scholarly journals Circulating MicroRNAs in the Second Trimester From Pregnant Women Who Subsequently Developed Preeclampsia: Potential Candidates as Predictive Biomarkers and Pathway Analysis for Target Genes of miR-204-5p

2021 ◽  
Vol 12 ◽  
Author(s):  
Marcelo R. Luizon ◽  
Izabela M. C. A. Conceição ◽  
Sarah Viana-Mattioli ◽  
Mayara Caldeira-Dias ◽  
Ricardo C. Cavalli ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Early Development ◽  
Target Genes ◽  
Clinical Symptoms ◽  
Expression Profiles ◽  
Predictive Biomarkers ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Second Trimester ◽  
Circulating Mirnas

MicroRNAs (miRNAs) play an important role in the pathophysiology of preeclampsia (PE). However, the expression of circulating miRNAs was not analyzed in the second trimester of pregnancy, a period of major relevance to identify predictive biomarkers for PE. Therefore, we examined the expression profiles of 84 circulating miRNAs using a PCR array in plasma collected between 20 and 25 weeks of gestation from pregnant women, who subsequently developed PE and those who remained healthy during pregnancy, randomly selected from a prospective cohort. Overall, 23 miRNAs had a fold change > 2.0 and were considered to be upregulated in plasma from pregnant women who subsequently developed PE, even before the onset of clinical symptoms of PE. However, only miR-204-5p was statistically significant (P = 0.0082). Experimentally validated interactions for the target genes of miR-204-5p extracted from miRTarBase were used in the gene set functional enrichment analysis to identify Reactome pathways. The network connecting the 37 target genes for miR-204-5p revealed pathways of known pathophysiological relevance during the early development of PE and included key genes related to PE, such as BDNF, MMP-9, MALAT1, TGFBR2, and SIRT1. We further depicted downstream targets of SIRT1 that are related to the vascular endothelial function or implicated in the pathophysiology of PE, namely, FOXO1, NFκB, HIF-1α, NOS3, and PPAR-γ. Our novel findings provide for circulating miRNAs upregulated in the second trimester on plasma from pregnant women who subsequently developed PE that is potentially related to the early development of PE, which may guide further studies focused on the validation of potential predictive biomarkers in PE.

scholarly journals Identification of Tumorigenic and Prognostic Biomarkers in Colorectal Cancer Based on microRNA Expression Profiles

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Yuntao Shi ◽  
Yingying Zhuang ◽  
Jialing Zhang ◽  
Mengxue Chen ◽  
Shangnong Wu
Keyword(s):  
Target Genes ◽  
Cox Regression ◽  
Expression Profiles ◽  
Survival Rates ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Risk Groups ◽  
Normal Mucosa ◽  
Microrna Expression ◽  
Functional Enrichment

Objective. Although noncoding RNAs, especially the microRNAs, have been found to play key roles in CRC development in intestinal tissue, the specific mechanism of these microRNAs has not been fully understood. Methods. GEO and TCGA database were used to explore the microRNA expression profiles of normal mucosa, adenoma, and carcinoma. And the differential expression genes were selected. Computationally, we built the SVM model and multivariable Cox regression model to evaluate the performance of tumorigenic microRNAs in discriminating the adenomas from normal tissues and risk prediction. Results. In this study, we identified 20 miRNA biomarkers dysregulated in the colon adenomas. The functional enrichment analysis showed that MAPK activity and MAPK cascade were highly enriched by these tumorigenic microRNAs. We also investigated the target genes of the tumorigenic microRNAs. Eleven genes, including PIGF, TPI1, KLF4, RARS, PCBP2, EIF5A, HK2, RAVER2, HMGN1, MAPK6, and NDUFA2, were identified to be frequently targeted by the tumorigenic microRNAs. The high AUC value and distinct overall survival rates between the two risk groups suggested that these tumorigenic microRNAs had the potential of diagnostic and prognostic value in CRC. Conclusions. The present study revealed possible mechanisms and pathways that may contribute to tumorigenesis of CRC, which could not only be used as CRC early detection biomarkers, but also be useful for tumorigenesis mechanism studies.

