ArticleCancer discovery2018
Resisting CAR T-cell Therapy: A Case Study.
Article in Cancer discovery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- From Multi-Omics to Visualization and Beyond: Bridging Micro and Macro Insights in CAR-T Cell Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
Corrections and comments
- Comment on
Authors and funding
0 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A case report highlights a novel, rare mechanism of resistance to chimeric antigen receptor (CAR) T-cell therapy, conferred by the accidental transduction of a single leukemic B cell with the anti-CD19 CAR (CAR19) gene during therapy manufacturing. Because CAR19 bound directly to CD19 on the cell surface-a phenomenon called in cis epitope masking-the therapeutic target was effectively hidden from reprogrammed T cells.
Indexed as
Identifiers
30366924What 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.