Analysis of Cancer Genomic Amplifications Identifies Druggable Collateral Dependencies within the Amplicon

SIMPLE SUMMARY: Genomic amplifications are highly prevalent in cancer and often contribute to increased proliferation or cell survival upon the administration of anti-cancer drugs. The identification of those amplified genes at which cancer cells are selectively dependent is crucial for the development of new targeted therapies. On this matter, CRISPR/Cas9 screens have emerged as a useful tool to deplete the expression of almost all genes while assessing their consequences for cell survival. Here, we analyzed data from CRISPR/Cas9 screens in 954 cancer cell lines to identify selective gene dependencies associated with common cancer genomic amplifications. Our results suggest that cell lines of different tumor types harboring the same genomic amplification are dependent almost entirely on the same amplified genes, providing a set of new promising targets specific to each genomic amplification. ABSTRACT: The identification of novel therapeutic targets for specific cancer molecular subtypes is crucial for the development of precision oncology. In the last few years, CRISPR/Cas9 screens have accelerated the discovery and validation of new targets associated with different tumor types, mutations, and fusions. However, there are still many cancer vulnerabilities associated with specific molecular features that remain to be explored. Here, we used data from CRISPR/Cas9 screens in 954 cancer cell lines to identify gene dependencies associated with 16 common cancer genomic amplifications. We found that high-copy-number genomic amplifications generate multiple collateral dependencies within the amplified region in most cases. Further, to prioritize candidate targets for each chromosomal region amplified, we integrated gene dependency parameters with both druggability data and subcellular location. Finally, analysis of the relationship between gene expression and gene dependency led to the identification of genes, the expression of which may constitute predictive biomarkers of dependency. In conclusion, our study provides a set of druggable targets specific for each amplification, opening the possibility to specifically target amplified tumors on this basis.