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      Pre-Operative Evaluation of DNA Methylation Profile in Oral Squamous Cell Carcinoma Can Predict Tumor Aggressive Potential

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          Abstract

          Background: Prognosis of oral squamous cell carcinoma (OSCC) is difficult to exactly assess on pre-operative biopsies. Since OSCC DNA methylation profile has proved to be a useful pre-operative diagnostic tool, the aim of the present study was to evaluate the prognostic impact of DNA methylation profile to discriminate OSCC with high and low aggressive potential. Methods: 36 OSCC cases underwent neoplastic cells collection by gentle brushing of the lesion, before performing a pre-operative biopsy. The CpG islands methylation status of 13 gene ( ZAP70, ITGA4, KIF1A, PARP15, EPHX3, NTM, LRRTM1, FLI1, MiR193, LINC00599, MiR296, TERT, GP1BB) was studied by bisulfite Next Generation Sequencing (NGS). A Cox proportional hazards model via likelihood-based component-wise boosting was used to evaluate the prognostic power of the CpG sites. Results: The boosting estimation identified five CpGs with prognostic significance: EPHX3-24, EPHX3-26, ITGA4-3, ITGA4-4, and MiR193-3. The combination of significant CpGs provided promising results for adverse events prediction (Brier score = 0.080, C-index = 0.802 and AUC = 0.850). ITGA4 had a strong prognostic power in patients with early OSCC. Conclusions: These data confirm that the study of methylation profile provides new insights into the molecular mechanisms of OSCC and can allow a better OSCC prognostic stratification even before surgery.

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          The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update

          Abstract Galaxy (homepage: https://galaxyproject.org, main public server: https://usegalaxy.org) is a web-based scientific analysis platform used by tens of thousands of scientists across the world to analyze large biomedical datasets such as those found in genomics, proteomics, metabolomics and imaging. Started in 2005, Galaxy continues to focus on three key challenges of data-driven biomedical science: making analyses accessible to all researchers, ensuring analyses are completely reproducible, and making it simple to communicate analyses so that they can be reused and extended. During the last two years, the Galaxy team and the open-source community around Galaxy have made substantial improvements to Galaxy's core framework, user interface, tools, and training materials. Framework and user interface improvements now enable Galaxy to be used for analyzing tens of thousands of datasets, and >5500 tools are now available from the Galaxy ToolShed. The Galaxy community has led an effort to create numerous high-quality tutorials focused on common types of genomic analyses. The Galaxy developer and user communities continue to grow and be integral to Galaxy's development. The number of Galaxy public servers, developers contributing to the Galaxy framework and its tools, and users of the main Galaxy server have all increased substantially.
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            Assessing the performance of prediction models: a framework for traditional and novel measures.

            The performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the receiver operating characteristic [ROC] curve), and goodness-of-fit statistics for calibration.Several new measures have recently been proposed that can be seen as refinements of discrimination measures, including variants of the c statistic for survival, reclassification tables, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Moreover, decision-analytic measures have been proposed, including decision curves to plot the net benefit achieved by making decisions based on model predictions.We aimed to define the role of these relatively novel approaches in the evaluation of the performance of prediction models. For illustration, we present a case study of predicting the presence of residual tumor versus benign tissue in patients with testicular cancer (n = 544 for model development, n = 273 for external validation).We suggest that reporting discrimination and calibration will always be important for a prediction model. Decision-analytic measures should be reported if the predictive model is to be used for clinical decisions. Other measures of performance may be warranted in specific applications, such as reclassification metrics to gain insight into the value of adding a novel predictor to an established model.
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              DNA methylation patterns and epigenetic memory.

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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                14 September 2020
                September 2020
                : 21
                : 18
                : 6691
                Affiliations
                [1 ]Section of Oral Science, Department of Biomedical and Neuromotor Sciences, University of Bologna, 40159 Bologna, Italy; davide.gissi@ 123456unibo.it (D.B.G.); andrea.gabusi3@ 123456unibo.it (A.G.); lucio.montebugnoli@ 123456unibo.it (L.M.)
                [2 ]Section of Anatomic Pathology at Bellaria Hospital, Department of Biomedical and Neuromotor Sciences, University of Bologna, 40139 Bologna, Italy; viscardopaolo.fabbr2@ 123456unibo.it (V.P.F.); sofia.melotti@ 123456studio.unibo.it (S.M.); sofia.asioli3@ 123456unibo.it (S.A.)
                [3 ]Section of Hygiene, Public Health and Medical Statistics, Department of Biomedical and Neuromotor Sciences, University of Bologna, 40126 Bologna, Italy; jacopo.lenzi2@ 123456unibo.it
                [4 ]Functional MR Unit, Bellaria Hospital, Department of Biomedical and Neuromotor Sciences, University of Bologna, 40139 Bologna, Italy
                [5 ]Unit of Oral and Maxillofacial Surgery, Azienda Ospedaliero-Universitaria di Bologna, Department of Biomedical and Neuromotor Sciences, University of Bologna, 40138 Bologna, Italy; achille.tarsitano2@ 123456unibo.it (A.T.); claudio.marchetti@ 123456unibo.it (C.M.)
                [6 ]Unit of Anatomic Pathology, S. Orsola Hospital, 40138 Bologna, Italy; tiziana.balbi@ 123456aosp.bo.it
                Author notes
                [* ]Correspondence: luca.morandi2@ 123456unibo.it
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-0195-7694
                https://orcid.org/0000-0002-7247-8615
                https://orcid.org/0000-0003-2882-4223
                https://orcid.org/0000-0002-3810-9760
                https://orcid.org/0000-0002-5815-7591
                https://orcid.org/0000-0002-4178-4257
                Article
                ijms-21-06691
                10.3390/ijms21186691
                7555204
                32937734
                bcee3ac2-6d2c-4361-93bc-cd4d64d57bdb
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 29 July 2020
                : 08 September 2020
                Categories
                Article

                Molecular biology
                dna methylation,bisulfite-seq,oral squamous cell carcinoma,pre-operative prognostic test,oral cancer,oral oncology

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