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Hao M, Qi Y, Xu R, Zhao K, Li M, Shan Y, Xia T, Yang K, Hasi W, Zhang C, Li D, Wang Y, Wang P, Kuang H. ENCD: a manually curated database of experimentally supported endocrine system disease and lncRNA associations. Database (Oxford) 2023; 2023:6991525. [PMID: 36653322 PMCID: PMC9849115 DOI: 10.1093/database/baac113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/07/2022] [Accepted: 12/28/2022] [Indexed: 01/20/2023]
Abstract
ENCD (http://www.bio-server.cn/ENCD/) is a manually curated database that provides comprehensive experimentally supported associations among endocrine system diseases (ESDs) and long non-coding ribonucleic acid (lncRNAs). The incidence of ESDs has increased in recent years, often accompanying other chronic diseases, and can lead to disability. A growing body of research suggests that lncRNA plays an important role in the progression and metastasis of ESDs. However, there are no resources focused on collecting and integrating the latest and experimentally supported lncRNA-ESD associations. Hence, we developed an ENCD database that consists of 1379 associations between 35 ESDs and 501 lncRNAs in 12 human tissues curated from literature. By using ENCD, users can explore the genetic data for diseases corresponding to the body parts of interest as well as study the lncRNA regulating mechanism for ESDs. ENCD also provides a flexible tool to visualize a disease- or gene-centric regulatory network. In addition, ENCD offers a submission page for researchers to submit their newly discovered endocrine disorders-genetic data entries online. Collectively, ENCD will provide comprehensive insights for investigating the ESDs associated with lncRNAs. Database URL http://www.bio-server.cn/ENCD.
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Affiliation(s)
| | | | | | | | - Mingqing Li
- Department of Endocrinology, The First Affiliated Hospital of Harbin Medical University, 23 Youzheng Road, Harbin 150081, China
| | - Yongyan Shan
- Department of Endocrinology, The First Affiliated Hospital of Harbin Medical University, 23 Youzheng Road, Harbin 150081, China
| | - Tian Xia
- Department of Endocrinology, The First Affiliated Hospital of Harbin Medical University, 23 Youzheng Road, Harbin 150081, China
| | - Kun Yang
- Department of Endocrinology, The First Affiliated Hospital of Harbin Medical University, 23 Youzheng Road, Harbin 150081, China
| | - Wuyang Hasi
- Department of Endocrinology, The First Affiliated Hospital of Harbin Medical University, 23 Youzheng Road, Harbin 150081, China
| | - Cong Zhang
- Department of Endocrinology, The First Affiliated Hospital of Harbin Medical University, 23 Youzheng Road, Harbin 150081, China
| | - Daowei Li
- Department of Endocrinology, The First Affiliated Hospital of Harbin Medical University, 23 Youzheng Road, Harbin 150081, China
| | - Yi Wang
- Department of Endocrinology, The First Affiliated Hospital of Harbin Medical University, 23 Youzheng Road, Harbin 150081, China
| | - Peng Wang
- *Corresponding author: Tel: +8645185555060; Fax: +8645185555060; Correspondence may also be addressed to Peng Wang. Tel: +8645186669617; Fax: +8645186669617;
| | - Hongyu Kuang
- *Corresponding author: Tel: +8645185555060; Fax: +8645185555060; Correspondence may also be addressed to Peng Wang. Tel: +8645186669617; Fax: +8645186669617;
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Yao JM, Zhao JY, Lv FF, Yang XB, Wang HJ. A Potential Nine-lncRNAs Signature Identification and Nomogram Diagnostic Model Establishment for Papillary Thyroid Cancer. Pathol Oncol Res 2022; 28:1610012. [PMID: 35280112 PMCID: PMC8906208 DOI: 10.3389/pore.2022.1610012] [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: 08/06/2021] [Accepted: 01/19/2022] [Indexed: 12/24/2022]
Abstract
The purpose of our current study was to establish a long non-coding RNA(lncRNA) signature and assess its prognostic and diagnostic power in papillary thyroid cancer (PTC). LncRNA expression profiles were obtained from the Cancer Genome Atlas (TCGA). The key module and hub lncRNAs related to PTC were determined by weighted gene co-expression network analysis (WGCNA) and LASSO Cox regression analyses, respectively. Functional enrichment analyses, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis were implemented to analyze the possible biological processes and signaling pathways of hub lncRNAs. Associations between key lncRNA expressions and tumor-infiltrating immune cells were identified using the TIMER website, and proportions of immune cells in high/low risk score groups were compared. Kaplan-Meier Plotter was used to evaluate the prognostic significance of hub genes in PTC. A diagnostic model was conducted with logistic regression analysis, and its diagnostic performance was assessed by calibration/receiver operating characteristic curves and principal component analysis. A nine-lncRNAs signature (SLC12A5-AS1, LINC02028, KIZ-AS1, LINC02019, LINC01877, LINC01444, LINC01176, LINC01290, and LINC00581) was established in PTC, which has significant diagnostic and prognostic power. Functional enrichment analyses elucidated the regulatory mechanism of the nine-lncRNAs signature in the development of PTC. This signature and expressions of nine hub lncRNAs were correlated with the distributions of tumor infiltrating immune cells. A diagnostic nomogram was also established for PTC. By comparing with the published models with less than or equal to nine lncRNAs, our signature showed a preferable performace for prognosis prediction. In conclusion, our present research established an innovative nine-lncRNAs signature and a six-lncRNAs nomogram that might act as a potential indicator for PTC prognosis and diagnosis, which could be conducive to the PTC treatment.
