Bioinformatics functional analysis of let-7a, miR-34a, and miR-199a/b reveals novel insights into immune system pathways and cancer hallmarks for hepatocellular carcinoma

Let-7a, miR-34a, and miR-199 a/b have gained a great attention as master regulators for cellular processes. In particular, these three micro-RNAs act as potential onco-suppressors for hepatocellular carcinoma. Bioinformatics can reveal the functionality of these micro-RNAs through target prediction and functional annotation analysis. In the current study, in silico analysis using innovative servers (miRror Suite, DAVID, miRGator V3.0, GeneTrail) has demonstrated the combinatorial and the individual target genes of these micro-RNAs and further explored their roles in hepatocellular carcinoma progression. There were 87 common target messenger RNAs (p ≤ 0.05) that were predicted to be regulated by the three micro-RNAs using miRror 2.0 target prediction tool. In addition, the functional enrichment analysis of these targets that was performed by DAVID functional annotation and REACTOME tools revealed two major immune-related pathways, eight hepatocellular carcinoma hallmarks–linked pathways, and two pathways that mediate interconnected processes between immune system and hepatocellular carcinoma hallmarks. Moreover, protein–protein interaction network for the predicted common targets was obtained by using STRING database. The individual analysis of target genes and pathways for the three micro-RNAs of interest using miRGator V3.0 and GeneTrail servers revealed some novel predicted target oncogenes such as SOX4, which we validated experimentally, in addition to some regulated pathways of immune system and hepatocarcinogenesis such as insulin signaling pathway and adipocytokine signaling pathway. In general, our results demonstrate that let-7a, miR-34a, and miR-199 a/b have novel interactions in different immune system pathways and major hepatocellular carcinoma hallmarks. Thus, our findings shed more light on the roles of these miRNAs as cancer silencers.

Download Full-text

Micro RNAs in Regulation of Cellular Redox Homeostasis

International Journal of Molecular Sciences ◽

10.3390/ijms22116022 ◽

2021 ◽

Vol 22 (11) ◽

pp. 6022

Author(s):

Sylwia Ciesielska ◽

Izabella Slezak-Prochazka ◽

Patryk Bil ◽

Joanna Rzeszowska-Wolny

Keyword(s):

Target Genes ◽

Redox Homeostasis ◽

Messenger Rnas ◽

Cellular Redox ◽

Cell Responses ◽

Regulatory Circuits ◽

Micro Rnas ◽

Cellular Behaviors ◽

Homeostasis Regulation ◽

Thioredoxin Reductases

In living cells Reactive Oxygen Species (ROS) participate in intra- and inter-cellular signaling and all cells contain specific systems that guard redox homeostasis. These systems contain both enzymes which may produce ROS such as NADPH-dependent and other oxidases or nitric oxide synthases, and ROS-neutralizing enzymes such as catalase, peroxiredoxins, thioredoxins, thioredoxin reductases, glutathione reductases, and many others. Most of the genes coding for these enzymes contain sequences targeted by micro RNAs (miRNAs), which are components of RNA-induced silencing complexes and play important roles in inhibiting translation of their targeted messenger RNAs (mRNAs). In this review we describe miRNAs that directly target and can influence enzymes responsible for scavenging of ROS and their possible role in cellular redox homeostasis. Regulation of antioxidant enzymes aims to adjust cells to survive in unstable oxidative environments; however, sometimes seemingly paradoxical phenomena appear where oxidative stress induces an increase in the levels of miRNAs which target genes which are supposed to neutralize ROS and therefore would be expected to decrease antioxidant levels. Here we show examples of such cellular behaviors and discuss the possible roles of miRNAs in redox regulatory circuits and further cell responses to stress.

Download Full-text

miRNA Mediated Noise Making of 3′UTR Mutations in Cancer

Genes ◽

10.3390/genes9110545 ◽

2018 ◽

Vol 9 (11) ◽

pp. 545 ◽

Cited By ~ 5

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.

