS2, HOTAIR, LINC00518, LNX1-AS1, MED4-AS1, MIG31HG, MUC2, TTTY16 and UCA1) were closely related with overall survival (OS).

Conclusions

In summary, the present study provides a deeper understanding of the lncRNA-related ceRNA network in NSCLC and some genes may be new target to treat for NSCLC patients.

Comprehensive analysis of dysregulated lncRNAs, miRNAs and mRNAs with associated ceRNA network in esophageal squamous cell carcinoma

Mounting evidence suggests that long noncoding RNAs (lncRNAs) play an important role in tumor biology. To date, some lncRNAs have been found to be involved in competitive binding of miRNAs, a major group of competitive endogenous RNAs (ceRNAs), through participation in a regulatory network of protein-coding gene expression. However, the functional roles of lncRNA-mediated ceRNAs in esophageal squamous cell carcinoma (ESCC) have rarely been reported. Here, we construct a hypothetical ceRNA network by analyzing differential expression of lncRNAs, miRNAs and mRNAs obtained from 96 ESCC tissues and 13 normal tissues in the Cancer Genome Atlas. Ultimately, 95 lncRNAs, 9 miRNAs, and 40 mRNAs were identified (fold change >1.5, P < .05) and included in the ceRNA network for ESCC. Moreover, three lncRNAs (IGF2-AS, MUC2 and SOX2-OT) were found to be significantly associated with overall survival (log-rank test, P < .05), and further experiments revealed that lncRNA DLX6-AS1 knockdown inhibited the proliferation and invasion of esophageal cancer cells by enhancing the endogenous function of mTOR. We believe that the identified ceRNA network can facilitate a better understanding of lncRNA-related mechanisms in ESCC.

Expression level and prospective mechanism of miRNA-99a-3p in head and neck squamous cell carcinoma based on miRNA-chip and miRNA-sequencing data in 1, 167 cases

BACKGROUND

The role of miR-99a-3p in Head and neck squamous cell carcinoma (HNSCC) has not been reported. Therefore, in this study, we examined the expression level and its molecular mechanisms of miR-99a-3p in HNSCC.

MATERIALS AND METHODS

MiR-99a-3p-related miRNA-chip and miRNA-sequencing data were collected. We then carried out meta-analyses to pool the standard mean difference (SMD) value and generate a summarized receiver operating characteristic (sROC) curve. MiR-99a-3p mimic was transfected into FaDu cells and those genes influenced by miR-99a-3p were gathered. The target genes were also predicted from 12 tools through miRwalk2.0, and combined with differentially expressed genes in HNSCC from the The Cancer Genome Atlas and Genotype-Tissue Expression sequencing databases. FunRich and DAVID were used for the pathway signaling analyses for the potential targets of miR-99a-3p in HNSCC.

RESULTS

The SMD was -0.30 (95% CI: -0.51, -0.08) in the fixed-effect model and -0.28 (95% CI: -0.67, 0.10) in the random-effect model (I2 = 60%), indicating a reduced expression level of miR-99a-3p in HNSCC tissues based on 1167 cases. In the sROC curve, the area under the curve (AUC) was 0.77 (95% CI: 0.73, 0.81). The 251 potential targets of miR-99a-3p were enriched in several pathways related to cancer, with the "Pathways in cancer" standing at the top. vascular endothelial growth factor A was selected as an example with up-regulated trend in HNSCC tissues.

CONCLUSION

MiR-99a-3p exhibits a significant lower expression status in HNSCC, and this reduced or deletion status promotes the malignant progression of HNSCC. However, its molecular mechanism is still unclear and requires further investigation.

Construction and comprehensive analysis of dysregulated long non-coding RNA-associated competing endogenous RNA network in clear cell renal cell carcinoma

OBJECTIVE

This study aimed to assess the long noncoding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in clear cell renal cell carcinoma (ccRCC) by gene expression analyses.

