Identification and functional analysis of lncRNAs and mRNAs between tumorigenesis and metastasis in CRC.
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ABSTRACT:
SUBMITTER: Liu H
PROVIDER: S-EPMC8751602 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Osteosarcoma (OS) is the most common pediatric malignant bone tumor, and occurrence of pulmonary metastasis generally causes a rapid and fatal outcome. Here we aimed to provide clues for exploring the mechanism of tumorigenesis and pulmonary metastasis for OS by comprehensive analysis of microRNA (miRNA), long non-coding RNA (lncRNA), and mRNA expression in primary OS and OS pulmonary metastasis. In this study, deep sequencing with samples from primary OS (n = 3), pulmonary metastatic OS (n = 3), and normal controls (n = 3) was conducted and differentially expressed miRNAs (DEmiRNAs), lncRNAs (DElncRNAs), and mRNAs (DEmRNAs) between primary OS and normal controls as well as pulmonary metastatic and primary OS were identified. A total of 65 DEmiRNAs, 233 DElncRNAs, and 1405 DEmRNAs were obtained between primary OS and normal controls; 48 DEmiRNAs, 50 DElncRNAs, and 307 DEmRNAs were obtained between pulmonary metastatic and primary OS. Then, the target DEmRNAs and DElncRNAs regulated by the same DEmiRNAs were searched and the OS tumorigenesis-related and OS pulmonary metastasis-related competing endogenous RNA (ceRNA) networks were constructed, respectively. Based on these ceRNA networks and Venn diagram analysis, we obtained 3 DEmiRNAs, 15 DElncRNAs, and 100 DEmRNAs, and eight target pairs including miR-223-5p/(CLSTN2, AC009951.1, LINC01705, AC090673.1), miR-378b/(ALX4, IGSF3, SULF1), and miR-323b-3p/TGFBR3 were involved in both tumorigenesis and pulmonary metastasis of OS. The TGF-β superfamily co-receptor TGFBR3, which is regulated by miR-323b-3p, acts as a tumor suppressor in OS tumorigenesis and acts as a tumor promoter in pulmonary metastatic OS via activation of the epithelial-mesenchymal transition (EMT) program.In conclusion, the OS transcriptome (miRNA, lncRNA, and mRNA) is dynamically regulated. These analyses might provide new clues to uncover the molecular mechanisms and signaling networks that contribute to OS progression, toward patient-tailored and novel-targeted treatments.
| S-EPMC6039476 | biostudies-literature
Project description:The colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide, but the pathogenesis of CRC remains not well-known. Increasing studies have highlighted the critical roles of long noncoding RNAs (lncRNAs) in tumorigenesis and cancer cells metastasis, however, the expression pattern, biological roles of lncRNAs, and the mechanisms responsible for their function in CRC remain elusive. In this study, we performed a genome-wide comprehensive analysis of lncRNAs profiling and clinical relevance to identify novel lncRNAs for the further study in CRC. RNA sequencing and microarray data obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were annotated and analyzed to find differentially expressed lncRNAs in CRC. Analysis of these datasets revealed that hundreds of lncRNAs expression are dysregulated in CRC tissues when compared with normal tissues. By genomic variation analyses, we identified that some of these lncRNAs dysregulation is associated with the copy number amplification or deletion. Moreover, many lncRNAs expression levels are significantly associated with CRC patients overall and recurrence-free survivals, such as H19, LEF1-AS1, and RP11-296E3.2. Furthermore, we identified one liver metastasis-associated lncRNA termed LUCAT1 in CRC by analyzing lncRNAs expression profiles in the CRC tissues from patients with liver metastasis compared with the CRC tissues without metastasis. Finally, loss-of-function assays determined that knockdown of LUCAT1 could impair CRC cells invasion. Taken together, aberrantly expressed lncRNAs may play critical roles in the development and liver metastasis of CRC, and our findings may provide useful resource for identification of novel biomarkers of CRC.
