Comprehensive Analysis of the Functions and Prognostic Value of RNA-Binding Proteins in Thyroid Cancer.
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SUBMITTER: Ma Y
PROVIDER: S-EPMC8010172 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:PurposeTo investigate the prognostic value and biological function of RNA binding proteins (RBPs) in stomach adenocarcinoma (STAD).Materials and methodsDatasets of the differentially expressed genes (DEGs) were downloaded from the TCGA-based (The Cancer Genome Atlas) GEPIA database, from which the differentially expressed RBPs were determined. Functions and prognostic values of these determined RBPs were systematically investigated by a series of methods in bioinformatics analysis. In addition, transwell assays were performed to explore the effect of PTBP1 in STAD cells.ResultsThree hundred and sixty-two differentially expressed RBPs were determined, with 331 up-regulated and 31 down-regulated. Seven RBPs (PTBP1, PPIH, SMAD5, MSI2, RBM15, MRPS17, and ADAT3) were identified to be prognosis-related and adopted to construct a prognostic model. Compared with low-risk patients in TCGA training cohort, TCGA testing cohort and GEO cohort, high-risk patients had poorer overall survival (OS). The area under the ROC curves of this prognostic model were 0.804, 0.644 and 0.581 for TCGA training cohort, TCGA testing cohort and GEO cohort, respectively, justifying itself as a good prognostic model with reliable predictive ability. Using the seven identified RBPs, we then constructed a nomogram to generate a clinical utility model. The regulatory networks and functions of the seven RBPs were then investigated, the results of which demonstrated that MRPS17 and PTBP1 reduced the number of infiltrated immune cells. In-vitro experiments showed that the downregulation of PTBP1 weakened the migration and invasion capability of AGS and HGC27 cells.ConclusionThe seven-gene signature can be used as a reliable STAD prognostic biomarker, and these findings help us better understand the prognostic roles and functions of RBPs in STAD.
| S-EPMC7942957 | biostudies-literature
Project description:Early detection and accurate evaluation were both critical to improving the prognosis of clear cell Renal Cell Carcinoma (ccRCC) patients. More importantly, RNA Binding Proteins (RBPs) play a vital role in the tumorigenesis and progression of numerous cancers. However, the relationship between RBPs and ccRCC is still unclear. Exploring the potential biological functions of RBPs in ccRCC and establishing a prognostic signature to predict the survival probability remains meaningful. In this study, transcriptome profiling and the corresponding clinical information were obtained from the TCGA database, GEO database, and ICGC database. By using the "edgeR" R package, 200 DERBPs were found, including 128 up-regulated and 72 down-regulated RBPs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that DERBPs were mainly involved in regulating transcriptional processes and metabolism. Furthermore, there were 4 hub genes (RPS2, RPS14, RPS20, and RPLP0) were found in the PPI network, which may play vital biological roles among those DERBPs. Then we used LASSO regression to construct a prognostic signature and validated the signature in the GEO and ICGC cohort. The time-dependent receiver operating characteristic (ROC) curve showed that the signature could accurately predict the prognosis of ccRCC patients. Then we established a nomogram, and the calibration curve and ROC curve showed that the nomogram could accurately predict 1-year, 3-year, and 5-year overall survival (OS) of ccRCC patients (The AUC value: 0.871, 0.829, and 0.816). In conclusion, we constructed a 10-RBPs-based prognostic signature integrating clinical parameters to predict the prognosis of ccRCC patients. The prognostic signature based on the differentially expressed RBPs (DERBPs) might serve as promising diagnostic and prognostic biomarkers in ccRCC.
| S-EPMC7545679 | biostudies-literature
Project description:Background and Purpose: Breast cancer is one of the leading causes of death among women. RNA binding proteins (RBPs) play a vital role in the progression of many cancers. Functional investigation of RBPs may contribute to elucidating the mechanisms underlying tumor initiation, progression, and invasion, therefore providing novel insights into future diagnosis, treatment, and prognosis. Methods: We downloaded RNA sequencing data from the cancer genome atlas (TCGA) by UCSC Xena and identified relevant RBPs through an integrated bioinformatics analysis. We then analyzed biological processes of differentially expressed genes (DEGs) by DAVID, and established their interaction networks and performed pathway analysis through the STRING database to uncover potential biological effects of these RBPs. We also explored the relationship between these RBPs and the prognosis of breast cancer patients. Results: In the present study, we obtained 1092 breast tumor samples and 113 normal controls. After data analysis, we identified 90 upregulated and 115 downregulated RBPs in breast cancer. GO and KEGG pathway analysis indicated that these significantly changed genes were mainly involved in RNA processing, splicing, localization and RNA silencing, DNA transposition regulation and methylation, alkylation, mitochondrial gene expression, and transcription regulation. In addition, some RBPs were related to histone H3K27 methylation, estrogen response, inflammatory mediators, and translation regulation. Our study also identified five RBPs associated with breast cancer prognosis. Survival analysis found that overexpression of DCAF13, EZR, and MRPL13 showed worse survival, but overexpression of APOBEC3C and EIF4E3 showed better survival. Conclusion: In conclusion, we identified key RBPs of breast cancer through comprehensive bioinformatics analysis. These RBPs were involved in a variety of biological and molecular pathways in breast cancer. Furthermore, we identified five RBPs as a potential prognostic biomarker of breast cancer. Our study provided novel insights to understand breast cancer at a molecular level.
