Investigating miRNA-lncRNA Interactions: Computational Tools and Resources

Transcranial focused ultrasound stimulation alleviates NLRP3-related neuroinflammation induced by ischemic stroke via regulation of the Nespas/miR-383-3p/SHP2 pathway

Transcranial focused ultrasound stimulation (tFUS) has emerged as a promising therapeutic strategy for mitigating brain injury in animal models. In this study, the effects and mechanisms of tFUS on ischemic stroke were explored in a transient middle cerebral artery occlusion (MCAO) rat model. Low-intensity tFUS was administered to the ischemic hemisphere 24 h post-MCAO for seven consecutive days. Neurological function was evaluated through neurobehavioral assessments following tFUS treatment. Western blotting, immunofluorescence staining, and quantitative real-time PCR were performed to examine the impact of tFUS on NLRP3-related neuroinflammation using brain tissues from MCAO rats and BV2 cells subjected to oxygen glucose deprivation/reperfusion (OGD/R). Additionally, RNA sequencing and cell transient transfection were employed to elucidate the underlying mechanisms. The findings revealed that tFUS improved neurobehavioral performance, reduced infarct size, and suppressed NLRP3 inflammasome activation seven days post-MCAO. Notably, Nespas expression was significantly elevated in tFUS-treated rats, whereas Nespas silencing exacerbated neurological deficits and enhanced NLRP3 activation. Moreover, Nespas positively regulated src homology 2 domain-containing tyrosine phosphatase-2 (SHP2), and SHP2 inhibition significantly amplified NLRP3 activation. Mechanistic in vitro studies further demonstrated that Nespas attenuated microglial NLRP3 activation via the Nespas/miR-383-3p/SHP2 pathway. These results suggest that the neuroprotective effects of tFUS are likely mediated through the upregulation of Nespas and suppression of NLRP3 via the Nespas/miR-383-3p/SHP2 axis, offering new insights into the molecular mechanisms supporting tFUS as a potential therapeutic approach for stroke-induced brain injury.

Pivotal Role of miRNA-lncRNA Interactions in Human Diseases

New technologies have shown that most of the genome comprises transcripts that cannot code for proteins and are referred to as non-coding RNAs (ncRNAs). Some ncRNAs, like long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), are of substantial interest because of their critical function in controlling genes and numerous biological activities. The expression levels and function of miRNAs and lncRNAs are rigorously monitored throughout developmental processes and the maintenance of physiological homeostasis. Due to their critical roles, any dysregulation or changes in their expression can significantly influence the pathogenesis of various human diseases. The interactions between miRNAs and lncRNAs have been found to influence gene expression in various ways. These interactions significantly influence the understanding of disease etiology, cellular processes, and potential therapeutic targets. Different experimental and in silico methods can be used to investigate miRNA-lncRNA interactions. By aiding the elucidation of miRNA-lncRNA interactions and deepening the understanding of post-transcriptional gene regulation, researchers can open a new window for designing hypotheses, conducting experiments, and discovering methods for diagnosing and treating complex human diseases. This review briefly summarizes miRNA and lncRNA functions, discusses their interaction mechanisms, and examines the experimental and computational methods used to study these interactions. Additionally, we highlight significant studies on lncRNA and miRNA interactions in various diseases from 2000 to 2024, using the academic research databases such as PubMed, Google Scholar, ScienceDirect, and Scopus.

ncRNAInter: a novel strategy based on graph neural network to discover interactions between lncRNA and miRNA

In recent years, many studies have illustrated the significant role that non-coding RNA (ncRNA) plays in biological activities, in which lncRNA, miRNA and especially their interactions have been proved to affect many biological processes. Some in silico methods have been proposed and applied to identify novel lncRNA-miRNA interactions (LMIs), but there are still imperfections in their RNA representation and information extraction approaches, which imply there is still room for further improving their performances. Meanwhile, only a few of them are accessible at present, which limits their practical applications. The construction of a new tool for LMI prediction is thus imperative for the better understanding of their relevant biological mechanisms. This study proposed a novel method, ncRNAInter, for LMI prediction. A comprehensive strategy for RNA representation and an optimized deep learning algorithm of graph neural network were utilized in this study. ncRNAInter was robust and showed better performance of 26.7% higher Matthews correlation coefficient than existing reputable methods for human LMI prediction. In addition, ncRNAInter proved its universal applicability in dealing with LMIs from various species and successfully identified novel LMIs associated with various diseases, which further verified its effectiveness and usability. All source code and datasets are freely available at https://github.com/idrblab/ncRNAInter.

