Role of the long non-coding RNA PVT1 in the dysregulation of the ceRNA-ceRNA network in human breast cancer

LncRNA Zfas1 boosts cell apoptosis and autophagy in myocardial injury induced by hypoxia via miR-383-5p/ATG10 axis

Background

Myocardial injury has been regarded as a major cause of several heart diseases. Long non-coding RNA (lncRNA) has emerged as a key regulator in a wide array of diseases.

Aim of the study

This study aims to explore the role of Zfas1 in myocardial injury.

Methods

3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay was adopted to evaluate the proliferative capability of H9c2 cells. Terminal deoxynucleotidyltransferase dUTP nick end labeling (TUNEL) and flow cytometry assays were employed to measure cell apoptosis. The expression of proteins related to apoptosis and autophagy was examined by Western blot. Immunofluorescence (IF) assay was performed to monitor the process of autophagy. Real-time reverse-transcription polymerase chain reaction (RT-qPCR) was employed to determine the expressions of autophagy-related gene 10 (ATG10), miR-383-5p and Zfas1. The interacting relationship between miR-383-5p and ATG10 (or Zfas1) was assessed by luciferase reporter and RNA-binding protein immunoprecipitation (RIP) assays.

Results

The treatment of hypoxia hindered cell proliferation but accelerated cell apoptosis and autophagy. ATG10 exhibited higher mRNA and protein expression in H9c2 cells induced by hypoxia. MiR-383-5p was revealed to be the upstream gene of ATG10 and could interact with ATG10. Zfas1 was validated to sponge miR-383-5p and positively regulated ATG10 expression. Zfas1 knockdown-mediated cellular proliferation, apoptosis and autophagy phenotypes were counteracted by ATG10 abundance.

Conclusions

LncRNA Zfas1 boosts cell apoptosis and autophagy in myocardial injury induced by hypoxia via miR-383-5p/ATG10 axis, indicating that Zfas1 may be utilized as a therapeutic target for myocardial injury.

Dual effects of circRNA in thyroid and breast cancer

CircRNA, the latest research hotspot in the field of RNA, is a special non-coding RNA molecule, which is unable to encode proteins and bind polyribosomes. As a regulatory molecule, circRNA participates in cancer cell generation and progression mainly through the mechanism of competitive endogenous RNA. In numerous regulated cancer organs, the thyroid and breast are both endocrine organs, and both are regulated by the hypothalamic pituitary gland axis. Thyroid cancer (TC) and breast cancer (BC) are both sexually prevalent in women and both are affected by hormones, thus they are intrinsically linked. In addition, recent epidemiological surveys have found that, early metastasis and recurrence of breast cancer remain the main cause of survival in breast cancer patients. Although at home and abroad, studies have shown that new targeted anti-tumor drugs with numerous tumor markers are gradually being used in the clinic, evidence for potential molecular mechanisms affecting its prognosis lacks clinical studies. Therefore, we search the relevant literature, and based on the latest domestic and international consensus, review the molecular mechanisms and regulation relevance of circRNA, compare the difference of the same circRNA in two tumors, to more deeply understand and lay the foundation for future clinical diagnostic, therapeutic and prognostic studies in large samples.

Circular RNA mediated gene regulation in human breast cancer: A bioinformatics analysis

Circular RNAs (circRNAs) are a new acknowledged class of RNAs that has been shown to play a major role in several biological functions both in physiological and pathological conditions, operating as critical part of regulatory processes, like competing endogenous RNA (ceRNA) networks. The ceRNA hypothesis is a recently discovered molecular mechanism that adds a new key layer of post-transcriptional regulation, whereby various types of RNAs can reciprocally influence each other's expression competing for binding the same pool of microRNAs, even affecting disease development. In this study, we build a network of circRNA-miRNA-mRNA interactions in human breast cancer, called CERNOMA, that is a bipartite graph with one class of nodes corresponding to differentially expressed miRNAs (DEMs) and the other one corresponding to differentially expressed circRNAs (DEC) and mRNAs (DEGs). A link between a DEC (or DEG) and DEM is placed if it is predicted to be a target of the DEM and shows an opposite expression level trend with respect to the DEM. Within the CERNOMA, we highlighted an interesting deregulated circRNA-miRNA-mRNA triplet, including the up-regulated hsa_circRNA_102908 (BRCA1 associated RING domain 1), the down-regulated miR-410-3p, and the up-regulated ESM1, whose overexpression has been already shown to promote tumor dissemination and metastasis in breast cancer.

Systematic analysis competing endogenous RNA coexpression network as a potentially prediction prognostic biomarker for colon adenocarcinoma

Colon adenocarcinoma (COAD) is one of the most common types of colon cancer, represents a major public health issue due to its high incidence and mortality. Competing endogenous RNAs (ceRNAs) hypothesis has generated a great interest in the study of molecular biological mechanisms of cancer progression. The aim of this study was to identify potential prediction prognostic biomarker associated with progression of COAD and illuminate regulatory mechanisms. Two RNA sequencing datasets downloaded from the Genotype-Tissue Expression and TCGA. The differentially expressed RNAs were analyzed. Weighted correlation network analysis was used to analyze the similarity of genes model with a trait in the network. Interactions between lncRNAs, miRNAs, and target mRNAs were predicted by MiRcode, starBase, miRTarBase, miRDB, and TargetScan, and the risk score of mRNAs was established. Based on the identified prognostic signature and independent clinical factors, then the nomogram survival model was built. Totally, we identified 3537 differentially expressed mRNAs, 2379 lncRNAs, and 449 microRNAs. Based on the 8 prognosis-associated mRNAs (CCNA2 + CEBPA + NEBL + SOX9 + DLG4 + RIMKLB + TCF7L1 + TUB), the risk score was proposed. After the independent clinical prognostic factors were identified, the nomogram survival model was built. LncRNA-miRNA-mRNA ceRNA network was built by 68 lncRNAs, 4 miRNAs, and 6 mRNAs, which might serve as prognostic biomarkers of COAD. These findings suggest several genes in ceRNA network might be novel important prognostic biomarkers and potential targets for COAD. CeRNA networks could provide further insight into the mRNA-related regulatory mechanism and COAD prognosis.

Identification of a prognosis-related ceRNA network in cholangiocarcinoma and potentially therapeutic molecules using a bioinformatic approach and molecular docking

Cholangiocarcinoma (CCA) is a highly malignant disease with a poor prognosis, and mechanisms of initiation and development are not well characterized. It is long noncoding RNAs (lncRNAs) acting as miRNA decoys to regulate cancer-related RNAs in competing endogenous RNA (ceRNA) networks that suggest a possible molecular mechanism in CCA. The current study aims to find potential prognosis biomarkers and small molecule therapeutic targets based on the construction of a CCA prognosis-related ceRNA network. A transcriptome dataset for CCA was downloaded from the TCGA database. Differentially expressed lncRNAs (DElncRNAs), DEmiRNAs and DEmRNAs were identified based on the differential expression and a DEceRNA network was constructed using predicted miRNA-lncRNA and miRNA-mRNA interactions. Heat maps, PCA analysis, and Pathway enrichment analysis and GO enrichment analysis were conducted. The prognostic risk model and molecular docking were constructed based on identified key ceRNA networks. A DElncRNA-miRNA-mRNAs network consisting of 434 lncRNA-miRNA pairs and 284 miRNA-mRNA pairs with 200 lncRNAs, 21 miRNAs, and 245 mRNAs was constructed. There were three lncRNAs (AC090772.1, LINC00519, and THAP7-AS1) and their downstream mRNAs (MECOM, MBNL3, RCN2) screened out as prognostic factors in CAA. Three key networks (LINC00519/ hsa-mir-22/ MECOM, THAP7-AS1/hsa-mir-155/MBNL3, and THAP7-AS1/hsa-mir-155/RCN2) were identified based on binding sites prediction and survival analysis. A prognostic risk model was established with a good predictive ability (AUC = 0.66–0.83). Four anticancer small molecules, MECOM and 17-alpha-estradiol (−7.1 kcal/mol), RCN2 and emodin (−8.3 kcal/mol), RCN2 and alpha-tocopherol (−5.6 kcal/mol), and MBNL3 and 17-beta-estradiol (−7.1 kcal/mol) were identified. Based on the DEceRNA network and Kaplan–Meier survival analysis, we identified three important ceRNA networks associated with the poor prognosis of CCA. Four anti-cancer small molecules were screened out by computer-assisted drug screening as potential small molecules for the treatment of CCA. This study provides theoretical support for the development of ceRNA network-based drugs to improve the prognosis of CCA.