MATERIALS AND METHODS

LncRNA, miRNA, and mRNA expression profiles in ccRCC were obtained from The Cancer Genome Atlas. Differentially expressed lncRNAs, mRNAs (cut-off: |log 2 [fold change, FC])| > 2.0 and adjusted P < 0.01) and miRNAs (|log 2FC| > 1.5 and adjusted P < 0.01) were unveiled using R. Cox regression analysis was performed to identify prognostic factors of ccRCC related to overall survival (OS). A protein-protein interaction (PPI) network was constructed for differentially expressed mRNAs (DEmRNAs) by Search Tool for the Retrieval of Interacting Genes (STRING). Key hub genes were screened from top 300 DEmRNAs. LncRNA-miRNA and miRNA-mRNA regulatory network were constructed and combined into the competing endogenous RNA regulatory network. Gene ontology biological terms were screened by STRING; Kyoto Encyclopedia of Genes and Genomes pathways were identified using the "clusterProfiler" package in R.

RESULTS

A total of 2331, 1517, and 83 DEmRNAs, lncRNAs, and miRNAs were identified, respectively. Eleven lncRNAs (AC016773.1, HOTTIP, LINC00460, NALCN-AS1, PVT1, TRIM36-IT1, WT1-AS, COL18A1-AS1, LINC00443, LINC00472, and TCL6), three miRNAs (hsa-mir-21, hsa-mir-144, and hsa-mir-155), and three mRNAs (COL4A4, NOD2, and GOLGA8B) were associated with OS. Specifically, four lncRNAs (PVT1, LINC00472, TCL6, and WT1-AS1) and one mRNA (Collagen Type IV Alpha 4 Chain) were verified as independent prognostic factors by Gene Expression Profiling Interactive Analysis. Eleven key hub genes were obtained by PPI analysis. "Cell adhesion molecules (CAMs)," "chemical carcinogenesis," and "cytokine-cytokine receptor interaction" were significantly enriched in the network.

CONCLUSION

The findings clarify the pathogenesis of ccRCC and might provide potential therapeutic targets.

Weighted gene co‑expression network analysis for identifying hub genes in association with prognosis in Wilms tumor

Wilms tumor (WT) is the most common type of renal malignancy in children. Survival rates are low and high-risk WT generally still carries a poor prognosis. To better elucidate the pathogenesis and tumorigenic pathways of high-risk WT, the present study presents an integrated analysis of RNA expression profiles of high-risk WT to identify predictive molecular biomarkers, for the improvement of therapeutic decision-making. mRNA sequence data from high-risk WT and adjacent normal samples were downloaded from The Cancer Genome Atlas to screen for differentially expressed genes (DEGs) using R software. From 132 Wilms tumor samples and six normal samples, 2,089 downregulated and 941 upregulated DEGs were identified. In order to identify hub DEGs that regulate target genes, weighted gene co-expression network analysis (WGCNA) was used to identify 11 free-scale gene co-expressed clusters. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were annotated using KEGG Orthology Based Annotation System annotation of different module genes. The Search Tool for the Retrieval of Interacting Genes was used to construct a protein-protein interaction network for the identified DEGs, and the hub genes of WGCNA modules were identified using the Cytohubb plugin with Cytoscape software. Survival analysis was subsequently performed to highlight hub genes with a clinical signature. The present results suggest that epidermal growth factor, cyclin dependent kinase 1, endothelin receptor type A, nerve growth factor receptor, opa-interacting protein 5, NDC80 kinetochore complex component and cell division cycle associated 8 are essential to high-risk WT pathogenesis, and they are closely associated with clinical prognosis.

The clinicopathological significance of decreased miR-125b-5p in hepatocellular carcinoma: evidence based on RT-qPCR, microRNA-microarray, and microRNA-sequencing

