Abstract 955: High-throughput functional screening for metastasis drivers of lung cancer
Authors: Grzeskowiak Caitlin L. , Minelli Rosalba , Wu Ping , Kundu Samrat , Gibbons Don L. , Scott Kenneth L. 
Published: August 2015

Large-scale profiling efforts by consortia such as The Cancer Genome Atlas (TCGA) are revealing the complexity of cancer genomes, which are comprised of causal “driver” aberrations and many biologically neutral “passengers”. Most cancers acquire one or more well-studied high frequency driver events that promote tumor growth (e.g., mutations/copy number changes in KRAS, TP53, EGFR, MYC). Much less is known about the thousands of low frequency gene aberrations and their contribution to cancer progression, particularly metastasis, which is the primary cause of cancer-related mortality. Comprehensive biological assessment of low frequency metastasis drivers is difficult given their large number and the fact that their activity may be influenced by the specific biological context of a given cancer such as tissue type, microenvironment, and the host immune system. We sought to address these challenges in the context of lung cancer, which presents as metastatic disease in approximately 65% of patients and carries a 5-year survival rate of &lt;15%. To do this, we leveraged our High-Throughput Mutagenesis and Molecular Barcoding (HiTMMoB) technology allowing (1) construction of gene “libraries” by high-throughput, accurate modeling of somatic aberrations (missense, nonsense, indels) or wild-type genes (representing amplifications) using our robotics driven platform of &gt;35,000 sequence verified human gene clones (2) a molecular barcoding strategy that permits simultaneous DNA tagging of gene clones through multi-fragment DNA recombineering for (3) pooled functional screening in vivo to identify metastasis drivers that work alone or in combination. We used these technologies to build gene libraries based on oncogenomics-guided integrations of mutant KRAS-specific gene signatures derived from mouse and human TCGA lung cancer datasets. The resulting barcoded libraries were delivered to non-metastatic lung cancer cells expressing oncogenic KRAS and then implanted into immune competent mice. Animals were sacrificed at maximal tumor burden and resulting primary tumors and metastases subjected to barcode enrichment analysis by next generation sequencing to identify gene aberrations enriched within metastatic lesions. Our screening approach has identified known (MYC and SNAI2) and many novel (e.g., MBIP and CCNE1) potent drivers of lung cancer growth and metastasis currently under mechanistic and pre-clinical evaluation. These efforts are revealing new pathways contributing to lung cancer aggression and our ultimate goal is to translate these findings into the care of metastatic lung cancer patients who have few treatment options. We have also scaled these efforts across other screening platforms, functionalizing thousands of aberrations across diverse cancer types. Together these systems reveal the highest priority targets to enroll in deep mechanistic biology studies and drug discovery and development programs.

Citation Format: Caitlin L. Grzeskowiak, Rosalba Minelli, Ping Wu, Samrat Kundu, Don L. Gibbons, Kenneth L. Scott. High-throughput functional screening for metastasis drivers of lung cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 955. doi:10.1158/1538-7445.AM2015-955