CeRNA regulatory network-based analysis to study the roles of noncoding RNAs in the pathogenesis of intrahepatic cholangiocellular carcinoma

MiR-380 inhibits the proliferation and invasion of cholangiocarcinoma cells by silencing LIS1

BACKGROUND

The objective of this study was to determine the role and regulatory mechanism of miR-380 in cholangiocarcinoma.

METHODS

The TargetScan database and a dual-luciferase reporter assay system were used to determine if LIS1 was a target gene of miR-380. The Cell Counting Kit 8 assay, flow cytometry, and Transwell assay were used to detect the effects of miR-380 and LIS1 on the proliferation, S-phase ratio, and invasiveness of HCCC-9810/HuCCT1/QBC939 cells. Western blotting was used to determine the effect of miR-380 on MMP-2/p-AKT. Immunohistochemistry detected the regulatory effect of miR-380 on the expression of MMP-2/p-AKT/LIS1.

RESULTS

Expression of miR-380 in cholangiocarcinoma was decreased but expression of LIS1 was increased. LIS1 was confirmed to be a target gene of miR-380. Transfection with miR-380 mimics inhibited the proliferation, S-phase arrest, and invasion of HCCC-9810/HuCCT1/QBC939 cells, and LIS1 reversed these inhibitory effects. miR-380 inhibitor promoted proliferation, S-phase ratio, and invasiveness of HCCC-9810/HuCCT1/QBC939 cells. si-LIS1 salvaged the promotive effect of miR-380 inhibitor. Overexpression of miR-380 inhibited expression of MMP-2/p-AKT/LIS1, but miR-380 inhibitor promoted their expression.

CONCLUSION

An imbalance of miR-380 expression is closely related to cholangiocarcinoma, and overexpression of miR-380 inhibits the expression of MMP-2/p-AKT by directly targeting LIS1.

METTL3 facilitates multiple myeloma tumorigenesis by enhancing YY1 stability and pri-microRNA-27 maturation in m6A-dependent manner

Multiple myeloma (MM) is a pernicious plasma cell disorder and has a poor prognosis. N6-methyladenosine (m6A) is an abundant epigenetic RNA modification and is important in cancer progression. Nevertheless, the function of m6A and its regulator METTL3 in MM are rarely reported. Here, we identified the m6A "writers", METTL3, was enhanced in MM and found that Yin Yang 1 (YY1) and primary-miR-27a-3p were the potential target for METTL3. METTL3 promoted primary-miR-27a-3p maturation and YY1 mRNA stability in an m6A manner. YY1 also was found to facilitate miR-27a-3p transcription. METTL3 affected the growth, apoptosis, and stemness of MM cells through accelerating the stability of YY1 mRNA and the maturation of primary-miR-27a-3p in vitro and in vivo. Our results reveal the key function of the METTL3/YY1/miR-27a-3p axis in MM and may provide fresh insights into MM therapy.

Circulating miRNAs as a Tool for Early Diagnosis of Endometrial Cancer-Implications for the Fertility-Sparing Process: Clinical, Biological, and Legal Aspects

This review article explores the possibility of developing an integrated approach to the management of the different needs of endometrial cancer (EC) patients seeking to become pregnant. Life preservation of the woman, health preservation of the baby, a precocious and-as much as possible-minimally invasive characterization of the health and fertility parameters of the patient, together with the concerns regarding the obstetric, neonatal, and adult health risks of the children conceived via assisted reproductive techniques (ART) are all essential aspects of the problem to be taken into consideration, yet the possibility to harmonize such needs through a concerted and integrated approach is still very challenging. This review aims to illustrate the main features of EC and how it affects the normal physiology of pre-menopausal women. We also focus on the prospect of a miR-based, molecular evaluation of patient health status, including both EC early diagnosis and staging and, similarly, the receptivity of the woman, discussing the possible evaluation of both aspects using a single specific panel of circulating miRs in the patient, thus allowing a relatively fast, non-invasive testing with a significantly reduced margin of error. Finally, the ethical and legal/regulatory aspects of such innovative techniques require not only a risk-benefit analysis; respect for patient autonomy and equitable health care access allocation are fundamental issues as well.

Genome wide identification and characterization of fertility associated novel CircRNAs as ceRNA reveal their regulatory roles in sheep fecundity