The aim of the study was to comprehensively evaluate the clinical value of miR-125b-5p in hepatocellular carcinoma (HCC) and its potential molecular mechanisms. MiR-125b-5p expression was remarkably lower as examined by real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) in 95 paired HCC and nonmalignant liver tissues in house (P<0.001), which was in accord with the results from miRNA-sequencing data with 371 cases of HCC. miRNA-chips from Gene Expression Omnibus (GEO) and ArrayExpress were screened. Among the seven included miRNA-chips, the relative expression of miR-125b-5p expression levels showed decreasing trends in HCC tissue samples compared with non-cancerous liver tissue samples. Altogether, A total of 655 cases of HCC tissues and 334 non-HCC liver tissues were included in the final meta-analysis. We observed that the expression of miR-125b-5p indeed decreased markedly in HCC tissues compared with the non-HCC tissues (SMD: -1.414, 95% CI: -1.894 to -0.935, P<0.001). The area under the SROC curve of lower expression of miR-125b-5p was 0.91 (95% CI: 0.89 to 0.94). A Kaplan-Meier survival analysis indicated that the lower expression or the absence of miR-125b-5p may be a risk factor for the poor outcome of HCC patients. Furthermore, the potential target genes of miR-125b-5p from 11 miRNA target prediction databases were intersected with 1,486 differentially expressed genes (DEGs) as calculated by RNA-sequencing data. Finally, a total of 330 GEGs were collected and enriched in the pathways of lysosome, focal adhesion, and pathways in cancer. In conclusion, this study utilizes a variety of research methods to confirm the lower level of miR-125b-5p in HCC tissues. This lower expression level of miR-125b-5p is closely related to increased disease progression in HCC patients.

Long non‑coding RNA DLX6‑AS1 is associated with malignant progression and promotes proliferation and invasion in esophageal squamous cell carcinoma

Despite being one of the most prevalent and fatal types of cancer worldwide, the biological details of esophageal squamous cell carcinoma (ESCC) remain unknown. Recent studies have demonstrated the crucial roles of long non‑coding RNAs (lncRNAs) in diverse biological processes including cancer initiation, progression and metastasis. The aim of the present study was to assess the expression profile of distal‑less homeobox 6 antisense RNA 1 (DLX6‑AS1) in ESCC tissues and its contributions to ESCC cell proliferation, apoptosis and invasion. The expression of DLX6‑AS1 in a series of ESCC samples and paired adjacent noncancerous tissues was evaluated by reverse transcription‑quantitative polymerase chain reaction. Cell proliferation, apoptosis, wound healing and Transwell invasion assays were performed to evaluate the roles of DLX6‑AS1 in the ESCC cell lines EC109 and KYSE30 transfected with DLX6‑AS1 small interfering RNA (siRNA). Compared with the paired adjacent noncancerous tissues, DLX6‑AS1 expression was upregulated in the ESCC tissues and significantly associated with differentiation status, Tumor‑Node‑Metastasis stage, distant metastasis, and lymph node metastasis. Knockdown of DLX6‑AS1 significantly suppressed cell proliferation, invasion and migration abilities, and enhanced the apoptotic rate in the two ESCC cell lines. Furthermore, western blot assays revealed that silencing DLX6‑AS1 partly influenced the epithelial‑mesenchymal transition process in ESCC cells. These results imply that the oncogenic function of DLX6‑AS1 may be a novel candidate target for treating human ESCC.

A comprehensive competitive endogenous RNA network pinpoints key molecules in diabetic retinopathy

Diabetic retinopathy (DR) is a severe microvascular complication of diabetes and the primary cause of vision loss in diabetic patients. Previous research has revealed that long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) play pivotal roles in the pathogenesis of DR. However, the roles of lncRNA-miRNA-mRNA interactions in DR are poorly understood. In the present study, we aimed to compute a global triple network of competitive endogenous RNAs (ceRNAs) in order to pinpoint essential molecules. We found that there were 802 nodes (121 lncRNA nodes, 17 miRNA nodes, and 664 mRNA nodes) and 949 edges in the ceRNA network. Further functional analysis suggested that some molecules were specifically related to DR. Surprisingly, these molecules were involved in visual perception, eye development, and lens development in camera-type eye. In summary, our study highlighted specific lncRNAs and miRNAs related to the pathogenesis of DR, which might be used as potential diagnostic biomarkers and therapeutic targets for DR.

