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Chen X, Dong X, Li H, Wu T, Liu H, Wu J, Ge W, Hao L, Zhang Z. RNA-binding proteins signature is a favorable biomarker of prognosis, immunotherapy and chemotherapy response for cervical cancer. Cancer Cell Int 2024; 24:80. [PMID: 38383371 PMCID: PMC10882920 DOI: 10.1186/s12935-024-03257-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 02/02/2024] [Indexed: 02/23/2024] Open
Abstract
Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) still present a huge threaten to women's health, especially the local advanced patients. Hence, developing more effectiveness prognostic signatures is urgently needed. This study constructed and verified a robust RNA-binding proteins (RBPs) related signature through a series of bioinformatics methods and explored the biological function of hub RBP in vitro experiments. As a result, the 10 RBPs signature was successfully established and could act as an independent prognostic biomarker in CESC patients, which displayed the highest sensitivity and specificity in prognosis prediction compared with other clinicopathological parameters. The risk model also presented good performance in risk stratification among CESC patients. Besides, a nomogram was constructed based on pathological stage and the risk signature and exhibited satisfactory accuracy in prognosis prediction. Functional enrichment indicated that the risk signature mainly participated in immune-related pathways and cancer-related pathways, and the infiltration level of immune cells and immune checkpoints showed a significantly higher degree in low-risk patients compared with high-risk patients. Notably, the 10 RBPs signature act as a novel biomarker in immunotherapy and chemotherapy response. In addition, PRPF40B was selected as hub RBP and its transcription and translation levels were obviously increased in CESC tissues, as well as Hela and Siha cells. Knockdown of PRPF40B inhibits the proliferation, migration and invasion of Hela and Siha cells in vitro. In conclusion, our research provides a noticeable strategy in prognostic prediction among CESC patients, which may illuminate the prospect of CESC patients' clinical outcome.
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Affiliation(s)
- Xiaomei Chen
- Nursing Department, Medical Centre Hospital of Qionglai City, Qionglai, 611530, Sichuan, China
| | - Xunhu Dong
- Institute of Toxicology, School of Military Preventive Medicine, Third Military Medical University (Army Medical University), 30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China
| | - Hong Li
- Department of Obstetrics and Gynecology, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China
| | - Tingting Wu
- Department of Obstetrics and Gynecology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400037, China
| | - Haoyin Liu
- Institute of Toxicology, School of Military Preventive Medicine, Third Military Medical University (Army Medical University), 30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China
| | - Jie Wu
- Institute of Toxicology, School of Military Preventive Medicine, Third Military Medical University (Army Medical University), 30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China
| | - Wei Ge
- Institute of Toxicology, School of Military Preventive Medicine, Third Military Medical University (Army Medical University), 30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China
| | - Lingji Hao
- Department of Obstetrics and Gynecology, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China
| | - Zhe Zhang
- Institute of Toxicology, School of Military Preventive Medicine, Third Military Medical University (Army Medical University), 30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China.
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McCarthy GA, Di Niro R, Finan JM, Jain A, Guo Y, Wyatt C, Guimaraes A, Waugh T, Keith D, Morgan T, Sears R, Brody J. Deletion of the mRNA stability factor ELAVL1 (HuR) in pancreatic cancer cells disrupts the tumor microenvironment integrity. NAR Cancer 2023; 5:zcad016. [PMID: 37089813 PMCID: PMC10113877 DOI: 10.1093/narcan/zcad016] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 03/08/2023] [Accepted: 04/06/2023] [Indexed: 04/25/2023] Open
Abstract
Stromal cells promote extensive fibrosis in pancreatic ductal adenocarcinoma (PDAC), which is associated with poor prognosis and therapeutic resistance. We report here for the first time that loss of the RNA-binding protein human antigen R (HuR, ELAVL1) in PDAC cells leads to reprogramming of the tumor microenvironment. In multiple in vivo models, CRISPR deletion of ELAVL1 in PDAC cells resulted in a decrease of collagen deposition, accompanied by a decrease of stromal markers (i.e. podoplanin, α-smooth muscle actin, desmin). RNA-sequencing data showed that HuR plays a role in cell-cell communication. Accordingly, cytokine arrays identified that HuR regulates the secretion of signaling molecules involved in stromal activation and extracellular matrix organization [i.e. platelet-derived growth factor AA (PDGFAA) and pentraxin 3]. Ribonucleoprotein immunoprecipitation analysis and transcription inhibition studies validated PDGFA mRNA as a novel HuR target. These data suggest that tumor-intrinsic HuR supports extrinsic activation of the stroma to produce collagen and desmoplasia through regulating signaling molecules (e.g. PDGFAA). HuR-deficient PDAC in vivo tumors with an altered tumor microenvironment are more sensitive to the standard of care gemcitabine, as compared to HuR-proficient tumors. Taken together, we identified a novel role of tumor-intrinsic HuR in its ability to modify the surrounding tumor microenvironment and regulate PDGFAA.
