Abstract 2975: Genome-scale CRISPR screen finds prostate lineage specific dependencies

Abstract

Functional genomics has held great promise for mapping cancer dependencies and identifying new therapeutic targets in cancer cell lines. However, this remains a major challenge for prostate cancer (PCa) due to the lack of cancer cell models and efficient optimization of pooled genetic perturbation screens. The Broad Cancer Cell Line Factory (CCLF) is attempting to fulfill this unmet need by generating novel prostate cancer cell models and uncovering prostate specific lineage dependencies. Encouragingly, Dr. Yu Chen at Memorial Sloan Kettering Cancer Center has developed several 3D cancer organoids from advanced prostate cancer. Although the success rate needs improvement for primary PCa, over 12 long-term models have been established by this group. In collaboration with Chen Lab, we aim to expand the prostate cell model collection by using PCa organoids and patient-derived normal cells. We can then apply these models for genetic perturbation profiling to unravel prostate lineage specific dependencies. Many historical cancer cell lines and cancer organoids were not compatible with genome-scale CRISPR screening due to the slow cellular growth. Here we first optimized the media conditions in these PCa organoids by using empirical media screening assay conditions through our HYBRID technology. The HYBRID technology allows for the systemic evaluation of 64 media conditions at once, so that we can perform RNAseq analysis to identify the conditions most physiologically resembling the PCa environment with the maximum doubling time. We have further developed our high throughput screening strategies for organoid culture using an optimized protocol to study 3D growth patterns in a 96-well format using the Incucyte S3 System. Next, to map out all possible dependencies, we are testing the feasibility of a pooled genome scale CRISPR screen. In our preliminary assay development results, we demonstrated the reproducible viral infectibility in several organoids ranging from 40-70% infection rate. We anticipate that these genome-wide CRISPR data in PCa organoid and normal prostate cell models can be integrated and analyzed with 4 previous PCa cell lines screened in the Broad Dependency Map to point out more prostate lineage specific genetic vulnerabilities and possible therapeutic targets. Citation Format: Adel Attari, Sean Misek, Pinar Eser, Alexa Yeagley, Yu Chen, Jesse Boehm, Yuen-Yi (Moony) Tseng. Genome-scale CRISPR screen finds prostate lineage specific dependencies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2975.