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      Impact of LMP7 (rs2071543) gene polymorphism in increasing cancer risk: evidence from a meta-analysis and trial sequential analysis

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          Abstract

          Genetic variant LMP7 (low molecular weight polypeptide 7) –145 C > A may influence the function of immune surveillance of an individual and lead to cancer development. Various studies have investigated the relevance of LMP7 –145 C > A gene polymorphism with cancer risk; but, their results are conflicting and inconsistent. To obtain a comprehensive conclusion, a meta-analysis was performed by including eight eligible published studies retrieved from PubMed (Medline), EMBASE and Google Scholar web search until December 2016. Individuals with AA genotype (AA vs CC: p = 0.001; OR = 2.602, 95% CI = 1.780 to 3.803) of LMP7 -145 C > A were found to have 2 folds higher risk of cancer than those with CC genotype. The recessive genetic model (AA vs AC + CC) also indicated that individuals with AA genotype have 2 folds higher cancer risk than AC and CC genotypes ( p = 0.001; OR = 2.216, 95% CI = 1.525 to 3.221). Also, significant increased cancer risk was observed in Asians but not in Caucasians. No publication bias was observed during the analysis. Trial sequential analysis also strengthened our current findings. These results suggest that genetic variant LMP7–145 C > A has significant role in increasing cancer risk in overall and Asian population, and could be useful as a prognostic marker for early cancer predisposition.

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          Most cited references 31

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          Exome sequencing identifies GRIN2A as frequently mutated in melanoma.

          The incidence of melanoma is increasing more than any other cancer, and knowledge of its genetic alterations is limited. To systematically analyze such alterations, we performed whole-exome sequencing of 14 matched normal and metastatic tumor DNAs. Using stringent criteria, we identified 68 genes that appeared to be somatically mutated at elevated frequency, many of which are not known to be genetically altered in tumors. Most importantly, we discovered that TRRAP harbored a recurrent mutation that clustered in one position (p. Ser722Phe) in 6 out of 167 affected individuals (∼4%), as well as a previously unidentified gene, GRIN2A, which was mutated in 33% of melanoma samples. The nature, pattern and functional evaluation of the TRRAP recurrent mutation suggest that TRRAP functions as an oncogene. Our study provides, to our knowledge, the most comprehensive map of genetic alterations in melanoma to date and suggests that the glutamate signaling pathway is involved in this disease.
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            The Impact of Study Size on Meta-analyses: Examination of Underpowered Studies in Cochrane Reviews

            Background Most meta-analyses include data from one or more small studies that, individually, do not have power to detect an intervention effect. The relative influence of adequately powered and underpowered studies in published meta-analyses has not previously been explored. We examine the distribution of power available in studies within meta-analyses published in Cochrane reviews, and investigate the impact of underpowered studies on meta-analysis results. Methods and Findings For 14,886 meta-analyses of binary outcomes from 1,991 Cochrane reviews, we calculated power per study within each meta-analysis. We defined adequate power as ≥50% power to detect a 30% relative risk reduction. In a subset of 1,107 meta-analyses including 5 or more studies with at least two adequately powered and at least one underpowered, results were compared with and without underpowered studies. In 10,492 (70%) of 14,886 meta-analyses, all included studies were underpowered; only 2,588 (17%) included at least two adequately powered studies. 34% of the meta-analyses themselves were adequately powered. The median of summary relative risks was 0.75 across all meta-analyses (inter-quartile range 0.55 to 0.89). In the subset examined, odds ratios in underpowered studies were 15% lower (95% CI 11% to 18%, P<0.0001) than in adequately powered studies, in meta-analyses of controlled pharmacological trials; and 12% lower (95% CI 7% to 17%, P<0.0001) in meta-analyses of controlled non-pharmacological trials. The standard error of the intervention effect increased by a median of 11% (inter-quartile range −1% to 35%) when underpowered studies were omitted; and between-study heterogeneity tended to decrease. Conclusions When at least two adequately powered studies are available in meta-analyses reported by Cochrane reviews, underpowered studies often contribute little information, and could be left out if a rapid review of the evidence is required. However, underpowered studies made up the entirety of the evidence in most Cochrane reviews.
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              Association studies for finding cancer-susceptibility genetic variants.

              Cancer is the result of complex interactions between inherited and environmental factors. Known genes account for a small proportion of the heritability of cancer, and it is likely that many genes with modest effects are yet to be found. Genetic-association studies have been widely used in the search for such genes, but success has been limited so far. Increased knowledge of the function of genes and the architecture of human genetic variation combined with new genotyping technologies herald a new era of gene mapping by association.
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                Author and article information

                Journal
                Oncotarget
                Oncotarget
                Oncotarget
                ImpactJ
                Oncotarget
                Impact Journals LLC
                1949-2553
                19 January 2018
                21 December 2017
                : 9
                : 5
                : 6572-6585
                Affiliations
                1 Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan 45142, Saudi Arabia
                2 The University College of Medical Sciences and GTB Hospital University of Delhi, Delhi 110095, India
                3 Department of Biosciences, Faculty of Natural Sciences, Jamia Millia Islamia A Central University, New Delhi 110025, India
                4 Centre for Life Sciences, Central University of Jharkhand, Ranchi, Jharkhand 835205, India
                5 Department of Biotechnology, Institute of Engineering and Technology, Lucknow, Uttar Pradesh 226021, India
                6 Department of Laboratory Medicine, Faculty of Applied Medical Sciences, Albaha University, Albaha 65431, Saudi Arabia
                Author notes
                Correspondence to: Shafiul Haque, shafiul.haque@ 123456hotmail.com
                [*]

                These authors contributed equally to this work

                Article
                23547
                10.18632/oncotarget.23547
                5814233
                29464093
                5c996cf4-54f0-4478-9956-ff55125e92ab
                Copyright: © 2018 Mandal et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Categories
                Meta-Analysis

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