Download Full-text

Identification of a Potential PPAR-Related Multigene Signature Predicting Prognosis of Patients with Hepatocellular Carcinoma

PPAR Research ◽

10.1155/2021/6642939 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Wenfang Xu ◽

Zhen Chen ◽

Gang Liu ◽

Yuping Dai ◽

Xuanfu Xu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Signaling Pathway ◽

Target Genes ◽

Prognostic Markers ◽

Cox Regression ◽

Clinical Information ◽

Gene Signature ◽

Peroxisome Proliferator ◽

Clinical Indicators ◽

Ppar Signaling

Peroxisome proliferator-activated receptors (PPARs) and part of their target genes have been reported to be related to the progression of hepatocellular carcinoma (HCC). The prognosis of HCC is not optimistic, and more accurate prognostic markers are needed. This study focused on discovering potential prognostic markers from the PPAR-related gene set. The mRNA data and clinical information of HCC were collected from TCGA and GEO platforms. Univariate Cox and lasso Cox regression analyses were used to screen prognostic genes of HCC. Three genes (MMP1, HMGCS2, and SLC27A5) involved in the PPAR signaling pathway were selected as the prognostic signature of HCC. A formula was established based on the expression values and multivariate Cox regression coefficients of selected genes, that was, risk score = 0.1488 ∗ expression value of M M P 1 + − 0.0393 ∗ expression value of H M G C S 2 + − 0.0479 ∗ expression value of S L C 27 A 5 . The prognostic ability of the three-gene signature was assessed in the TCGA HCC dataset and verified in three GEO sets (GSE14520, GSE36376, and GSE76427). The results showed that the risk score based on our signature was a risk factor with a HR (hazard ratio) of 2.72 ( 95 % CI Confidence Interval = 1.87 ~ 3.95 , p < 0.001 ) for HCC survival. The signature could significantly ( p < 0.0001 ) distinguish high-risk and low-risk patients with poor prognosis for HCC. In addition, we further explored the independence and applicability of the signature with other clinical indicators through multivariate Cox analysis ( p < 0.001 ) and nomogram analysis ( C ‐ index = 0.709 ). The above results indicate that the combination of MMP1, HMGCS2, and SLC27A5 selected from the PPAR signaling pathway could effectively, independently, and applicatively predict the prognosis of HCC. Our research provided new insights to the prognosis of HCC.

Download Full-text

Using Context-Sensitive Text Mining to Identify miRNAs in Different Stages of Atherosclerosis

Thrombosis and Haemostasis ◽

10.1055/s-0039-1693165 ◽

2019 ◽

Vol 119 (08) ◽

pp. 1247-1264 ◽

Cited By ~ 2

Author(s):

Markus Joppich ◽

Christian Weber ◽

Ralf Zimmer

Keyword(s):

Data Analysis ◽

Text Mining ◽

High Throughput ◽

Target Genes ◽

Mirna Gene ◽

Cell Types ◽

Gene Interactions ◽

Messenger Rnas ◽

New Findings ◽

Micro Rnas

790 human and mouse micro-RNAs (miRNAs) are involved in diseases. More than 26,428 miRNA–gene interactions are annotated in humans and mice. Most of these interactions are posttranscriptional regulations: miRNAs bind to the messenger RNAs (mRNAs) of genes and induce their degradation, thereby reducing the gene expression of target genes. For atherosclerosis, 667 miRNA–gene interactions for 124 miRNAs and 343 genes have been identified and described in numerous publications. Some interactions were observed through high-throughput experiments, others were predicted using bioinformatic methods, and some were determined by targeted experiments. Several reviews collect knowledge on miRNA–gene interactions in (specific aspects of) atherosclerosis.Here, we use our bioinformatics resource (atheMir) to give an overview of miRNA–gene interactions in the context of atherosclerosis. The interactions are based on public databases and context-based text mining of 28 million PubMed abstracts. The miRNA–gene interactions are obtained from more than 10,000 publications, of which more than 1,000 are in a cardiovascular disease context (266 in atherosclerosis). We discuss interesting miRNA–gene interactions in atherosclerosis, grouped by specific processes in different cell types and six phases of atherosclerotic progression. All evidence is referenced and easily accessible: Relevant interactions are provided by atheMir as supplementary tables for further evaluation and, for example, for the subsequent data analysis of high-throughput measurements as well as for the generation and validation of hypotheses. The atheMir approach has several advantages: (1) the evidence is easily accessible, (2) regulatory interactions are uniformly available for subsequent high-throughput data analysis, and (3) the resource can incrementally be updated with new findings.

