Abstract 1115: Functionally prioritizing somatic driver aberrations in cancer.
Authors: Dogruluk Turgut , Tsang Yiu-Huen , Wu Ping , Nair Nikitha , Gifford Armel , Bonnen Penelope , Zhang Jianhua , Scott Kenneth L. 
Published: August 2014

The Cancer Genome Atlas and similar efforts are cataloging genomic aberrations across major tumor lineages. These projects are revealing an extraordinary level of genome complexity made up of not only key “driver” events critical to pathogenesis, but also numerous biologically-neutral “passengers” inherent to unstable tumor genomes. The challenge now is to identify functional driver aberrations, as targeting such events or their activated pathways has great potential for improving patient outcomes. Efficient driver identification requires robust pipelines to prioritize the thousands of putative targets emerging from genomics studies. However, little progress has been made toward developing gain-of-function systems for validating overexpressed or activated oncogenes. We have assembled a platform of ∼32,000 sequence-verified open reading frames (ORFs, hereafter termed “genes”). We have integrated these reagents into infrastructure enabling high-content genetic screens. This work is made possible through technological advances made in our laboratory that include 1) robotics driven, high-throughput modeling of somatic mutations (missense, indels, etc) in a manner that permits construction of every aberration found within a given candidate gene and 2) a molecular barcoding approach that facilitates detection of driver events following in vitro and in vivo pooled functional screens. This scalable "HiTMMoB" (High-Throughput Mutagenesis and Molecular Barcoding) platform allows rapid construction of expression-ready wild-type and mutant gene clones. These reagents are being used in our functional genomics pipelines to 1) identify novel cancer driver genes, 2) to examine functionality of rare “tail mutations” in known cancer genes and 3) to asses these genes for their ability to modulate cell response to available therapeutics. An important feature of our system is that target cells, once infected with a gene library, can be entered into parallel screens to maximize discovery (e.g., screens for driver addiction, cell invasion, anchorage-independent growth, drug resistance). While cell-based screening systems are tractable, in vitro models do not fully recapitulate all hallmarks of cancer. To address this challenge, we have developed in vivo screening models that leverage barcode sequencing technology to identify drivers positively selected within tumors and metastases. We are using these platforms to identify drivers of pancreas, lung and breast cancer among others through our participation in multiple projects that include one within the NIH Cancer Target Discovery and Development Network, a consortium whose goal is to leverage these and other tools to identify new cancer targets across a variety of cancer types. Our "prioritization pipeline" will provide the cancer research community information on the most promising somatic aberrations for downstream biomarker and drug development.

Citation Format: Turgut Dogruluk, Yiu-Huen Tsang, Ping Wu, Nikitha Nair, Armel Gifford, Penelope Bonnen, Jianhua Zhang, Kenneth L. Scott. Functionally prioritizing somatic driver aberrations in cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1115. doi:10.1158/1538-7445.AM2013-1115