Reproductive traits play a vital role in determining the production efficiency of sheep. Maximizing the production is of paramount importance for breeders worldwide due to the growing population. Circular RNAs (circRNAs) act as miRNA sponges by absorbing miRNA activity through miRNA response elements (MREs) and participate in ceRNA regulatory networks (ceRNETs) to regulate mRNA expression. Despite of extensive research on role of circRNAs as miRNA sponges in various species, their specific regulatory roles and mechanism in sheep ovarian tissue are still not well understood. In this study, we performed whole genome sequencing of circRNAs, miRNA and mRNA employing bioinformatic techniques on ovine tissues of two contrasting sheep breeds "Small tail Han (X_LC) and Dolang sheep (D_LC)", which results into identification of 9,878 circRNAs with a total length of 23,522,667 nt and an average length of 2,381.32 nt. Among them, 44 differentially expressed circRNAs (DECs) were identified. Moreover, correlation between miRNA-mRNA and lncRNA-miRNA provided us with to prediction of miRNA binding sites on nine differentially expressed circRNAs and 165 differentially expressed mRNAs using miRanda. miRNA-mRNA and lncRNA-miRNA pairs with negative correlation were selected to determine the ceRNA score along with positively correlated pairs from lncRNA and mRNA network. Integration of ceRNA score and positively correlated pairs exhibit a significant ternary relationship among circRNAs-miRNA-mRNA demonestrated by ceRNA, comprising of 50 regulatory pairs sharring common nodes and predicted potential differentially expressed circRNAs-miRNAs-mRNAs regulatory axis. Based on functional enrichment analysis shortlisted key ceRNA regulatory pairs associated with reproduction including circRNA_3257-novel579_mature-EPHA3, circRNA_8396-novel130_mature-LOC101102473, circRNA_4140- novel34_mature > novel661_mature-KCNK9, and circRNA_8312-novel339_mature-LOC101110545. Furthermore, expression profiling, functional enrichments and qRT-PCR analysis of key target genes infer their implication in reproduction and metabolism. ceRNA target mRNAs evolutionary trajectories, expression profiling, functional enrichments, subcellular localizations following genomic organizations will provide new insights underlying molecular mechanisms of reproduction, and establish a solid foundation for future research. Graphical abstract summarizing the scheme of study.

Sparse Independence Component Analysis for Competitive Endogenous RNA Co-Module Identification in Liver Hepatocellular Carcinoma

OBJECTIVE

Long non-coding RNAs (lncRNAs) have been shown to be associated with the pathogenesis of different kinds of diseases and play important roles in various biological processes. Although numerous lncRNAs have been found, the functions of most lncRNAs and physiological/pathological significance are still in its infancy. Meanwhile, their expression patterns and regulation mechanisms are also far from being fully understood.

METHODS

In order to reveal functional lncRNAs and identify the key lncRNAs, we develop a new sparse independence component analysis (ICA) method to identify lncRNA-mRNA-miRNA expression co-modules based on the competitive endogenous RNA (ceRNA) theory using the sample-matched lncRNA, mRNA and miRNA expression profiles. The expression data of the three RNA combined together is approximated sparsely to obtain the corresponding sparsity coefficient, and then it is decomposed by using ICA constraint optimization to obtain the common basis and modules. Subsequently, affine propagation clustering is used to perform cluster analysis on the common basis under multiple running conditions to obtain the co-modules for the selection of different RNA elements.

RESULTS

We applied sparse ICA to Liver Hepatocellular Carcinoma (LIHC) dataset and the experiment results demonstrate that the proposed sparse ICA method can effectively discover biologically functional expression common modules.

CONCLUSION

It may provide insights into the function of lncRNAs and molecular mechanism of LIHC. Clinical and Translational Impact Statement-The results on LIHC dataset demonstrate that the proposed sparse ICA method can effectively discover biologically functional expression common modules, which may provide insights into the function of IncRNAs and molecular mechanism of LIHC.

Development and validation of machine learning models for predicting prognosis and guiding individualized postoperative chemotherapy: A real-world study of distal cholangiocarcinoma

BACKGROUND

Distal cholangiocarcinoma (dCCA), originating from the common bile duct, is greatly associated with a dismal prognosis. A series of different studies based on cancer classification have been developed, aimed to optimize therapy and predict and improve prognosis. In this study, we explored and compared several novel machine learning models that might lead to an improvement in prediction accuracy and treatment options for patients with dCCA.

METHODS

In this study, 169 patients with dCCA were recruited and randomly divided into the training cohort (n = 118) and the validation cohort (n = 51), and their medical records were reviewed, including survival outcomes, laboratory values, treatment strategies, pathological results, and demographic information. Variables identified as independently associated with the primary outcome by least absolute shrinkage and selection operator (LASSO) regression, the random survival forest (RSF) algorithm, and univariate and multivariate Cox regression analyses were introduced to establish the following different machine learning models and canonical regression model: support vector machine (SVM), SurvivalTree, Coxboost, RSF, DeepSurv, and Cox proportional hazards (CoxPH). We measured and compared the performance of models using the receiver operating characteristic (ROC) curve, integrated Brier score (IBS), and concordance index (C-index) following cross-validation. The machine learning model with the best performance was screened out and compared with the TNM Classification using ROC, IBS, and C-index. Finally, patients were stratified based on the model with the best performance to assess whether they benefited from postoperative chemotherapy through the log-rank test.

