Portrait of Tissue-Specific Coexpression Networks of Noncoding RNAs (miRNA and lncRNA) and mRNAs in Normal Tissues

Bioinformatics analysis of a disease-specific lncRNA-miRNA-mRNA regulatory network in recurrent spontaneous abortion (RSA)

BACKGROUND

This study investigated the molecular mechanisms of long non-coding RNAs (lncRNAs) in RSA using the lncRNA-miRNA-mRNA regulatory network.

METHODS

The present study obtained expression datasets of long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), and microRNAs (miRNAs) from blood samples of individuals with unexplained recurrent spontaneous abortion (RSA) and healthy controls. Differentially expressed lncRNAs (DELs), mRNAs (DEMs), and miRNAs (DEmiRs) were identified. A regulatory network comprising lncRNA, miRNA, and mRNA was constructed, and Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEM. Also, a protein-protein interaction (PPI) network was made and key genes were identified.

RESULTS

A total of 57 DELs, 212 DEmiRs, and 301 DEMs regarding RSA were identified. Later analysis revealed a lncRNA-miRNA-mRNA network comprising nine lncRNAs, 14 miRNAs, and 65 mRNAs. Then, the ceRNA network genes were subjected to functional enrichment and pathway analysis, which showed their association with various processes, such as cortisol and thyroid hormone synthesis and secretion, human cytomegalovirus infection, and parathyroid hormone synthesis. In addition, ten hub genes (ITGB3, GNAI2, GNAS, SRC, PLEC, CDC42, RHOA, RAC1, CTNND1, and FN1) were identified based on the PPI network results.

CONCLUSION

In summary, the outcomes of our study provided some data regarding the alteration genes involved in RSA pathogenic mechanism via the lncRNA-miRNA-mRNA network and reveal the possibility of identifying new lncRNAs and miRNAs as promising molecular biomarkers.

CRISPR/Cas9-mediated activation of NR5A1 steers female human embryonic stem cell-derived bipotential gonadal-like cells towards a steroidogenic cell fate

The nuclear receptor subfamily 5 group A member 1 (NR5A1), encoding steroidogenic factor 1 (SF-1), has been identified as a critical factor in gonadal development in animal studies. A previous study of ours suggested that upregulation of NR5A1 during early gonadal differentiation in male (46,XY) human pluripotent stem cells steers the cells into a more mature gonadal cell type. However, the detailed role of NR5A1 in female gonadal differentiation has yet to be determined. In this study, by combining the processes of gonadal differentiation and conditional gene activation, we show that NR5A1 induction predominantly upregulates the female gonadal marker inhibin subunit α (INHA) and steroidogenic markers steroidogenic acute regulatory protein (STAR), cytochrome P450 family 11 subfamily A member 1 (CYP11A1), cytochrome P450 family 17 subfamily A member 1 (CYP17A1), hydroxy-delta-5-steroid dehydrogenase (HSD3B2) and hydroxysteroid 17-beta dehydrogenase 1 (HSD17B1). In contrast, NR5A1 induction did not seem to affect the bipotential gonadal markers gata binding protein 4 (GATA4) and Wilms' tumour suppressor 1 (WT1) nor the female gonadal markers r-spondin 1 (RSPO1) and wnt family member 4 (WNT4). Differentially expressed genes were highly associated with adrenal and ovarian steroidogenesis pathways. Moreover, time-series analysis revealed different dynamic changes between male and female induced samples, where continuously upregulated genes in female gonadal differentiation were mostly associated with adrenal steroidogenesis. Thus, in contrast to male gonadal differentiation, NR5A1 is necessary but not sufficient to steer human embryonic stem cell (hESC)-derived bipotential gonadal-like cells towards a more mature somatic, female cell fate. Instead, it seems to direct bipotential gonadal-like cells more towards a steroidogenic-like cell population. The information obtained in this study helps in elucidating the role of NR5A1 in gonadal differentiation of a female stem cell line.

The development of a novel signature based on the m6A RNA methylation regulator-related ceRNA network to predict prognosis and therapy response in sarcomas

Background: N⁶ methyladenosine (m⁶A)-related noncoding RNAs (including lncRNAs and miRNAs) are closely related to the development of cancer. However, the gene signature and prognostic value of m⁶A regulators and m⁶A-associated RNAs in regulating sarcoma (SARC) development and progression remain largely unexplored. Therefore, further research is required.