The molecular characterization and therapeutic strategies of papillary renal cell carcinoma

Introduction: Papillary renal cell carcinoma (pRCC) is an important subtype of kidney cancer with a problematic pathological classification and highly variable clinical behavior. In this review, we summarize the current progression on pRCC in molecular level. Our findings highlight the need for molecular markers to accurately subtype pRCC and may lead to the development of more targeted agents and better patient stratification in clinical trials for pRCC. Areas covered: This review highlights the need for molecular markers to accurately subtype PRCC and may lead to the development of more targeted agents and better patient stratification in clinical trials for pRCC. Expert commentary: There are mainly two subtypes of pRCC based on histology. However, little is known about the genetic characterization of the sporadic forms of pRCC and there are currently no standard forms of therapy for patients with advanced disease. Both MET inhibitors and immunotherapy may be effective in advanced pRCC treatment. Therefore, understanding the molecular basis of pRCC and identifying the main goal of treatment is crucial for the selection of the best strategy.

The landscape of miRNA-related ceRNA networks for marking different renal cell carcinoma subtypes

We know that different types of cancers usually have different responses to the same treatment. Therefore, it is important to understand the similarities and differences across subtypes of cancers, so as to provide a basis for the individualized treatments. Until now, no comprehensive investigation on competing endogenous RNAs (ceRNAs) has been reported for the three main subtypes of renal cell carcinoma (RCC), so the regulation characteristics of ceRNAs in three subtypes are not well revealed. This paper firstly describes a comparative analysis of ceRNA-ceRNA interaction networks for all the three subtypes of RCC based on differential microRNAs (miRNAs). We comprehensively summarized all miRNA and messenger RNAdata of RCC from 126 matched tumor-normal tissues in The Cancer Genome Atlas, systematically analyzed a total of more than 80 000 ceRNA interactions and highlighted the common and specific properties among them, aiming to identify critical genes to classify them for providing supplementary help in the precise diagnosis of RCC. From three aspects, including common or specific ceRNAs, upregulated or downregulated and classifications across the three subtypes, we highlighted the common and specific properties for the three subtypes and also explored the classification of RCC by combining the specific ceRNAs with differential regulations. Moreover, for the most major subtype of clear cell renal cell carcinoma (KIRC), three critical genes were screened out from KIRC ceRNA network and further demonstrated to be the potential biomarkers of KIRC by performing biological experiments at the transcriptional level.

Functional Long Noncoding RNAs (lncRNAs) in Clear Cell Kidney Carcinoma Revealed by Reconstruction and Comprehensive Analysis of the lncRNA-miRNA-mRNA Regulatory Network

BACKGROUND A variety of treatment strategies have been developed for clear cell kidney carcinoma (KIRC); however, there is still a need for effective therapeutic targets and prognostic molecular biomarkers. Given that long noncoding RNAs (lncRNAs) has been emerging as an important regulator in tumorigenesis, we explored potential functional lncRNAs in KIRC by comprehensively analyzing the lncRNA-miRNA-mRNA regulatory network with bioinformatics processing tools. MATERIAL AND METHODS RNA-seq/miRNA-seq data of KIRC in The Cancer Genome Atlas (TCGA) were obtained and analyzed. The "edgeR" package in R software was used to identify differentially expressed lncRNAs (DElncRNAs, differentially expressed long noncoding RNAs), miRNAs (DEmiRNAs, differentially expressed micro RNAs), and mRNAs (DEmRNAs, differentially expressed messenger RNAs) in KIRC and normal samples. A global triple network was conducted based on the competing endogenous RNA (ceRNA) theory, and survival analysis was conducted by "survival" package in R software. RESULTS A total of 4246 DElncRNAs, 179 DEmiRNAs, and 5758 DEmRNAs were identified, among which a subset of them (321 lncRNAs, 26 miRNAs, and 1068 mRNAs) were found to constitute a global ceRNA network in KIRC. Four lncRNAs (ENTPD3-AS1, FGD5-AS1, LIFR-AS1, and UBAC2-AS1) were revealed to be potential therapeutic targets as well as prognostic biomarkers of KIRC by our extensive functional analysis. CONCLUSIONS We reported here the identification of functional lncRNAs in KIRC via a TCGA data-based bioinformatics analysis. We believe that this study might contribute to improving the comprehension of the lncRNA-mediated ceRNA regulatory mechanisms in the tumorigenesis of KIRC. Meanwhile, our results suggested that 4 lncRNAs might act as potential therapeutic targets or candidate prognostic biomarkers in KIRC.

