scholarly journals A Novel LncRNA-miRNA-mRNA Triple Network Identifies LncRNA RP11-363E7.4 as An Important Regulator of miRNA and Gene Expression in Gastric Cancer

2018 ◽  
Vol 47 (3) ◽  
pp. 1025-1041 ◽  
Author(s):  
Pengcheng Wang ◽  
Jing Li ◽  
Wei Zhao ◽  
Chunyang Shang ◽  
Xian Jiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Regulatory Networks ◽  
Functional Enrichment ◽  
Microrna Target ◽  
Kaplan Meier ◽  
Important Regulator ◽  
Non Coding Rnas ◽  
Gc Gene ◽  
Insight Into

Background/Aims: Recent evidence has shown that some long non-coding RNAs (lncRNAs) play important roles in various biological processes. However, the regulatory mechanism of lncRNA in gastric cancer (GC) remains unclear. Methods: We reannotated the GC gene expression profile into a lncRNA-mRNA biphasic profile and integrated the microRNA target data to construct a global GC triple network. A further clustering and random walk with restart analyses was performed on the triple network from the level of topology analyses. Quantitative real-time PCR was used to determine expression of lncRNA RP11-363E7.4. Kaplan-Meier analyses was performed to evaluate the prognostic value of lncRNA RP11-363E7.4. Results: We constructed a gastric cancer lncRNA-miRNA-mRNA network (GCLMN) including six lncRNAs, 332 mRNAs, and 3,707 edges. For the shared lncRNA RP11-363E7.4, the interacting gene and microRNA functional enrichment studies implied that lncRNA RP11-363E7.4 might function as a new regulator in GC. The expression of lncRNA RP11-363E7.4 was downregulated compared with that of paracarcinoma tissues in five GC samples. High expression of lncRNA RP11-363E7.4 was found to be correlated to better overall survival (OS) for GC patients. Conclusions: This study focused on GC lncRNA-miRNA-mRNA regulatory networks, and found that lncRNA RP11-363E7.4 was a new GC risk lncRNA, which might provide novel insight into a better understanding of the pathogenesis of GC.

scholarly journals CircRNAs as Potential Blood Biomarkers and Key Elements in Regulatory Networks in Gastric Cancer

2022 ◽  
Vol 23 (2) ◽  
pp. 650
Author(s):  
Laís Reis-das-Mercês ◽  
Tatiana Vinasco-Sandoval ◽  
Rafael Pompeu ◽  
Aline Cruz Ramos ◽  
Ana K. M. Anaissi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Minimally Invasive ◽  
Regulatory Networks ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Circular Rnas ◽  
Rna Seq ◽  
Tissue Samples ◽  
Molecular Alterations ◽  
Non Coding Rnas

Gastric cancer (GC) is the fifth most common type of cancer and the third leading cause of cancer death in the world. It is a disease that encompasses a variety of molecular alterations, including in non-coding RNAs such as circular RNAs (circRNAs). In the present study, we investigated hsa_circ_0000211, hsa_circ_0000284, hsa_circ_0000524, hsa_circ_0001136 and hsa_circ_0004771 expression profiles using RT-qPCR in 71 gastric tissue samples from GC patients (tumor and tumor-adjacent samples) and volunteers without cancer. In order to investigate the suitability of circRNAs as minimally invasive biomarkers, we also evaluated their expression profile through RT-qPCR in peripheral blood samples from patients with and without GC (n = 41). We also investigated the predicted interactions between circRNA-miRNA-mRNA and circRNA-RBP using the KEGG and Reactome databases. Overall, our results showed that hsa_circ_0000211, hsa_circ_0000284 and hsa_circ_0004771 presented equivalent expression profiles when analyzed by different methods (RNA-Seq and RT-qPCR) and different types of samples (tissue and blood). Further, functional enrichment results identified important signaling pathways related to GC. Thus, our data support the consideration of circRNAs as new, minimally invasive biomarkers capable of aiding in the diagnosis of GC and with great potential to be applied in clinical practice.

