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

Li, Wei; Li, Na; Gao, Lina; You, Chongge

doi:10.7717/peerj.8509

Cited by 31 publications

(22 citation statements)

References 49 publications

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“…In glioma, a series of analyses were performed to provide a valuable RBP resource during tumor progression, which revealed promising molecular candidates that were intimately involved in glioma tumorigenesis and had the potential of serving as cancer therapy targets (Wang et al, 2019). What is more, potential markers were screened out from differently expressed RBPs to predict cancer progression in lung cancer, and ROC curve analysis further confirmed that these selected hub genes had relatively good diagnostic efficacy to distinguish lung adenocarcinoma (Li et al, 2020b).…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Analysis of the Roles and Prognostic Value of RNA-Binding Proteins in Head and Neck Squamous Cell Carcinoma

Qin

2020

DNA and Cell Biology

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Head and neck squamous cell carcinoma (HNSCC) is a malignancy with relatively high incidence and poor prognosis. RNA-binding proteins (RBPs) were reported to be dysregulated in multiple cancers and were closely associated with tumor initiation and progression. However, an integrated analysis of the roles of RBPs in HNSCC has not been conducted. In the present study, we obtained transcriptome data and corresponding clinical information of HNSCC patients from The Cancer Genome Atlas database and screened out differentially expressed RBPs between tumor and normal tissues. Subsequently, we utilized a series of bioinformatics analyses to elucidate the potential functions and prognostic value of these RBPs in HNSCC. As a result, a total of 88 aberrantly expressed RBPs were identified, including 63 downregulated and 25 upregulated RBPs. Functional enrichment analysis suggested that the differentially expressed RBPs mainly participated in mRNA metabolic processes, RNA processing, RNA transport, regulation of RNA stability, RNA degradation, and mRNA surveillance pathway. Three RBP genes (NOVA1, EZH2, and RBM24) were determined as prognosisrelated hub genes from which EZH2 and NOVA1 were selected to construct a prognostic signature based on LASSO Cox regression algorithm. Further analysis demonstrated that the high-risk patient group stratified by the risk signature has advanced tumor grade and poorer overall survival when compared with low-risk group. Moreover, univariate analysis showed that the risk score, tumor stage, T stage, and N stage were significantly associated with patient overall survival and the multivariate analysis results indicated that the risk score and age were greatly correlated with patient prognosis. Overall, this study provided a comprehensive landscape of RBPs in HNSCC and identified an effective gene signature for predicting the clinical outcomes of HNSCC patient, which may contribute to clinical decision making and individualized cancer treatment.

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Section: Discussionmentioning

confidence: 99%

Comprehensive Analysis of the Roles and Prognostic Value of RNA-Binding Proteins in Head and Neck Squamous Cell Carcinoma

Qin

2020

DNA and Cell Biology

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“…LUAD, which is highly heterogeneous in morphological characteristics and remarkably variable in prognosis, is the most prevalent subtype of non-small cell lung cancer (NSCLC) [4,23]. More and more attention has been recently paid to the key role of gene signatures based on specific correlation in predicting the prognosis of LUAD because of the rapid advances in high-throughput technologies and bioinformatics methodology [24][25][26][27]. Moreover, the identification of novel gene signatures that predict the prognosis of patients is beneficial for the choice of treatment regimens and the improvement of survival rate [28,29].…”

Section: Discussionmentioning

confidence: 99%

Establishment and Validation of a Prognostic Signature for Lung Adenocarcinoma Based on Metabolism-Related Genes

Wang

Embaye

Yang

et al. 2020

Preprint

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Background: Given that dysregulated metabolism has been recently identified as a hallmark of cancer biology, this study aims to establish and validate a prognostic signature of lung adenocarcinoma (LUAD) based on metabolism-related genes(MRGs). Methods: The gene sequencing data of LUAD samples with clinical information and the metabolism-related gene set were obtained from The Cancer Genome Atlas (TCGA) and Molecular Signatures Database (MSigDB), respectively. The differentially expressed MRGs were identified by Wilcoxon rank sum test. Then, univariate Cox regression analysis were performed to identify MRGs that related to overall survival(OS). A prognostic signature was developed by multivariate Cox regression analysis. Furthermore, the signature was validated in the GSE31210 dataset. In addition, a nomogram that combined the prognostic signature was created for predicting the 1-, 3- and 5-year OS of LUAD.The accuracy of the nomogram prediction was evaluated using a calibration plot. Finally, cox regression analysis was applied to identify the prognostic value and clinical relationship of the signature in LUAD. Results: A total of 116 differentially expressed MRGs were detected in the TCGA dataset. We found that 12 MRGs were most significantly associated with OS by using the univariate regression analysis in LUAD. Then, multivariate Cox regression analyses were applied to construct the prognostic signature, which consisted of six MRGs(ALDOA, CAT, ENTPD2, GNPNAT1, LDHA, and TYMS). The prognostic value of this signature was further successfully validated in the GSE31210 dataset. Furthermore, the calibration curve of the prognostic nomogram demonstrated good agreement between the predicted and observed survival rates for each of OS. Further analysis indicated that this signature could be an independent prognostic indicator after adjusting to other clinical factors. Finally, the signature was found to be associated with various clinicopathological features. Conclusions: We established a prognostic signature based on MRGs for LUAD and validated the performance of the model, which may provide a promising tool for the diagnosis and prognosis in patients with LUAD.