| S-EPMC5633553 | biostudies-other
Project description:Messenger RNA (mRNA) and long noncoding RNA (lncRNA) are two main subgroups of RNAs participating in transcription regulation. With the development of next generation sequencing, increasing lncRNAs are identified. Many hidden functions of lncRNAs are also revealed. However, the differences in lncRNAs and mRNAs are still unclear. For example, we need to determine whether lncRNAs have stronger tissue specificity than mRNAs and which tissues have more lncRNAs expressed. To investigate such tissue expression difference between mRNAs and lncRNAs, we encoded 9339 lncRNAs and 14,294 mRNAs with 71 expression features, including 69 maximum expression features for 69 types of cells, one feature for the maximum expression in all cells, and one expression specificity feature that was measured as Chao-Shen-corrected Shannon's entropy. With advanced feature selection methods, such as maximum relevance minimum redundancy, incremental feature selection methods, and random forest algorithm, 13 features presented the dissimilarity of lncRNAs and mRNAs. The 11 cell subtype features indicated which cell types of the lncRNAs and mRNAs had the largest expression difference. Such cell subtypes may be the potential cell models for lncRNA identification and function investigation. The expression specificity feature suggested that the cell types to express mRNAs and lncRNAs were different. The maximum expression feature suggested that the maximum expression levels of mRNAs and lncRNAs were different. In addition, the rule learning algorithm, repeated incremental pruning to produce error reduction algorithm, was also employed to produce effective classification rules for classifying lncRNAs and mRNAs, which gave competitive results compared with random forest and could give a clearer picture of different expression patterns between lncRNAs and mRNAs. Results not only revealed the heterogeneous expression pattern of lncRNA and mRNA, but also gave rise to the development of a new tool to identify the potential biological functions of such RNA subgroups.
| S-EPMC6274976 | biostudies-literature
Project description:BACKGROUND This study aimed to identify significantly altered circRNAs/lncRNAs/miRNAs/mRNAs pathways in preeclampsia (PE), investigate their target relationships, and determine their biological functions. MATERIAL AND METHODS Base on RNA-seq technique and the GEO database, expression profiles of circRNAs/lncRNAs/miRNAs/mRNAs related to PE were obtained. Differentially expressed RNAs were determined using the Limma package in R. Gene set enrichment analysis (GSEA) was performed using GSEA software (v. 3.0) and illustrated by ClusterProfiler and ggplot2 package in R. DAVID database (v. 6.8) was implemented to analyze functional categories and the association between genes and the corresponding Gene Ontology (GO) classification. The R visualization package GOPlot was used to get a better visualization of the relationships between genes and the selected functional categories. CeRNA networks which visualized the correlations between circRNA/lncRNA-miRNA-mRNA were constructed using Cytoscape software (v. 3.6.0). Targetscan and miRanda database were used to predict target relationships between circRNA/lncRNA-miRNA-mRNA. QRT-PCR and luciferase reporter assay were used to verify the expression and target relationship of has_circ_0088196/LINC01492/miR-100-5p/LIF (leukemia inhibitory factor). RESULTS The jak-stat signaling pathway was activated and miR-100-5p was downregulated in PE compared with normal tissues both in collected placental tissue samples and GEO database. Upregulated LIF, LINC01492, and hsa_circ_0088196 were negatively correlated with miR-100-5p expression and had a targeted relationship with miR-100-5p. CONCLUSIONS miR-100-5p may suppress PE development, while LIF, LINC01492, and hsa_circ_0088196 may promote it though inhibiting miR-100-5p. The jak-stat signaling pathway was activated and involved in PE progression.
| S-EPMC6413561 | biostudies-literature
Project description:Colorectal cancer is one of the top three causes of cancer-related mortality globally, but no predictive molecular biomarkers are currently available for identifying the disease stage of colorectal cancer patients. Common molecular patterns in the disease, beyond superficial manifestations, can be significant in determining treatment choices. In this study, we used microarray data from colorectal cancer and adjacent normal tissue from the GEO database. These data were categorized into four consensus molecular subtypes based on distinct gene expression signatures. Weighted gene-based protein-protein interaction network analysis was performed for each subtype. NUSAP1, CD44, and COL4A1 modules were found to be statistically significant and present among all the subtypes and displayed though similar but not identical functional enrichment results. Reference of the characteristics of the subtypes to functional modules is necessary since the latter can stay resistant to platform changes and technique noise when compared with other analyses. The CMS4-mesenchymal group, which currently has a poor prognosis, was examined in the study. It is composed mainly of genes involved in immune and stromal expression, with modules focused on ECM dysregulation and chemokine biological processes. Hub genes detection and its' mapping into the protein-protein interaction network can be indicative of possible targets against specific modules. This approach identified subtypes using enrichment-oriented analysis in functional modules. Proper annotation of functional analysis of modules from different subtypes of CRC might be directive for finding extra options for treatment targets and guiding clinical routines.
