Abstract
Cancer is a disease of the genome. Using genomic approaches alone, it is difficult to ascertain which variants drive pathogenesis because most of these are functionally irrelevant passenger mutations. Highly recurrent events point to drivers; however, the majority of genomic alterations in tumors occur at low frequency. In addition, the products of many oncogenes and tumor suppressor genes are not druggable. However, such abnormalities can cause unanticipated gene/pathway dependencies (synthetic lethality), providing alternate avenues for drug development. Lentiviral-based shRNA libraries enables genome-wide screening of cultured cancer cells in a pooled format, facilitating the identification of genes necessary for cancer cell proliferation and survival in cultured cells. We screened a panel of > 75 breast cancer cell lines using an 80,000 lentiviral shRNA library targeting 16,000 genes and integrated these screen results with gene expression, copy-number variation (CNV), and somatic mutations derived from the same lines. We identified several classes of gene dropouts, which are required for survival or growth of all (or some) cell lines, irrespective of subtype and several subtype-specific genes, whose essentiality is restricted to a defined subtype. These include well-known HER2 subtype-specific genes, ERBB2, ERBB3, and TFAP2C and luminal subtype-specific gene FOXA1, SPDEF, GATA3, and ESR1. In addition, the unprecedented number of lines allows the identification of synthetic lethal interaction with common breast cancer somatic mutations or CNV such as PIK3CA and PTEN or 9p21 deletion, respectively, which encodes the CDKN2A, CDKN2B, and MTAP genes. Finally, integration of gene expression, copy number variation, and functional screening results identified potential biomarkers with common genetic changes and functional drivers. Overall, our study represents an extensive functional genetic survey of breast cancer, reveals complexities between genomic and functional genomic results, and uncovers several unexpected gene dependencies and potential novel therapeutic target for each subtype.
This abstract is also presented as Poster A033.
Citation Format: Richard Marcotte, Azin Sayad, Cathy Iorio, Maliha Haider, Jason Moffat, Benjamin G. Neel. Integrative functional genomics of breast cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research: Genetics, Biology, and Clinical Applications; Oct 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2013;11(10 Suppl):Abstract nr PR07.
RSS Feeds