Identification of dysregulated long non-coding RNAs/microRNAs/mRNAs in TNM I stage lung adenocarcinoma

The Long Non-Coding RNA ANRIL in Cancers

ANRIL (Antisense Noncoding RNA in the INK4 Locus), a long non-coding RNA encoded in the human chromosome 9p21 region, is a critical factor for regulating gene expression by interacting with multiple proteins and miRNAs. It has been found to play important roles in various cellular processes, including cell cycle control and proliferation. Dysregulation of ANRIL has been associated with several diseases like cancers and cardiovascular diseases, for instance. Understanding the oncogenic role of ANRIL and its potential as a diagnostic and prognostic biomarker in cancer is crucial. This review provides insights into the regulatory mechanisms and oncogenic significance of the 9p21 locus and ANRIL in cancer.

NcPath: a novel platform for visualization and enrichment analysis of human non-coding RNA and KEGG signaling pathways

SUMMARY

Non-coding RNAs play important roles in transcriptional processes and participate in the regulation of various biological functions, in particular miRNAs and lncRNAs. Despite their importance for several biological functions, the existing signaling pathway databases do not include information on miRNA and lncRNA. Here, we redesigned a novel pathway database named NcPath by integrating and visualizing a total of 178 308 human experimentally validated miRNA-target interactions (MTIs), 32 282 experimentally verified lncRNA-target interactions (LTIs) and 4837 experimentally validated human ceRNA networks across 222 KEGG pathways (including 27 sub-categories). To expand the application potential of the redesigned NcPath database, we identified 556 798 reliable lncRNA-protein-coding genes (PCG) interaction pairs by integrating co-expression relations, ceRNA relations, co-TF-binding interactions, co-histone-modification interactions, cis-regulation relations and lncPro Tool predictions between lncRNAs and PCG. In addition, to determine the pathways in which miRNA/lncRNA targets are involved, we performed a KEGG enrichment analysis using a hypergeometric test. The NcPath database also provides information on MTIs/LTIs/ceRNA networks, PubMed IDs, gene annotations and the experimental verification method used. In summary, the NcPath database will serve as an important and continually updated platform that provides annotation and visualization of the pathways on which non-coding RNAs (miRNA and lncRNA) are involved, and provide support to multimodal non-coding RNAs enrichment analysis. The NcPath database is freely accessible at http://ncpath.pianlab.cn/.

AVAILABILITY AND IMPLEMENTATION

NcPath database is freely available at http://ncpath.pianlab.cn/. The code and manual to use NcPath can be found at https://github.com/Marscolono/NcPath/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC

LncRNAs have arisen as new players in the world of non-coding RNA. Disrupted expression of these molecules can be tightly linked to the onset, promotion and progression of cancer. The present study estimated the usefulness of 14 lncRNAs (HAGLR, ADAMTS9-AS2, LINC00261, MCM3AP-AS1, TP53TG1, C14orf132, LINC00968, LINC00312, TP73-AS1, LOC344887, LINC00673, SOX2-OT, AFAP1-AS1, LOC730101) for early detection of non-small-cell lung cancer (NSCLC). The total RNA was isolated from paired fresh-frozen cancerous and noncancerous lung tissue from 92 NSCLC patients diagnosed with either adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC). The expression level of lncRNAs was evaluated by a quantitative real-time PCR (qPCR). Based on Ct and delta Ct values, logistic regression and gradient boosting decision tree classifiers were built. The latter is a novel, advanced machine learning algorithm with great potential in medical science. The established predictive models showed that a set of 14 lncRNAs accurately discriminates cancerous from noncancerous lung tissues (AUC value of 0.98 ± 0.01) and NSCLC subtypes (AUC value of 0.84 ± 0.09), although the expression of a few molecules was statistically insignificant (SOX2-OT, AFAP1-AS1 and LOC730101 for tumor vs. normal tissue; and TP53TG1, C14orf132, LINC00968 and LOC730101 for LUAD vs. LUSC). However for subtypes discrimination, the simplified logistic regression model based on the four variables (delta Ct AFAP1-AS1, Ct SOX2-OT, Ct LINC00261, and delta Ct LINC00673) had even stronger diagnostic potential than the original one (AUC value of 0.88 ± 0.07). Our results demonstrate that the 14 lncRNA signature can be an auxiliary tool to endorse and complement the histological diagnosis of non-small-cell lung cancer.

Multiscale part mutual information for quantifying nonlinear direct associations in networks

MOTIVATION

For network-assisted analysis, which has become a popular method of data mining, network construction is a crucial task. Network construction relies on the accurate quantification of direct associations among variables. The existence of multiscale associations among variables presents several quantification challenges, especially when quantifying nonlinear direct interactions.

RESULTS

In this study, the multiscale part mutual information (MPMI), based on part mutual information (PMI) and nonlinear partial association (NPA), was developed for effectively quantifying nonlinear direct associations among variables in networks with multiscale associations. First, we defined the MPMI in theory and derived its five important properties. Second, an experiment in a three-node network was carried out to numerically estimate its quantification ability under two cases of strong associations. Third, experiments of the MPMI and comparisons with the PMI, NPA and conditional mutual information were performed on simulated datasets and on datasets from DREAM challenge project. Finally, the MPMI was applied to real datasets of glioblastoma and lung adenocarcinoma to validate its effectiveness. Results showed that the MPMI is an effective alternative measure for quantifying nonlinear direct associations in networks, especially those with multiscale associations.