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Affiliation(s)
- Grace A McCarthy
- Department of Surgery, Oregon Health & Science University, Portland, OR 97239, USA
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR 97201, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - Roberto Di Niro
- Department of Surgery, Oregon Health & Science University, Portland, OR 97239, USA
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR 97201, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - Jennifer M Finan
- Department of Surgery, Oregon Health & Science University, Portland, OR 97239, USA
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR 97201, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - Aditi Jain
- The Jefferson Pancreas, Biliary and Related Cancer Center, Department of Surgery, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Yifei Guo
- Department of Surgery, Oregon Health & Science University, Portland, OR 97239, USA
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR 97201, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - Cory R Wyatt
- Department of Diagnostic Radiology, Oregon Health & Science University, Portland, OR 97239, USA
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Alexander R Guimaraes
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
- Department of Diagnostic Radiology, Oregon Health & Science University, Portland, OR 97239, USA
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Trent A Waugh
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR 97201, USA
| | - Dove Keith
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR 97201, USA
| | - Terry K Morgan
- Department of Pathology, Oregon Health & Science University, Portland, OR 97239, USA
| | - Rosalie C Sears
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR 97201, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR 97239, USA
- Cancer Early Detection Advanced Research Center, Oregon Health & Science University, Portland, OR 97201, USA
| | - Jonathan R Brody
- Department of Surgery, Oregon Health & Science University, Portland, OR 97239, USA
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR 97201, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
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Wang Z, Zeng Z, Gao F, Gui Z, Du J, Shen N, Shang Y, Yang Z, Shang L, Wei R, Ma W, Wang C. Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression. BMC Med Genomics 2023; 16:30. [PMID: 36803385 PMCID: PMC9942349 DOI: 10.1186/s12920-023-01456-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 02/11/2023] [Indexed: 02/22/2023] Open
Abstract
BACKGROUND Osteosarcoma has been the most common primary bone malignant tumor in children and adolescents. Despite the considerable improvement in the understanding of genetic events attributing to the rapid development of molecular pathology, the current information is still lacking, partly due to the comprehensive and highly heterogeneous nature of osteosarcoma. The study is to identify more potential responsible genes during the development of osteosarcoma, thus identifying promising gene indicators and aiding more precise interpretation of the disease. METHODS Firstly, from GEO database, osteosarcoma transcriptome microarrays were used to screen the differential expression genes (DEGS) in cancer comparing to normal bone samples, followed by GO/KEGG interpretation, risk score assessment and survival analysis of the genes, for the purpose of selecting a credible key gene. Further, the basic physicochemical properties, predicted cellular location, gene expression in human cancers, the association with clinical pathological features and potential signaling pathways involved in the key gene's regulation on osteosarcoma development were in succession explored. RESULTS Based on the selected GEO osteosarcoma expression profiles, we identified the differential expression genes in osteosarcoma versus normal bone samples, and the genes were classified into four groups based on the difference level, further genes interpretation indicated that the high differently level (> 8 fold) genes were mainly located extracellular and related to matrix structural constituent regulation. Meanwhile, module function analysis of the 67 high differential level (> 8 fold) DEGS revealed a 22-gene containing extracellular matrix regulation associated hub gene cluster. Further survival analysis of the 22 genes revealed that STC2 was an independent prognosis indicator in osteosarcoma. Moreover, after validating the differential expression of STC2 in cancer vs. normal tissues using local hospital osteosarcoma samples by IHC and qRT-PCR experiment, the gene's physicochemical property revealed STC2 as a cellular stable and hydrophilic protein, and the gene's association with osteosarcoma clinical pathological parameters, expression in pan-cancers and the probable biological functions and signaling pathways it involved were explored. CONCLUSION Using multiple bioinformatic analysis and local hospital samples validation, we revealed the gain of expression of STC2 in osteosarcoma, which associated statistical significantly with patients survival, and the gene's clinical features and potential biological functions were also explored. Although the results shall provide inspiring insights into further understanding of the disease, further experiments and detailed rigorous clinical trials are needed to reveal its potential drug-target role in clinical medical use.
