Abstract PR06: Modeling the tumor microenvironment to identify novel loss of function mutations in breast cancer progression

Abstract Recent next generation sequencing studies have comprehensively mapped the genetic landscape of breast cancer and revealed that only a small number of genes are recurrently mutated in more than 10% of unselected tumors (i.e. TP53, PIK3CA and GATA3), and that the vast majority of recurrent mutations occur at low frequencies. Although some have been shown to be drivers (i.e. confer a selective advantage), such as oncogenic ERBB2 mutations, there is a myriad of significantly altered lower frequency mutations whose functional impact is unknown. We utilized a functional genomics approach silencing the 200 most frequently mutated genes in breast cancer in 3D spheroid cultures that more accurately recapitulate in vivo like conditions, using the MCF10A progression series cell line panel to identify novel loss of function mutations that affect breast cancer progression from non-malignant to highly invasive disease. Genes whose silencing significantly altered spheroid growth were integrated with comprehensive copy number and mutation data in order to analyze the impact of these genes in concert with additional driver alterations in genes such as TP53 and PIK3CA mutations. We identified 11 genes whose silencing with siRNA had a significant effect on growth in two or more cell lines in 3D, including FMN2, FOXA1, NIPBL and CREBBP. Silencing of FMN2 increased spheroid growth in the invasive cell lines only, suggesting loss of function mutations are a later event in breast cancer progression. A second targeted validation screen showed that silencing of a cohort of these genes had limited effect under traditional 2D culture conditions, for example, silencing of maltase-glucoamylase (MGAM) resulted in increased growth in AT1 and DCIS.com cells in 3D while having no effect in 2D; an effect that was recapitulated by treating cells with an established MGAM inhibitor. Furthermore, loss of NIPBL significantly increased spheroid growth in cells harboring TP53 nuclear accumulation, and was significantly co-mutated in TP53 mutant primary tumors, suggestive of epistasis. Integrating genes that when silenced decreased spheroid growth with mutation status in the cell lines identified 3D specific oncogenic dependencies with PIK3CA and novel SZT2 mutations. Using a functional genomic approach in 3D models we have identified recurrently mutated genes whose loss or gain of function contribute to breast cancer progression and furthermore may be epistatic or cooperate with established driver mutations in breast cancer. Citation Format: Barrie Peck, Sarah Maguire, Eamonn Morrison, Patty Wai, Rachael Natrajan. Modeling the tumor microenvironment to identify novel loss of function mutations in breast cancer progression. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr PR06.

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