Construction and analysis of a ceRNA network and patterns of immune infiltration in chronic rhinosinusitis with nasal polyps: based on data mining and experimental verification

Recent studies have revealed the significant role of the competing endogenous RNA (ceRNA) network in human diseases. However, systematic analysis of the ceRNA mechanism in chronic rhinosinusitis with nasal polyps (CRSwNP) is limited. In this study, we constructed a competitive endogenous RNA (ceRNA) network and identified a potential regulatory axis in CRSwNP based on bioinformatics analysis and experimental verification. We obtained lncRNA, miRNA, and mRNA expression profiles from the Gene Expression Omnibus. After analysis of CRSwNP patients and the control groups, we identified 565 DE-lncRNAs, 23 DE-miRNAs, and 1799 DE-mRNAs by the DESeq2 R package or limma R package. Enrichment analysis of 1799 DE-mRNAs showed that CRSwNP was associated with inflammation and immunity. Moreover, we identified 21 lncRNAs, 8 miRNAs and 8 mRNAs to construct the lncRNA-miRNA-mRNA ceRNA network. A potential MIAT/miR-125a/IRF4 axis was determined according to the degree and positive correlation between a lncRNA and its competitive endogenous mRNAs. The GSEA results suggested that IRF4 may be involved in immune cell infiltration. The validation of another dataset confirmed that MIAT and IRF4 were differentially expressed between the CRSwNP and control groups. The area under the ROC curve (AUC) of MIAT and IRF4 was 0.944. The CIBERSORT analysis revealed that eosinophils and M2 macrophages may be involved in the CRSwNP process. MIAT was correlated with dendritic cells and M2 macrophages, and IRF4 was correlated with dendritic cells. Finally, to validate the key genes, we performed in-silico validation using another dataset and experimental validation using immunohistochemistry, immunofluorescence, and Western blot. In summary, the constructed novel MIAT/miR-125a/IRF4 axis may play a critical role in the development and progression of CRSwNP. We believe that the ceRNA network and immune cell infiltration could offer further insight into novel molecular therapeutic targets for CRSwNP.

Profiling and Integrated Analysis of Differentially Expressed MicroRNAs as Novel Biomarkers of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a heterogeneous disease that has multiple etiologies. It is the most common primary liver cancer, the sixth highest cause of cancer incidences, and the fourth highest cause of cancer-related deaths. The discovery of new biomarkers for the early detection, treatment, and prognosis of HCC would therefore be extremely useful. This study investigated differentially expressed ribonucleic acid (RNA) profiles by constructing a genome-wide profile of clinical samples. Differential expression analysis identified 1,280 differentially expressed messenger RNAs (dif-mRNAs), 99 differentially expressed microRNAs (dif-miRNAs), 181 differentially expressed long non-coding RNAs (dif-lncRNAs), and 31 differentially expressed circular RNAs (dif-circRNAs). Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) path analysis were then conducted on these differentially expressed RNAs, revealing that they were clearly related to cell division, foreign body metabolism, and ribosome assembly. A competing endogenous RNA (ceRNA) network was then constructed based on the regulatory dif-miRNA-dif-mRNA and dif-miRNA-dif-lncRNA relationships. These results were also verified using HCC data from the Cancer Genome Atlas (TCGA); seven dif-miRNAs were verified in clinical samples by real-time quantitative polymerase chain reaction (RT-qPCR). Kaplan-Meier survival analysis revealed that the expression levels of Hsa-miR-1269a, Hsa-miR-421, and Hsa-miR-190b were correlated with overall survival. (P <0.05). Survival analysis of clinical samples showed that hsa-mir-1269a, hsa-mir-421 were associated with prognosis (p<0.05).This study revealed the general expression characteristics of specific differentially expressed miRNAs using a ceRNA network constructed from HCC samples. Hsa-mir-1269a, hsa-mir-421 may be promising candidates.

Illuminating lncRNA Function Through Target Prediction

Most of the transcribed human genome codes for noncoding RNAs (ncRNAs), and long noncoding RNAs (lncRNAs) make for the lion's share of the human ncRNA space. Despite growing interest in lncRNAs, because there are so many of them, and because of their tissue specialization and, often, lower abundance, their catalog remains incomplete and there are multiple ongoing efforts to improve it. Consequently, the number of human lncRNA genes may be lower than 10,000 or higher than 200,000. A key open challenge for lncRNA research, now that so many lncRNA species have been identified, is the characterization of lncRNA function and the interpretation of the roles of genetic and epigenetic alterations at their loci. After all, the most important human genes to catalog and study are those that contribute to important cellular functions-that affect development or cell differentiation and whose dysregulation may play a role in the genesis and progression of human diseases. Multiple efforts have used screens based on RNA-mediated interference (RNAi), antisense oligonucleotide (ASO), and CRISPR screens to identify the consequences of lncRNA dysregulation and predict lncRNA function in select contexts, but these approaches have unresolved scalability and accuracy challenges. Instead-as was the case for better-studied ncRNAs in the past-researchers often focus on characterizing lncRNA interactions and investigating their effects on genes and pathways with known functions. Here, we focus most of our review on computational methods to identify lncRNA interactions and to predict the effects of their alterations and dysregulation on human disease pathways.

Long non-coding RNA PVT1 facilitates cell migration and invasion by regulating miR-148a-3p and ROCK1 in breast cancer

PURPOSE

Breast cancer (BC) is one of the most common malignant tumors for women. The role and potential mechanisms of long non-coding RNA plasmacytoma variant translocation 1 (lncRNA PVT1) were explored in BC cell migration and invasion.

METHODS

PVT1, miR-148a-3p and Rho‑associated, coiled‑coil containing protein kinase 1 (ROCK1) mRNA expressions were detected using real-time fluorescent quantitative polymerase chain reaction (qRT-PCR). The ROCK1 protein expression was detected by Western blotting. The relationship of PVT1, miR-148a-3p and ROCK1 was analyzed by Dual Luciferase activity, RNA immunoprecipitation (RIP) and Spearman correlation analysis. Cell invasion and migration were detected by Transwell assay.

RESULTS

Upregulation of PVT1 and ROCK1, and downregulation of miR-148a-3p were observed in BC tissues and cell lines. According to the analysis of Dual Luciferase activity, RIP and Spearman correlation analysis, miR-148a-3p directly binds to PVT1, and ROCK1 is a target of miR-148a-3p. In addition, PVT1 regulated the cells migration and invasion by regulating miR-148a-3p and ROCK1 expression.

CONCLUSION

These data demonstrated that PVT1 was upregulated and facilitated to the cell migration and invasion of BC by the regulation of miR-148a-3p and ROCK1, indicating that PVT1 may be a potential biomarker of BC diagnosis and treatment.

Identification and validation of a five-lncRNA signature for predicting survival with targeted drug candidates in ovarian cancer

The dysregulation of long non-coding RNAs (lncRNAs) plays a crucial role in ovarian cancer (OC). In this study, we screened out five differentially expressed lncRNAs (AC092718.4, AC138035.1, BMPR1B-DT, RNF157-AS1, and TPT1-AS1) between OC and normal ovarian based on TCGA and GTEx RNA-seq databases by using Kaplan-Meier analysis and univariate Cox, LASSO, and multivariate Cox regression. Then, a risk signature was constructed, with 1, 3, 5-year survival prediction accuracy confirmed by ROC curves, and an online survival calculator for easier clinical use. With lncRNA-microRNA-mRNA regulatory networks established, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed, suggesting the involvement of a variety of cancer-related functions and pathways. Finally, five candidate small-molecule drugs (thioridazine, trifluoperazine, loperamide, LY294002, and puromycin) were predicted by Connectivity Map. In conclusion, we identified a 5-lncRNA signature of prognostic value with its ceRNA networks, and five candidate drugs against OC.[Figure: see text].

Integrated analysis of long non-coding RNA-microRNA-mRNA competing endogenous RNAregulatory networks in thromboangiitis obliterans

Thromboangiitis obliterans (TAO) is a non-atherosclerotic, segmental, chronic vascular inflammatory disease. Our aim was to explore the underlying mechanisms of long non-coding RNA (lncRNA)-related competing endogenous RNAs (ceRNAs) in TAO. Six blood samples were collected from patients with TAO and healthy individuals (three for each category). Total RNA was extracted from the blood of each participant and sequenced. Differentially expressed lncRNAs (DE-lncRNAs) and miRNAs (DE-miRNAs) were screened, and ceRNA networks associated with TAO were constructed. Thereafter, the genes in the ceRNA network were subjected to functional analyses. Finally, a ceRNA relationship (lncRNA NEAT1-hsa-miR-1-3p-mRNA GNA12) was selected for further validation. Analysis revealed that 347 DE-lncRNAs (150 downregulated and 197 upregulated) and 16 DE-miRNAs (3 downregulated and 13 upregulated) were identified in TAO. Further, TAO-associated ceRNA networks, which included 219 lncRNAs, 6 miRNAs, and 53 mRNAs, were proposed and subjected to gene annotation and pathway analysis. Additionally, NEAT1 and GNA12 levels were significantly upregulated, while miR-1-3p levels were evidently downregulated in TAO patients, as compared with those in healthy controls. Dual luciferase reporter assays showed that NEAT1, miR-1-3p, and GNA12 interacted with each other. We report potential TAO-associated ceRNA regulatory networks and suggest activation of NEAT1/miR-1-3p/GNA12 signaling as a novel mechanism for TAO progression.

Construction and comprehensive analysis of a competitive endogenous RNA network to reveal potential biomarkers for the malignant differentiation of glioma

BACKGROUND

Long noncoding RNAs (lncRNAs) can act as microRNA (miRNA) sponges to regulate protein-coding gene expression; therefore, lncRNAs are considered major components of the competitive endogenous RNA (ceRNA) network and have attracted growing attention. This study explored the regulatory mechanisms and functional roles of lncRNAs as ceRNAs in the malignant differentiation of low-grade glioma (LGG) to glioblastoma (GBM) and their potential impact on the prognosis of patients with GBM.

