Integrated Analysis of RNA-Binding Proteins in Glioma

RNA-binding proteins (RBPs) play important roles in many cancer types. However, RBPs have not been thoroughly and systematically studied in gliomas. Global analysis of the functional impact of RBPs will provide a better understanding of gliomagenesis and new insights into glioma therapy. In this study, we integrated a list of the human RBPs from six sources—Gerstberger, SONAR, Gene Ontology project, Poly(A) binding protein, CARIC, and XRNAX—which covered 4127 proteins with RNA-binding activity. The RNA sequencing data were downloaded from The Cancer Genome Atlas (TCGA) (n = 699) and Chinese Glioma Genome Atlas (CGGA) (n = 325 + 693). We examined the differentially expressed genes (DEGs) using the R package DESeq2, and constructed a weighted gene co-expression network analysis (WGCNA) of RBPs. Furthermore, survival analysis was also performed based on the univariate and multivariate Cox proportional hazards regression models. In the WGCNA analysis, we identified a key module involved in the overall survival (OS) of glioblastomas. Survival analysis revealed eight RBPs (PTRF, FNDC3B, SLC25A43, ZC3H12A, LRRFIP1, HSP90B1, HSPA5, and BNC2) are significantly associated with the survival of glioblastoma patients. Another 693 patients within the CGGA database were used to validate the findings. Additionally, 3564 RBPs were classified into canonical and non-canonical RBPs depending on the domains that they contain, and non-canonical RBPs account for the majority (72.95%). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that some non-canonical RBPs may have functions in glioma. Finally, we found that the knockdown of non-canonical RBPs, PTRF, or FNDC3B can alone significantly inhibit the proliferation of LN229 and U251 cells. Simultaneously, RNA Immunoprecipitation (RIP) analysis indicated that PTRF may regulate cell growth and death- related pathways to maintain tumor cell growth. In conclusion, our findings presented an integrated view to assess the potential death risks of glioblastoma at a molecular level, based on the expression of RBPs. More importantly, we identified non-canonical RNA-binding proteins PTRF and FNDC3B, showing them to be potential prognostic biomarkers for glioblastoma.

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

10.21203/rs.3.rs-29330/v1 ◽

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.

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Integrated analysis of the roles and prognostic value of RNA binding proteins in lung adenocarcinoma

PeerJ ◽

10.7717/peerj.8509 ◽

2020 ◽

Vol 8 ◽

pp. e8509 ◽

Cited By ~ 4

Author(s):

Wei Li ◽

Na Li ◽

Lina Gao ◽

Chongge You

Keyword(s):

Lung Adenocarcinoma ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

Malignant Tumors ◽

Prognostic Significance ◽

Rna Degradation ◽

The Cancer Genome Atlas ◽

Integrated Analysis ◽

Poor Overall Survival

Lung cancer is the top cause of carcinoma-associated deaths worldwide. RNA binding proteins (RBPs) dysregulation has been reported in various malignant tumors, and that dysregulation is closely associated with tumorigenesis and tumor progression. However, little is known about the roles of RBPs in lung adenocarcinoma (LUAD). In this study, we downloaded the RNA sequencing data of LUAD from The Cancer Genome Atlas (TCGA) database and determined the differently expressed RBPs between normal and cancer tissues. We then performed an integrative analysis to explore the expression and prognostic significance of these RBPs. A total of 164 differently expressed RBPs were identified, including 40 down-regulated and 124 up-regulated RBPs. Pathway and Gene ontology (GO) analysis indicated that the differently expressed RBPs were mainly related to RNA processing, RNA metabolic process, RNA degradation, RNA transport, splicing, localization, regulation of translation, RNA binding, TGF-beta signaling pathway, mRNA surveillance pathway, and aminoacyl-tRNA biosynthesis. Survival analysis revealed that the high expression of BOP1 or GNL3 or WDR12 or DCAF13 or IGF2BP3 or IGF2BP1 were associated with poor overall survival (OS). Conversely, overexpression of KHDRBS2/SMAD predicted high OS in these patients. ROC curve analysis showed that the eight hub genes with a better diagnostic accuracy to distinguish lung adenocarcinoma. The results provided novel insights into the pathogenesis of LUAD and the development of treatment targets and prognostic molecular markers.

