Identification of RNA Expression Profiles in Thyroid Cancer to Construct a Competing Endogenous RNA (ceRNA) Network of mRNAs, Long Noncoding RNAs (lncRNAs), and microRNAs (miRNAs)

Unveiling four axes ADAMTS9-AS2|MEG3/hsa-miR-150/PRKCA|MMP14 within prostate cancer through establishment of the ceRNA network

Prostate cancer is among the most common cancers in males. Recent application of system biology methods has resulted in identification of key genes in the process of carcinogenesis. In the current study, we selected two datasets related to prostate cancer (PCa) and performed bulk RNA-seq analysis by selecting samples with Gleason scores greater than 7 and combining them. Subsequently, using several systems biology approaches, we constructed the ceRNA network and ultimately identified key axes related to PCa. Our analyses revealed importance of ADAMTS9-AS2/miR-150/PRKCA, ADAMTS9-AS2/miR-150/MMP14, MEG3/miR-150/PRKCA and MEG3/miR-150/MMP14 with miR-150 being a central component. Remarkably, miR-150 exhibited strong statistical significance in survival analyses. Further, analyzing expression levels from TCGA datasets, the expression of the identified genes associates significantly with prostate cancer compared to normal tissue confirming the bioinformatic analyses. Therefore, these genes can be regarded as prognostic markers in prostate cancer and the pathways are potential targets for therapeutic interventions.

MicroRNAs Associated with IgLON Cell Adhesion Molecule Expression

The IgLON family of cell adhesion molecules consists of five members (LSAMP, OPCML, neurotrimin, NEGR1, and IgLON5) discovered as supporters of neuronal development, axon growth and guidance, and synapse formation and maintenance. Tumour suppression properties have recently been emerging based on antiproliferative effects through the modulation of oncogenic pathways. Available evidence endorses a role for non-coding RNAs or microRNAs as relevant controllers of IgLON molecule expression that can impact their critical physiological and pathological roles. Current findings support a function for long non-coding RNAs and microRNAs in the modulation of LSAMP expression in cell senescence, cancer biogenesis, addiction, and pulmonary hypertension. For OPCML, data point to a role for several microRNAs in the control of tumorigenesis. MicroRNAs were detected in neurotrimin-mediated functions in cancer biogenesis and in Schwann cell responses to peripheral nerve injury. For NEGR1, studies have mainly investigated microRNA involvement in neuronal responses to ischaemic injury, although data also exist about tumorigenesis and endothelial cell dysfunction. For IgLON5, information is only available about microRNA involved in myocardial infarction. In conclusion, despite much information being still missing and further research needed, the emerging picture favours a model in which non-coding RNAs exert a crucial role in modulating IgLON expression, ultimately affecting their important physiological functions.

Integrative analysis of plasma and substantia nigra in Parkinson's disease: unraveling biomarkers and insights from the lncRNA-miRNA-mRNA ceRNA network

Introduction

Parkinson's disease (PD) is a rapidly growing neurological disorder characterized by diverse movement symptoms. However, the underlying causes have not been clearly identified, and accurate diagnosis is challenging. This study aimed to identify potential biomarkers suitable for PD diagnosis and present an integrative perspective on the disease.

Methods

We screened the GSE7621, GSE8397-GPL96, GSE8397-GPL97, GSE20163, and GSE20164 datasets in the NCBI GEO database to identify differentially expressed (DE) mRNAs in the substantia nigra (SN). We also screened the GSE160299 dataset from the NCBI GEO database to identify DE lncRNAs and miRNAs in plasma. We then constructed 2 lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) regulatory networks based on the ceRNA hypothesis. To understand the biological function, we performed Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses for each ceRNA network. The receiver operating characteristic analyses (ROC) was used to assess ceRNA results.

Results

We identified 7 upregulated and 29 downregulated mRNAs as common DE mRNAs in the 5 SN datasets. In the blood dataset, we identified 31 DE miRNAs (9 upregulated and 22 downregulated) and 332 DE lncRNAs (69 upregulated and 263 downregulated). Based on the determined interactions, 5 genes (P2RX7, HSPA1, SLCO4A1, RAD52, and SIRT4) appeared to be upregulated as a result of 10 lncRNAs sponging 4 miRNAs (miR-411, miR-1193, miR-301b, and miR-514a-2/3). Competing with 9 genes (ANK1, CBLN1, RGS4, SLC6A3, SYNGR3, VSNL1, DDC, KCNJ6, and SV2C) for miR-671, a total of 26 lncRNAs seemed to function as ceRNAs, influencing genes to be downregulated.

Discussion

In this study, we successfully constructed 2 novel ceRNA regulatory networks in patients with PD, including 36 lncRNAs, 5 miRNAs, and 14 mRNAs. Our results suggest that these plasma lncRNAs are involved in the pathogenesis of PD by sponging miRNAs and regulating gene expression in the SN of the brain. We propose that the upregulated and downregulated lncRNA-mediated ceRNA networks represent mechanisms of neuroinflammation and dopamine neurotransmission, respectively. Our ceRNA network, which was associated with PD, suggests the potential use of DE miRNAs and lncRNAs as body fluid diagnostic biomarkers. These findings provide an integrated view of the mechanisms underlying gene regulation and interactions in PD.

