Evidence map›Paper›PMID 37654973›Full record

ArticleMolecular therapy oncolytics2023

Development of a bicistronic anti-CD19/CD20 CAR construct including abrogation of unexpected nucleic acid sequence deletions.

Norris Lam, Richard Finney, Shicheng Yang, Stephanie Choi, Xiaolin Wu, Lauren Cutmore, Jorge Andrade, Lei Huang, Christina Amatya, Margaret Cam and 1 more

Open access · goldAbstract read
In one paragraph

Article in Molecular therapy oncolytics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.9field-weighted citation impact, top 6% of its field
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

14 citing papers in PubMed, 17 citations in OpenAlex.

  1. Trial
  2. Article
  3. Trogocytosis in cancer immunity and cellular immunotherapy: mechanisms, therapeutic challenges, and translational opportunities.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  4. Article
  5. Article
  6. Can we cure autoimmunity?Current opinion in immunology · 2026
    Review
  7. Review
  8. Review
  9. Targets for CAR Therapy in Multiple Myeloma.International journal of molecular sciences · 2025
    Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. 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

11 authors at 2 institutions in 1 country.

Norris LamNational Institutes of Health, National Cancer Institute, Center for Cancer Research, Surgery Branch, Bethesda, MD, USA.
Richard FinneyNational Institutes of Health, National Cancer Institute, Center for Cancer Research, Office of the Director, Bethesda, MD, USA.
Shicheng YangNational Institutes of Health, National Cancer Institute, Center for Cancer Research, Surgery Branch, Bethesda, MD, USA.
Stephanie ChoiNational Institutes of Health, National Cancer Institute, Center for Cancer Research, Surgery Branch, Bethesda, MD, USA.
Xiaolin WuCancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD 21701, USA.
Lauren CutmoreNational Institutes of Health, National Cancer Institute, Center for Cancer Research, Surgery Branch, Bethesda, MD, USA.
Jorge AndradeKite, A Gilead Company, Santa Monica, CA, USA.
Lei HuangKite, A Gilead Company, Santa Monica, CA, USA.
Christina AmatyaNational Institutes of Health, National Cancer Institute, Center for Cancer Research, Surgery Branch, Bethesda, MD, USA.
Margaret CamNational Institutes of Health, National Cancer Institute, Center for Cancer Research, Office of the Director, Bethesda, MD, USA.
James N KochenderferNational Institutes of Health, National Cancer Institute, Center for Cancer Research, Surgery Branch, Bethesda, MD, USA.
National Institutes of Health · USFrederick National Laboratory for Cancer Research · US

Funding

WORK ORDER 126643 B539 EXPAND IC SUITE75N91019D00024 · NIAID · LEIDOS BIOMEDICAL RESEARCH, INC. · PI BRISCOE, LYNN · 2019 to 2025
$3932.6M
NCI NIH HHS 75N91019D00024
6 · The paper itself

Abstract

To address CD19 loss from lymphoma after anti-CD19 chimeric antigen receptor (CAR) T cell therapy, we designed a bicistronic construct encoding an anti-CD19 CAR and an anti-CD20 CAR. We detected deletions from the expected bicistronic construct sequence in a minority of transcripts by mRNA sequencing. Loss of bicistronic construct transgene DNA was also detected. Deletions of sequence were present at much higher frequencies in transduced T cell mRNA versus gamma-retroviral vector RNA. We concluded that these deletions were caused by intramolecular template switching of the reverse transcriptase enzyme during reverse transcription of gamma-retroviral vector RNA into transgene DNA of transduced T cells. Intramolecular template switching was driven by repeated regions of highly similar nucleic acid sequence within CAR sequences. We optimized the sequence of the bicistronic CAR construct to reduce repeated regions of highly similar sequences. This optimization nearly eliminated sequence deletions. This work shows that repeated regions of highly similar nucleic acid sequence must be avoided in complex CAR constructs. We further optimized the bicistronic construct by lengthening the linker of the anti-CD20 single-chain variable fragment. This modification increased CD20-specific interleukin-2 release and reduced CD20-specific activation-induced cell death. We selected an optimized anti-CD19/CD20 bicistronic construct for clinical development.

Indexed as

antigen-escapebicistronicCARCD19CD20chimeric antigen receptorlymphomarecombinationretrovirussequence deletionsT cells

Identifiers

PMID37654973
PMCPMC10465854
OpenAlexW4384831437

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.