RESULTS

Among medical features, five variables, including tumor differentiation, T-stage, lymph node metastasis (LNM), albumin-to-fibrinogen ratio (AFR), and carbohydrate antigen 19-9 (CA19-9), were used to develop machine learning models. In the training cohort and the validation cohort, C-index achieved 0.763 vs. 0.686 (SVM), 0.749 vs. 0.692 (SurvivalTree), 0.747 vs. 0.690 (Coxboost), 0.745 vs. 0.690 (RSF), 0.746 vs. 0.711 (DeepSurv), and 0.724 vs. 0.701 (CoxPH), respectively. The DeepSurv model (0.823 vs. 0.754) had the highest mean area under the ROC curve (AUC) than other models, including SVM (0.819 vs. 0.736), SurvivalTree (0.814 vs. 0.737), Coxboost (0.816 vs. 0.734), RSF (0.813 vs. 0.730), and CoxPH (0.788 vs. 0.753). The IBS of the DeepSurv model (0.132 vs. 0.147) was lower than that of SurvivalTree (0.135 vs. 0.236), Coxboost (0.141 vs. 0.207), RSF (0.140 vs. 0.225), and CoxPH (0.145 vs. 0.196). Results of the calibration chart and decision curve analysis (DCA) also demonstrated that DeepSurv had a satisfactory predictive performance. In addition, the performance of the DeepSurv model was better than that of the TNM Classification in C-index, mean AUC, and IBS (0.746 vs. 0.598, 0.823 vs. 0.613, and 0.132 vs. 0.186, respectively) in the training cohort. Patients were stratified and divided into high- and low-risk groups based on the DeepSurv model. In the training cohort, patients in the high-risk group would not benefit from postoperative chemotherapy (p = 0.519). In the low-risk group, patients receiving postoperative chemotherapy might have a better prognosis (p = 0.035).

CONCLUSIONS

In this study, the DeepSurv model was good at predicting prognosis and risk stratification to guide treatment options. AFR level might be a potential prognostic factor for dCCA. For the low-risk group in the DeepSurv model, patients might benefit from postoperative chemotherapy.

Impact of lncRNA SOX9-AS1 overexpression on the prognosis and progression of intrahepatic cholangiocarcinoma

BACKGROUND

Intrahepatic cholangiocarcinoma (ICC) is a latent and malignant tumor with a dismal prognosis. This study was to evaluate the clinical relevance and therapeutic potential of SOX9-AS1 expression in ICC.

METHODS

The cancerous tissues and adjacent normal tissues were collected from ICC patients. Blood samples from ICC, hepatocellular carcinoma (HCC) group, the extrahepatic cholangiocarcinoma (ECC) group and the healthy controls were collected. SOX9-AS1 levels were evaluated in tissues (versus normal tissues) and plasma samples (versus plasma from HCC and ECC by quantitative real-time RT-PCR. The diagnostic value of SOX9-AS1 for ICC was estimated using receiver operating characteristic (ROC) curves. The relevancy between SOX9-AS1 expression and overall survival or recurrence-free survival was assessed by Kaplan-Meier curves multivariate analyses. The overexpression and knockdown of SOX9-AS1 on cell behavior were assessed by CCK-8 and transwell assay.

RESULTS

SOX9-AS1 levels were increased in ICC, both in the tissues and the cell lines. The upregulation of SOX9-AS1 showed a highly discriminative profile, distinguishing ICC patients from healthy subjects or HCC or ECC patients. Upregulation of SOX9-AS1 was related to shorter overall survival and recurrence-free survival. Muli-variate analysis revealed that SOX9-AS1 expression was an independent prognostic purpose factor of worst overall survival and recurrence-free survival.

CONCLUSIONS

SOX9-AS1 drives tumor growth and metastasis in ICC. SOX9-AS1 may be applied as a new diagnostic and prognostic purposed marker, in addition to a promising therapeutic target in ICC.

LncRNA RP3-525N10.2-NFKB1-PROS1 triplet-mediated low PROS1 expression is an onco-immunological biomarker in low-grade gliomas: a pan-cancer analysis with experimental verification

Background

Glioma is the most common cancer in the central nervous system, and low grade gliomas are notorious for many types of tumors and heterogeneity. PROS1 not only plays an important role in the blood coagulation system, and recent studies have found that it was correlated with the development of tumors, especially related to tumor immune infiltration. However, the study of underlying role and mechanism of PROS1 in gliomas, especially in low-grade gliomas, is almost absent.

Methods

We integrated the information of patients with LGG in The Cancer Genome Atlas (TCGA) cohort and Chinese Glioma Genome Atlas (CGGA) cohort. Then, we systematically demonstrated the differences and prognostic prognosis value of PROS1 based on multi-omics analyses. In addition, Cell counting kit-8 (CCK-8) assay, colony formation assay, 5-Ethynyl-2’-deoxyuridine (EdU) incorporation assay, and Transwell assays were performed to evaluate cell proliferation and invasion. qRT-PCR and immunohistochemistry were used to evaluate the expression of PROS1 in LGG.

Results

Various bioinformatics approaches revealed that PROS1 was a valuable prognostic marker and may influence tumour development via distinct mechanisms, including expression of DNA methyltransferase, RNA modification, and DNA mismatch repair system genes, copy number variation, single nucleotide variation frequency, genomic heterogeneity, cancer stemness, DNA methylation, and alternative PROS1 splicing. Our analyses indicated that the long non-coding RNA RP3-525N10.2 may “decoy” or “guide” the transcription factor NFKB1 and prevent its association with PROS1, thereby reducing PROS1 expression and improving poor LGG prognosis. PROS1 expression was also closely associated with tumour infiltration by immune cells, especially tumour-associated macrophages, as well as the expression of various immune checkpoint inhibitors, immunomodulators, and immune cell markers.