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Affiliation(s)
- Ziyue Wang
- grid.24696.3f0000 0004 0369 153XDepartment of Pathology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Zixin Zeng
- grid.263452.40000 0004 1798 4018Basic Medical school of ShanXi Medical University, Tai Yuan city, ShanXi Province China
| | - Feng Gao
- grid.263452.40000 0004 1798 4018Department of Orthopedics, The Six Clinical Medical School of ShanXi Medical University, Tai Yuan, ShanXi Province China
| | - Ziwei Gui
- grid.263452.40000 0004 1798 4018Basic Medical school of ShanXi Medical University, Tai Yuan city, ShanXi Province China
| | - Juan Du
- grid.452845.a0000 0004 1799 2077Department of Pathology, The Second Hospital of ShanXi Medical University, No.382 WuYi Road, 030000 Tai Yuan City, ShanXi Province China
| | - Ningning Shen
- grid.452845.a0000 0004 1799 2077Department of Pathology, The Second Hospital of ShanXi Medical University, No.382 WuYi Road, 030000 Tai Yuan City, ShanXi Province China
| | - Yangwei Shang
- grid.452845.a0000 0004 1799 2077Department of Pathology, The Second Hospital of ShanXi Medical University, No.382 WuYi Road, 030000 Tai Yuan City, ShanXi Province China
| | - Zhiqing Yang
- grid.452845.a0000 0004 1799 2077Department of Pathology, The Second Hospital of ShanXi Medical University, No.382 WuYi Road, 030000 Tai Yuan City, ShanXi Province China
| | - Lifang Shang
- grid.452845.a0000 0004 1799 2077Department of Pathology, The Second Hospital of ShanXi Medical University, No.382 WuYi Road, 030000 Tai Yuan City, ShanXi Province China
| | - Rong Wei
- grid.452845.a0000 0004 1799 2077Department of Pathology, The Second Hospital of ShanXi Medical University, No.382 WuYi Road, 030000 Tai Yuan City, ShanXi Province China
| | - Wenxia Ma
- Department of Pathology, The Second Hospital of ShanXi Medical University, No.382 WuYi Road, 030000, Tai Yuan City, ShanXi Province, China.
| | - Chen Wang
- Department of Pathology, The Second Hospital of ShanXi Medical University, No.382 WuYi Road, 030000, Tai Yuan City, ShanXi Province, China.
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Jain A, McCoy M, Coats C, Brown SZ, Addya S, Pelz C, Sears RC, Yeo CJ, Brody JR. HuR Plays a Role in Double-Strand Break Repair in Pancreatic Cancer Cells and Regulates Functional BRCA1-Associated-Ring-Domain-1(BARD1) Isoforms. Cancers (Basel) 2022; 14:cancers14071848. [PMID: 35406624 PMCID: PMC8997573 DOI: 10.3390/cancers14071848] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/07/2022] [Accepted: 04/02/2022] [Indexed: 02/06/2023] Open
Abstract
Human Antigen R (HuR/ELAVL1) is known to regulate stability of mRNAs involved in pancreatic ductal adenocarcinoma (PDAC) cell survival. Although several HuR targets are established, it is likely that many remain currently unknown. Here, we identified BARD1 mRNA as a novel target of HuR. Silencing HuR caused a >70% decrease in homologous recombination repair (HRR) efficiency as measured by the double-strand break repair (pDR-GFP reporter) assay. HuR-bound mRNAs extracted from RNP-immunoprecipitation and probed on a microarray, revealed a subset of HRR genes as putative HuR targets, including the BRCA1-Associated-Ring-Domain-1 (BARD1) (p < 0.005). BARD1 genetic alterations are infrequent in PDAC, and its context-dependent upregulation is poorly understood. Genetic silencing (siRNA and CRISPR knock-out) and pharmacological targeting of HuR inhibited both full length (FL) BARD1 and its functional isoforms (α, δ, Φ). Silencing BARD1 sensitized cells to olaparib and oxaliplatin; caused G2-M cell cycle arrest; and increased DNA-damage while decreasing HRR efficiency in cells. Exogenous overexpression of BARD1 in HuR-deficient cells partially rescued the HRR dysfunction, independent of an HuR pro-oncogenic function. Collectively, our findings demonstrate for the first time that BARD1 is a bona fide HuR target, which serves as an important regulatory point of the transient DNA-repair response in PDAC cells.
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Affiliation(s)
- Aditi Jain
- The Jefferson Pancreas, Biliary and Related Cancer Center, Department of Surgery, Thomas Jefferson University, Philadelphia, PA 19107, USA; (C.C.); (S.Z.B.); (C.J.Y.)
- Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA 19107, USA;
- Correspondence: (A.J.); (J.R.B.); Tel.: +1-215-955-2693 (A.J.); +1-443-812-1852 (J.R.B.)
| | - Matthew McCoy
- Department of Oncology, Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC 20007, USA;
| | - Carolyn Coats
- The Jefferson Pancreas, Biliary and Related Cancer Center, Department of Surgery, Thomas Jefferson University, Philadelphia, PA 19107, USA; (C.C.); (S.Z.B.); (C.J.Y.)
| | - Samantha Z. Brown
- The Jefferson Pancreas, Biliary and Related Cancer Center, Department of Surgery, Thomas Jefferson University, Philadelphia, PA 19107, USA; (C.C.); (S.Z.B.); (C.J.Y.)
- The Department of Surgery, Brenden-Colson Center for Pancreatic Care, The Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
| | - Sankar Addya
- Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA 19107, USA;
| | - Carl Pelz
- The Department of Molecular and Medical Genetics, Brenden-Colson Center for Pancreatic Care, The Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA; (C.P.); (R.C.S.)
| | - Rosalie C. Sears
- The Department of Molecular and Medical Genetics, Brenden-Colson Center for Pancreatic Care, The Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA; (C.P.); (R.C.S.)
| | - Charles J. Yeo
- The Jefferson Pancreas, Biliary and Related Cancer Center, Department of Surgery, Thomas Jefferson University, Philadelphia, PA 19107, USA; (C.C.); (S.Z.B.); (C.J.Y.)
- Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA 19107, USA;
| | - Jonathan R. Brody
- The Department of Surgery, Brenden-Colson Center for Pancreatic Care, The Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA
- Correspondence: (A.J.); (J.R.B.); Tel.: +1-215-955-2693 (A.J.); +1-443-812-1852 (J.R.B.)
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Huang Z, Li F, Li Q. Expression profile of RNA binding protein in cervical cancer using bioinformatics approach. Cancer Cell Int 2021; 21:647. [PMID: 34863153 PMCID: PMC8642772 DOI: 10.1186/s12935-021-02319-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 11/05/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND It has been demonstrated by studies globally that RNA binding proteins (RBPs) took part in the development of cervical cancer (CC). Few studies concentrated on the correlation between RBPs and overall survival of CC patients. We retrieved significant DEGs (differently expressed genes, RNA binding proteins) correlated to the process of cervical cancer development. METHODS Expressions level of genes in cervical cancer and normal tissue samples were obtained from GTEx and TCGA database. Differently expressed RNA binding proteins (DEGs) were retrieved by Wilcoxon sum-rank test. ClusterProfiler package worked in R software was used to perform GO and KEGG enrichment analyses. Univariate proportional hazard cox regression and multivariate proportional hazard cox regressions were applied to identify DEGs equipped with prognostic value and other clinical independent risk factors. ROC curve was drawn for comparing the survival predict feasibility of risk score with other risk factors in CC patients. Nomogram was drawn to exhibit the prediction model and validated by C-index and calibration curve. Correlations between differentially expressed RNA binding proteins (DEGs) and other clinical features were investigated by t test or Cruskal Wallis analysis. Correlation between Immune and DEGs in cervical cancer was investigated by ssGSEA. RESULTS 347 differentially expressed RBPs (DEGs) were retrieved from cervical cancer tissue and normal tissue samples. GO enrichment analysis showed that these DEGs involved in RNA splicing, catabolic process and metabolism. Cox regression model showed that there were ten DEGs significantly associated with overall survival of cervical cancer patients. WDR43 (HR = 0.423, P = 0.008), RBM38 (HR = 0.533, P < 0.001), RNASEH2A (HR = 0.474, P = 0.002) and HENMT1 (HR = 0.720, P = 0.071) played protective roles in survival among these ten genes. Stage (Stage IV vs Stage I HR = 3.434, P < 0.001) and risk score (HR = 1.214, P < 0.001) were sorted as independent prognostic risk factors based on multivariate cox regression. ROC curve validated that risk score was preferable to predict survival of CC patients than other risk factors. Additionally, we found some of these ten predictor DEGs were correlated significantly in statistic with tumor grade or stage, clinical T stage, clinical N stage, pathology or risk score (all P < 0.05). Part of immune cells and immune functions showed a lower activity in high risk group than low risk group which is stratified by median risk score. CONCLUSION Our discovery showed that many RNA binding proteins involved in the progress of cervical cancer, which could probably serve as prognostic biomarkers and accelerate the discovery of treatment targets for CC patients.
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Affiliation(s)
- Zhiyuan Huang
- Research Center for Translational Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, 200120, China
- Department of Cardiothoracic Surgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, 200120, China
| | - Fang Li
- Department of Gynecology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, 200120, China.
| | - Qinchuan Li
- Research Center for Translational Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, 200120, China.
- Department of Cardiothoracic Surgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, 200120, China.
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Xing Q, Liu S, Luan J, Wang Y, Ma L. A novel 13 RNA binding proteins (RBPs) signature could predict prostate cancer biochemical recurrence. Pathol Res Pract 2021; 225:153587. [PMID: 34419719 DOI: 10.1016/j.prp.2021.153587] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 08/04/2021] [Accepted: 08/11/2021] [Indexed: 01/07/2023]
Abstract
BACKGROUND Cancer precision medicine requires biomarkers or signatures to predict prognosis and therapeutic benefits. Driven by this, we established a biochemical recurrence (BCR) predictive model for prostate cancer (PCA) patients based on RNA-binding proteins (RBPs). METHODS RNA-sequencing and corresponding clinicopathological data were downloaded from the Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Univariate COX, LASSO and multivariate COX regression analyses were carried out to develop the BCR predictive riskScore model. Survival analysis, ROC curve, independent prognostic analysis, nomogram were also performed to evaluate this signature internally and externally. RESULTS A total of 13 RBPs including TRMT1L, WBP4, MBNL3, SMAD9, NSUN7, ENG9, PIWIL4, PEG10, CSDC2, HELZ2, CELF2, YBX2 and ESRP2 were eventually identified as BCR-related hub biomarkers and utilized to establish a riskScore. Further analysis including external and internal verification indicated that the patients with high riskScores had shorter time to BCR compared to those with low riskScores in both TCGA and GSE116918. The area under the curve (AUC) of the time-dependent receiver operator characteristic curve (ROC) of the predictive model exhibited a good predictive performance. The signature was also proven to be a valuable independent prognostic factor (all P < 0.05). We also established a nomogram based on the 13 RBPs to visualize the relationships between individual predictors and 1-, 3- and 5-year BCR for PCA. CONCLUSIONS Our results successfully screened out 13 RBPs as a robust BCR-predictive signature in PCA by external and internal verification, helping clinician predict patients' cancer progression status and promoting the specific individualized treatment than original clinical parameters.