A novel exosome-related prognostic risk model for thyroid cancer

AIM

The aim was to build an exosome-related gene (ERG) risk model for thyroid cancer (TC) patients.

METHODS

Note that, 510 TC samples from The Cancer Genome Atlas database and 121 ERGs from the ExoBCD database were obtained. Differential gene expression analysis was performed to get ERGs in TC (TERGs). Functional enrichment analyses including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted on the TERGs. Then we constructed a model based on LASSO Cox regression analysis. Kaplan-Meier survival analysis was applied and a Nomogram model was also built. The immune landscape was evaluated by CIBERSORT.

RESULTS

Thirty-eight TERGs were identified and their functions were enriched on 591 GO terms and 30 KEGG pathways. We built a Risk Score model based on FGFR3, ADRA1B, and POSTN. Risk Scores were significantly higher in T4 than in other stages, meanwhile, it didn't significantly differ in genders and TNM N or M classifications. The nomogram model could reliably predict the overall survival of TC patients. The mutation rate of BRAF and expression of cytotoxic T-lymphocyte-associated protein 4 were significantly higher in the high-risk group than in the low-risk group. The risk score was significantly correlated to the immune landscape.

CONCLUSION

We built a Risk Score model using FGFR3, ADRA1B, and POSTN which could reliably predict the prognosis of TC patients.

A nomogram based on clinicopathological and ultrasound characteristics to predict central neck lymph node metastases in papillary thyroid cancer

Purpose

Papillary thyroid cancer (PTC) has grown rapidly in prevalence over the past few decades, and central neck lymph node metastasis (CNLNM) is associated with poor prognoses. However, whether to carry out preventive central neck lymph node dissection (CNLND) is still controversial. We aimed to construct a prediction model of CNLNM to facilitate making clinical surgical regimens.

Methods

A total of 691 patients with PTC between November 2018 and December 2021 were included in our study. Univariate and multivariate analyses were performed on basic information and clinicopathological characteristics, as well as ultrasound characteristics (American College of Radiology (ACR) scores). The prediction model was constructed and performed using a nomogram, and then discriminability, calibrations, and clinical applicability were evaluated.

Results

Five variables, namely, male, age >55 years, clinical lymph node positivity, tumor size ≥1 cm, and ACR scores ≥6, were independent predictors of CNLNM in the multivariate analysis, which were eventually included to construct a nomogram model. The area under the curve (AUC) of the model was 0.717, demonstrating great discriminability. A calibration curve was developed to validate the calibration of the present model by bootstrap resampling, which indicated that the predicted and actual values were in good agreement and had no differentiation from the ideal model. The decision curve analysis (DCA) indicated that the prediction model has good clinical applicability.

Conclusions

Our non-invasive prediction model combines ACR scores with clinicopathological features presented through nomogram and has shown good performance and application prospects for the prediction of CNLNM in PTCs.

Construction of ceRNA network and identification of hub differentially expressed genes associated with breast cancer using reanalysis of microarray dataset: A systems biology approach

The interaction between long non-coding RNAs (lncRNAs), miRNAs and mRNAs has implications in the pathogenesis of different cancer, including breast cancer. In the current study, we developed an in-silico approach to ascertain the competing endogenous RNA (ceRNA) network in breast cancer. Our approach led to identification of 1816 differentially expressed (DE) mRNAs, including 1039 downregulated DEmRNAs (such as LEP and ADIPOQ) and 777 upregulated DEmRNAs (such as COL11A1 and COL10A1), 19 DElncRNAs, including 15 downregulated DElncRNAs (such as CARMN and COPG2IT1) and 4 upregulated DElncRNAs (such as MALAT1 and NRAV) and 27 DEmiRNAs, including 15 downregulated DEmiRNAs (such as MIR452 and MIR224) and 12 upregulated DEmiRNAs (such as MIR6787 and MIR21). Pathway analysis revealed down-regulation of PPAR, Fatty acid metabolism, Adipocytokine, Vascular smooth muscle contraction and Metabolism of xenobiotics by cytochrome P450, while up-regulation of Pyrimidine metabolism, p53 signaling pathway, Cell cycle, Oocyte meiosis and RNA transport pathways in breast cancer. Finally, we constructed an lncRNA/miRNA/mRNA ceRNA network consisted of 2 lncRNAs, 15 mRNAs, and 4 miRNAs. This network represents an appropriate target for design of anti-cancer modalities and documentation of novel markers for breast cancer.

Integrated network pharmacology analysis and in vitro validation revealed the underlying mechanism of Xiyanping injection in treating coronavirus disease 2019

BACKGROUND

Coronavirus disease 2019 (COVID-19) has spread rapidly worldwide, leading to a pandemic. In China, Xiyanping injection (XYP) has been recommended as a drug for COVID-19 treatment in the Guideline on Diagnosis and Treatment of COVID-19 by the National Health Commission of the People Republic of China and National Administration of Traditional Chinese Medicine (Trial eighth Edition). However, the relevant mechanisms at the molecular-level need to be further elucidated.