Conclusion

long non-coding RNA RP3-525N10.2-NFKB1-PROS1 triplet-mediated PROS1 expression could serve as a biomarker for cancer diagnosis, prognosis, therapy selection, and follow-up in LGG patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03536-y.

Analysis of Competitive Endogenous Mechanism and Survival Prognosis of Serum Exosomes in Ovarian Cancer Patients Based on Sequencing Technology and Bioinformatics

Background: We determined the competitive endogenous in serum exosomes of ovarian cancer patients via sequencing technology and raw signal analysis. We performed an in-depth study of the potential mechanisms of ovarian cancer, predicted potential therapeutic targets and performed survival analysis of the potential targets.

Methods: Serum exosomes from three ovarian cancer patients were used as the experimental group, serum exosomes from three patients with uterine fibroids were used as the control group, and whole transcriptome analysis of serum exosomes was performed to identify differentially expressed long noncoding RNAs (lncRNAs) and mRNAs in ovarian cancer. The miRcode database and miRNA target gene prediction website were used to predict the target genes. Cytoscape software was used to generate a competing endogenous RNA (ceRNA) network of competitive endogenous mechanism of serum exosomes in ovarian cancer, and the R language was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the target genes. Finally, the TCGA website was used to download clinical and expression data related to ovarian cancer, and the common potential target genes obtained previously were analyzed for survival.

Results: A total of 117 differentially expressed lncRNAs as well as 513 differentially expressed mRNAs (p < 0.05, |log2 fold change (FC)|≥ 1.0) were obtained by combining sequencing data and raw signal analysis, and 841 predicted target genes were reciprocally mapped by combining the data from the miRcode database and miRNA target gene prediction website, resulting in 11 potential target genes related to ovarian cancer (FGFR3, BMPR1B, TRIM29, FBN2, PAPPA, CCDC58, IGSF3, FBXO10, GPAM, HOXA10, and LHFPL4). Survival analysis of the above 11 target genes revealed that the survival curve was statistically significant (p < 0.05) for HOXA10 but not for the other genes. Through enrichment analysis, we found that the above target genes were mainly involved in biological processes such as regulation of transmembrane receptor protein kinase activity, structural molecule activity with elasticity, transforming growth factor-activated receptor activity, and GABA receptor binding and were mainly enriched in signaling pathways regulating stem cell pluripotency, bladder cancer, glycerolipid metabolism, central carbon metabolism of cancer, and tyrosine stimulation to EGFR in signaling pathways such as resistance to enzyme inhibitors.

Conclusions: The serum exosomal DIO3OS-hsa-miR-27a-3p-HOXA10 competitive endogenous signaling axis affects ovarian cancer development and disease survival by targeting dysregulated transcriptional pathways in cancer.

Cholangiopathies and the noncoding revolution

PURPOSE OF REVIEW

Noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) among others, have attracted a great deal of attention for their potential role as master regulators of gene expression and as therapeutic targets. This review focuses on recent advances on the role of ncRNAs in the pathogenesis, diagnosis and treatment of diseases of the cholangiocytes (i.e. cholangiopathies).

RECENT FINDINGS

In the recent years, there has been an exponential growth in the knowledge on ncRNAs and their role in cholangiopathies, particularly cholangiocarcinoma.

SUMMARY

Although several studies focused on miRNAs as noninvasive biomarkers for diagnosis and staging, several studies also highlighted their functions and provided new insights into disease mechanisms.

Hsa_circRNA_0040462: a sensor of cells' response to CAP treatment with double-edged roles on breast cancer malignancy

Cold atmospheric plasma (CAP) represents a novel onco-therapeutic approach that has demonstrated its efficacy in many types of tumors. The efficacy of CAP is dose-dependent that determines the panel of tumors feasible for receiving CAP treatment under a certain parameter configuration. Identifying markers for easy and fast prognosis of tumors' sensitivity in response to CAP exposure is of critical value towards optimized therapeutic outcome, the lack of which has largely limited the translation of CAP into clinics. Circular RNAs represent a novel type of biomarkers for disease diagnosis that is featured by easy detection and stability. Through whole transcriptome sequencing, followed by in vitro validations, computational predictions and preliminary functional studies, we identified hsa_circRNA_0040462 as a sensor of breast cancer cells' response to CAP treatment. Yet we warrant the use of hsa_circRNA_0040462 as an onco-therapeutic target given its double-edged roles on breast cancer progression, i.e., suppressive on the growth and promotive on the migrative ability of triple negative breast cancer cells. Our study for the first time focused on markers prognostic of CAP's efficacy and tumors' sensitivity to CAP treatment under a certain parameter configuration, and reported hsa_circRNA_0040462 as a sensor of cells' response to CAP treatment. Also, the uncovered dual roles of hsa_circRNA_0040462 further advanced our knowledge on the complex yet critical regulatory functionalities of circular RNAs in cancer progression.