scholarly journals miRNA Mediated Noise Making of 3′UTR Mutations in Cancer

Genes ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 545 ◽  
Author(s):  
Wei Wu ◽  
Lingxiang Wu ◽  
Mengyan Zhu ◽  
Ziyu Wang ◽  
Min Wu ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Target Genes ◽  
Expression Profiles ◽  
Tumor Development ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Messenger Rnas ◽  
Cellular Functions ◽  
Mrna Binding

Somatic mutations in 3′-untranslated regions (3′UTR) do not alter amino acids and are considered to be silent in cancers. We found that such mutations can promote tumor progression by altering microRNA (miRNA) targeting efficiency and consequently affecting miRNA–mRNA interactions. We identified 67,159 somatic mutations located in the 3′UTRs of messenger RNAs (mRNAs) which can alter miRNA–mRNA interactions (functional somatic mutations, funcMutations), and 69.3% of these funcMutations (the degree of energy change > 12 kcal/mol) were identified to significantly promote loss of miRNA-mRNA binding. By integrating mRNA expression profiles of 21 cancer types, we found that the expression of target genes was positively correlated with the loss of absolute affinity level and negatively correlated with the gain of absolute affinity level. Functional enrichment analysis revealed that genes carrying funcMutations were significantly enriched in the MAPK and WNT signaling pathways, and analysis of regulatory modules identified eighteen miRNA modules involved with similar cellular functions. Our findings elucidate a complex relationship between miRNA, mRNA, and mutations, and suggest that 3′UTR mutations may play an important role in tumor development.

scholarly journals Identification and characterization of Piwi-interacting RNAs in human placentas of preeclampsia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie He ◽  
Miaomiao Chen ◽  
Jiacheng Xu ◽  
Jie Fang ◽  
Zheng Liu ◽  
...  
Keyword(s):  
Expression Pattern ◽  
Human Placenta ◽  
Target Genes ◽  
Expression Profiles ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Small Rna Sequencing ◽  
Common Disease

AbstractPreeclampsia is a common disease of pregnancy that poses a serious threat to the safety of pregnant women and the fetus; however, the etiology of preeclampsia is inconclusive. Piwi-interacting RNAs (piRNAs) are novel non-coding RNAs that are present at high levels in germ cells and are associated with spermatogenesis. Emerging evidence demonstrated that piRNA is expressed in a variety of human tissues and is closely associated with tumorigenesis. However, changes in the piRNA expression profile in the placenta have not been investigated. In this study, we used small RNA sequencing to evaluate the differences in piRNA expression profiles between preeclampsia and control patients and potential functions. Differential expression analysis found 41 up-regulated and 36 down-regulated piRNAs in preeclamptic samples. In addition, the functional enrichment analysis of piRNAs target genes indicated that they were related to the extracellular matrix (ECM) formation and tissue-specific. Finally, we examined the expression pattern of the PIWL family proteins in the placenta, and PIWL3 and PIWIL4 were the primary subtypes in the human placenta. In summary, this study first summarized the changes in the expression pattern of piRNA in preeclampsia and provided new clues for the regulatory role of piRNA in the human placenta.

scholarly journals Understanding the Modus Operandi of MicroRNA Regulatory Clusters

Cells ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1103 ◽  
Author(s):  
Arthur C. Oliveira ◽  
Luiz A. Bovolenta ◽  
Lucas Alves ◽  
Lucas Figueiredo ◽  
Amanda O. Ribeiro ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Modus Operandi ◽  
Wide Range