METHODS

In this study, XYP related active ingredients, potential targets and COVID-19 related genes were searched in public databases. Protein-protein interaction network and module analyzes were used to screen for key targets. gene ontology and Kyoto encyclopedia of genes and genomes were performed to investigate the potentially relevant signaling pathways. Molecular docking was performed using Autodock Tools and Vina. For the validation of potential mechanism, PolyI:C was used to induce human lung epithelial cells for an inflammation model. Subsequently, CCK-8 assays, enzyme-linked immunosorbent assay, reverse transcription quantitative polymerase chain reaction and western blot were employed to determine the effect of XYP on the expression of key genes.

RESULTS

Seven effective active ingredients in XYP were searched for 123 targets in the relevant databases. Furthermore, 6446 COVID-19 disease targets were identified. Sodium 9-dehydro-17-hydro-andrographolide-19-yl sulfate was identified as the vital active compounds, and IL-6, TNF, IL-1β, CXCL8, STAT3, MAPK1, MAPK14, and MAPK8 were considered as the key targets. In addition, molecular docking revealed that the active compound and the targets showed good binding affinities. The enrichment analysis predicted that the XYP could regulate the IL-17, Toll-like receptor, PI3K-Akt and JAK-STAT signaling pathways. Consistently, further in vitro experiments demonstrated that XYP could slow down the cytokine storm in the lung tissue of COVID-19 patients by down-regulating IL-6, TNF-α, IL-1β, CXCL8, and p-STAT3.

CONCLUSION

Through effective network pharmacology analysis and molecular docking, this study suggests that XYP contains many effective compounds that may target COVID-19 related signaling pathways. Moreover, the in vitro experiment confirmed that XYP could inhibit the cytokine storm by regulating genes or proteins related to immune and inflammatory responses.

Single cell RNA-seq analysis with a systems biology approach to recognize important differentially expressed genes in pancreatic ductal adenocarcinoma compared to adjacent non-cancerous samples by targeting pancreatic endothelial cells

Pancreatic ductal adenocarcinoma (PDAC) is a cancer that is usually diagnosed at late stages. This highly aggressive tumor is resistant to most therapeutic approaches, necessitating identification of differentially expressed genes to design new therapies. Herein, we have analyzed single cell RNA-seq data with a systems biology approach to identify important differentially expressed genes in PDAC samples compared to adjacent non-cancerous samples. Our approach revealed 1462 DEmRNAs, including 1389 downregulated DEmRNAs (like PRSS1 and CLPS) and 73 upregulated DEmRNAs (like HSPA1A and SOCS3), 27 DElncRNAs, including 26 downregulated DElncRNAs (like LINC00472 and SNHG7) and 1 upregulated DElncRNA (SNHG5). We also listed a number of dysregulated signaling pathways, abnormally expressed genes and aberrant cellular functions in PDAC which can be used as possible biomarkers and therapeutic targets in this type of cancer.

Construction of a circRNA- lincRNA-lncRNA-miRNA-mRNA ceRNA regulatory network identifies genes and pathways linked to goat fertility

Background: There is growing interest in the genetic improvement of fertility traits in female goats. With high-throughput genotyping, single-cell RNA sequencing (scRNA-seq) is a powerful tool for measuring gene expression profiles. The primary objective was to investigate comparative transcriptome profiling of granulosa cells (GCs) of high- and low-fertility goats, using scRNA-seq. Methods: Thirty samples from Ji'ning Gray goats (n = 15 for high fertility and n = 15 for low fertility) were retrieved from publicly available scRNA-seq data. Functional enrichment analysis and a literature mining approach were applied to explore modules and hub genes related to fertility. Then, interactions between types of RNAs identified were predicted, and the ceRNA regulatory network was constructed by integrating these interactions with other gene regulatory networks (GRNs). Results and discussion: Comparative transcriptomics-related analyses identified 150 differentially expressed genes (DEGs) between high- and low-fertility groups, based on the fold change (≥5 and ≤-5) and false discovery rate (FDR <0.05). Among these genes, 80 were upregulated and 70 were downregulated. In addition, 81 mRNAs, 58 circRNAs, 8 lincRNAs, 19 lncRNAs, and 55 miRNAs were identified by literature mining. Furthermore, we identified 18 hub genes (SMAD1, SMAD2, SMAD3, SMAD4, TIMP1, ERBB2, BMP15, TGFB1, MAPK3, CTNNB1, BMPR2, AMHR2, TGFBR2, BMP4, ESR1, BMPR1B, AR, and TGFB2) involved in goat fertility. Identified biological networks and modules were mainly associated with ovary signature pathways. In addition, KEGG enrichment analysis identified regulating pluripotency of stem cells, cytokine-cytokine receptor interactions, ovarian steroidogenesis, oocyte meiosis, progesterone-mediated oocyte maturation, parathyroid and growth hormone synthesis, cortisol synthesis and secretion, and signaling pathways for prolactin, TGF-beta, Hippo, MAPK, PI3K-Akt, and FoxO. Functional annotation of identified DEGs implicated important biological pathways. These findings provided insights into the genetic basis of fertility in female goats and are an impetus to elucidate molecular ceRNA regulatory networks and functions of DEGs underlying ovarian follicular development.