Long noncoding RNA SNHG14 knockdown exerts a neuroprotective role in MPP+-induced Parkinson's disease cell model through mediating miR-135b-5p/KPNA4 axis

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative disease resulted from the loss of dopaminergic neurons. Here, we analyzed the role of long noncoding RNA (lncRNA) small nucleolar RNA host gene 14 (SNHG14) in PD using 1-methyl-4-phenyl pyridine (MPP⁺)-induced PD cell model.

METHODS

Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and Western blot assay were performed to determine RNA and protein expression, respectively. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and flow cytometry (FCM) analysis were conducted to analyze cell viability and apoptosis. Enzyme-Linked Immunosorbent Assay (ELISA) was conducted to analyze the release of inflammatory cytokines. Cytotoxicity was assessed using reactive oxygen species (ROS) assay kit, superoxide dismutase (SOD) activity assay kit and lactate dehydrogenase (LDH) activity assay kit. Dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay were performed to confirm the interaction between microRNA-135b-5p (miR-135b-5p) and SNHG14 or karyopherin subunit alpha 4 (KPNA4).

RESULTS

MPP⁺ treatment elevated the expression of SNHG14 in SK-N-SH cells in a dose and time-dependent manner. SNHG14 knockdown alleviated MPP⁺-induced apoptosis, inflammation, and cytotoxicity in SK-N-SH cells. SNHG14 interacted with miR-135b-5p, and SNHG14 silencing-mediated effects were partly overturned by miR-135b-5p knockdown in PD cell model. Besides, miR-135b-5p interacted with the 3' untranslated region (3'UTR) of KPNA4, and KPNA4 overexpression partly reversed miR-135b-5p overexpression-induced effects in PD cell model. SNHG14 knockdown reduced the protein level of KPNA4 partly by up-regulating miR-135b-5p in SK-N-SH cells.

CONCLUSION

SNHG14 promoted MPP⁺-induced neuro injury in PD cell model through mediating miR-135b-5p/KPNA4 axis.

BoT-Net: a lightweight bag of tricks-based neural network for efficient LncRNA–miRNA interaction prediction

Background and objective:

Interactions of long non-coding ribonucleic acids (lncRNAs) with micro-ribonucleic acids (miRNAs) play an essential role in gene regulation, cellular metabolic, and pathological processes. Existing purely sequence based computational approaches lack robustness and efficiency mainly due to the high length variability of lncRNA sequences. Hence, the prime focus of the current study is to find optimal length trade-offs between highly flexible length lncRNA sequences.

Method

The paper at hand performs in-depth exploration of diverse copy padding, sequence truncation approaches, and presents a novel idea of utilizing only subregions of lncRNA sequences to generate fixed-length lncRNA sequences. Furthermore, it presents a novel bag of tricks-based deep learning approach “Bot-Net” which leverages a single layer long-short-term memory network regularized through DropConnect to capture higher order residue dependencies, pooling to retain most salient features, normalization to prevent exploding and vanishing gradient issues, learning rate decay, and dropout to regularize precise neural network for lncRNA–miRNA interaction prediction.

Results

BoT-Net outperforms the state-of-the-art lncRNA–miRNA interaction prediction approach by 2%, 8%, and 4% in terms of accuracy, specificity, and matthews correlation coefficient. Furthermore, a case study analysis indicates that BoT-Net also outperforms state-of-the-art lncRNA–protein interaction predictor on a benchmark dataset by accuracy of 10%, sensitivity of 19%, specificity of 6%, precision of 14%, and matthews correlation coefficient of 26%.