MicroRNAs (miRNAs) are non-coding RNAs that regulate a wide range of biological pathways by post-transcriptionally modulating gene expression levels. Given that even a single miRNA may simultaneously control several genes enrolled in multiple biological functions, one would expect that these tiny RNAs have the ability to properly sort among distinctive cellular processes to drive protein production. To test this hypothesis, we scrutinized previously published microarray datasets and clustered protein-coding gene expression profiles according to the intensity of fold-change levels caused by the exogenous transfection of 10 miRNAs (miR-1, miR-7, miR-9, miR-124, miR-128a, miR-132, miR-133a, miR-142, miR-148b, miR-181a) in a human cell line. Through an in silico functional enrichment analysis, we discovered non-randomic regulatory patterns, proper of each cluster identified. We demonstrated that miRNAs are capable of equivalently modulate the expression signatures of target genes in regulatory clusters according to the biological function they are assigned to. Moreover, target prediction analysis applied to ten vertebrate species, suggest that such miRNA regulatory modus operandi is evolutionarily conserved within vertebrates. Overall, we discovered a complex regulatory cluster-module strategy driven by miRNAs, which relies on the controlled intensity of the repression over distinct targets under specific biological contexts. Our discovery helps to clarify the mechanisms underlying the functional activity of miRNAs and makes it easier to take the fastest and most accurate path in the search for the functions of miRNAs in any distinct biological process of interest.

scholarly journals Identification of Key Genes and Evaluation of Their Prognosis Potential in Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

2020 ◽  
Author(s):  
Jankun Liu ◽  
zy liu ◽  
Wei Li ◽  
Xinghua Pan ◽  
Zongjiang Fan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Target Genes ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Survival Curve ◽  
Treatment Strategies ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Key Genes

Abstract Background Hepatocellular carcinoma (HCC) is a malignancy causing highly death rate in the world. Despite the development of treatment strategies for HCC, prognosis of this malignancy remains unsatisfactory. In this study, we aimed to identify the target genes associated with the prognosis of HCC patients. Methods Three expression profiles of HCC tissues were extracted from the Gene Expression Omnibus database to explore the differentially expressed genes (DEGs) using GEO2R method. Functional enrichment analysis was performed to reveal the biological characteristics of DEGs. Protein-protein interaction (PPI) network was constructed using Cytoscape software. The survival curve of identified DEGs were tested by Kaplan-Meier analysis. Results We identified 15 DEGs (CYP39A1, CYR61, FOS, FOXO1, GADD45B, ID1, IL1RAP, MT1M, PHLDA1, RND3, SDS, SOCS2, TAT, S100P, and SPINK1) in HCC tissues. Prognosis analysis showed that 4 DEGs (FOXO1,SPINK1༌SOCS2, and TAT) correlated with overall survival time of HCC patients, which might serve as therapeutic targets for HCC patients. Conclusions By integrated bioinformatics analysis, we proposed a novel way to reveal key genes that closely relate to HCC development.

scholarly journals Integrated network analysis identifying potential novel drug candidates and targets for Parkinson's disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pusheng Quan ◽  
Kai Wang ◽  
Shi Yan ◽  
Shirong Wen ◽  
Chengqun Wei ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Drug Target ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Control Group ◽  
Drug Candidates ◽  
Novel Drug

AbstractThis study aimed to identify potential novel drug candidates and targets for Parkinson’s disease. First, 970 genes that have been reported to be related to PD were collected from five databases, and functional enrichment analysis of these genes was conducted to investigate their potential mechanisms. Then, we collected drugs and related targets from DrugBank, narrowed the list by proximity scores and Inverted Gene Set Enrichment analysis of drug targets, and identified potential drug candidates for PD treatment. Finally, we compared the expression distribution of the candidate drug-target genes between the PD group and the control group in the public dataset with the largest sample size (GSE99039) in Gene Expression Omnibus. Ten drugs with an FDR < 0.1 and their corresponding targets were identified. Some target genes of the ten drugs significantly overlapped with PD-related genes or already known therapeutic targets for PD. Nine differentially expressed drug-target genes with p < 0.05 were screened. This work will facilitate further research into the possible efficacy of new drugs for PD and will provide valuable clues for drug design.

scholarly journals Dynamic characteristics and functional analysis provide new insights into long non-coding RNA responsive to Verticillium dahliae infection in Gossypium hirsutum

