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Identification of a clinically efficacious CAR T cell subset in diffuse large B cell lymphoma by dynamic multidimensional single-cell profiling

Nature Cancer (2024)Cite this article

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An Author Correction to this article was published on 22 May 2024

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Abstract

Chimeric antigen receptor (CAR) T cells used for the treatment of B cell malignancies can identify T cell subsets with superior clinical activity. Here, using infusion products of individuals with large B cell lymphoma, we integrated functional profiling using timelapse imaging microscopy in nanowell grids with subcellular profiling and single-cell RNA sequencing to identify a signature of multifunctional CD8+ T cells (CD8-fit T cells). CD8-fit T cells are capable of migration and serial killing and harbor balanced mitochondrial and lysosomal volumes. Using independent datasets, we validate that CD8-fit T cells (1) are present premanufacture and are associated with clinical responses in individuals treated with axicabtagene ciloleucel, (2) longitudinally persist in individuals after treatment with CAR T cells and (3) are tumor migrating cytolytic cells capable of intratumoral expansion in solid tumors. Our results demonstrate the power of multimodal integration of single-cell functional assessments for the discovery and application of CD8-fit T cells as a T cell subset with optimal fitness in cell therapy.

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Fig. 1: Study design for integrated single-cell multiomic profiling of IPs.
Fig. 2: T cells from individuals with CR were enriched for migration, serial killing and mitochondrial volume compared to T cells from individuals with PR/PD.
Fig. 3: Molecular profile of CD8-fit T cells, a subset of CAR T cell IPs associated with clinical response revealed by scRNA-seq.
Fig. 4: Marker-free transwell migration assay enables the enrichment of CD8-fit T cells.
Fig. 5: Phenotype and in vivo efficacy of migratory CAR T cells.
Fig. 6: Quantifying the link between migration and functionality in diverse CARs.

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Data availability

The scRNA-seq data of the IPs are available under GEO accession number GSE208052, and migratory CAR T cell scRNA-seq data are available under GEO accession number GSE253872. External datasets used for CD8-fit T cell signature validation were accessed under GEO accession numbers GSE197268 (ref. 24) and GSE151511 (ref. 8) and EMBL-EBI accession number E-MTAB-11536 (ref. 28). The external dataset used for T cell persistence was accessed via dbGaP under study accession phs002966.v1.p1 (ref. 25). The healthy donor T cell scRNA-seq data were accessed under accession number GSE201035 (ref. 32). Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

Code availability

All relevant package and software information is provided in the Methods. No custom code was generated in the course of this study.

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Acknowledgements

This publication was supported by the NIH (R01GM143243, to N.V.), CPRIT (RP180466, to N.V.), MRA Established Investigator Award (509800, to N.V.), NSF (1705464, to N.V.), CDMRP (CA160591, to N.V.) and Owens foundation (to N.V.). scRNA-seq was performed at the Single Cell Genomics Core at Baylor College of Medicine supported by the NIH shared instrument grants S10OD018033, S10OD023469, S10OD025240 and P30EY002520 to Rui Chen. Sequencing was performed at the Genomic and RNA Profiling Core at Baylor College of Medicine with funding from the NIH NCI (P30CA125123) and CPRIT (RP200504). We would like to acknowledge the MD Anderson Cancer Center Flow Cytometry and Cellular Imaging Core facility for FACS sorting (NCI P30CA16672), Intel for the loan of the computing cluster and the Research Computing Data Core at the University of Houston for the use of the Carya and Sabine clusters.

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Authors and Affiliations

  1. Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA

    Ali Rezvan, Gabrielle Romain, Melisa Martinez-Paniagua, Xingyue An, Irfan N. Bandey, Melisa J. Montalvo, Jay R. T. Adolacion, Arash Saeedi, Fatemeh Sadeghi & Navin Varadarajan

  2. CellChorus, Houston, TX, USA

    Mohsen Fathi & Laurence J. N. Cooper

  3. Kite, a Gilead Company, Santa Monica, CA, USA

    Darren Heeke, Mike Mattie & Adrian Bot

  4. Texas Children’s Hospital, Baylor College of Medicine, Houston, TX, USA

    Kristen Fousek & Nabil Ahmed

  5. Department of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Nahum Puebla-Osorio & Sattva Neelapu

  6. Department of Biologics Development, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Chantale Bernatchez

  7. Divsion of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Harjeet Singh

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  1. Ali Rezvan
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Contributions

A.R., G.R., S.N., L.J.N.C., H.S. and N.V. designed the study. A.R., G.R., M.F., H.S., S.N., M.J.M., N.V. and L.J.N.C. prepared the paper. A.R., G.R., M.F., M.M.P., K.F., X.A., F.S., M.J.M. and I.N.B. performed the experiments. A.R., G.R., M.F., A.S., M.M.P., X.A., N.A., J.R.T.A., M.J.M. and F.S. analyzed the data. H.S., L.J.N.C., S.N., N.P.O., A.B., C.B., M.M. and D.H. provided human samples. All authors edited and approved the paper.