Identification of potential LncRNAs as papillary thyroid carcinoma biomarkers based on integrated bioinformatics analysis using TCGA and RNA sequencing data

The roles and mechanisms of long non-coding RNAs (lncRNAs) in papillary thyroid cancer (PTC) remain elusive. We obtained RNA sequencing (RNA-seq) data of surgical PTC specimens from patients with thyroid cancer (THCA; n = 20) and identified differentially expressed genes (DEGs) between cancer and cancer-adjacent tissue samples. We identified 2309 DEGs (1372 significantly upregulated and 937 significantly downregulated). We performed Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment, and protein-protein interaction network analyses and screened for hub lncRNAs. Using the same methods, we analyzed the RNA-seq data from THCA dataset in The Cancer Genome Atlas (TCGA) database to identify differentially expressed lncRNAs. We identified 15 key differentially expressed lncRNAs and pathways that were closely related to PTC. Subsequently, by intersecting the differentially expressed lncRNAs with hub lncRNAs, we identified LINC02407 as the key lncRNA. Assessment of the associated clinical characteristics and prognostic correlations revealed a close correlation between LINC02407 expression and N stage of patients. Furthermore, receiver operating characteristic curve analysis showed that LINC02407 could better distinguish between cancerous and cancer-adjacent tissues in THCA patients. In conclusion, our findings suggest that LINC02407 is a potential biomarker for PTC diagnosis and the prediction of lymph node metastasis.

Construction and validation of a novel algorithm based on oncosis-related lncRNAs comprising the immune landscape and prediction of colorectal cancer prognosis

Colorectal cancer (CRC) has high morbidity and mortality, particularly if diagnosed at an advanced stage. Although there have been several studies on CRC, few have investigated the relationship between oncosis and CRC. Thus, the purpose of the present study was to identify oncosis-related long noncoding RNAs (lncRNAs) and to establish a clinical prognostic model. Original data were acquired from The Cancer Genome Atlas database and PubMed. Differentially expressed oncosis-related lncRNAs (DEorlncRNAs) were identified and were subsequently formed into pairs. Next, a series of tests and analyses, including both univariate and multivariate analyses, as well as Lasso and Cox regression analyses, were performed to establish a receiver operating characteristic curve. A cut-off point was subsequently used to divide the samples into groups labelled as high- or low-risk. Thus, a model was established and evaluated in several dimensions. Six pairs of DEorlncRNAs associated with prognosis according to the algorithm were screened out and the CRC cases were divided into high- and low-risk groups. Significant differences between patients in the different risk groups were observed for several traits, including survival outcomes, clinical pathology characteristics, immune cell infiltration status and drug sensitivity. In addition, PCR and flow cytometry were performed to further verify the model. In summary, a new risk model algorithm based on six pairs of DEorlncRNAs in CRC, which does not require specific data regarding the level of gene expression, was established and validated. This algorithm may be used to predict patient prognosis, immune cell infiltration and drug sensitivity.

Long Non-coding RNA HOXA11-AS Facilitates Proliferation of Lung Adenocarcinoma Cells via Targeting the Let-7c-5p/IGF2BP1 Axis

Objective: This study investigates the relationship between the HOXA11-AS/let-7c-5p/IGF2BP1 regulatory axis and lung adenocarcinoma.

Methods: The expression levels of HOXA11-AS, let-7c-5p, and IGF2BP1 were evaluated in LUAD tissue and cell lines. Subcellular fractionation detection assay was adopted to verify the HOXA11-AS distribution in LUAD cells. The interaction relationship between let-7c-5p and HOXA11-AS or IGF2BP1 was validated by dual-luciferase reporter detection. In RNA binding protein immunoprecipitation assay, the binding relationship between HOXA11-AS and let-7c-5p was identified. The cell viability of transfected cells was tested by the Cell Counting Kit-8 assay. The mouse xenograft model was used to identify the effect of HOXA11-AS on tumor growth in vivo.

Results: Upregulation of lncRNA HOXA11-AS was found in LUAD, and suppression of HOXA11-AS could suppress the proliferative ability of LUAD cells. The let-7c-5p was expressed to be downregulated, which played an inhibitory role in LUAD cell proliferation. Let-7c-5p was negatively regulated by HOXA11-AS. HOXA11-AS promoted LUAD cell proliferation, while let-7c-5p had an inverse effect. Besides, IGF2BP1, regulated by let-7c-5p, had a positive relation with HOXA11-AS, while overexpression of IGF2BP1 could suppress the inhibition of silencing HOXA11-AS on LUAD cell proliferation. Experiments on mice confirmed that HOXA11-AS facilitated LUAD cell growth in vivo through regulating the let-7c-5p/IGF2BP1 axis.

Conclusion: HOXA11-AS promoted LUAD cell proliferation by targeting let-7c-5p/IGF2BP1, which could be potential molecular targets for LUAD.