scholarly journals Integrative Analysis of Genomics and Transcriptome Data to Identify Regulation Networks in Female Osteoporosis

2020 ◽  
Vol 11 ◽  
Author(s):  
Xianzuo Zhang ◽  
Kun Chen ◽  
Xiaoxuan Chen ◽  
Nikolaos Kourkoumelis ◽  
Guoyuan Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Muscle Disease ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Mineral Density ◽  
Hub Genes ◽  
Pathway Enrichment ◽  
Gene Modules ◽  
Non Coding Rnas

Background: Osteoporosis is a highly heritable skeletal muscle disease. However, the genetic mechanisms mediating the pathogenesis of osteoporosis remain unclear. Accordingly, in this study, we aimed to clarify the transcriptional regulation and heritability underlying the onset of osteoporosis.Methods: Transcriptome gene expression data were obtained from the Gene Expression Omnibus database. Microarray data from peripheral blood monocytes of 73 Caucasian women with high and low bone mineral density (BMD) were analyzed. Differentially expressed messenger RNAs (mRNAs) and long non-coding RNAs (lncRNAs) were identified. Differences in BMD were then attributed to several gene modules using weighted gene co-expression network analysis (WGCNA). LncRNA/mRNA regulatory networks were constructed based on the WGCNA and subjected to functional enrichment analysis.Results: In total, 3,355 mRNAs and 999 lncRNAs were identified as differentially expressed genes between patients with high and low BMD. The WGCNA yielded three gene modules, including 26 lncRNAs and 55 mRNAs as hub genes in the blue module, 36 lncRNAs and 31 mRNAs as hub genes in the turquoise module, and 56 mRNAs and 30 lncRNAs as hub genes in the brown module. JUN and ACSL5 were subsequently identified in the modular gene network. After functional pathway enrichment, 40 lncRNAs and 16 mRNAs were found to be related to differences in BMD. All three modules were enriched in metabolic pathways. Finally, mRNA/lncRNA/pathway networks were constructed using the identified regulatory networks of lncRNAs/mRNAs and pathway enrichment relationships.Conclusion: The mRNAs and lncRNAs identified in this WGCNA could be novel clinical targets in the diagnosis and management of osteoporosis. Our findings may help elucidate the complex interactions between transcripts and non-coding RNAs and provide novel perspectives on the regulatory mechanisms of osteoporosis.

scholarly journals Nomogram Models Based on Gene Expression in Prediction of Breast Cancer Bone Metastasis

2021 ◽  
Author(s):  
Teng-di Fan ◽  
Di-kai Bei ◽  
Song-wei Li
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Bone Metastasis ◽  
Gene Signature ◽  
Functional Enrichment ◽  
Training Set ◽  
Hub Genes ◽  
Kaplan Meier ◽  
Patient Prognosis ◽  
Kaplan Meier Plotter

Abstract Objective: To design a weighted co-expression network and build gene expression signature-based nomogram (GESBN) models for predicting the likelihood of bone metastasis in breast cancer (BC) patients. Methods: Dataset GSE124647 was used as a training set, and GSE14020 was taken as a validation set. In the training cohort, limma package in R was adopted to obtain differentially expressed genes (DEGs) between BC non-bone metastasis and bone metastasis patients, which were used for functional enrichment analysis. After weighted co-expression network analysis (WGCNA), univariate Cox regression and Kaplan-Meier plotter analyses were performed to screen potential prognosis-related genes. Then, GESBN models were constructed and evaluated. Further, the expression levels of genes in the models were explored in the training set, which was validated in GSE14020. Finally, the prognostic value of hub genes in BC was explored. Results: A total of 1858 DEGs were obtained. WGCNA result showed that the blue module was most significantly related to bone metastasis and prognosis. After survival analyses, GAJ1, SLC24A3, ITGBL1, and SLC44A1 were subjected to construct a GESBN model for overall survival. While GJA1, IGFBP6, MDFI, ITGFBI, ANXA2, and SLC24A3 were subjected to build a GESBN model for progression-free survival. Kaplan-Meier plotter and receiver operating characteristic analyses presented the reliable prediction ability of the models. Besides, GJA1, IGFBP6, ITGBL1, SLC44A1, and TGFBI expressions were significantly different between the two groups in GSE124647 and GSE14020. The hub genes had a significant impact on patient prognosis. Conclusion: Both the four-gene signature and six-gene signature could accurately predict patient prognosis, which may provide novel treatment insights for BC bone metastasis.