Conclusion

In the benchmark lncRNA–miRNA interaction prediction dataset, the length of the lncRNA sequence varies from 213 residues to 22,743 residues and in the benchmark lncRNA–protein interaction prediction dataset, lncRNA sequences vary from 15 residues to 1504 residues. For such highly flexible length sequences, fixed length generation using copy padding introduces a significant level of bias which makes a large number of lncRNA sequences very much identical to each other and eventually derail classifier generalizeability. Empirical evaluation reveals that within 50 residues of only the starting region of long lncRNA sequences, a highly informative distribution for lncRNA–miRNA interaction prediction is contained, a crucial finding exploited by the proposed BoT-Net approach to optimize the lncRNA fixed length generation process.

Availability:

BoT-Net web server can be accessed at https://sds_genetic_analysis.opendfki.de/lncmiRNA/.

Graphic Abstract

DeepWalk based method to predict lncRNA-miRNA associations via lncRNA-miRNA-disease-protein-drug graph

BACKGROUND

Long non-coding RNAs (lncRNAs) play a crucial role in diverse biological processes and have been confirmed to be concerned with various diseases. Largely uncharacterized of the physiological role and functions of lncRNA remains. MicroRNAs (miRNAs), which are usually 20-24 nucleotides, have several critical regulatory parts in cells. LncRNA can be regarded as a sponge to adsorb miRNA and indirectly regulate transcription and translation. Thus, the identification of lncRNA-miRNA associations is essential and valuable.

RESULTS

In our work, we present DWLMI to infer the potential associations between lncRNAs and miRNAs by representing them as vectors via a lncRNA-miRNA-disease-protein-drug graph. Specifically, DeepWalk can be used to learn the behavior representation of vertices. The methods of fingerprint, k-mer and MeSH descriptors were mainly used to learn the attribute representation of vertices. By combining the above two kinds of information, unknown lncRNA-miRNA associations can be predicted by the random forest classifier. Under the five-fold cross-validation, the proposed DWLMI model obtained an average prediction accuracy of 95.22% with a sensitivity of 94.35% at the AUC of 98.56%.

CONCLUSIONS

The experimental results demonstrated that DWLMI can effectively predict the potential lncRNA-miRNA associated pairs, and the results can provide a new insight for related non-coding RNA researchers in the field of combing biology big data with deep learning.

METTL3-mediated LINC00657 promotes osteogenic differentiation of mesenchymal stem cells via miR-144-3p/BMPR1B axis

N6-methyladenosine (m6A) modification plays a crucial role in the progression of osteoporosis (OP). The study aimed to explore the effects of methyltransferase-like 3 (METTL3) in OP. The levels of METTL3, LINC00657, miR-144-3p and BMPR1B were detected using qPCR. Osteogenesis was assessed using alizarin red and alkaline phosphatase (ALP) staining assays. The protein expression of Bglap, Runx2 and Col1a1 was measured by western blot. The targets of LINC00657 and miR-144-3p were screened by bioinformatic analysis. The interaction between miR-144-3p and LINC00657 or BMPR1B was analyzed by dual-luciferase reporter assay and RNA pull-down assay. The results showed that METTL3 was downregulated in OP. METTL3 mediated m6A methylation of LINC00657 to promote the development of osteogenesis. Further study indicated that LINC00657 functioned as a ceRNA to upregulate BMPR1B via sponging miR-144-3p. Additionally, BMPR1B knockdown alleviated the effects of METTL3 on osteogenesis of bone marrow mesenchymal stem cells (BMSCs). Taken together, METTL3 facilitated osteogenic differentiation of BMSCs via the LINC00657/miR-144-3p/BMPR1B axis. Our findings may provide a novel insight of m6A methylation in the development of OP.

LncRNA IPW inhibits growth of ductal carcinoma in situ by downregulating ID2 through miR-29c

BACKGROUND

Ductal carcinoma in situ (DCIS) of breast is the noninvasive lesion that has propensity to progress to the malignant form. At present, it is still unknown which lesions can potentially progress to invasive forms. In this study, we aimed to identify key lncRNAs involved in DCIS growth.

METHODS

We employ disease-related lncProfiler array to identify IPW in specimens of DCIS and matching control samples and validate the observations in three DCIS-non-tumorigenic cell lines. Further, we examine the mechanism of IPW action and the downstream signaling in in vitro and in vivo assays. Importantly, we screened a library containing 390 natural compounds to identify candidate compound selectively inhibiting IPW low DCIS cells.