| S-EPMC6405693 | biostudies-literature
Project description: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.
| S-EPMC8258248 | biostudies-literature
Project description:BackgroundNeuroblastoma (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.MethodsWe 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.ResultsIn 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).ConclusionsThis 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.
| S-EPMC8654225 | biostudies-literature
Project description: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.
| S-EPMC7007976 | biostudies-literature
Project description:BackgroundHepatocellular 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.MethodsWe used RNA sequencing data from TCGA to display dysfunctional RBPs microenvironments and provide potential useful biomarkers for HCC diagnosis and prognosis.Results330 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.ConclusionBased on the online database, we identified novel RBPs markers for the prognosis of hepatocellular carcinoma.
| S-EPMC8204501 | biostudies-literature
Project description:BACKGROUND:N6-methyladenosine (m6A) is the most prevalent RNA modification. While the role of m6A in prostate cancer remains unknown. We aim to measure the effects of m6A methylation regulatory genes during the development and progression of prostate cancer. METHODS:We collected transcriptome information and gene-level alteration data from The Cancer Genome Atlas datasets. The log-rank test and Cox regression model were used to examine the prognosis value of m6A methylation regulatory genes of prostate cancer. RESULTS:We discovered that most of m6A methylation regulators were highly expressed in aggressive prostate cancer. Univariable and multivariable Cox regression results showed that the expression of Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3), Heterogeneous nuclear ribonucleoproteins A2/B1 (HNRNPA2B1) and N6-adenosine-methyltransferase non-catalytic subunit (METTL14) and copy number variant of AlkB Homolog 5 (ALKBH5) were considerably associated with a recurrence-free survival of prostate cancer. Furthermore, a high level of m6A methylation in mRNA promotes the progression of prostate cancer via regulating subcellular protein localization. CONCLUSION:Patients with a high level of mRNA methylation resulted from overexpression of reader proteins and methyltransferase complexes had poor survival benefits through influencing protein subcellular location in prostate cancer.
| S-EPMC7425456 | biostudies-literature
Project description:Lung cancer is the leading cause of cancer-related deaths worldwide. Dysregulation of RNA binding proteins (RBPs) has been found in a variety of cancers and is related to oncogenesis and progression. However, the functions of RBPs in lung squamous cell carcinoma (LUSC) remain unclear. In this study, we obtained gene expression data and corresponding clinical information for LUSC from The Cancer Genome Atlas (TCGA) database, identified aberrantly expressed RBPs between tumors and normal tissue, and conducted a series of bioinformatics analyses to explore the expression and prognostic value of these RBPs. A total of 300 aberrantly expressed RBPs were obtained, comprising 59 downregulated and 241 upregulated RBPs. Functional enrichment analysis indicated that the differentially expressed RBPs were mainly associated with mRNA metabolic processes, RNA processing, RNA modification, regulation of translation, the TGF-beta signaling pathway, and the Toll-like receptor signaling pathway. Nine RBP genes (A1CF, EIF2B5, LSM1, LSM7, MBNL2, RSRC1, TRMU, TTF2, and ZCCHC5) were identified as prognosis-associated hub genes by univariate, least absolute shrinkage and selection operator (LASSO), Kaplan-Meier survival, and multivariate Cox regression analyses, and were used to construct the prognostic model. Further analysis demonstrated that high risk scores for patients were significantly related to poor overall survival according to the model. The area under the time-dependent receiver operator characteristic curve of the prognostic model was 0.712 at 3 years and 0.696 at 5 years. We also developed a nomogram based on nine RBP genes, with internal validation in the TCGA cohort, which showed a favorable predictive efficacy for prognosis in LUSC. Our results provide novel insights into the pathogenesis of LUSC. The nine-RBP gene signature showed predictive value for LUSC prognosis, with potential applications in clinical decision-making and individualized treatment.
| S-EPMC7066120 | biostudies-literature
Project description:BackgroundCeramide plays an important role in the occurrence and development of tumor. The synthesis of ceramide needs the participation of LASS. Current studies have shown that different LASS family members play different functions in tumors, especially LASS6, has been proved to play a key role in breast cancer, gastric cancer, melanoma and so on, but the research on ovarian cancer is very limited.MethodsBioinformatics web resources, including Oncomine, UALCAN, Kaplan-Meier Plotter and TIMER were used to analyze the expression profile, prognostic value and immune infiltration of LASS6. The related genes of LASS6 in ovarian cancer were mined by Regulome Explorer and LinkedOmics database, and cluster analysis was done by DAVID. The PPI network involving LASS6 was constructed by STRING database. Finally, the correlation between 10 genes and LASS6 was analyzed by GEPIA database, and their prognostic value in ovarian cancer was analyzed by Kaplan-Meier plotter.ResultsThe expression of LASS6 was up-regulated in ovarian cancer, which was related to the progression and poor prognosis of ovarian cancer. Through GO/KEGG cluster analysis, we also found that LASS6 may affect calcium ion channel and its transport pathways. The analysis of regulatory network involved in LASS6 showed that the high mRNAs of 7 key genes were associated with poor prognosis of OS in patients with ovarian cancer, among which DEGS1 was the most significant.ConclusionsLASS6 may play an important role in the regulation of calcium pathway and become a new therapeutic target and potential prognostic marker in ovarian cancer.
| S-EPMC8422657 | biostudies-literature