Using BioPAX-Parser (BiP) to enrich lists of genes or proteins with pathway data

BACKGROUND

Pathway enrichment analysis (PEA) is a well-established methodology for interpreting a list of genes and proteins of interest related to a condition under investigation. This paper aims to extend our previous work in which we introduced a preliminary comparative analysis of pathway enrichment analysis tools. We extended the earlier work by providing more case studies, comparing BiP enrichment performance with other well-known PEA software tools.

METHODS

PEA uses pathway information to discover connections between a list of genes and proteins as well as biological mechanisms, helping researchers to overcome the problem of explaining biological entity lists of interest disconnected from the biological context.

RESULTS

We compared the results of BiP with some existing pathway enrichment analysis tools comprising Centrality-based Pathway Enrichment, pathDIP, and Signaling Pathway Impact Analysis, considering three cancer types (colorectal, endometrial, and thyroid), for a total of six datasets (that is, two datasets per cancer type) obtained from the The Cancer Genome Atlas and Gene Expression Omnibus databases. We measured the similarities between the overlap of the enrichment results obtained using each couple of cancer datasets related to the same cancer.

CONCLUSION

As a result, BiP identified some well-known pathways related to the investigated cancer type, validated by the available literature. We also used the Jaccard and meet-min indices to evaluate the stability and the similarity between the enrichment results obtained from each couple of cancer datasets. The obtained results show that BiP provides more stable enrichment results than other tools.

Downregulation of miR-519d-3p is Associated with Poor Outcomes and Facilitates Tumor Progression in Papillary Thyroid Cancer by Regulating FOXQ1

MicroRNA-519d-3p (miR-519d-3p) has emerged as a tumor suppressor in several human cancers. But whether miR-519d-3p is involved in papillary thyroid cancer (PTC) remains elusive. In this study, we investigated the potential relevance of miR-miR-519d-3p in PTC. A retrospective study of 119 PTCs was carried out. The RT-qPCR analysis was used to measure the expression of miR-519d-3p and FOXQ1 in PTC tissues and cells. Chi-square test, Kaplan-Meier curve analysis, and multivariate Cox regression analyses were performed to assess the clinical and prognostic value of miR-519d-3p in PTC. Then cellular experiments were used to explore its biological effects on PTC cells. Finally, the Pearson correlation coefficient, dual-luciferase reporter assay, and rescue experiments were used to analyze the association between miR-519d-3p and FOXQ1. miR-519d-3p was significantly downregulated in PTC tissues and cell lines. The decreased expression of miR-519d-3p was associated with reduced overall survival and progression-free survival of patients. The proliferative, migratory, and invasive abilities of cells were blocked or elevated after upregulation or downregulation of miR-519d-3p, while FOXQ1 reversed these cellular behaviors caused after upregulation or knockdown of miR-519d-3p. In conclusion, miR-519d-3p was downregulated in PTC and associated with OS and PFS of patients. MiR-519d-3p may be a tumor-inhibiting miRNA in PTC, and that miR-519d-3p/FOXQ1 axis mediated PTC tumor progression from cell proliferation, migration, and invasion in PTC cells.

Thymosin β10 mediates the effects of microRNA-184 in the proliferation and epithelial-mesenchymal transition of BCPAP cells

Thyroid cancer is the most common malignant tumor of the endocrine system. It has been reported that thymosin β10 (TMSB10) serves a vital role in tumor invasion and metastasis, and further understanding the role of TMSB10 in thyroid cancer may provide new insights into the development of novel targeted drugs. Bioinformatics analysis suggested that there might exist a regulatory relationship between miR-184 and TMSB10. Therefore, the expression of microRNA (miR)-184 was investigated in the TPC-1 and BCPAP thyroid cancer cell lines and the Nthy-ori 3-1 thyroid epithelial cell line via reverse transcription-quantitative PCR. The effect of miR-184 on BCPAP cell proliferation was evaluated using MTT and colony formation assays. In addition, the expression levels of epithelial-mesenchymal transition (EMT)-associated proteins were examined via western blot analysis and immunofluorescence staining. Furthermore, the targeting association between miR-184 and TMSB10 was verified using a dual-luciferase reporter assay. Notably, miR-184 overexpression attenuated BCPAP cell proliferation, increased the expression level of the epithelial marker E-cadherin, and decreased that of the mesenchymal marker vimentin. These effects were reversed in BCPAP cells following TMSB10 overexpression. The present study revealed that TMSB10 may be considered as a key mediator in promoting papillary thyroid carcinoma (PTC) cell proliferation and EMT, which were negatively regulated by miR-184. Therefore, the findings of the present study may provide a novel potential therapeutic target for attenuating PTC cell proliferation.

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.