AVAILABILITY AND IMPLEMENTATION

The source code of MPMI is available online at https://github.com/CDMB-lab/MPMI.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The miR-106b/NR2F2-AS1/PLEKHO2 Axis Regulates Migration and Invasion of Colorectal Cancer through the MAPK Pathway

Increasing numbers of miRNAs have been observed as oncogenes or tumor suppressors in colorectal cancer (CRC). It was recently reported that hsa-miR-106b-5p (miR-106b) promoted CRC cell migration and invasion. However, there were also studies showing contradictory results. Therefore, in the present study, we further explore the role of miR-106b and its downstream networks in the carcinogenesis of CRC. We observed that the expression of miR-106b is significantly increased in Pan-Cancer and CRC tissues compared with normal tissues from The Cancer Genome Atlas (TCGA) database. Furthermore, we used Transwell, Cell Counting Kit-8, and colony formation assays to clarify that miR-106b promotes the migratory, invasive, and proliferative abilities of CRC cells. For the first time, we systematically screened the target mRNAs and lncRNAs of miR-106b using TCGA database and the bioinformatics algorithms. Dual-luciferase reporter assay confirmed that NR2F2-AS1 and PLEKHO2 are the direct targets of miR-106b. Furthermore, NR2F2-AS1 acts as a competing endogenous RNA (ceRNA) to regulate PLEKHO2 expression by sponging miR-106b. The results of Gene set enrichment analysis (GSEA) and Western blot indicated that they play important roles in CRC progression by regulating MAPK pathway. Thus, miR-106b/NR2F2-AS1/PLEKHO2/MAPK signaling axis may suggest the potential usage in CRC treatment.

LncRNA H19 promotes inflammatory response induced by cerebral ischemia-reperfusion injury through regulating the miR-138-5p-p65 axis

Recent studies have shown that long non-coding RNA(LncRNA) H19 is up-regulated in the brain of rats suffering from cerebral ischemia-reperfusion (I/R) injury, inducing severe disability and mortality. Little was known about the molecular mechanisms underlying the involvement of H19 in cerebral I/R injury. In this study, a rat model of I/R was induced by transient middle cerebral artery occlusion (tMCAO). PC-12 cells exposed to oxygen and glucose deprivation/reoxygenation (OGD/R) were used as an in vitro model. Our results show that H19 is up-regulated in both in vivo and in our in vitro model. Further study indicated that knockdown of H19 promotes cell proliferation, decreases the rate of cell apoptosis, and ameliorates inflammation after OGD/R simulation. Our in vivo study shows that H19 knockdown ameliorates inflammation and improves neurological function in our rat model of tMCAO. Remarkably, the results from our luciferase reporter assays suggest that H19 negatively regulates the expression of miR-138-5p, and p65 was identified as a target of miR-138-5p. To sum up, this study demonstrated that H19 promotes an inflammatory response and improves neurological function in a rat model of tMCAO by regulating the expression of miR-138-5p and p65. This study reveals the important role and underlying mechanism of H19 in the progress of cerebral I/R injury, which could serve as a potential target for further treatment.

FENDRR: A pivotal, cancer-related, long non-coding RNA

Long non-coding RNAs (lncRNAs) have more than 200 nucleotides and do not encode proteins. Based on numerous studies, lncRNAs have emerged as new and crucial regulators of biological function and have been implicated in the pathogenesis of a variety of diseases, especially cancers. Specific lncRNAs have been identified as novel molecular biomarkers for cancer diagnosis, prognosis, and treatment efficacy. Fetal-lethal non-coding developmental regulatory RNA (FENDRR, also known as FOXF1-AS1) is a novel lncRNA that is located at chr3q13.31 and has four exons and 3099 nucleotides, and its genomic site is located at chr3q13.31. FENDRR is abnormally expressed in a variety of cancers and is significantly associated with different clinical characteristics. In addition, FENDRR has shown potential as a biomarker for cancer diagnosis, prognosis, and treatment. In this review, we summarize the current understanding of FENDRR and its mechanistic role in cancer progression. We also discuss recent insights into the clinical significance of FENDRR for cancer diagnosis, prognosis, and treatment.

Silencing of Long Non-Coding RNA LINC01106 Suppresses the Proliferation, Migration and Invasion of Endometrial Cancer Cells Through Regulating the miR-449a/MET Axis

PURPOSE

Endometrial cancer (EC) is an aggressive tumor in females and the development of EC is considered to regulate by some long non-coding RNAs (lncRNAs). Therefore, this study aimed to investigate the regulatory mechanism of lncRNA LINC01106 on EC.

METHODS

The expression of lncRNA LINC01106, miR-449a and MET in EC tissues and cells was detected by qRT-PCR. Through MTT, wound healing and transwell invasion assays, the proliferation, migration and invasion of EC cells were detected, respectively. The xenograft tumor model was constructed in nude mice to confirm the inhibiting effect of LINC01106 knockdown on EC in vivo. The interactions between miR-449a and LINC01106/MET were predicted by Starbase/Targetscan software and verified by the dual-luciferase reporter assay or RNA immunoprecipitation assay. Western blot assay was performed to determine the protein level of MET.

RESULTS

LncRNA LINC01106 expression was highly up-regulated in EC tissues and cells. The proliferation, migration and invasion of EC cells in vitro were inhibited by the transfection of sh-LINC01106. The growth of tumor xenograft was suppressed by injection of sh-LINC01106. MiR-449a was a target of LINC01106and was negatively modulated by LINC01106. MiR-449a overexpression suppressed the proliferation, migration and invasion of EC cells. In addition, MET was identified as a target gene of miR-449a. Both the high expression of miR-449a and low expression of MET reversed the inhibiting effects of LINC01106 knockdown on Ishikawa cells.

CONCLUSION

Silencing of LINC01106 inhibits the occurrence and development of EC via regulating the miR-449a/MET axis. This study provides a possible therapeutic strategy for EC.

Identification of lncRNA biomarkers for lung cancer through integrative cross-platform data analyses

This study was designed to identify lncRNA biomarker candidates using lung cancer data from RNA-Seq and microarray platforms separately.

Lung cancer datasets were obtained from the Gene Expression Omnibus (GEO, n = 287) and The Cancer Genome Atlas (TCGA, n = 216) repositories, only common lncRNAs were used. Differentially expressed (DE) lncRNAs in tumors with respect to normal were selected from the Affymetrix and TCGA datasets. A training model consisting of the top 20 DE Affymetrix lncRNAs was used for validation in the TCGA and Agilent datasets. A second similar training model was generated using the TCGA dataset.