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Affiliation(s)
- Jin-Ming Yao
- Department of Endocrinology and Metabology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China.,Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Jinan, China.,Shandong Institute of Nephrology, Jinan, China
| | - Jun-Yu Zhao
- Department of Endocrinology and Metabology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China.,Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Jinan, China.,Shandong Institute of Nephrology, Jinan, China
| | - Fang-Fang Lv
- Department of Endocrinology and Metabology, The 960th hospital of the PLA Joint Logistics Support Force, Jinan, China
| | - Xue-Bo Yang
- Beijing Splinger Institute of Medicine, Jinan, China
| | - Huan-Jun Wang
- Department of Endocrinology and Metabology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China.,Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Jinan, China.,Shandong Institute of Nephrology, Jinan, China
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Lv W, Tan Y, Zhao C, Wang Y, Wu M, Wu Y, Ren Y, Zhang Q. Identification of pyroptosis-related lncRNAs for constructing a prognostic model and their correlation with immune infiltration in breast cancer. J Cell Mol Med 2021; 25:10403-10417. [PMID: 34632690 PMCID: PMC8581320 DOI: 10.1111/jcmm.16969] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 08/28/2021] [Accepted: 09/19/2021] [Indexed: 12/19/2022] Open
Abstract
The inflammasome-dependent cell death, which is denoted as pyroptosis, might be abnormally regulated during oncogenesis and tumour progression. Long non-coding RNAs (LncRNAs) are pivotal orchestrators in breast cancer (BC), which have the potential to be a biomarker for BC diagnosis and therapy. The present study aims to explore the correlation between pyroptosis-related lncRNAs and BC prognosis. In this study, a profile of 8 differentially expressed lncRNAs was screened in the TCGA database and used to construct a prognostic model. The BC patients were divided into high- and low-risk groups dependent on the median cutoff of the risk score in the model. Interestingly, the risk model significantly distinguished the clinical characteristics of BC patients between high- and low-risk groups. Then, the risk score of the model was identified to be an excellent independent prognostic factor. Notably, the GO, KEGG, GSEA and ssGSEA analyses revealed the different immune statuses between the high- and low-risk groups. Particularly, the 8 lncRNAs expressed differentially in BC tissues between two risk subgroups in vitro validation. Collectively, this constructed well-validated model is of high effectiveness to predict the prognosis of BC, which will provide novel means that is applicable for BC prognosis recognition.