Dysregulated LncRNAs Act as Competitive Endogenous RNAs and Are Associated With Cervical Cancer Development in UYGHUR Women

Cervical cancer is one of the most malignant tumors in women, particularly those in rural and remote areas. Its underlying molecular mechanisms, including the functions of non-coding RNA (ncRNAs), require more extensive investigation. In this study, high throughput transcriptome sequencing (RNA-seq) was used to identify differentially expressed lncRNAs and mRNAs in normal, cervical intraepithelial neoplasia and cervical cancer tissues from Uyghur women in western China. Dysregulated lncRNAs were found to extensively participate in cervical cancer development, including viral carcinogenesis, cell cycle and cytokine-cytokine receptor signaling. Two miRNA-host lncRNAs, LINC00925 and MIR155HG, showed elevated expression in cervical cancer samples, but prolonged the survival time of cervical cancer patients. The 2 mature miRNAs of the above 2 lncRNAs, miR-9 and miR-155, also showed similar features in cervical cancer. In addition, we identified 545 lncRNAs with potential functions in regulating these 2 miRNAs as competing endogenous RNAs (ceRNAs). In summary, our study demonstrated the dysregulated lncRNAs/miRNAs, particularly LINC00925/miR-9 and MIR155HG/miR-155, regulate the development of cervical cancer by forming a interaction network with mRNAs, highlighting the importance of elucidating the underlying mechanisms of ncRNAs in cervical cancer development.

Identification of Potential lncRNAs and miRNAs as Diagnostic Biomarkers for Papillary Thyroid Carcinoma Based on Machine Learning

BACKGROUND

Papillary thyroid carcinoma (PTC) accounts for most of the proportion of thyroid cancer (TC). The objective of this study was to identify diagnostic, differentially expressed long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), contributing to understanding the epigenetics mechanism of PTC.

METHODS

The data of lncRNA, miRNA, and mRNA were downloaded from the Cancer Genome Atlas (TCGA) dataset, followed by functional analysis of differentially expressed mRNAs. Optimal diagnostic lncRNA and miRNA biomarkers were identified via random forest. The regulatory network between optimal diagnostic lncRNA and mRNAs and optimal diagnostic miRNA and mRNAs was identified, followed by the construction of ceRNA network of lncRNA-mRNA-miRNA. Expression validation and diagnostic analysis of lncRNAs, miRNAs, and mRNAs were performed. Overexpression of ADD3-AS1 was performed in PTC-UC3 cell lines, and cell proliferation and invasion assay were used for investigating the role of ADD3-AS1 in PTC.

RESULTS

A total of 107 differentially expressed lncRNAs, 81 differentially expressed miRNAs, and 515 differentially expressed mRNAs were identified. 11 lncRNAs and 6 miRNAs were regarded as the optimal diagnostic biomarkers for PTC. The epigenetic modifications via the above diagnostic lncRNAs and miRNAs were identified, including MIR181A2HG-FOXP2-hsa-miR-146b-3p, BLACAT1/ST7-AS1-RPS6KA5-hsa-miR-34a-5p, LBX2-AS1/MIR100HG-CDHR3-hsa-miR-34a-5p, ADD3-AS1-PTPRE-hsa-miR-9-5p, ADD3-AS1-TGFBR1-hsa-miR-214-3p, LINC00506-MMRN1-hsa-miR-4709-3p, and LOC339059-STK32A-hsa-miR-199b-5p. In the functional analysis, MMRN1 and TGFBR1 were involved in cell adhesion and endothelial cell migration, respectively. Overexpression of ADD3-AS1 inhibited cell growth and invasion in PTC cell lines.

CONCLUSION

The identified lncRNAs/miRNAs/mRNA were differentially expressed between normal and cancerous tissues. In addition, identified altered lncRNAs and miRNAs may be potential diagnostic biomarkers for PTC. Additionally, epigenetic modifications via the above lncRNAs and miRNAs may be involved in tumorigenesis of PTC.

Platycodin D (PD) regulates LncRNA-XIST/miR-335 axis to slow down bladder cancer progression in vitro and in vivo

Recently, increasing evidences indicated that Platycodin D (PD) served as an effective anti-tumor drug for cancer treatment in clinic. However, the molecular mechanisms are still unclear. In the present study, we proved that PD regulated LncRNA-XIST/miR-335 axis to hamper the development of bladder cancer in vitro and in vivo. Mechanistically, PD inhibited malignant phenotypes, including cell proliferation, invasion, migration and epithelial-mesenchymal transition (EMT), and promoted cell apoptosis in bladder cancer cells in a time- and dose-dependent manner. In addition, the following experiments validated that PD inhibited LncRNA-XIST expressions, while increased miR-335 expression levels in bladder cancer cells. Next, by conducting the dual-luciferase reporter gene system assay and RNA pull-down assay, we validated that LncRNA-XIST inhibited miR-335 expressions through acting as RNA sponges, and the promoting effects of PD stimulation on miR-335 levels were abrogated by upregulating LncRNA-XIST. Interestingly, both silencing LncRNA-XIST and miR-335 overexpression enhanced the inhibiting effects of PD on the malignant phenotypes in bladder cancer cells. Consistently, the xenograft tumor-bearing mice models were established, and the data indicated that PD slowed down tumor growth and inhibited tumorigenesis in vivo, which were also aggravated by downregulating LncRNA-XIST. In general, analysis of data proved that targeting LncRNA-XIST/miR-335 axis was novel to enhance the anti-tumor effects of PD in bladder cancer in vitro and in vivo, and this study provided alternative therapeutic strategies for bladder cancer treatment in clinic.