scholarly journals Demethylation alters transcriptome profiling of buds and leaves in ‘Kyoho’ grape

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Haoran Jia ◽  
Zibo Zhang ◽  
Ehsan Sadeghnezhad ◽  
Qianqian Pang ◽  
Shangyun Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Epigenetic Modification ◽  
Deep Understanding ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Glutathione Metabolism ◽  
Endogenous Factors

Abstract Background Grape buds and leaves are directly associated with the physiology and metabolic activities of the plant, which is monitored by epigenetic modifications induced by environment and endogenous factors. Methylation is one of the epigenetic regulators that could be involved in DNA levels and affect gene expression in response to stimuli. Therefore, changes of gene expression profile in leaves and bud through inhibitors of DNA methylation provide a deep understanding of epigenetic effects in regulatory networks. Results In this study, we carried out a transcriptome analysis of ‘Kyoho’ buds and leaves under 5-azacytidine (5-azaC) exposure and screened a large number of differentially expressed genes (DEGs). GO and KEGG annotations showed that they are mainly involved in photosynthesis, flavonoid synthesis, glutathione metabolism, and other metabolic processes. Functional enrichment analysis also provided a holistic perspective on the transcriptome profile when 5-azaC bound to methyltransferase and induced demethylation. Enrichment analysis of transcription factors (TFs) also showed that the MYB, C2H2, and bHLH families are involved in the regulation of responsive genes under epigenetic changes. Furthermore, hormone-related genes have also undergone significant changes, especially gibberellin (GA) and abscisic acid (ABA)-related genes that responded to bud germination. We also used protein-protein interaction network to determine hub proteins in response to demethylation. Conclusions These findings provide new insights into the establishment of molecular regulatory networks according to how methylation as an epigenetic modification alters transcriptome patterns in bud and leaves of grape.

Label-free proteomic analysis reveals large dynamic changes to the cellular proteome upon expression of the miRNA-23a-27a-24-2 microRNA cluster

2020 ◽  
Vol 98 (1) ◽  
pp. 61-69 ◽  
Author(s):  
Ramanaguru S. Piragasam ◽  
S. Faraz Hussain ◽  
Steven G. Chaulk ◽  
Zaeem A. Siddiqi ◽  
Richard P. Fahlman
Keyword(s):  
Gene Expression ◽  
Proteomic Analysis ◽  
Small Rnas ◽  
Regulatory Networks ◽  
Mirna Cluster ◽  
Label Free ◽  
Dynamic Changes ◽  
Mrna Targets ◽  
Order Of Magnitude ◽  
Non Coding Rnas

In deciphering the regulatory networks of gene expression controlled by the small non-coding RNAs known as microRNAs (miRNAs), a major challenge has been with the identification of the true mRNA targets by these RNAs within the context of the enormous numbers of predicted targets for each of these small RNAs. To facilitate the system-wide identification of miRNA targets, a variety of system wide methods, such as proteomics, have been implemented. Here we describe the utilization of quantitative label-free proteomics and bioinformatics to identify the most significant changes to the proteome upon expression of the miR-23a-27a-24-2 miRNA cluster. In light of recent work leading to the hypothesis that only the most pronounced regulatory events by miRNAs may be physiologically relevant, our data reveal that label-free analysis circumvents the limitations of proteomic labeling techniques that limit the maximum differences that can be quantified. The result of our analysis identifies a series of novel candidate targets that are reduced in abundance by more than an order of magnitude upon the expression of the miR-23a-27a-24-2 cluster.

