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      Identification of Modulated MicroRNAs Associated with Breast Cancer, Diet, and Physical Activity

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          Healthy diet and physical activity are able to induce beneficial molecular modifications that have been associated with a lower risk of breast cancer (BC) incidence and a better prognosis for BC patients. Although the beneficial effects of healthy lifestyle have been described, the beneficial epigenetic modifications induced by dietary and exercise intervention in BC patients have not been elucidated yet. On these bases, the aim of the present study was to computationally identify microRNAs (miRNAs) strictly associated with BC progression and with dietary and exercise interventions. Through several computational approaches, a set of miRNAs modulated by diet and exercise and useful as diagnostic and prognostic biomarkers for BC was identified. The results obtained represent the starting point for further validation analyses performed on BC patients undergoing lifestyle interventions to propose the miRNAs here identified as novel biomarkers for BC management.

          Abstract

          Background: Several studies have shown that healthy lifestyles prevent the risk of breast cancer (BC) and are associated with better prognosis. It was hypothesized that lifestyle strategies induce microRNA (miRNA) modulation that, in turn, may lead to important epigenetic modifications. The identification of miRNAs associated with BC, diet, and physical activity may give further insights into the role played by lifestyle interventions and their efficacy for BC patients. To predict which miRNAs may be modulated by diet and physical activity in BC patients, the analyses of different miRNA expression datasets were performed. Methods: The GEO DataSets database was used to select miRNA expression datasets related to BC patients, dietary interventions, and physical exercise. Further bioinformatic approaches were used to establish the value of selected miRNAs in BC development and prognosis. Results: The analysis of datasets allowed the selection of modulated miRNAs associated with BC development, diet, and physical exercise. Seven miRNAs were also associated with the overall survival of BC patients. Conclusions: The identified miRNAs may play a role in the development of BC and may have a prognostic value in patients treated with integrative interventions including diet and physical activity. Validation of such modulated miRNAs on BC patients undergoing lifestyle strategies will be mandatory.

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

            Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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              GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses

              Abstract Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.
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                Author and article information

                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                08 September 2020
                September 2020
                : 12
                : 9
                : 2555
                Affiliations
                [1 ]IRCCS Istituto Nazionale Tumori “Fondazione G. Pascale”, Epidemiology Unit, 80131 Naples, Italy; m.grimaldi@ 123456istitutotumori.na.it (M.G.); e.celentano@ 123456istitutotumori.na.it (E.C.); livia.augustin@ 123456utoronto.ca (L.S.A.A.)
                [2 ]Department of Biomedical and Biotechnological Sciences, University of Catania, 95123 Catania, Italy
                [3 ]Research Centre for Prevention, Diagnosis, and Treatment of Cancer, University of Catania, 95123 Catania, Italy
                Author notes
                [* ]Correspondence: luca.falzone@ 123456unict.it (L.F.); mlibra@ 123456unict.it (M.L.); Tel.: +39-095-478-1278 (L.F.); +39-095-478-1271 (M.L.)
                Author information
                https://orcid.org/0000-0001-7349-6826
                https://orcid.org/0000-0002-7232-7737
                Article
                cancers-12-02555
                10.3390/cancers12092555
                7564431
                32911851
                e67a4ee0-f443-4996-90b6-22eea1d62f07
                © 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
                : 20 July 2020
                : 07 September 2020
                Categories
                Article

                microrna,breast cancer,biomarkers,bioinformatics,prognosis,epigenetic,diet,physical activity

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