RT Journal Article
SR Electronic
T1 Big Data–Led Cancer Research, Application, and Insights
JF Cancer Research
JO Cancer Res
FD American Association for Cancer Research
SP 6167
OP 6170
DO 10.1158/0008-5472.CAN-16-0860
VO 76
IS 21
A1 Brown, James A.L.
A1 Ni Chonghaile, Triona
A1 Matchett, Kyle B.
A1 Lynam-Lennon, Niamh
A1 Kiely, Patrick A.
YR 2016
UL http://cancerres.aacrjournals.org/content/76/21/6167.abstract
AB Insights distilled from integrating multiple 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. Cancer Res; 76(21); 6167–70. ©2016 AACR.