scholarly journals Identification of Novel RNA Binding Proteins Influencing Circular RNA Expression in Hepatocellular Carcinoma

2021 ◽  
Vol 22 (14) ◽  
pp. 7477
Author(s):  
Rok Razpotnik ◽  
Petra Nassib ◽  
Tanja Kunej ◽  
Damjana Rozman ◽  
Tadeja Režen
Keyword(s):  
Hepatocellular Carcinoma ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Regulatory Protein ◽  
Circular Rna ◽  
Differentially Expressed ◽  
Circular Rnas ◽  
Bioinformatics Analyses ◽  
Published Evidence

Circular RNAs (circRNAs) are increasingly recognized as having a role in cancer development. Their expression is modified in numerous cancers, including hepatocellular carcinoma (HCC); however, little is known about the mechanisms of their regulation. The aim of this study was to identify regulators of circRNAome expression in HCC. Using publicly available datasets, we identified RNA binding proteins (RBPs) with enriched motifs around the splice sites of differentially expressed circRNAs in HCC. We confirmed the binding of some of the candidate RBPs using ChIP-seq and eCLIP datasets in the ENCODE database. Several of the identified RBPs were found to be differentially expressed in HCC and/or correlated with the overall survival of HCC patients. According to our bioinformatics analyses and published evidence, we propose that NONO, PCPB2, PCPB1, ESRP2, and HNRNPK are candidate regulators of circRNA expression in HCC. We confirmed that the knocking down the epithelial splicing regulatory protein 2 (ESRP2), known to be involved in the maintenance of the adult liver phenotype, significantly changed the expression of candidate circRNAs in a model HCC cell line. By understanding the systemic changes in transcriptome splicing, we can identify new proteins involved in the molecular pathways leading to HCC development and progression.

scholarly journals Identification of an RNA binding protein-related gene signature in hepatocellular carcinoma patients

2020 ◽  
Vol 26 (1) ◽  
Author(s):  
Li Wang ◽  
Na Zhou ◽  
Jialin Qu ◽  
Man Jiang ◽  
Xiaochun Zhang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Binding Proteins ◽  
Rna Binding ◽  
Cox Regression ◽  
Rna Binding Proteins ◽  
Characteristic Curve ◽  
Gene Signature ◽  
Clinicopathological Parameters ◽  
Lasso Regression ◽  
Bioinformatics Analyses

Abstract Background Hepatocellular carcinoma (HCC) is a common malignant primary cancer with high mortality. Previous studies have demonstrated that RNA binding proteins (RBPs) are involved in the biological processes of cancers, including hepatocellular cancer. Methods In this study, we aimed to identify the clinical value of RNA-binding proteins for hepatocellular carcinoma. We obtained gene expression and clinical data of hepatocellular carcinoma patients from the TCGA and ICGC databases. The prognostic value of RBP-related genes in patients with hepatocellular carcinoma and their function were studied by comprehensive bioinformatics analyses. The gene signature of SMG5, EZH2, FBLL1, ZNF239, and IGF2BP3 was generated by univariate and multivariate Cox regression and LASSO regression analyses. We built and verified a prognostic nomogram based on RBP-related genes. The gene signature was validated by the ICGC database. The expression of RBP-related genes was validated by the Oncomine database, the Human Protein Atlas and Kaplan–Meier plotter. Result Most RBP-related genes were significantly different in cancer and normal tissues. The survival of patients in the different groups was significantly different. The gene signature showed good performance for predicting the survival of HCC patients by having a better area under the receiver operating characteristic curve than other clinicopathological parameters. Conclusion Gene signatures based on RNA-binding proteins can be independent risk factors for hepatocellular carcinoma patients.

scholarly journals Systematic Analysis of the Function and Prognostic Value of RNA-Binding Proteins in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
TONG WU ◽  
Zhiyun Yang ◽  
Yuying Yang ◽  
Yuyong Jiang ◽  
Peipei Meng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Roc Curve ◽  
Prognostic Model ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Curve Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Roc Curve Analysis