First, a model using the top 20 DE lncRNAs from Affymetrix for training and validated using TCGA and Agilent, achieved high prediction accuracy for both training (98.5% AUC for Affymetrix) and validation (99.2% AUC for TCGA and 92.8% AUC for Agilent). A similar model using the top 20 DE lncRNAs from TCGA for training and validated using Affymetrix and Agilent, also achieved high prediction accuracy for both training (97.7% AUC for TCGA) and validation (96.5% AUC for Affymetrix and 80.9% AUC for Agilent). Eight lncRNAs were found to be overlapped from these two lists.

Large-scale transcriptome analysis identified RNA methylation regulators as novel prognostic signatures for lung adenocarcinoma

Background

The abnormal expression of genes is an essential factor affecting the prognosis of cancer. RNA modification is a way of regulating post-transcriptional levels, including m⁶A, m⁵C, m¹A RNA methylation. Studies have found that RNA methylation regulates tumorigenesis development and stem cell regeneration. However, there are few studies on lung adenocarcinoma. This study aims to explore the clinical value of RNA methylation for lung adenocarcinoma.

Methods

We summarized thirty-one RNA methylation regulators. The training set was obtained from The Cancer Genome Atlas (TCGA) database, and the test set was obtained from the Gene Expression Omnibus (GEO) database. The Wilcoxon test was used to analyze the expression of RNA methylation regulators. We constructed tumor subgroup models and risk models based on the expression of those regulators. Principal component analysis (PCA) and the receiver operating characteristic (ROC) confirmed the accuracy of the models. Real-time polymerase chain reaction (PCR) validates the results in vitro.

Results

Most RNA methylation regulators had distinct expressions in tumor tissues and adjacent tissues (P<0.05). All the models showed high predictive performance (AUC: 0.65-0.82), and the five-year survival of patients in each group was statistically different (P<0.05). The patients in the high-risk group were more likely to have a higher stage, more lymph node metastases, and distant metastases, showing a poor clinical outcome. Patients with high expression of NOP2 or HNRNP were more likely to have a poorly differentiated in vitro experiment.

Conclusions

With our study, we found that the expressions of most RNA methylation regulators were significantly different in cancer and para-cancerous tissues. Different molecular phenotypes constructed by RNA methylation regulators can be independent risk factors for the prognosis of lung adenocarcinoma. Our study demonstrates the critical role of RNA methylation in lung adenocarcinoma, and it is expected to supply a reference for the prognostic stratification and treatment strategy development of lung adenocarcinoma.

Exosomal Long Non-Coding RNAs in Lung Diseases

Within the non-coding genome landscape, long non-coding RNAs (lncRNAs) and their secretion within exosomes are a window that could further explain the regulation, the sustaining, and the spread of lung diseases. We present here a compilation of the current knowledge on lncRNAs commonly found in Chronic Obstructive Pulmonary Disease (COPD), asthma, Idiopathic Pulmonary Fibrosis (IPF), or lung cancers. We built interaction networks describing the mechanisms of action for COPD, asthma, and IPF, as well as private networks for H19, MALAT1, MEG3, FENDRR, CDKN2B-AS1, TUG1, HOTAIR, and GAS5 lncRNAs in lung cancers. We identified five signaling pathways targeted by these eight lncRNAs over the lung diseases mentioned above. These lncRNAs were involved in ten treatment resistances in lung cancers, with HOTAIR being itself described in seven resistances. Besides, five of them were previously described as promising biomarkers for the diagnosis and prognosis of asthma, COPD, and lung cancers. Additionally, we describe the exosomal-based studies on H19, MALAT1, HOTAIR, GAS5, UCA1, lnc-MMP2-2, GAPLINC, TBILA, AGAP2-AS1, and SOX2-OT. This review concludes on the need for additional studies describing the lncRNA mechanisms of action and confirming their potential as biomarkers, as well as their involvement in resistance to treatment, especially in non-cancerous lung diseases.

Construction and Comprehensive Analyses of a Competing Endogenous RNA Network in Tumor-Node-Metastasis Stage I Hepatocellular Carcinoma

Background

Long noncoding RNAs (lncRNAs) can function as competing endogenous RNAs (ceRNAs) and interact with microRNAs (miRNAs) to regulate target gene expression, which can greatly influence tumor development and progression. Different tumor-node-metastasis (TNM) stages of hepatocellular carcinoma (HCC) defined by the American Joint Committee on Cancer (AJCC) have different clinical results. Our purpose was to comprehensively analyze differentially expressed (DE) lncRNAs, miRNAs, and mRNAs in stage I HCC and identify prognosis-associated RNAs.

Methods

RNA-seq data were obtained from The Cancer Genome Atlas (TCGA) database. A stage I HCC-associated miRNA-lncRNA-mRNA network was constructed. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analyses of ceRNA-associated DEmRNAs were performed using Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8 and Clusterprofile in the R package. The protein-protein interaction (PPI) network of the above mRNAs was then constructed using STRING. Finally, the association between lncRNAs and mRNAs in the ceRNA network and prognosis of patients was further analyzed. Linear regression analysis of the above lncRNAs and mRNAs associated with overall survival was performed.

Results

After a comparison between HCC and adjacent nontumor tissues, 778 lncRNAs, 1608 mRNAs, and 102 miRNAs that were abnormally expressed were identified. The ceRNA network was composed of 56 DElncRNAs, 14 DEmiRNAs, and 30 DEmRNAs. Functional analysis results showed that 30 DEmRNAs were enriched in 14 GO biological process categories and 6 KEGG categories (false discovery rate (FDR) < 0.05). A PPI network was composed of 22 nodes and 58 edges. We detected 4 DElncRNAs (BPESC1, AC061975.6, AC079341.1, and CLLU1) and 6 DEmRNAs (CEP55, E2F1, E2F7, EZH2, G6PD, and SLC7A11) that had significant influences on the overall survival (OS) of stage I HCC patients (P < 0.05). lncRNA BPESC1 was positively correlated with mRNA CEP55 via miR-424, and lncRNA AC061975.6 was positively correlated with mRNA E2F1 via miR-519d.