Prognostic lncRNA, miRNA, and mRNA Signatures in Papillary Thyroid Carcinoma

The current focus in the treatment of papillary thyroid carcinoma (PTC) is tumor progression. The aim of this study was to build RNA-based classifiers and develop a comprehensive model to provide progression-free interval (PFI) risk prediction for PTC. The RNAseq data, miRNAseq data, and clinical information of PTC were downloaded from The Cancer Genome Atlas database. Based on the differently expressed RNAs, the least absolute shrinkage and selection operator (LASSO) Cox regression model was utilized to build the RNA-based classifiers for PFI of the patients with PTC. A 6-messenger RNA (mRNA)-based classifier, a 5-long non-coding RNA (lncRNA)-based classifier, and a 4-microRNA (miRNA)-based classifier were constructed to predict the PFI. Patients with high risk based on the constructed RNA-based classifiers had worse prognosis in Kaplan–Meier curve analysis with log-rank test. The areas under the curves of the first, third, and fifth years in the training and testing set were 0.83, 0.82, and 0.82 and 0.67, 0.72, and 0.73 for the 6-mRNA-based classifier, respectively; 0.75, 0.84, and 0.85 and 0.71, 0.67, and 0.71 for the 5-lncRNA-based classifier, respectively; and 0.70, 0.77, and 0.79 and 0.74, 0.67, and 0.66 for the 4-miRNA-based classifier, respectively. The prediction capability of the three RNA-based classifiers was superior to the TNM stage system. Furthermore, a nomogram based on the verified independent prognostic factors was established for the prognostic prediction. The C-index and calibration plots indicated good predictive accuracy of the nomogram. In summary, the 6-mRNA-based classifier and 5-lncRNA-based classifier constructed in this study were independent prognostic factors for PTC.

Propofol upregulates miR-320a and reduces HMGB1 by downregulating ANRIL to inhibit PTC cell malignant behaviors

BACKGROUND

Our previous study states that propofol suppresses proliferation and migration of papillary thyroid cancer (PTC) cells by downregulation of lncRNA ANRIL. This study intended to probe the downstream mechanism of ANRIL in PTC with potential microRNAs (miR) and genes.

METHODS

ANRIL expression was detected in normal thyroid epithelial cells (Nthy-ori 3-1) and PTC cells (TPC-1, FTC-133, K1 and BCPAP). ANRIL expression was inhibited in TPC-1 and BCPAP cells to explore the effects of si-ANRIL in PTC malignant behaviors. The gain-and loss-of functions of ANRIL/miR-320a were performed to measure their roles in PTC. Levels of ANRIL, miR-320a, HMGB1, apoptosis- and Wnt/β-catenin and NF-κB pathways-related proteins were measured. Dual-luciferase reporter gene assay and RNA pull-down assay were applied to verify ANRIL/miR-320a/HMGB1 relation. si-ANRIL was transplanted into xenograft tumors in nude mice.

RESULTS

ANRIL was upregulated in TPC-1 and BCPAP cells. miR-320a targeted HMGB1, and ANRIL bound to miR-320a. In TPC-1 and BCPAP cells, si-ANRIL prevented PTC cell malignant behaviors, and inactivated the Wnt/β-catenin and NF-κB pathways; while si-ANRIL + miR-320a inhibition showed opposite trends. Overexpressing miR-320a promoted malignant behaviors of TPC-1 cells. In 6 μg/mL propofol-treated TPC-1 cells, miR-320a inhibition weakened propofol's inhibitory effects on PTC cell growth. After ANRIL inhibition, the volume and weight of xenograft tumors were decreased.

CONCLUSION

Propofol upregulated miR-320a and reduced HMGB1 by downregulating ANRIL and inactivating the Wnt/β-catenin and NF-κB pathways, thus preventing PTC cell malignant behaviors. This study may offer new insights in PTC prevention and treatment.

Long noncoding RNA LINC01278 favors the progression of osteosarcoma via modulating miR-133a-3p/PTHR1 signaling

As one of the most aggressive malignancies, osteosarcoma has high risks of death. Although long noncoding RNAs (lncRNAs) may promote the osteosarcoma progression as verified, the potential molecular mechanism of lncRNAs in osteosarcoma remains unknown. Herein, we analyzed lncRNA microarray of osteosarcoma and selected LINC01278 as the study object. Then, we found that the expression of LINC01278 tested by quantitative reverse-transcription polymerase chain reaction was enhanced in tumor tissues compared with the para-carcinoma tissues and related to clinical stage, distant metastasis in osteosarcoma. In addition, the clinical outcomes were poor in osteosarcoma patients with high LINC01278 level. Moreover, LINC01278 promoted proliferation and restrained apoptosis in osteosarcoma cells. Afterward, mechanistic studies turned out that LINC01278 was a competing endogenous RNA of parathyroid hormone type 1 receptor (PTHR1) in osteosarcoma by sponging miR-133a-3p, which was considered as a tumor inhibitor in osteosarcoma. Furthermore, PTHR1 downregulation restored the impacts of inhibited miR-133a-3p on the processes in osteosarcoma cells. Our findings clarified that the carcinogenic effect of LINC01278 in osteosarcoma was mediated through miR-133a-3p/PTHR1 signaling, creating a novel insight into good targets for the therapy and prognosis of osteosarcoma.

