1
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Zhou W, Jie Q, Pan T, Shi J, Jiang T, Zhang Y, Ding N, Xu J, Ma Y, Li Y. Single-cell RNA binding protein regulatory network analyses reveal oncogenic HNRNPK-MYC signalling pathway in cancer. Commun Biol 2023; 6:82. [PMID: 36681772 PMCID: PMC9867709 DOI: 10.1038/s42003-023-04457-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 01/10/2023] [Indexed: 01/22/2023] Open
Abstract
RNA-binding proteins (RBPs) are key players of gene expression and perturbations of RBP-RNA regulatory network have been observed in various cancer types. Here, we propose a computational method, RBPreg, to identify the RBP regulators by integration of single cell RNA-Seq (N = 233,591) and RBP binding data. Pan-cancer analyses suggest that RBP regulators exhibit cancer and cell specificity and perturbations of RBP regulatory network are involved in cancer hallmark-related functions. We prioritize an oncogenic RBP-HNRNPK, which is highly expressed in tumors and associated with poor prognosis of patients. Functional assays performed in cancer cells reveal that HNRNPK promotes cancer cell proliferation, migration, and invasion in vitro and in vivo. Mechanistic investigations further demonstrate that HNRNPK promotes tumorigenesis and progression by directly binding to MYC and perturbed the MYC targets pathway in lung cancer. Our results provide a valuable resource for characterizing RBP regulatory networks in cancer, yielding potential biomarkers for precision medicine.
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Affiliation(s)
- Weiwei Zhou
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China
| | - Qiuling Jie
- Hainan Provincial Key Laboratory for Human Reproductive Medicine and Genetic Research, Hainan Clinical Research Center for Thalassemia, Reproductive Medical Center, National Center for International Research "China-Myanmar Joint Research Center for Prevention and Treatment of Regional Major Disease", The First Affiliated Hospital of Hainan Medical University, Hainan Medical University, Haikou, 571199, China
| | - Tao Pan
- College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, 571199, China
| | - Jingyi Shi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China
| | - Tiantongfei Jiang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China
| | - Ya Zhang
- College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, 571199, China
| | - Na Ding
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China
| | - Juan Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China.
| | - Yanlin Ma
- Hainan Provincial Key Laboratory for Human Reproductive Medicine and Genetic Research, Hainan Clinical Research Center for Thalassemia, Reproductive Medical Center, National Center for International Research "China-Myanmar Joint Research Center for Prevention and Treatment of Regional Major Disease", The First Affiliated Hospital of Hainan Medical University, Hainan Medical University, Haikou, 571199, China.
| | - Yongsheng Li
- Hainan Provincial Key Laboratory for Human Reproductive Medicine and Genetic Research, Hainan Clinical Research Center for Thalassemia, Reproductive Medical Center, National Center for International Research "China-Myanmar Joint Research Center for Prevention and Treatment of Regional Major Disease", The First Affiliated Hospital of Hainan Medical University, Hainan Medical University, Haikou, 571199, China.
- College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, 571199, China.
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2
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Zhang J, Pan T, Zhou W, Zhang Y, Xu G, Xu Q, Li S, Gao Y, Wang Z, Xu J, Li Y. Long noncoding RNA LINC01132 enhances immunosuppression and therapy resistance via NRF1/DPP4 axis in hepatocellular carcinoma. J Exp Clin Cancer Res 2022; 41:270. [PMID: 36071454 PMCID: PMC9454129 DOI: 10.1186/s13046-022-02478-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 08/28/2022] [Indexed: 12/21/2022] Open
Abstract
Background Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and play fundamental roles in various types of cancer. Current developments in transcriptome analyses unveiled the existence of lncRNAs; however, their functional characterization remains a challenge. Methods A bioinformatics screen was performed by integration of multiple omics data in hepatocellular carcinoma (HCC) prioritizing a novel oncogenic lncRNA, LINC01132. Expression of LINC01132 in HCC and control tissues was validated by qRT-PCR. Cell viability and migration activity was examined by MTT and transwell assays. Finally, our results were confirmed in vivo mouse model and ex vivo patient derived tumor xenograft experiments to determine the mechanism of action and explore LINC01132-targeted immunotherapy. Results Systematic investigation of lncRNAs genome-wide expression patterns revealed LINC01132 as an oncogene in HCC. LINC01132 is significantly overexpressed in tumor and associated with poor overall survival of HCC patients, which is mainly driven by copy number amplification. Functionally, LINC01132 overexpression promoted cell growth, proliferation, invasion and metastasis in vitro and in vivo. Mechanistically, LINC01132 acts as an oncogenic driver by physically interacting with NRF and enhancing the expression of DPP4. Notably, LINC01132 silencing triggers CD8+ T cells infiltration, and LINC01132 knockdown combined with anti-PDL1 treatment improves antitumor immunity, which may prove a new combination therapy in HCC. Conclusions LINC01132 functions as an oncogenic driver that induces HCC development via the NRF1/DPP4 axis. Silencing LINC01132 may enhance the efficacy of anti-PDL1 immunotherapy in HCC patients. Supplementary Information The online version contains supplementary material available at 10.1186/s13046-022-02478-z.