Conclusion

Our study identified novel lncRNAs and mRNAs that were associated with the progression and prognosis of stage I HCC and further investigated the regulatory mechanism of lncRNA-mediated ceRNAs in the development of stage I HCC.

Long non‑coding RNA LINC00312 regulates breast cancer progression through the miR‑9/CDH1 axis

Long non‑coding RNAs (lncRNAs) are important mediators of the initiation and progression of tumors, including breast cancer (BC). The exact role of long intergenic non‑coding RNA 00312 (LINC00312) in BC and its mechanism of action have not been reported to date. In the present study, LINC00312 was found to be downregulated in human BC tissues and cell lines by RT‑qPCR. The findings of a functional study indicated that overexpression of LINC00312 suppressed the proliferation, colony forming ability, migration and invasiveness of BC cell lines. Mechanistically, LINC00312 was found to induce suppression of cell migration and invasion by directly binding to miR‑9. Overexpression of LINC00312 increased the expression of cadherin 1 (CDH1), a direct target of miR‑9, and decreased the expression of vimentin (VIM), a major cytoskeletal component of mesenchymal cells as determined by western blot analysis. miR‑9 partly abrogated the upregulation of CDH1 and downregulation of VIM induced by LINC00312. Taken together, the results of the present study indicate a role for the LINC00312/miR‑9/CDH1 axis in the progression of BC, and suggest a novel lncRNA‑based diagnostic biomarker or therapeutic target for BC.

Transcriptome-wide Profiling of Cerebral Cavernous Malformations Patients Reveal Important Long noncoding RNA molecular signatures

Cerebral cavernous malformations (CCMs) are low-flow vascular malformations in the brain associated with recurrent hemorrhage and seizures. The current treatment of CCMs relies solely on surgical intervention. Henceforth, alternative non-invasive therapies are urgently needed to help prevent subsequent hemorrhagic episodes. Long non-coding RNAs (lncRNAs) belong to the class of non-coding RNAs and are known to regulate gene transcription and involved in chromatin remodeling via various mechanism. Despite accumulating evidence demonstrating the role of lncRNAs in cerebrovascular disorders, their identification in CCMs pathology remains unknown. The objective of the current study was to identify lncRNAs associated with CCMs pathogenesis using patient cohorts having 10 CCM patients and 4 controls from brain. Executing next generation sequencing, we performed whole transcriptome sequencing (RNA-seq) analysis and identified 1,967 lncRNAs and 4,928 protein coding genes (PCGs) to be differentially expressed in CCMs patients. Among these, we selected top 6 differentially expressed lncRNAs each having significant correlative expression with more than 100 differentially expressed PCGs. The differential expression status of the top lncRNAs, SMIM25 and LBX2-AS1 in CCMs was further confirmed by qRT-PCR analysis. Additionally, gene set enrichment analysis of correlated PCGs revealed critical pathways related to vascular signaling and important biological processes relevant to CCMs pathophysiology. Here, by transcriptome-wide approach we demonstrate that lncRNAs are prevalent in CCMs disease and are likely to play critical roles in regulating important signaling pathways involved in the disease progression. We believe, that detailed future investigations on this set of identified lncRNAs can provide useful insights into the biology and, ultimately, contribute in preventing this debilitating disease.

Benchmark of long non-coding RNA quantification for RNA sequencing of cancer samples

BACKGROUND

Long non-coding RNAs (lncRNAs) are emerging as important regulators of various biological processes. While many studies have exploited public resources such as RNA sequencing (RNA-Seq) data in The Cancer Genome Atlas to study lncRNAs in cancer, it is crucial to choose the optimal method for accurate expression quantification.

RESULTS

In this study, we compared the performance of pseudoalignment methods Kallisto and Salmon, alignment-based transcript quantification method RSEM, and alignment-based gene quantification methods HTSeq and featureCounts, in combination with read aligners STAR, Subread, and HISAT2, in lncRNA quantification, by applying them to both un-stranded and stranded RNA-Seq datasets. Full transcriptome annotation, including protein-coding and non-coding RNAs, greatly improves the specificity of lncRNA expression quantification. Pseudoalignment methods and RSEM outperform HTSeq and featureCounts for lncRNA quantification at both sample- and gene-level comparison, regardless of RNA-Seq protocol type, choice of aligners, and transcriptome annotation. Pseudoalignment methods and RSEM detect more lncRNAs and correlate highly with simulated ground truth. On the contrary, HTSeq and featureCounts often underestimate lncRNA expression. Antisense lncRNAs are poorly quantified by alignment-based gene quantification methods, which can be improved using stranded protocols and pseudoalignment methods.

CONCLUSIONS

Considering the consistency with ground truth and computational resources, pseudoalignment methods Kallisto or Salmon in combination with full transcriptome annotation is our recommended strategy for RNA-Seq analysis for lncRNAs.

Survival analysis and functional annotation of long non-coding RNAs in lung adenocarcinoma

Long non-coding RNAs (lncRNAs) are a subclass of non-protein coding transcripts that are involved in several regulatory processes and are considered as potential biomarkers for almost all cancer types. This study aims to investigate the prognostic value of lncRNAs for lung adenocarcinoma (LUAD), the most prevalent subtype of lung cancer. To this end, the processed data of The Cancer Genome Atlas LUAD were retrieved from GEPIA and circlncRNAnet databases, matched with each other and integrated with the analysis results of a non-small cell lung cancer plasma RNA-Seq study. Then, the data were filtered in order to separate the differentially expressed lncRNAs that have a prognostic value for LUAD. Finally, the selected lncRNAs were functionally annotated using a bioinformatic and systems biology approach. Accordingly, we identified 19 lncRNAs as the novel LUAD prognostic lncRNAs. Also, based on our results, all 19 lncRNAs might be involved in lung cancer-related biological processes. Overall, we suggested several novel biomarkers and drug targets which could help early diagnosis, prognosis and treatment of LUAD patients.