Corresponding author

Correspondence to Navin Varadarajan.

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Competing interests

L.J.N.C. and N.V. are cofounders of CellChorus that licensed TIMING from University of Houston. N.V. is a cofounder of AuraVax Therapeutics. L.J.N.C. has equity ownership in Alaunos Oncology (formerly Ziopharm Oncology). The Sleeping Beauty system for CD19-specific CAR T cells is licensed including to Ziopharm Oncology. M.F. is an employee of CellChorus. None of these conflicts of interest influenced any part of the study design or results. The remaining authors declare no competing interests.

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Nature Cancer thanks Michael Dustin, Frederick Locke and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Phenotype characteristics of infusion products measured by flow cytometry.

(a) Comparisons of CAR + T cells recorded by flow cytometry for all sixteen patients (n). There is no significant difference in the CAR frequency between CR and PR/PD. (b) Comparisons of CD4 + T cells recorded by flow cytometry for all sixteen patients (n). There is no significant difference in the CD4 frequency between CR and PR/PD.

Source data

Extended Data Fig. 2 T cells from CR are enriched for serial killing, increasing mitochondrial and lysosomal size, and persistent migration.

(a) Schematic of a killing event at an E:T of 1:1 in which a CAR T-cell conjugates and kills a NALM-6 cell. The plot on the right shows the killing rate comparison between T cells from CR and PR/PD within all 1E:1T nanowells. Each dot (n) represents the frequency of killer T cells for each IP. Micrograph showing an example of 1E:1T killing event through the 6-hours (hh:mm) of time-lapse imaging from a CR IP. (b) Schematic of a killing event, showing the interaction parameters. tSeek defined as the time for CAR-T cell to find and conjugate to the NALM-6 cell. tconjugation is defined as the duration of CAR-T cell in stable conjugation with NALM-6 cell. tDeath is the time interval between the start of the conjugation and the apoptosis of the NALM-6 cell. Plots show the comparison between T cells from CR and PD/PR for these parameters. Each dot (n) represents the average value for all T cells within each IP. (c) Representative violin plot shows the interaction parameters from one responder IP: tSeek (n = 96 events), tconjugation (n = 94 events), tDeath (n = 30 events). The bar graph shows the killing frequencies of the same responder IP at an E:T of both 1:1 and 1:2. (d) Schematics and examples of serial killing, mono killing and no-killing events in nanowells with an E:T of 1:2. (e) Unsupervised hierarchical clustering based on parameters from TIMING, and confocal microscopy. Serial killing, migration, increasing mitochondrial and lysosomal volume were features associated with T cells from CR patients. (f) Cytotoxicity and motility correlations with CD4/CD8 ratio. Each point represents the average parameter for each IP (n = 9 patient IPs). Cytotoxicity is defined as the frequency of 1E:1T killing from TIMING. The Pearson’s correlation coefficient was calculated for CR and PR/PD IP.

Source data

Extended Data Fig. 3 T-cell phenotypes defined using scRNA-seq.

(a) Uniform Manifold Approximation and Projection (UMAP) for 21,469 cells from nine IPs. Bar graph showing the distribution of T cells from CR and PD/PR among 10 clusters determined using unsupervised clustering. (b) Bubble plot showing key genes associated with T-cell migration and exhaustion phenotypes. (c) Pseudotime trajectory analysis for two clusters enriched in PD (CD8-1: n = 572 cells, CD8-2: n = 1,031 cells) and one cluster enriched in CR (CD8-6: n = 1,253 cells). Necklace plots show CD8-2 (Central Memory dominant) differentiate into Effector/Effector Memory dominant CD8-fit (CD8-6) and CD8-1. (d) Violin plot (left) showing the ssGSEA score for AMPK activation calculated for two clusters enriched in PD (CD8-1: n = 572 cells, CD8-2: n = 1,031 cells) and CD8-fit (CD8-6: n = 1,253 cells) cluster enriched in CR. Violin plot (right) showing the ssGSEA score for the TCF7 signature for the three clusters. The black bar represents the median and the dotted lines denote quartiles. P values were computed using two-tailed Welch’s T-test. (e) Schematic overview of the experimental process used to identify signatures of persistent CAR T cells. Single-cell gene expression and T-cell receptor (TCR) datasets were generated by sequencing pre- (GMP: good manufacturing practice facility) and post-infusion CD19 CAR T cells from blood and bone marrow samples of pediatric patients with B-ALL. (f) Violin plots showing the transcriptome similarities between the CD8+ T cells from our datasets and CD8+ GMP effector precursors. P values were calculated using two-tailed t-test. The black bar represents the median and the dotted lines denote quartiles. P values were computed using two-tailed Welch’s T-test. (g) Gene set enrichment analysis (GSEA) of CD8+ GMP effector precursors gene signatures within cells from CD8-fit cluster compared with cells from all other CD8 clusters. The effector precursors gene signature is based on differentially expressed genes between the CD8+ effector precursors clusters and all other GMP CD8+ T cells from part E.