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guoning Wang ◽  
Xingfen Wang ◽  
Yan Zhang ◽  
Jun Yang ◽  
Zhikun Li ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Verticillium Wilt ◽  
Dynamic Characteristics ◽  
Target Genes ◽  
Acid Metabolism ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Alpha Linolenic Acid ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Abstract Background Verticillium wilt is a widespread and destructive disease, which causes serious loss of cotton yield and quality. Long non-coding RNA (lncRNA) is involved in many biological processes, such as plant disease resistance response, through a variety of regulatory mechanisms, but their possible roles in cotton against Verticillium dahliae infection remain largely unclear. Results Here, we measured the transcriptome of resistant G. hirsutum following infection by V. dahliae and 4277 differentially expressed lncRNAs (delncRNAs) were identified. Localization and abundance analysis revealed that delncRNAs were biased distribution on chromosomes. We explored the dynamic characteristics of disease resistance related lncRNAs in chromosome distribution, induced expression profiles, biological function, and these lncRNAs were divided into three categories according to their induced expression profiles. For the delncRNAs, 687 cis-acting pairs and 14,600 trans-acting pairs of lncRNA-mRNA were identified, which indicated that trans-acting was the main way of Verticillium wilt resistance-associated lncRNAs regulating target mRNAs in cotton. Analyzing the regulation pattern of delncRNAs revealed that cis-acting and trans-acting lncRNAs had different ways to influence target genes. Gene Ontology (GO) enrichment analysis revealed that the regulatory function of delncRNAs participated significantly in stimulus response process, kinase activity and plasma membrane components. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that delncRNAs participated in some important disease resistance pathways, such as plant-pathogen interaction, alpha-linolenic acid metabolism and plant hormone signal transduction. Additionally, 21 delncRNAs and 10 target genes were identified as being involved in alpha-linolenic acid metabolism associated with the biosynthesis of jasmonic acid (JA). Subsequently, we found that GhlncLOX3 might regulate resistance to V. dahliae through modulating the expression of GhLOX3 implicated in JA biosynthesis. Further functional analysis showed that GhlncLOX3-silenced seedlings displayed a reduced resistance to V. dahliae, with down-regulated expression of GhLOX3 and decreased content of JA. Conclusion This study shows the dynamic characteristics of delncRNAs in multiaspect, and suggests that GhlncLOX3-GhLOX3-JA network participates in response to V. dahliae invasion. Our results provide novel insights for genetic improvement of Verticillium wilt resistance in cotton using lncRNAs.

scholarly journals Pineal gland transcriptomic profiling reveals the differential regulation of lncRNA and mRNA related to prolificacy in STH sheep with two FecB genotypes

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Chunyan Li ◽  
Xiaoyun He ◽  
Zijun Zhang ◽  
Chunhuan Ren ◽  
Mingxing Chu
Keyword(s):  
Pineal Gland ◽  
Expression Pattern ◽  
Noncoding Rna ◽  
Target Genes ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Rna Seq ◽  
Important Regulator ◽  
Gsh Metabolism ◽  
Transcriptome Expression

Abstract Background Long noncoding RNA (lncRNA) has been identified as important regulator in hypothalamic-pituitary-ovarian axis associated with sheep prolificacy. However, little is known of their expression pattern and potential roles in the pineal gland of sheep. Herein, RNA-Seq was used to detect transcriptome expression pattern in pineal gland between follicular phase (FP) and luteal phase (LP) in FecBBB (MM) and FecB++ (ww) STH sheep, respectively, and differentially expressed (DE) lncRNAs and mRNAs associated with reproduction were identified. Results Overall, 135 DE lncRNAs and 1360 DE mRNAs in pineal gland between MM and ww sheep were screened. Wherein, 39 DE lncRNAs and 764 DE mRNAs were identified (FP vs LP) in MM sheep, 96 DE lncRNAs and 596 DE mRNAs were identified (FP vs LP) in ww sheep. Moreover, GO and KEGG enrichment analysis indicated that the targets of DE lncRNAs and DE mRNAs were annotated to multiple biological processes such as phototransduction, circadian rhythm, melanogenesis, GSH metabolism and steroid biosynthesis, which directly or indirectly participate in hormone activities to affect sheep reproductive performance. Additionally, co-expression of lncRNAs-mRNAs and the network construction were performed based on correlation analysis, DE lncRNAs can modulate target genes involved in related pathways to affect sheep fecundity. Specifically, XLOC_466330, XLOC_532771, XLOC_028449 targeting RRM2B and GSTK1, XLOC_391199 targeting STMN1, XLOC_503926 targeting RAG2, XLOC_187711 targeting DLG4 were included. Conclusion All of these differential lncRNAs and mRNAs expression profiles in pineal gland provide a novel resource for elucidating regulatory mechanism underlying STH sheep prolificacy.