Integrated analysis of long noncoding RNA associated-competing endogenous RNA as prognostic biomarkers in clear cell renal carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant carcinomas and its molecular mechanisms remain unclear. Long noncoding RNA (lncRNA) could bind sites of miRNA which affect the expression of mRNA according to the competing endogenous (ceRNA) theory. The aim of the present study was to construct a ceRNA network and to identify key lncRNA to predict survival prognosis. We identified differentially expressed mRNA, lncRNA and miRNA between tumor tissues and normal tissues from The Cancer Genome Atlas database. Then, using bioinformatics tools, we explored the connection of 89 lncRNA, 10 miRNA and 22 mRNA, and we constructed the ceRNA network. Furthermore, we analyzed the functions and pathways of 22 differentially expressed mRNA. Then, univariate and multivariate Cox regression analyses of these 89 lncRNA and overall survival were explored. Nine lncRNA were finally screened out in the training group. The patients were divided into high‐risk and low‐risk groups according to the 9 lncRNA and low‐risk scores having better clinical overall survival (P < .01). Furthermore, the receiver operating characteristic curve demonstrates the predicted role of the 9 lncRNA. The 9‐lncRNA signature was successfully proved in the testing group and the entire group. Finally, multivariate Cox regression analysis and stratification analysis further proved that the 9‐lncRNA signature was an independent factor to predict survival. In summary, the present study provides a deeper understanding of the lncRNA‐related ceRNA network in ccRCC and suggests that the 9‐lncRNA signature could serve as an independent biomarker to predict survival in ccRCC patients.

Comparison of tumor related signaling pathways with known compounds to determine potential agents for lung adenocarcinoma

Background

This study compared tumor‐related signaling pathways with known compounds to determine potential agents for lung adenocarcinoma (LUAD) treatment.

Methods

Kyoto Encyclopedia of Genes and Genomes signaling pathway analyses were performed based on LUAD differentially expressed genes from The Cancer Genome Atlas (TCGA) project and genotype‐tissue expression controls. These results were compared to various known compounds using the Connectivity Mapping dataset. The clinical significance of the hub genes identified by overlapping pathway enrichment analysis was further investigated using data mining from multiple sources. A drug‐pathway network for LUAD was constructed, and molecular docking was carried out.

Results

After the integration of 57 LUAD‐related pathways and 35 pathways affected by small molecules, five overlapping pathways were revealed. Among these five pathways, the p53 signaling pathway was the most significant, with CCNB1, CCNB2, CDK1, CDKN2A, and CHEK1 being identified as hub genes. The p53 signaling pathway is implicated as a risk factor for LUAD tumorigenesis and survival. A total of 88 molecules significantly inhibiting the five LUAD‐related oncogenic pathways were involved in the LUAD drug‐pathway network. Daunorubicin, mycophenolic acid, and pyrvinium could potentially target the hub gene CHEK1 directly.

Conclusion

Our study highlights the critical pathways that should be targeted in the search for potential LUAD treatments, most importantly, the p53 signaling pathway. Some compounds, such as ciclopirox and AG‐028671, may have potential roles for LUAD treatment but require further experimental verification.

Comprehensive analysis of a long noncoding RNA-associated competing endogenous RNA network in colorectal cancer

Purpose

This study was aimed to develop a lncRNA-associated competing endogenous RNA (ceRNA) network to provide further understanding of the ceRNA regulatory mechanism and pathogenesis in colorectal cancer (CRC).