Abstract Background: RNA-binding proteins (RBPs) are abnormally expressed in a variety of malignant tumors and are closely related to tumorigenesis, tumor progression, and prognosis. The role of RBPs in hepatocellular carcinoma (HCC) is unclear. Based on the cancer genome atlas (TCGA) database, we conducted a systematic bioinformatics analysis of abnormally expressed RBPs in HCC, with the aim of identifying the prognostic markers and potential therapeutic targets.Methods: HCC RNA sequencing data downloaded from TCGA database were used to determine the differentially expressed RBPs in livery cancer and normal tissues, followed by performing functional enrichment analysis and visualization of interaction relationships. Univariate and multivariate Cox regression analyses were subsequently used to identify RBPs that were significantly related to the prognosis to construct a prognostic model. The predictive performance of the prognostic model was evaluated by survival analysis and receiver operating characteristic (ROC) curve analysis and verified in the test cohort. Human protein atlas online database was used to verify the expression level of RBPs in the prognostic model.Results: In total, 82 differentially expressed RBPs were identified, including 55 upregulated and 27 downregulated RBPs. Further functional enrichment and interaction analyses showed that the differentially expressed RBPs were mainly related to regulating of mRNA metabolic process, RNA catabolic, mRNA catabolic process, and macromolecule methylation. Five RBP genes, LIN28B, SMG5, PPARGC1A, LARP1B, and ANG were identified as prognostic-related genes and used to construct the prognostic model. The predictive ability of the prognostic model was verified in the test cohort. ROC curve analysis showed that the prognostic model had good sensitivity and specificity. Independent prognostic analysis showed that the risk score may be an independent prognostic factor for HCC.Conclusion: This study constructed a reliable prognostic prediction model by analyzing the differentially expressed RBPs of HCC, facilitating the identification of HCC prognostic biomarkers and therapeutic targets.

scholarly journals The effective function of circular RNA in colorectal cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mandana Ameli-Mojarad ◽  
Melika Ameli-Mojarad ◽  
Mahrooyeh Hadizadeh ◽  
Chris Young ◽  
Hosna Babini ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Mechanisms ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Circular Rna ◽  
Circular Rnas ◽  
Colorectal Tumorigenesis ◽  
Non Coding Rnas ◽  
Mirna Sponges ◽  
Mechanisms Of Development

AbstractColorectal cancer (CRC) is the 3rd most common type of cancer worldwide. Late detection plays role in one-third of annual mortality due to CRC. Therefore, it is essential to find a precise and optimal diagnostic and prognostic biomarker for the identification and treatment of colorectal tumorigenesis. Covalently closed, circular RNAs (circRNAs) are a class of non-coding RNAs, which can have the same function as microRNA (miRNA) sponges, as regulators of splicing and transcription, and as interactors with RNA-binding proteins (RBPs). Therefore, circRNAs have been investigated as specific targets for diagnostic and prognostic detection of CRC. These non-coding RNAs are also linked to metastasis, proliferation, differentiation, migration, angiogenesis, apoptosis, and drug resistance, illustrating the importance of understanding their involvement in the molecular mechanisms of development and progression of CRC. In this review, we present a detailed summary of recent findings relating to the dysregulation of circRNAs and their potential role in CRC.

scholarly journals The Regulatory Functions of Circular RNAs in Digestive System Cancers

Cancers ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 770 ◽  
Author(s):  
Xiao Yuan ◽  
Ya Yuan ◽  
Zhi He ◽  
Diyan Li ◽  
Bo Zeng ◽  
...  
Keyword(s):  
Digestive System ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Circular Rna ◽  
Research Progress ◽  
Circular Rnas ◽  
Biological Functions ◽  
Ribonucleic Acids ◽  
Mirna Sponges ◽  
And Biological Markers

Circular ribonucleic acids (circRNAs), which are a type of covalently closed circular RNA, are receiving increasing attention. An increasing amount of evidence suggests that circRNAs are involved in the biogenesis and development of multiple diseases such as digestive system cancers. Dysregulated circRNAs have been found to act as oncogenes or tumour suppressors in digestive system cancers. Moreover, circRNAs are related to ageing and a wide variety of processes in tumour cells, such as cell apoptosis, invasion, migration, and proliferation. Moreover, circRNAs can perform a remarkable multitude of biological functions, such as regulating splicing or transcription, binding RNA-binding proteins to enable function, acting as microRNA (miRNA) sponges, and undergoing translated into proteins. However, in digestive system cancers, circRNAs function mainly as miRNA sponges. Herein, we summarise the latest research progress on biological functions of circRNAs in digestive system cancers. This review serves as a synopsis of potential therapeutic targets and biological markers for digestive system cancer.

