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      Prognostic Significance of EBV Latent Membrane Protein 1 Expression in Lymphomas: Evidence from 15 Studies

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          Abstract

          Background

          Epstein-Barr virus (EBV) infection has been associated with lymphoma development. EBV latent membrane protein 1 (LMP1) is essential for EBV-mediated transformation and progression of different human cells, including lymphocytes. This meta-analysis investigated LMP1 expression with prognosis of patients with lymphoma.

          Methods

          The electronic databases of PubMed, Embase, and Chinese Biomedicine Databases were searched. There were 15 published studies available for a random effects model analysis. Quality assessment was performed using the Newcastle-Ottawa Quality Assessment Scale for cohort studies. A funnel plot was used to investigate publication bias, and sources of heterogeneity were identified by meta-regression analysis. The combined hazard ratios (HR) and their corresponding 95% confidence intervals of LMP1 expression were calculated by comparison to the overall survival.

          Results

          Overall, there was no statistical significance found between LMP1 expression and survival of lymphoma patients (HR 1.25 [95% CI, 0.92–1.68]). In subgroup analyses, LMP1 expression was associated with survival in patients with non-Hodgkin lymphoma (NHL) (HR  = 1.84, 95% CI: 1.02–3.34), but not with survival of patients with Hodgkin disease (HD) (HR  =  1.03, 95% CI: 0.74–1.44). In addition, significant heterogeneity was present and the meta-regression revealed that the outcome of analysis was mainly influenced by the cutoff value.

          Conclusions

          This meta-analysis demonstrated that LMP1 expression appears to be an unfavorable prognostic factor for overall survival of NHL patients. The data suggested that EBV infection and LMP1 expression may be an important factor for NHL development or progression.

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          Most cited references46

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          Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints.

          M Parmar, V. Torri, L. Stewart (1998)
          Meta-analyses aim to provide a full and comprehensive summary of related studies which have addressed a similar question. When the studies involve time to event (survival-type) data the most appropriate statistics to use are the log hazard ratio and its variance. However, these are not always explicitly presented for each study. In this paper a number of methods of extracting estimates of these statistics in a variety of situations are presented. Use of these methods should improve the efficiency and reliability of meta-analyses of the published literature with survival-type endpoints.
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            Persistence of the Epstein-Barr virus and the origins of associated lymphomas.

            David A. Thorley-Lawson, Andrew Gross (2004)
            Article 0 comments Cited 258 times – based on 0 reviews     Review now
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              Selecting immunohistochemical cut-off scores for novel biomarkers of progression and survival in colorectal cancer.

              Russell Steele, Luigi Terracciano, Alessandro Lugli … (2007)
              Cut-off scores for determining positivity of biomarkers detected by immunohistochemistry are often set arbitrarily and vary between reports. To evaluate the performance of receiver operating characteristic (ROC) curve analysis in determining clinically important cut-off scores for a novel tumour marker, the receptor for hyaluronic acid mediated motility (RHAMM), and show the reproducibility of the selected cut-off scores in 1197 mismatch-repair (MMR) proficient colorectal cancers (CRC). Immunohistochemistry for RHAMM was performed using a tissue microarray of 1197 MMR-proficient CRC. Immunoreactivity was scored using a semi-quantitative scoring method by evaluating the percentage of positive tumour cells. ROC curve analysis was performed for T stage, N stage, tumour grade, vascular invasion and survival. The score with the shortest distance from the curve to the point with both maximum sensitivity and specificity, i.e. the point (0.0, 1.0), was selected as the cut-off score leading to the greatest number of tumours correctly classified as having or not having the clinical outcome. In order to determine the reliability of the selected cut-off scores, 100 bootstrapped replications were performed to resample the data. The cut-off score for T stage, N stage, tumour grade and vascular invasion was 100% and that for survival 90%. The most frequently selected cut-off score from the 100 resamples was also 100% for T stage, N stage, tumour grade, and vascular invasion and 90% for survival. ROC curve analysis can be used as an alternative method in the selection and validation of cut-off scores for determining the clinically relevant threshold for immunohistochemical tumour positivity.
              Article 0 comments Cited 80 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Joseph S. Pagano: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, USA )
                ISSN (Electronic): 1932-6203
                Publication date Collection: 2013
                Publication date (Electronic): 17 April 2013
                Volume: 8
                Issue: 4
                Electronic Location Identifier: e60313
                Affiliations
                [1 ]Department of Otolaryngology-Head and Neck Surgery, Jiangsu Province Official Hospital, Nanjing, China
                [2 ]Huadong Medical Institute of Biotechnology, Nanjing, China
                [3 ]Department of Otolaryngology-Head and Neck Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
                [4 ]Jiangsu Provincial Blood Center, Nanjing, China
                [5 ]Department of Otolaryngology-Head and Neck Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
                [6 ]Department of Clinical Laboratory, Jiangsu Province Official Hospital, Nanjing, China
                [7 ]Department of Hematology and Oncology, Jiangsu Province Official Hospital, Nanjing, China
                [8 ]The Key Laboratory of Cancer Biomarkers, Prevention & Treatment Cancer Center and The Key Laboratory of Antibody Technique of Ministry of Health, Nanjing Medical University, Nanjing, China
                The University of North Carolina at Chapel Hill, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: JRX RJC JZ. Performed the experiments: YM HL MPL. Analyzed the data: YM MPL ZGL. Contributed reagents/materials/analysis tools: MPL DWZ YL QDL. Wrote the paper: YM. Study supervision: JRX RJC JZ.

                Article
                Publisher ID: PONE-D-12-29651
                DOI: 10.1371/journal.pone.0060313
                PMC ID: 3629080
                PubMed ID: 23613723
                SO-VID: df98fa39-7723-449c-bf98-87e13ba555b9
                Copyright statement: Copyright @ 2013
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 27 September 2012
                Date accepted : 26 February 2013
                Page count
                Pages: 9
                Funding
                The authors have no support or funding to report.
                Categories
                Subject: Research Article
                Subject: Biology
                Subject: Computational Biology
                Subject: Molecular Genetics
                Subject: Gene Expression
                Subject: Genetics
                Subject: Gene Expression
                Subject: Molecular Cell Biology
                Subject: Gene Expression
                Subject: Medicine
                Subject: Clinical Research Design
                Subject: Meta-Analyses
                Subject: Hematology
                Subject: Hematologic Cancers and Related Disorders
                Subject: Lymphomas
                Subject: Infectious Diseases
                Subject: Viral Diseases
                Subject: Epstein-Barr virus infectious mononucleosis
                Subject: Oncology
                Subject: Cancers and Neoplasms
                Subject: Hematologic Cancers and Related Disorders
                Subject: Lymphomas

                ScienceOpen disciplines: Uncategorized
                Data availability:
                ScienceOpen disciplines: Uncategorized

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