METHODS

LncRNA and messenger RNA (mRNA) data were extracted from the Cancer Genome Atlas (TCGA) database from 156 GBM samples and 529 LGG samples. Separately, the miRNA expression data were downloaded from the Gene Expression Omnibus database, with the GSE112009 dataset containing miRNA expression data from 10 GBM samples and 15 LGG samples. Weighted gene coexpression network analysis was performed to screen the glioma grade-related lncRNAs. Then, a ceRNA network was established. The database for annotation, visualization, and integrated discovery was adopted to conduct functional enrichment analysis based on 57 upregulated differentially expressed mRNAs in the ceRNA network. Finally, Kaplan-Meier curves were created for the survival analysis of 13 hub lncRNA by combining the clinical data of GBM patients in TCGA.

RESULTS

A ceRNA network including 16 lncRNAs, 18 miRNAs, and 78 mRNAs specific to the malignant differentiation of LGG to GBM was established. The 57 upregulated differentially expressed mRNAs in the ceRNA network were significantly enriched in 35 gene ontology terms and 5 pathways. The survival analysis showed that 2 lncRNAs (LINC00261 and HOXA10-AS) were prognostic biomarkers for patients with GBM in TCGA.

CONCLUSION

The proposed ceRNA network may help elucidate the regulatory mechanism by which lncRNAs function as ceRNAs and contribute to the malignant differentiation of LGG to GBM. Importantly, the candidate lncRNAs, miRNAs, and mRNAs involved in the ceRNA network can be further evaluated as potential therapeutic targets and prognostic biomarkers for GBM.

Identification and Roles of miR-29b-1-3p and miR29a-3p-Regulated and Non-Regulated lncRNAs in Endocrine-Sensitive and Resistant Breast Cancer Cells

Despite improvements in the treatment of endocrine-resistant metastatic disease using combination therapies in patients with estrogen receptor α (ERα) primary tumors, the mechanisms underlying endocrine resistance remain to be elucidated. Non-coding RNAs (ncRNAs), including microRNAs (miRNA) and long non-coding RNAs (lncRNA), are targets and regulators of cell signaling pathways and their exosomal transport may contribute to metastasis. Previous studies have shown that a low expression of miR-29a-3p and miR-29b-3p is associated with lower overall breast cancer survival before 150 mos. Transient, modest overexpression of miR-29b1-3p or miR-29a-3p inhibited MCF-7 tamoxifen-sensitive and LCC9 tamoxifen-resistant cell proliferation. Here, we identify miR-29b-1/a-regulated and non-regulated differentially expressed lncRNAs in MCF-7 and LCC9 cells using next-generation RNA seq. More lncRNAs were miR-29b-1/a-regulated in LCC9 cells than in MCF-7 cells, including DANCR, GAS5, DSCAM-AS1, SNHG5, and CRND. We examined the roles of miR-29-regulated and differentially expressed lncRNAs in endocrine-resistant breast cancer, including putative and proven targets and expression patterns in survival analysis using the KM Plotter and TCGA databases. This study provides new insights into lncRNAs in endocrine-resistant breast cancer.

Comprehensive Characterization of Common and Cancer-Specific Differently Expressed lncRNAs in Urologic Cancers

Urologic cancers, comprising prostate carcinoma (PCa), renal cell carcinoma (RCC), and bladder carcinoma (BCa), were the commonly occurred carcinoma amid males. Long noncoding RNAs (lncRNAs) with the length of more than 200 nt functioned importantly in physiological and pathological advancement. Nevertheless, further investigation regarding lncRNA expression feature and function in urologic cancers should be essential. This study is aimed at uncovering the roles of the differently expressed lncRNAs in urologic cancers. The data of gene expression levels was downloaded from lncRNAtor datasets. The lncRNA expression pattern existing in different urologic cancers was assessed by hierarchical clustering analysis. Gene Ontology (GO) analysis and KEGG pathway analysis were separately applied to evaluate the biological function and process and the biological pathways involving differently expressed lncRNAs. Our results indicated that 18 lncRNA expressions were increased, and 16 lncRNA expressions were reduced in urologic cancers after comparison with that in normal tissues. Moreover, our results demonstrated 61, 422, 137, and 281 lncRNAs were specifically dysregulated in bladder cancer (BLCA), kidney renal clear cell cancer (KIRC), kidney renal papillary cell cancer (KIRP), and prostate adenocarcinoma (PRAD), respectively. Bioinformatics analysis showed that differently expressed lncRNAs displayed crucially in urologic cancers. The prognostic value of common and cancer-specific differently expressed lncRNAs, such as PVT1, in cancer outcomes, was emphasized here. Our research has deeply unearthed the mechanism of differently expressed lncRNAs in urologic cancers development.

Comprehensive analysis of lncRNA-miRNA-mRNA regulatory networks for microbiota-mediated colorectal cancer associated with immune cell infiltration

Recent findings have identified microbiota as crucial participants in many disease conditions, including cancers. Competing endogenous RNA (ceRNA) is regarded as a candidate mechanism involving relevant biological processes. We therefore constructed a ceRNA network using the TCGA and GEO database, to determine the potential mechanisms of microbiota-mediated colorectal carcinogenesis and progression. We found a total of 75 lncRNAs, 8 miRNAs, and 9 mRNAs in the probiotics-mediated ceRNA network and a total of 49 lncRNAs, 4 miRNAs, and 3 mRNA in the pathobiont-mediated ceRNA network, which could induce the microbiota-mediated carcinogenesis and progression. The GO and KEGG analysis indicated that the ceRNA network is mainly enriched in the metabolic process, and two unique pathways (the p53 signaling pathway and microRNA in cancer), respectively. A four-gene signature (FRMD6-AS2, DIRC3, LIFR-AS1, and MRPL23-AS1) was suggested as an independent prognostic factor. Four lncRNAs (LINC00355, KCNQ1OT1, LINC00491, and HOTAIR) were associated with poor survival. Three small molecule candidate anticancer drugs (Pentoxyverine, Rimexolone, and Doxylamine) were identified. A four-gene signature (FAM129A, BCL2, PMAIP1, and RPS6) is significantly correlated with immune infiltration level. This study provides a promising biomarker reservoir to explore the mechanism by which microbiota regulate the ceRNA network involving the immune response, and further participate in colorectal carcinogenesis and progression.

CircRAB3IP upregulates twist family BHLH transcription factor (TWIST1) to promote osteosarcoma progression by sponging miR-580-3p

Circular RNAs (circ RNAs) have been found to play an important role in cancer development. However, the role of circRAB3IP in osteosarcoma (OS) is unclear.

In the present study, We found that circRAB3IP was highly expressed in OS tissues and OS cells. High levels of circRAB3IP was correlated with advanced TNM stage, distant metastasis. CircRAB3IP knockdown inhibited cell proliferation, migration, and invasion. Moreover, circRAB3IP directly binds to miR-580-3p. TWIST1 is directly targeted by miR-580-3p. We also demonstrated that circRAB3IP act as the sponge of miR-580-3p to promote TWIST1 expression. CircRAB3IP promotes OS cells proliferation, migration, and invasion through modulating miR-580-3p/TWIST1 axis. Moreover, circRAB3IP facilitated tumor formation in vivo. Our findings suggested that circRAB3IP acts as an oncogene in OS by regulating miR-580-3p/TWIST1 axis.

Comprehensive analysis of ceRNA networks in HPV16- and HPV18-mediated cervical cancers reveals XIST as a pivotal competing endogenous RNA

Cervical cancer (CC) is one of the most common cancers in women worldwide, being closely related to high-risk human papillomavirus (HR-HPVs). After a particular HR-HPV infects a cervical cell, transcriptional changes in the host cell are expected, including the regulation of lncRNAs, miRNAs, and mRNAs. Such transcripts may work independently or integrated in complex molecular networks - as in competing endogenous RNA (ceRNA) networks. In our research, we gathered transcriptome data from samples of HPV16/HPV18 cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), from The Cancer Genome Atlas (TCGA) project. Using GDCRNATools, we identified ceRNA networks that differentiate HPV16- from HPV18-mediated CESC. For HPV16-CESC, three lncRNA-mRNA co-expressed pairs were reported, all led by the X-inactive specific transcript (XIST): XIST | DLG5, XIST | LGR4, and XIST | ZNF81. The XIST | LGR4 and XIST | ZNF81 pairs shared 11 miRNAs, suggesting an increased impact on their final biological effect. XIST also stood out as an important lncRNA in HPV18-CESC, leading 35 of the 42 co-expressed pairs. Some mRNAs, such as ADAM9 and SLC38A2, emerged as important players in the ceRNA regulatory networks due to sharing a considerable amount of miRNAs with XIST. Furthermore, some XIST-associated axes, namely XIST | miR-23a-3p | LGR4 and XIST | miR-30b-5p or miR-30c-5p or miR-30e-5p I ADAM9, had a significant impact on the overall survival of HPV16- and HPV18-CESC patients, respectively. Together, these data suggest that XIST has an important role in HPV-mediated tumorigenesis, which may implicate different molecular signatures between HPV16 and HPV18-associated tumors.

Identification of Potential Biomarkers in Neonatal Sepsis by Establishing a Competitive Endogenous RNA Network

BACKGROUND

Neonatal sepsis is a serious and difficult-to-diagnose systemic infectious disease occurring during the neonatal period.

