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

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8509 ◽  
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.

scholarly journals Integrated analysis of the functions and prognostic values of RNA binding proteins in hepatocellular carcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zeng-Hong Wu ◽  
Hong-Ming Huang ◽  
Dong-Liang Yang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Influenza A ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Malignant Tumors ◽  
Rna Degradation ◽  
Integrated Analysis ◽  
Sequencing Data ◽  
Herpes Simplex Virus 1

Abstract Background Hepatocellular carcinoma (HCC), one of the most common malignant tumors worldwide, ranks as the fifth most common cancer and has been the second most frequent cause of cancer-related death. RNA binding proteins (RBPs) are proteins that interact with different classes of RNA and are commonly detected in cells. Methods We used RNA sequencing data from TCGA to display dysfunctional RBPs microenvironments and provide potential useful biomarkers for HCC diagnosis and prognosis. Results 330 differently expressed RBPs (208 upregulated and 122 downregulated) were identified. KEGG were mainly enriched in RNA degradation, Influenza A, Hepatitis C, RIG-I-like receptor signaling pathway, Herpes simplex virus 1 infection and RNA transport. CBioPortal results demonstrated that these genes were altered in 50 samples out of 357 HCC patients (14%) and the amplification of BRCA1 was the largest frequent copy-number alteration. Conclusion Based on the online database, we identified novel RBPs markers for the prognosis of hepatocellular carcinoma.

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 Prognosis-Associated RNA-Binding Protein Genes and Candidate Drugs in Renal Papillary Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Silin Jiang ◽  
Xiaohan Ren ◽  
Shouyong Liu ◽  
Zhongwen Lu ◽  
Aiming Xu ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Rna Binding ◽  
Cox Regression ◽  
Rna Binding Proteins ◽  
Biological Effects ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Poor Overall Survival ◽  
Cox Regression Analysis

RNA-binding proteins (RBPs) play significant roles in various cancer types. However, the functions of RBPs have not been clarified in renal papillary cell carcinoma (pRCC). In this study, we identified 31 downregulated and 89 upregulated differentially expressed RBPs on the basis of the cancer genome atlas (TCGA) database and performed functional enrichment analyses. Subsequently, through univariate Cox, random survival forest, and multivariate Cox regression analysis, six RBPs of SNRPN, RRS1, INTS8, RBPMS2, IGF2BP3, and PIH1D2 were screened out, and the prognostic model was then established. Further analyses revealed that the high-risk group had poor overall survival. The area under the curve values were 0.87 and 0.75 at 3 years and 0.78 and 0.69 at 5 years in the training set and test set, respectively. We then plotted a nomogram on the basis of the six RBPs and tumor stage with the substantiation in the TCGA cohort. Moreover, we selected two intersectant RBPs and evaluate their biological effects by GSEA and predicted three drugs, including STOCK1N-28457, pyrimethamine, and trapidil by using the Connectivity Map. Our research provided a novel insight into pRCC and improved the determination of prognosis and individualized therapeutic strategies.

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

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.

scholarly journals Integrated Analysis of RNA-Binding Proteins in Glioma

Cancers ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 892 ◽  
Author(s):  
Zhixing Wang ◽  
Wanjun Tang ◽  
Jiangang Yuan ◽  
Boqin Qiang ◽  
Wei Han ◽  
...  
Keyword(s):  
Gene Ontology ◽  
Survival Analysis ◽  
Cell Growth ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Global Analysis ◽  
The Cancer Genome Atlas ◽  
Integrated Analysis ◽  
Genome Atlas

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.

scholarly journals Clinical characteristics and prognostic value of MEX3A mRNA in liver cancer

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8252 ◽  
Author(s):  
Dingquan Yang ◽  
Yan Jiao ◽  
Yanqing Li ◽  
Xuedong Fang
Keyword(s):  
Liver Cancer ◽  
Clinical Data ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Prognostic Significance ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Diagnostic Ability ◽  
Kaplan Meier ◽  
Cox Analysis

Background MEX3A is an RNA-binding proteins (RBPs) that promotes the proliferation, invasion, migration and viability of cancer cells. The aim of this study was to explore the clinicopathological characteristics and prognostic significance of MEX3A mRNA expression in liver cancer. Methods RNA-Seq and clinical data were collected from The Cancer Genome Atlas (TCGA). Boxplots were used to represent discrete variables of MEX3A. Chi-square tests were used to analyze the correlation between clinical features and MEX3A expression. Receiver operating characteristic (ROC) curves were used to confirm diagnostic ability. Independent prognostic ability and values were assessed using Kaplan–Meier curves and Cox analysis. Results We acquired MEX3A RNA-Seq from 50 normal liver tissues and 373 liver cancer patients along with clinical data. We found that MEX3A was up-regulated in liver cancer which increased according to histological grade (p < 0.001). MEX3A showed moderate diagnostic ability for liver cancer (AUC = 0.837). Kaplan–Meier curves and Cox analysis revealed that the high expression of MEX3A was significantly associated with poor survival (OS and RFS) (p < 0.001). Moreover, MEX3A was identified as an independent prognostic factor of liver cancer (p < 0.001). Conclusions MEX3A expression shows promise as an independent predictor of liver cancer prognosis.

scholarly journals Identification of molecular markers associated with the progression and prognosis of lung adenocarcinoma:a bioinformatic study

2020 ◽  
Author(s):  
Kexin Du ◽  
Xioahan Wang
Keyword(s):  
Survival Rate ◽  
Lung Adenocarcinoma ◽  
Malignant Tumors ◽  
Prognostic Significance ◽  
The Cancer Genome Atlas ◽  
Venn Diagram ◽  
Receptor Interaction ◽  
Average Score ◽  
High Survival ◽  
Overlapping Genes