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3
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Zhang X, Kong W, Gao M, Huang W, Peng C, Huang Z, Xie Z, Guo H. Robust prognostic model based on immune infiltration-related genes and clinical information in ovarian cancer. J Cell Mol Med 2022; 26:3659-3674. [PMID: 35735060 PMCID: PMC9258710 DOI: 10.1111/jcmm.17360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 03/25/2022] [Accepted: 04/17/2022] [Indexed: 11/30/2022] Open
Abstract
Immune infiltration of ovarian cancer (OV) is a critical factor in determining patient's prognosis. Using data from TCGA and GTEx database combined with WGCNA and ESTIMATE methods, 46 genes related to OV occurrence and immune infiltration were identified. Lasso and multivariate Cox regression were applied to define a prognostic score (IGCI score) based on 3 immune genes and 3 types of clinical information. The IGCI score has been verified by K‐M curves, ROC curves and C‐index on test set. In test set, IGCI score (C‐index = 0.630) is significantly better than AJCC stage (C‐index = 0.541, p < 0.05) and CIN25 (C‐index = 0.571, p < 0.05). In addition, we identified key mutations to analyse prognosis of patients and the process related to immunity. Chi‐squared tests revealed that 6 mutations are significantly (p < 0.05) related to immune infiltration: BRCA1, ZNF462, VWF, RBAK, RB1 and ADGRV1. According to mutation survival analysis, we found 5 key mutations significantly related to patient prognosis (p < 0.05): CSMD3, FLG2, HMCN1, TOP2A and TRRAP. RB1 and CSMD3 mutations had small p‐value (p < 0.1) in both chi‐squared tests and survival analysis. The drug sensitivity analysis of key mutation showed when RB1 mutation occurs, the efficacy of six anti‐tumour drugs has changed significantly (p < 0.05).
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Affiliation(s)
- Xi Zhang
- Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China
| | - Weikaixin Kong
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Institute Sanqu Technology (Hangzhou) Co., Ltd., Hangzhou, China
| | - Miaomiao Gao
- Department of Pharmacology, School of Basic Medical Sciences, Peking University, Beijing, China
| | - Weiran Huang
- Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing, China
| | - Chao Peng
- Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing, China
| | - Zhuo Huang
- Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing, China
| | - Zhengwei Xie
- Peking University International Cancer Institute and Department of Pharmacology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China
| | - Hongyan Guo
- Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China
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4
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Chen J, Liu HF, Qiao LB, Wang FB, Wang L, Lin Y, Liu J. Global RNA editing identification and characterization during human pluripotent-to-cardiomyocyte differentiation. MOLECULAR THERAPY-NUCLEIC ACIDS 2021; 26:879-891. [PMID: 34760335 PMCID: PMC8551472 DOI: 10.1016/j.omtn.2021.10.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 09/05/2021] [Accepted: 10/01/2021] [Indexed: 01/19/2023]
Abstract
RNA editing is widely involved in stem cell differentiation and development; however, RNA editing events during human cardiomyocyte differentiation have not yet been characterized and elucidated. Here, we identified genome-wide RNA editing sites and systemically characterized their genomic distribution during four stages of human cardiomyocyte differentiation. It was found that the expression level of ADAR1 affected the global number of adenosine to inosine (A-to-I) editing sites but not the editing degree. Next, we identified 43, 163, 544, and 141 RNA editing sites that contribute to changes in amino acid sequences, variation in alternative splicing, alterations in miRNA-target binding, and changes in gene expression, respectively. Generally, RNA editing showed a stage-specific pattern with 211 stage-shared editing sites. Interestingly, cardiac muscle contraction and heart-disease-related pathways were enriched by cardio-specific editing genes, emphasizing the connection between cardiomyocyte differentiation and heart diseases from the perspective of RNA editing. Finally, it was found that these RNA editing sites are also related to several congenital and noncongenital heart diseases. Together, our study provides a new perspective on cardiomyocyte differentiation and offers more opportunities to understand the mechanisms underlying cell fate determination, which can promote the development of cardiac regenerative medicine and therapies for human heart diseases.
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Affiliation(s)
- Juan Chen
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui 230009, China
| | - Hui-Fang Liu
- Department of Endocrinology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430014, China
| | - Li-Bo Qiao
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui 230009, China
| | - Fang-Bin Wang
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui 230009, China
| | - Lu Wang
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui 230009, China
| | - Yan Lin
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui 230009, China
| | - Jian Liu
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui 230009, China.,Engineering Research Center of Bio-process, Ministry of Education, Hefei University of Technology, Hefei, Anhui 230009, China
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5
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Jiang T, Zhou W, Chang Z, Zou H, Bai J, Sun Q, Pan T, Xu J, Li Y, Li X. ImmReg: the regulon atlas of immune-related pathways across cancer types. Nucleic Acids Res 2021; 49:12106-12118. [PMID: 34755873 PMCID: PMC8643631 DOI: 10.1093/nar/gkab1041] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 10/10/2021] [Accepted: 10/14/2021] [Indexed: 01/05/2023] Open
Abstract
Immune system gene regulation perturbation has been found to be a major cause of the development of various types of cancer. Numbers of mechanisms contribute to gene expression regulation, thus, systematically identification of potential regulons of immune-related pathways is critical to cancer immunotherapy. Here, we comprehensively chart the landscape of transcription factors, microRNAs, RNA binding proteins and long noncoding RNAs regulation in 17 immune-related pathways across 33 cancers. The potential immunology regulons are likely to exhibit higher expressions in immune cells, show expression perturbations in cancer, and are significantly correlated with immune cell infiltrations. We also identify a panel of clinically relevant immunology regulons across cancers. Moreover, the regulon atlas of immune-related pathways helps prioritizing cancer-related genes (i.e. ETV7, miR-146a-5p, ZFP36 and HCP5). We further identified two molecular subtypes of glioma (cold and hot tumour phenotypes), which were characterized by differences in immune cell infiltrations, expression of checkpoints, and prognosis. Finally, we developed a user-friendly resource, ImmReg (http://bio-bigdata.hrbmu.edu.cn/ImmReg/), with multiple modules to visualize, browse, and download immunology regulation. Our study provides a comprehensive landscape of immunology regulons, which will shed light on future development of RNA-based cancer immunotherapies.