OBJECTIVE

This study aimed to identify potential biomarkers of neonatal sepsis and explore its underlying mechanisms.

METHODS

We downloaded the neonatal sepsis-related gene profile GSE25504 from the NCBI Gene Expression Omnibus (GEO) database. The differentially expressed RNAs (DERs) were screened and identified using LIMMA. Then, the functions of the DERs were evaluated using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Finally, a competing endogenous RNA (ceRNA) network was constructed and functional analyses were performed.

RESULTS

The initial screening identified 444 differentially expressed (DE)-mRNAs and 45 DElncRNAs. GO analysis showed that these DE-mRNAs were involved in immune response, defense response, and positive regulation of immune system process. KEGG analysis showed that these DE-mRNAs were enriched in 30 activated pathways and 6 suppressed pathways, and those with the highest scores were the IL-17 signaling pathway and ribosome. Next, 722 miRNAs associated with the identified lncRNAs were predicted using miRWalk. A ceRNA network was constructed that included 6 lncRNAs, 11 mRNAs, and 55 miRNAs. In this network, HCP5, LINC00638, XIST and TP53TG1 were hub nodes. Functional analysis of this network identified some essential immune functions, hematopoietic functions, osteoclast differentiation, and primary immunodeficiency as associated with neonatal sepsis.

CONCLUSION

HCP5, LINC00638, TP53TG1, ST20-AS1, and SERPINB9P1 may be potential biomarkers of neonatal sepsis and may be useful for rapid diagnosis; the biological process of the immune response was related to neonatal sepsis.

Targeting PVT1 Exon 9 Re-Expresses Claudin 4 Protein and Inhibits Migration by Claudin-Low Triple Negative Breast Cancer Cells

PVT1 is a long non-coding RNA transcribed from a gene located at the 8q24 chromosomal region that has been implicated in multiple cancers including breast cancer (BC). Amplification of the 8q24 chromosomal region is a common event in BC and is associated with poor clinical outcomes. Claudin-low (CL) triple negative breast cancer (TNBC) is a subtype of BC with a particularly dismal outcome. We assessed PVT1 exon 9 expression in the T47D estrogen receptor positive BC cell line, and in the MDA MB 468 and MDA MB 231 TNBC cell lines, followed by the assessment of the expression of claudins 1, 3, 4 and 7, in MDA MB 468 and MDA MB 231 (TNBC) cells. We found that MDA MB 231 TNBC cells significantly express less claudin 1, 3, 4, and 7 than MDA MB 468 TNBC cells. PVT1 exon 9 is significantly upregulated in MDA MB 231 CL TNBC cells, and significantly downregulated in MDA MB 468 claudin high (CH) TNBC cells, in comparison to T47D estrogen receptor positive BC cells. We then analyzed the functional consequences of siRNA targeting of PVT1 exon 9 expression in the MDA MB 231 CL TNBC cells. Notably, siRNA targeting of PVT1 exon 9 expression in the MDA MB 231 CL TNBC cells led to a significant reduction in migration and the re-expression of claudin 4. Taken together, our data indicate that PVT1 exon 9 regulates claudin 4 expression and migration in CL TNBC cells, and may have clinical implications in CL TNBC.

The Implications of ncRNAs in the Development of Human Diseases

The mammalian genome comprehends a small minority of genes that encode for proteins (barely 2% of the total genome in humans) and an immense majority of genes that are transcribed into RNA but not encoded for proteins (ncRNAs). These non-coding genes are intimately related to the expression regulation of protein-coding genes. The ncRNAs subtypes differ in their size, so there are long non-coding genes (lncRNAs) and other smaller ones, like microRNAs (miRNAs) and piwi-interacting RNAs (piRNAs). Due to their important role in the maintenance of cellular functioning, any deregulation of the expression profiles of these ncRNAs can dissemble in the development of different types of diseases. Among them, we can highlight some of high incidence in the population, such as cancer, neurodegenerative, or cardiovascular disorders. In addition, thanks to the enormous advances in the field of medical genomics, these same ncRNAs are starting to be used as possible drugs, approved by the FDA, as an effective treatment for diseases.

CeNet Omnibus: an R/Shiny application to the construction and analysis of competing endogenous RNA network

Background

The competing endogenous RNA (ceRNA) regulation is a newly discovered post-transcriptional regulation mechanism and plays significant roles in physiological and pathological progress. CeRNA networks provide global views to help understand the regulation of ceRNAs. CeRNA networks have been widely used to detect survival biomarkers, select candidate regulators of disease genes, and predict long noncoding RNA functions. However, there is no software platform to provide overall functions from the construction to analysis of ceRNA networks.

Results

To fill this gap, we introduce CeNet Omnibus, an R/Shiny application, which provides a unified framework for the construction and analysis of ceRNA network. CeNet Omnibus enables users to select multiple measurements, such as Pearson correlation coefficient (PCC), mutual information (MI), and liquid association (LA), to identify ceRNA pairs and construct ceRNA networks. Furthermore, CeNet Omnibus provides a one-stop solution to analyze the topological properties of ceRNA networks, detect modules, and perform gene enrichment analysis and survival analysis. CeNet Omnibus intends to cover comprehensiveness, high efficiency, high expandability, and user customizability, and it also offers a web-based user-friendly interface to users to obtain the output intuitionally.

Conclusion

CeNet Omnibus is a comprehensive platform for the construction and analysis of ceRNA networks. It is highly customizable and outputs the results in intuitive and interactive. We expect that CeNet Omnibus will assist researchers to understand the property of ceRNA networks and associated biological phenomena. CeNet Omnibus is an R/Shiny application based on the Shiny framework developed by RStudio. The R package and detailed tutorial are available on our GitHub page with the URL https://github.com/GaoLabXDU/CeNetOmnibus.

PVT1: A long non-coding RNA recurrently involved in neoplasia-associated fusion transcripts

NGS technologies and bioinformatics tools allow the rapid identification of chimeric transcripts in cancer. More than 40,000 fusions are so far reported in the literature; however, for most of them, the role in oncogenesis is still not fully understood. This is the case for fusions involving the long non-coding RNA (lncRNA) Plasmacytoma variant translocation 1 (PVT1) (8q24.21). This lncRNA displays oncogenic functions in several cancer types interacting with microRNAs and proteins, but the role of PVT1 fusion transcripts is more obscure. These chimeras have been identified in both hematological malignancies and solid tumors, mainly arising from rearrangements and/or amplification of the 8q24 chromosomal region. In this review, we detail the full spectrum of PVT1 fusions in cancer, summarizing current knowledge about their genesis, function, and role as biomarkers.

Influence of pentoxifylline on gene expression of PAG1/ miR-1206/ SNHG14 in ischemic heart disease

The regulation by immune checkpoint is able to prevent excessive tissue damage caused by ischemia reperfusion (I/R); therefore, the study aims to investigate the behavior of phosphoprotein associated with glycosphingolipid-enriched microdomains 1 (PAG1) mRNA, miR-1206 and small nucleolar RNA host gene 14 (SNHG14) during I/R and intake of pentoxifylline (PTX) as a protective drug. The relative expression level of PAG1/miR-1206/SNHG14 was determined by qRT-PCR. Cardiac tissue levels of cytotoxic T-lymphocyte associated antigen 4 (CTLA4) and PAG1 protein expression were determined by ELISA technique. The regulatory T cells achieved by the flow cytometry. The results found that the relative expression of SNHG14 was significantly upregulated in I/R, but suppressed in PTX treated groups with enhancement of the relative expression level of miR-1206. The gene and protein expression of PAG1 were downregulated with effective doses of PTX. The results showed that (30 and 40 mg/kg bwt) PTX dose suppressed the CTLA4 development significantly. The mean of the regulatory T cell in PTX protective groups is significantly reduced at (p < 0.001) in a comparison with I/R group. Spearman's correlation analysis revealed a significant negative correlation between SNHG14 and miR-1206, but a significant positive correlation between SNHG14 and PAG1 in I/R heart tissue. The results indicated that miR-1206 and SNHG14 can be used as biomarkers with perfect sensitivity and specificity. Using PTX reduced cardiac tissue damage. SNHG14 and miR-1206 can be used as a diagnostic tool in I/R.

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Positive correlation between SNHG14 and PAG1 relative expression in I/R heart tissues.

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SNHG14 and miR-1206 can be used as a diagnostic tool in ischemia reperfusion.

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Negative correlation between SNHG14 and miR-1206.

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Using pentoxifylline as a protective drug renders cardiac tissues more resistance to ischemia.

An Overview of the Computational Models Dealing with the Regulatory ceRNA Mechanism and ceRNA Deregulation in Cancer

Pools of RNA molecules can act as competing endogenous RNAs (ceRNAs) and indirectly alter their expression levels by competitively binding shared microRNAs. This ceRNA cross talk yields an additional posttranscriptional regulatory layer, which plays key roles in both physiological and pathological processes. MicroRNAs can act as decoys by binding multiple RNAs, as well as RNAs can act as ceRNAs by competing for binding multiple microRNAs, leading to many cross talk interactions that could favor significant large-scale effects in spite of the weakness of single interactions. Identifying and studying these extended ceRNA interaction networks could provide a global view of the fine-tuning gene regulation in a wide range of biological processes and tumor progressions. In this chapter, we review current progress of predicting ceRNA cross talk, by summarizing the most up-to-date databases, which collect computationally predicted and/or experimentally validated miRNA-target and ceRNA-ceRNA interactions, as well as the widespread computational methods for discovering and modeling possible evidences of ceRNA-ceRNA interaction networks. These methods can be grouped in two categories: statistics-based methods exploit multivariate analysis to build ceRNA networks, by considering the miRNA expression levels when evaluating miRNA sponging relationships; mathematical methods build deterministic or stochastic models to analyze and predict the behavior of ceRNA cross talk.

