Identification of breast cancer targets by functional genetic screening of overexpressed genes for tumor-promoting function and tumor cell dependency

Abstract There are several hundreds of genes overexpressed in a typical breast cancer cell, and their overexpression is often assumed to have a pro-cancer function, but what percentage of these overexpressed genes have a role in promoting and maintaining tumorigenicity isn’t known. To address this question, we screened an unbiased set of seventy-five genes overexpressed in breast cancer for their ability to induce malignant transformation and for breast cancer cell expression dependency. Barcoded open-reading frames under the control of a constitutive promoter were tested by pooled screening for their ability to promote tumor formation of premalignant mammary epithelial cells and growth in 2D and 3D culture. We found that growth in 3D cell culture was more strongly correlated with tumorigenic growth than was 2D growth, validating a long-standing hypothesis. Genes with high activity in promoting both 3D growth and in vivo tumor formation included CEACAM5, CXCL8, NKX2-5, PYGO2 and WWTR1/TAZ. To screen for corresponding tumor dependencies on these six genes, we performed shRNA screening of breast cancer cell lines and found uniform dependency on expression of the Hippo pathway transcriptional activator WWTR1, selective dependencies on CEACAM5 expression, but no consistent effects for the other three genes. Since breast cancer dependency upon WWTR1 is well established, we focused our follow-up studies on CEACAM5. We confirmed that CEACAM5 overexpression conferred tumorigenicity to pre-malignant mammary epithelial cells and that reduced expression selectively decreased the clonogenicity of luminal breast cancer cell lines. Protein analysis indicated that CEACAM5 activated Cdk4/6 and mTOR signaling. We also determined that CEACAM5 overexpression strongly promoted cell number increase in 3D spheroid culture by a novel mechanism that increased the number of epithelial cell layers from a single layer to multiple layers. These results outline a strategy for functional genomic identification of cancer targets, starting with a set of genes overexpressed in cancer, then using pooled approaches to identify those that promote tumorigenicity and cancer cell dependency, followed by validation experiments and exploration of oncogenic mechanisms. We propose that larger screens would substantially increase the number of potential targets for treating breast cancer.