Big Data-Led Cancer Research, Application, and Insights

被引：6

作者：

Brown, James A. L. ^{[1
]}

Chonghaile, Triona Ni ^{[2
]}

Matchett, Kyle B. ^{[3
]}

Lynam-Lennon, Niamh ^{[4
]}

Kiely, Patrick A. ^{[5
]}

机构：

[1] Natl Univ Ireland Galway, Lambe Inst Translat Res, Sch Med, Discipline Surg, Galway, Ireland

[2] Royal Coll Surgeons Ireland, Physiol & Med Phys Dept, Dublin, Ireland

[3] Queens Univ Belfast, Ctr Canc Res & Cell Biol, Belfast, Antrim, North Ireland

[4] Trinity Coll Dublin, Trinity Translat Med Inst, Dept Surg, Dublin, Ireland

[5] Univ Limerick, Grad Entry Med Sch, Limerick, Ireland

来源：

CANCER RESEARCH | 2016年 / 76卷 / 21期

关键词：

MICROBIOME; INTERFACE; DISCOVERY; TUMORS; OMICS; CELLS;

D O I：

10.1158/0008-5472.CAN-16-0860

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

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.

引用

页码：6167 / 6170

页数：4

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