Construction and analysis of competing endogenous RNA network of MCF-7 breast cancer cells based on the inhibitory effect of 6-thioguanine on cell proliferation

Previous research has proven that 6-thioguanine (6-TG) inhibits the growth of MCF-7 breast cancer cells. Accumulating evidence indicates that long non-coding (lnc)RNAs are involved in the development of various cancer types as competitive endogenous (ce)RNA molecules. The present study was conducted to investigate the regulatory mechanism underlying the function of lncRNAs as ceRNA molecules in MCF-7 cells and to identify more effective prognostic biomarkers for breast cancer treatment. The expression profiles of lncRNAs in untreated MCF-7 cells and 6-TG-treated MCF-7 cells were compared by RNA-seq. The regulatory associations among lncRNAs, micro (mi)RNAs and mRNAs were analyzed and verified by the TargetScan, miRDB and miRTarBas databases. The ceRNA networks were constructed by Cytoscape. The expression levels of two lncRNAs and two miRNAs in the ceRNA network were measured by reverse transcription-quantitative PCR. The OncoLnc and Kaplan-Meier plotter network databases were utilized to determine the effects of lncRNA and miRNA expression on the survival of patients with breast cancer. A ceRNA network was constructed for MCF-7 breast cancer cells treated with 6-TG, and this network may provide valuable information for further research elucidating the molecular mechanism underlying the effects of 6-TG on breast cancer. Moreover, LINC00324, MIR22HG, miR-370-3p and miR-424-5p were identified as potential prognostic and therapeutic biomarkers for breast cancer.

Identification of the 3-lncRNA Signature as a Prognostic Biomarker for Colorectal Cancer

Colorectal cancer (CRC) is one of the most common malignant carcinomas in the world, and metastasis is the main cause of CRC-related death. However, the molecular network involved in CRC metastasis remains poorly understood. Long noncoding RNA (lncRNA) plays a vital role in tumorigenesis and may act as a competing endogenous RNA (ceRNA) to affect the expression of mRNA by suppressing miRNA function. In this study, we identified 628 mRNAs, 144 lncRNAs, and 25 miRNAs that are differentially expressed (DE) in metastatic CRC patients compared with nonmetastatic CRC patients from the Cancer Genome Atlas (TCGA) database. Functional enrichment analyses confirmed that the identified DE mRNAs are extensively involved in CRC tumorigenesis and migration. By bioinformatics analysis, we constructed a metastasis-associated ceRNA network for CRC that includes 28 mRNAs, 12 lncRNAs, and 15 miRNAs. We then performed multivariate Cox regression analysis on the ceRNA-related DE lncRNAs and identified a 3-lncRNA signature (LINC00114, LINC00261, and HOTAIR) with the greatest prognostic value for CRC. Clinical feature analysis and functional enrichment analysis further proved that these three lncRNAs are involved in CRC tumorigenesis. Finally, we used Transwell, Cell Counting Kit (CCK)-8, and colony formation assays to clarify that the inhibition of LINC00114 promotes the migratory, invasive, and proliferative abilities of CRC cells. The results of the luciferase assay suggest that LINC00114 is the direct target of miR-135a, which also verified the ceRNA network. In summary, this study provides a metastasis-associated ceRNA network for CRC and suggests that the 3-lncRNA signature may be a useful candidate for the diagnosis and prognosis of CRC.

Competing endogenous RNAs and cancer: How coding and non-coding molecules cross-talk can impinge on disease

Cancers are characterized by several dramatic biological changes. Among the many post-transcriptional regulatory mechanisms, microRNAs are known as fine-tune regulators for their transcript silencing ability. Competing endogenous RNAs (ceRNAs) are transcripts that share microRNA binding elements and can compete for them, thus regulating each other indirectly. ceRNA networks interconnect the regulatory control of different transcript classes of the coding and non-coding space and co-operate with other cellular and molecular regulatory mechanisms. Altered ceRNA networks are involved in tumor formation and progression as well as in chemoresistance, in invasion and in the onset of metastases. The analysis of changes in the balance between ceRNA transcripts could offer hints to identify novel pathways for diagnosis, prognosis and therapies in precision medicine interventions. Moreover, the possibility to query highly specific tumor databases, such as TCGA, and to combine clinical data, transcript expression and sequence information is allowing to develop specific predictive tools for precision medicine.

LINC00174 is a novel prognostic factor in thymic epithelial tumors involved in cell migration and lipid metabolism

Long non-coding RNAs are emerging as new molecular players involved in many biological processes, such as proliferation, apoptosis, cell cycle, migration, and differentiation. Their aberrant expression has been reported in variety of diseases. The aim of this study is the identification and functional characterization of clinically relevant lncRNAs responsible for the inhibition of miR-145-5p, a key tumor suppressor in thymic epithelial tumors (TETs). Starting from gene expression analysis by microarray in a cohort of fresh frozen thymic tumors and normal tissues, we identified LINC00174 as upregulated in TET. Interestingly, LINC00174 expression is positively correlated with a 5-genes signature in TETs. Survival analyses, performed on the TCGA dataset, showed that LINC00174 and its associated 5-genes signature are prognostic in TETs. Specifically, we show that LINC00174 favors the expression of SYBU, FEM1B, and SCD5 genes by sponging miR-145-5p, a well-known tumor suppressor microRNA downregulated in a variety of tumors, included TETs. Functionally, LINC00174 impacts on cell migration and lipid metabolism. Specifically, SCD5, one of the LINC00174-associated genes, is implicated in the control of lipid metabolism and promotes thymic cancer cells migration. Our study highlights that LINC00174 and its associated gene signature are relevant prognostic indicators in TETs. Of note, we here show that a key controller of lipid metabolism, SCD5, augments the migration ability of TET cells, creating a link between lipids and motility, and highlighting these pathways as relevant targets for the development of novel therapeutic approaches for TET.

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.

Long non-coding RNA HOTAIRM1 promotes proliferation and inhibits apoptosis of glioma cells by regulating the miR-873-5p/ZEB2 axis

Background

Glioblastoma is one of the most common malignant brain tumors. Conventional clinical treatment of glioblastoma is not sufficient, and the molecular mechanism underlying the initiation and development of this disease remains unclear. Our study aimed to explore the expression and function of miR-873a-5p in glioblastoma and related molecular mechanism.

Methods

We analyzed the most dysregulated microRNAs from the Gene Expression Omnibus (GEO) database and examined the expression of miR-873-5p in 20 glioblastoma tissues compared with ten normal brain tissues collected in the Zhejiang Tongde Hospital. We then overexpressed or inhibited miR-873-5p expression in U87 glioblastoma cell lines and analyzed the phenotype using the cell counting kit-8 assay, wound healing assay, and apoptosis. In addition, we predicted upstream and downstream genes of miR-873-5p in glioblastoma using bioinformatics analysis and tested our hypothesis in U87 cells using the luciferase reporter gene assay and Western blotting assay. The differences between two groups were analyzed by Student's t test. The Kruskal-Wallis test was used for the comparison of multiple groups. A P < 0.05 was considered to be significant.

Results

The miR-873-5p was downregulated in glioblastoma tissues compared with that in normal brain tissues (normal vs. tumor, 0.762 ± 0.231 vs. 0.378 ± 0.114, t = 4.540, P < 0.01). Overexpression of miR-873-5p inhibited cell growth (t = 6.095, P < 0.01) and migration (t = 3.142, P < 0.01) and promoted cell apoptosis (t = 4.861, P < 0.01), while inhibition of miR-873-5p had the opposite effect. Mechanistically, the long non-coding RNA HOTAIRM1 was found to act as a sponge of miR-873-5p to activate ZEB2 expression in U87 cells.

Conclusions

We uncovered a novel HOTAIRM1/miR-873-5p/ZEB2 axis in glioblastoma cells, providing new insight into glioblastoma progression and a theoretical basis for the treatment of glioblastoma.

Long Noncoding RNA PVT1 Is Regulated by Bromodomain Protein BRD4 in Multiple Myeloma and Is Associated with Disease Progression

Long noncoding RNAs (lncRNAs) are deregulated in human cancers and are associated with disease progression. Plasmacytoma Variant Translocation 1 (PVT1), a lncRNA, is located adjacent to the gene MYC, which has been linked to multiple myeloma (MM). PVT1 is expressed in MM and is associated with carcinogenesis. However, its role and regulation remain uncertain. We examined PVT1/MYC expression using real-time PCR in plasma cells purified from 59 monoclonal gammopathy of undetermined significance (MGUS) and 140 MM patients. The MM cell lines KMS11, KMS12PE, OPM2, and RPMI8226 were treated with JQ1, an MYC super-enhancer inhibitor, or MYC inhibitor 10058-F4. The expression levels of PVT1 and MYC were significantly higher in MM than in MGUS (p < 0.0001) and were positively correlated with disease progression (r = 0.394, p < 0.0001). JQ1 inhibited cell proliferation and decreased the expression levels of MYC and PVT1. However, 10054-F4 did not alter the expression level of PVT1. The positive correlation between MYC and PVT1 in patients, the synchronous downregulation of MYC and PVT1 by JQ1, and the lack of effect of the MYC inhibitor on PVT1 expression suggest that the expression of these two genes is co-regulated by a super-enhancer. Cooperative effects between these two genes may contribute to MM pathogenesis and progression.

