ArticleCell2026
AI-driven discovery of GPNMB CAR T cells as a multi-cancer therapy.
Article in Cell, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- AI and authorship: Norms and uses to preserve human-led science.PNAS nexus · 2026Article
- Artificial intelligence in oncology: linking biological discovery to clinical utility.Molecular cancer · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
Chimeric antigen receptor (CAR) T cells have demonstrated curative potential in hematologic cancers and increasing efficacy in solid tumors and non-malignant diseases. However, target identification remains a major bottleneck. We developed an artificial intelligence (AI)-driven approach for CAR T cell target discovery by integrating single-cell RNA sequencing datasets from human skin cancer and healthy tissue. Candidates were refined using public datasets to optimize for tumor composition, tissue specificity, and clinical feasibility. Large language models were applied to prioritize and nominate targets with therapeutic promise. Glycoprotein non-metastatic melanoma protein B (GPNMB) was the most frequently nominated target. We validated its expression across hematologic and solid tumors. We engineered a human GPNMB-directed CAR T cell, which showed potent anti-tumor activity in mouse models of monoblastic leukemia, melanoma, and colorectal adenocarcinoma. These findings establish a scalable pipeline for CAR T cell target discovery and support the translation of GPNMB-directed CAR T cells as a multi-cancer therapeutic.
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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.