Methods: We obtained expression data for RNA sequencing (RNA-seq) and miRNAs of SARC from The Cancer Genome Atlas (TCGA) datasets. Correlation analysis and two target gene prediction databases (miRTarBase and LncBase v.2) were used to deduce m⁶A-related miRNAs and lncRNAs, and Cytoscape software was used to construct ceRNA-regulating networks. Based on univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression analyses, an m⁶A-associated RNA risk signature (m6Ascore) model was established. Prognostic differences between subgroups were explored using Kaplan–Meier (KM) analysis. Risk score-related biological phenotypes were analyzed in terms of functional enrichment, tumor immune signature, and tumor mutation signature. Finally, potential immunotherapy features and drug sensitivity predictions for this model were also discussed.

Results: A total of 16 miRNAs, 104 lncRNAs, and 11 mRNAs were incorporated into the ceRNA network. The risk score was obtained based on RP11-283I3.6, hsa-miR-455-3p, and CBLL1. Patients were divided into two risk groups using the risk score, with patients in the low-risk group having longer overall survival (OS) than those in the high-risk group. The receiver operating characteristic (ROC) curves indicated that risk characteristic performed well in predicting the prognosis of patients with SARC. In addition, lower m6Ascore was also positively correlated with the abundance of immune cells such as monocytes and mast cells activated, and several immune checkpoint genes were highly expressed in the low-m6Ascore group. According to our analysis, lower m6Ascore may lead to better immunotherapy response and OS outcomes. The risk signature was significantly associated with the chemosensitivity of SARC. Finally, a nomogram was constructed to predict the OS in patients with SARC. The concordance index (C-index) for the nomogram was 0.744 (95% CI: 0.707–0.784). The decision curve analysis (DCA), calibration plot, and ROC curve all showed that this nomogram had good predictive performance.

Conclusion: This m6Ascore risk model based on m⁶A RNA methylation regulator-related RNAs may be promising for clinical prediction of prognosis and might contain potential biomarkers for treatment response prediction for SARC patients.

Long Noncoding RNAs That Function in Nutrition: Lnc-ing Nutritional Cues to Metabolic Pathways

Long noncoding RNAs (lncRNAs) are sensitive to changing environments and play key roles in health and disease. Emerging evidence indicates that lncRNAs regulate gene expression to shape metabolic processes in response to changing nutritional cues. Here we review various lncRNAs sensitive to fasting, feeding, and high-fat diet in key metabolic tissues (liver, adipose, and muscle), highlighting regulatory mechanisms that trigger expression changes of lncRNAs themselves, and how these lncRNAs regulate gene expression of key metabolic genes in specific cell types or across tissues. Determining how lncRNAs respond to changes in nutrition is critical for our understanding of the complex downstream cascades following dietary changes and can shape how we treat metabolic disease. Furthermore, investigating sex biases that might influence lncRNA-regulated responses will likely reveal contributions toward the observed disparities between the sexes in metabolic diseases.

Identification of key miRNAs in prostate cancer progression based on miRNA-mRNA network construction

