PD-1 signaling uncovers a pathogenic subset of T cells in inflammatory arthritis.


Journal

bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
17 Nov 2023
Historique:
medline: 28 11 2023
pubmed: 28 11 2023
entrez: 28 11 2023
Statut: epublish

Résumé

PD-1 is an immune checkpoint on T cells and interventions to block this receptor result in T cell activation and enhanced immune response to tumors. Paired to that, and despite a decade of research, approaches to treat autoimmunity with PD-1 agonists still need to be more successful. To resolve this, new methods must be developed to augment PD-1 function beyond engaging the receptor. We conducted a flow cytometry analysis of T cells isolated from the peripheral blood and synovial fluid of patients with rheumatoid arthritis. In addition, we performed a genome-wide CRISPR/Cas9 screen to identify genes associated with PD-1 signaling. We further analyzed genes involved in PD-1 signaling using publicly available bulk and single-cell RNA sequencing datasets. Our screen confirmed known regulators in proximal PD-1 signaling and, importantly, found an additional 1,112 unique genes related to PD-1 ability to inhibit T cell functions. These genes were strongly associated with the response of cancer patients to PD-1 blockades and with high tumor immune dysfunction and exclusion scores, confirming their role downstream of PD-1. Functional annotation revealed that more significant genes uncovered were those associated with known immune regulation processes. Remarkably, these genes were considerably downregulated in T cells isolated from patients with inflammatory arthritis, supporting their overall inhibitory functions. A study of rheumatoid arthritis single-cell RNA sequencing data demonstrated that five genes, KLRG1, CRTAM, SLAMF7, PTPN2, and KLRD1, were downregulated in activated and effector T cells isolated from synovial fluids. Back-gating these genes to canonical cytotoxic T cell signatures revealed PD-1 We concluded that PD-1

Sections du résumé

Background UNASSIGNED
PD-1 is an immune checkpoint on T cells and interventions to block this receptor result in T cell activation and enhanced immune response to tumors. Paired to that, and despite a decade of research, approaches to treat autoimmunity with PD-1 agonists still need to be more successful. To resolve this, new methods must be developed to augment PD-1 function beyond engaging the receptor.
Methods UNASSIGNED
We conducted a flow cytometry analysis of T cells isolated from the peripheral blood and synovial fluid of patients with rheumatoid arthritis. In addition, we performed a genome-wide CRISPR/Cas9 screen to identify genes associated with PD-1 signaling. We further analyzed genes involved in PD-1 signaling using publicly available bulk and single-cell RNA sequencing datasets.
Results UNASSIGNED
Our screen confirmed known regulators in proximal PD-1 signaling and, importantly, found an additional 1,112 unique genes related to PD-1 ability to inhibit T cell functions. These genes were strongly associated with the response of cancer patients to PD-1 blockades and with high tumor immune dysfunction and exclusion scores, confirming their role downstream of PD-1. Functional annotation revealed that more significant genes uncovered were those associated with known immune regulation processes. Remarkably, these genes were considerably downregulated in T cells isolated from patients with inflammatory arthritis, supporting their overall inhibitory functions. A study of rheumatoid arthritis single-cell RNA sequencing data demonstrated that five genes, KLRG1, CRTAM, SLAMF7, PTPN2, and KLRD1, were downregulated in activated and effector T cells isolated from synovial fluids. Back-gating these genes to canonical cytotoxic T cell signatures revealed PD-1
Conclusion UNASSIGNED
We concluded that PD-1

Identifiants

pubmed: 38014321
doi: 10.1101/2023.11.16.566893
pmc: PMC10680732
pii:
doi:

Types de publication

Preprint

Langues

eng

Auteurs

Classifications MeSH