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Computational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens.

cam.issuedOnline2022-05-16
dc.contributor.authorYim, Soorin
dc.contributor.authorHwang, Woochang
dc.contributor.authorHan, Namshik
dc.contributor.authorLee, Doheon
dc.date.accessioned2022-06-07T08:10:01Z
dc.date.available2022-06-07T08:10:01Z
dc.date.issued2022
dc.date.submitted2022-02-26
dc.date.updated2022-06-07T08:10:01Z
dc.description.abstractCancer 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.
dc.identifier.doi10.17863/CAM.85136
dc.identifier.eissn1664-3224
dc.identifier.issn1664-3224
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/337727
dc.languageen
dc.language.isoeng
dc.publisherFrontiers Media SA
dc.publisher.urlhttp://dx.doi.org/10.3389/fimmu.2022.884561
dc.subjectcell-cell communication
dc.subjectcytotoxic T cells
dc.subjectgenome-wide CRISPR screen
dc.subjectimmune checkpoint inhibitors
dc.subjectintercellular interactions
dc.subjectligand-receptor interactions
dc.subjecttarget discovery
dc.subjecttriple-negative breast cancer
dc.subjectCRISPR-Cas Systems
dc.subjectClustered Regularly Interspaced Short Palindromic Repeats
dc.subjectHumans
dc.subjectImmunotherapy
dc.subjectT-Lymphocytes, Cytotoxic
dc.subjectTriple Negative Breast Neoplasms
dc.titleComputational Discovery of Cancer Immunotherapy Targets by Intercellular CRISPR Screens.
dc.typeArticle
dcterms.dateAccepted2022-04-07
prism.publicationNameFront Immunol
prism.volume13
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
rioxxterms.versionVoR
rioxxterms.versionofrecord10.3389/fimmu.2022.884561

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