Download Full-text

Identification of microRNAs and target genes associated with the development of human intervertebral disc degeneration by bioinformatic analysis and verification

10.21203/rs.2.17292/v1 ◽

2019 ◽

Author(s):

Hongze Chang ◽

Xiaolong Yang ◽

Kemin You ◽

Mingwei Jiang ◽

Feng Cai ◽

...

Keyword(s):

Cell Differentiation ◽

Intervertebral Disc ◽

Wnt Signaling ◽

Disc Degeneration ◽

Intervertebral Disc Degeneration ◽

Target Genes ◽

Cell Development ◽

Functional Enrichment ◽

Hub Genes ◽

Micro Rnas

Abstract Micro RNAs (miRNAs) are widely recognized to play an essential role via target genes in the development of intervertebral disc degeneration( IDD), but the molecular mechanisms remain unclear. To identify the key microRNAs and potential targets during IDD, the Gene Expression Omnibus datasets (GSE19943, GSE63492, and GSE116726) were downloaded.An R package was used to identify differentially expressed miRNAs (DEMs) and four online tools(TargetScan, miRDB, miRTarBase, and DIANA-TarBase) were performed to predict their target genes. Functional enrichment analysis revealed that DEMs gene targets were highly enriched in cell development, cell differentiation, and the p53 and Wnt signaling pathways. we identified 13 hub genes with node degree≥10 through established a protein-protein interaction (PPI) network. Among them,MAPK8, BMP4, and GSK3B were top 3 highest degree. After constructing the miRNA-target gene-functional analysis network, we found that most hub genes could be regulated by miR-557 and were mainly enriched in cell development, cell differentiation, and Wnt signaling pathway. Further in vitro experiment by qRT-PCR confirmed that miR-577 was significantly downregulated than the control,whereas miR-516-3p was significantly upregulated. Together, the key microRNA and their target genes identified in this study help us understand the underlying pathogenesis mechanisms in the development of IDD, and provide diagnostic biomarkers and new therapeutic strategies for the treatment of IDD.

Download Full-text

MAPK Signaling Pathway was Dysregulated in Acute Myeloid Leukemia with RUNX1 Mutations

10.21203/rs.3.rs-502740/v1 ◽

2021 ◽

Author(s):

Mingmin he ◽

Xiongwei Cai ◽

Yuanyuan Zeng

Keyword(s):

Acute Myeloid Leukemia ◽

Signaling Pathway ◽

Myeloid Leukemia ◽

Target Genes ◽

Mapk Signaling ◽

Mapk Signaling Pathway ◽

Functional Enrichment ◽

Wild Type ◽

The Relationship ◽

Acute Myeloid

Abstract The purpose of this study was to investigate the relationship between RUNX1 mutations and MAPK signaling pathway in acute myeloid leukemia (AML). In this study, we analyzed miRNA expression with 5 mutant RUNX1 and 9 wild-type RUNX1 cases from TCGA database of AML. Six miRNAs were differently expressed with significance, and three of them were related to overall survival. Predicted target genes of these 3 miRNAs were highly enriched in MAPK signaling pathway by functional enrichment with miRWalk3.0. Besides, genes among RUNX1 associated genes directly regulated by RUNX1 were involved in MAPK signaling pathway, too. Taken together, we demonstrate three DEmiRNAs and three genes correlated to RUNX1 were correlated with prognosis in AML, and RUNX1 modulated MAPK signaling pathway in AML.

Download Full-text

Computational Model for Predicting the Relationship Between Micro-RNAs and Their Target Messenger RNAs in Breast and Colon Cancers

Cancer Informatics ◽

10.1177/1176935118785145 ◽

2018 ◽

Vol 17 ◽

pp. 117693511878514

Author(s):

Shinuk Kim

Keyword(s):