scholarly journals Biogenesis mechanisms of circular RNA can be categorized through feature extraction of a machine learning model

2019 ◽  
Vol 35 (23) ◽  
pp. 4867-4870
Author(s):  
Chengyu Liu ◽  
Yu-Chen Liu ◽  
Hsien-Da Huang ◽  
Wei Wang
Keyword(s):  
Feature Extraction ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Cpg Island ◽  
Cpg Islands ◽  
Circular Rna ◽  
Training Data ◽  
Supplementary Information ◽  
Circular Rnas ◽  
Genomic Locus

Abstract Motivation In recent years, multiple circular RNAs (circRNA) biogenesis mechanisms have been discovered. Although each reported mechanism has been experimentally verified in different circRNAs, no single biogenesis mechanism has been proposed that can universally explain the biogenesis of all tens of thousands of discovered circRNAs. Under the hypothesis that human circRNAs can be categorized according to different biogenesis mechanisms, we designed a contextual regression model trained to predict the formation of circular RNA from a random genomic locus on human genome, with potential biogenesis factors of circular RNA as the features of the training data. Results After achieving high prediction accuracy, we found through the feature extraction technique that the examined human circRNAs can be categorized into seven subgroups, according to the presence of the following sequence features: RNA editing sites, simple repeat sequences, self-chains, RNA binding protein binding sites and CpG islands within the flanking regions of the circular RNA back-spliced junction sites. These results support all of the previously reported biogenesis mechanisms of circRNA and solidify the idea that multiple biogenesis mechanisms co-exist for different subset of human circRNAs. Furthermore, we uncover a potential new links between circRNA biogenesis and flanking CpG island. We have also identified RNA binding proteins putatively correlated with circRNA biogenesis. Availability and implementation Scripts and tutorial are available at http://wanglab.ucsd.edu/star/circRNA. This program is under GNU General Public License v3.0. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals The Emerging Role of the Interactions between Circular RNAs and RNA-binding Proteins in Common Human Cancers

2021 ◽  
Vol 12 (17) ◽  
pp. 5206-5219
Author(s):  
Meng-Ping Jiang ◽  
Wen-Xiu Xu ◽  
Jun-Chen Hou ◽  
Qi Xu ◽  
Dan-Dan Wang ◽  
...  
Keyword(s):  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Circular Rnas ◽  
Human Cancers

scholarly journals An autoregulation loop in fust-1 for circular RNA regulation in Caenorhabditis elegans

2021 ◽  
Author(s):  
Dong Cao
Keyword(s):  
Caenorhabditis Elegans ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Exon Skipping ◽  
Circular Rna ◽  
Circular Rnas ◽  
Rna Regulation ◽  
Fused In Sarcoma ◽  
Specific Factors ◽  
Isoform B

Circular RNAs (circRNAs) are always expressed tissue-specifically, suggestive of specific factors that regulate their biogenesis. Here, taking advantage of available mutation strains of RNA binding proteins (RBPs) in Caenorhabditis elegans, I performed a screening of circRNA regulation in thirteen conserved RBPs. Among them, loss of FUST-1, the homolog of FUS (Fused in Sarcoma), caused downregulation of multiple circRNAs. By rescue experiments, I confirmed FUST-1 as a circRNA regulator. Further, I showed that FUST-1 regulates circRNA formation without affecting the levels of the cognate linear mRNAs. When recognizing circRNA pre-mRNAs, FUST-1 can affect both exon-skipping and circRNA in the same genes. Moreover, I identified an autoregulation loop in fust-1, where FUST-1, isoform a promotes the skipping of exon 5 of its own pre-mRNA, which produces FUST-1, isoform b with different N-terminal sequences. FUST-1, isoform a is the functional isoform in circRNA regulation. Although FUST-1, isoform b has the same functional domains as isoform a, it cannot regulate either exon-skipping or circRNA formation.

scholarly journals Integrated analysis of the functions and prognostic values of RNA binding proteins in colon adenocarcinoma

