ArticleInternational journal of molecular sciences2022
Comparison of FACS and PCR for Detection of BCMA-CAR-T Cells.
Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 18 citations in OpenAlex.
- Universal high-sensitivity CAR T-cell monitoring by targeting linker sequences.Frontiers in immunology · 2026Article
- Impact of the kinetics of circulating anti-BCMA CAR-T cells and normal lymphocytes on the outcome of MM patients.HemaSphere · 2025Article
- Challenges in the preclinical design and assessment of CAR-T cells.Frontiers in immunology · 2025Review
- Review
- Teclistamab impairs detection of BCMA CAR-T cells.Blood advances · 2023Article
- Monitoring of kinetics and exhaustion markers of circulating CAR-T cells as early predictive factors in patients with B-cell malignancies.Frontiers in immunology · 2023Article
- Changes in Bone Marrow Tumor and Immune Cells Correlate with Durability of Remissions Following BCMA CAR T Therapy in Myeloma.Blood cancer discovery · 2022Article
- An Analysis of Monitoring Solutions for CAR T Cell Production.Healthcare technology lettersReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chimeric-antigen-receptor (CAR)-T-cell therapy is already widely used to treat patients who are relapsed or refractory to chemotherapy, antibodies, or stem-cell transplantation. Multiple myeloma still constitutes an incurable disease. CAR-T-cell therapy that targets BCMA (B-cell maturation antigen) is currently revolutionizing the treatment of those patients. To monitor and improve treatment outcomes, methods to detect CAR-T cells in human peripheral blood are highly desirable. In this study, three different detection reagents for staining BCMA-CAR-T cells by flow cytometry were compared. Moreover, a quantitative polymerase chain reaction (qPCR) to detect BCMA-CAR-T cells was established. By applying a cell-titration experiment of BCMA-CAR-T cells, both methods were compared head-to-head. In flow-cytometric analysis, the detection reagents used in this study could all detect BCMA-CAR-T cells at a similar level. The results of false-positive background staining differed as follows (standard deviation): the BCMA-detection reagent used on the control revealed a background staining of 0.04% (±0.02%), for the PE-labeled human BCMA peptide it was 0.25% (±0.06%) and for the polyclonal anti-human IgG antibody it was 7.2% (±9.2%). The ability to detect BCMA-CAR-T cells down to a concentration of 0.4% was similar for qPCR and flow cytometry. The qPCR could detect even lower concentrations (0.02-0.01%). In summary, BCMA-CAR-T-cell monitoring can be reliably performed by both flow cytometry and qPCR. In flow cytometry, reagents with low background staining should be preferred.
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.