Breast Cancer ◽

Colon Cancer ◽

Target Gene ◽

Target Genes ◽

Computational Method ◽

Numerical Code ◽

Messenger Rnas ◽

Unknown Parameters ◽

Micro Rnas ◽

The Relationship

Motivation: Uncovering the relationship between micro-RNAs (miRNAs) and their target messenger RNAs (mRNAs) can provide critical information regarding the mechanisms underlying certain types of cancers. In this context, we have proposed a computational method, referred to as prediction analysis by optimization method (PAOM), to predict miRNA-mRNA relations using data from normal and cancer tissues, and then applying the relevant algorithms to colon and breast cancers. Specifically, we used 26 miRNAs and 26 mRNAs with 676 (= 26 × 26) relationships to be recovered as unknown parameters. Results: Optimization methods were used to detect 61 relationships in breast cancer and 32 relationships in colon cancer. Using sequence filtering, we detected 18 relationships in breast cancer and 15 relationships in colon cancer. Among the 18 relationships, CD24 is the target gene of let-7a and miR-98, and E2F1 is the target gene of miR-20. In addition, the frequencies of the target genes of miR-223, miR-23a, and miR-20 were significant in breast cancer, and the frequencies of the target genes of miR-17, miR-124, and miR-30a were found to be significant in colon cancer. Availability: The numerical code is available from the authors on request.

Download Full-text

Potential lncRNA Biomarkers for HBV-Related Hepatocellular Carcinoma Diagnosis Revealed by Analysis on Coexpression Network

BioMed Research International ◽

10.1155/2021/9972011 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Shunqiang Nong ◽

Xiaohao Chen ◽

Zechen Wang ◽

Guidan Xu ◽

Wujun Wei ◽

...

Keyword(s):

Gene Expression ◽

Machine Learning ◽

Hepatocellular Carcinoma ◽

Functional Annotation ◽

Expression Profiles ◽

Functional Enrichment ◽

Coexpression Network ◽

Support Vector ◽

Immune Microenvironment ◽

Tumor Immune Microenvironment

Background. Increasing evidence demonstrated that long noncoding RNA (lncRNA) could affect inflammatory tumor immune microenvironment by modulating gene expression and could be used as a biomarker for HBC-related hepatocellular carcinoma (HCC) but still needs further research. The aim of the present study was to determine an lncRNA signature for the diagnosis of HBV-related HCC. Methods. HBV-related HCC expression profiles (GSE55092, GSE19665, and GSE84402) were abstracted from the GEO (Gene Expression Omnibus) data resource, and R package limma and RobustRankAggreg were employed to identify common differentially expressed genes (DEGs). Using machine learning, optimal diagnostic lncRNA molecular markers for HBV-related HCC were identified. The expression of candidate lncRNAs was cross-validated in GSE121248, and an ROC (receiver operating characteristic) curve of lncRNA biomarkers was carried out. Additionally, a coexpression network and functional annotation was built, after which a PPI (protein-protein interaction) network along with module analysis were conducted with the Cytoscape open source software. Result. A total of 38 DElncRNAs and 543 DEmRNAs were identified with a fold change larger than 2.0 and a P value < 0.05. By machine learning, AL356056.2, AL445524.1, TRIM52-AS1, AC093642.1, EHMT2-AS1, AC003991.1, AC008040.1, LINC00844, and LINC01018 were screened out as optional diagnostic lncRNA biosignatures for HBV-related HCC. The AUC (areas under the curve) of the SVM (support vector machine) model and random forest model were 0.957 and 0.904, respectively, and the specificity and sensitivity were 95.7 and 100% and 94.3 and 86.5%, respectively. The results of functional enrichment analysis showed that the integrated coexpressed DEmRNAs shared common cascades in the p53 signaling pathway, retinol metabolism, PI3K-Akt signaling cascade, and chemical carcinogenesis. The integrated DEmRNA PPI network complex was found to be comprised of 87 nodes, and two vital modules with a high degree were selected with the MCODE app. Conclusion. The present study identified nine potential diagnostic biomarkers for HBV-related HCC, all of which could potentially modulated gene expression related to inflammatory conditions in the tumor immune microenvironment. The functional annotation of the target DEmRNAs yielded novel evidence in evaluating the precise functions of lncRNA in HBV-related HCC.

Download Full-text

Integrated Analysis of lncRNA and mRNA Reveals Novel Insights into Wool Bending in Zhongwei Goat

Animals ◽

10.3390/ani11113326 ◽

2021 ◽

Vol 11 (11) ◽

pp. 3326

Author(s):

Xiaobo Li ◽

Zhanfa Liu ◽

Shaohui Ye ◽

Yue Liu ◽

Qian Chen ◽

...

