Abstract The number of patients benefiting from precision cancer medicine (PCM) is very limited. The Cancer Dependency Map Initiative aims to dramatically accelerate PCM by systematically identifying the landscape of cancer vulnerabilities across all tumors. Genome-wide knockout screens have been performed in over 1000 cancer cell lines, but these have been sourced from historically derived models, leaving many cancers underrepresented. Advances have been made in model derivation by growing cells in 3D formats, such as organoids or spheroids. These models present an opportunity to screen new cancer types, but come with challenges that require a new pipeline. Here, we present a set of screens using a genome wide CAS12 library in organoid tumor models representing novel subtypes of pancreatic, esophageal, and gastric cancer, along with treatment-resistant breast, ovarian, and prostate cancer organoids. We show that genome-wide screening of these models is feasible and can be achieved with quality comparable to 2D cell lines. Our work uncovered a set of novel dependencies associated with cell-ECM interactions that have not previously been identified in 2D models. Our methods provide a framework for screening future patient derived 3D culture models and discovering vulnerabilities in new tumor types. Citation Format: James V. Neiswender, Lisa Brenan, Tate Bertea, Jimmy Guo, Ashley Anderson, Megan Wong, Zoe Posner, Kevin Kapner, Connor Hennessey, Sarah Wie, Isabella Boyle, Barbara De Kegel, Joshua Dempster, Yuen-Yi (Moony) Tseng, David Root, Andrew Aguirre, Francisca Vazquez. Charting new cancer dependencies with patient derived organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6088.