CircRNAs as Potential Blood Biomarkers and Key Elements in Regulatory Networks in Gastric Cancer.
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ABSTRACT:
SUBMITTER: Reis-das-Merces L
PROVIDER: S-EPMC8776217 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Lung cancer is the second most commonly diagnosed carcinoma and is the leading cause of cancer death. Although significant progress has been made towards its understanding and treatment, unraveling the complexities of lung cancer is still hampered by a lack of comprehensive knowledge on the mechanisms underlying the disease. High-throughput and multidimensional genomic data have shed new light on cancer biology. In this study, we developed a network-based approach integrating somatic mutations, the transcriptome, DNA methylation, and protein-DNA interactions to reveal the key regulators in lung adenocarcinoma (LUAD). By combining Bayesian network analysis with tissue-specific transcription factor (TF) and targeted gene interactions, we inferred 15 disease-related core regulatory networks in co-expression gene modules associated with LUAD. Through target gene set enrichment analysis, we identified a set of key TFs, including known cancer genes that potentially regulate the disease networks. These TFs were significantly enriched in multiple cancer-related pathways. Specifically, our results suggest that hepatitis viruses may contribute to lung carcinogenesis, highlighting the need for further investigations into the roles that viruses play in treating lung cancer. Additionally, 13 putative regulatory long non-coding RNAs (lncRNAs), including three that are known to be associated with lung cancer, and nine novel lncRNAs were revealed by our study. These lncRNAs and their target genes exhibited high interaction potentials and demonstrated significant expression correlations between normal lung and LUAD tissues. We further extended our study to include 16 solid-tissue tumor types and determined that the majority of these lncRNAs have putative regulatory roles in multiple cancers, with a few showing lung-cancer specific regulations. Our study provides a comprehensive investigation of transcription factor and lncRNA regulation in the context of LUAD regulatory networks and yields new insights into the regulatory mechanisms underlying LUAD. The novel key regulatory elements discovered by our research offer new targets for rational drug design and accompanying therapeutic strategies.
| S-EPMC5793165 | biostudies-literature
Project description:CircRNAs are novel endogenous non-coding small RNAs involved in the regulation of multiple biological processes. However, little is known regarding circRNAs in ovarian development and maturation of fish. Our study, for the first time, provides the genome-wide overview of the types and relative abundances of circRNAs in tongue sole tissues during three ovarian developmental stages. We detected 6790 circRNAs in the brain, 5712 in the pituitary gland, 4937 in the ovary and 4160 in the liver. Some circRNAs exhibit tissue-specific expression, and qRT-PCR largely confirmed 6 differentially expressed (DE) circRNAs. Gene Ontology and KEGG pathway analyses of DE mRNAs were performed. Some DE circRNA parental genes were closely associated with biological processes in key signalling pathways and may play essential roles in ovarian development and maturation. We found that the selected circRNAs were involved in 10 pathways. RNase R digestion experiment and Sanger sequencing verified that the circRNA had a ring structure and was RNase R resistant. qRT-PCR results largely confirmed differential circRNA expression patterns from the RNA-seq data. These findings indicate that circRNAs are widespread in terms of present in production-related tissues of tongue sole with potentially important regulatory roles in ovarian development and maturation.
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Project description:BackgroundWe aimed to identify the key differentially expressed genes (DEGs) associated with poor prognosis in gastric cancer (GC) and to elucidate the underlying molecular mechanisms in order to provide a therapeutic target for this disease.MethodsThe DEGs common in two datasets, GSE54129 and GSE79973, were screened. GO and KEGG enrichment analyses were then performed for these DEGs using DAVID's tool. STRING and the Cytoscope software were also used to analyze the protein-protein interaction (PPI) networks of the DEGs common between the two datasets.ResultsA total of 164 common DEGs were identified from GSE79973 and GSE54129 datasets, 42 were up-regulated and 122 were down-regulated in GC. KEGG analysis demonstrated that up-regulated DEGs were mainly enriched for focal adhesion, ECM-receptor interaction, PI3K-Akt signaling pathway, protein digestion and absorption, and vascular smooth muscle contraction, while down-regulated DEGs were enriched for chemical carcinogenesis, metabolism of xenobiotics by cytochrome P450, drug metabolism-cytochrome P450, and retinol metabolism (P<0.05). Obtained PPI network for the 164 DEGs via Cytotype software, using MCODE app of Cytotype software we identified 13 hub genes. Twelve of these genes were found to be associated with poor prognosis in GC by survival analysis. Post validation by the GEPIA, Oncomine, and Human Protein Atlas databases, eight genes (COL4A1, COL6A3, COL1A2, COL1A1, THBS2, COL11A1, SPP1, and FN1) were found to be up-regulated in GC tissues and correlated with poor prognosis of GC.ConclusionsCOL4A1, COL6A3, COL1A2, COL1A1, THBS2, COL11A1, SPP1, and FN1 could serve as potential targets for GC diagnosis and prognosis.