Diagnostic Value of MiR-125b as a Potential Biomarker for Stage I Lung Adenocarcinoma

Background:

We aimed at exploring biological functions of differentially expressed miRNAs during carcinogenesis, to identify miRNAs dysegulations involved in DNA repair mechanisms, and to evaluate potential of miRNAs as prognostic and diagnostic biomarkers for early lung adenocarcinomas (LAC).

Methods:

We obtained 21 LAC and paired adjacent normal formalin-fixed, paraffinembedded lung tissues from patients who underwent curative resection for stage I LAC. We compared expression levels of eight miRNAs involved in the DNA repair mechanism between LAC and adjacent tissues.

Results:

Expressions of Hsa-miR-9-5p, hsa-miR-24-3p, hsa-miR-125a-3p, hsa-miR- 125b-5p, hsa-miR-155-5p, and hsa-let-7a-5p were significantly up-regulated in stage I LAC tissues compared with those in the adjacent tissues. In addition, expressions of hsa-mir-9-5p, hsa-mir-24-3p, hsa-mir-125a-3p, hsa-mir-125b-5p, and hsa-mir-155-5p were significantly up-regulated in stage Ia LAC tissues, whereas expressions of hsa-mir- 125a-3p and hsa-mir-125b-5p were significantly up-regulated in stage Ib LAC tissues. Receiver operating characteristic (ROC) analysis revealed that AUROC of hsa-mir-125b- 5p was 0.875 (P < 0.001).

Conclusion:

Expression of hsa-mir-125b-5p could be used to distinguish LAC from adjacent tissues. Our result suggests that hsa-mir125b-5p can be a prognostic and diagnostic biomarker for LAC.

Downregulation of LINC00515 in high-grade serous ovarian cancer and its relationship with platinum resistance

Aim: To investigate the expression of long intergenic noncoding RNA 00515 (LINC00515) in high-grade serous ovarian cancer (HGSOC) and its potential correlation with platinum resistance. Patients & methods: Expression of LINC00515 in HGSOC (n = 115) and normal (n = 19) tissues was detected via quantitative real-time PCR (qRT-PCR). We further explored the statistical significance of the relationship between LINC00515 expression and platinum resistance in HGSOC. Results: LINC00515 was gradually downregulated in the order of normal > platinum-sensitive > platinum-resistant tissue (p < 0.05). Results demonstrated that LINC00515 downregulation was correlated with platinum resistance and relapse-free survival (RFS) of HGSOC (p < 0.05). Conclusion: LINC00515 downregulation is correlated with HGSOC development, platinum resistance and RFS, supporting its utility as a potential biomarker to predict platinum resistance and prognosis of RFS.

Long noncoding RNA LINC00515 promotes cell proliferation and inhibits apoptosis by sponging miR-16 and activating PRMT5 expression in human glioma

Introduction: In recent years, an increasing amount of literature has demonstrated the functional role of long non-coding RNA (lncRNA) in human diseases. LINC00515 is a newly defined lncRNA and is reported to act as an oncogene in multiple myeloma. However, the function of LINC00515 in glioma is still uncertain.

Materials and methods: We examined the expression levels of LINC00515 in human glioma tissues and cell lines using real-time PCR analysis. In addition, we confirmed the distribution of LINC00515 in glioma cells and suppressed LINC00515 expression with siRNAs. CCK-8, colony formation assay and apoptosis analysis were used to study the function of LINC00515 in glioma progression. Then, we used bioinformatics prediction and subsequent experiments to reveal the underlying molecular mechanism.

Results: We found that LINC00515 was up-regulated in glioma tissues and cell lines. LINC00515 was mainly located in the cytoplasm in glioma cells. Knockdown of LINC00515 led to decreased proliferation and increased apoptosis of glioma cells. Mechanistically, our data indicated that there was a LINC00515/miR-16/PRMT5 regulatory axis in glioma. LINC00515 could activate PRMT5 expression and promote glioma progression by acting as a sponge of miR-16.

Conclusion: LINC00515 expression is elevated in human glioma and promotes growth and inhibits apoptosis of glioma cells. The regulatory cascade LINC00515/miR-16/PRMT5 plays a critical role in glioma progression.

Analysis of long non-coding RNAs in glioblastoma for prognosis prediction using weighted gene co-expression network analysis, Cox regression, and L1-LASSO penalization

Purpose

This study focused on identification of long non-coding RNAs (lncRNAs) for prognosis prediction of glioblastoma (GBM) through weighted gene co-expression network analysis (WGCNA) and L1-penalized least absolute shrinkage and selection operator (LASSO) Cox proportional hazards (PH) model.

Materials and methods

WGCNA was performed based on RNA expression profiles of GBM from Chinese Glioma Genome Atlas (CGGA), National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), and the European Bioinformatics Institute ArrayExpress for the identification of GBM-related modules. Subsequently, prognostic lncRNAs were determined using LASSO Cox PH model, followed by constructing a risk scoring model based on these lncRNAs. The risk score was used to divide patients into high- and low-risk groups. Difference in survival between groups was analyzed using Kaplan-Meier survival analysis. IncRNA-mRNA networks were built for the prognostic lncRNAs, followed by pathway enrichment analysis for these networks.