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“…The previous research has demonstrated that prognostic RBPs signature could predict the prognosis of several of cancer [61,62]. However, in lung cancer, the previous prognostic RBPs signature was constructed based on lung squamous cell carcinoma or lung adenocarcinoma [20][21][22], which only predict a part of patients. A prognostic RBPs signature was constructed by multivariable Cox regression analysis concluding 13 differentially expressed RBPs (ZC3H12C, ZC3H12D, BOP1, CASC3, DDX24, IGF2BP1, KHDC1, FASTKD3, TARBP1, INTS7, NOL12, SNRPB, PABPC1L) in the current study, which could predict most lung cancer patients.…”

Section: Discussionmentioning

confidence: 99%

“…In addition. RBPs-associated prognostic signature was also constructed in lung adenocarcinoma, and the high-risk group had poor overall survival (OS) [21,22]. However, the RBPs associated prognostic signature involved with lung cancer only presents a part of lung cancer patients.…”

Section: Introductionmentioning

confidence: 99%

Identification and Validation of an RNA Binding Proteins-Associated Prognostic Signature for Non-Small Cell Lung Cancer

Miao¹,

Chen

Xiao

et al. 2020

Preprint

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Background: Non-small cell lung cancer (NSCLC) is a malignancy with relatively high incidence and poor prognosis. RNA-binding proteins (RBPs) were reported to be dysregulated in multiple cancers and were closely associated with tumor initiation and progression. However, the functions of RBPs in NSCLC remain unclear. Method: The RNA sequencing data and corresponding clinical information of NSCLC was downloaded from The Cancer Genome Atlas (TCGA) database. We identified aberrantly expressed RBPs between tumor and control tissue, and systemically investigated the expression and prognostic value of these RBPs by a series of bioinformatics analysis.Results: A total of 459 aberrantly expressed RBPs (291 up-regulated and 168 down-regulated RBPs) were identified. Functional enrichment analysis indicated that the differentially expressed RBPs were mainly associated with RNA splicing, ncRNA metabolic process, regulation of translation, mRNA surveillance pathway, RNA degradation, and RNA transport. Thirteen RBPs (ZC3H12C, ZC3H12D, BOP1, CASC3, DDX24, IGF2BP1, KHDC1, FASTKD3, TARBP1, INTS7, NOL12, SNRPB, PABPC1L) were identified as prognostic RBPs by multivariate Cox regression analysis, and were used to construct a prognostic signature. Further analysis demonstrated that high-risk group were significantly related to poor overall survival in training and testing cohort. The area under receiver operator characteristic curve of the prognostic signature was 0.703 in training cohort and 0.636 in testing cohort. In addition, the prognostic signature was further validated in differently clinical subgroup (>=65, <65, female, male, stage I-II, III- IV, T1-2, T3-4, N0, N1-3, M0 and M1). The risk score was an independent prognostic factor of NSCLC. A nomogram based on thirteen RBPs was constructed to predict the survival of patients.Conclusion: Our results provide novel insights into the pathogenesis of NSCLC. The RBPs-associated prognostic signature showed predictive value for NSCLC prognosis, with potential applications in clinical decision-making and individualized treatment.

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

Cited by 31 publications

References 49 publications

Comprehensive Analysis of the Roles and Prognostic Value of RNA-Binding Proteins in Head and Neck Squamous Cell Carcinoma

Comprehensive Analysis of the Roles and Prognostic Value of RNA-Binding Proteins in Head and Neck Squamous Cell Carcinoma

Establishment and Validation of a Prognostic Signature for Lung Adenocarcinoma Based on Metabolism-Related Genes

Identification and Validation of an RNA Binding Proteins-Associated Prognostic Signature for Non-Small Cell Lung Cancer

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