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Affiliation(s)
- Qianwei Xing
- Department of Urology, Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Shouyong Liu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Jiaochen Luan
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China
| | - Yi Wang
- Department of Urology, Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China.
| | - Limin Ma
- Department of Urology, Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China.
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Integrated Analysis of the Roles of RNA Binding Proteins and Their Prognostic Value in Clear Cell Renal Cell Carcinoma. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:5568411. [PMID: 34306592 PMCID: PMC8263288 DOI: 10.1155/2021/5568411] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 04/02/2021] [Accepted: 06/09/2021] [Indexed: 12/24/2022]
Abstract
Methods We downloaded the RNA sequencing data of ccRCC from the Cancer Genome Atlas (TCGA) database and identified differently expressed RBPs in different tissues. In this study, we used bioinformatics to analyze the expression and prognostic value of RBPs; then, we performed functional analysis and constructed a protein interaction network for them. We also screened out some RBPs related to the prognosis of ccRCC. Finally, based on the identified RBPs, we constructed a prognostic model that can predict patients' risk of illness and survival time. Also, the data in the HPA database were used for verification. Results In our experiment, we obtained 539 ccRCC samples and 72 normal controls. In the subsequent analysis, 87 upregulated RBPs and 38 downregulated RBPs were obtained. In addition, 9 genes related to the prognosis of patients were selected, namely, RPL36A, THOC6, RNASE2, NOVA2, TLR3, PPARGC1A, DARS, LARS2, and U2AF1L4. We further constructed a prognostic model based on these genes and plotted the ROC curve. This ROC curve performed well in judgement and evaluation. A nomogram that can judge the patient's life span is also made. Conclusion In conclusion, we have identified differentially expressed RBPs in ccRCC and carried out a series of in-depth research studies, the results of which may provide ideas for the diagnosis of ccRCC and the research of new targeted drugs.
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Wu Y, Liu Z, Wei X, Feng H, Hu B, Liu B, Luan Y, Ruan Y, Liu X, Liu Z, Wang S, Liu J, Wang T. Identification of the Functions and Prognostic Values of RNA Binding Proteins in Bladder Cancer. Front Genet 2021; 12:574196. [PMID: 34239534 PMCID: PMC8258248 DOI: 10.3389/fgene.2021.574196] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 05/19/2021] [Indexed: 12/01/2022] Open
Abstract
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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Affiliation(s)
- Yue Wu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zheng Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xian Wei
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Huan Feng
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bintao Hu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bo Liu
- Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Luan
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yajun Ruan
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaming Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhuo Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shaogang Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jihong Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tao Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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9
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Yang L, Zhang R, Guo G, Wang G, Wen Y, Lin Y, Zhang X, Yu X, Huang Z, Zhao D, Zhang L. Development and validation of a prediction model for lung adenocarcinoma based on RNA-binding protein. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:474. [PMID: 33850871 PMCID: PMC8039651 DOI: 10.21037/atm-21-452] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Background RNA-binding proteins (RBPs) have been found to participate in the development and progression of cancer. This present study aimed to construct a RBP-based prognostic prediction model for lung adenocarcinoma (LUAD). Methods RNA sequencing data and corresponding clinical information were acquired from The Cancer Genome Atlas (TCGA) and served as a training set. The prediction model was validated using the dataset in Gene Expression Omnibus (GEO) databases. Univariate and multivariate Cox regression analyses were conducted to identify the RBPs associated with survival. R software (http://www.r-project.org) was used for analysis in this study. Results Nine hub prognostic RBPs (CIRBP, DARS2, DDX24, GAPDH, LARP6, SNRPE, WDR3, ZC3H12C, ZC3H12D) were identified by univariate Cox regression analysis and multivariate Cox regression analysis. Using a risk score based on the nine-hub RBP model, we separated the LUAD patients into a low-risk group and a high-risk group. The outcomes revealed that patients in the high-risk group had poorer survival than those in the low-risk group. This signature was validated in the GEO database. Further study revealed that the risk score can be an independent prognostic biomarker for LUAD. A nomogram based on the nine hub RBPs was built to quantitatively predict the prognosis of LUAD patients. Conclusions Our nine-gene signature model could be used as a marker to predict the prognosis of LUAD and has potential for use in treatment individualization.
