Abstract C048: Inducible activation of sgRNA libraries in tumor xenografts empowers large-scale in vivo target discovery screens
Authors: Fenoglio Silvia , Tepper James , Grove Lauren , Uijttewaal Esther CH , Bejnood Alborz , Yu Yi , Wu Hsin-Jung , Devault Annabel , Liu Shangtao , Shen Binzhang , Meier Samuel R , Choi Ashley H , Khendu Tenzing , Stowe Hannah , Zhang Minjie , Haines Brian B , Huang Alan , Andersen Jannik N , Pan Xuewen , Elling Ulrich , Teng Teng 
Published: December 2023

CRISPR-mediated genome editing is a powerful approach to understanding disease biology, including identifying genes essential for cancer cell proliferation, immune evasion and survival. We routinely use the technology to identify novel therapeutic targets for cancer using both in vitro and in vivo tumor models, focusing on targets that are synthetic lethal with tumor suppressor gene loss. Large-scale CRISPR screens are often conducted using in vitro cell culture systems as in vivo ‘drop-out’ screens face several bottlenecks resulting in poor sgRNA library representation and low signal to noise ratio. These inherent limitations of in vivo screens occur because only a small fraction of the injected cells contribute to xenograft tumor formation, and because of the uneven clonal expansion due to heterogenous growth conditions in the tumor microenvironment. Hence, many in vivo screens are underpowered for statistical analysis, resulting in a high rate of ‘false negatives’ or ‘false positives’ unless a large number of animals are used or the size of the sgRNA library is greatly reduced to overcome sampling noise. Here, we validate a novel in vivo screening technology, CRISPR-StAR (Stochastic Activation by Recombination), that overcomes these challenges by (i) activating the sgRNA library in established tumors and (ii) generating internally matched-pair controls for each sgRNA using molecular barcodes to capture the history of each clone within the tumor. Using this clonal information, we developed a robust computational pipeline that extracts meaningful target sgRNA-level data from individual tumors, despite the random under-representation of the larger library. Statistical (down-sampling) analysis revealed that CRISPR-StAR has a resolution of 1,000 sgRNAs per tumor which reduces the number of animals required by 7-fold to traditional approaches. Consequently, we have performed several druggable genome screens (~30,000 sgRNA) using just 30-40 individual tumors and identified a catalog of tumor suppressor genes that, when lost, strongly promote tumor growth in vivo without affecting cell proliferation in vitro. This group of genes is enriched with epigenetic modifiers, in particular multiple members of the COMPASS family and the SWI/SNF chromatin remodeling complexes. These results validate CRISPR-StAR as a powerful in vivo functional genomics platform for high throughput target discovery screens.

Citation Format: Silvia Fenoglio, James Tepper, Lauren Grove, Esther CH Uijttewaal, Alborz Bejnood, Yi Yu, Hsin-Jung Wu, Annabel Devault, Shangtao Liu, Binzhang Shen, Samuel R Meier, Ashley H Choi, Tenzing Khendu, Hannah Stowe, Minjie Zhang, Brian B Haines, Alan Huang, Jannik N Andersen, Xuewen Pan, Ulrich Elling, Teng Teng. Inducible activation of sgRNA libraries in tumor xenografts empowers large-scale in vivo target discovery screens [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr C048.