Characterization of super-enhancer-associated functional lncRNAs acting as ceRNAs in ESCC

Long noncoding RNAs (lncRNAs) have important regulatory roles in cancer biology. Although some lncRNAs have well-characterized functions, the vast majority of this class of molecules remains functionally uncharacterized. To systematically pinpoint functional lncRNAs, a computational approach was proposed for identification of lncRNA-mediated competing endogenous RNAs (ceRNAs) through combining global and local regulatory direction consistency of expression. Using esophageal squamous cell carcinoma (ESCC) as model, we further identified many known and novel functional lncRNAs acting as ceRNAs (ce-lncRNAs). We found that most of them significantly regulated the expression of cancer-related hallmark genes. These ce-lncRNAs were significantly regulated by enhancers, especially super-enhancers (SEs). Landscape analyses for lncRNAs further identified SE-associated functional ce-lncRNAs in ESCC, such as HOTAIR, XIST, SNHG5, and LINC00094. THZ1, a specific CDK7 inhibitor, can result in global transcriptional downregulation of SE-associated ce-lncRNAs. We further demonstrate that a SE-associated ce-lncRNA, LINC00094 can be activated by transcription factors TCF3 and KLF5 through binding to SE regions and promoted ESCC cancer cell growth. THZ1 downregulated expression of LINC00094 through inhibiting TCF3 and KLF5. Our data demonstrated the important roles of SE-associated ce-lncRNAs in ESCC oncogenesis and might serve as targets for ESCC diagnosis and therapy.

[The analysis of association between multiple sclerosis and genetic markers identified in genome-wide association studies]

OBJECTIVE

Our aim was to analyse the association with multiple sclerosis of the genetic markers of autoimmune disorders identified in genome-wide association studies in ethnically homogenous groups of Russians and Tatars residing in the Republic of Bashkortostan.

MATERIAL AND METHODS

We performed genotyping of the genetic variants rs2069762 in IL2 gene, rs759648 in PVT1 gene, rs1800682 in FAS gene and rs12708716 in CLEC16A gene in the study group consisting of 1724 people (547 patients with multiple sclerosis, 1177 representatives of the control group). We analysed the association of the studied genetic markers with multiple sclerosis using logistic regression under additive genetic model implemented in PLINK program with sex a covariate.

RESULTS

In the group of Tatars, we detected an association of PVT1 rs759648*Callele with multiple sclerosis (OR=1.42, p=0,023). Meta-analysis of the study results in the two ethnic groups we confirmed the association of the PVT1 rs759648*C allele with the disease (random effects model and fixed effect model: OR=1.29, p=0,018).

CONCLUSION

Our results provide an evidence of an association between multiple sclerosis and the PVT1 rs759648 allele in the populations of Russian and Tatars from the Republic of Bashkortostan. No association with any other studied polymorphic variant was found in the two ethnic groups.

A long non-coding RNA OLBC15 promotes triple-negative breast cancer progression via enhancing ZNF326 degradation

BACKGROUND

The long non-coding RNAs (lncRNAs) have been involved in various processes, including cancer. However, the function of many lncRNAs is still elusive in triple-negative breast cancer (TNBC).

METHODS

LncRNA profiling was used to screen for novel lncRNAs related to TNBC. OLBC15 expression was measured via qRT-PCR. In vitro migration and viability assays were conducted to determine the oncogenic role of OLBC15. Xenograft and metastatic models were performed to further investigate effects in vivo. RNA immunoprecipitation (RIP), mass spectrometry (MS), and fluorescence in situ hybridization (FISH) strategies were designed to identify the interaction between ZNF326 and OLBC15.

RESULTS

In the current study, we have identified a novel oncogenic lncRNA termed OLBC15 via lncRNA profiling. OLBC15 is highly expressed especially in triple-negative breast cancer. OLBC15 promoted viability and migration in breast cancer cells. Moreover, OLBC15 could accelerate metastasis and xenograft tumor growth. Mechanistic study suggested that OLBC15 could bind a well-characterized tumor suppressor ZNF326 and OLBC15-ZNF326 interaction resulted in ZNF326 destabilization. OLBC15 induced proteasomal ZNF326 degradation through enhanced ubiquitination. OLBC15 and ZNF326 protein expression is also negatively correlated in clinical specimens.

CONCLUSIONS

Collectively, OLBC15 may serve as an oncogenic lncRNA to facilitate TNBC progression and a putative target for therapeutic anti-breast cancer intervention.

RETRACTED: Long noncoding RNA LCTS5 inhibits non-small cell lung cancer by interacting with INO80

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted at the request of the Editor-in-Chief. The journal was alerted to an associated PubPeer post reporting that a migration assay image represented in Figure 2E appeared to have been previously published in another article, as detailed here: https://pubpeer.com/publications/EB45D50E3D52ABE00BDD60C2BD3057. The journal performed independent image analysis and confirmed this suspected image duplication. As per journal policy, authors were contacted and asked to provide an explanation to these concerns and associated raw data, but the authors failed to respond. The Editor-in-Chief assessed the case and decided to retract the article.

Lnc-M2 controls M2 macrophage differentiation via the PKA/CREB pathway

Long noncoding RNAs (lncRNAs) play an indispensable role in the process of M1 macrophage via regulating the development of macrophages and their responses to bacterial pathogens and viral infections. However, there are few studies on the lncRNA-mediated functions and regulatory mechanisms of M2 macrophage polarization. In this study, we found a number of differentially expressed lncRNAs between human monocyte derived M0 and M2 macrophages according to array analysis and quantitative polymerase chain reaction (qPCR) validation. The lncRNA RP11-389C8.2 (we named lnc-M2 in this study) was observed to be highly expressed in M2 macrophages. In Situ Localization and Quantification Analysis showed that lnc-M2 was expressed in the nucleus and cytosolic compartments of M2 macrophages. Notably, lnc-M2 knockdown enhanced the phagocytic ability of M2 macrophages. Ulteriorly, the results of RNA-Protein interaction experiments indicated that protein kinase A (PKA) was a lnc-M2 associated RNA-binding protein (RBP). Western blot showed that phosphorylated cAMP response element binding protein (p-CREB), a well-known key downstream transcription factor of PKA, was lowly phosphorylated in lnc-M2-silencing M2 macrophages. Furthermore, we found that transcriptional factor Signal Transducer And Activator Of Transcription 3 (STAT3) promoted lnc-M2 transcription along with the up-regulation of epigenetic histone modification markers at the lnc-M2 promoter locus, indicating that STAT3 activated lnc-M2 and eventually facilitated the process of M2 macrophage differentiation via the PKA/CREB pathway. Collectively, our date provide evidence that the transcription factor STAT3 can promote the transcription of lnc-M2 and facilitated the process of M2 macrophage differentiation via the PKA/CREB pathway. This study highlights a novel mechanism underlying the M2 macrophage differentiation.

LncRNA PVT1 epigenetically stabilizes and post-transcriptionally regulates FOXM1 by acting as a microRNA sponge and thus promotes malignant behaviors of ovarian cancer cells

Accumulating evidence demonstrates that long noncoding RNAs (lncRNAs) may be involved in the regulation of cancer biology. PVT1, which is overexpressed in tumor samples, acts as an oncogenic promoter in several kinds of cancers, including ovarian cancer. However, the mechanisms of its regulation of malignant behaviors in ovarian cancer remain largely unknown. In this study, the expression of PVT1 in several ovarian cancer cell lines was analyzed by qRT-PCR. The effect of PVT1 on malignant behaviors, including cell proliferation, migration and invasion, was analyzed. The posttranscriptional regulation of FOXM1 by PVT1 was analyzed by western blotting. The results illustrated that PVT1 acted as a sponge and bound miR-370 on two binding sites. The expression of PVT1 positively regulated malignant behaviors in ovarian cancer cells, including cell proliferation, migration and invasion, which could be reversed by the introduction of miR-370 mimics. Sponged miR-370 failed to posttranscriptionally regulate FOXM1, which resulted in the promotion of malignant behavior. PVT1 was also found to bind to FOXM1 directly and stabilize the FOXM1 protein. The promoting effect of PVT1 on malignant behaviors and chemoresistance to cisplatin could be reversed by knockdown of FOXM1 and introduction of miR-370 mimics. Together, these results suggest that lncRNA PVT1 promotes malignant behavior and induces chemoresistance in ovarian cancer by epigenetic and posttranscriptional regulation of FOXM1.

