Insights distilled from integratingmultiple big-data or "omic" datasets have revealed functional hierarchies of molecular networks driving tumorigenesis and modifiers of treatment response. Identifying these novel key regulatory and dysregulated elements is now informing personalized medicine. Crucially, although there are many advantages to this approach, there are several key considerations to address. Here, we examine how this big data–led approach is impacting many diverse areas of cancer research, through review of the key presentations given at the Irish Association for Cancer Research Meeting and importantly how the results may be applied to positively affect patient outcomes.
Brown, J. A. L., Ni Chonghaile, T., Matchett, K. B., Lynam-Lennon, N., & Kiely, P. A. (2016). Big data-led cancer research, applications and insights. Cancer Research, 76(21), 6167-6170. https://doi.org/10.1158/0008-5472.CAN-16-0860