Construction of an HCC recurrence model based on the investigation of immune-related lncRNAs and related mechanisms

Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and play fundamental roles in immune regulation. Growing evidence suggests that immune-related genes and lncRNAs can serve as markers to predict the prognosis of patients with cancers, including hepatocellular carcinoma (HCC). This study aimed to contract an immune-related lncRNA (IR-lncRNA) signature for prospective assessment to predict early recurrence of HCC. A total of 319 HCC samples under radical resection were randomly divided into a training cohort (161 samples) and a testing cohort (158 samples). In the training dataset, univariate, lasso, and multivariate Cox regression analyses identified a 9-IR-lncRNA signature closely related to disease-free survival. Kaplan-Meier analysis, principal component analysis, gene set enrichment analysis, and nomogram were used to evaluate the risk model. The results were further confirmed in the testing cohort. Furthermore, we constructed a competitive endogenous RNA regulatory network. The results of the present study indicated that this 9-IR-lncRNA signature has important clinical implications for improving predictive outcomes and guiding individualized treatment in HCC patients. These IR-lncRNAs and regulated genes may be potential biomarkers associated with the prognosis of HCC.

Exosomes secreted by M2 macrophages promote cancer stemness of hepatocellular carcinoma via the miR-27a-3p/TXNIP pathways

OBJECTIVE

Accumulating evidence has suggested that microRNAs (miRNAs) derived from M2 macrophage-derived exosomes (M2 exosomes) can regulate the progression of hepatocellular carcinoma (HCC). Nevertheless, the effect of miR-27a-3p derived from M2 exosomes on HCC has not been reported. We aim to explore the role of M2 exosomal miR-27a-3p in the cancer stemness of HCC via regulating thioredoxin-interacting protein (TXNIP).

METHODS

Exosomes were extracted from transfected M2 macrophages and were then co-cultured with HCC cells. Expression of miR-27a-3p and TXNIP, stemness, proliferation, drug resistance, migration, invasion and in vivo tumorigenicity of HCC cells were determined to assess the role of M2 exosomal miR-27a-3p in HCC. The binding relationship between miR-27a-3p and TXNIP was detected.

RESULTS

MiR-27a-3p was upregulated and TXNIP was downregulated in HCC cells, and M2 exosomes further upregulated miR-27a-3p. The upregulated M2 exosomal miR-27a-3p promoted stemness, proliferation, drug resistance, migration, invasion and in vivo tumorigenicity of HCC cells. TXNIP was confirmed as a target gene of miR-27a-3p.

CONCLUSION

M2 macrophages-derived exosomal miR-27a-3p promotes cancer stemness of HCC via downregulating TXNIP.

Identification of a novel mutation gene signature HAMP for cholangiocarcinoma through comprehensive TCGA and GEO data mining

Cholangiocarcinoma (CHOL), the second most common malignant liver tumor, is clinically heterogeneous. In this study, we used gene expression profiles of CHOL obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases to identify novel mutation signatures in CHOL. Hepcidin antimicrobial peptide (HAMP) was identified as a novel diagnostic biomarker for CHOL using the intersection of mutation analysis and receiver operating characteristic (ROC) analysis. We then explored the expression signatures of HAMP in CHOL. HAMP-related differentially expressed genes (DEGs) were selected for the identification of hub genes related to HAMP and for prognostic prediction model analysis. Gene set enrichment analysis (GSEA) showed that the HAMP-related DEGs were mainly enriched for signaling pathways related to cholangiocarcinoma development. Through immunohistochemistry validation, clinical cohorts analysis, and TCGA analysis, we investigated the association between HAMP and clinical parameters and found that decreased HAMP expression was correlated with advanced pathological grade and poor prognosis. Besides, we estimated the immune infiltration level in CHOL and its relationship with HAMP expression. The proportion of tumor-infiltrating cells revealed that gamma delta T cells and monocytes were positively correlated with HAMP expression. Besides, HAMP was also correlated with chemokine, CCL16. This evidence suggested that HAMP might contribute to immune activation in the CHOL microenvironment. Therefore, HAMP may play a synergistic role with these immune cells and chemokines to inhibit CHOL development. HAMP serves as a valuable biomarker in CHOL and is closely correlated with its progression.