Extended Data Fig. 4 Matrix binding genes are significantly upregulated in the CD8-fit population.

Violin plots showing the expression of matrix binding genes enriched in CD8-fit cluster (CD8-1: n = 572 cells, CD8-2: n = 1,031 cells, CD8-fit: n = 1,253 cells). The black bar represents the median and the dotted lines denote quartiles. P values were computed using two-tailed Welch’s T-test.

Extended Data Fig. 5 CD8-fit cells can be identified in healthy donor derived T cells and in the premanufacture PBMCs of patients treated with CAR T cells.

(a) Overview of external dataset study GSE201035. (b) Uniform Manifold Approximation and Projection (UMAP) for 6,713 cells from two donors. Bar graph showing the distribution of CD8+ T cells among 8 clusters determined using unsupervised clustering. (c) Violin plot showing the CD8-fit ssGSEA score comparison between the 8 healthy donor CD8 + T-cell clusters. For the violin plot, the black bar represents the median and the dotted lines denote quartiles. P values were computed using one-way ANOVA with Holm-Šídák’s multiple comparisons test. (d) Validation of the association between CD8-fit and clinical responses in pre-manufactured T cells. Single-cell gene expression datasets were generated by sequencing pre-manufactured T cells from patients with B-cell lymphoma. ssGSEA-derived migration scores between CD8+ T cells from CR (n = 13,930) and PD (n = 3,679) were computed. For the violin plot, the black bar represents the median and the dotted lines denote quartiles. P value was computed using two-tailed Welch’s T-test.

Extended Data Fig. 6 CD4+T-cell phenotypes defined using scRNA-seq.

(a) Comparisons of the T-cell migration scores between all CD4+ T cells (n = 12,527) from 9 CR and PD/PR IPs. The black bar represents the median and the dotted lines denote quartiles. P values were computed using two-tailed Welch’s T-test. (b) UMAP for CD4+ T cells (n = 12,527). Nine clusters were identified using unsupervised clustering. (c) Heat map of two CD4+ T-cell clusters generated by unsupervised clustering. CD4-4 mostly cells from PR/PD while CD4-1 are enriched with CR cells. A color-coded track on top shows the cells from infusion products of CR (green) and PR/PD (red). The track below the heatmap, shows the sample origin for each cell. (d) Bubble plot showing key genes differentially expressed among CD4+ T clusters. P value was calculated using the Wilcoxon rank sum test with Bonferroni correction.

Extended Data Fig. 7 The impact of AMPK inhibition on T cell antitumor function revealed by TIMING.

(A/B) (a, b) The migration and polarization of 19-28z T cells treated with Compound C (CC). All data representative of three independent experiments with 19-28z T cells from three healthy human donors at an E:T of 1:1. The black bar represents the median and the dotted lines denote quartiles. The P value was computed using a two-tailed Welch’s t-test. (c) Comparisons of the killing frequency of vehicle treated (DMSO) or CC treated 19-28z CAR T cells. Each data point represents a single cell. P value was computed using two-tailed log-rank test. (d) The cumulative frequency of T cells conjugating to tumors cells over 8 hours. P value was computed using two-tailed log-rank test. (e) The duration of conjugation between individual T cells and tumor cells. Each data point represents a single cell. The black bar represents the median and the dotted lines denote quartiles. The P value was computed using a two-tailed Welch’s t-test. (f) The impact of AMPK inhibition on migrating capabilities of expanded tumor infiltrating lymphocytes (TILs) from melanoma patients. The migration speed of individual TILs as measured by TIMING (1E:0T). Each data point represents average migration for a single cell. The black bar represents the median and the dotted lines denote quartiles. P value was computed using two-tailed Welch’s t-test.

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Extended Data Fig. 8 Enrichment and functional characterization of migratory 19-28z T cells.

