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CD19-targeting CAR T cell immunotherapy outcomes correlate with genomic modification by vector integration
Abstract
Chimeric antigen receptor-engineered T cells targeting CD19 (CART19) provide an effective treatment for pediatric acute lymphoblastic leukemia but are less effective for chronic lymphocytic leukemia (CLL), focusing attention on improving efficacy. CART19 harbor an engineered receptor, which is delivered through lentiviral vector integration, thereby marking cell lineages and modifying the cellular genome by insertional mutagenesis. We recently reported that vector integration within the host TET2 gene was associated with CLL remission. Here, we investigated clonal population structure and therapeutic outcomes in another 39 patients by high-throughput sequencing of vector-integration sites. Genes at integration sites enriched in responders were commonly found in cell-signaling and chromatin modification pathways, suggesting that insertional mutagenesis in these genes promoted therapeutic T cell proliferation. We also developed a multivariate model based on integration-site distributions and found that data from preinfusion products forecasted response in CLL successfully in discovery and validation cohorts and, in day 28 samples, reported responders to CLL therapy with high accuracy. These data clarify how insertional mutagenesis can modulate cell proliferation in CART19 therapy and how data on integration-site distributions can be linked to treatment outcomes.
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“Lentiviral integrationmediated disruption of loci encoding genes mutated in CH has also been associated with cell-intrinsic alterations in CAR T cell expansion and differentiation [183][184][185] .”
From Clonal haematopoiesis and dysregulation of the immune system (2023) · cites this paper as [183]
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“Notably, knockdown of TET2 183 or knockout of DNMT3A 187 in experimental models of CAR T cells also led to increased differentiation of central memory CD8 + T cells and antitumour responses dependent on CAR stimulation (Fig. 3),”
From Clonal haematopoiesis and dysregulation of the immune system (2023) · cites this paper as [183]
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“suggesting that the effects TET2 disruption in CAR T cells were the result of biallelic impairment in TET2 function 183 .”
From Clonal haematopoiesis and dysregulation of the immune system (2023) · cites this paper as [183]
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Metadata
- Authors
- Nobles, C. L., Sherrill-Mix, S., Everett, J. K., Reddy, S., Fraietta, J. A., Porter, D. L., Frey, N., Gill, S. I., Grupp, S. A., Maude, S. L., Siegel, D. L., Levine, B. L., June, C. H., Lacey, S. F., Melenhorst, J. J., & Bushman, F. D.
- Venue
- Journal of Clinical Investigation
- Published
- 2019-12-17
- Volume
- 130
- Issue
- 2
- Pages
- 673-685
- ISSN
- 0021-9738
- 1558-8238
- Cited by
- 130
- References
- 73
- Language
- en
- Funders
- National Institutes of Health (T32 CA009140, P01 CA214278, P30 CA016520, R01 CA226983, K08 CA194256, R01 AI082020, R01 AI117950, P30 AI045008)
- Gabrielle’s Angel Foundation (--)
- PennCHOP Microbiome Program (--)
- Novartis Institute for Biomedical Research (000)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