Results

This study identified eight preserved GBM-related modules, including 188 lncRNAs. Consequently, C20orf166-AS1, LINC00645, LBX2-AS1, LINC00565, LINC00641, and PRRT3-AS1 were identified by LASSO Cox PH model. A risk scoring model based on the lncRNAs was constructed that could divide patients into different risk groups with significantly different survival rates. Prognostic value of this six-lncRNA signature was validated in two independent sets. C20orf166-AS1 was associated with antigen processing and presentation and cell adhesion molecule pathways, involving nine common genes. LBX2-AS1, LINC00641, PRRT3-AS1, and LINC00565 were related to focal adhesion, extracellular matrix receptor interaction, and mitogen-activated protein kinase signaling pathways, which shared 12 common genes.

Conclusion

This prognostic six-lncRNA signature may improve prognosis prediction of GBM. This study reveals many pathways and genes involved in the mechanisms behind these lncRNAs.

Network analysis of differentially expressed smoking-associated mRNAs, lncRNAs and miRNAs reveals key regulators in smoking-associated lung cancer

Lung cancer is the leading cause of cancer-associated mortality worldwide. Smoking is one of the most significant etiological contributors to lung cancer development. However, the molecular mechanisms underlying smoking-induced induction and progression of lung cancer have remained to be fully elucidated. Furthermore, long non-coding RNAs (lncRNAs) are increasingly recognized to have important roles in diverse biological processes. The present study focused on identifying differentially expressed mRNAs, lncRNAs and micro (mi)RNAs in smoking-associated lung cancer. Smoking-associated co-expression networks and protein-protein interaction (PPI) networks were constructed to identify hub lncRNAs and genes in smoking-associated lung cancer. Furthermore, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses of differentially expressed lncRNAs were performed. A total of 314 mRNAs, 24 lncRNAs and 4 miRNAs were identified to be deregulated in smoking-associated lung cancer. PPI network analysis identified 20 hub genes in smoking-associated lung cancer, including dynein axonemal heavy chain 7, dynein cytoplasmic 2 heavy chain 1, WD repeat domain 78, collagen type III α 1 chain (COL3A1), COL1A1 and COL1A2. Furthermore, co-expression network analysis indicated that relaxin family peptide receptor 1, receptor activity modifying protein 2-antisense RNA 1, long intergenic non-protein coding RNA 312 (LINC00312) and LINC00472 were key lncRNAs in smoking-associated lung cancer. A bioinformatics analysis indicated these smoking-associated lncRNAs have a role in various processes and pathways, including cell proliferation and the cyclic guanosine monophosphate cGMP)/protein kinase cGMP-dependent 1 signaling pathway. Of note, these hub genes and lncRNAs were identified to be associated with the prognosis of lung cancer patients. In conclusion, the present study provides useful information for further exploring the diagnostic and prognostic value of the potential candidate biomarkers, as well as their utility as drug targets for smoking-associated lung cancer.

The FENDRR/miR-214-3P/TET2 axis affects cell malignant activity via RASSF1A methylation in gastric cancer

To explore the effect of fetal-lethal non-coding developmental regulatory RNA (FENDRR) in the initiation and progression of gastric cancer (GC). We detected the levels of FENDRR, microRNA-214-3p (miR-214-3p), and ten-eleven-translocation (TET2) in GC tissues and GC cell lines. In addition, we evaluated the location of FENDRR in GC cell lines by fluorescence in situ hybridization (FISH). Cell proliferation and apoptosis were measured by CCK-8 and Hoechst staining assays. Methylation-specific PCR assay (MSP) was used to evaluate the methylation status of ras-association domain family 1A (RASSF1A). We also observed the direct binding of miR-214-3p on FENDRR by dual-luciferase activity assay in GC cells. FENDRR and TET2 expressions were significantly down-regulated and miR-214-3p was up-regulated in gastric cancer tissues compared to adjacent unaffected tissues. In addition, RASSF1A was hypermethylated in gastric cancer tissues compared to adjacent tissues. The expressions of all the three indicators were influenced by differentiation of tumor, TNM stage of tumors, and lymph node metastasis in patients with GC. A gastric cancer cell line with low FENDRR expression compared to a high FENDRR expressing cell line showed again increased miR-214-3p expression, decreased TET2 and RASSF1A expressions, and RASSF1A hypermethylation, resulting in decreased apoptosis and increased proliferation. Furthermore, we observed a negative correlation between FENDRR and miR-214-3p in GC. The FENDRR/miR-214-3P/TET2 axis plays a critical role in GC progress via methylation of RASSF1A.

Roles of miR-200 family members in lung cancer: more than tumor suppressors

miRNAs are a class of single-stranded noncoding RNAs, which have no coding potential, but modulate many molecular mechanisms including cancer pathogenesis. miRNAs participate in cell proliferation, differentiation, apoptosis, as well as carcinogenesis or cancer progression, and their involvement in lung cancer has been recently shown. They are suggested to have bidirectional functions on important cancer-related genes so as to enhance or attenuate tumor genesis. Epithelial-mesenchymal transition (EMT) is a fundamental process which contributes to integrity of organogenesis and tissue differentiation as well as tissue repair, organ fibrosis and the progression of carcinoma, and several miRNAs were suggested to form the network regulating EMT in lung cancer, among which, miR-200 family members (miR-200a, miR-200b, miR-200c, miR-429 and miR-141) play crucial roles in the suppression of EMT.

Long Noncoding RNA LINC00472 Inhibits Proliferation and Promotes Apoptosis of Lung Adenocarcinoma Cells via Regulating miR-24-3p/ DEDD

OBJECTIVE

We aimed to detect the role of LINC00472 via regulating miR-24-3p and death effector domain-containing DNA-binding protein in lung adenocarcinoma.

METHODS

Long noncoding RNA, microRNA, and messenger RNA levels were determined using reverse transcription quantitative polymerase chain reaction. The expression of death effector domain-containing DNA-binding protein was determined using Western blot assay. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and colony formation assay were conducted to explore the proliferation of cells. The cell apoptosis was tested by flow cytometry assay. Target relationships between miR-24-3p, death effector domain-containing DNA-binding protein, and LINC00472 were validated by dual-luciferase reporter gene assay.

