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      Overexpressed PLAU and its potential prognostic value in head and neck squamous cell carcinoma

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          Abstract

          Background

          Metastasis is a major event for survival and prognosis in patients with head and neck squamous cell carcinomas (HNSCC). A primary cause of metastasis is the proteolytic degradation of the extracellular matrix (ECM). The plasminogen activator urokinase (PLAU) is involved in the transformation of plasminogen to plasmin leading to hydrolyzation of ECM-related proteins. However, the role of PLAU expression in HNSCC is unclear and the worth being investigated.

          Methods

          PLAU expression profiles and clinical parameters from multiple HNSCC datasets were used to investigate the relationship of PLAU expression and HNSCC survival. GO and PPI network were established on PLAU-related downstream molecular. The stroma score was deconvoluted for analysis of PLAU’s association with the immune environment. ROC analysis was applied to show the performance of PLAU in predicting HNSCC prognosis.

          Results

          PLAU mRNA was significantly elevated, as opposed to its methylation, in HNSCC tumor samples over normal specimens (all p < 0.01). Univariate and multivariate cox analysis showed PLAU could be an independent indicator for HNSCC prognosis. Combining with neck lymph node status, the AUC of PLAU in predicting 5-years overall survival reached to 0.862. GO enrichment analysis showed the major biological process (extracellular matrix organization and the P13K-Akt signaling pathway) may involve to the possible mechanism of PLAU’s function on HNSCC prognosis. Furthermore, PLAU expression was positively correlated with stroma cell score, M1 type macrophages, and negatively associated with CD4 + T cell, Tregs cell, and follicular helper T cell.

          Conclusions

          PLAU might be an independent biomarker for predicting outcomes of HNSCC patients. The elevated expression of PLAU was associated with HPV positivity and neck node status. The PI3K-Akt pathway and aberrant proportions of immune cells might underly the mechanism of PLAU’s oncogene role in HNSCC.

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          Most cited references50

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          Hallmarks of Cancer: The Next Generation

          The hallmarks of cancer comprise six biological capabilities acquired during the multistep development of human tumors. The hallmarks constitute an organizing principle for rationalizing the complexities of neoplastic disease. They include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis. Underlying these hallmarks are genome instability, which generates the genetic diversity that expedites their acquisition, and inflammation, which fosters multiple hallmark functions. Conceptual progress in the last decade has added two emerging hallmarks of potential generality to this list-reprogramming of energy metabolism and evading immune destruction. In addition to cancer cells, tumors exhibit another dimension of complexity: they contain a repertoire of recruited, ostensibly normal cells that contribute to the acquisition of hallmark traits by creating the "tumor microenvironment." Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer. Copyright © 2011 Elsevier Inc. All rights reserved.
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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.
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              We introduce CIBERSORT, a method for characterizing cell composition of complex tissues from their gene expression profiles. When applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen, and fixed tissues, including solid tumors, CIBERSORT outperformed other methods with respect to noise, unknown mixture content, and closely related cell types. CIBERSORT should enable large-scale analysis of RNA mixtures for cellular biomarkers and therapeutic targets (http://cibersort.stanford.edu).
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                15 January 2021
                2021
                : 9
                : e10746
                Affiliations
                [1 ]Department of Otolaryngology-Head and Neck Surgery, The Xiangya Hospital, Central South University , Changsha, Hunan, China
                [2 ]Otolaryngology Major Disease Research Key Laboratory of Hunan Province , Changsha, Hunan, China
                [3 ]Clinical Research Center for Pharyngolaryngeal Diseases and Voice Disorders in Hunan Province , Changsha, Hunan, China
                [4 ]National Clinical Research Center for Geriatric Disorders , Changsha, Hunan, China
                [5 ]Department of Otolaryngology-Head and Neck Surgery, The Second Xiangya Hospital, Central South University , Changsha, Hunan, China
                Article
                10746
                10.7717/peerj.10746
                7812932
                33520474
                6915670c-cf66-4129-9bf0-95843af407a1
                ©2021 Li et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 27 July 2020
                : 18 December 2020
                Funding
                Funded by: Project of Hunan Health Commission
                Award ID: B2019165
                Funded by: National Natural Science Foundation of China
                Award ID: 81974424
                Award ID: 81874133
                Award ID: 81772903
                Award ID: 81602389
                Funded by: Natural Science Foundation of Hunan Province
                Award ID: 2020JJ4827
                Award ID: 2019JJ50944
                Award ID: 2018JJ2630
                Funded by: Huxiang Young Talent Project
                Award ID: 2018RS3024
                This research was supported by the Project of Hunan Health Commission (B2019165), the National Natural Science Foundation of China (Nos. 81974424, 81874133, 81772903, and 81602389), the Natural Science Foundation of Hunan Province (Nos. 2020JJ4827, 2019JJ50944, and 2018JJ2630) and the Huxiang Young Talent Project (No. 2018RS3024). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Bioinformatics
                Oncology
                Otorhinolaryngology

                the plasminogen activator urokinase (plau),head and neck squamous cell carcinomas (hnscc),the cancer genome atlas (tcga),bioinformatics analysis,gene expression omnibus (geo),survival

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