Prostate cancer (PC) is one of the major male cancers. Differential diagnosis of PC is indispensable for the individual therapy, i.e., Gleason score (GS) that describes the grade of cancer can be used to choose the appropriate therapy. However, the current techniques for PC diagnosis and prognosis are not always effective. To identify potential markers that could be used for differential diagnosis of PC, we analyzed miRNA-mRNA interactions and we build specific networks for PC onset and progression. Key differentially expressed miRNAs for each GS were selected by calculating three parameters of network topology measures: the number of their single regulated mRNAs (NSR), the number of target genes (NTG) and NSR/NTG. miRNAs that obtained a high statistically significant value of these three parameters were chosen as potential biomarkers for computational validation and pathway analysis. 20 miRNAs were identified as key candidates for PC. 8 out of 20 miRNAs (miR-25-3p, miR-93-3p, miR-122-5p, miR-183-5p, miR-615-3p, miR-7-5p, miR-375, and miR-92a-3p) were differentially expressed in all GS and proposed as biomarkers for PC onset. In addition, "Extracellular-receptor interaction", "Focal adhesion", and "microRNAs in cancer" were significantly enriched by the differentially expressed target genes of the identified miRNAs. miR-10a-5p was found to be differentially expressed in GS 6, 7, and 8 in PC samples. 3 miRNAs were identified as PC GS-specific differentially expressed miRNAs: miR-155-5p was identified in PC samples with GS 6, and miR-142-3p and miR-296-3p in PC samples with GS 9. The efficacy of 20 miRNAs as potential biomarkers was revealed with a Random Forest classification using an independent dataset. The results demonstrated our 20 miRNAs achieved a better performance (AUC: 0.73) than miRNAs selected with Boruta algorithm (AUC: 0.55), a method for the automated feature extraction. Studying miRNA-mRNA associations, key miRNAs were identified with a computational approach for PC onset and progression. Further experimental validations are needed for future translational development.

Identification of long non-coding RNAs and RNA binding proteins in breast cancer subtypes

Breast cancer is a heterogeneous disease classified into four main subtypes with different clinical outcomes, such as patient survival, prognosis, and relapse. Current genetic tests for the differential diagnosis of BC subtypes showed a poor reproducibility. Therefore, an early and correct diagnosis of molecular subtypes is one of the challenges in the clinic. In the present study, we identified differentially expressed genes, long non-coding RNAs and RNA binding proteins for each BC subtype from a public dataset applying bioinformatics algorithms. In addition, we investigated their interactions and we proposed interacting biomarkers as potential signature specific for each BC subtype. We found a network of only 2 RBPs (RBM20 and PCDH20) and 2 genes (HOXB3 and RASSF7) for luminal A, a network of 21 RBPs and 53 genes for luminal B, a HER2-specific network of 14 RBPs and 30 genes, and a network of 54 RBPs and 302 genes for basal BC. We validated the signature considering their expression levels on an independent dataset evaluating their ability to classify the different molecular subtypes with a machine learning approach. Overall, we achieved good performances of classification with an accuracy >0.80. In addition, we found some interesting novel prognostic biomarkers such as RASSF7 for luminal A, DCTPP1 for luminal B, DHRS11, KLC3, NAGS, and TMEM98 for HER2, and ABHD14A and ADSSL1 for basal. The findings could provide preliminary evidence to identify putative new prognostic biomarkers and therapeutic targets for individual breast cancer subtypes.

The Regulation of Collagen Processing by miRNAs in Disease and Possible Implications for Bone Turnover

This article describes several recent examples of miRNA governing the regulation of the gene expression involved in bone matrix construction. We present the impact of miRNA on the subsequent steps in the formation of collagen type I. Collagen type I is a main factor of mechanical bone stiffness because it constitutes 90–95% of the organic components of the bone. Therefore, the precise epigenetic regulation of collagen formation may have a significant influence on bone structure. We also describe miRNA involvement in the expression of genes, the protein products of which participate in collagen maturation in various tissues and cancer cells. We show how non-collagenous proteins in the extracellular matrix are epigenetically regulated by miRNA in bone and other tissues. We also delineate collagen mineralisation in bones by factors that depend on miRNA molecules. This review reveals the tissue variability of miRNA regulation at different levels of collagen maturation and mineralisation. The functionality of collagen mRNA regulation by miRNA, as proven in other tissues, has not yet been shown in osteoblasts. Several collagen-regulating miRNAs are co-expressed with collagen in bone. We suggest that collagen mRNA regulation by miRNA could also be potentially important in bone metabolism.

Long Non-Coding RNAs at the Chromosomal Risk Loci Identified by Prostate and Breast Cancer GWAS

Long non-coding RNAs (lncRNAs) are emerging as key players in a variety of cellular processes. Deregulation of the lncRNAs has been implicated in prostate and breast cancers. Recently, germline genetic variations associated with cancer risk have been correlated with lncRNA expression and/or function. In addition, single nucleotide polymorphisms (SNPs) at well-characterized cancer-associated lncRNAs have been analyzed for their association with cancer risk. These SNPs may occur within the lncRNA transcripts or spanning regions that may alter the structure, function, and expression of these lncRNA molecules and contribute to cancer progression and may have potential as therapeutic targets for cancer treatment. Additionally, some of these lncRNA have a tissue-specific expression profile, suggesting them as biomarkers for specific cancers. In this review, we highlight some of the cancer risk-associated SNPs that modulated lncRNAs with a potential role in prostate and breast cancers and speculate on how these lncRNAs may contribute to cancer development.