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Affiliation(s)
- Tiantongfei Jiang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Weiwei Zhou
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Zhenghong Chang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Haozhe Zou
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Jing Bai
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Qisen Sun
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Tao Pan
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China
| | - Juan Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Yongsheng Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China
| | - Xia Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.,Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou 571199, China
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6
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Zhu D, Chen J, Hou T. Development and Validation of a Prognostic Model of RNA-Binding Proteins in Colon Adenocarcinoma: A Study Based on TCGA and GEO Databases. Cancer Manag Res 2021; 13:7709-7722. [PMID: 34675667 PMCID: PMC8517423 DOI: 10.2147/cmar.s330434] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 09/20/2021] [Indexed: 12/24/2022] Open
Abstract
Background Previous studies reported that dysregulation of RNA-binding proteins (RBPs) is significantly associated with the development of cancer. However, there are few studies to date on the role of RBPs in colon adenocarcinoma (COAD). Methods RNA sequencing and clinical data for COAD patients were downloaded from The Cancer Genome Atlas (TCGA) database to identify differentially expressed (DE) RBPs between COAD tissue and normal colon tissue, and then the expression and prognostic significance of these RBPs were investigated in detail by systematic bioinformatics analysis. qRT-PCR was used to validate the expressions of prognosis-related RBP-encoding genes. Results Seven RBPs (RPL10L, ERI1, POP1, CAPRIN2, TDRD7, SNIP1 and PPARGC1A) were identified as hub genes associated with prognosis by a series of regression analyses, and were then used to construct a prognostic model. Further analysis based on this model indicated that the overall survival (OS) of the high-risk groups was lower than that of the low-risk groups. In this prognostic model, the area under the ROC curve (AUC) was 0.694, 0.709 and 0.665 for the TCGA cohort at 1, 3 and 5 years, respectively, while the AUC was 0.671, 0.633 and 0.601 for the GEO combined cohort at 1, 3 and 5 years, respectively, indicating the good predictive ability of the model. We also built a nomogram based on the 7 RBPs in the TCGA cohort, and the model showed good discriminatory ability for COAD. Conclusion We screened seven prognosis-related genes in COAD patients based on RBP-related genes, validated the expressions of the seven prognosis-related RBP-encoding genes by qRT-PCR and constructed a prognosis-related nomogram for patients with COAD.
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Affiliation(s)
- Dandan Zhu
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510006, People's Republic of China.,Department of Laboratory Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, 510080, People's Republic of China
| | - Jierong Chen
- Department of Laboratory Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, 510080, People's Republic of China
| | - Tieying Hou
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510006, People's Republic of China.,Department of Laboratory Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, 510080, People's Republic of China
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7
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Li Y, Xu J. Editorial: Perturbation of RNA Binding Protein Regulation in Cancer. Front Genet 2021; 12:693766. [PMID: 34249108 PMCID: PMC8264501 DOI: 10.3389/fgene.2021.693766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 05/31/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Yongsheng Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Juan Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
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8
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Li Y, Burgman B, Khatri IS, Pentaparthi SR, Su Z, McGrail DJ, Li Y, Wu E, Eckhardt SG, Sahni N, Yi SS. e-MutPath: computational modeling reveals the functional landscape of genetic mutations rewiring interactome networks. Nucleic Acids Res 2021; 49:e2. [PMID: 33211847 PMCID: PMC7797045 DOI: 10.1093/nar/gkaa1015] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 10/07/2020] [Accepted: 10/20/2020] [Indexed: 02/06/2023] Open
Abstract
Understanding the functional impact of cancer somatic mutations represents a critical knowledge gap for implementing precision oncology. It has been increasingly appreciated that the interaction profile mediated by a genomic mutation provides a fundamental link between genotype and phenotype. However, specific effects on biological signaling networks for the majority of mutations are largely unknown by experimental approaches. To resolve this challenge, we developed e-MutPath (edgetic Mutation-mediated Pathway perturbations), a network-based computational method to identify candidate ‘edgetic’ mutations that perturb functional pathways. e-MutPath identifies informative paths that could be used to distinguish disease risk factors from neutral elements and to stratify disease subtypes with clinical relevance. The predicted targets are enriched in cancer vulnerability genes, known drug targets but depleted for proteins associated with side effects, demonstrating the power of network-based strategies to investigate the functional impact and perturbation profiles of genomic mutations. Together, e-MutPath represents a robust computational tool to systematically assign functions to genetic mutations, especially in the context of their specific pathway perturbation effect.