RESULTS

We identified lncRNA IPW as a novel tumor suppressor critical for inhibiting DCIS growth. Ectopic expression of IPW in DCIS cells strongly inhibited cell proliferation, colony formation and cell cycle progression while silencing IPW in primary breast cells promoted their growth. Additionally, orthotropic implantation of cells with ectopic expression of IPW exhibited decreased tumor growth in vivo. Mechanistically, IPW epigenetically enhanced miR-29c expression by promoting H3K4me3 enrichment in its promoter region. Furthermore, we identified that miR-29c negatively regulated a stemness promoting gene, ID2, and diminished self-renewal ability of DCIS cells. Importantly, we screened a library containing 390 natural compounds and identified toyocamycin as a compound that selectively inhibited the growth of DCIS with low expression of IPW, while it did not affect DCIS with high IPW expression. Toyocamycin also suppressed genes associated with self-renewal ability and inhibited DCIS growth in vivo.

CONCLUSION

Our findings revealed a critical role of the IPW-miR-29c-ID2 axis in DCIS formation and suggested potential clinical use of toyocamycin for the treatment of DCIS.

Non-Coding RNA Polymorphisms (rs2910164 and rs1333049) Associated With Prognosis of Lung Cancer Under Platinum-Based Chemotherapy

Purpose: Lung cancer is the largest cause of cancer deaths in the world. Platinum-based chemotherapy is a foundation of first-line chemotherapy. However, the prognosis of lung cancer treated with platinum-based chemotherapy is still a challenge. Single nucleotide polymorphism of non-coding RNA has the potential to be a biomarker, but its effectiveness has yet to be comprehensively assessed. In this study, we explored the association between polymorphisms of non-coding RNA and prognosis of lung cancer patients receiving platinum-based chemotherapy.

Materials and Methods: For 446 lung cancer patients receiving platinum-based chemotherapy, 22 single nucleotide polymorphisms of microRNA and long noncoding RNA were genotyped by MALDI-TOF mass spectrometry. Cox regression analysis, Kaplan-Meier method, and long-rank test have been performed to assess the association of overall and progression-free survival with polymorphisms.

Results: In the additive and dominant models, genetic polymorphism of ANRIL rs1333049 (G > C) was significantly associated with progression-free survival. Additive model: CC vs GC vs GG [HR = 0.84, p = 0.021, 95% CI (0.73–0.97)]; Recessive model: CC vs GG + GC [HR = 0.77, p = 0.026, 95% CI (0.61–0.97)]. In the dominant model, compared with the CC genotype patients, lower risk of death [HR = 0.81, p = 0.036, 95% CI (0.66–0.99)] and lower risk of progression [HR = 0.81, p = 0.040, 95% CI (0.67–0.99)] have been observed on the patients with CG or GG genotype in miR-146A rs2910164.

Conclusion: Our research demonstrated the potential of using ANRIL rs1333049 (G > C) and miR-146A rs2910164 (C > G) as biomarkers to support the prediction of a better prognosis for lung cancer patients receiving platinum-based chemotherapy.

A systematic evaluation of the computational tools for lncRNA identification

The computational identification of long non-coding RNAs (lncRNAs) is important to study lncRNAs and their functions. Despite the existence of many computation tools for lncRNA identification, to our knowledge, there is no systematic evaluation of these tools on common datasets and no consensus regarding their performance and the importance of the features used. To fill this gap, in this study, we assessed the performance of 17 tools on several common datasets. We also investigated the importance of the features used by the tools. We found that the deep learning-based tools have the best performance in terms of identifying lncRNAs, and the peptide features do not contribute much to the tool accuracy. Moreover, when the transcripts in a cell type were considered, the performance of all tools significantly dropped, and the deep learning-based tools were no longer as good as other tools. Our study will serve as an excellent starting point for selecting tools and features for lncRNA identification.

Recent development of bioinformatics tools for microRNA target prediction

MicroRNAs (miRNAs) are central players that regulate the post-transcriptional processes of gene expression. Binding of miRNAs to target mRNAs can repress their translation by inducing the degradation or by inhibiting the translation of the target mRNAs. High-throughput experimental approaches for miRNA target identification are costly and time-consuming, depending on various factors. It is vitally important to develop the bioinformatics methods for accurately predicting miRNA targets. With the increase of RNA sequences in the post-genomic era, bioinformatics methods are being developed for miRNA studies specially for miRNA target prediction. This review summarizes the current development of state-of-the-art bioinformatics tools for miRNA target prediction, points out the progress and limitations of the available miRNA databases, and their working principles. Finally, we discuss the caveat and perspectives of the next-generation algorithms for the prediction of miRNA targets.