SNHG12 regulates biological behaviors of ox-LDL-induced HA-VSMCs through upregulation of SPRY2 and NUB1

BACKGROUND AND AIMS

Human vascular smooth muscle cells (HA-VSMCs) are an important cell type involved in atherosclerosis. Low density lipoprotein (LDL) is a lipoprotein particle that carries cholesterol into peripheral tissue cells, and oxidized modified LDL (ox-LDL) is a well-known inducer of the atherosclerosis-related phenotype switch in VSMCs, leading to the occurrence of atherosclerosis. Accumulating studies have revealed that long non-coding RNAs (lncRNAs) mediate the effect of ox-LDL on the atherosclerosis-related biological activities of HA-VSMCs, including proliferation, migration, and apoptosis. However, the mechanism of small nucleolar RNA host gene 12 (SNHG12) in ox-LDL-induced phenotype switch of VSMCs remains unclear. Thus, this research dug in whether SNHG12 mediated the influence of ox-LDL on HA-VSMCs and the potential mechanism.

METHODS

Fundamental experiments and functional assays were performed to measure the function of SNHG12 on HA-VSMCs. Then, mechanism assays and rescue assays were performed to study the regulatory mechanism of SNHG12 in HA-VSMCs.

RESULTS

SNHG12 reversed the influence of ox-LDL treatment in enhancing cell proliferative and migratory abilities and weakening apoptotic ability in HA-VSMCs. SNHG12 was a competitive endogenous RNA (ceRNA) competing with sprouty RTK signaling antagonist 2 (SPRY2) to bind to miR-1301-3p, thus up-regulating SPRY2 expression in ox-LDL-treated HA-VSMCs. Besides, SNHG12 recruited serine and arginine rich splicing factor 1 (SRSF1) to stabilize negative regulator of ubiquitin like proteins 1 (NUB1) expression.

CONCLUSIONS

This study illustrated that SNHG12 inhibited cell proliferation, migration and facilitated cell apoptosis in ox-LDL-induced HA-VSMCs by up-regulating SPRY2 and NUB1.

In Silico Identification of miRNA-lncRNA Interactions in Male Reproductive Disorder Associated with COVID-19 Infection

Coronavirus disease 2019 (COVID-19), a global pandemic, is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Angiotensin-converting enzyme 2 (ACE2) is the receptor for SARS-CoV-2 and transmembrane serine protease 2 (TMPRSS2) facilitates ACE2-mediated virus entry. Moreover, the expression of ACE2 in the testes of infertile men is higher than normal, which indicates that infertile men may be susceptible to be infected and SARS-CoV-2 may cause reproductive disorder through the pathway induced by ACE2 and TMPRSS2. Little is known about the pathway regulation of ACE2 and TMPRSS2 expression in male reproductive disorder. Since the regulation of gene expression is mediated by microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) at the post-transcriptional level, the aim of this study was to analyze the dysregulated miRNA–lncRNA interactions of ACE2 and TMPRSS2 in male reproductive disorder. Using bioinformatics analysis, we speculate that the predicted miRNAs including miR-125a-5p, miR-125b-5p, miR-574-5p, and miR-936 as regulators of ACE2 and miR-204-5p as a modulator of TMPRSS2 are associated with male infertility. The lncRNAs with a tissue-specific expression for testis including GRM7-AS3, ARHGAP26-AS1, BSN-AS1, KRBOX1-AS1, CACNA1C-IT3, AC012361.1, FGF14-IT1, AC012494.1, and GS1-24F4.2 were predicted. The identified miRNAs and lncRNAs are proposed as potential biomarkers to study the possible association between COVID-19 and male infertility. This study encourages further studies of miRNA–lncRNA interactions to explain the molecular mechanisms of male infertility in COVID-19 patients.