VECTOR: An Integrated Correlation Network Database for the Identification of CeRNA Axes in Uveal Melanoma

Uveal melanoma (UM) is the most common primary intraocular malignant tumor in adults and, although its genetic background has been extensively studied, little is known about the contribution of non-coding RNAs (ncRNAs) to its pathogenesis. Indeed, its competitive endogenous RNA (ceRNA) regulatory network comprising microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and mRNAs has been insufficiently explored. Thanks to UM findings from The Cancer Genome Atlas (TCGA), it is now possible to statistically elaborate these data to identify the expression relationships among RNAs and correlative interaction data. In the present work, we propose the VECTOR (uVeal mElanoma Correlation NeTwORk) database, an interactive tool that identifies and visualizes the relationships among RNA molecules, based on the ceRNA model. The VECTOR database contains: (i) the TCGA-derived expression correlation values of miRNA-mRNA, miRNA-lncRNA and lncRNA-mRNA pairs combined with predicted or validated RNA-RNA interactions; (ii) data of sense-antisense sequence overlapping; (iii) correlation values of Transcription Factor (TF)-miRNA, TF-lncRNA, and TF-mRNA pairs associated with ChiPseq data; (iv) expression data of miRNAs, lncRNAs and mRNAs both in UM and physiological tissues. The VECTOR web interface can be queried, by inputting the gene name, to retrieve all the information about RNA signaling and visualize this as a graph. Finally, VECTOR provides a very detailed picture of ceRNA networks in UM and could be a very useful tool for researchers studying RNA signaling in UM. The web version of Vector is freely available at the URL reported at the end of the Introduction.

Bioinformatics Analysis of ceRNA Network Related to Polycystic Ovarian Syndrome

Introduction

Polycystic ovary syndrome (PCOS) is caused by the hormonal environment in utero, abnormal metabolism, and genetics, and it is common in women of childbearing age. A large number of studies have reported that lncRNA is important to the biological process of cancer and can be used as a potential prognostic biomarker. Thus, we studied lncRNAs' roles in PCOS in this article.

Methods

We obtained mRNAs', miRNAs', and lncRNAs' expression profiles in PCOS specimens and normal specimens from the National Biotechnology Information Gene Expression Comprehensive Center database. The EdgeR software package is used to distinguish the differentially expressed lncRNAs, miRNAs, and mRNAs. Functional enrichment analysis was carried out by the clusterProfiler R Package, and the lncRNA-miRNA-mRNA interaction ceRNA network was built in Cytoscape plug-in BiNGO and Database for Annotation, Visualization, and Integration Discovery (DAVID), respectively.

Results

We distinguished differentially expressed RNAs, including 1087 lncRNAs, 14 miRNAs, and 566 mRNAs in PCOS. Among them, 410 lncRNAs, 11 miRNAs, and 185 mRNAs were contained in the ceRNA regulatory network. The outcomes from Gene Ontology (GO) analysis showed that the differentially expressed mRNAs (DEMs) were mainly enriched in response to the maternal process involved in female pregnancy, morphogenesis of embryonic epithelium, and the intracellular steroid hormone receptor signaling pathway. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis data showed that DEMs were primarily enriched in pathways related to the TGF-β signaling pathway, Type I diabetes mellitus, and glycolysis/gluconeogenesis. In addition, we chose NONHSAT123397, ENST00000564619, and NONHSAT077997 as key lncRNAs due to their high bearing on PCOS.

Conclusion

ceRNA networks play an important role in PCOS. The research indicated that specific lncRNAs were related to PCOS development. NONHSAT123397, ENST00000564619, and NONHSAT077997 could be regarded as potential diagnostic mechanisms and biomarkers for PCOS. This discovery might provide more effective and more novel insights into the mechanisms of PCOS worthy of further exploration.

A pseudotemporal causality approach to identifying miRNA-mRNA interactions during biological processes

MOTIVATION

microRNAs (miRNAs) are important gene regulators and they are involved in many biological processes, including cancer progression. Therefore, correctly identifying miRNA-mRNA interactions is a crucial task. To this end, a huge number of computational methods has been developed, but they mainly use the data at one snapshot and ignore the dynamics of a biological process. The recent development of single cell data and the booming of the exploration of cell trajectories using 'pseudotime' concept have inspired us to develop a pseudotime-based method to infer the miRNA-mRNA relationships characterizing a biological process by taking into account the temporal aspect of the process.

RESULTS

We have developed a novel approach, called pseudotime causality, to find the causal relationships between miRNAs and mRNAs during a biological process. We have applied the proposed method to both single cell and bulk sequencing datasets for Epithelia to Mesenchymal Transition, a key process in cancer metastasis. The evaluation results show that our method significantly outperforms existing methods in finding miRNA-mRNA interactions in both single cell and bulk data. The results suggest that utilizing the pseudotemporal information from the data helps reveal the gene regulation in a biological process much better than using the static information.

AVAILABILITY AND IMPLEMENTATION

R scripts and datasets can be found at https://github.com/AndresMCB/PTC.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A metabolism-related 4-lncRNA prognostic signature and corresponding mechanisms in intrahepatic cholangiocarcinoma

Background

Long non-coding RNA (lncRNA) plays a critical role in the malignant progression of intrahepatic cholangiocarcinoma (iCCA). This study aimed to establish a 4-lncRNA prognostic signature and explore corresponding potential mechanisms in patients with iCCA.