| S-EPMC6716647 | biostudies-literature
Project description:Competitive endogenous RNA regulation suggests an intricate network of all transcriptional RNAs that have the function of repressing miRNA function and regulating mRNA expression. Today, the specific ceRNA regulatory mechanisms of lncRNA-miRNA-mRNA in patients who have diabetes mellitus (DM) and myocardial infarction (MI) are still unknown. Two data sets, GSE34198 and GSE112690, were rooted in the Gene Expression Omnibus database to search for changes of lncRNA, miRNA, and mRNA in MI patients with diabetes. Weighted gene correlation network analysis (WGCNA) was used to identify the modules related to the development of diabetes in patients with MI. Target genes of miRNAs were predicted using miRWalk, TargetScan, mirDB, RNA22, and miRanda. Then, functional and enrichment analyses were performed to build the lncRNA-miRNA-mRNA interaction network. We built ceRNA regulatory networks with three lncRNAs, two miRNAs, and nine mRNAs. Differentially expressed genes enriched in biological process, including neutrophil activation, refer to immune response and positive system of defense feedback. Besides, there is significant enrichment in molecular function of calcium toll-like receptor binding, icosanoid binding, RAGE receptor binding, and arachidonic acid binding. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis enriched differentially expressed genes (DEGs) in pathways that were well known in MI, indicating inflammation and immune response. Pathways associated with diabetes were also significantly enriched. We confirmed significantly altered lncRNA, miRNA, and mRNA in MI patients with diabetes, which might serve as biomarkers for the progress and development of diabetic cardiovascular diseases. We constructed a ceRNA regulatory network of lncRNA-miRNA-mRNA, which will enable us to understand the novel molecular mechanisms included in the initiation, progression, and interaction between DM and MI, laying the foundation for clinical diagnosis and treatment.
| S-EPMC9112177 | biostudies-literature
Project description:ObjectiveDaweizi (DWZ) is a famous indigenous pig breed in China and characterized by tender meat and high fat percentage. However, the expression profiles and functions of transcripts in DWZ pigs is still in infancy. The object of this study was to depict the transcript profiles in DWZ pigs and screen the potential pathway influence adipogenesis and fat deposition.MethodsHistological analysis of backfat tissue was firstly performed between DWZ and lean-type Yorkshire pigs, and then RNA sequencing technology was utilized to explore miRNAs, lncRNAs and mRNAs profiles in backfat tissue. 18 differentially expressed (DE) transcripts were randomly selected for quantitative real-time polymerase chain reaction (QPCR) to validate the reliability of the sequencing results. Finally, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis were conducted to investigate the potential pathways influence adipocyte differentiation, adipogenesis and lipid metabolism, and a schematic model was further proposed.ResultsA total of 1,625 differentially expressed transcripts were identified in DWZ pigs, including 27 upregulated and 45 downregulated miRNAs, 64 upregulated and 119 downregulated lncRNA, 814 upregulated and 556 downregulated mRNAs. QPCR analysis exhibited strong consistency with the sequencing data. GO and KEGG analysis elucidated that the differentially expressed transcripts were mainly associated with cell growth and death, signal transduction, peroxisome proliferator-activated receptors (PPAR), AMP-activated protein kinase (AMPK), PI3K-Akt, adipocytokine and foxo signaling pathways, all of which are strongly involved in cell development, lipid metabolism and adipogenesis. Further analysis indicated that the BGIR9823_87926/miR-194a-5p/AQP7 network may be effective in the process of adipocyte differentiation or adipogenesis.ConclusionOur study provides comprehensive insights into the regulatory network of backfat deposition and lipid metabolism in pigs from the point of view of miRNAs, lncRNAs and mRNAs.
| S-EPMC9996253 | biostudies-literature
Project description:BackgroundThis study was aimed at mining crucial long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) for the development of polycystic ovary syndrome (PCOS) based on the coexpression and the competitive endogenous RNA (ceRNA) theories and investigating the underlying therapeutic drugs that may function by reversing the expression of lncRNAs, miRNAs, and mRNAs.MethodsRNA (GSE106724, GSE114419, GSE137684, and GSE138518) or miRNA (GSE84376 and GSE138572) expression profile datasets of PCOS patients were downloaded from the Gene Expression Omnibus database. The weighted gene coexpression network analysis (WGCNA) using four RNA datasets was conducted to construct the lncRNA-mRNA coexpression networks, while the common differentially expressed miRNAs in two miRNA datasets and module RNAs were used to establish the ceRNA network. A protein-protein interaction (PPI) network was created to explore the potential interactions between genes. Gene Ontology and KEGG pathway enrichment analyses were performed to explore the functions of genes in networks. Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD) analyses were performed to identify potential therapeutic agents for PCOS.ResultsThree modules (black, magenta, and yellow) were identified to be PCOS-related after WGCNA analysis, in which KLF3-AS1-PLCG2, MAPKAPK5-AS1-MAP3K14, and WWC2-AS2-TXNIP were important coexpression relationship pairs. WWC2-AS2-hsa-miR-382-PLCG2 was a crucial ceRNA loop in the ceRNA network. The PPI network showed that MAP3K14 and TXNIP could interact with hub genes PLK1 (degree = 21) and TLR1 (degree = 18), respectively. These genes were enriched into mitosis (PLK1), immune response (PLCG2 and TLR1), and cell cycle (TXNIP and PLK1) biological processes. Ten small molecule drugs (especially quercetin) were considered to be therapeutical for PCOS.ConclusionOur study may provide a novel insight into the mechanisms and therapy for PCOS.
