Translational Medicine Reports <p><strong>Translational Medicine Reports</strong> is a peer-reviewed international journal publishing articles in the field of molecular biology, biochemistry and nanotechnology applied to the treatment of chronic-degenerative diseases including diabetes, cancer, neurological, cardiovascular and metabolic disorders. Aim of the Journal is to contribute to bridging the gap between basic research and clinical applications from an interdisciplinary perspective. <strong>Translational Medicine Reports</strong> addresses researchers and managers in academia, biotechnology and pharmaceutical industry researchers, physician scientists, <em>etc.</em> Original Articles with interdisciplinary topics, Reviews, Editorials, From Bench-to-Bedside Articles, Conference Proceedings, and Letters to the Editor are welcome. Every article published in the Journal will be peer-reviewed by experts in the field and selected by members of the Editorial Board.&nbsp;</p> <p><strong>The journal is completely free: no charge for publication, as it is supported by private funds.</strong></p> PAGEPress Scientific Publications, Pavia, Italy en-US Translational Medicine Reports 2532-1250 <p><strong>PAGEPress</strong> has chosen to apply the&nbsp;<a href="" target="_blank" rel="noopener"><strong>Creative Commons Attribution NonCommercial 4.0 International License</strong></a>&nbsp;(CC BY-NC 4.0) to all manuscripts to be published.<br><br> An Open Access Publication is one that meets the following two conditions:</p> <ol> <li>the author(s) and copyright holder(s) grant(s) to all users a free, irrevocable, worldwide, perpetual right of access to, and a license to copy, use, distribute, transmit and display the work publicly and to make and distribute derivative works, in any digital medium for any responsible purpose, subject to proper attribution of authorship, as well as the right to make small numbers of printed copies for their personal use.</li> <li>a complete version of the work and all supplemental materials, including a copy of the permission as stated above, in a suitable standard electronic format is deposited immediately upon initial publication in at least one online repository that is supported by an academic institution, scholarly society, government agency, or other well-established organization that seeks to enable open access, unrestricted distribution, interoperability, and long-term archiving.</li> </ol> <p>Authors who publish with this journal agree to the following terms:</p> <ol> <li>Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.</li> <li>Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.</li> <li>Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.</li> </ol> Application of omic technologies in cancer research Understanding the biology of health and diseases such as cancer, generating insight into the triggers and potentiators of disease and the development of therapeutic approaches to counter and treat disease requires detailed interrogation of inherited genes, and the dynamic positioning of the transcriptome and proteome. In the last 10 years, significant technological developments and increases in sample throughput capabilities have led to a dramatic increase in the size and complexity of the datasets that can be generated. A key challenge now is to develop robust approaches for analysing and interpreting these, and converting data into biologically- and clinically-relevant information. Herein, we provide an overview of approaches for acquiring, integrating and interpreting complex datasets generated using multiple omic platforms, with a focus on the field of cancer research, and highlight key successful data handling and integration applications. Sarah Wagner Graham R. Ball A. Graham Pockley Amanda K. Miles ##submission.copyrightStatement## 2018-05-15 2018-05-15 2 2 10.4081/tmr.7176 Relationship between type 2 diabetes and pancreatic cancer Diabetes mellitus and cancer are conditions that constitute a serious problem for the health of the world’s population, and their co-existence in the same person is becoming increasingly common. Glucose metabolism and the presence of insulin in inflammatory situations appear to be the main factors driving this association, where hyperinsulinemia has been shown to contribute to an increase in risk of association between type 2 diabetes and cancer. Therefore, administering lower levels of exogenously administered insulin to patients with type 1 diabetes would decrease their risk of developing cancer when compared to patients with type 2 diabetes. The results from animal experiments seem promising in terms of pharmacological treatment. M. Temel Yilmaz Ali Osman Gürol ##submission.copyrightStatement## 2018-11-19 2018-11-19 2 2 10.4081/tmr.7002