Evidence map›Paper›PMID 27401141›Full record

ArticleMolecular therapy : the journal of the American Society of Gene Therapy2016

Feasibility and Safety of RNA-transfected CD20-specific Chimeric Antigen Receptor T Cells in Dogs with Spontaneous B Cell Lymphoma.

M Kazim Panjwani, Jenessa B Smith, Keith Schutsky, Josephine Gnanandarajah, Colleen M O'Connor, Daniel J Powell, Nicola J Mason

Open access · bronzeAbstract read
In one paragraph

Article in Molecular therapy : the journal of the American Society of Gene Therapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
6.1field-weighted citation impact, top 2% 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

67 citing papers in PubMed, 127 citations in OpenAlex.

  1. Article
  2. Advances inMolecular therapy. Nucleic acids · 2026
    Review
  3. Review
  4. Review
  5. A New Method of Canine CD4International journal of molecular sciences · 2025
    Article
  6. Article
  7. Article
  8. Applications and Opportunities for Immune Cell CAR Engineering in Comparative Oncology.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
    Review
  9. Article
  10. Article
  11. RNA-Based Therapeutic Technology.International journal of molecular sciences · 2023
    Review
  12. Article
  13. Review
  14. Article
  15. Racing CARs to veterinary immuno-oncology.Frontiers in veterinary science · 2023
    Review
  16. Article
  17. Applying a clinical lens to animal models of CAR-T cell therapies.Molecular therapy. Methods & clinical development · 2022
    Review
  18. Review
  19. Review
  20. Review

7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

M Kazim PanjwaniDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Jenessa B SmithDepartment of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Keith SchutskyDepartment of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Josephine GnanandarajahDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Colleen M O'ConnorCAVU Biotherapies, Houston, Texas, USA.
Daniel J PowellDepartment of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Nicola J MasonDepartment of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
University of Pennsylvania · US

Funding

IMMUNOBIOLOGY OF NORMAL AND NEOPLASTIC LYMPHOCYTEST32CA009140 · NCI · UNIVERSITY OF PENNSYLVANIA · PI Malay Haldar, WARREN S PEAR · 1985 to 2026
$16.1M
NCI NIH HHS T32 CA009140
6 · The paper itself

Abstract

Preclinical murine models of chimeric antigen receptor (CAR) T cell therapy are widely applied, but are greatly limited by their inability to model the complex human tumor microenvironment and adequately predict safety and efficacy in patients. We therefore sought to develop a system that would enable us to evaluate CAR T cell therapies in dogs with spontaneous cancers. We developed an expansion methodology that yields large numbers of canine T cells from normal or lymphoma-diseased dogs. mRNA electroporation was utilized to express a first-generation canine CD20-specific CAR in expanded T cells. The canine CD20 (cCD20) CAR expression was efficient and transient, and electroporated T cells exhibited antigen-specific interferon-gamma (IFN-γ) secretion and lysed cCD20+ targets. In a first-in-canine study, autologous cCD20-ζ CAR T cells were administered to a dog with relapsed B cell lymphoma. Treatment was well tolerated and led to a modest, but transient, antitumor activity, suggesting that stable CAR expression will be necessary for durable clinical remissions. Our study establishes the methodologies necessary to evaluate CAR T cell therapy in dogs with spontaneous malignancies and lays the foundation for use of outbred canine cancer patients to evaluate the safety and efficacy of next-generation CAR therapies and their optimization prior to translation into humans.

Indexed as

Immunotherapy, AdoptiveRNA, MessengerAnimalsAntigen-Presenting CellsAntigens, CD20Antineoplastic Combined Chemotherapy ProtocolsCell Line, TumorCyclophosphamideDogsDoxorubicinElectroporationGene ExpressionHumansInterleukin-2Interleukin-21InterleukinsAntigens, CD20CyclophosphamideDoxorubicinInterleukin-2Interleukin-21InterleukinsPrednisoneReceptors, Antigen, T-CellRNA, MessengerVincristine

Identifiers

PMID27401141
PMCPMC5113111
OpenAlexW2465431026

What OpenQuestion holds

Textmetadata
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.