Roles of a TMPO-AS1/microRNA-200c/TMEFF2 ceRNA network in the malignant behaviors and 5-FU resistance of ovarian cancer cells

Competing endogenous RNA (ceRNA) networks consisted of long non-coding RNA (lncRNA), microRNA (miRNA) and mRNAs have aroused great interests recently. The current study aims to probe the mechanisms of lncRNA TMPO-AS1 in ovarian cancer (OC) development. A 5-fluorouracil (5-FU)-resistant subline of OC SKOV3 cells was developed, and differentially expressed lncRNAs in OC tissues and SKOV3 cells were analyzed. The miRNAs, genes and signaling pathways interacted with TMPO-AS1 were predicted and validated. TMPO-AS1 and the validated miRNA were inhibited to analyze their roles in malignant behaviors and 5-FU resistance of OC cells. In vivo studies were performed by inducing xenograft tumors in nude mice. Consequently, TMPO-AS1 was highly expressed in OC tissues and SKOV3 cells. TMPO-AS1 regulated transmembrane protein with epidermal growth factor and two follistatin motifs 2 (TMEFF2) through sponging miR-200c in OC cells, during which the PI3K/Akt signaling pathway was activated. Silenced TMPO-AS1 and over-expressed miR-200c inhibited epithelial-mesenchymal transition (EMT), invasion, migration and 5-FU resistance of OC cells. This study demonstrated that silencing of TMPO-AS1 might attenuate OC progression through inhibiting the invasion, metastasis and drug resistance of OC cells via the miR-200c/TMEFF2 network and the disruption of the PI3K/Akt signaling pathway.

Identification of specific microRNA-messenger RNA regulation pairs in four subtypes of breast cancer

Four subtypes of breast cancer, luminal A, luminal B, basal-like, human epidermal growth factor receptor-enriched, have been identified based on gene expression profiles of human tumours. The goal of this study is to find whether the same groups' genes would exhibit different networks among the four subtypes. Differential expressed genes between each of the four subtypes and the normal samples were identified. The overlaps between the four groups of differentially expressed genes were used to construct regulations networks for each of the four subtypes. Univariate and multivariate Cox regressions were employed to test the genes in the four regulation networks. This study demonstrated that the common genes in four subtypes showed different regulation. Also, the hsa-miR-182 and decorin pair performs different functions among the four subtypes of breast cancer. The result indicated that heterogeneity of breast cancer is not only reflected in the different expression patterns among different genes, but also in the different regulatory networks of the same group of genes.

CircRNA hsa_circ_0070934 functions as a competitive endogenous RNA to regulate HOXB7 expression by sponging miR‑1236‑3p in cutaneous squamous cell carcinoma

Circular ribonucleic acids (circRNAs) serve a vital role in the pathological processes of a number of diseases. Previous microarray results of circRNA expression revealed that hsa_circ_0070933 and hsa_circ_0070934, two circRNAs associated with the La ribonucleoprotein 1B gene, were highly expressed in cutaneous squamous cell carcinoma (CSCC). The present study aimed to explore the specific role of these circRNAs in CSCC. Through reverse transcription-quantitative PCR, hsa_circ_0070933 and hsa_circ_0070934 expression levels in CSCC cell lines and a human keratino-cyte cell line were detected. Additionally, direct interactions between miR-1236-3p and HOXB7 or circ-0070934 were identified using RNA binding protein immunoprecipitation assays and dual-luciferase reporter assays. Cell Counting Kit-8, 5-ethynyl-2′-deoxyuridine, Transwell invasion and flow cytometry assays were used to assess the roles of miR-1236-3p or circ-0070934 in cell invasion, proliferation and apoptosis. Subsequently, in vivo tumor formation assays were used to verify the role of circ-0070934 in CSCC. The results demonstrated that the expression of circ-0070934 was stably upregulated in a number of CSCC cell lines compared with that in normal human keratinocytes. Knockdown of circ-0070934 inhibited the invasive and proliferative potential of CSCC cells and promoted apoptosis both in vivo and in vitro. In addition, circ-0070934 modulated HOXB7 expression through competitive binding with miR-1236-3p. In conclusion, the results of the present study demonstrated the effects of the circ-0070934/miR-1236-3p/HOXB7 regulatory axis on CSCC and provided a novel insight for the pathogenesis of CSCC.

CCHE1 accelerated the initiation of oral squamous cell carcinoma through enhancing PAK2 expression by sponging miR-922

BACKGROUND

Oral squamous cell carcinoma (OSCC) is a normal form of mouth cancer, comprising the majority of oral cancers. A large number of long non-coding RNAs (lncRNAs) have been reported due to their oncogenic function in cancers. Recent studies show that lncRNA CCHE1 is an oncogene in a wide range of cancers. Whether CCHE1 accelerates the progression of OSCC is still undiscovered.

METHODS

The qRT-PCR analysis was used to determine CCHE1, miR-922, and PAK2 expression levels. CCK8 and colony formation assays were applied to evaluate OSCC cell proliferative ability. Transwell assay was performed to investigate the capability of cell migration and invasion. Cell apoptosis was assessed by flow cytometry analysis. The distribution of CCHE1 in OSCC cells was confirmed via subcellular fractionation assay. Luciferase reporter assay was used to verify the connection between miR-922 and CCHE1 or PAK2.

RESULTS

qRT-PCR analysis identified the upregulation of CCHE1 in OSCC cells. Knockdown of CCHE1 curbed the proliferation, migration, and invasion and hastened the apoptosis in OSCC cell lines. Moreover, it was found that miR-922 could interact with CCHE1. Besides, PAK2 was identified as the target gene of miR-922 and its expression was negatively modulated by miR-922 and positively regulated by CCHE1. Restoration assay manifested that the suppressing influence of CCHE1 depletion on OSCC progression was rescued by amplified PAK2.

CONCLUSIONS

CCHE1 increases the expression of PAK2 to promote the progression of OSCC by competitively binding to miR-922 in OSCC cells.

Long noncoding RNA PVT1 acts as an oncogenic driver in human pan-cancer

Increasing evidence indicates that long noncoding RNAs (lncRNAs) play pivotal roles during tumorigenesis in multiple types of cancers. However, little is known about the exact role of plasmacytoma variant translocation 1 (PVT1) in human pan-cancer. Here, we report the oncogenic role and function of PVT1 in human pan-cancer, including breast cancer. The expression of PVT1 in human tumor tissues and nontumor tissues, the upstream regulation of PVT1 and the relationship between its expression and prognosis and chemoresistance were examined by using The Cancer Genome Atlas data. PVT1 expression is higher in human cancer tissues compared with adjacent noncancerous tissues, and patients with high levels of PVT1 expression usually have tumors with a higher TNM stage. High PVT1 expression is also associated with worse disease outcomes in patients with cancer. Hypomethylation and transcription factor binding in the PVT1 promoter locus activates its transcriptional expression. Guilt by association analysis revealed that PVT1 may be involved in processes associated with tumorigenesis. Moreover, PVT1 may trigger chemoresistance in human cancer. These results indicated that PVT1 may act as an oncogenic driver and maybe a potential therapeutic target in human cancer.

Construction of competing endogenous RNA networks from paired RNA-seq data sets by pointwise mutual information

BACKGROUND

A long noncoding RNA (lncRNA) can act as a competing endogenous RNA (ceRNA) to compete with an mRNA for binding to the same miRNA. Such an interplay between the lncRNA, miRNA, and mRNA is called a ceRNA crosstalk. As an miRNA may have multiple lncRNA targets and multiple mRNA targets, connecting all the ceRNA crosstalks mediated by the same miRNA forms a ceRNA network. Methods have been developed to construct ceRNA networks in the literature. However, these methods have limits because they have not explored the expression characteristics of total RNAs.

RESULTS

We proposed a novel method for constructing ceRNA networks and applied it to a paired RNA-seq data set. The first step of the method takes a competition regulation mechanism to derive candidate ceRNA crosstalks. Second, the method combines a competition rule and pointwise mutual information to compute a competition score for each candidate ceRNA crosstalk. Then, ceRNA crosstalks which have significant competition scores are selected to construct the ceRNA network. The key idea, pointwise mutual information, is ideally suitable for measuring the complex point-to-point relationships embedded in the ceRNA networks.

CONCLUSION

Computational experiments and results demonstrate that the ceRNA networks can capture important regulatory mechanism of breast cancer, and have also revealed new insights into the treatment of breast cancer. The proposed method can be directly applied to other RNA-seq data sets for deeper disease understanding.

Long noncoding RNAs in cancer: From discovery to therapeutic targets

Long noncoding RNAs (lncRNAs) have recently gained considerable attention as key players in biological regulation; however, the mechanisms by which lncRNAs govern various disease processes remain mysterious and are just beginning to be understood. The ease of next-generation sequencing technologies has led to an explosion of genomic information, especially for the lncRNA class of noncoding RNAs. LncRNAs exhibit the characteristics of mRNAs, such as polyadenylation, 5' methyl capping, RNA polymerase II-dependent transcription, and splicing. These transcripts comprise more than 200 nucleotides (nt) and are not translated into proteins. Directed interrogation of annotated lncRNAs from RNA-Seq datasets has revealed dramatic differences in their expression, largely driven by alterations in transcription, the cell cycle, and RNA metabolism. The fact that lncRNAs are expressed cell- and tissue-specifically makes them excellent biomarkers for ongoing biological events. Notably, lncRNAs are differentially expressed in several cancers and show a distinct association with clinical outcomes. Novel methods and strategies are being developed to study lncRNA function and will provide researchers with the tools and opportunities to develop lncRNA-based therapeutics for cancer.