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Comprehensive Analysis of the Functions and Prognostic Value of RNA-Binding Proteins in Thyroid Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.625007 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yue Ma ◽

Shi Yin ◽

Xiao-feng Liu ◽

Jing Hu ◽

Ning Cai ◽

...

Keyword(s):

Gene Expression ◽

Thyroid Cancer ◽

Gene Expression Data ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Integrated Analysis ◽

Expression Data

RNA binding proteins (RBPs) have been proved to play pivotal roles in a variety types of tumors. However, there is no convincible evidence disclosing the functions of RBPs in thyroid cancer (THCA) thoroughly and systematically. Integrated analysis of the functional and prognostic effect of RBPs help better understanding tumorigenesis and development in thyroid and may provide a novel therapeutic method for THCA. In this study, we obtained a list of human RBPs from Gerstberger database, which covered 1,542 genes encoding RBPs. Gene expression data of THCA was downloaded from The Cancer Genome Atlas (TCGA, n = 567), from which we extracted 1,491 RBPs’ gene expression data. We analyzed differentially expressed RBPs using R package “limma”. Based on differentially expressed RBPs, we constructed protein-protein interaction network and the GO and KEGG pathway enrichment analyses were carried out. We found six RBPs (AZGP1, IGF2BP2, MEX3A, NUDT16, NUP153, USB1) independently associated with prognosis of patients with thyroid cancer according to univariate and multivariate Cox proportional hazards regression models. The survival analysis and risk score analysis achieved good performances from this six-gene prognostic model. Nomogram was constructed to guide clinical decision in practice. Finally, biological experiments disclosed that NUP153 and USB1 can significantly impact cancer cell proliferation and migration. In conclusion, our research provided a new insight of thyroid tumorigenesis and development based on analyses of RBPs. More importantly, the six-gene model may play an important role in clinical practice in the future.

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Identification of Dynamic RNA-Binding Proteins Uncovers a Cpeb4-Controlled Regulatory Cascade During Pathological Cell Growth of Cardiomyocytes

SSRN Electronic Journal ◽

10.2139/ssrn.3647257 ◽

2020 ◽

Author(s):

Eva Riechert ◽

Frank Stein ◽

Thomas Schwarzl ◽

Thileepan Sekaran ◽

Lonny Jürgensen ◽

...

Keyword(s):

Cell Growth ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

Regulatory Cascade

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Double-stranded RNA-binding Proteins and the Control of Protein Synthesis and Cell Growth

Cold Spring Harbor Symposia on Quantitative Biology ◽

10.1101/sqb.2001.66.485 ◽

2001 ◽

Vol 66 (0) ◽

pp. 485-498 ◽

Cited By ~ 16

Author(s):

L.M. PARKER ◽

I. FIERRO-MONTI ◽

T.W. REICHMAN ◽

S. GUNNERY ◽

M.B. MATHEWS

Keyword(s):

Protein Synthesis ◽

Cell Growth ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

Double Stranded Rna

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AU-rich RNA binding proteins in hematopoiesis and leukemogenesis

Blood ◽

10.1182/blood-2011-07-347237 ◽

2011 ◽

Vol 118 (22) ◽

pp. 5732-5740 ◽

Cited By ~ 35

Author(s):

Maria Baou ◽

John D. Norton ◽

John J. Murphy

Keyword(s):

Cell Growth ◽

Regulatory Networks ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

Binding Protein ◽

Rna Binding Protein ◽

Growth And Survival ◽

Hematopoietic Malignancies ◽

Gene Regulatory

Abstract Posttranscriptional mechanisms are now widely acknowledged to play a central role in orchestrating gene-regulatory networks in hematopoietic cell growth, differentiation, and tumorigenesis. Although much attention has focused on microRNAs as regulators of mRNA stability/translation, recent data have highlighted the role of several diverse classes of AU-rich RNA-binding protein in the regulation of mRNA decay/stabilization. AU-rich elements are found in the 3′-untranslated region of many mRNAs that encode regulators of cell growth and survival, such as cytokines and onco/tumor-suppressor proteins. These are targeted by a burgeoning number of different RNA-binding proteins. Three distinct types of AU-rich RNA binding protein (ARE poly-U–binding degradation factor-1/AUF1, Hu antigen/HuR/HuA/ELAVL1, and the tristetraprolin/ZFP36 family of proteins) are essential for normal hematopoiesis. Together with 2 further AU-rich RNA-binding proteins, nucleolin and KHSRP/KSRP, the functions of these proteins are intimately associated with pathways that are dysregulated in various hematopoietic malignancies. Significantly, all of these AU-rich RNA-binding proteins function via an interconnected network that is integrated with microRNA functions. Studies of these diverse types of RNA binding protein are providing novel insight into gene-regulatory mechanisms in hematopoiesis in addition to offering new opportunities for developing mechanism-based targeted therapeutics in leukemia and lymphoma.