Patients and methods

Expression profiles of mRNAs, lncRNAs, and miRNAs, and clinical information for CRC patients were obtained from The Cancer Genome Atlas. The differentially expressed mRNAs, lncRNAs, and miRNAs (referred to as “DEmRNAs”, “DElncRNAs”, and “DEmiRNAs”, respectively) were screened out between 539 CRC samples and 11 normal samples. The interactions between DElncRNAs and DEmiRNAs were predicted by miRcode. The DEmRNAs targeted by the DEmiRNAs were retrieved according to TargetScan, miRTar-Base, and miRDB. The lncRNA–miRNA–mRNA ceRNA network was constructed based on the DEmiRNA–DElncRNA and DEmiRNA–DEmRNA interactions. Functional enrichment analysis revealed the biological processes and pathways of DEmRNAs involved in the development of CRC. Key lncRNAs were further analyzed for their associations with overall survival and clinical features of CRC patients.

Results

A total of 1,767 DEmRNAs, 608 DElncRNAs, and 283 DEmiRNAs were identified as CRC-specific RNAs. Three hundred eighty-two DEmiRNA–DElncRNA interactions and 68 DEmiRNA–DEmRNA interactions were recognized according to the relevant databases. The lncRNA–miRNA–mRNA ceRNA network was constructed using 25 DEmiRNAs, 52 DEmRNAs, and 64 DElncRNAs. Two DElncRNAs, five DEmiRNAs, and six DEmRNAs were demonstrated to be related to the prognosis of CRC patients. Four DElncRNAs were found to be associated with clinical features. Twenty-eight Gene Ontology terms and 10 Kyoto Encyclopedia of Genes and Genomes pathways were found to be significantly enriched by the DEmRNAs in the ceRNA network.

Conclusion

Our results showed cancer-specific mRNA, lncRNA, and miRNA expression patterns and enabled us to construct an lncRNA-associated ceRNA network that provided new insights into the molecular mechanisms of CRC. Key RNA transcripts related to the overall survival and clinical features were also found with promising potential as biomarkers for diagnosis, survival prediction, and classification of CRC.

Long non-coding RNAs: An essential emerging field in kidney pathogenesis

Human Genome Project has made it clear that a majority of the genome is transcribed into the non-coding RNAs including microRNAs as well as long non-coding RNAs (lncRNAs) which both can affect different features of cells. LncRNAs are long heterogenous RNAs that regulate gene expression and a variety of signaling pathways involved in cellular homeostasis and development. Studies over the past decade have shown that lncRNAs have a major role in the kidney pathogenesis. The effective roles of lncRNAs have been recognized in renal ischemia, injury, inflammation, fibrosis, glomerular diseases, renal transplantation, and renal cell carcinoma. The present review outlines the role and function of lncRNAs in kidney pathogenesis as novel essential regulators. Molecular mechanism insights into the functions of lncRNAs in kidney pathophysiological processes may contribute to effective future therapeutics.

Long non-coding RNA DLX6-AS1 aggravates hepatocellular carcinoma carcinogenesis by modulating miR-203a/MMP-2 pathway

Long non-coding RNAs (lncRNAs) have been wildly verified to modulate multiple tumorigenesis, especially hepatocellular carcinoma (HCC). In present study, our team aims to investigate the role of lncRNA DLX6-AS1 in the HCC carcinogenesis. Results of early-stage experiments found that DLX6-AS1 expression level was up-regulated in 60 cases of HCC tissue samples compared with adjacent normal tissue. Moreover, the aberrant overexpression of DLX6-AS1 indicated the poor prognosis of HCC patients. Loss-of-function experiments revealed that DLX6-AS1 knockdown inhibited the proliferation, migration and invasion of HCC cells in vitro, and decreased the tumor growth in vivo. Bioinformatics analysis predicted that miR-203a potentially targeted DLX6-AS1 3'-UTR, suggesting the interaction between miR-203a and DLX6-AS1. Furthermore, miR-203a also targeted MMP-2 mRNA 3'-UTR, which was validated by luciferase reporter assay. Taken together, our study discovered the oncogenic role of DLX6-AS1 in clinical specimens and cellular experiments, showing the potential DLX6-AS1/miR-203a/MMP-2 pathway. This results and findings provide a novel insight for HCC tumorigenesis.