scholarly journals Integrative Omic Profiling Reveals Unique Hypoxia Induced Signatures in Gastric Cancer Associated Myofibroblasts

Cancers ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 263
Author(s):  
Hanna Najgebauer ◽  
Andrew Jarnuczak ◽  
Andrea Varro ◽  
Christopher Sanderson
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Normal Tissue ◽  
Tumour Progression ◽  
Cancer Cell Migration ◽  
Hypoxic Conditions ◽  
Mechanistic Insight ◽  
Functional Characterisation ◽  
Induced Changes ◽  
Insight Into

Although hypoxia is known to contribute to several aspects of tumour progression, relatively little is known about the effects of hypoxia on cancer-associated myofibroblasts (CAMs), or the consequences that conditional changes in CAM function may have on tumour development and metastasis. To investigate this issue in the context of gastric cancer, a comparative multiomic analysis was performed on populations of patient-derived myofibroblasts, cultured under normoxic or hypoxic conditions. Data from this study reveal a novel set of CAM-specific hypoxia-induced changes in gene expression and secreted proteins. Significantly, these signatures are not observed in either patient matched adjacent tissue myofibroblasts (ATMs) or non-cancer associated normal tissue myofibroblasts (NTMs). Functional characterisation of different myofibroblast populations shows that hypoxia-induced changes in gene expression not only enhance the ability of CAMs to induce cancer cell migration, but also confer pro-tumorigenic (CAM-like) properties in NTMs. This study provides the first global mechanistic insight into the molecular changes that contribute to hypoxia-induced pro-tumorigenic changes in gastric stromal myofibroblasts.

scholarly journals The involvement of human endogenous retroviruses K (HERV-K) in aging processes via induction of inflammation

2019 ◽  
Author(s):  
Chingis Ochirov
Keyword(s):  
Gene Expression ◽  
Regulation Of Gene Expression ◽  
Endogenous Retroviruses ◽  
Human Organism ◽  
Human Endogenous Retroviruses ◽  
Regulate Gene Expression ◽  
Spontaneous Transition ◽  
Developmental Program ◽  
Non Coding Rnas ◽  
Insight Into

This detailed analysis provides an insight into aging processes in the human organism. The developmental program that controls the regulation of gene expression through epigenetic modifications leads to cellular senescence in the latter life. This epigenetic development system uses endogenous retroviruses and other retrotransposons as control elements that regulate gene expression through non-coding RNAs. Interaction with sex hormones causes activation of human endogenous retroviruses K (HERV-K) inducing a prolonged innate immune response and therefore chronic inflammation leading to complex changes in the signaling pathways inside the cell and thus contributes to age-associated phenotype in the form of tissue deterioration and may cause a spontaneous transition of tissues to cancer state.

scholarly journals Discovery and Validation of Novel Methylation Markers in Helicobacter pylori-Associated Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Huan Wang ◽  
Nian-Shuang Li ◽  
Cong He ◽  
Chuan Xie ◽  
Yin Zhu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Dna Methylation ◽  
Helicobacter Pylori ◽  
Gene Expression Data ◽  
Functional Enrichment ◽  
Expression Data ◽  
H Pylori

Previous studies have shown that abnormal methylation is an early key event in the pathogenesis of most human cancers, contributing to the development of tumors. However, little attention has been given to the potential of DNA methylation patterns as markers for Helicobacter pylori- (H. pylori-) associated gastric cancer (GC). In this study, an integrated analysis of DNA methylation and gene expression was conducted to identify some potential key epigenetic markers in H. pylori-associated GC. DNA methylation data of 28 H. pylori-positive and 168 H. pylori-negative GC samples were compared and analyzed. We also analyzed the gene expression data of 18 H. pylori-positive and 145 H. pylori-negative GC cases. Finally, the results were verified by in vitro and in vivo experiments. A total of 5609 differentially methylated regions associated with 2454 differentially methylated genes were identified. A total of 228 differentially expressed genes were identified from the gene expression data of H. pylori-positive and H. pylori-negative GC cases. The screened genes were analyzed for functional enrichment. Subsequently, we obtained 28 genes regulated by methylation through a Venn diagram, and we identified five genes (GSTO2, HUS1, INTS1, TMEM184A, and TMEM190) downregulated by hypermethylation. HUS1, GSTO2, and TMEM190 were expressed at lower levels in GC than in adjacent samples ( P < 0.05 ). Moreover, H. pylori infection decreased HUS1, GSTO2, and TMEM190 expression in vitro and in vivo. Our study identified HUS1, GSTO2, and TMEM190 as novel methylation markers for H. pylori-associated GC.