| S-EPMC8799033 | biostudies-literature
Project description:Regulatory elements determine the connectivity of molecular networks and mediate a variety of regulatory processes ranging from DNA looping to transcriptional, posttranscriptional, and posttranslational regulation. This review highlights our current understanding of the different types of regulatory elements found in molecular networks with a focus on DNA regulatory elements. We highlight technical advances and current challenges for the mapping of regulatory elements at the genome-wide scale, and describe new computational methods to uncover these elements via reconstructing regulatory networks from large genomic datasets. WIREs Syst Biol Med 2017, 9:e1374. doi: 10.1002/wsbm.1374 For further resources related to this article, please visit the WIREs website.
| S-EPMC5400678 | biostudies-literature
Project description:Gastric cancer is one of the most commonly occurring cancers worldwide. Investigation of long noncoding RNAs is of increasing interest, particularly in relation to their contribution to progression and prognosis of gastric cancers; however, insufficient studies been performed investigating the part of long noncoding RNAs play in gastric cancer carcinogenesis. Patterns of dysregulated long noncoding RNA and messenger RNA between mucosa gastric cancer and adjacent normal tissues were identified using long noncoding RNAs microarray analysis. Quantitative real-time polymerase chain reaction was conducted as a means to verify the obtained data. Both Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were subsequently used to investigate the function of dysregulated long noncoding RNAs and messenger RNAs. Cis and trans action was used to predict the possible targets of long noncoding RNAs, and a coexpression network was created to simulate the complex intergenic interactions. Ninety-five dysregulated long noncoding RNAs and 123 messenger RNAs were identified, and quantitative real-time polymerase chain reaction was used to validate 6 filtered long noncoding RNAs. Gene Ontology and KEGG pathway analyses identified several remarkably biological processes and signaling pathways, including spliceosome, RNA transport, and ubiquitin-mediated proteolysis. The transcriptional factors MYC, GABPA, and E2F1 were found to play a central function in the long noncoding RNAs process, as indicated by the coexpression network. This study revealed the dysregulated long noncoding RNA profiles of mucosal gastric cancer. The results shed light on the biological function of long noncoding RNAs in gastric cancer pathogenesis. This provides useful information for exploring potential early screening biomarkers in gastric cancer.
| S-EPMC7268121 | biostudies-literature
Project description:BackgroundGastric cancer (GC) is one of the most common cancers all over the world, causing high mortality. Gastric cancer screening is one of the effective strategies used to reduce mortality. We expect that good biomarkers can be discovered to diagnose and treat gastric cancer as early as possible.MethodsWe download four gene expression profiling datasets of gastric cancer (GSE118916, GSE54129, GSE103236, GSE112369), which were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between gastric cancer and adjacent normal tissues were detected to explore biomarkers that may play an important role in gastric cancer. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of overlap genes were conducted by the Metascape online database; the protein-protein interaction (PPI) network was constructed by the STRING online database, and we screened the hub genes of the PPI network using the Cytoscape software. The survival curve analysis was conducted by km-plotter and the stage plots of hub genes were created by the GEPIA online database. PCR, WB, and immunohistochemistry were used to verify the expression of hub genes. A neural network model was established to quantify the predictors of gastric cancer.ResultsThe relative expression level of cadherin-3 (CDH3), lymphoid enhancer-binding factor 1 (LEF1), and matrix metallopeptidase 7 (MMP7) were significantly higher in gastric samples, compared with the normal groups (p<0.05). Receiver operator characteristic (ROC) curves were constructed to determine the effect of the three genes' expression on gastric cancer, and the AUC was used to determine the degree of confidence: CDH3 (AUC = 0.800, P<0.05, 95% CI =0.857-0.895), LEF1 (AUC=0.620, P<0.05, 95%CI=0.632-0.714), and MMP7 (AUC=0.914, P<0.05, 95%CI=0.714-0.947). The high-risk warning indicator of gastric cancer contained 8<CDH3<15 and 10<expression of LEF1<16.ConclusionsCDH3, LEF1, and MMP7 can be used as candidate biomarkers to construct a neural network model from hub genes, which may be helpful for the early diagnosis of gastric cancer.