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Affiliation(s)
- Yongsheng Li
- Department of Oncology, Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.,Oden Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin, Austin, TX 78712, USA
| | - Brandon Burgman
- Department of Oncology, Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.,Interdisciplinary Life Sciences Graduate Programs (ILSGP), College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Ishaani S Khatri
- Department of Oncology, Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.,Oden Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin, Austin, TX 78712, USA
| | - Sairahul R Pentaparthi
- Department of Oncology, Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA
| | - Zhe Su
- Department of Oncology, Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.,Oden Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin, Austin, TX 78712, USA
| | - Daniel J McGrail
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Yang Li
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Science Park, Smithville, TX 78957, USA
| | - Erxi Wu
- Department of Oncology, Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.,Neuroscience Institute and Department of Neurosurgery, Baylor Scott & White Health, Temple, TX 76502, USA.,Department of Surgery, Texas A & M University Health Science Center, College of Medicine, Temple, TX 76508, USA.,Department of Pharmaceutical Sciences, Texas A & M University Health Science Center, College of Pharmacy, College Station, TX 77843, USA
| | - S Gail Eckhardt
- Department of Oncology, Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.,Interdisciplinary Life Sciences Graduate Programs (ILSGP), College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Nidhi Sahni
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Science Park, Smithville, TX 78957, USA.,Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.,Program in Quantitative and Computational Biosciences (QCB), Baylor College of Medicine, Houston, TX 77030, USA
| | - S Stephen Yi
- Department of Oncology, Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA.,Oden Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin, Austin, TX 78712, USA.,Interdisciplinary Life Sciences Graduate Programs (ILSGP), College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA.,Department of Biomedical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX 78712, USA
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9
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Rodríguez M, Ajona D, Seijo LM, Sanz J, Valencia K, Corral J, Mesa-Guzmán M, Pío R, Calvo A, Lozano MD, Zulueta JJ, Montuenga LM. Molecular biomarkers in early stage lung cancer. Transl Lung Cancer Res 2021; 10:1165-1185. [PMID: 33718054 PMCID: PMC7947407 DOI: 10.21037/tlcr-20-750] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Low dose computed tomography (LDCT) screening, together with the recent advances in targeted and immunotherapies, have shown to improve non-small cell lung cancer (NSCLC) survival. Furthermore, screening has increased the number of early stage-detected tumors, allowing for surgical resection and multimodality treatments when needed. The need for improved sensitivity and specificity of NSCLC screening has led to increased interest in combining clinical and radiological data with molecular data. The development of biomarkers is poised to refine inclusion criteria for LDCT screening programs. Biomarkers may also be useful to better characterize the risk of indeterminate nodules found in the course of screening or to refine prognosis and help in the management of screening detected tumors. The clinical implications of these biomarkers are still being investigated and whether or not biomarkers will be included in further decision-making algorithms in the context of screening and early lung cancer management still needs to be determined. However, it seems clear that there is much room for improvement even in early stage lung cancer disease-free survival (DFS) rates; thus, biomarkers may be the key to refine risk-stratification and treatment of these patients. Clinicians’ capacity to register, integrate, and analyze all the available data in both high risk individuals and early stage NSCLC patients will lead to a better understanding of the disease’s mechanisms, and will have a direct impact in diagnosis, treatment, and follow up of these patients. In this review, we aim to summarize all the available data regarding the role of biomarkers in LDCT screening and early stage NSCLC from a multidisciplinary perspective. We have highlighted clinical implications, the need to combine risk stratification, clinical data, radiomics, molecular information and artificial intelligence in order to improve clinical decision-making, especially regarding early diagnostics and adjuvant therapy. We also discuss current and future perspectives for biomarker implementation in routine clinical practice.
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Affiliation(s)
- María Rodríguez
- Department of Thoracic Surgery, Clínica Universidad de Navarra, Madrid, Spain
| | - Daniel Ajona
- Program in Solid Tumors, Center for Applied Medical Research (CIMA), University of Navarra, Pamplona, Spain.,Navarra Institute for Health Research (IdISNA), Pamplona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Department of Biochemistry and Genetics, School of Sciences, University of Navarra, Pamplona, Spain
| | - Luis M Seijo
- Department of Pulmonology, Clínica Universidad de Navarra, Madrid, Spain.,Centro de Investigación Biomédica en Red Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - Julián Sanz
- Department of Pathology, Clínica Universidad de Navarra, Madrid, Spain
| | - Karmele Valencia
- Program in Solid Tumors, Center for Applied Medical Research (CIMA), University of Navarra, Pamplona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Department of Biochemistry and Genetics, School of Sciences, University of Navarra, Pamplona, Spain
| | - Jesús Corral
- Department of Oncology, Clínica Universidad de Navarra, Madrid, Spain
| | - Miguel Mesa-Guzmán
- Department of Thoracic Surgery, Clínica Universidad de Navarra, Pamplona, Spain
| | - Rubén Pío
- Program in Solid Tumors, Center for Applied Medical Research (CIMA), University of Navarra, Pamplona, Spain.,Navarra Institute for Health Research (IdISNA), Pamplona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Department of Biochemistry and Genetics, School of Sciences, University of Navarra, Pamplona, Spain
| | - Alfonso Calvo
- Program in Solid Tumors, Center for Applied Medical Research (CIMA), University of Navarra, Pamplona, Spain.,Navarra Institute for Health Research (IdISNA), Pamplona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Department of Pathology, Anatomy and Physiology, Schools of Medicine and Sciences, University of Navarra, Pamplona, Spain
| | - María D Lozano
- Navarra Institute for Health Research (IdISNA), Pamplona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Department of Pathology, Anatomy and Physiology, Schools of Medicine and Sciences, University of Navarra, Pamplona, Spain.,Department of Pathology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Javier J Zulueta
- Navarra Institute for Health Research (IdISNA), Pamplona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Department of Pulmonology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Luis M Montuenga