scholarly journals Highly Divergent Neuropeptide - non-coding RNA regulatory networks underpin variant host-finding behaviours in Steinernema species infective juveniles

2020 ◽  
Author(s):  
Neil D. Warnock ◽  
Erwan Atcheson ◽  
Ciaran McCoy ◽  
Johnathan J. Dalzell
Keyword(s):  
Gene Expression ◽  
Small Rna ◽  
Regulatory Networks ◽  
Host Finding ◽  
Protein Coding ◽  
Rna Analysis ◽  
New Family ◽  
Non Coding Rna ◽  
Non Coding Rnas ◽  
Shared Gene

AbstractWe conducted a transcriptomic and small RNA analysis of infective juveniles (IJs) from three behaviourally distinct Steinernema species. Substantial variation was found in the expression of shared gene orthologues, revealing gene expression signatures that correlate with behavioural states. 97% of predicted microRNAs are novel to each species. Surprisingly, our data provide evidence that isoform variation can effectively convert protein-coding neuropeptide genes into non-coding transcripts, which may represent a new family of long non-coding RNAs. These data suggest that differences in neuropeptide gene expression, isoform variation, and small RNA interactions could contribute to behavioural differences within the Steinernema genus.

scholarly journals Identification of Key Genes and miRNA-mRNA Regulatory Pathways in Bronchopulmonary Dysplasia in Preterm Infants by Bioinformatics Methods

2020 ◽  
Author(s):  
Tong Sun ◽  
Haiyang Yu ◽  
Jianhua Fu
Keyword(s):  
Gene Expression ◽  
Preterm Infants ◽  
Bronchopulmonary Dysplasia ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Regulatory Pathways ◽  
Ppi Networks ◽  
Key Genes

Abstract Background: Bronchopulmonary dysplasia (BPD) remains a severe respiratory complication of preterm infants in neonatal intensive care units (NICUs). However, its pathogenesis has been unclear. Bioinformatics analysis, which can help us explore genetic alternations and recognize latent diagnostic biomarkers, has recently promoted the comprehension of the molecular mechanisms underlying disease occurrence and development. Methods: In this study, we identified key genes and miRNA-mRNA regulatory networks in BPD in preterm infants to elucidate the pathogenesis of BPD. We downloaded and analyzed miRNA and gene expression microarray datasets from the Gene Expression Omnibus database (GEO). Differentially expressed miRNA (DEMs) and differentially expressed genes (DEGs) were obtained through NetworkAnalyst. We performed pathway enrichment analysis using the Database for Annotation, Visualization and Integrated Discovery program (DAVID), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Then we used the STRING to establish protein–protein interactions and the Cytoscape tool to establish miRNA–mRNA regulatory networks. Results: We identified 19 significant DEMs and 140 and 33 significantly upregulated and downregulated DEGs, respectively. Functional enrichment analysis indicated that significant DEGs were associated with the antigen processing and presentation, and B-cell receptor signaling pathways in BPD. Key DEGs, such as CD19, CD79B, MS4A1, and FCGR2B were selected as hub genes in PPI networks. Conclusions: In this study, we screened out 19 DEMs that might play important roles in the regulatory networks of BPD. Higher expression of miRNAs such as miR-15b-5p, hsa-miR-32-5p, miR-3613-3p, and miR-33a-5p and lower expression of miRNAs such as miR-3960, miR-425-5p, and miR-3202 might be correlated with the process of BPD.

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