LncmiRSRN: identification and analysis of long non-coding RNA related miRNA sponge regulatory network in human cancer

Motivation

MicroRNAs (miRNAs) are small non-coding RNAs with the length of ∼22 nucleotides. miRNAs are involved in many biological processes including cancers. Recent studies show that long non-coding RNAs (lncRNAs) are emerging as miRNA sponges, playing important roles in cancer physiology and development. Despite accumulating appreciation of the importance of lncRNAs, the study of their complex functions is still in its preliminary stage. Based on the hypothesis of competing endogenous RNAs (ceRNAs), several computational methods have been proposed for investigating the competitive relationships between lncRNAs and miRNA target messenger RNAs (mRNAs). However, when the mRNAs are released from the control of miRNAs, it remains largely unknown as to how the sponge lncRNAs influence the expression levels of the endogenous miRNA targets.

Results

We propose a novel method to construct lncRNA related miRNA sponge regulatory networks (LncmiRSRNs) by integrating matched lncRNA and mRNA expression profiles with clinical information and putative miRNA-target interactions. Using the method, we have constructed the LncmiRSRNs for four human cancers (glioblastoma multiforme, lung cancer, ovarian cancer and prostate cancer). Based on the networks, we discover that after being released from miRNA control, the target mRNAs are normally up-regulated by the sponge lncRNAs, and only a fraction of sponge lncRNA-mRNA regulatory relationships and hub lncRNAs are shared by the four cancers. Moreover, most sponge lncRNA-mRNA regulatory relationships show a rewired mode between different cancers, and a minority of sponge lncRNA-mRNA regulatory relationships conserved (appearing) in different cancers may act as a common pivot across cancers. Besides, differential and conserved hub lncRNAs may act as potential cancer drivers to influence the cancerous state in cancers. Functional enrichment and survival analysis indicate that the identified differential and conserved LncmiRSRN network modules work as functional units in biological processes, and can distinguish metastasis risks of cancers. Our analysis demonstrates the potential of integrating expression profiles, clinical information and miRNA-target interactions for investigating lncRNA regulatory mechanism.

Availability and implementation

LncmiRSRN is freely available (https://github.com/zhangjunpeng411/LncmiRSRN).

Supplementary information

Supplementary data are available at Bioinformatics online.

LncRNA PVT1 up-regulation is a poor prognosticator and serves as a therapeutic target in esophageal adenocarcinoma

Background

PVT1 has emerged as an oncogene in many tumor types. However, its role in Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) is unknown. The aim of this study was to assess the role of PVT1 in BE/EAC progression and uncover its therapeutic value against EAC.

Methods

PVT1 expression was assessed by qPCR in normal, BE, and EAC tissues and statistical analysis was performed to determine the association of PVT1 expression and EAC (stage, metastases, and survival). PVT1 antisense oligonucleotides (ASOs) were tested for their antitumor activity in vitro and in vivo.

Results

PVT1 expression was up-regulated in EACs compared with paired BEs, and normal esophageal tissues. High expression of PVT1 was associated with poor differentiation, lymph node metastases, and shorter survival. Effective knockdown of PVT1 in EAC cells using PVT1 ASOs resulted in decreased cell proliferation, invasion, colony formation, tumor sphere formation, and reduced proportion of ALDH1A1⁺ cells. Mechanistically, we discovered mutual regulation of PVT1 and YAP1 in EAC cells. Inhibition of PVT1 by PVT1 ASOs suppressed YAP1 expression through increased phosphor-LATS1and phosphor-YAP1 while knockout of YAP1 in EAC cells significantly suppressed PVT1 levels indicating a positive regulation of PVT1 by YAP1. Most importantly, we found that targeting both PVT1 and YAP1 using their specific ASOs led to better antitumor activity in vitro and in vivo.

Conclusions

Our results provide strong evidence that PVT1 confers an aggressive phenotype to EAC and is a poor prognosticator. Combined targeting of PVT1 and YAP1 provided the highest therapeutic index and represents a novel therapeutic strategy.

Electronic supplementary material

The online version of this article (10.1186/s12943-019-1064-5) contains supplementary material, which is available to authorized users.

Systematic analysis identifies three-lncRNA signature as a potentially prognostic biomarker for lung squamous cell carcinoma using bioinformatics strategy

Background

Lung squamous cell carcinoma (LUSC) is the second most common histological subtype of lung cancer (LC), and the prognoses of most LUSC patients are so far still very poor. The present study aimed at integrating lncRNA, miRNA and mRNA expression data to identify lncRNA signature in competitive endogenous RNA (ceRNA) network as a potentially prognostic biomarker for LUSC patients.

Methods

Gene expression data and clinical characteristics of LUSC patients were retrieved from The Cancer Genome Atlas (TCGA) database, and were integratedly analyzed using bioinformatics methods including Differentially Expressed Gene Analysis (DEGA), Weighted Gene Co-expression Network Analysis (WGCNA), Protein and Protein Interaction (PPI) network analysis and ceRNA network construction. Subsequently, univariate and multivariate Cox regression analyses of differentially expressed lncRNAs (DElncRNAs) in ceRNA network were performed to predict the overall survival (OS) in LUSC patients. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of multivariate Cox regression model. Gene expression profiling interactive analysis (GEPIA) was used to validate key genes.

Results

WGCNA showed that turquoise module including 1,694 DElncRNAs, 2,654 DEmRNAs as well as 113 DEmiRNAs was identified as the most significant modules (cor=0.99, P<1e-200), and differentially expressed RNAs in the module were used to subsequently analyze. PPI network analysis identified FPR2, GNG11 and ADCY4 as critical genes in LUSC, and survival analysis revealed that low mRNA expression of FPR2 and GNG11 resulted in a higher OS rate of LUSC patients. A lncRNA-miRNA-mRNA ceRNA network including 121 DElncRNAs, 18 DEmiRNAs and 3 DEmRNAs was established, and univariate and multivariate Cox regression analysis of those 121 DElncRNAs showed a group of 3 DElncRNAs (TTTY16, POU6F2-AS2 and CACNA2D3-AS1) had significantly prognostic value in OS of LUSC patients. ROC analysis showed that the area under the curve (AUC) of the 3-lncRNA signature associated with 3-year survival was 0.629.

Conclusions

The current study provides novel insights into the lncRNA-related regulatory mechanisms underlying LUSC, and identifying 3-lncRNA signature may serve as a potentially prognostic biomarker in predicting the OS of LUSC patients.

Cancer-related long noncoding RNAs show aberrant expression profiles and competing endogenous RNA potential in esophageal adenocarcinoma

Long non-coding RNAs (lncRNAs) govern gene expression by competitively binding to microRNA response elements (MREs). Although they were initially considered as transcriptional noise, lncRNAs have attracted increased attention in oncology. Dysregulation of lncRNAs occurs in various types of human tumor, including esophageal adenocarcinoma (EAC). However, the functions of these cancer-associated lncRNAs and of their related competitive endogenous RNA (ceRNA) network in EAC remains unknown. To determine the relevant potential mechanisms, the present study analyzed the transcriptome sequencing data and clinical information of 79 patients with EAC, including 79 tumor samples and 11 normal samples, which were obtained from The Cancer Genome Atlas esophageal cancer project. The edgeR v3.25.0 software was used for differential gene expression analysis. The results exhibited 561 cancer-associated lncRNAs with a >2.0-fold change and a false discovery rate-adjusted P<0.01. Among these lncRNAs, 26 were significantly associated with patient overall survival. According to data from bioinformatics databases and differentially expressed RNAs, an lncRNA-regulated ceRNA network for EAC was constructed. The results demonstrated that the aberrantly expressed lncRNA-associated ceRNA network included 37 EAC cancer-associated lncRNAs, five miRNAs and 13 mRNAs. In conclusion, the present study identified novel lncRNAs as candidate prognostic biomarkers and revealed a potential regulatory network of gene expression in EAC.

Predicting lncRNA-miRNA Interaction via Graph Convolution Auto-Encoder

The interaction of miRNA and lncRNA is known to be important for gene regulations. However, the number of known lncRNA-miRNA interactions is still very limited and there are limited computational tools available for predicting new ones. Considering that lncRNAs and miRNAs share internal patterns in the partnership between each other, the underlying lncRNA-miRNA interactions could be predicted by utilizing the known ones, which could be considered as a semi-supervised learning problem. It is shown that the attributes of lncRNA and miRNA have a close relationship with the interaction between each other. Effective use of side information could be helpful for improving the performance especially when the training samples are limited. In view of this, we proposed an end-to-end prediction model called GCLMI (Graph Convolution for novel lncRNA-miRNA Interactions) by combining the techniques of graph convolution and auto-encoder. Without any preprocessing process on the feature information, our method can incorporate raw data of node attributes with the topology of the interaction network. Based on a real dataset collected from a public database, the results of experiments conducted on k-fold cross validations illustrate the robustness and effectiveness of the prediction performance of the proposed prediction model. We prove the graph convolution layer as designed in the proposed model able to effectively integrate the input data by filtering the graph with node features. The proposed model is anticipated to yield highly potential lncRNA-miRNA interactions in the scenario that different types of numerical features describing lncRNA or miRNA are provided by users, serving as a useful computational tool.