Methods

The original lncRNA-seq and clinical data were collected from the TCGA and GEO databases. Overlapping and differentially expressed lncRNAs (DE-lncRNAs) were further identified from transcriptome data. Univariate regression analysis was performed to screen survival-related DE-lncRNAs, which were further selected to develop an optimal signature to predict prognosis using multivariate regression analysis. The Kaplan-Meier survival curve visualized the discrimination of the signature on overall survival (OS). The area under the curve (AUC) and C-index were used to verify the predictive accuracy of the signature. Combined with clinical data, multivariate survival analysis was used to reveal the independent predictive capability of the signature. In addition, a prognostic nomogram was constructed. Finally, the common target genes of 4 lncRNAs were predicted by the co-expression method, and the corresponding functions were annotated by GO and KEGG enrichment analysis. Gene set enrichment analysis (GSEA) was also performed to explore the potential mechanism of the signature. Quantitative real-time PCR was used to evaluated the expression of 4 lncRNAs in an independent cohort.

Results

We identified and constructed a 4-lncRNA (AC138430.1, AGAP2-AS1, AP001783.1, and AP005233.2) prognostic signature using regression analysis, and it had the capability to independently predict prognosis. The AUCs were 0.952, 0.909, and 0.882 at 1, 2, and 3 years, respectively, and the C-index was 0.808, which showed good predictive capability. Subsequently, combined with clinical data, we constructed a nomogram with good clinical application. Finally, 252 target genes of all four lncRNAs were identified by the co-expression method, and functional enrichment analysis showed that the signature was strongly correlated with metabolism-related mechanisms in tumourigenesis. The same results were also validated via GSEA.

Conclusion

We demonstrated that a metabolism-related 4-lncRNA prognostic signature could be a novel biomarker and deeply explored the target genes and potential mechanism. This study will provide a promising therapeutic strategy for patients with intrahepatic cholangiocarcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08322-5.

Identification and Development of Long Non-coding RNA Associated Regulatory Network in Pancreatic Adenocarcinoma

Background and Aims

Pancreatic adenocarcinoma (PAAD) is the most lethal cancer type around the world. With the in-depth exploration of the function of long non‐coding RNAs (lncRNAs), the competing endogenous RNA (ceRNA) mechanism has shown its potential to partially reveal the pathogenesis of PAAD. This study aimed to construct a lncRNA‐associated ceRNA network and explore ceRNA regulatory axes with experimental and prognostic value in PAAD.

Methods

First, we applied differential expression analysis in the TCGA_PAAD dataset. Then, interaction analysis and survival analysis in multiple RNA interaction databases were conducted to construct a ceRNA network. Finally, a potential regulatory axis was validated using clinical samples and cell lines by quantitative realtime PCR (qRT‐PCR).

Results

A ceRNA network comprising 13 lncRNAs, 96 miRNAs, and 30 mRNAs was successfully constructed. Survival analysis further narrowed this network to five lncRNAs, three miRNAs, and seven mRNAs, which were significantly associated with patients’ overall survival. A potential regulatory axis CASC8-miR-129-5p-TOB1 was further experimentally validated. The expression of these genes was associated with clinicopathological factors and their expression trend was consistent with ceRNA mechanism. Specifically, knockdown of lncRNA-CASC8 led to the overexpression of miR-129-5p and down-regulation of TOB1, while overexpression of CASC8 showed opposite effects.

Conclusion

This novel ceRNA regulatory network could provide new insight into the pathogenesis of PAAD. The new regulatory axis CASC8-miR-129-5p-TOB1 might serve as a potential therapeutic target for patients.

Emerging roles of long noncoding RNAs in cholangiocarcinoma: Advances and challenges

Cholangiocarcinoma (CCA), a cancer with a relatively low incidence rate, is usually associated with poor prognosis. Current modalities for the diagnosis and treatment of CCA patients are still far from satisfactory. In recent years, numerous long noncoding RNAs (lncRNAs) have been identified as crucial players in the development of various cancers, including CCA. Abnormally expressed lncRNAs in CCA, regulated by some upstream molecules, significantly influence the biological behavior of tumor cells and are involved in tumor development through various mechanisms, including interactions with functional proteins, participation in competing for endogenous RNA (ceRNA) regulatory networks, activation of cancer‐related signaling pathways and epigenetic modification of gene expression. Furthermore, several lncRNAs are closely associated with the clinicopathological features of CCA patients, and are promising biomarkers for diagnosing and prognostication of CCA. Some of these lncRNAs play an important role in chemotherapy drug resistance. In addition, lncRNAs have also been shown to be involved in the inflammation microenvironment of CCA and malignant outcome of CCA risk factors, such as cholestatic liver diseases. In view of the difficulty of diagnosing CCA, more attention should be paid to detectable lncRNAs in the serum or bile. This review summarizes the recent knowledge on lncRNAs in CCA and provides a new outlook on the molecular mechanisms of CCA development from the perspective of lncRNAs. Moreover, we also discussed the limitations of the current studies and differential expression of lncRNAs in different types of CCA.

Knockdown of lncRNA LINC01234 Suppresses the Tumorigenesis of Liver Cancer via Sponging miR-513a-5p

Background

Liver cancer is a frequent malignancy with poor prognosis and high mortality all over the world. It has been reported many lncRNAs could modulate the tumorigenesis of liver cancer. To identify novel potential targets for liver cancer, the differential expressed lncRNAs between liver cancer and adjacent normal tissues was analyzed with bioinformatics tool.

