Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens.
Authors
Yim, Soorin
Hwang, Woochang
Han, Namshik
Lee, Doheon
Publication Date
2022Journal Title
Front Immunol
ISSN
1664-3224
Publisher
Frontiers Media SA
Volume
13
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Yim, S., Hwang, W., Han, N., & Lee, D. (2022). Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens.. Front Immunol, 13 https://doi.org/10.3389/fimmu.2022.884561
Abstract
Cancer immunotherapy targets the interplay between immune and cancer cells. In particular, interactions between cytotoxic T lymphocytes (CTLs) and cancer cells, such as PD-1 (PDCD1) binding PD-L1 (CD274), are crucial for cancer cell clearance. However, immune checkpoint inhibitors targeting these interactions are effective only in a subset of patients, requiring the identification of novel immunotherapy targets. Genome-wide clustered regularly interspaced short palindromic repeats (CRISPR) screening in either cancer or immune cells has been employed to discover regulators of immune cell function. However, CRISPR screens in a single cell type complicate the identification of essential intercellular interactions. Further, pooled screening is associated with high noise levels. Herein, we propose intercellular CRISPR screens, a computational approach for the analysis of genome-wide CRISPR screens in every interacting cell type for the discovery of intercellular interactions as immunotherapeutic targets. We used two publicly available genome-wide CRISPR screening datasets obtained while triple-negative breast cancer (TNBC) cells and CTLs were interacting. We analyzed 4825 interactions between 1391 ligands and receptors on TNBC cells and CTLs to evaluate their effects on CTL function. Intercellular CRISPR screens discovered targets of approved drugs, a few of which were not identifiable in single datasets. To evaluate the method's performance, we used data for cytokines and costimulatory molecules as they constitute the majority of immunotherapeutic targets. Combining both CRISPR datasets improved the recall of discovering these genes relative to using single CRISPR datasets over two-fold. Our results indicate that intercellular CRISPR screens can suggest novel immunotherapy targets that are not obtained through individual CRISPR screens. The pipeline can be extended to other cancer and immune cell types to discover important intercellular interactions as potential immunotherapeutic targets.
Keywords
cell-cell communication, cytotoxic T cells, genome-wide CRISPR screen, immune checkpoint inhibitors, intercellular interactions, ligand-receptor interactions, target discovery, triple-negative breast cancer, CRISPR-Cas Systems, Clustered Regularly Interspaced Short Palindromic Repeats, Humans, Immunotherapy, T-Lymphocytes, Cytotoxic, Triple Negative Breast Neoplasms
Identifiers
External DOI: https://doi.org/10.3389/fimmu.2022.884561
This record's URL: https://www.repository.cam.ac.uk/handle/1810/337727
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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