ReviewJournal for immunotherapy of cancer2025
Intentional heterogeneity in autologous cell-based gene therapies: strategic considerations for first-in-human trials.
Review in Journal for immunotherapy of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Stem cell and extracellular vesicle therapies for wound healing: An umbrella review of predominantly diabetic and preclinical evidence.Cell transplantationPooled it
- Advancing adoptive T cell therapy in ovarian cancer: barriers, innovations, and emerging platforms.Journal for immunotherapy of cancer · 2026Review
- Site-specific genome engineering of primary human natural killer cells for programmable anti-tumor function.bioRxiv : the preprint server for biology · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cell-based gene therapies, including chimeric antigen receptor-T, T-cell receptor-T, and tumor-infiltrating lymphocyte therapies, have transformed the treatment landscape for certain cancers, yet their efficacy in solid tumors remains limited. Next-generation therapies aim to overcome biological barriers, enhance potency and safety, and streamline development timelines through innovative approaches. Recent advances in genome editing technologies have identified hundreds of gene edits that improve T-cell functionality in preclinical models. However, the limited direct translatability of these findings and the impracticality of testing each of the individual edits in a traditional clinical trial highlight the need for more efficient strategies.This article provides an overview of genome-wide screens that identify gene knockouts and knock-ins to enhance T-cell function and the limitations with translating these results to human trials. Next, we propose a novel clinical trial design for testing multiple gene modifications simultaneously within a single T-cell infusion product. This approach would enable head-to-head evaluation of edits in an internally controlled setting, accelerating the identification of promising candidate edits. Key considerations for Chemistry, Manufacturing, and Controls, non-clinical evaluation, and clinical protocols are discussed, with an emphasis on patient safety and ethical transparency.This framework is informed by insights shared at the "Unlocking Complex Cell-based Gene Therapies" workshop, held on May 6, 2024. Co-hosted by Friends of Cancer Research and the Parker Institute for Cancer Immunotherapy, the event brought together participants from academia, the US Food and Drug Administration, and patient advocacy groups. By fostering collaboration among these stakeholders, this innovative approach aims to accelerate the development of effective cell-based therapies for complex diseases.
Indexed as
Identifiers
What OpenQuestion holds
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.