- Program in Solid Tumors, Center for Applied Medical Research (CIMA), University of Navarra, Pamplona, Spain.,Navarra Institute for Health Research (IdISNA), Pamplona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Department of Pathology, Anatomy and Physiology, Schools of Medicine and Sciences, University of Navarra, Pamplona, Spain
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10
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Zhang Y, Xu S, Xu G, Gao Y, Li S, Zhang K, Tian Z, Guo J, Li X, Xu J, Li Y. Dynamic Expression of m 6A Regulators During Multiple Human Tissue Development and Cancers. Front Cell Dev Biol 2021; 8:629030. [PMID: 33575259 PMCID: PMC7870680 DOI: 10.3389/fcell.2020.629030] [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] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 12/21/2020] [Indexed: 12/20/2022] Open
Abstract
N6-methyladenosine (m6A) plays critical roles in human development and cancer progression. However, our knowledge regarding the dynamic expression of m6A regulators during human tissue development is still lacking. Here, we comprehensively analyzed the dynamic expression alterations of m6A regulators during seven tissue development and eight cancer types. We found that m6A regulators globally exhibited decreased expression during development. In addition, IGF2BP1/2/3 (insulinlike growth factor 2 MRNA-binding protein 1/2/3) exhibited reverse expression pattern in cancer progression, suggesting an oncofetal reprogramming in cancer. The expressions of IGF2BP1/2/3 were regulated by genome alterations, particularly copy number amplification in cancer. Clinical association analysis revealed that higher expressions of IGF2BP1/2/3 were associated with worse survival of cancer patients. Finally, we found that genes significantly correlated with IGF2BP1/2/3 were significantly enriched in cancer hallmark-related pathways. In summary, dynamic expression analysis will guide both mechanistic and therapeutic roles of m6A regulators during tissue development and cancer progression.
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Affiliation(s)
- Ya Zhang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Sicong Xu
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Gang Xu
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Yueying Gao
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Si Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Ke Zhang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Zhanyu Tian
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Jing Guo
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Xia Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Juan Xu
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Yongsheng Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
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11
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Chen Q, Li ZL, Fu SQ, Wang SY, Liu YT, Ma M, Yang XR, Xie WJ, Gong BB, Sun T. Development of prognostic signature based on RNA binding proteins related genes analysis in clear cell renal cell carcinoma. Aging (Albany NY) 2021; 13:3926-3944. [PMID: 33461173 PMCID: PMC7906138 DOI: 10.18632/aging.202360] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 11/20/2020] [Indexed: 12/27/2022]
Abstract
RNA binding proteins (RBPs) play significant roles in the development of tumors. However, a comprehensive analysis of the biological functions of RBPs in clear cell renal cell carcinoma (ccRCC) has not been performed. Our study aimed to construct an RBP-related risk model for prognosis prediction in ccRCC patients. First, RNA sequencing data of ccRCC were downloaded from The Cancer Genome Atlas (TCGA) database. Three RBP genes (EIF4A1, CARS, and RPL22L1) were validated as prognosis-related hub genes by univariate and multivariate Cox regression analyses and were integrated into a prognostic model by least absolute shrinkage and selection operator (LASSO) Cox regression analysis. According to this model, patients with high risk scores displayed significantly worse overall survival (OS) than those with low risk scores. Moreover, the multivariate Cox analysis results indicated that risk score, tumor grade, and tumor stage were significantly correlated with patient OS. A nomogram was constructed based on the three RBP genes and showed a good ability to predict outcomes in ccRCC patients. In conclusion, this study identified a three-RBP gene risk model for predicting the prognosis of patients, which is conducive to the identification of novel diagnostic and prognostic molecular markers.
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Affiliation(s)
- Qiang Chen
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Zhi-Long Li
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Sheng-Qiang Fu
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Si-Yuan Wang
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Yu-Tang Liu
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Ming Ma
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Xiao-Rong Yang
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Wen-Jie Xie
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Bin-Bin Gong
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Ting Sun
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
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12
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Xiao J, Jin X, Zhang C, Zou H, Chang Z, Han N, Li X, Zhang Y, Li Y. Systematic analysis of enhancer regulatory circuit perturbation driven by copy number variations in malignant glioma. Am J Cancer Res 2021; 11:3060-3073. [PMID: 33537074 PMCID: PMC7847679 DOI: 10.7150/thno.54150] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 12/16/2020] [Indexed: 12/18/2022] Open
Abstract
Background: Enhancers are emerging regulatory regions controlling gene expression in diverse cancer types. However, the functions of enhancer regulatory circuit perturbations driven by copy number variations (CNVs) in malignant glioma are unclear. Therefore, we aimed to investigate the comprehensive enhancer regulatory perturbation and identify potential biomarkers in glioma. Results: We performed a meta-analysis of the enhancer centered regulatory circuit perturbations in 683 gliomas by integrating CNVs, gene expression, and transcription factors (TFs) binding. We found widespread CNVs of enhancers during glioma progression, and CNVs were associated with the perturbations of enhancer activities. In particular, the degree of perturbations for amplified enhancers was much greater accompanied by the glioma malignant progression. In addition, CNVs and enhancers cooperatively regulated the expressions of cancer-related genes. Genome-wide TF binding profiles revealed that enhancers were pervasively regulated by TFs. A network-based analysis of TF-enhancer-gene regulatory circuits revealed a core TF-gene module (58 interactions including seven genes and 14 TFs) that was associated survival of patients with glioma (p < 0.001). Finally, we validated this prognosis-associated TF-gene regulatory module in an independent cohort. In summary, our analyses provided new molecular insights for enhancer-centered transcriptional perturbation in glioma therapy. Conclusion: Integrative analysis revealed enhancer regulatory perturbations in glioma and also identified a network module that was associated with patient survival, thereby providing novel insights into enhancer-centered cancer therapy.