Methods

The differential expressed lncRNAs between liver cancer and adjacent normal tissues were analyzed with bioinformatics tool. Cell viability and proliferation was tested by CCK8 and Ki67, respectively. Apoptosis of liver cancer cells was tested by flow cytometry. Gene and protein expressions in liver cancer cells were measured by qRT-PCR and western blot, respectively. In vivo model of liver cancer was established to detect the effect of LINC01234 on liver cancer in vivo.

Results

LINC01234 was found to be negatively correlated with the survival rate of patients with liver cancer. Moreover, knockdown of LINC01234 significantly suppressed the proliferation and invasion of liver cancer cells via inducing the apoptosis. Meanwhile, miR-513a-5p was sponged by LINC01234, and USP4 was found to be a direct target of miR-513a-5p. In addition, LINC01234 knockdown inhibited the tumorigenesis of liver cancer via inactivating TGF-β signaling. Furthermore, silencing of LINC01234 notably inhibited the tumor growth of liver cancer in vivo.

Conclusion

Downregulation of LINC01234 could inhibit the tumorigenesis of liver cancer via mediation of miR-513a-5p/USP4/TGF-β axis. Thus, LINC01234 might serve as a new target for the treatment of liver cancer.

Long Non-Coding RNA LINC00662 Regulated Proliferation and Migration by Targeting miR-34a-5p/LMAN2L Axis in Glioma

Background

Numerous studies suggest that long non-coding RNAs (lncRNAs) participate in the biological process of diverse malignancies, including glioma. Although many differentially expressed lncRNAs have been identified in glioma, to our best knowledge, the role of LINC00662 and its potential underlying mechanism in glioma progression remains unclear. This study aimed to explore the function and regulatory network of LINC00662 in glioma.

Methods

Expressions of LINC00662, miR-34a-5p and lectin mannose-binding 2-like (LMAN2L) in glioma tissues were analyzed using The Cancer Genome Atlas Program (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases. Colony formation, Celltiter-Glo and BrdU (5-bromo-2'-deoxyuridine) incorporation assays were used to detect cell proliferation in vitro. Xenograft mouse models were established to determine cell proliferation in vivo. Transwell and wound healing assay was used to detect cell migration. In addition, epithelial-mesenchymal transition (EMT) markers were detected by Western blot. Annexin V and 7-AAD were used to stain apoptotic cells. Interactions between miR-34a-5p and LINC00662 or the 3'-UTR of LMAN2L were predicted and determined by bioinformatics analysis, luciferase reporter assay and RNA immunoprecipitation (RIP) assays.

Results

High LINC00662 level predicted poor overall survival of glioma patients. Functional studies revealed that suppression of LINC00662 remarkably inhibited cell proliferation, clonogenicity and EMT pathway. Mechanistically, LINC00662 sponged miR-34a-5p to regulate LMAN2L expression. Furthermore, miR-34a-5p inhibitor reversed the anti-proliferation and anti-migration effect of LINC00662 knockdown, which could be rescued by downregulation of LMAN2L in glioma cells.

Conclusion

Our study was the first to report that LINC00662 acted as a competing endogenous RNA (ceRNA) to regulate glioma progression by targeting miR-34a-5p/LMAN2L axis, providing a new therapeutic target for glioma.

Comprehensive analysis of long non‑coding RNA using an associated competitive endogenous RNA network in Wilms tumor

Wilms tumor (WT) is the most common malignant renal neoplasm in children; however, the underlying molecular mechanisms are not well understood. According to the competing endogenous RNA (ceRNA) theory, long non-coding RNAs (lncRNAs) can regulate the expression of target genes by adsorbing microRNAs (miRNAs/miRs). However, the role of lncRNAs in WT has not been fully elucidated. The aim of the present study was to construct a ceRNA network to identify the potential lncRNAs involved in WT. The expression profiles of lncRNAs, miRNAs and mRNAs in 120 WT and six normal tissues were obtained from the Therapeutically Applicable Research to Generate Effective Treatments database. A total of 442 lncRNAs, 214 miRNAs and 4,912 mRNAs were identified as differentially expressed in WT and were enriched in 472 Gene Ontology terms (355 biological processes, 89 cellular components and 29 molecular functions) and 18 Kyoto Encyclopedia of Genes and Genomes pathways. A lncRNA-miRNA-mRNA ceRNA network of WT consisting of with 32 lncRNAs, 14 miRNAs and 158 mRNAs was constructed, based on the bioinformatics analysis of the miR target prediction database and the miRNAcode, miRTarBase and TargetScan databases. Subsequently, three lncRNAs, three miRNAs and 17 mRNAs, which had a significant effect on the overall survival rate of patients with WT, were identified based on the survival analysis. The three lncRNAs were also differentially expressed in the late and early stages of WT and were validated using the GSE66405 dataset obtained from the Gene Expression Omnibus database. In conclusion, the present study generated a specific lncRNA-related ceRNA network of WT, which may provide a novel perspective on the molecular mechanisms underlying the progression and prognosis of the disease.