Expression Profile of Long Noncoding RNAs and Circular RNAs in Mouse C3H10T1/2 Mesenchymal Stem Cells Undergoing Myogenic and Cardiomyogenic Differentiation

Background

Currently, a heterogeneous category of noncoding RNAs (ncRNA) that directly regulate the expression or function of protein-coding genes is shown to have an effect on the fate decision of stem cells. However, the detailed regulatory roles of ncRNAs in myogenic and cardiomyogenic differentiation of mouse C3H10T1/2 mesenchymal stem cells (MSCs) are far from clear.

Methods

In this study, 5-azacytidine- (5-AZA-) treated C3H10T1/2 cells were differentiated into myocyte-like and cardiomyocyte-like cells. Next, ncRNA associated with myogenic and cardiomyogenic differentiation was identified using high-throughput RNA sequencing (RNA-seq) data. Bioinformatics analysis was conducted to identify the differentially expressed ncRNAs and the related signaling pathways.

Results

Myotube-like structure was formed after 5-AZA treatment of C3H10T1/2 cells. In addition, myogenic and cardiomyogenic differentiation-related genes like GATA4, cTnt, MyoD, and Desmin were upregulated significantly after the 5-AZA treatment. Totally, 1538 differentially expressed lncRNAs and 3398 differentially expressed mRNAs were identified, including 1175 upregulated and 363 downregulated lncRNAs and 2429 upregulated and 969 downregulated mRNAs. In addition, 46 differentially expressed circRNAs were identified, including 25 upregulated and 21 downregulated circRNAs. Moreover, the differentially expressed mRNAs were enriched into 5 significant pathways, including those for focal adhesion, ECM-receptor interaction, PI3K-AKT signaling pathway, PPAR signaling pathway, and Tyrosine metabolism.

Conclusions

A systematic view of the expression of ncRNAs in myogenic and cardiomyogenic differentiation of MSCs was provided in the study.

The role of M6A modification in the regulation of tumor-related lncRNAs

N⁶-methyladenosine (m⁶A) is the most abundant modification in eukaryotic cells, and it regulates RNA transcription, processing, splicing, degradation, and translation. Long non-coding RNAs (lncRNAs), as transcriptional products with no or limited protein coding ability more than 200 nt in length, play an important role in epigenetic modification, mRNA transcription, splicing, stability, translation, and other biological functions. Extensive studies have shown that both m⁶A modification and lncRNAs are involved in the pathogenesis of various diseases, such as kinds of cancers, heart failure, Alzheimer’s disease, periodontitis, human abdominal aortic aneurysm, and obesity. To date, m⁶A modification has been identified as an important biological function in enrichment and regulation of lncRNAs. In this review, we summarize the role of m⁶A modification in the regulation and function of tumor-related lncRNAs. Moreover, we discuss the potential applications and possible future directions in the field.

MicroRNA treatment modulates osteogenic differentiation potential of mesenchymal stem cells derived from human chorion and placenta

Mesenchymal stem cells (MSCs) are important in regenerative medicine because of their potential for multi-differentiation. Bone marrow, chorion and placenta have all been suggested as potential sources for clinical application. However, the osteogenic differentiation potential of MSCs derived from chorion or placenta is not very efficient. Bone morphogenetic protein-2 (BMP-2) plays an important role in bone development. Its effect on osteogenic augmentation has been addressed in several studies. Recent studies have also shown a relationship between miRNAs and osteogenesis. We hypothesized that miRNAs targeted to Runt-related transcription factor 2 (Runx-2), a major transcription factor of osteogenesis, are responsible for regulating the differentiation of MSCs into osteoblasts. This study examines the effect of BMP-2 on the osteogenic differentiation of MSCs isolated from chorion and placenta in comparison to bone marrow-derived MSCs and investigates the role of miRNAs in the osteogenic differentiation of MSCs from these sources. MSCs were isolated from human bone marrow, chorion and placenta. The osteogenic differentiation potential after BMP-2 treatment was examined using ALP staining, ALP activity assay, and osteogenic gene expression. Candidate miRNAs were selected and their expression levels during osteoblastic differentiation were examined using real-time RT-PCR. The role of these miRNAs in osteogenesis was investigated by transfection with specific miRNA inhibitors. The level of osteogenic differentiation was monitored after anti-miRNA treatment. MSCs isolated from chorion and placenta exhibited self-renewal capacity and multi-lineage differentiation potential similar to MSCs isolated from bone marrow. BMP-2 treated MSCs showed higher ALP levels and osteogenic gene expression compared to untreated MSCs. All investigated miRNAs (miR-31, miR-106a and miR148) were consistently downregulated during the process of osteogenic differentiation. After treatment with miRNA inhibitors, ALP activity and osteogenic gene expression increased over the time of osteogenic differentiation. BMP-2 has a positive effect on osteogenic differentiation of chorion- and placenta-derived MSCs. The inhibition of specific miRNAs enhanced the osteogenic differentiation capacity of various MSCs in culture and this strategy might be used to promote bone regeneration. However, further in vivo experiments are required to assess the validity of this approach.

