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      High Endothelin Receptor Type A Expression as an Independent Prognostic Biomarker and Correlated with Immune Infiltrates in Stomach Adenocarcinoma


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          Stomach adenocarcinoma (STAD) is the most common gastrointestinal cancer and is associated with high mortality worldwide. Endothelin receptor type A (EDNRA) is associated with guanine-nucleotide-binding (G) proteins and plays important roles in cellular processes and various diseases.


          To investigate the prognosis value of EDNRA expression and its correlation with immune infiltrates in patients with STAD.


          The association between clinical characteristics and EDNRA expression in STAD was analyzed using the Wilcoxon signed-rank test and logistic regression. The Kaplan–Meier plotter analysis and Cox regression were constructed to evaluate the influence of EDNRA on prognosis, and a receiver operating characteristic (ROC) curve and nomogram were constructed. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were conducted to analyze the correlation between EDNRA and immune infiltrates. In addition, Oncomine, TIMER databases and qRT-PCR of STAD cell lines were used to verify the EDNRA expression in STAD.


          Our results revealed that EDNRA expression was significantly higher in patients with STAD than normal gastric tissues, and the results have been confirmed by RT-qPCR. KM-plotter analysis revealed that patients with STAD had shorter OS, FP, and PPS (P<0.001). Multivariate Cox analysis further confirmed that high EDNRA expression was an independent risk factor for OS in patients with STAD. Moreover, other clinicopathologic features were related with worse prognosis in STAD, including age, lymph nodes metastases and primary outcome. More importantly, ROC analysis also confirmed the diagnostic value, and a prognostic nomogram involving age, T, M, N classification, pathologic stage, residual tumor and EDNRA was constructed. GSEA revealed that high EDNRA expression was correlated with immunoregulatory interactions between lymphoid and non lymphoid cells pathways, natural killer cell activation involved in immune response, interleukin 1 receptor binding and pathways in cancer, and ssGSEA showed that EDNRA is correlated with macrophages and NK cells.


          Collectively, EDNRA can be an independent prognostic biomarker and correlated with immune infiltration in stomach adenocarcinoma.

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          Most cited references29

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            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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              Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.

                Author and article information

                Cancer Manag Res
                Cancer Manag Res
                Cancer Management and Research
                28 June 2021
                : 13
                : 5013-5026
                [1 ]The First Clinical Medical College, Guangzhou University of Chinese Medicine , Guangzhou, 510000, People’s Republic of China
                [2 ]Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University , Changsha, Hunan, 410011, People’s Republic of China
                [3 ]Department of Gastroenterology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine , Guangzhou, 510000, People’s Republic of China
                Author notes
                Correspondence: Peiwu Li; Yi Wen Email doctorlipw@gzucm.edu.cn; 421491922@qq.com
                © 2021 Yan et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                Page count
                Figures: 9, Tables: 6, References: 29, Pages: 14
                Funded by: Guangdong natural science fund project, China;
                Funded by: Major research project of Guangzhou University of Chinese medicine, China;
                This study was supported by D3-2-4 Young scholar of Qihuang, No. 08004001004003002004; Guangdong natural science fund project, China (2019), No.2019A1515011145; Major research project of Guangzhou University of Chinese medicine, China, No. A1-AFD018201A51; The first affiliated hospital of Guangzhou University of Chinese medicine “Innovative Strong Hospital ” clinical research project, China (2019), No.2019IIT19;Liu Fengbin, Guangdong famous traditional Chinese medicine inheritance studio (Guangdong traditional Chinese medicine office [2020] no. 1).
                Original Research

                Oncology & Radiotherapy
                Oncology & Radiotherapy
                ednra, stad, bioinformatics, prognosis


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