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Reducing disparities is critical to promote equity of access to precision treatments for all patients with cancer. While socioenvironmental factors are a major driver behind such disparities, biological differences also are likely to contribute. The prioritization of cancer drug targets is foundational for drug discovery, yet whether ancestry-related signals in target discovery pipelines exist has not been systematically explored due to the absence of data at the appropriate scale. Here, we analyzed data from 611 genome-scale CRISPR/Cas9 viability experiments in human cell line models as part of the Cancer Dependency Map to identify ancestry-associated genetic dependencies. Surprisingly, we found that most putative associations between ancestry and dependency arose from artifacts related to germline variants that are present at different frequencies across ancestry groups. In 2-5% of genes profiled in each cellular model, germline variants in sgRNA targeting sequences likely reduced cutting by the CRISPR/Cas9 nuclease. Unfortunately, this bias disproportionately affected cell models derived from individuals of recent African descent because their genomes tended to diverge more from the consensus genome typically used for CRISPR/Cas9 guide design. To help the scientific community begin to resolve this source of bias, we report three complementary methods for ancestry-agnostic CRISPR experiments. This report adds to a growing body of literature describing ways in which ancestry bias impacts cancer research in underappreciated ways.

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.

Precision medicine promises to improve the treatment of cancer patients, but a lack of therapeutic targets and associated predictive biomarkers limit this reality. To identify novel strategies, we integrate genome-scale CRISPR viability screens across many cancer models with cellular and molecular features to systematically define The Cancer Dependency Map. Using this data, we have identified that XPR1, an inorganic phosphate exporter protein, is a highly selective dependency gene in ovarian and uterine cancers. These cancers are sensitive to loss of XPR1 due to over-expression of SLC34A2, a phosphate importer protein. These data suggest a synthetic lethal relationship in which intracellular phosphate homeostasis is dysregulated in cancer. As proof-of-concept of pharmacological inhibition of XPR1, we have developed protein ligands based on the receptor binding domain of viruses which use XPR1 for cellular entry. These ligands inhibit XPR1 and kill cancer cells in an on-mechanism manner, but may be limited in their clinical utility. As such, we are deepening our understanding of the mechanisms of XPR1-dependent phosphate efflux, and have identified a novel partner protein that is integral to phosphate efflux, possibly revealing functional domains that small molecule inhibitors might target. Overall, these data highlight a novel mechanism to treat cancers by leveraging cancer-specific phosphate dysregulation and further reinforce the Cancer Dependency Map as a powerful engine to uncover novel therapeutic vulnerabilities. Citation Format: Daniel Bondeson, Brenton Paolella, Adhana Asfaw, Michael Rothberg, Thomas Skipper, Gabriel Mesa, Alfredo Gonzalez, Lauren E. Surface, Kentaro Ito, Mariya Kazachkova, William N. Colgan, Allie Warren, Joshua Dempster, J Michael Krill-Burger, Maria Ericsson, Andrew Tang, Iris Fung, Emily S. Chambers, Mai Abdusamad, Nancy Dumont, John Doench, Federica Piccioni, David Root, Jesse Boehm, William C. Hahn, Michael Mannstadt, James McFarland, Francisca Vazquez, Todd Golub. Phosphate dysregulation as a novel therapeutic strategy in ovarian and uterine cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1028.

