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      Prognostic value from integrative analysis of transcription factors c-Jun and Fra-1 in oral squamous cell carcinoma: a multicenter cohort study

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          Abstract

          Transcription factors c-Jun and Fra-1 have been reported to play a role during the initiation and progression in oral squamous cell carcinoma (OSCC). However, cohort studies are rarely reported. Here is an integrative analysis of their prognostic value in OSCC through a multicenter cohort study.313 OSCC patients were included in this study and received regular follow-up. The survival rate and hazard ratios( HR) were generated by survival analysis. The concordance probability and receiver operating characteristic curve area were chosen to measure the model discrimination. High expressions of c-Jun or Fra-1 were associated with poor prognosis, meanwhile the high expression of Fra-1 meant worse prognosis of patients than the high expression of c-Jun. Besides, the interaction effect of c-Jun and Fra-1 was antagonism, when the expression of c-Jun and Fra-1 was both high, the HR was lower than the hazard ratio when only the Fra-1 was at high expression. c-Jun and Fra-1 were both proved to be high risky predictors of death in OSCC, the antagonistic effect suggested that these biomarkers’ activities could be influenced by each other. It may provide a new sight for the studies of OSCC prognosis and treatment.

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          Most cited references37

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          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          J A Hanley, B J McNeil, Marnix van Holsbeeck (1982)
          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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            AP-1: a double-edged sword in tumorigenesis.

            Robert Eferl, Erwin F. Wagner (2003)
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              Identifying co-morbidity in surgical patients using administrative data with the Royal College of Surgeons Charlson Score.

              J N Armitage, J van der Meulen (2010)
              Surgical outcomes are influenced by co-morbidity. The Royal College of Surgeons (RCS) Co-morbidity Consensus Group was convened to improve existing instruments that identify co-morbidity in International Classification of Diseases tenth revision administrative data. The RCS Charlson Score was developed using a coding philosophy that enhances international transferability and avoids misclassifying complications as co-morbidity. The score was validated in English Hospital Episode Statistics data for abdominal aortic aneurysm (AAA) repair, aortic valve replacement, total hip replacement and transurethral prostate resection. With exception of AAA, patients with co-morbidity were older and more likely to be admitted as an emergency than those without. All patients with co-morbidity stayed longer in hospital, required more augmented care, and had higher in-hospital and 1-year mortality rates. Multivariable prognostic models incorporating the RCS Charlson Score had better discriminatory power than those that relied only on age, sex, admission method (elective or emergency) and number of emergency admissions in the preceding year. The RCS Charlson Score identifies co-morbidity in surgical patients in England at least as well as existing instruments. Given its explicit coding philosophy, it may be used as a co-morbidity scoring instrument for international comparisons. Copyright 2010 British Journal of Surgery Society Ltd.
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                Author and article information

                Contributors
                Zhi-Yong Wang: zhiyong.wang@scu.edu.cn
                Qian-Ming Chen: qmchen@scu.edu.cn
                Journal
                Journal ID (nlm-ta): Sci Rep
                Journal ID (iso-abbrev): Sci Rep
                Title: Scientific Reports
                Publisher: Nature Publishing Group UK (London )
                ISSN (Electronic): 2045-2322
                Publication date (Electronic): 8 August 2017
                Publication date PMC-release: 8 August 2017
                Publication date Collection: 2017
                Volume: 7
                Electronic Location Identifier: 7522
                Affiliations
                [1 ]ISNI 0000 0001 0807 1581, GRID grid.13291.38, Department of epidemiology and health statistics, West China School of Public Health, , Sichuan University, ; Chengdu, 610041 China
                [2 ]ISNI 0000 0001 0807 1581, GRID grid.13291.38, Department of Oral Biology and Medicine, State Key Laboratory of Oral Diseases, West China School of Stomatology, , Sichuan University, ; Chengdu, 610041 China
                [3 ]ISNI 0000 0001 0807 1581, GRID grid.13291.38, School of Mathematics, , Sichuan University, ; Chengdu, 610041 China
                [4 ]ISNI 0000 0000 8653 0555, GRID grid.203458.8, Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, College of Stomatology, , Chongqing Medical University, ; Chongqing, 400016 China
                Article
                Publisher ID: 5106
                DOI: 10.1038/s41598-017-05106-5
                PMC ID: 5548725
                PubMed ID: 28790303
                SO-VID: d593c57b-3142-414b-956d-a4d47e357411
                Copyright © © The Author(s) 2017
                License:

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 10 March 2017
                Date accepted : 23 May 2017
                Categories
                Subject: Article
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                issue-copyright-statement © The Author(s) 2017

                ScienceOpen disciplines: Uncategorized
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