LncRNA LINC00460 promotes the papillary thyroid cancer progression by regulating the LINC00460/miR-485-5p/Raf1 axis

Background

Papillary thyroid cancer (PTC) is the most common malignancy of all thyroid cancers. LncRNA LINC00460 has been proved to play roles in the oncogenesis and progression of various tumors, including papillary thyroid cancer. However, the potential molecular mechanism of LINC00460 in PTC is poorly investigated.

Results

LINC00460 was upregulated in PTC tissues and cells. Raf1 was upregulated in PTC tissues, but miR-485-5p was down-regulated. High LINC00460 expression was associated with poor prognosis. LINC00460 knockdown suppressed proliferation, migration, invation and EMT of PTC cells. Bioinformatics prediction revealed that LINC00460 had binding sites with miR-485-5p, which was validated by luciferase reporter assay. In addition, miR-485-5p was confirmed to directly target Raf1 3′-UTR. Moreover, LINC00460 promoted PTC progression by sponging miR-485-5p to elevate the expression of Raf1. Knockdown of LINC00460 restrained tumor growth in vivo.

Conclusion

LINC00460 induced proliferation, migration, invation and EMT of PTC cells by regulating the LINC00460/miR-485-5p/Raf1 axis, which indicated that LINC00460 may be a potential biomarker and therapeutic target for PTC.

Competitive endogenous RNA (ceRNA) regulation network of lncRNAs, miRNAs, and mRNAs in Wilms tumour

Background

Competitive endogenous RNAs (ceRNAs) have revealed a new mechanism of interaction between RNAs. However, an understanding of the ceRNA regulatory network in Wilms tumour (WT) remains limited.

Methods

The expression profiles of mRNAs, miRNAs and lncRNAs in Wilms tumour samples and normal samples were obtained from the Therapeutically Applicable Research to Generate Effective Treatment (TARGET) database. The EdgeR package was employed to identify differentially expressed lncRNAs, miRNAs and mRNAs. Functional enrichment analyses via the ClusterProfile R package were performed, and the lncRNA–miRNA–mRNA interaction ceRNA network was established in Cytoscape. Subsequently, the correlation between the ceRNA network and overall survival was analysed.

Results

A total of 2037 lncRNAs, 154 miRNAs and 3609 mRNAs were identified as differentially expressed RNAs in Wilms tumour. Of those, 205 lncRNAs, 26 miRNAs and 143 mRNAs were included in the ceRNA regulatory network. The results of Gene Ontology (GO) analysis revealed that the differentially expressed genes (DEGs) were mainly enriched in terms related to response to mechanical stimuli, transcription factor complexes, and transcription factor activity (related to RNA polymerase II proximal promoter sequence-specific DNA binding). The results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the DEGs were mainly enriched in pathways related to the cell cycle. The survival analysis results showed that 16 out of the 205 lncRNAs, 1 out of 26 miRNAs and 5 out of 143 mRNAs were associated with overall survival in Wilms tumour patients (P < 0.05).

Conclusions

CeRNA networks play an important role in Wilms tumour. This finding might provide effective, novel insights for further understanding the mechanisms underlying Wilms tumour.

Heterogenous nature of gene expression patterns in BRAF-like papillary thyroid carcinomas with BRAFV600E

PURPOSE

Papillary thyroid cancers (PTCs) are the most common type of thyroid cancers, in which BRAF^V600E is the most prevalent driver mutation. It is known that BRAF^V600E-positive PTCs are clinically and molecularly heterogenous in terms of aggressiveness and prognosis. The molecular mechanisms of this heterogeneity were evaluated.

METHODS

The publicly available RNA-seq data for 26 classical (c) and 5 follicular variant (fv) PTCs with BRAF^V600E mutation and the BRAF-like expression signature in the BRAF^V600E-RAS score (BRS) and their respective normal adjacent tissues were downloaded, and analyzed for differentially expressed genes (DEGs). The DEGs were then analyzed with the Gene Ontology annotation and the KEGG pathway dataset.

RESULTS

We found four lines of evidence for heterogeneity of cPTCs. First, the cluster dendrogram and principle component analyses could not completely distinguish the cancer tissues from normal tissues. Second, the DEGs identified in each sample were highly diverse from one another. Third, although the DEGs were enriched in many terms containing the word "extracellular" ("extracellular region", "extracellular space", and so on) when analyzed as groups, the degree of this enrichment was variable when analyzed individually. Fourth, there are only a few intersections in the over-/underexpressed genes annotated with the terms containing the word "extracellular" among the samples examined. Essentially same results were obtained with BRAF-like, fvPTCs with BRAF^V600E. Nevertheless, some frequently over-/underexpressed genes were detected, of which LIPH (lipase H) expression was found to be prognostic and its high expression was favorable for PTCs.

CONCLUSION

Groups of BRAF-like, BRAF^V600E-positive cPTCs and fvPTCs that are homogenous in regard to histopathology, driver mutation and BRS were found to be highly heterogenous in terms of gene expression patterns. Yet, among the genes that were annotated with the terms containing the word "extracellular" and frequently over-/underexpressed, LIPH is a favorable prognostic marker for PTCs.