Integrated analysis of lncRNA-miRNA-mRNA ceRNA network and the potential prognosis indicators in sarcomas

Background

Competitive endogenous RNA (ceRNA) networks have revealed a new mechanism of interaction between RNAs, and play crucial roles in multiple biological processes and development of neoplasms. They might serve as diagnostic and prognosis markers as well as therapeutic targets.

Methods

In this work, we identified differentially expressed mRNAs (DEGs), lncRNAs (DELs) and miRNAs (DEMs) in sarcomas by comparing the gene expression profiles between sarcoma and normal muscle samples in Gene Expression Omnibus (GEO) datasets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were applied to investigate the primary functions of the overlapped DEGs. Then, lncRNA-miRNA and miRNA-mRNA interactions were predicted, and the ceRNA regulatory network was constructed using Cytoscape software. In addition, the protein–protein interaction (PPI) network and survival analysis were performed.

Results

A total of 1296 DEGs were identified in sarcoma samples by combining the GO and KEGG enrichment analyses, 338 DELs were discovered after the probes were reannotated, and 36 DEMs were ascertained through intersecting two different expression miRNAs sets. Further, through target gene prediction, a lncRNA–miRNA–mRNA ceRNA network that contained 113 mRNAs, 69 lncRNAs and 29 miRNAs was constructed. The PPI network identified the six most significant hub proteins. Survival analysis revealed that seven mRNAs, four miRNAs and one lncRNA were associated with overall survival of sarcoma patients.

Conclusions

Overall, we constructed a ceRNA network in sarcomas, which might provide insights for further research on the molecular mechanism and potential prognosis biomarkers.

Angiogenesis regulation by microRNAs and long non-coding RNAs in human breast cancer

MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are capable of regulating gene expression post-transcriptionally. Since the past decade, a number of in vitro, in vivo, and clinical studies reported the roles of these non-coding RNAs (ncRNAs) in regulating angiogenesis, an important cancer hallmark that is associated with metastases and poor prognosis. The specific roles of various miRNAs and lncRNAs in regulating angiogenesis in breast cancer, with particular focus on the downstream targets and signalling pathways regulated by these ncRNAs will be discussed in this review. In light of the recent trend in exploiting ncRNAs as cancer therapeutics, the potential use of miRNAs and lncRNAs as biomarkers and novel therapeutic agent against angiogenesis was also discussed.

Web tools to perform long non-coding RNAs analysis in oncology research

Accumulated evidence suggests that the widely expressed long-non-coding RNAs (lncRNAs) are involved in biogenesis. Some aberrant lncRNAs are closely related to pathological changes, for instance, in cancer. Both in tumorigenesis and cancer progression, depending on the interplay with cellular molecules, lncRNAs can modulate transcriptional interference, chromatin remodeling, post-translational regulation and protein modification, and further interfere with signaling pathways. Aiming to the diagnosis/ prognosis markers or potential therapeutical targets, it is important to figure out the specific mechanism and the tissue-specific expressing patterns of lncRNAs. Generally, the bioinformatics analysis is the first step. More and more in silico databases are increasing. But the existing integrative online platforms’ functions are not only having their unique features but also share some common features, which may lead to a waste of time for researchers. Here, we reviewed these web tools according to the functions. For each database, we clarified the data source, analysis method and the evidence that the analysis result is derived from. This review also illustrated examples in practical use for a specific lncRNA by these web tools. It will provide convenience for researchers to quickly choose the appropriate bioinformatics web tools in oncology studies.