Long non-coding RNA maternally expressed gene 3 affects cell proliferation, apoptosis and migration by targeting the microRNA-9-5p/midkine axis and activating the phosphoinositide-dependent kinase/AKT pathway in hepatocellular carcinoma

Long non-coding RNA (lncRNA) maternally expressed gene 3 (MEG3) is a tumor suppressor in several cancers, such as glioma, prostate cancer and esophageal cancer. However, the role of MEG3 in hepatocellular carcinoma (HCC) and the related molecular mechanisms are not well understood. The present study aimed to determine the biological function of MEG3 in regulating HCC cell viability, apoptosis and migration. In addition, the interaction between MEG3, microRNA (miR)-9-5p and Midkine (MDK), and the activation of the phosphoinositide-dependent kinase (PDK)/AKT pathway in HCC cell line MHCC-97L were examined. Luciferase reporter assays, reverse transcription-quantitative PCR and western blotting were used to determine the interaction between MEG3, miR-9-5p and MDK and the activation of the PDK/AKT pathway. Cell viability was determined by the CCK8 assay and the cell cycle analysis using flow cytometry analysis. Cell apoptosis was examined by flow cytometry analysis and caspase 3/9 activity. Wound healing assays and western blotting were used to investigate cell migration. The present study demonstrated that MEG3 suppressed HCC cell viability and migration, and induced cell apoptosis. In addition, it was also found that MEG3 targets the miR-9-5p/MDK axis and modulates the PDK/AKT pathway in HCC. In conclusion, the findings of the present study demonstrated that lncRNA MEG3 affects HCC cell viability, apoptosis and migration through its targeting of miR-9-5p/MDK and regulation of the PDK/AKT pathway. The MEG3/miR-9-5p/MDK axis may be a potential therapeutic target in HCC.

Functional Interaction among lncRNA HOTAIR and MicroRNAs in Cancer and Other Human Diseases

Simple Summary

This review aimed to describe the contribution of functional interaction between the lncRNA HOTAIR and microRNAs in human diseases, including cancer. HOTAIR/miRNAs complexes interfere with different cellular processes during carcinogenesis, mainly deregulating a series of oncogenic signaling pathways. A great number of ncRNAs-related databases have been established, supported by bioinformatics technologies, to identify the ncRNA-mediated sponge regulatory network. These approaches need experimental validation through cells and animal models studies. The optimization of systems to interfere with HOTAIR/miRNAs interplay could represent a new tool for the definition of diagnostic therapeutics in cancer patients.

Abstract

LncRNAs are a class of non-coding RNAs mostly involved in regulation of cancer initiation, metastatic progression, and drug resistance, through participation in post-transcription regulatory processes by interacting with different miRNAs. LncRNAs are able to compete with endogenous RNAs by binding and sequestering miRNAs and thereby regulating the expression of their target genes, often represented by oncogenes. The lncRNA HOX transcript antisense RNA (HOTAIR) represents a diagnostic, prognostic, and predictive biomarker in many human cancers, and its functional interaction with miRNAs has been described as crucial in the modulation of different cellular processes during cancer development. The aim of this review is to highlight the relation between lncRNA HOTAIR and different microRNAs in human diseases, discussing the contribution of these functional interactions, especially in cancer development and progression.

