The generation of multidimensional datasets characterizing genetic, epigenetic, and functional properties of large normal and tumor-related samples is creating unique opportunities for the systems-level dissection of mechanisms associated with malignant phenotypes. Integrated data sets may lead to more efficient and specific approaches for the elucidation of therapeutic targets and biomarkers and for the identification of specific small molecule inhibitors. However, the power of these computational methods to study human cancer from an unbiased global perspective is severely compromised by the low through-put approaches necessary to functionally validate the in silico predictions. During the last years, RNA interference (RNAi) emerged as a very powerful genetic strategy to functionally interrogate the entire genome by loss-of-function studies. This cellular process can be experimentally controlled to knock down the expression of any specific gene. Our group has pioneered the development of RNAi-based genetic tools to translate RNAi studies to mammalian systems generating a shRNA-mir pooled lentiviral library that allows performing functional studies at genome-wide level. ErbB2 is a receptor tyrosine kinase found overexpressed in 20-40% of breast tumors correlating with a malignant phenotype and worse prognosis. Different targeted therapies have been developed to specifically inhibit its activity such the monoclonal antibody Herceptin, or the small tyrosine kinase inhibitor Lapatinib. Despite of the success of these inhibitors in the treatment of tumors that overexpress ErbB2, about 30% of them become resistant making necessary to look for alternative targets in these cases. The combination of the state-of-the-art computational analysis and RNAi-based technology toward system biology studies must represent a powerful tool to dissect the regulatory networks that govern the homeostasis of breast tumors. Applying this combined approach to an overexpressing ErbB2 breast cancer model we have identified the genes that are critical in those cells.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5137. doi:1538-7445.AM2012-5137

©2012 American Association for Cancer Research
2012