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Affiliation(s)
- Longjun Yang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Rusi Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Guangran Guo
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Gongming Wang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yingsheng Wen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yongbin Lin
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xuewen Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Anesthesiology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xiangyang Yu
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zirui Huang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Dechang Zhao
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Lanjun Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
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10
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Li T, Hui W, Halike H, Gao F. RNA Binding Protein-Based Model for Prognostic Prediction of Colorectal Cancer. Technol Cancer Res Treat 2021; 20:15330338211019504. [PMID: 34080453 PMCID: PMC8182183 DOI: 10.1177/15330338211019504] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is a kind of gastrointestinal tumor with serious high morbidity and mortality. Several reports have implicated the disorder of RNA-binding proteins (RBPs) in plenty of tumors, associating it to tumorigenesis and disease progression. The study is intended to construct novel prognostic biomarkers associated with CRC patients. METHODS Data of gene expression was acquired from the TCGA database, prognosis-related genes were selected. Besides, we analyzed GO and KEGG pathways. Univariate and multivariate Cox analyses were performed to generate a prognostic-related gene signature, which was evaluated by the Kaplan-Meier (K-M) and the Receiver Operating Characteristic (ROC) curve. The independent prognostic factor was established by survival analysis. GSE38832 dataset was used to validate the signature. Finally, expression of 8 genes was further confirmed by qRT-PCR in SW480 and SW620 cell lines. RESULTS We obtained 224 differentially expressed RBPS in total, of which 78 were downregulated and 146 were upregulated. Univariate COX analysis was conducted in the TCGA cohort to select 13 RBPs with P < 0.005, stepwise multivariate COX regression analysis was used to construct an 8-RBP signature (TERT, PPARGC1A, BRCA1, CELF4, TDRD7, LUZP4, PNLDC1, ZC3H12C). Based on the model, systematic analysis illustrated that a high risk score was obviously connected to a poor prognosis. The prognostic value of the risk score was validated in GSE38832 dataset, indicating that the risk model was accurate and effective. The prognostic signature-based risk score was identified as an independent prognostic indicator for CRC. The expression results of qRT-PCR were consistent with the results of differential expression analysis. CONCLUSIONS The eight-RBP signature can predict the survival of CRC patients and potentially act as CRC prognostic biomarker.
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Affiliation(s)
- Ting Li
- Department of Gastroenterology, People’s Hospital of Xinjiang Uygur
Autonomous Region, Urumqi, Xinjiang Province, China
| | - Wenjia Hui
- Department of Gastroenterology, People’s Hospital of Xinjiang Uygur
Autonomous Region, Urumqi, Xinjiang Province, China
| | - Halina Halike
- Department of Gastroenterology, People’s Hospital of Xinjiang Uygur
Autonomous Region, Urumqi, Xinjiang Province, China
| | - Feng Gao
- Department of Gastroenterology, People’s Hospital of Xinjiang Uygur
Autonomous Region, Urumqi, Xinjiang Province, China
- Feng Gao, PhD, Department of
Gastroenterology, People’s Hospital of Xinjiang Uygur Autonomous Region, Urumqi
830000, Xinjiang Province, China.
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11
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Qin X, Liu Z, Yan K, Fang Z, Fan Y. Integral Analysis of the RNA Binding Protein-associated Prognostic Model for Renal Cell Carcinoma. Int J Med Sci 2021; 18:953-963. [PMID: 33456353 PMCID: PMC7807188 DOI: 10.7150/ijms.50704] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 11/19/2020] [Indexed: 12/22/2022] Open
Abstract
RNA binding protein (RBPs) dysregulation has been reported in various malignant tumors and plays a pivotal role in tumor carcinogenesis and progression. However, the underlying mechanisms in renal cell carcinoma (RCC) are still unknown. In the present study, we performed a bioinformatics analysis using data from TCGA database to explore the expression and prognostic value of RBPs. We identified 125 differently expressed RBPs between tumor and normal tissue in RCC patients, including 87 upregulated and 38 downregulated RBPs. Eight RBPs (RPL22L1, RNASE2, RNASE3, EZH2, DDX25, DQX1, EXOSC5, DDX47) were selected as prognosis-related RBPs and used to construct a risk score model. In the risk score model, the high-risk subgroup had a poorer overall survival (OS) than the low-risk subgroup, and we divided the 539 RCC patients into two groups and conducted a time-dependent receiver operating characteristic (ROC) analysis to further test the prognostic ability of the eight hub RBPs. The area under the curve (AUC) of the ROC curve was 0.728 in train-group and 0.688 in test-group, indicating a good prognostic model. More importantly, we established a nomogram based on the selected eight RBPs. The eight selected RBPS have predictive value for RCC patients, with potential applications in clinical decision-making and individualized treatment.