2020 ◽  
Author(s):  
Xinhong Liu ◽  
Fang Tan ◽  
Xingyao Long ◽  
Ruokun Yi ◽  
Dingyi Yang ◽  
...  
Keyword(s):  
Prognostic Model ◽  
Binding Proteins ◽  
Rna Binding ◽  
Prediction Models ◽  
Cox Regression ◽  
Rna Binding Proteins ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Cox Regression Analysis

Abstract Background RNA binding proteins (RBPs) play an important role in a variety of cancers. However, the role of RBPs in colorectal adenocarcinoma (COAD) has not been studied. Integrated analysis of RBPs will provide a better understanding of disease genesis and new insights into COAD treatment. Methods The gene expression data and corresponding clinical information for COAD were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis was used to screen for RBPs associated with COAD recurrence, and multivariate Cox proportional hazards regression analyses were used to identify genes that were associated with COAD recurrence. A nomogram was constructed to predict the recurrence of COAD, and a receiver operating characteristic (ROC) curve analysis was performed to determine the accuracy of the prediction models. The Human Protein Atlas database was used in prediction models to confirm the expression of key genes in COAD patients. Result A total of 177 differentially expressed RBPs was obtained, comprising 123 upregulated and 54 downregulated. GO and KEGG enrichment analysis showed that the differentially expressed RBPs were mainly related to mRNA metabolism, RNA processing and translation regulation. Seven RBP genes (TDRD6, POP1, TDRD7, PPARGC1A, LIN28B, LRRFIP2 and PNLDC1) were identified as prognosis-associated genes and were used to construct the prognostic model. Conclusion We constructed a COAD prognostic model through bioinformatics analysis, which indicated that prognostic model RBPs have a potential role in the diagnosis and prognosis of COAD. Moreover, the nomogram can effectively predict the 1-year, 3-year, and 5-year survival rate for COAD patients.

scholarly journals Integrated analysis of the functions and prognostic values of RNA-binding proteins in neuroblastoma

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260876
Author(s):  
Jun Yang ◽  
Jiaying Zhou ◽  
Cuili Li ◽  
Shaohua Wang
Keyword(s):  
Regression Analysis ◽  
Risk Score ◽  
Prognostic Model ◽  
Binding Proteins ◽  
Rna Binding ◽  
Risk Model ◽  
Cox Regression ◽  
Rna Binding Proteins ◽  
Differentially Expressed ◽  
Lasso Regression

Background Neuroblastoma (NB) is the most common solid tumor in children. NB treatment has made significant progress; however, given the high degree of heterogeneity, basic research findings and their clinical application to NB still face challenges. Herein, we identify novel prognostic models for NB. Methods We obtained RNA expression data of NB and normal nervous tissue from TARGET and GTEx databases and determined the differential expression patterns of RNA binding protein (RBP) genes between normal and cancerous tissues. Lasso regression and Cox regression analyses identified the five most important differentially expressed genes and were used to construct a new prognostic model. The function and prognostic value of these RBPs were systematically studied and the predictive accuracy verified in an independent dataset. Results In total, 348 differentially expressed RBPs were identified. Of these, 166 were up-regulated and 182 down-regulated RBPs. Two hubs RBPs (CPEB3 and CTU1) were identified as prognostic-related genes and were chosen to build the prognostic risk score models. Multivariate Cox analysis was performed on genes from univariate Cox regression and Lasso regression analysis using proportional hazards regression model. A five gene prognostic model: Risk score = (-0.60901*expCPEB3)+(0.851637*expCTU1) was built. Based on this model, the overall survival of patients in the high-risk subgroup was lower (P = 2.152e-04). The area under the curve (AUC) of the receiver-operator characteristic curve of the prognostic model was 0.720 in the TARGET cohort. There were significant differences in the survival rate of patients in the high and low-risk subgroups in the validation data set GSE85047 (P = 0.1237e-08), with the AUC 0.730. The risk model was also regarded as an independent predictor of prognosis (HR = 1.535, 95% CI = 1.368–1.722, P = 2.69E-13). Conclusions This study identified a potential risk model for prognosis in NB using Cox regression analysis. RNA binding proteins (CPEB3 and CTU1) can be used as molecular markers of NB.

Sign in / Sign up

Export Citation Format

Share Document