Transforming Big Data into cancer-relevant insight: An initial, multi-tier approach to assess reproducibility and relevance*

Image by the University of Michigan School of Natural Resources and Environment; used under a Creative Commons license.  

Image by the University of Michigan School of Natural Resources and Environment; used under a Creative Commons license.  

Gerhard DS, Clemons PA, Shamji AF, Hon C, Wagner BK, Schreiber SL, Krasnitz A, Sordella R, Sander C, Lowe SW, Powers S, Smith K, Aburi M, Iavarone A, Lasorella A, Silva J, Stockwell BR, Califano A, Boehm JS, Vazquez F, Weir BA, Hahn WC, Khuri FR, Moreno CS, Johns M, Fu H, Nikolova O, Mendez E, Gadi VK, Margolin AA, Grandori C, Kemp CJ, Warren EH, Riddell SR, McIntosh MW, Gevaert O, Kuo CJ, Ji HP, Dhruv H, Finlay D, Kiefer J, Kim S, Vuori K, Berens ME, Hangauer M, Boettcher M, Weissman JS, Bivona TG, Bandyopadhyay S, McManus MT, McCormick F, Aksoy O, Simonds EF, Zheng T, Chen J, An Z, Balmain A, Weiss WA, Chen K, Liang H, Scott KL, Mills GB, Posner BA, MacMillan J, Minna J, White M, Roth MG, Jagu S, Mazerik J

Molecular Cancer Research

August 01, 2016

The Cancer Target Discovery and Development (CTD^2) Network was established to accelerate the transformation of "Big Data" into novel pharmacological targets, lead compounds, and biomarkers for rapid translation into improved patient outcomes. It rapidly became clear in this collaborative network that a key central issue was to define what constitutes sufficient computational or experimental evidence to support a biologically or clinically relevant finding. This manuscript represents a first attempt to delineate the challenges of supporting and confirming discoveries arising from the systematic analysis of large-scale data resources in a collaborative work environment and to provide a framework that would begin a community discussion to resolve these challenges. The Network implemented a multi-Tier framework designed to substantiate the biological and biomedical relevance as well as the reproducibility of data and insights resulting from its collaborative activities. The same approach can be used by the broad scientific community to drive development of novel therapeutic and biomarker strategies for cancer.

Program:
CTD²
Last updated: November 27, 2017