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Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens
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 in...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9149307/ https://www.ncbi.nlm.nih.gov/pubmed/35651625 http://dx.doi.org/10.3389/fimmu.2022.884561 |
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author | Yim, Soorin Hwang, Woochang Han, Namshik Lee, Doheon |
author_facet | Yim, Soorin Hwang, Woochang Han, Namshik Lee, Doheon |
author_sort | Yim, Soorin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9149307 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91493072022-05-31 Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens Yim, Soorin Hwang, Woochang Han, Namshik Lee, Doheon Front Immunol Immunology 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. Frontiers Media S.A. 2022-05-16 /pmc/articles/PMC9149307/ /pubmed/35651625 http://dx.doi.org/10.3389/fimmu.2022.884561 Text en Copyright © 2022 Yim, Hwang, Han and Lee https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Yim, Soorin Hwang, Woochang Han, Namshik Lee, Doheon Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens |
title | Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens |
title_full | Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens |
title_fullStr | Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens |
title_full_unstemmed | Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens |
title_short | Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens |
title_sort | computational discovery of cancer immunotherapy targets by intercellular crispr screens |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9149307/ https://www.ncbi.nlm.nih.gov/pubmed/35651625 http://dx.doi.org/10.3389/fimmu.2022.884561 |
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