| S-EPMC8416116 | biostudies-literature
Project description:Glaucoma is the leading cause of irreversible blindness globally. Circular RNAs (circRNAs) play vital roles in various biological processes as microRNA (miRNA) sponges and, thus, have been investigated as potential biomarkers and therapeutic targets in numerous human diseases. However, the underlying mechanisms of circRNAs in the pathogenesis of glaucoma remain unclear. Therefore, transcriptome sequencing was performed to identify relevant circRNAs in peripheral blood samples from patients with primary angle-closure glaucoma. Bioinformatics analysis was performed to investigate the potential roles of differentially expressed circRNAs (DEcircRNAs) in the pathogenesis of glaucoma. In total, 481 differentially expressed genes in addition to 345 DEcircRNAs were identified in patients with glaucoma. Based on a public database, targeted gene analysis identified 11 DEcircRNAs that potentially regulate the expression of five genes as miRNA sponges in glaucoma. In addition, quantitative reverse transcription PCR analysis verified that expression of the circRNA hsa-circ-0000745 was positively correlated with the expression of NEAT1 as a potential target gene. These results suggest that DEcircRNAs are involved in a gene expression regulatory network related to immune cell function and progression of glaucoma. Thus, DEcircRNAs in peripheral blood are potential biomarkers and therapeutic targets for glaucoma.
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Project description:Postoperative delirium (POD) is a common postoperative complication in elderly patients and seriously affects postoperative recovery. The exact mechanism of POD is still unclear. Therefore, it is necessary to explore the mechanism of POD in transcriptional regulation. At present, circRNAs have been proven to play an important role in a variety of mental health and cognitive disorders, such as Alzheimer's disease, depression and schizophrenia. To reveal the effect of circRNA on POD, we used microarray to analyze the differential expression profiles of circRNAs in the hippocampus of 12-month-old mice between the tibial fracture and control groups. A total of 1,4236 circRNAs were identified. Compared with the control group, there were 500 circRNAs with increased expression and 187 with decreased expression. The accuracy of the microarray data was further verified by qRT-PCR. Finally, GO enrichment and KEGG pathway analyses indicated that changes in axon orientation, ubiquitin-mediated proteolysis, glutamate synapses, the estrogen signaling pathway, the RAS signaling pathway and other systems may be important potential pathological mechanisms in the progression of POD. In particular, we found that the HOMER1 gene and its transcript mmu_circRNA_26701 are specifically expressed in the glutamate synapse, which may provide new clues and intervention targets for the progression of this refractory disease.
| S-EPMC9047966 | biostudies-literature
Project description:BackgroundThe expression of circular RNA (circRNA) may affect tumor progression. However, there have been no systemic meta-analysis for cancer diagnosis by using circRNAs in clinical till now. Herein, we aimed to collect and examined all the evidence on the potential role of circRNA as novel biomarker in human cancers.MethodsA comprehensive search strategy was used to search relevant literatures in the databases of PubMed, Embase, and the Web of Science from 2015 to August 2017. The correlation between circRNA expression and the diagnostic accuracy of tumor markers was analyzed. The methodological quality of each study was assessed by quality assessment for the diagnostic accuracies of the eligible studies (QUADAS-2). Statistical analysis was performed by applying the STATA (version 12.0) software.ResultsThe present meta-analysis included 1752 patients with circRNA expression data of tumor and paired adjacent non-tumorous tissues from 17 publications (19 studies). The pooled sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic OR (DOR) with their 95% confidential intervals (95%CIs), and AUC values were 0.72 (0.67-0.76), 0.74 (0.69-0.78), 2.80 (2.40-3.10), 0.38 (0.33-0.44), 7.00 (6.00-9.00), and 0.79, respectively. Subgroup analyses showed that the expression of circRNA in tissues of hepatocellular carcinoma (HCC) group was more prone to be detected than other tumor types, with a high values of the specificity, DOR, and AUC.ConclusionscircRNAs might be suitable as diagnostic biomarkers for tumors, especially in HCC diagnosis. Further prospective studies on the diagnostic value of circRNAs from the different tumors are needed in the future.
| S-EPMC5859638 | biostudies-literature
Project description:Cytosine methylation (5mC) of CpG is the major epigenetic modification of mammalian DNA, playing essential roles during development and cancer. Although DNA methylation is generally associated with transcriptional repression, its role in gene regulation during cell fate decisions remains poorly understood. DNA demethylation can be either passive or active when initiated by TET dioxygenases. During active demethylation, transcription factors (TFs) recruit TET enzymes (TET1, 2, and 3) to specific gene regulatory regions to first catalyze the oxidation of 5mC to 5-hydroxymethylcytosine (5hmC) and subsequently to higher oxidized cytosine derivatives. Only TET2 is frequently mutated in the hematopoietic system from the three TET family members. These mutations initially lead to the hematopoietic stem cells (HSCs) compartment expansion, eventually evolving to give rise to a wide range of blood malignancies. This review focuses on recent advances in characterizing the main TET2-mediated molecular mechanisms that activate aberrant transcriptional programs in blood cancer onset and development. In addition, we discuss some of the key outstanding questions in the field.
| S-EPMC8834528 | biostudies-literature