Abstract S4-01: An integrated genomics approach identifies novel drivers of oncogenic pathway activity in human breast cancer
Authors: Gatza ML , Silva G , Hoadley KA , Fan C , Perou CM 
Published: August 2014

Background:

Breast cancer is not a single disease, but rather is a collection of unique diseases with distinct molecular mechanisms and clinical characteristics. Although substantial progress has been made in the development and directed administration of new cancer therapies, the reality is that most patients with advanced tumors will succumb to their disease. Since recent studies have suggested that the activity of altered oncogenic pathways may be an important determinant of the biology of the tumor and potential response to therapy, identifying mechanisms driving key oncogenic pathways is paramount to understanding the transformation process and ultimately enabling the development of therapeutic regimens that can match the complexity of a given patient's tumor.

Methods:

A series of gene expression signatures (n = 52) that measure oncogenic pathway activity in human breast tumors were utilized as a conceptual framework to integrate genome-wide level expression and DNA copy number data in order to identify genetic drivers of oncogenic pathway activity.

Results:

A panel of pathway-based gene expression signatures was applied to a collection of nearly 500 breast tumor samples from the TCGA project. In addition to expression data, each tumor had matched DNA copy number data that were used to identify chromosomal alterations associated with each pathway signature. This strategy was validated by identifying associations between pathway activity and copy number alterations (CNA) of core pathway components including the correlation between ERBB2, cMYC, and E2F1 amplification and the Her2, Myc, and E2F1 signatures, respectively. These results were further confirmed by analyzing Reverse Phase Protein Array (RPPA) data to identify functional activation of the pathway as illustrated by changes in protein expression including increased phosphorylated (p) AKT, Myc and pEGFR relative to the PI3K, Myc, and EGFR signatures, respectively. Finally, to identify those amplified genes that are essential for cell viability in a pathway-dependent manner, we analyzed a dataset of breast cancer cell lines with available mRNA expression and genome-wide shRNA proliferation data. By integrating DNA copy number and shRNA analyses, we identified SOX4 as a novel regulator of PI3K signaling in basal-like breast cancers. We determined that SOX4 is amplified in approximately 40% of basal-like breast tumors with high PI3K signaling, which is comparable to the frequency of PIK3CA or PTEN alterations. By analyzing RPPA data, we demonstrate that tumors with SOX4 amplification have increased expression of core PI3K protein components including pAKT, thus further confirming the association between SOX4 amplification and aberrant PI3K/AKT signaling.

Conclusions:

In this study, we used a panel of pathway-based gene expression signatures as a means to integrate four disparate forms of genomic data to identify drivers of oncogenic pathway activity, including SOX4 amplification as a novel modulator of PI3K signaling in basal-like breast cancers. This novel strategy is able to identify oncogenic events in a context specific manner, which is essential for understanding mechanisms driving tumorigenesis and for the development of personalized therapeutic strategies.

Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr S4-01.