Evidence map›Paper›PMID 37217245›Full record

ArticleJournal for immunotherapy of cancer2023

CAR T-cell detection scoping review: an essential biomarker in critical need of standardization.

David P Turicek, Victoria M Giordani, Josquin Moraly, Naomi Taylor, Nirali N Shah

Abstract readScoping Review
In one paragraph

Article in Journal for immunotherapy of cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Need for standardization of cytokine profiling in CAR T cell therapy.Molecular therapy : the journal of the American Society of Gene Therapy · 2024
    Review
  17. Finding Your CAR: The Road Ahead for Engineered T Cells.The American journal of pathology · 2024
    Review
  18. Review
  19. Review
  20. A rapid method to assess theImmunotherapy advances · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

David P TuricekPediatric Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA.ORCID 0000-0003-0837-2688
Victoria M Giordani *Pediatric Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA.
Josquin Moraly *Pediatric Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA.
Naomi TaylorNational Cancer Institute, Bethesda, Maryland, USA.ORCID 0000-0002-2459-4558
Nirali N ShahNIH, Bethesda, Maryland, USA nirali.shah@nih.gov.ORCID 0000-0002-8474-9080

Funding

Metabolic regulation of T cell effector function and anti-tumor immunotherapyZIABC011923 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI TAYLOR, NAOMI · 2019 to 2025
$9.5M
Immunotherapeutic approaches to treat pediatric hematologic malignanciesZIABC011823 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI SHAH, NIRALI · 2019 to 2025
$6.1M
Intramural NIH HHS ZIA BC011823Intramural NIH HHS ZIA BC011923
6 · The paper itself

Abstract

The expansion and persistence of chimeric antigen receptor (CAR) T-cells in patients are associated with response, toxicity, and long-term efficacy. As such, the tools used to detect CAR T-cells following infusion are fundamental for optimizing this therapeutic approach. Nevertheless, despite the critical value of this essential biomarker, there is significant variability in CAR T-cell detection methods as well as the frequency and intervals of testing. Furthermore, heterogeneity in the reporting of quantitative data adds layers of complexity that limit intertrial and interconstruct comparisons. We sought to assess the heterogeneity of CAR T-cell expansion and persistence data in a scoping review using the PRISMA-ScR checklist. Focusing on 21 clinical trials from the USA, featuring a Food and Drug Administration-approved CAR T-cell construct or one of its predecessors, 105 manuscripts were screened and 60 were selected for analysis, based on the inclusion of CAR T-cell expansion and persistence data. Across the array of CAR T-cell constructs, flow cytometry and quantitative PCR were identified as the two primary techniques for detecting CAR T-cells. However, despite apparent uniformity in detection techniques, the specific methods used were highly variable. Detection time points and the number of evaluated time points also ranged markedly and quantitative data were often not reported. To evaluate whether subsequent manuscripts from a trial resolved these issues, we analyzed all subsequent manuscripts reporting on the 21 clinical trials, recording all expansion and persistence data. While additional detection techniques-including droplet digital PCR, NanoString, and single-cell RNA sequencing-were reported in follow-up publications, inconsistencies with respect to detection time points and frequency remained, with a significant amount of quantitative data still not readily available. Our findings highlight the critical need to establish universal standards for reporting on CAR T-cell detection, especially in early phase studies. The current reporting of non-interconvertible metrics and limited provision of quantitative data make cross-trial and cross-CAR T-cell construct comparisons extremely challenging. Establishing a standardized approach for collecting and reporting data is urgently needed and would represent a substantial advancement in the ability to improve outcomes for patients receiving CAR T-cell therapies.

Indexed as

Receptors, Antigen, T-CellT-LymphocytesBiomarkersHumansImmunotherapy, AdoptiveReference StandardsUnited StatesBiomarkersReceptors, Antigen, T-Cellimmunotherapy, adoptivereceptors, chimeric antigenreview

Identifiers

PMID37217245
PMCPMC10230989

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.