Socioeconomic factors and discrimination play major roles in variable cancer treatment outcomes across individuals from different ancestral backgrounds. Tumors from patients of different ancestry groups also have divergent patterns of somatic and germline alterations. This led us to hypothesize that these molecular differences may also contribute to the variable treatment outcomes observed in the clinic. We hypothesized that the ancestry of cell lines would impact their genetic dependencies. To test this hypothesis, we leveraged The Cancer Dependency Map (DepMap) which has performed genome-wide CRISPR screens across >1,000 cell lines and >30 cancer types. We first leveraged variant calls from WES/WGS to infer cell line ancestry, then correlated these ancestries with DepMap gene dependency scores. This analysis was underpowered to detect differences in cell lines of African, American, and South Asian descent, since cell lines from these ancestry groups are poorly represented in DepMap, and in cancer research models in general. We were, however, able to detect 71 gene dependencies that were associated with either European or East Asian ancestry. Since different ancestry groups have divergent patterns of germline alterations, we reasoned that specific germline alterations may result in ancestry-associated dependencies. Surprisingly, we identified cis-QTLs for >75% of the ancestry-associated genes. We originally hypothesized that these variants would alter the function of the encoded protein, but instead found that these variants mapped to the targeting sequences of the sgRNA. This suggests that ancestry-associated mismatches within sgRNA targeting sequences can preclude Cas9-mediated genome editing. To understand this problem systematically, we mapped the germline variants that were catalogued in gnomAD to multiple genome-wide CRISPR libraries. The fraction of affected genes differed from library to library and was typically between 2-5%, but we found that individuals of African descent were consistently more affected by this problem across all CRISPR libraries. This is important because it suggests that cell lines of African descent have a higher rate of false negatives in all CRISPR-based experiments. In total, we identified a subset of genes that have ancestry-associated dependency profiles. Most of these genes are the result of ancestry-associated mismatches within the sgRNA targeting sequences. However, many of these genes are not, and require further investigation to understand the influence of ancestry on these genetic dependencies. Citation Format: Sean Alexander Misek, Aaron Fultineer, Jeremie Kalfon, Javad Noorbakhsh, Isabella Boyle, Joshua Dempster, Lia Petronio, Katherine Huang, James McFarland, Rameen Beroukhim, Jesse Boehm. Ancestry bias in CRISPR guide design impedes discovery of genetic dependencies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2173.

Phenotypic screening is a valuable tool to identify compounds to treat cancer, but is limited as it is time and resource intensive to screen hundreds of cancer cell lines. In order to increase the throughput of phenotypic screening, we set out to expand and further develop the PRISM method (Profiling Relative Inhibition Simultaneously in Mixtures) [Yu et al., 2016]. PRISM is a method to barcode cell lines with a unique 24 nucleotide barcode and mix them together to screen simultaneously in a pool, decreasing the time and cost of screening. The previously described PRISM method was limited in that it used only 100 adherent cell lines of one cancer model context, it required the use of a highly specialized Luminex bead-based detection system, and it was only applicable to small molecule screening. Here we report on the expansion of our barcoded cell line collection to 800 cancer cell lines of over 45 lineages, an improved method called PRISMseq using next-generation sequencing, and a novel method to perform genetic perturbations in 500 cancer cell lines simultaneously called PRISPR (PRISM/CRISPR). PRISMseq allows for assaying compound cell line sensitivity profiles in a large pool of hundreds of cell lines and detecting the DNA barcodes using next-generation sequencing (NGS). We recapitulate the known biology for established oncology drugs like the BRAF, EGFR, BCR-ABL and MDM2 inhibitor classes using this method with our cell line panel. We also further extended this method to be applicable to genetic perturbation using CRISPR/Cas9 knockout of individual genes concurrently in hundreds of cancer cell lines. We are able to recover expected biomarkers or genetic dependencies for our CRISPR/Cas9 validation reagents. This expanded PRISM profiling approach increases statistical power due to the addition of cancer contexts in our cell line collection, and improves versatility by enabling the screening of both small molecules and genetic perturbations. We believe that this method has overcome the limitations of the original PRISM method. It has also overcome the limitations of phenotypic screening, as the resources required to screen hundreds of cell lines has been decreased by orders of magnitude. Citation Format: Samantha Bender, Cong Zhu, Li Wang, Michael Rothberg, Joshua Dempster, Brenton Paolella, Mustafa Kocak, Massami Laird, Jordan Rossen, Karolina Stumbraite, Jordan Bryan, Vickie Wang, John Doench, Francisca Vazquez, Aviad Tsherniak, Todd Golub, Jennifer Roth. Massively parallel multiplexed methods to screen hundreds of barcoded cancer cell line models with small molecules or genetic perturbations using next-generation sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2690.