LncRNA HOTAIR promotes breast cancer progression through regulating the miR-129-5p/FZD7 axis

Breast cancer is the most common malignancies worldwide. LncRNA HOX transcript antisense intergenic RNA (HOTAIR) has been shown to promote progression and metastasis of various cancers, including breast cancer. This reasearch aimed to investigate the downstream regulatory pathways of HOTAIR in breast cancer. The levels of HOTAIR and miR-129-5p were examined in breast cancer tissues and SKBR3 and MCF7 cells by quantitative real-time PCR (qRT-PCR). Cell proliferation was examined by Cell Counting Kit-8 (CCK-8) assay. Cell migration and invasion were estimated by transwell assay. Epithelial-to-mesenchymal transition (EMT)-related markers (E-cadherin, N-cadherin and Vimentin) were measured by Western blot assay. The expression of Frizzled 7 (FZD7) was detected using qRT-PCR or Western blot assay. Bioinformatics analysis, luciferase reporter assay or RNA Immunoprecipitation (RIP) assay was performed to explore the molecular mechanism of HOTAIR in breast cancer. Xenograft analysis was utilized to evaluate the tumor growth in vivo. HOTAIR and FZD7 were upregulated, while miR-129-5p was down-regulated in breast cancer tissues and cells. Knockdown of miR-129-5p reversed the effect of HOTAIR knockdown on cell proliferation, migration, invasion and EMT. FZD7 restored the inhibition of miR-129-5p on breast cancer progression. Furthermore, HOTAIR was a sponge of miR-129-5p and FZD7 was a target of miR-129-5p. Knockdown of HOTAIR inhibited the tumor growth in vivo. HOTAIR facilitated breast cancer progression by regulating the miR-129-5p/FZD7 axis, indicating that HOTAIR may be a potential biomarker and therapeutic target for breast cancer.

LMI-DForest: A deep forest model towards the prediction of lncRNA-miRNA interactions

The interactions between miRNAs and long non-coding RNAs (lncRNAs) are subject to intensive recent studies due to its critical role in gene regulations. Computational prediction of lncRNA-miRNA interactions has become a popular alternative strategy to the experimental methods for identification of underlying interactions. It is desirable to develop the machine learning-based models for prediction of lncRNA-miRNA based on the experimentally validated interactions between lncRNAs and miRNAs. The accuracy and robustness of existing models based on machine learning techniques are subject to further improvement. Considering that the attributes of lncRNA and miRNA contribute key importance in the interaction between these two RNAs, a deep learning model, named LMI-DForest, is proposed here by combining the deep forest and autoencoder strategies. Systematic comparison on the experiment validated datasets for lncRNA-miRNA interaction datasets demonstrates that the proposed method consistently shows superior performance over the other machine learning models in the lncRNA-miRNA interaction prediction.

LncRNA-SNHG7 Enhances Chemotherapy Resistance and Cell Viability of Breast Cancer Cells by Regulating miR-186

BACKGROUND

Clinical tolerance to trastuzumab greatly affects the therapeutic effect in breast cancer (BC). Long-chain non-coding RNA (lncRNA) plays an important role in the development of trastuzumab resistance, in which SNHG7 can promote the epithelial mesenchymal transformation (EMT) of breast cancer cells into, while EMT is related to trastuzumab resistance of breast cancer cells.

OBJECTIVE

To investigate whether lncRNA-SNHG7 can enhance chemotherapy resistance and cell viability of BC cells by regulating miR-186.

METHODS

SK-BR-3 and SNHG7 of HER2+BC cells were induced to enhance the resistance of BC cells to trastuzumab by regulating miR-186, and to regulate the expression levels of SNHG7 and miR-186. The sensitivity of drug-resistant cells to trastuzumab and the changes of cell proliferation, migration, apoptosis, and EMT were measured and verified by tumorigenesis in vivo. The effects of miR-186 on SNHG7 were investigated through rescue experiments; the regulatory relationship between the expression of SNHG7 and miR-186 was verified by the double luciferase reporter (DLR) and the mechanism of SNHG7 was explored.

RESULTS

Down-regulation of SNHG7 or up-regulation of miR-186 could increase the sensitivity of BC cells to trastuzumab, inhibit the proliferation, migration and EMT, and promote apoptosis. Compared with the down-regulation of SNHG7 or miR-186 alone, simultaneous down-regulation of SNHG7 and miR-186 on drug-resistant cells brought notably lower sensitivity to trastuzumab and apoptosis rate, and higher proliferation and apoptosis ability. The DLR showed that miR-186 could specifically inhibit the expression of SNHG7. The results of tumorigenesis in vivo revealed that down-regulation of SNHG7 or up-regulation of miR-186 could improve the therapeutic effect of trastuzumab and reduce the tumor volume, and miR-186 could also antagonize the effect of SNHG7.