| S-EPMC7666708 | biostudies-literature
Project description:Intraductal papillary mucinous neoplasm (IPMN) is an intraepithelial precancerous lesion of pancreatic ductal adenocarcinoma (PDAC) that progresses from adenoma to carcinoma, and long noncoding RNAs (lncRNA) might be involved in the tumorigenesis. In this study, we obtained the expression profiles of more than 4000 lncRNAs by probe reannotation of a microarray dataset. As a correlation network-based systems biology method, weighted gene coexpression network analysis (WGCNA) was used to find clusters of highly correlated lncRNAs in the tumorigenesis of IPMN, which covered four stepwise stages from normal main pancreatic duct to invasive IPMN. In the most relevant module (R2 = -0.75 and P = 5E-05), three hub lncRNAs were identified (HAND2-AS1, CTD-2033D15.2, and lncRNA-TFG). HAND2-AS1 and CTD-2033D15.2 were negatively correlated with the tumorigenesis (P in one-way ANOVA test = 1.45E-07 and 1.39E-0.5), while lncRNA-TFG were positively correlated with the tumorigenesis (P = 3.99E-08). The validation set reached consistent results (P = 2.66E-03 in HAND2-AS1, 1.47E-04 in CTD-2033D15.2 and 6.23E-08 in lncRNA-TFG). In functional enrichment analysis, the target genes of microRNAs targeting also these lncRNAs were overlapped in multiple biological processes, pathways and malignant diseases including pancreatic cancer. In survival analysis, patients with higher expression of HAND2-AS1-targeted and CTD-2033D15.2-targeted microRNAs showed a significantly poorer prognosis in PDAC, while high expression of lncRNA-TFG-targeted microRNAs demonstrated an obviously better prognosis (log-rank P < .05). In conclusion, by coexpression network analysis of the lncRNA profiles, three key lncRNAs were identified in association with the tumorigenesis of IPMN, and those lncRNAs might act as early diagnostic biomarkers or therapeutic targets in pancreatic cancer.
| S-EPMC7286472 | biostudies-literature
Project description:Osteoporosis is a complex and multifactorial disease caused by an imbalance between bone formation and resorption. Post‑menopausal women with endogenous estrogen deficiency suffer from systemic bone loss and osteoporosis, and are at high risk of this affecting the jaw bones. MicroRNAs (miRNAs or miRs) have been implicated in the mechanisms of metabolic bone diseases and are expressed at differential levels in alveolar bone following ovariectomy. In the present study, we systematically analyzed the expression profiles of miRNAs, mRNAs and long non‑coding RNA (lncRNAs) in the mandible of ovariectomized (OVX) mice. A complex miRNA‑mRNA‑lncRNA regulatory network was constructed based on differentially expressed RNAs. Two core differentially expressed genes (DEGs), namely, LRP2 binding protein (Lrp2bp) and perilipin 4 (Plin4), significantly influenced the network targeted by differentially expressed miRNAs. Moreover, peroxisome proliferator-activated receptor (PPAR) and insulin signaling pathways were significantly dysregulated in the mandible of OVX mice. Several differentially expressed lncRNAs were also implicated in the two signaling pathways, which influenced mandible development by forming competing endogenous RNA. On the whole, our data indicate that the comprehensive analysis of miRNAs, mRNAs and lncRNAs provides insight into the pathogenesis of estrogen deficiency‑induced osteoporosis in the mandible. This study proposes potential biomarkers for diagnosis or therapeutic targets for osteoporosis which may aid in the development of novel drugs for the treatment of osteoporosis.
| S-EPMC5547976 | biostudies-other