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      Potential role of m6A RNA methylation regulators in osteosarcoma and its clinical prognostic value

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          Abstract

          Background

          Osteosarcoma is a disease with high mortality in children and adolescents, and metastasis is one of the important clinical features of osteosarcoma. N6-Methyladenosine (m6A) is the most abundant methylation modification in mRNA, which is regulated by m6A regulators. It is reported that it is related to the occurrence and development of tumors. However, the mechanism of its action in osteosarcoma is rarely known. The purpose of this study was to identify the potential role of m6A regulatory factor in osteosarcoma and its clinical prognostic value.

          Methods

          Here, we used The Cancer Genome Atlas (TCGA) to comprehensively analyze the relationship between m6A regulatory factors and osteosarcoma (metastasis group and non-metastasis group). We analyzed their survival relationship and analyzed all the m6A regulatory factors in TCGA tumor data set by using the univariate Cox proportional hazard regression model. Finally, we selected two survival-related methylation regulators (FTO and IGF2BP2) as risk gene signature.

          Results

          According to the median risk, patients were divided into low-risk group and high-risk group. Multivariate Cox regression analysis showed that these two risk genes were considered to be the key factors independently predicting the prognosis of patients with osteosarcoma. In addition, we verified their characteristics with gene expression omnibus (GEO) DataSets and confirmed that they are related to tumor and immune-related signaling pathways through gene set enrichment analysis (GESA) and immune infiltration analysis.

          Conclusions

          In conclusion, m6A regulators might play an important role in the metastasis of osteosarcoma and have potential important value for the prognosis and treatment strategy of osteosarcoma patients.

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          Most cited references43

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          Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

          Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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            TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells.

            Recent clinical successes of cancer immunotherapy necessitate the investigation of the interaction between malignant cells and the host immune system. However, elucidation of complex tumor-immune interactions presents major computational and experimental challenges. Here, we present Tumor Immune Estimation Resource (TIMER; cistrome.shinyapps.io/timer) to comprehensively investigate molecular characterization of tumor-immune interactions. Levels of six tumor-infiltrating immune subsets are precalculated for 10,897 tumors from 32 cancer types. TIMER provides 6 major analytic modules that allow users to interactively explore the associations between immune infiltrates and a wide spectrum of factors, including gene expression, clinical outcomes, somatic mutations, and somatic copy number alterations. TIMER provides a user-friendly web interface for dynamic analysis and visualization of these associations, which will be of broad utilities to cancer researchers. Cancer Res; 77(21); e108-10. ©2017 AACR.
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              N6-Methyladenosine in Nuclear RNA is a Major Substrate of the Obesity-Associated FTO

              We report here that FTO (fat mass and obesity-associated protein) exhibits efficient oxidative demethylation activity of abundant N 6-methyladenosine (m6A) residues in RNA in vitro. FTO knockdown with siRNA led to an increased level of m6A in mRNA, whereas overexpression of FTO resulted in a decreased level of m6A in human cells. We further show that FTO partially colocalizes with nuclear speckles, supporting m6A in nuclear RNA as a physiological substrate of FTO.
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                Author and article information

                Contributors
                caizgemail@126.com
                Journal
                J Orthop Surg Res
                J Orthop Surg Res
                Journal of Orthopaedic Surgery and Research
                BioMed Central (London )
                1749-799X
                5 May 2021
                5 May 2021
                2021
                : 16
                : 294
                Affiliations
                [1 ]Department of Orthopedics, Haian Hospital of Traditional Chinese Medicine, 55 Ninghai Middle Road, Haian, Nantong, Jiangsu Province 226600 People’s Republic of China
                [2 ]GRID grid.260483.b, ISNI 0000 0000 9530 8833, Key Laboratory of Neuroregeneration of Jiangsu and Ministry of Education, , Nantong University, ; Nantong, Jiangsu Province 226001 People’s Republic of China
                [3 ]Clinical Laboratory, Haian Hospital of Traditional Chinese Medicine, Haian, Nantong, Jiangsu Province 226600 People’s Republic of China
                Author information
                http://orcid.org/0000-0002-7882-1875
                Article
                2422
                10.1186/s13018-021-02422-5
                8097785
                33952279
                a401a77a-6909-4d73-a042-29041e462dd0
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 16 February 2021
                : 14 April 2021
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2021

                Surgery
                osteosarcoma,m6a,m6a regulators,prognosis,tcga
                Surgery
                osteosarcoma, m6a, m6a regulators, prognosis, tcga

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