Keyword(s):

Signaling Pathway ◽

Target Genes ◽

Economic Value ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Hair Follicles ◽

Functional Enrichment ◽

Integrated Analysis ◽

Rna Seq ◽

Camp Signaling Pathway

Chinese Zhongwei goat is a rare and precious fur breed as its lamb fur is a well-known fur product. Wool bending of lamb fur of the Zhongwei goat is its most striking feature. However, the curvature of the wool decreases gradually with growth, which significantly affects its quality and economic value. The mechanism regulating the phenotypic changes of hair bending is still unclear. In the present study, the skin tissues of Zhongwei goats at 45 days (curving wool) and 108 days (slight-curving wool) after birth were taken as the research objects, and the expression profiling of long non-coding RNAs (lncRNAs) and mRNAs were analyzed based on the Ribo Zero RNA sequencing (RNA-seq) method. In total, 46,013 mRNAs and 13,549 lncRNAs were identified, of which 352 were differentially expressed mRNAs and 60 were. lncRNAs. Functional enrichment analysis of the target genes of lncRNAs were mainly enriched in PI3K-Akt, Arachidonic acid metabolic, cAMP, Wnt, and other signaling pathways. The qRT-PCR results of eight selected lncRNAs and target genes were consistent with the sequencing result, which indicated our data were reliable. Through the analysis of the weighted gene co-expression network, 13 co-expression modules were identified. The turquoise module contained a large number of differential expressed lncRNAs, which were mainly enriched in the PI3K-Akt signaling pathway and cAMP signaling pathway. The predicted LOC102172600 and LOC102191729 might affect the development of hair follicles and the curvature of wool by regulating the target genes. Our study provides novel insights into the potential roles of lncRNAs in the regulation of wool bending. In addition, the study offers a theoretical basis for further study of goat wool growth, so as to be a guidance and reference for breeding and improvement in the future.

Download Full-text

Identification and validation of putative target genes regulated by miR-34 in cervical cancer

10.1101/2021.09.02.458804 ◽

2021 ◽

Author(s):

Nalini Venkatesan ◽

Ashley Xavier ◽

Sindhu K.J. ◽

Himanshu Sinha ◽

Karunagaran Devarajan

Keyword(s):

Cervical Cancer ◽

Candidate Genes ◽

Large Scale ◽

Cancer Metastasis ◽

Target Genes ◽

Epithelial Mesenchymal Transition ◽

Target Prediction ◽

Functional Enrichment ◽

Mesenchymal Transition ◽

Putative Target

The emergence of large-scale transcriptomic data provides the opportunity for identifying novel putative targets of microRNAs (miRNAs). In this study, we followed a computational pipeline to predict the candidate gene targets of the miR-34 family. This approach integrates the expressions of miR-34 with genes of heterogeneous primary cervical epithelial squamous cell carcinomas (CESC). Integration of miR-34b and epithelial-mesenchymal transition (EMT) regulated genes has also been focussed, EMT being a reversible process that fuels cancer metastasis. An in-silico approach involving three processes was carried out with CESC datasets of the cancer atlas genome (TCGA), which includes correlation analysis, target prediction database lookup, functional enrichment, network analysis, survival analysis, and EMT score derivation. The results indicate that the miR-34 family may regulate the candidate genes of the mTOR pathway, cell cycle (CCND2) and cell adhesion functions (FZD4). Further, the study reveals the possible regulation of EMT signature genes, namely BMP7, CAV1 and ID2by miR-34b. Further, these transcriptomic signatures were validated in a subset of CESC from the South Asian Indian population (n = 10) and in non-cancerous cervical tissues (n = 5). Upon stably expressing miR-34b in cervical cancer cells (C33A and HeLa), we found repression of these candidate genes and a low negative correlation (r2 = 0.07) between miR-34b and EMT score indicating FN1 as its putative target. Together, these studies revealed the potential targets of the miR-34 family, especially miR-34b, with the hope that they would emerge as potential biomarkers and/or promising therapeutic targets in CESC.

Download Full-text