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Integrated Analysis of RNA-Binding Proteins Associated With the Prognosis and Immunosuppression in Squamous Cell Carcinoma of Head and Neck

Frontiers in Genetics ◽

10.3389/fgene.2020.571403 ◽

2021 ◽

Vol 11 ◽

Author(s):

Guangsheng Hu ◽

Qingshan Jiang ◽

Lijun Liu ◽

Hong Peng ◽

Yaya Wang ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Head And Neck ◽

Risk Score ◽

Squamous Cell ◽

Binding Proteins ◽

Rna Binding ◽

Risk Model ◽

Rna Binding Proteins ◽

Integrated Analysis

RNA-binding proteins (RBPs) interacting with target RNAs play essential roles in RNA metabolism at the post-transcription level. Perturbations of RBPs can accelerate cancer development and cause dysregulation of the immune cell function and activity leading to evade immune destruction of cancer cells. However, few studies have systematically analyzed the potential prognostic value and functions of RBPs in squamous cell carcinoma of head and neck (SCCHN). Here, for the first time, we comprehensively identified 92 differentially expressed RBPs from The Cancer Genome Atlas (TCGA) database. In the training set, a prognosis risk model was constructed with six RBPs, including NCBP2, MKRN3, MRPL47, AZGP1, IGF2BP2, and EZH2, and validated by the TCGA test set, the TCGA all set, and the GEO data set. In addition, the risk score was related to the clinical stage, T classification, and N classification. Furthermore, the high-risk score was significantly correlated with immunosuppression, and low expression of EZH2 and AZGP1 and high expression of IGF2BP2 were the main factors. Thus, the risk model may serve as a prognostic signature and offer highlights for individualized immunotherapy in SCCHN patients.

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Identification of the Functions and Prognostic Values of RNA Binding Proteins in Bladder Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.574196 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yue Wu ◽

Zheng Liu ◽

Xian Wei ◽

Huan Feng ◽

Bintao Hu ◽

...

Keyword(s):

Bladder Cancer ◽

Risk Score ◽

Binding Proteins ◽

Rna Binding ◽

Rna Binding Proteins ◽

Characteristic Curve ◽

Regulatory Protein ◽

Receiver Operator Characteristic Curve ◽

High Risk Group ◽

The Cancer Genome Atlas

Post-transcriptional regulation plays a leading role in gene regulation and RNA binding proteins (RBPs) are the most important posttranscriptional regulatory protein. RBPs had been found to be abnormally expressed in a variety of tumors and is closely related to its occurrence and progression. However, the exact mechanism of RBPs in bladder cancer (BC) is unknown. We downloaded transcriptomic data of BC from the Cancer Genome Atlas (TCGA) database and used bioinformatics techniques for subsequent analysis. A total of 116 differentially expressed RBPs were selected, among which 61 were up-regulated and 55 were down-regulated. We then identified 12 prognostic RBPs including CTIF, CTU1, DARS2, ENOX1, IGF2BP2, LIN28A, MTG1, NOVA1, PPARGC1B, RBMS3, TDRD1, and ZNF106, and constructed a prognostic risk score model. Based on this model we found that patients in the high-risk group had poorer overall survival (P < 0.001), and the area under the receiver operator characteristic curve for this model was 0.677 for 1 year, 0.697 for 3 years, and 0.709 for 5 years. Next, we drew a nomogram based on the risk score and other clinical variables, which showed better predictive performance. Our findings contribute to a better understanding of the pathogenesis, progression and metastasis of BC. The model of these 12 genes has good predictive value and may have good prospects for improving clinical treatment regimens and patient prognosis.

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