RESULTS

LINC00472 and death effector domain-containing DNA-binding protein were found to be underexpressed, whereas miR-24-3p was found overexpressed in lung adenocarcinoma cell lines and tissues. Both LINC00472 and death effector domain-containing DNA-binding protein can bind to miR-24-3p. Overexpression of LINC00472 led to higher death effector domain-containing DNA-binding protein level, demoting cell proliferation while promoting apoptosis. Overexpression of miR-24-3p reduced death effector domain-containing DNA-binding protein level, which facilitated cell proliferation and inhibited cell apoptosis, as well as to some extent restrained the effects of LINC00472. The high expression of miR-24-3p in tumor cells was negatively related to LINC00472 and death effector domain-containing DNA-binding protein, whereas the expression of LINC00472 and that of death effector domain-containing DNA-binding protein were positively correlated.

CONCLUSION

Our findings suggested that LINC00472 contributed to the increase in lung adenocarcinoma cell apoptosis and the inhibition of proliferation via regulating miR-24-3p/ DEDD, which might provide a novel insight into potential therapeutic approach for lung adenocarcinoma.

Identification of ceRNA network based on a RNA-seq shows prognostic lncRNA biomarkers in human lung adenocarcinoma

Previous studies have emphasized the significant functions of long non-coding RNAs (lncRNAs) as competing endogenous RNAs (ceRNAs) in tumor biology. However, the functions of certain cancer lncRNAs in the lncRNA-related ceRNA network in lung adenocarcinoma (LUAD) are unknown. A systematic and integrative survey of RNA-seq data from The Cancer Genome Atlas (TCGA) was performed to identify candidate lncRNAs for the prognosis of LUAD. In total, 20,502 genes that contain 181 lncRNAs were evaluated in a cohort of 570 LUAD cases. Initially, 6,280 differentially expressed genes (fold-change >2, P<0.05) were obtained using R package, which includes 75 lncRNAs. Next, by univariate regression and multivariate Cox proportional hazards analysis, 32 genes were associated with survival in LUAD. Using these 29 mRNAs and 3 lncRNAs, a prognosis index (PI) was calculated to accurately estimate the survival in LUAD: PI=∑exp_{risk gene} × HRrisk gene. Furthermore, the 32-gene signature was an independent prognostic indicator for LUAD (HR >1; P<0.05, by multivariate analysis). Weighted gene co-expression network analysis (WGCNA) of three risk lncRNAs-FAM138B, NHEG1 and TLX1NB-was performed, based on the P-values of the associated genes, and the top 27 miRNAs that bound to these lncRNAs were predicted by Miranda as target miRNAs. Next, these target miRNAs were transferred to the TarBase, miRTarBase, miRecards and starBase v2.0 databases to obtain their target genes. According to the previous miRNA-mRNA and miRNA-lncRNA data, three lncRNA-miRNA-mRNA ceRNA networks were established, based on the 29 prognostic mRNAs, forming a regulatory network in LUAD. The present study provided insight into the lncRNA-related ceRNA network in LUAD and has identified potential diagnostic and prognostic biomarkers.

Lamins in Lung Cancer: Biomarkers and Key Factors for Disease Progression through miR-9 Regulation?

Lung cancer represents the primary cause of cancer death in the world. Malignant cells identification and characterization are crucial for the diagnosis and management of patients with primary or metastatic cancers. In this context, the identification of new biomarkers is essential to improve the differential diagnosis between cancer subtypes, to select the most appropriate therapy, and to establish prognostic correlations. Nuclear abnormalities are hallmarks of carcinoma cells and are used as cytological diagnostic criteria of malignancy. Lamins (divided into A- and B-types) are localized in the nuclear matrix comprising nuclear lamina, where they act as scaffolding protein, involved in many nuclear functions, with regulatory effects on the cell cycle and differentiation, senescence and apoptosis. Previous studies have suggested that lamins are involved in tumor development and progression with opposite results concerning their prognostic role. This review provides an overview of lamins expression in lung cancer and the relevance of these findings for disease diagnosis and prognosis. Furthermore, we discuss the link between A-type lamins expression in lung carcinoma cells and nuclear deformability, epithelial to mesenchymal transition, and metastatic potential, and which mechanisms could regulate A-type lamins expression in lung cancer, such as the microRNA miR-9.

Integrated analysis of long non‑coding RNA competing interactions revealed potential biomarkers in cervical cancer: Based on a public database

Cervical cancer (CC) is a common gynecological malignancy in women worldwide. Using an RNA sequencing profile from The Cancer Genome Atlas (TCGA) and the CC patient information, the aim of the present study was to identify potential long non‑coding RNA (lncRNA) biomarkers of CC using bioinformatics analysis and building a competing endogenous RNA (ceRNA) co‑expression network. Results indicated several CC‑specific lncRNAs, which were associated with CC clinical information and selected some of them for validation and evaluated their diagnostic values. Bioinformatics analysis identified 51 CC‑specific lncRNAs (fold‑change >2 and P<0.05), and 42 of these were included in ceRNA network consisting of lncRNA‑miRNA‑mRNA interactions. Further analyses revealed that differential expression levels of 19 lncRNAs were significantly associated with different clinical features (P<0.05). A total of 11 key lncRNAs in the ceRNA network for reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) analysis to detect their expression levels in 31 pairs of CC clinical samples. The results indicated that 7 lncRNAs were upregulated and 4 lncRNAs were downregulated in CC patients. The fold‑changes between the RT‑qPCR experiments and the TCGA bioinformatics analyses were the same. Furthermore, the area under the receiver operating characteristic (ROC) curve of four lncRNAs (EMX20S, MEG3, SYS1‑DBNDD2 and MIR9‑3HG) indicated that their combined use may have a significant diagnostic value in CC (P<0.05). To the best of our knowledge, the present study is the first to have identified CC‑specific lncRNAs to construct a ceRNA network and has also provided new insights for further investigation of a lncRNA‑associated ceRNA network in CC. In additon, the verification results suggested that the method of bioinformatics analysis and screening of lncRNAs was accurate and reliable. To conclude, the use of multiple lncRNAs may thus improve diagnostic efficacy in CC. In addition, these specific lncRNAs may serve as new candidate biomarkers for clinical diagnosis, classification and prognosis of CC.