CONCLUSION

Down-regulation of SNHG7-targeted miR-186 can reverse trastuzumab resistance of BC cells, inhibit the proliferation, migration, and EMT levels of BC cells, and promote apoptosis.

miRTissue ce: extending miRTissue web service with the analysis of ceRNA-ceRNA interactions

BACKGROUND

Non-coding RNAs include different classes of molecules with regulatory functions. The most studied are microRNAs (miRNAs) that act directly inhibiting mRNA expression or protein translation through the interaction with a miRNAs-response element. Other RNA molecules participate in the complex network of gene regulation. They behave as competitive endogenous RNA (ceRNA), acting as natural miRNA sponges to inhibit miRNA functions and modulate the expression of RNA messenger (mRNA). It became evident that understanding the ceRNA-miRNA-mRNA crosstalk would increase the functional information across the transcriptome, contributing to identify new potential biomarkers for translational medicine.

RESULTS

We present miRTissue ce, an improvement of our original miRTissue web service. By introducing a novel computational pipeline, miRTissue ce provides an easy way to search for ceRNA interactions in several cancer tissue types. Moreover it extends the functionalities of previous miRTissue release about miRNA-target interaction in order to provide a complete insight about miRNA mediated regulation processes. miRTissue ce is freely available at http://tblab.pa.icar.cnr.it/mirtissue.html .

CONCLUSIONS

The study of ceRNA networks and its dynamics in cancer tissue could be applied in many fields of translational biology, as the investigation of new cancer biomarker, both diagnostic and prognostic, and also in the investigation of new therapeutic strategies of intervention. In this scenario, miRTissue ce can offer a powerful instrument for the analysis and characterization of ceRNA-ceRNA interactions in different tissue types, representing a fundamental step in order to understand more complex regulation mechanisms.

Long non‑coding RNA SNHG16 inhibits the oxygen‑glucose deprivation and reoxygenation‑induced apoptosis in human brain microvascular endothelial cells by regulating miR‑15a‑5p/bcl‑2

MicroRNA (miR) 15a-5p can promote ischemia/reperfusion (I/R)-induced apoptosis of cerebral vascular endothelial cells, which is inhibited by long non-coding RNAs (lncRNAs). The present study investigated the potential of lncRNAs targeting miR-15a-5p to regulate oxygen-glucose deprivation and reoxygenation (OGD-R)-induced apoptosis of human brain microvascular endothelial cells (hBMECs). hBMECs were transfected with or without miR-15a-5p or its mutant, together with p-small nucleolar RNA host gene 16 (SNHG16) or its mutant. Following OGD-R, proliferation, apoptosis and miR-15a-5p, SNHG16 and Bcl-2 expression levels were determined using MTT, flow cytometry, reverse transcription-quantitative PCR or western blotting. The potential interaction of SNHG16 with miR-15a-5p was analyzed by pull-down, luciferase and immunoprecipitation assays. OGD-R induced apoptosis of hBMECs and increased miR-15a-5p expression levels in a time-dependent manner. miR-15a-5p overexpression decreased the proliferation of hBMECs and promoted apoptosis by decreasing Bcl-2 expression levels. SNHG16 was pulled-down by miR-15a-5p and anti-Ago2. miR-15a-5p overexpression significantly decreased SNHG16-regulated luciferase activity and hBMEC survival by increasing apoptosis. SNHG16 overexpression decreased miR-15a-5p expression levels in hBMECs. SNHG16 gradually decreased following OGD-R and its overexpression decreased miR-15a-5p expression levels and promoted the proliferation of hBMECs by decreasing apoptosis. SNHG16 enhanced Bcl-2 expression levels in hBMECs, which was abrogated by miR-15a-5p. Bioinformatics suggest that SNHG16 may antagonize the binding of miR-15a-5p to the 3′UTR of Bcl-2 mRNA. These findings suggest that SNHG16 may protect hBMECs from OGD-R-induced apoptosis by antagonizing the miR-15a-5p/bcl-2 axis. Thus, targeting SNHG16-based mechanisms may provide novel therapeutic strategies for treatment of ischemic stroke.