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Affiliation(s)
- Wenchang Lv
- Department of Plastic and Cosmetic SurgeryTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Yufang Tan
- Department of Plastic and Cosmetic SurgeryTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Chongru Zhao
- Department of Plastic and Cosmetic SurgeryTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Yichen Wang
- Department of Plastic and Cosmetic SurgeryTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Min Wu
- Department of Plastic and Cosmetic SurgeryTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Yiping Wu
- Department of Plastic and Cosmetic SurgeryTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Yuping Ren
- Department of Plastic and Cosmetic SurgeryTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Qi Zhang
- Department of Plastic and Cosmetic SurgeryTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
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Lai J, Chen B, Zhang G, Li X, Mok H, Liao N. Molecular characterization of breast cancer: a potential novel immune-related lncRNAs signature. J Transl Med 2020; 18:416. [PMID: 33160384 PMCID: PMC7648293 DOI: 10.1186/s12967-020-02578-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Accepted: 10/24/2020] [Indexed: 12/11/2022] Open
Abstract
Background Accumulating evidence has demonstrated that immune-related lncRNAs (IRLs) are commonly aberrantly expressed in breast cancer (BC). Thus, we aimed to establish an IRL-based tool to improve prognosis prediction in BC patients. Methods We obtained IRL expression profiles in large BC cohorts (N = 911) from The Cancer Genome Atlas (TCGA) database. Then, in light of the correlation between each IRL and recurrence-free survival (RFS), we screened prognostic IRL signatures to construct a novel RFS nomogram via a Cox regression model. Subsequently, the performance of the IRL-based model was evaluated through discrimination, calibration ability, risk stratification ability and decision curve analysis (DCA). Results A total of 52 IRLs were obtained from TCGA. Based on multivariate Cox regression analyses, four IRLs (A1BG-AS1, AC004477.3, AC004585.1 and AC004854.2) and two risk parameters (tumor subtype and TNM stage) were utilized as independent indicators to develop a novel prognostic model. In terms of predictive accuracy, the IRL-based model was distinctly superior to the TNM staging system (AUC: 0.728 VS 0.673, P = 0.010). DCA indicated that our nomogram had favorable clinical practicability. In addition, risk stratification analysis showed that the IRL-based tool efficiently divided BC patients into high- and low-risk groups (P < 0.001). Conclusions A novel IRL-based model was constructed to predict the risk of 5-year RFS in BC. Our model can improve the predictive power of the TNM staging system and identify high-risk patients with tumor recurrence to implement more appropriate treatment strategies.
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Affiliation(s)
- Jianguo Lai
- Department of Breast Cancer, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Yuexiu district, Guangzhou, 510080, Guangdong, China
| | - Bo Chen
- Department of Breast Cancer, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Yuexiu district, Guangzhou, 510080, Guangdong, China
| | - Guochun Zhang
- Department of Breast Cancer, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Yuexiu district, Guangzhou, 510080, Guangdong, China
| | - Xuerui Li
- Department of Breast Cancer, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Yuexiu district, Guangzhou, 510080, Guangdong, China
| | - Hsiaopei Mok
- Department of Breast Cancer, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Yuexiu district, Guangzhou, 510080, Guangdong, China
| | - Ning Liao
- Department of Breast Cancer, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Yuexiu district, Guangzhou, 510080, Guangdong, China.
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Dobre EG, Dinescu S, Costache M. Connecting the Missing Dots: ncRNAs as Critical Regulators of Therapeutic Susceptibility in Breast Cancer. Cancers (Basel) 2020; 12:E2698. [PMID: 32967267 PMCID: PMC7565380 DOI: 10.3390/cancers12092698] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Revised: 09/10/2020] [Accepted: 09/14/2020] [Indexed: 12/24/2022] Open
Abstract
Whether acquired or de novo, drug resistance remains a significant hurdle in achieving therapeutic success in breast cancer (BC). Thus, there is an urge to find reliable biomarkers that will help in predicting the therapeutic response. Stable and easily accessible molecules such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are regarded as valuable prognostic biomarkers and therapeutic targets since they act as crucial regulators of the various mechanisms involved in BC drug resistance. Here, we reviewed the current literature on ncRNAs as mediators of resistance to systemic therapies in BC. Interestingly, upon integrating data results from individual studies, we concluded that miR-221, miR-222, miR-451, Urothelial Carcinoma Associated 1 (UCA1), and Growth arrest-specific 5 (GAS5) are strong candidates as prognostic biomarkers and therapeutic targets since they are regulating multiple drug resistance phenotypes in BC. However, further research around their clinical implications is needed to validate and integrate them into therapeutic applications. Therefore, we believe that our review may provide relevant evidence for the selection of novel therapeutic targets and prognostic biomarkers for BC and will serve as a foundation for future translational research in the field.
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Affiliation(s)
- Elena-Georgiana Dobre
- AMS Genetic Lab, 030882 Bucharest, Romania;
- Department of Biochemistry and Molecular Biology, University of Bucharest, 050095 Bucharest, Romania;
| | - Sorina Dinescu
- Department of Biochemistry and Molecular Biology, University of Bucharest, 050095 Bucharest, Romania;
- The Research Institute of the University of Bucharest, 050095 Bucharest, Romania
| | - Marieta Costache
- Department of Biochemistry and Molecular Biology, University of Bucharest, 050095 Bucharest, Romania;
- The Research Institute of the University of Bucharest, 050095 Bucharest, Romania
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