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Affiliation(s)
- Xin Qin
- Department of Urology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Ji'nan, 250012, PR China
| | - Zhengfang Liu
- Department of Urology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Ji'nan, 250012, PR China
| | - Keqiang Yan
- Department of Urology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Ji'nan, 250012, PR China
| | - Zhiqing Fang
- Department of Urology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Ji'nan, 250012, PR China.,Department of Medicine, Center for Molecular Medicine (CMM) and Bioclinicum, Karolinska Institute and Karolinska University Hospital Solna, Solna 171 64, Sweden
| | - Yidong Fan
- Department of Urology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Ji'nan, 250012, PR China
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12
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Zhong W, Huang C, Lin J, Zhu M, Zhong H, Chiang MH, Chiang HS, Hui MS, Lin Y, Huang J. Development and Validation of Nine-RNA Binding Protein Signature Predicting Overall Survival for Kidney Renal Clear Cell Carcinoma. Front Genet 2020; 11:568192. [PMID: 33133154 PMCID: PMC7566920 DOI: 10.3389/fgene.2020.568192] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 08/31/2020] [Indexed: 12/20/2022] Open
Abstract
Cumulative studies have shown that RNA binding proteins (RBPs) play an important role in numerous malignant tumors and are related to the occurrence and progression of tumors. However, the role of RBPs in kidney renal clear cell carcinoma (KIRC) is not fully understood. In this study, we first downloaded gene expression data and corresponding clinical information of KIRC from the Cancer Genome Atlas (TCGA) database, International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) database, respectively. A total of 137 differentially expressed RBPs (DERBPs) were then identified between normal and tumor tissue, including 38 downregulated and 99 upregulated RBPs. Nine RBPs (EIF4A1, RPL36A, EXOSC5, RPL28, RPL13, RPS19, RPS2, EEF1A2, and OASL) were served as prognostic genes and exploited to construct a prognostic model through survival analysis. Kaplan-Meier curves analysis showed that the low-risk group had a better survival outcome when compared with the high-risk group. The area under the curve (AUC) value of the prognostic model was 0.713 in the TCGA data set (training data set), 0.706 in the ICGC data set, and 0.687 in the GSE29609 data set, respectively, confirming a good prognostic model. The prognostic model was also identified as an independent prognostic factor for KIRC survival by performing cox regression analysis. In addition, we also built a nomogram relying on age and the prognostic model and internal validation in the TCGA data set. The clinical benefit of the prognostic model was revealed by decision curve analysis (DCA). Gene set enrichment analysis revealed several crucial pathways (ERBB signaling pathway, pathways in cancer, MTOR signaling pathway, WNT signaling pathway, and TGF BETA signaling pathway) that may explain the underlying mechanisms of KIRC. Furthermore, potential drugs for KIRC treatment were predicted by the Connectivity Map (Cmap) database based on DERBPs, including several important drugs, such as depudecin and vorinostat, that could reverse KIRC gene expression, which may provide reference for the treatment of KIRC. In summary, we developed and validated a robust nine-RBP signature for KIRC prognosis prediction. A nomogram with risk score and age can be applied to promote the individualized prediction of overall survival in patients with KIRC. Moreover, the two drugs depudecin and vorinostat may contribute to KIRC treatment.
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Affiliation(s)
| | | | | | - Maoshu Zhu
- The Fifth Hospital of Xiamen, Xiamen, China
| | | | - Ming-Hsien Chiang
- Taiwan LinkMed Asia Public Health & Healthcare Management Research Association, Taipei, Taiwan
| | - Huei-Shien Chiang
- Taiwan LinkMed Asia Public Health & Healthcare Management Research Association, Taipei, Taiwan
| | | | - Yao Lin
- Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, College of Life Sciences, Fujian Normal University, Fuzhou, China
| | - Jiyi Huang
- The Fifth Hospital of Xiamen, Xiamen, China.,Xiang'an Branch, The First Affiliated Hospital of Xiamen University, Xiamen University, Xiamen, China
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13
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Competitive endogenous network of lncRNA, miRNA, and mRNA in the chemoresistance of gastrointestinal tract adenocarcinomas. Biomed Pharmacother 2020; 130:110570. [PMID: 32763816 DOI: 10.1016/j.biopha.2020.110570] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 07/17/2020] [Accepted: 07/26/2020] [Indexed: 12/12/2022] Open
Abstract
Chemotherapy is one of the main therapeutic strategies used for gastrointestinal tract adenocarcinomas (GTAs), but resistance to anticancer drugs is a substantial obstacle in successful chemotherapy. Accumulating evidence shows that non-coding RNAs, especially long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), can affect the drug resistance of tumor cells by forming a ceRNA regulatory network with mRNAs. The efficiency of the competing endogenous RNAs (ceRNAs) network can be affected by the number and integrality of miRNA recognition elements (MREs). Dynamic factors such as RNA editing, alternative splicing, single nucleotide polymorphism (SNP), RNA-binding proteins and RNA secondary structure can influence the MRE activity, which may in turn be involved in the regulation of chemoresistance-associated ceRNA network by prospective approaches. Besides activities in a single tumor cell, the components of the tumor micoenvironment (TME) also affect the ceRNA network by regulating the expression of non-coding RNA directly or indirectly. The alternation of the ceRNA network often has an impact on the malignant phenotype of tumor including chemoresistance. In this review, we focused on how MRE-associated dynamic factors and components of TME affected the ceRNA network and speculated the potential association of ceRNA network with chemoresistance. We also summarized the ceRNA network of lncRNAs, miRNAs, and mRNAs which efficiently triggers chemoresistance in the specific types of GTAs and analyzed the role of each RNA as a "promoter" or "suppressor" of chemoresistance.