LncRNA FENDRR Upregulation Promotes Hepatic Carcinoma Cells Apoptosis by Targeting miR-362-5p Via NPR3 and p38-MAPK Pathway

Background: Abnormal long noncoding RNA FOXF1 adjacent noncoding developmental regulatory RNA (FENDRR) expression has been discovered in multiple human cancers pathogenesis, but its role in hepatocellular carcinoma (HCC) cells is rarely reported. Its effects on HCC cells are covered in this study. Materials and Methods: MiR-362-5p and NPR3 expressions in HCC tissues and cell were detected by quantitative real-time polymerase chain reaction and Western blot as needed. Cell viability and apoptosis were detected by MTT assay and flow cytometry, respectively. Target gene and potential binding sites of FENDRR, miR-362-5p, and NPR3 were predicted and confirmed by TargetScan and Starbase, and dual-luciferase reporter assay. Results: FENDRR expression was downregulated while miR-362-5p expression was upregulated in HCC tissues and cells. FENDRR upregulation inhibited HCC cells viability yet induced apoptosis, which was reversed by miR-362-5p. In addition, miR-362-5p resulted in p38-mitogen-activated protein kinase (MAPK) pathway activation and NPR3 expression decrease in HCC cells, which was reversed by FENDRR. Conclusion: FENDRR inhibited HCC cells viability yet promoted apoptosis by targeting miR-362-5p by promoting NPR3 and deactivating p38-MAPK pathway, thus exerting its anticarcinogenic effects in HCC cells.

Ghrelin protects against obesity-induced myocardial injury by regulating the lncRNA H19/miR-29a/IGF-1 signalling axis

BACKGROUND

Obesity is associated with the impairment of cardiac fitness and consequent ventricular dysfunction and heart failure. Ghrelin has been largely documented to be cardioprotective against ischaemia/reperfusion injury. However, the role of ghrelin in obesity-induced myocardial injury is largely unknown. This study sought to determine the cardiac effect of ghrelin against obesity-induced injury and the underlying mechanisms.

METHODS

The effect of ghrelin was evaluated in a mouse model of obesity and a palmitic acid (PA)-treated cardiomyocyte cell line with or without ghrelin transfection. Gene and protein expression levels were determined by real-time PCR and western blot, respectively. Cell apoptosis was measured by flow cytometry analysis.

RESULTS

In the present study, we found that both a high-fat diet (HFD) and PA treatment caused myocardial injury by increasing apoptosis and the expression of inflammatory cytokines. Overexpression of ghrelin reversed the effects induced by HFD or PA treatment. Knockdown of lncRNA H19 or overexpression of miR-29a abrogated the cardioprotective effects of ghrelin against apoptosis and inflammation. We also found that IGF-1 was a target gene of miR-29a and that H19 regulated IGF-1 expression via miR-29a. Overexpression of IGF-1 partially reversed the apoptosis and inflammation promoting effects of miR-29a.

CONCLUSIONS

Our findings suggested that ghrelin protected against obesity-induced myocardial injury by regulating the H19/miR-29a/IGF-1 signalling axis, providing further evidence for the clinical application of ghrelin.

LncRNA AWPPH promotes osteosarcoma progression via activation of Wnt/β-catenin pathway through modulating miR-93-3p/FZD7 axis

Long noncoding RNAs (lncRNAs) have important regulatory roles in osteosarcoma (OS) progression. Recent researches have shown lncRNA AWPPH promotes lung cancer progression and bladder cancer development. Yet, the function of AWPPH in OS is unknown. In this research, results indicated AWPPH levels were increased in OS tissues in contrast to paracancerous controls. Up-regulated AWPPH was associated with advanced stage, tumor size and metastasis. Besides, AWPPH up-regulation indicated a low survival rate in OS patients. Silencing of AWPPH suppressed proliferation, migration and invasion of OS cells. Mechanistically, AWPPH was demonstrated to sponge miR-93-3p and promote FZD7 expression, causing activation of Wnt/β-catenin. Inhibition of miR-93-3p effectively reversed the effects of AWPPH knockdown on OS cells. Collectively, our findings suggested AWPPH may be a prognostic biomarker and potential therapeutic target. AWPPH enhances FZD7-mediated activation of Wnt/β-catenin by sponging miR-93-3p to promote OS progression.