scholarly journals Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients

2021 ◽  
Vol 22 (5) ◽  
pp. 2442
Author(s):  
Qun Wang ◽  
Aurelia Vattai ◽  
Theresa Vilsmaier ◽  
Till Kaltofen ◽  
Alexander Steger ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Clinical Data ◽  
Regulatory Network ◽  
Univariate Analysis ◽  
Predictive Biomarkers ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Functional Enrichment ◽  
Wilcoxon Test

Cervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics associated with cervical cancer prognosis. The Cancer Genome Atlas (TCGA) public database has stored abundant sequencing or microarray data, and clinical data, offering a feasible and reliable approach for this study. In the present study, gene profile and clinical data were downloaded from TCGA, and the Immunology Database and Analysis Portal (ImmPort) database. Wilcoxon-test was used to compare the difference in gene expression. Univariate analysis was adopted to identify immune-related genes (IRGs) and transcription factors (TFs) correlated with survival. A prognostic prediction model was established by multivariate cox analysis. The regulatory network was constructed and visualized by correlation analysis and Cytoscape, respectively. Gene functional enrichment analysis was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 204 differentially expressed IRGs were identified, and 22 of them were significantly associated with the survival of cervical cancer. These 22 IRGs were actively involved in the JAK-STAT pathway. A prognostic model based on 10 IRGs (APOD, TFRC, GRN, CSK, HDAC1, NFATC4, BMP6, IL17RD, IL3RA, and LEPR) performed moderately and steadily in squamous cell carcinoma (SCC) patients with FIGO stage I, regardless of the age and grade. Taken together, a risk score model consisting of 10 novel genes capable of predicting survival in SCC patients was identified. Moreover, the regulatory network of IRGs associated with survival (SIRGs) and their TFs provided potential molecular targets.

scholarly journals Screening Driving Transcription Factors in the Processing of Gastric Cancer

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Guangzhong Xu ◽  
Kai Li ◽  
Nengwei Zhang ◽  
Bin Zhu ◽  
Guosheng Feng
Keyword(s):  
Gastric Cancer ◽  
Transcription Factors ◽  
Regulatory Network ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Regulatory Mechanisms ◽  
Integrated Analysis ◽  
Transcriptional Regulatory

Background. Construction of the transcriptional regulatory network can provide additional clues on the regulatory mechanisms and therapeutic applications in gastric cancer.Methods. Gene expression profiles of gastric cancer were downloaded from GEO database for integrated analysis. All of DEGs were analyzed by GO enrichment and KEGG pathway enrichment. Transcription factors were further identified and then a global transcriptional regulatory network was constructed.Results. By integrated analysis of the six eligible datasets (340 cases and 43 controls), a bunch of 2327 DEGs were identified, including 2100 upregulated and 227 downregulated DEGs. Functional enrichment analysis of DEGs showed that digestion was a significantly enriched GO term for biological process. Moreover, there were two important enriched KEGG pathways: cell cycle and homologous recombination. Furthermore, a total of 70 differentially expressed TFs were identified and the transcriptional regulatory network was constructed, which consisted of 566 TF-target interactions. The top ten TFs regulating most downstream target genes were BRCA1, ARID3A, EHF, SOX10, ZNF263, FOXL1, FEV, GATA3, FOXC1, and FOXD1. Most of them were involved in the carcinogenesis of gastric cancer.Conclusion. The transcriptional regulatory network can help researchers to further clarify the underlying regulatory mechanisms of gastric cancer tumorigenesis.

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