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14
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Shi LE, Shang X, Nie KC, Xu Q, Chen NB, Zhu ZZ. Identification of potential crucial genes associated with the pathogenesis and prognosis of pancreatic adenocarcinoma. Oncol Lett 2020; 20:60. [PMID: 32793313 PMCID: PMC7418510 DOI: 10.3892/ol.2020.11921] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 06/22/2020] [Indexed: 02/06/2023] Open
Abstract
Pancreatic adenocarcinoma (PAAD) is a type of malignant tumor with the highest mortality rate among all neoplasms worldwide, and its exact pathogenesis is still poorly understood. Timely diagnosis and treatment are of great importance in order to decrease the mortality rate of PAAD. Therefore, identifying new biomarkers for diagnosis and prognosis is essential to enable early detection of PAAD and to improve the overall survival (OS) rate. In order to screen and integrate differentially expressed genes (DEGs) between PAAD and normal tissues, a total of seven datasets were downloaded from the Gene Expression Omnibus database and the ‘limma’ and ‘robustrankggreg’ packages in R software were used. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the DEGs was performed using the Database for Annotation, Visualization and Integrated Discovery website, and the protein-protein interaction network analysis was performed using the Search Tool for the Retrieval of Interacting Genes/Proteins database. A gene prognostic signature was constructed using the Cox regression model. A total of 10 genes (CDK1, CCNB1, CDC20, ASPM, UBE2C, TPX2, TOP2A, NUSAP1, KIF20A and DLGAP5) that may be associated with pancreatic adenocarcinoma were identified. According to the differentially expressed genes in The Cancer Genome Atlas, the present study set up four prognostic signatures (matrix metalloproteinase 12, sodium voltage-gated channel α subunit 11, tetraspanin 1 and SH3 domain and tetratricopeptide repeats-containing 2), which effectively predicted OS. The hub genes that were highly associated with the occurrence, development and prognosis of PAAD were identified, which may be helpful to further understand the molecular basis of pancreatic cancer and guide the synthesis of drugs for PPAD.
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Affiliation(s)
- Lan-Er Shi
- Department of Endocrinology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510405, P.R. China
| | - Xin Shang
- Department of Endocrinology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510405, P.R. China
| | - Ke-Chao Nie
- Department of Endocrinology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510405, P.R. China
| | - Qiang Xu
- Department of Endocrinology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510405, P.R. China
| | - Na-Bei Chen
- Department of Endocrinology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510405, P.R. China
| | - Zhang-Zhi Zhu
- Department of Endocrinology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510405, P.R. China
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15
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Li W, Gao LN, Song PP, You CG. Development and validation of a RNA binding protein-associated prognostic model for lung adenocarcinoma. Aging (Albany NY) 2020; 12:3558-3573. [PMID: 32087603 PMCID: PMC7066909 DOI: 10.18632/aging.102828] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Accepted: 01/27/2020] [Indexed: 12/21/2022]
Abstract
RNA binding proteins (RBPs) dysregulation have been reported in various malignant tumors and associated with the occurrence and development of cancer. However, the role of RBPs in lung adenocarcinoma (LUAD) is poorly understood. 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. The study then systemically investigated the expression and prognostic value of these RBPs by a series of bioinformatics analysis. A total of 223 differently expressed RBPs were identified, including 101 up-regulated and 122 down-regulated RBPs. Eight RBPs (IGF2BP1, IFIT1B, PABPC1, TLR8, GAPDH, PIWIL4, RNPC3, and ZC3H12C) were identified as prognosis related hub gene and used to construct a prognostic model. Further analysis indicated that the patients in the high-risk subgroup had poor overall survival(OS) compared to those in low-risk subgroup based on the model. The area under the curve of the time-dependent receiver operator characteristic curve of the prognostic model are 0.775 in TCGA cohort and 0.814 in GSE31210 cohort, confirming a good prognostic model. We also established a nomogram based on eight RBPs mRNA and internal validation in the TCGA cohort, which displayed a favorable discriminating ability for lung adenocarcinoma.
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Affiliation(s)
- Wei Li
- Laboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou 730030, China
| | - Li-Na Gao
- Laboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou 730030, China
| | - Pei-Pei Song
- Laboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou 730030, China
| | - Chong-Ge You
- Laboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou 730030, China
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16
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Li W, Li N, Gao L, You C. Integrated analysis of the roles and prognostic value of RNA binding proteins in lung adenocarcinoma. PeerJ 2020; 8:e8509. [PMID: 32071816 PMCID: PMC7007976 DOI: 10.7717/peerj.8509] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Accepted: 01/03/2020] [Indexed: 12/19/2022] Open
Abstract
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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Affiliation(s)
- Wei Li
- Laboratory Medicine Center, Lanzhou University Second Hospital, Langzhou, China
| | - Na Li
- Department of Pathology, the First Affiliated Hospital of Hunan University of Medicine, Huaihua, China
| | - Lina Gao
- Laboratory Medicine Center, Lanzhou University Second Hospital, Langzhou, China
| | - Chongge You
- Laboratory Medicine Center, Lanzhou University Second Hospital, Langzhou, China
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