miRNA Targets: From Prediction Tools to Experimental Validation

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression in both animals and plants. By pairing to microRNA responsive elements (mREs) on target mRNAs, miRNAs play gene-regulatory roles, producing remarkable changes in several physiological and pathological processes. Thus, the identification of miRNA-mRNA target interactions is fundamental for discovering the regulatory network governed by miRNAs. The best way to achieve this goal is usually by computational prediction followed by experimental validation of these miRNA-mRNA interactions. This review summarizes the key strategies for miRNA target identification. Several tools for computational analysis exist, each with different approaches to predict miRNA targets, and their number is constantly increasing. The major algorithms available for this aim, including Machine Learning methods, are discussed, to provide practical tips for familiarizing with their assumptions and understanding how to interpret the results. Then, all the experimental procedures for verifying the authenticity of the identified miRNA-mRNA target pairs are described, including High-Throughput technologies, in order to find the best approach for miRNA validation. For each strategy, strengths and weaknesses are discussed, to enable users to evaluate and select the right approach for their interests.

Long noncoding RNA ZFAS1 promoting small nucleolar RNA-mediated 2'-O-methylation via NOP58 recruitment in colorectal cancer

BACKGROUND

Increasing evidence supports the role of small nucleolar RNAs (snoRNAs) and long non-coding RNAs (lncRNAs) as master gene regulators at the epigenetic modification level. However, the underlying mechanism of these functional ncRNAs in colorectal cancer (CRC) has not been well investigated.

METHODS

The dysregulated expression profiling of lncRNAs-snoRNAs-mRNAs and their correlations and co-expression enrichment were assessed by GeneChip microarray analysis. The candidate lncRNAs, snoRNAs, and target genes were detected by in situ hybridization (ISH), RT-PCR, qPCR and immunofluorescence (IF) assays. The biological functions of these factors were investigated using in vitro and in vivo studies that included CCK8, trans-well, cell apoptosis, IF assay, western blot method, and the xenograft mice models. rRNA 2'-O-methylation (Me) activities were determined by the RTL-P assay and a novel double-stranded primer based on the single-stranded toehold (DPBST) assay. The underlying molecular mechanisms were explored by bioinformatics and RNA stability, RNA fluorescence ISH, RNA pull-down and translation inhibition assays.

RESULTS

To demonstrate the involvement of lncRNA and snoRNAs in 2'-O-Me modification during tumorigenesis, we uncovered a previously unreported mechanism linking the snoRNPs NOP58 regulated by ZFAS1 in control of SNORD12C, SNORD78 mediated rRNA 2'-O-Me activities in CRC initiation and development. Specifically, ZFAS1 exerts its oncogenic functions and significantly up-regulated accompanied by elevated NOP58, SNORD12C/78 expression in CRC cells and tissues. ZFAS1 knockdown suppressed CRC cell proliferation, migration, and increased cell apoptosis, and this inhibitory effect could be reversed by NOP58 overexpression in vitro and in vivo. Mechanistically, the NOP58 protein could be recognized by the specific motif (AAGA or CAGA) of ZFAS1. This event accelerates the assembly of SNORD12C/78 to allow for further guiding of 2'-O-Me at the corresponding Gm3878 and Gm4593 sites. Importantly, silencing SNORD12C or 78 reduced the rRNAs 2'-O-Me activities, which could be rescued by overexpression ZFAS1, and this subsequently inhibits the RNA stability and translation activity of their downstream targets (e.g., EIF4A3 and LAMC2).

CONCLUSION

The novel ZFAS1-NOP58-SNORD12C/78-EIF4A3/LAMC2 signaling axis that functions in CRC tumorigenesis provides a better understanding regarding the role of lncRNA-snoRNP-mediated rRNAs 2'-O-Me activities for the prevention and treatment of CRC.

In Silico Discovery of Candidate Drugs against Covid-19

Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of ACE2-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with ACE2. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide.