scholarly journals The Function and Prognostic Value of RNA-Binding Proteins in Colorectal Adenocarcinoma Were Analyzed Based on Bioinformatics of Smart Medical Big Data

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Haoran Zhao ◽  
Peng Wang ◽  
Haishi Liu ◽  
Yueyang Li ◽  
Qian Luo ◽  
...  
Keyword(s):  
Big Data ◽  
Prognostic Value ◽  
Prognostic Model ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Biological Effects ◽  
Test Group ◽  
Differentially Expressed ◽  
Medical Big Data

Colon cancer is the third most frequent cancer in the world and is mainly adenocarcinoma in terms of pathological type. It has been confirmed that the dysregulation of RNA-binding proteins (RBPs) significantly participates in the occurrence and development of numerous malignant tumors. Therefore, we analyzed the RBPs associated with colon adenocarcinoma (COAD) to assess their possible biological effects and prognostic value. A total of 398 COAD tissue datasets and 39 normal tissue datasets were retrieved from the TCGA data resource and screened out the RBPs, which are differentially expressed between tumor tissues and nontumor tissues. Then, bioinformatics analyses based on smart medical big data were conducted on these RBPs. Overall, 181 differentially expressed RBPs were uncovered, consisting of 121 upregulated RBPs and 60 downregulated RBPs. Finally, we selected 7 prognostic-related RBPs with research prospects and constructed a prognostic model according to the median risk score. There were remarkable differences in OS between the high-risk and low-risk groups. In addition, the performance of the prognostic model was evaluated and verified with other COAD patient data in the TCGA database. The results showed that the area under the ROC curve (AUC) for the train group was 0.744 and the one for the test group was 0.661, confirming that the model assesses patients’ prognosis to some extent. And based on 7 hub RBPs, we constructed a nomogram as a reference for evaluating the survival rate of COAD patients.

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.

scholarly journals A Novel Prognostic Model In Oral Squamous Carcinoma: The Functions And Prognostic Values Of Rna Binding Proteins

2020 ◽  
Author(s):  
Yingjuan Lu ◽  
Yongcong Yan ◽  
Mo Liu ◽  
Yancan Liang ◽  
Yushan Ye ◽  
...  
Keyword(s):  
Risk Score ◽  
Prognostic Model ◽  
Binding Proteins ◽  
Rna Binding ◽  
Cox Regression ◽  
Rna Binding Proteins ◽  
Squamous Carcinoma ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Oral Squamous Carcinoma

Abstract Background: The biological roles and clinical significance of RNA-binding proteins (RBPs) in oral squamous cell carcinoma (OSCC) are not fully understood. We investigated the prognostic value of RBPs in OSCC by several bioinformatic strategies.Methods: OSCC data were obtained from a public online database, the Limma R package was used to identify differentially expressed RBPs, and functional enrichment analysis was performed to elucidate the biological functions of the above RBPs in OSCC. We performed protein-protein interaction (PPI) network and Cox regression analyses to extract prognosis-related hub RBPs. Next, we established and validated a prognostic model based on the hub RBPs by Cox regression and risk score analyses.Results: We found that the differentially expressed RBPs were closely related to the defence response to virus and multiple RNA processes. We obtained ten prognosis-related hub RBPs (ZC3H12D, OAS2, INTS10, ACO1, PCBP4, RNASE3, PTGES3L-AARSD1, RNASE13, DDX4, and PCF11) and effectively predicted the overall survival of OSCC patients. The area under the ROC curve (AUC) of the risk score model was 0.781, suggesting that our model had good prognostic performance. Finally, we built a nomogram integrating the ten RBPs. The internal validation cohort results showed a reliable predictive capability of the nomogram for OSCC.Conclusions: We established a novel ten-RBP-based model for OSCC that could enable precise therapeutic targets in the future.

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 Construction And Verification of A Prognostic Model Related To RNA-Binding Proteins In Uterine Corpus Endometrial Carcinoma

2021 ◽  
Author(s):  
Yukun Jia ◽  
Zhan Peng ◽  
Guangye Wang
Keyword(s):  
Endometrial Carcinoma ◽  
Risk Score ◽  
Prognostic Model ◽  
Binding Proteins ◽  
Rna Binding ◽  
Cox Regression ◽  
Rna Binding Proteins ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: RNA binding proteins (RBP) plays an important role in post-transcriptional regulation. Although the dysregulation of RBP expression is closely related to the occurrence and metastasis of a variety of tumors, there are few reports on RBP in endometrial carcinoma (UCEC). This study aims to establish a RBP-related prognostic model of UCEC. Methods: We downloaded UCEC gene expression and clinical information data from the Cancer Genome Atlas (TCGA) and GEO database, and determined RBPs that are differentially expressed between tumors and normal tissues. Then, used functional enrichment analysis to analyze the biological functions of the differentially expressed RBP. Used univariate Cox regression analysis to screen prognostic-related RBP and construct a prognostic model. Subsequently, Kaplan-Meier and recipient operating characteristic (ROC) curves were drawn to evaluate the model. Finally, established a nomogram. Results: This study identified 531 differentially expressed RBPs, including 325 up-regulated and 206 down-regulated RBPs, respectively. Then six independent prognostic-related RBPs (REXO2, MARS2, XPO5, YBX1, YBX2, and CELF4) were used to construct a prognostic model. According to this model, the overall survival (OS) of patients in the high-risk score group was significantly lower than that of the low-risk score group. In the training queue and the test queue, the areas under the ROC curve were 0.799 and 0.669, respectively, showing the moderate predictive value of the model. Conclusion: We have developed and validated the RBP-related prognostic model.

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 Biological functions and prognostic value of RNA Binding Proteins in clear cell Renal Cell Carcinoma

2020 ◽  
Vol 11 (22) ◽  
pp. 6591-6600 ◽  
Author(s):  
Zhenpeng Zhu ◽  
Anbang He ◽  
Lanruo Lin ◽  
Chunru Xu ◽  
Tianyu Cai ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Value ◽  
Binding Proteins ◽  
Rna Binding ◽  
Clear Cell ◽  
Rna Binding Proteins ◽  
Biological Functions ◽  
Cell Renal Cell Carcinoma

scholarly journals The expression and prognostic value of RNA binding proteins in clear cell renal cell carcinoma

2020 ◽  
Vol 9 (12) ◽  
pp. 7415-7431
Author(s):  
Can-Xuan Li ◽  
Jie Chen ◽  
Zheng-Guang Xu ◽  
Wing-Keung Yiu ◽  
Yen-Ting Lin
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Value ◽  
Binding Proteins ◽  
Rna Binding ◽  
Clear Cell ◽  
Rna Binding Proteins ◽  
Cell Renal Cell Carcinoma
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