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13
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Zhang Z, Wang L, Wang Q, Zhang M, Wang B, Jiang K, Ye Y, Wang S, Shen Z. Molecular Characterization and Clinical Relevance of RNA Binding Proteins in Colorectal Cancer. Front Genet 2020; 11:580149. [PMID: 33193701 PMCID: PMC7597397 DOI: 10.3389/fgene.2020.580149] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2020] [Accepted: 09/17/2020] [Indexed: 12/22/2022] Open
Abstract
Abnormal expression of RNA binding proteins (RBPs) has been reported across various cancers. However, the potential role of RBPs in colorectal cancer (CRC) remains unclear. In this study, we performed a systematic bioinformatics analysis of RBPs in CRC. We downloaded CRC data from The Cancer Genome Atlas (TCGA) database. Our analysis identified 242 differentially expressed RBPs between tumor and normal tissues, including 200 upregulated and 42 downregulated RBPs. Next, we found eight RBPs (RRS1, PABPC1L, TERT, SMAD6, UPF3B, RP9, NOL3, and PTRH1) related to the prognoses of CRC patients. Among these eight prognosis-related RBPs, four RBPs (NOL3, PTRH1, UPF3B, and SMAD6) were selected to construct a prognostic risk score model. Furthermore, our results indicated that the prognostic risk score model accurately predicted the prognosis of CRC patients [area under the receiver operating characteristic curve (AUC)for 3- and 5-year overall survival (OS) and was 0.645 and 0.672, respectively]. Furthermore, we developed a nomogram based on a prognostic risk score model. The nomogram was able to demonstrate the wonderful performance in predicting 3- and 5-year OS. Additionally, we validated the clinical value of four risk genes in the prognostic risk score model and identified that these risk genes were associated with tumorigenesis, lymph node metastasis, distant metastasis, clinical stage, and prognosis. Finally, we used the TIMER and Human Protein Atlas (HPA)database to validate the expression of four risk genes at the transcriptional and translational levels, respectively, and used a clinical cohort to validate the roles of NOL3 and UPF3B in predicting the prognosis of CRC patients. In summary, our study demonstrated that RBPs have an effect on CRC tumor progression and might be potential prognostic biomarkers for CRC patients.
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Affiliation(s)
- Zhen Zhang
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, China.,Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, China
| | - Ling Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Hepatopancreatobiliary Surgery Department I, Peking University Cancer Hospital and Institute, Beijing, China
| | - Quan Wang
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, China.,Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, China
| | - Mengmeng Zhang
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, China.,Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, China
| | - Bo Wang
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, China.,Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, China
| | - Kewei Jiang
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, China.,Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, China
| | - Yingjiang Ye
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, China.,Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, China
| | - Shan Wang
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, China.,Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, China
| | - Zhanlong Shen
- Department of Gastroenterological Surgery, Peking University People's Hospital, Beijing, China.,Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Research, Peking University People's Hospital, Beijing, China
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14
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Wang Z, Yin J, Zhou W, Bai J, Xie Y, Xu K, Zheng X, Xiao J, Zhou L, Qi X, Li Y, Li X, Xu J. Complex impact of DNA methylation on transcriptional dysregulation across 22 human cancer types. Nucleic Acids Res 2020; 48:2287-2302. [PMID: 32002550 PMCID: PMC7049702 DOI: 10.1093/nar/gkaa041] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 01/14/2020] [Indexed: 12/18/2022] Open
Abstract
Accumulating evidence has demonstrated that transcriptional regulation is affected by DNA methylation. Understanding the perturbation of DNA methylation-mediated regulation between transcriptional factors (TFs) and targets is crucial for human diseases. However, the global landscape of DNA methylation-mediated transcriptional dysregulation (DMTD) across cancers has not been portrayed. Here, we systematically identified DMTD by integrative analysis of transcriptome, methylome and regulatome across 22 human cancer types. Our results revealed that transcriptional regulation was affected by DNA methylation, involving hundreds of methylation-sensitive TFs (MethTFs). In addition, pan-cancer MethTFs, the regulatory activity of which is generally affected by DNA methylation across cancers, exhibit dominant functional characteristics and regulate several cancer hallmarks. Moreover, pan-cancer MethTFs were found to be affected by DNA methylation in a complex pattern. Finally, we investigated the cooperation among MethTFs and identified a network module that consisted of 43 MethTFs with prognostic potential. In summary, we systematically dissected the transcriptional dysregulation mediated by DNA methylation across cancer types, and our results provide a valuable resource for both epigenetic and transcriptional regulation communities.
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Affiliation(s)
- Zishan Wang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Jiaqi Yin
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Weiwei Zhou
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Jing Bai
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yunjin Xie
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Kang Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Xiangyi Zheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Jun Xiao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Li Zhou
- Department of Nephrology, Affiliated Hospital of Chengde Medical College, Chengde, Hebei Province, China
| | - Xiaolin Qi
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, Hainan 571199, China
| | - Yongsheng Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.,Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, Hainan 571199, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, Hainan 570100, China
| | - Xia Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.,Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, Hainan 571199, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, Hainan 570100, China
| | - Juan Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.,Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou, Hainan 571199, China.,College of Biomedical Information and Engineering, Hainan Medical University, Haikou, Hainan 570100, China
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15
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Li W, Li X, Gao LN, You CG. Integrated Analysis of the Functions and Prognostic Values of RNA Binding Proteins in Lung Squamous Cell Carcinoma. Front Genet 2020; 11:185. [PMID: 32194639 PMCID: PMC7066120 DOI: 10.3389/fgene.2020.00185] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Accepted: 02/17/2020] [Indexed: 12/17/2022] Open
Abstract
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.