Abstract Objective: For the identification of genes of prognostic significance related to tumor microenvironment (TME) in lung adenocarcinoma.Methods and Materials: Transcriptome data and clinical data of lung adenocarcinoma originated from the Cancer Genome Atlas (TCGA) database. Immune scores and stromal scores were calculated by “Estimation of Stromal and Immune cells in Malignant Tumors using Expression data” algorithm. Based on these calculated scores, the samples were classified as high and low score groups. The average score of respective gene in different groups was calculated. A heat map was created to screen out genes exhibiting differential expressions. The interaction of up-regulated differentially expressed genes (DEGs) and down-regulated DEGs was harvested from a Venn diagram and then covered in the overlapping genes. The core genes influencing prognosis of lung adenocarcinoma were screened out by function enrichment analysis, protein-protein interaction network analysis and Kaplan-Meier (K-M) method on the overlapping genes.Results: A total of 515 samples of lung adenocarcinoma were harvested from TCGA database. As revealed from the results, a high immune score was related to a high survival rate, while the matrix did not show significant relationships to survival rate. A total of 775 DEGs and 367 overlapping genes were harvested. The functions of these overlapping genes were tightly correlated with DEGs and immune response and were noticeably improved in cytokine-cytokine receptor interaction and chemokine signaling pathway. Eight genes, namely, CCR5, CCR2, CCL14, GNRH2, PKHD1L1, MS4A1, FCER2 and FDCSP, were correlated with prognosis of lung adenocarcinoma.Conclusion: The genes and pathways affecting prognosis of lung adenocarcinoma were screened out, which offer ideas for subsequent study on lung adenocarcinoma.

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

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.

scholarly journals Identification and Validation of a Novel RNA-Binding Protein-Related Gene-Based Prognostic Model for Multiple Myeloma

2021 ◽  
Vol 12 ◽  
Author(s):  
Wei Wang ◽  
Shi-wen Xu ◽  
Xia-yin Zhu ◽  
Qun-yi Guo ◽  
Min Zhu ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Rna Binding ◽  
Cox Regression ◽  
Rna Binding Proteins ◽  
Prognostic Significance ◽  
Staging System ◽  
The Cancer Genome Atlas ◽  
Prognostic Signature ◽  
Major Pathway ◽  
Risk Status

BackgroundMultiple myeloma (MM) is a malignant hematopoietic disease that is usually incurable. RNA-binding proteins (RBPs) are involved in the development of many tumors, but their prognostic significance has not been systematically described in MM. Here, we developed a prognostic signature based on eight RBP-related genes to distinguish MM cohorts with different prognoses.MethodAfter screening the differentially expressed RBPs, univariate Cox regression was performed to evaluate the prognostic relevance of each gene using The Cancer Genome Atlas (TCGA)-Multiple Myeloma Research Foundation (MMRF) dataset. Lasso and stepwise Cox regressions were used to establish a risk prediction model through the training set, and they were validated in three Gene Expression Omnibus (GEO) datasets. We developed a signature based on eight RBP-related genes, which could classify MM patients into high- and low-score groups. The predictive ability was evaluated using bioinformatics methods. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and gene set enrichment analyses were performed to identify potentially significant biological processes (BPs) in MM.ResultThe prognostic signature performed well in the TCGA-MMRF dataset. The signature includes eight hub genes: HNRNPC, RPLP2, SNRPB, EXOSC8, RARS2, MRPS31, ZC3H6, and DROSHA. Kaplan–Meier survival curves showed that the prognosis of the risk status showed significant differences. A nomogram was constructed with age; B2M, LDH, and ALB levels; and risk status as prognostic parameters. Receiver operating characteristic (ROC) curve, C-index, calibration analysis, and decision curve analysis (DCA) showed that the risk module and nomogram performed well in 1, 3, 5, and 7-year overall survival (OS). Functional analysis suggested that the spliceosome pathway may be a major pathway by which RBPs are involved in myeloma development. Moreover, our signature can improve on the R-International Staging System (ISS)/ISS scoring system (especially for stage II), which may have guiding significance for the future.ConclusionWe constructed and verified the 8-RBP signature, which can effectively predict the prognosis of myeloma patients, and suggested that RBPs are promising biomarkers for MM.

scholarly journals Changes in mRNA abundance drive shuttling of RNA binding proteins, linking cytoplasmic RNA degradation to transcription

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Sarah Gilbertson ◽  
Joel D Federspiel ◽  
Ella Hartenian ◽  
Ileana M Cristea ◽  
Britt Glaunsinger
Keyword(s):  
Gene Expression ◽  
Rna Polymerase Ii ◽  
Mrna Decay ◽  
Binding Proteins ◽  
Rna Binding ◽  
Nuclear Translocation ◽  
Rna Binding Proteins ◽  
Binding Protein ◽  
Protein Localization ◽  
Rna Degradation

Alterations in global mRNA decay broadly impact multiple stages of gene expression, although signals that connect these processes are incompletely defined. Here, we used tandem mass tag labeling coupled with mass spectrometry to reveal that changing the mRNA decay landscape, as frequently occurs during viral infection, results in subcellular redistribution of RNA binding proteins (RBPs) in human cells. Accelerating Xrn1-dependent mRNA decay through expression of a gammaherpesviral endonuclease drove nuclear translocation of many RBPs, including poly(A) tail-associated proteins. Conversely, cells lacking Xrn1 exhibited changes in the localization or abundance of numerous factors linked to mRNA turnover. Using these data, we uncovered a new role for relocalized cytoplasmic poly(A) binding protein in repressing recruitment of TATA binding protein and RNA polymerase II to promoters. Collectively, our results show that changes in cytoplasmic mRNA decay can directly impact protein localization, providing a mechanism to connect seemingly distal stages of gene expression.

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