ArticleThe Journal of experimental medicine2024
Framework for in vivo T cell screens.
Article in The Journal of experimental medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- A community machine learning challenge to predict the effects of gene perturbations on T cell differentiation for cancer immunotherapy.bioRxiv : the preprint server for biology · 2026Article
- Neutrophil Antigen Presentation Reprograms the Tumor Microenvironment and Elicits Durable and Broad Antitumor Immunity.Cancer research communications · 2026Article
- CRISPR-screen informed engineered T cell therapies.Frontiers in immunology · 2026Review
- Article
- CRISPR screens identify STUB1 as an inhibitor of cytokine signaling in CD8Nature immunology · 2025Article
- A STUB1-CHIC2 complex inhibits CD8Nature immunology · 2025Article
- A roadmap toward genome-wide CRISPR screening throughout the organism.Cell genomics · 2025Review
- THE BIOLOGY BEHIND PD-1 CHECKPOINT BLOCKADE.Transactions of the American Clinical and Climatological Association · 2025Review
- Dissecting host-microbe interactions with modern functional genomics.Current opinion in microbiology · 2024Review
- In Vivo CRISPR Screening Reveals CHD7 as a Positive Regulator of Short-lived Effector Cells.Journal of immunology (Baltimore, Md. : 1950) · 2024Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
In vivo T cell screens are a powerful tool for elucidating complex mechanisms of immunity, yet there is a lack of consensus on the screen design parameters required for robust in vivo screens: gene library size, cell transfer quantity, and number of mice. Here, we describe the Framework for In vivo T cell Screens (FITS) to provide experimental and analytical guidelines to determine optimal parameters for diverse in vivo contexts. As a proof-of-concept, we used FITS to optimize the parameters for a CD8+ T cell screen in the B16-OVA tumor model. We also included unique molecular identifiers (UMIs) in our screens to (1) improve statistical power and (2) track T cell clonal dynamics for distinct gene knockouts (KOs) across multiple tissues. These findings provide an experimental and analytical framework for performing in vivo screens in immune cells and illustrate a case study for in vivo T cell screens with UMIs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.