Linc00659, a long noncoding RNA, acts as novel oncogene in regulating cancer cell growth in colorectal cancer

Background

Colorectal cancer (CRC) is one of the most common cancers and causes of cancer-related death worldwide. In patients with CRC, metastasis is a crucial problem that leads to treatment failure and is the primary cause of the lethality of colon cancer. Long noncoding RNAs (lncRNAs) have recently emerged as critical molecules in the development, cell growth, apoptosis, and metastasis of CRC.

Method

We investigated the transcriptome profiles of human lncRNAs in the primary tumor tissues and in the corresponding normal mucosa of two patients with CRC by using a microarray approach. The expression levels of lncRNAs were verified in colon cancer by real-time PCR. Using bioinformatics approach to illustrate putative biological function of Linc00659 in colon cancer. The effects of Linc00659 on cell growth, proliferation, cell cycle and apoptosis were studies by in vitro assays.

Results

Our data revealed that compared with adjacent normal tissues, 201 lncRNAs were deregulated (fold change ≥ 4 or ≤ 0.25) in CRC tissues. Among them, the expression levels of Linc00659 were significantly increased in colon cancer, and high expression levels were correlated with poor survival in patients with CRC. Bioinformatics analysis results indicated that Linc00659 was significantly coexpressed with cycle-related genes in CRC. Linc00659 expression knockdown could significantly suppress colon cancer cell growth by impairing cell cycle progression. In addition, our results showed that Linc00659 expression knockdown could accelerate cell apoptosis in colon cancer cells treated with chemotherapy drugs. Meanwhile, our results also demonstrated that silencing of Linc00659 expression leads to cell growth inhibition and induced apoptosis, possibly by suppressing PI3K-AKT signaling in colon cancer.

Conclusion

Linc00659 is a novel oncogenic lncRNA involved in colon cancer cell growth by modulating the cell cycle. Our findings give an insight into lncRNA regulation and provide an application for colon cancer therapy.

Electronic supplementary material

The online version of this article (10.1186/s12943-018-0821-1) contains supplementary material, which is available to authorized users.

Modes of Interaction of KMT2 Histone H3 Lysine 4 Methyltransferase/COMPASS Complexes with Chromatin

Regulation of gene expression is achieved by sequence-specific transcriptional regulators, which convey the information that is contained in the sequence of DNA into RNA polymerase activity. This is achieved by the recruitment of transcriptional co-factors. One of the consequences of co-factor recruitment is the control of specific properties of nucleosomes, the basic units of chromatin, and their protein components, the core histones. The main principles are to regulate the position and the characteristics of nucleosomes. The latter includes modulating the composition of core histones and their variants that are integrated into nucleosomes, and the post-translational modification of these histones referred to as histone marks. One of these marks is the methylation of lysine 4 of the core histone H3 (H3K4). While mono-methylation of H3K4 (H3K4me1) is located preferentially at active enhancers, tri-methylation (H3K4me3) is a mark found at open and potentially active promoters. Thus, H3K4 methylation is typically associated with gene transcription. The class 2 lysine methyltransferases (KMTs) are the main enzymes that methylate H3K4. KMT2 enzymes function in complexes that contain a necessary core complex composed of WDR5, RBBP5, ASH2L, and DPY30, the so-called WRAD complex. Here we discuss recent findings that try to elucidate the important question of how KMT2 complexes are recruited to specific sites on chromatin. This is embedded into short overviews of the biological functions of KMT2 complexes and the consequences of H3K4 methylation.

Long noncoding RNA lncHERG promotes cell proliferation, migration and invasion in glioblastoma

Long noncoding RNAs have recently been proven to regulate tumorgenesis in many cancers. However, their biological functions in glioblastoma remain largely unknown. Here we found an uncharacteristic lncRNA lncHERG that is highly expressed in human glioblastoma (GBM). We found that lncHERG knockdown inhibited cell proliferation, migration and invasion in glioblastoma in vitro and in vivo. Moreover, the higher expression of lncHERG in patients with glioblastoma indicated lower survival rate and poorer prognosis. Mechanistically, we found that lncHERG can serve as a sponge for miR-940 which is a tumor suppressor in cervical cancer and whose function has not been defined in glioblastoma. We showed that miR-940 was down-regulated in glioblastoma tissues compared to peritumor tissues. LncHERG knockdown impaired cell proliferation, migration and invasion while inhibition of miR-940 in the meantime reversed this trend. In conclusion, our study highlights the essential role of lncHERG in glioblastoma by acting as a competing endogenous RNA of miR-940, which may serve as a new prognostic biomarker in glioblastoma.

Comprehensive epigenetic analysis of the signature genes in lung adenocarcinoma

Aim: This study aimed to explore the epigenetic modifications of signature genes in lung adenocarcinoma. Materials & methods: The data of miRNA expression, mRNA expression and DNA methylation were downloaded from The Cancer Genome Atlas. Differential analysis was performed, followed by correlation analysis of miRNA–mRNA and DNA methylation-mRNA. Results: A total of 14 significant inverse correlations between gene expression and DNA methylation were identified, the expressions of which were selected for further validation via GSE27262, displaying similar pattern with that of the integrated analysis. In addition, qRT-PCR results showed that the expression profiling results of six mRNAs and one miRNA were consistent with the findings of integrated analysis. Five genes showed higher diagnostic value, which was also associated with overall survival of patients. Conclusion: Taken together, the epigenetic alterations of signature genes may hold promise for becoming biomarkers for the early detection of lung adenocarcinoma.