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Affiliation(s)
- Wei Li
- Laboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou, China
| | - Xue Li
- Laboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou, China
| | - Li-Na Gao
- Laboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou, China
| | - Chong-Ge You
- Laboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou, China
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16
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Zhang J, Li S, Zhang L, Xu J, Song M, Shao T, Huang Z, Li Y. RBP EIF2S2 Promotes Tumorigenesis and Progression by Regulating MYC-Mediated Inhibition via FHIT-Related Enhancers. Mol Ther 2020; 28:1105-1118. [PMID: 32059763 DOI: 10.1016/j.ymthe.2020.02.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 01/20/2020] [Indexed: 12/15/2022] Open
Abstract
RNA-binding proteins (RBPs) play fundamental roles in cancer; however, we still lack knowledge about to what extent RBPs are dysregulated, as well as about perturbed signaling pathways in cancer. In this study, we integrated analysis of multidimensional data across >10,000 cancer patients and >1,000 cell lines. We identified a top candidate RBP: eukaryotic translation initiation factor 2 subunit beta (EIF2S2). EIF2S2 is highly expressed in tumors and is associated with malignant features as well as patient prognosis. Functional assays performed in cancer cells revealed that EIF2S2 promotes cancer cell proliferation, migration, and invasion in vitro as well as tumor growth and metastasis in vivo. Mechanistic investigations further demonstrated that EIF2S2 promotes tumorigenesis and progression by directly binding to a long non-coding RNA, LINC01600, which physically interacts with the MYC protein and increases its stability. Interestingly, we revealed that the EIF2S2-LINC01600-MYC axis can activate the Wnt/β-catenin pathway by inhibiting the activity of FHIT-related enhancers and FHIT expression. Finally, EIF2S2 knockdown combined with oxaliplatin treatment could be a potential combination therapy in cancer. Our integrated analysis provided detailed knowledge of the function of the EIF2S2-LINC01600-MYC axis, which will facilitate the development of rational combination therapies for cancer.
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Affiliation(s)
- Jiwei Zhang
- The MOE Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
| | - Shengli Li
- Department of Biochemistry and Molecular Biology, The University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX 77030, USA
| | - Ling Zhang
- College of Life Science, Zhejiang Chinese Medical University, Hangzhou 310009, China
| | - Juan Xu
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou 571199, China; College of Biomedical Information and Engineering, Hainan Medical University, Haikou 571199, China; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Mingxu Song
- Wuxi Cancer Institute, Affiliated Hospital of Jiangnan University, 200 Huihe Road, Wuxi Shi, Jiangsu Province 214123, China
| | - Tingting Shao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China
| | - Zhaohui Huang
- Wuxi Cancer Institute, Affiliated Hospital of Jiangnan University, 200 Huihe Road, Wuxi Shi, Jiangsu Province 214123, China.
| | - Yongsheng Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, Haikou 571199, China; College of Biomedical Information and Engineering, Hainan Medical University, Haikou 571199, China; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
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17
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Wang J, Qi J, Hou X. Systematically Dissecting the Function of RNA-Binding Proteins During Glioma Progression. Front Genet 2020; 10:1394. [PMID: 32047515 PMCID: PMC6997557 DOI: 10.3389/fgene.2019.01394] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 12/19/2019] [Indexed: 12/14/2022] Open
Abstract
RNA-binding proteins (RBPs) play important roles in regulating gene expression and dysregulation of RBPs have been observed in various types of cancer. However, the role of RBPs during glioma progression, and particular in Chinese patients, is only starting to be unveiled. Here, we systematically analyzed the somatic mutation, gene expression patterns of 2949 RBPs during glioma progression. Our comprehensive study reveals several of highly mutated genes (such as ATRX, TTN and SETD2) and differentially expressed genes (such as KIF4A, TTK and CEP55). Integration of the expression of RBPs and genes, we constructed a regulatory network in glioma and revealed the functional links between RBPs and cancer-related genes. Moreover, we identified the prognosis spectrum of RBPs during glioma progression. The expression of a number of RBPs, such as SNRPN and IGF2BP3, are significantly associated with overall survival of patients in all grades. Taken together, our analyses provided a valuable RBP resource during glioma progression, and revealed several candidates that potentially contribute to development of therapeutic targets for glioma.
