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

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 f...

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Detalles Bibliográficos
Autores: Pons, Guillem|||0000-0001-8128-740X, Gallo-Oller, Gabriel|||0000-0002-3864-1941, Navarro Barea, Natalia|||0000-0002-2160-6656, Zarzosa, Patricia|||0000-0002-9711-8384, Sansa-Girona, Júlia|||0000-0003-3285-7845, García-Gilabert, Lia|||0000-0003-2079-7232, Magdaleno, Ainara|||0000-0002-2718-3244, Segura, Miguel F.|||0000-0003-0916-3618, Sánchez de Toledo Codina, José|||0000-0002-1034-1920, Gallego, Soledad|||0000-0002-4712-9624, Moreno Martin Retortillo, Lucas|||0000-0002-0708-1670, Roma, Josep|||0000-0001-7692-6123
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:281414
Acceso en línea:https://ddd.uab.cat/record/281414
https://dx.doi.org/urn:doi:10.3390/cancers15061636
Access Level:acceso abierto
Palabra clave:Cancer
CRISPR-Cas9 screenings
Drug development
Gene dependencies
Gene amplifications
Descripción
Sumario: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.