(a) Comparisons between the migration of migrated (migratory) and unsorted cells as measured by TIMING (1E:0T). The black bar represents the median and the dotted lines denote quartiles. P value was computed using two-tailed Welch’s t-test. (b) The frequency of conjugation of T cells to tumor cells comparing migratory and unsorted 19-28z T cells evaluated using TIMING (1E:1T). P value was computed using a two-tailed chi-square test. (c) Killing percentage of migratory and unsorted 19-28z T cells evaluated using TIMING (1E:1T). P value was computed using a two-tailed chi-square test. (d) Phenotyping of matched 19-28z and migratory 19-28z T-cell populations. This data is representative of at least four healthy donor-derived T-cell populations measured by flow cytometry. Gating strategies are shown from the side scatter and forward scatter panels on the far left.

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Extended Data Fig. 9 Migratory 19-28z T cells showed enhanced antitumor activity compared to the unsorted 19-28z T cells in suboptimal dose model.

(a) Design of mice experiments to determine the relative efficacy of the 19-28z populations. Mice were treated with either 19-28z T cells or migratory 19-28z T cells five days after the injection of ffLuc expressing EGFP + NALM-6 cells. The mice were euthanized on day 31 and five mice from each of the two T-cell treated groups was used to quantify both the tumor cells and persisting T cells within the spleen and bone marrow of mice. (b) False-colored images illustrating the photon flux from ffLuc expressing EGFP+NALM-6 cells treated with suboptimal doses of 19-28z T cells. (c) Time course of the longitudinal measurements of NALM-6 derived photon flux from the three separate cohorts of mice (n = 5 in each group). The dotted line marks the day (Day 5) where 19-28z T cells were introduced into the mice. The background luminescence was defined based on mice with no tumor. Error bars represent SEM and P values were computed using a two-tailed Mann-Whitney t-test.

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Extended Data Fig. 10 Quantifying the link between migration and functionality in diverse CARs.

(a–c) The polarization (reflective of the morphology of migratory cells) of individual killer and nonkiller CAR T cells without and with conjugation to tumor cells. All data from an E:T of 1:1. (A) shows the data for 19-8-28z T cells tested against NALM-6 cells. (B) and (C) show the data for two different constructs of tri-specific CAR+ T cells tested against patient-derived tumor cells. The black bar represents the median and the dotted lines denote quartiles. All P values were computed using two-tailed t-tests and each data point represents a single effector cell.

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Supplementary information

Reporting Summary

Supplementary Tables 1–4

Supplementary Tables 1–4.

Supplementary Video 1

Representative example of a CAR+ T cell from an individual with CR killing a NALM-6 tumor cell. Red denotes target labeling, blue denotes effector, and green indicates apoptosis (Annexin V staining). The movie is sped up 1,500×. Time is displayed as hh:mm; scale bar, 20 µm.

Supplementary Video 2

Representative example of a CAR+ T cell serial killing two NALM-6 tumor cells. Red denotes target labeling, blue denotes effector, and green indicates apoptosis (Annexin V staining). The movie is sped up 1,500×. Time is displayed as hh:mm; scale bar, 20 µm.

Supplementary Video 3

Representative examples of serial killing, monokilling and no-killing events in nanowells with an E:T ratio of 1:2. Red denotes target labeling, blue denotes effector, and green indicates apoptosis (Annexin V staining). The movie is sped up 1,500×. Time is displayed as hh:mm; scale bar, 20 µm.

Supplementary Video 4

Representative examples of a T cell with high (2 µm min–1) and low migratory capacity (0.2 µm min–1). The movie is sped up 1,500×. Time is displayed as hh:mm; scale bar, 20 µm.

Supplementary Video 5

Representative example of CAR T cell migration before and during conjugation with a NALM-6 cell. Red denotes target labeling, and blue denotes effector. The movie is sped up 1,500×. Time is displayed as hh:mm; scale bar, 20 µm.

Supplementary Video 6

Representative example of a killer CAR T cell and a nonkiller CAR T cell. Red denotes target labeling, blue denotes effector, and green indicates apoptosis (Annexin V staining). The movie is sped up 1,500×. Time is displayed as hh:mm; scale bar, 20 µm.

Supplementary Video 7

Representative examples of tumor-infiltrating lymphocytes treated with DMSO (control) and CC (AMPK inhibitor) profiled using TIMING. The movie is sped up 1,500×. Time is displayed as hh:mm; scale bar, 20 µm.

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Rezvan, A., Romain, G., Fathi, M. et al. Identification of a clinically efficacious CAR T cell subset in diffuse large B cell lymphoma by dynamic multidimensional single-cell profiling. Nat Cancer (2024). https://doi.org/10.1038/s43018-024-00768-3

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