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Affiliation(s)
- Jianjun Wang
- Department of Neurosurgery, The First Hospital Affiliated with Shandong First Medical University, Shandong Provincial Qianfoshan Hospital, Jinan, China
| | - Jianfeng Qi
- Department of Neurosurgery, The First Hospital Affiliated with Shandong First Medical University, Shandong Provincial Qianfoshan Hospital, Jinan, China.,College of Medicine, Shandong First Medical University, Taian, China
| | - Xianzeng Hou
- Department of Neurosurgery, The First Hospital Affiliated with Shandong First Medical University, Shandong Provincial Qianfoshan Hospital, Jinan, China
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18
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Nahalka J. The role of the protein-RNA recognition code in neurodegeneration. Cell Mol Life Sci 2019; 76:2043-2058. [PMID: 30980111 PMCID: PMC11105320 DOI: 10.1007/s00018-019-03096-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Revised: 03/14/2019] [Accepted: 04/08/2019] [Indexed: 12/14/2022]
Abstract
MicroRNAs are small endogenous RNAs that pair and bind to sites on mRNAs to direct post-transcriptional repression. However, there is a possibility that microRNAs directly influence protein structure and activity, and this influence can be termed post-translational riboregulation. This conceptual review explores the literature on neurodegenerative disorders. Research on the association between neurodegeneration and RNA-repeat toxicity provides data that support a protein-RNA recognition code. For example, this code explains why hnRNP H and SFPQ proteins, which are involved in amyotrophic lateral sclerosis, are sequestered by the (GGGGCC)n repeat sequence. Similarly, it explains why MNBL proteins and (CTG)n repeats in RNA, which are involved in myotonic dystrophy, are sequestered into RNA foci. Using this code, proteins involved in diseases can be identified. A simple protein BLAST search of the human genome for amino acid repeats that correspond to the nucleotide repeats reveals new proteins among already known proteins that are involved in diseases. For example, the (CAG)n repeat sequence, when transcribed into possible peptide sequences, leads to the identification of PTCD3, Rem2, MESP2, SYPL2, WDR33, COL23A1, and others. After confirming this approach on RNA repeats, in the next step, the code was used in the opposite manner. Proteins that are involved in diseases were compared with microRNAs involved in those diseases. For example, a reasonable correspondence of microRNA 9 and 107 with amyloid-β-peptide (Aβ42) was identified. In the last step, a miRBase search for micro-nucleotides, obtained by transcription of a prion amino acid sequence, revealed new microRNAs and microRNAs that have previously been identified as involved in prion diseases. This concept provides a useful key for designing RNA or peptide probes.
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Affiliation(s)
- Jozef Nahalka
- Institute of Chemistry, Centre for Glycomics, Slovak Academy of Sciences, Dubravska cesta 9, 84538, Bratislava, Slovak Republic.
- Institute of Chemistry, Centre of Excellence for White-green Biotechnology, Slovak Academy of Sciences, Trieda Andreja Hlinku 2, 94976, Nitra, Slovak Republic.
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19
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Li Y, Zhang Y, Li X, Yi S, Xu J. Gain-of-Function Mutations: An Emerging Advantage for Cancer Biology. Trends Biochem Sci 2019; 44:659-674. [PMID: 31047772 DOI: 10.1016/j.tibs.2019.03.009] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 03/21/2019] [Accepted: 03/26/2019] [Indexed: 02/08/2023]
Abstract
Advances in next-generation sequencing have identified thousands of genomic variants that perturb the normal functions of proteins, further contributing to diverse phenotypic consequences in cancer. Elucidating the functional pathways altered by loss-of-function (LOF) or gain-of-function (GOF) mutations will be crucial for prioritizing cancer-causing variants and their resultant therapeutic liabilities. In this review, we highlight the fundamental function of GOF mutations and discuss the potential mechanistic effects in the context of signaling networks. We also summarize advances in experimental and computational resources, which will dramatically help with studies on the functional and phenotypic consequences of mutations. Together, systematic investigations of the function of GOF mutations will provide an important missing piece for cancer biology and precision therapy.
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Affiliation(s)
- Yongsheng Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China; Department of Oncology, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA
| | - Yunpeng Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
| | - Xia Li
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China; College of Bioinformatics, Hainan Medical University, Haikou 570100, China.
| | - Song Yi
- Department of Oncology, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA; Department of Biomedical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
| | - Juan Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
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Jimenez M, Arechederra M, Ávila MA, Berasain C. Splicing alterations contributing to cancer hallmarks in the liver: central role of dedifferentiation and genome instability. Transl Gastroenterol Hepatol 2018; 3:84. [PMID: 30505971 DOI: 10.21037/tgh.2018.10.11] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 10/22/2018] [Indexed: 12/11/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is a major cause of cancer-related death worldwide. HCCs are molecularly heterogeneous tumors, and this complexity is to a great extent responsible for their poor response to conventional and targeted therapies. In this review we summarize recent evidence indicating that imbalanced expression of mRNA splicing factors can be a relevant source for this heterogeneity. We also discuss how these alterations may play a driver role in hepatocarcinogenesis by impinging on the general hallmarks of cancer. Considering the natural history of HCC, we focused on two pathogenic features that are characteristic of liver tumors: chromosomal instability and phenotypic de-differentiation. We highlight mechanisms connecting splicing derangement with these two processes and the enabling capacities acquired by liver cells along their neoplastic transformation. A thorough understanding of the alterations in the splicing machinery may also help to identify new HCC biomarkers and to design novel therapeutic strategies.
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Affiliation(s)
- Maddalen Jimenez
- Hepatology Program, CIMA, University of Navarra, Pamplona, Spain
| | | | - Matías A Ávila
- Hepatology Program, CIMA, University of Navarra, Pamplona, Spain.,CIBERehd, Instituto de Salud Carlos III, Madrid, Spain.,Instituto de Investigaciones Sanitarias de Navarra-IdiSNA, Pamplona, Spain
| | - Carmen Berasain
- Hepatology Program, CIMA, University of Navarra, Pamplona, Spain.,CIBERehd, Instituto de Salud Carlos III, Madrid, Spain.,Instituto de Investigaciones Sanitarias de Navarra-IdiSNA, Pamplona, Spain
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