Evidence map›Paper›PMID 42373802›Full record

ReviewNature biomedical engineering2026

The evolving role of cytokines for CAR-T cell manufacturing and beyond.

Mar Guaza-Lasheras, Johanna Nimmerfroh, Dominic Schwarz, Tanja D de Gruijl, Jessica Hartmann, Christian Klein, Heinz Läubli, Michal Lotem, Joerg Mittelstaet, Christophe Paget and 8 more

Erratum issuedAbstract readReview
In one paragraph

Review in Nature biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Mar Guaza-Lasheras *Department of Molecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, Langen, Germany.
Johanna Nimmerfroh *Department of Biomedicine, University of Basel, Basel, Switzerland.
Dominic Schwarz *Faculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Munich, Germany.ORCID http://orcid.org/0000-0002-0322-5059
Tanja D de GruijlDepartment of Medical Oncology, Cancer Center Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
Jessica HartmannDepartment of Molecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, Langen, Germany.ORCID http://orcid.org/0000-0001-9372-8954
Christian KleinFaculty for Chemistry and Pharmacy, Ludwig-Maximilians-Universität München, Munich, Germany.ORCID http://orcid.org/0000-0001-7594-7280
Heinz LäubliDepartment of Biomedicine, University of Basel, Basel, Switzerland.ORCID http://orcid.org/0000-0002-8910-5620
Michal LotemSharet Institute of Oncology, Hadassah Hebrew University Medical Center, Jerusalem, Israel.
Joerg MittelstaetFaculty of Life Sciences, Reutlingen University, Reutlingen, Germany.
Christophe PagetInstitut National de la Santé et de la Recherche Médicale, Centre d'Etude des Pathologies Respiratoires (CEPR), UMR 1100, Université de Tours, Tours, France.
Sine Reker HadrupDepartment of Health Technology, Technical University of Denmark, Copenhagen, Denmark.ORCID http://orcid.org/0000-0002-5937-4344
Sonja SchallenbergMiltenyi Biotec BV & Co. KG, Bergisch Gladbach, Germany.ORCID http://orcid.org/0000-0002-5040-6426
Per Thor StratenCenter for Cancer Immune therapy (CCIT), Department of Oncology, Herlev University Hospital, Herlev, Denmark.
Sebastian TheurichDepartment of Medicine III, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany.
Dario VenetzRoche Innovation Center Zürich, Schlieren, Switzerland.
Alfred ZippeliusDepartment of Biomedicine, University of Basel, Basel, Switzerland.
Laurence ZitvogelFaculté de Médecine, Université Paris-Saclay, Le Kremlin-Bicêtre, France.
Sebastian KoboldInstitute of Clinical Pharmacology, LMU Hospital, Ludwig Maximilians Universität (LMU), Munich, Germany. sebastian.kobold@med.uni-muenchen.de.ORCID http://orcid.org/0000-0002-5612-4673

Funding

EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 Marie Skłodowska-Curie Actions (H2020 Excellent Science - Marie Skłodowska-Curie Actions) 955575
6 · The paper itself

Abstract

Chimeric antigen receptor (CAR)-T cells represent a recent clinically validated modality in cancer therapy and beyond. However, broad industrial implementation faces technological, logistical, regulatory and financial challenges. A major bottleneck is the ex vivo production process, where cytokines are essential and product-determining constituents. To better understand the complexity of cytokine utilization throughout the production process, we rigorously reviewed the existing literature, including extended manufacturing parameters from 292 available clinical reports. We found a progressive reduction of interleukin-2 exposure, driven by its association with unfavourable cell characteristics. Preclinically, this catalysed the evaluation of alternative cytokines with potential to preserve naive phenotypes, support cell expansion and enhance the efficacy of CAR-T cells. Here we illustrate the evolving use of cytokines, reveal non-standardized clinical CAR-T cell manufacturing parameters, and summarize preclinical and next-generation concepts, which may improve manufacturing efficiency, cost-effectiveness and therapeutic outcomes. Our observations may further guide the development of cytokine-armouring strategies to promote in-patient expansion and persistence, even as innovations such as shortened manufacturing and in vivo engineering techniques could reduce reliance on cytokines during ex vivo culture.

Indexed as

CytokinesImmunotherapy, AdoptiveReceptors, Chimeric AntigenT-LymphocytesAnimalsCell Culture TechniquesHumansInterleukin-2CytokinesInterleukin-2Receptors, Chimeric Antigen

Identifiers

PMID42373802
PMCPMC7619229

What OpenQuestion holds

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Registered trials

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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.