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Label-free metabolic imaging monitors the fitness of chimeric antigen receptor T cells

Nature Biomedical Engineering (2025)Cite this article

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Abstract

Chimeric antigen receptor (CAR) T cell therapy for solid tumours is challenging because of the immunosuppressive tumour microenvironment and a complex manufacturing process. Cellular manufacturing protocols directly impact CAR T cell yield, phenotype and metabolism, which correlates with in vivo potency and persistence. Although metabolic fitness is a critical quality attribute, how T cell metabolic requirements vary throughout the manufacturing process remains unexplored. Here we use optical metabolic imaging (OMI), a non-invasive, label-free method to evaluate single-cell metabolism. Using OMI, we identified the impacts of media composition on CAR T cell metabolism, activation strength and kinetics, and phenotype. We demonstrate that OMI parameters can indicate cell cycle stage and optimal gene transfer conditions for both viral transduction and electroporation-based CRISPR/Cas9. In a CRISPR-edited anti-GD2 CAR T cell model, OMI measurements allow accurate prediction of an oxidative metabolic phenotype that yields higher in vivo potency against neuroblastoma. Our data support OMI as a robust, sensitive analytical tool to optimize manufacturing conditions and monitor cell metabolism for increased CAR T cell yield and metabolic fitness.

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Fig. 1: Activating media, not activating antibody, determines CD3 T cell metabolism.
Fig. 2: OMI is sensitive to metabolic changes as T cells progress through cell cycle following activation.
Fig. 3: OMI identifies optimal timeframe for CRISPR/Cas9 genome editing.
Fig. 4: Media composition has a substantial impact on CAR T cell metabolism and phenotype post-expansion.
Fig. 5: CAR T cells undergoing media transition showed a distinct OMI metabolic profile with lower glycolytic activity compared with those expanded in singular media.
Fig. 6: OMI metabolic features of CAR T cells pre-infusion predict in vivo potency.

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Data availability

All data supporting the findings of this study have been deposited and are available via Zenodo at https://doi.org/10.5281/zenodo.15628321 (ref. 68).

Code availability

All relevant analysis codes have been deposited via Zenodo at https://doi.org/10.5281/zenodo.15628321 (ref. 68).

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Acknowledgements

We thank members of the Capitini, Saha and Skala labs for helpful discussion and comments on the paper, the University of Wisconsin (UW) Carbone Cancer Center Small Animal Imaging and Radiotherapy facility and Flow Cytometry Laboratory (supported by NIH P30 CA014520 and NIH S10 OD025225), M. Brenner (Baylor College of Medicine) for the retroviral 14G2a-OX40-CD28-ζ CAR sequence and C. Mackall (Stanford University) for the retroviral 14G2a-41BB-ζ CAR sequence, the National Cancer Institute for 1A7 antibody for detection of CAR expression, M. Otto (UW–Madison) for the parental CHLA20 cell line, and J. Thomson and J. Zhang (Morgridge Institute for Research) for the AkaLUC-GFP CHLA20 cell line used for in vivo studies. We thank M. Stefely and A. Williams for graphic and paper edits. M.C.S., K. Saha and C.M.C. disclose support for the research described in this study from NIH R01 CA278051, NSF Engineering Research Center (ERC) for Cell Manufacturing Technologies (CMaT) and NSF-EEC 1648035 (C.M.C., K. Saha and M.C.S.). C.M.C. and K. Saha disclose support from St. Baldrick’s Foundation Empowering Pediatric Immunotherapy for Childhood Cancers Team grant, UW–Madison Office of the Vice Chancellor for Research and Graduate Education with funding from the Wisconsin Alumni Research Foundation, Hyundai Hope on Wheels (C.M.C. and K. Saha) and Grainger Institute for Engineering at UW–Madison. C.M.C. discloses support for the research in this publication from MACC Fund. K. Saha discloses funding support from NIH R35 GM119644-01.

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Author notes

  1. These authors contributed equally: Dan L. Pham, Dan Cappabianca.

Authors and Affiliations

  1. Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, USA

    Dan L. Pham, Dan Cappabianca, Cole Weaver, Anna Tommasi, Madison Bugel, Krishanu Saha & Melissa C. Skala

  2. Morgridge Institute for Research, Madison, WI, USA

    Dan L. Pham, Cole Weaver, Jorgo Lika, Jing Fan & Melissa C. Skala

  3. Wisconsin Institute for Discovery, University of Wisconsin–Madison, Madison, WI, USA

    Dan Cappabianca, Anna Tommasi, Madison Bugel & Krishanu Saha

  4. Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA

    Matthew H. Forsberg & Christian M. Capitini

  5. Department of Pediatrics, Division of Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Katherine P. Mueller

  6. Promega Corporation, Fitchburg, WI, USA

    Jolanta Vidugiriene, Anthony Lauer & Kayla Sylvester

  7. Department of Cellular and Molecular Biology, University of Wisconsin–Madison, Madison, WI, USA

    Jorgo Lika

  8. Department of Medical Microbiology and Immunology, University of Wisconsin–Madison, Madison, WI, USA

    Jing Fan

  9. University of Wisconsin Carbone Cancer Center, University of Wisconsin–Madison, Madison, WI, USA

    Christian M. Capitini

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Contributions

D.L.P. and D.C. contributed equally. D.L.P. and C.W. performed the OMI imaging and analysis of T cell samples, and performed the T cell isolation and activation. D.C., A.T. and M.B. isolated and cultured T cells and generated electroporation-based CRISPR-edited CAR T cells. K.P.M. performed viral transductions. M.H.F. performed the mouse study. J.V., A.L. and K. Sylvester performed the ATP production and cellular reducing potential analysis on activated T cells. J.L. performed the metabolomics analysis of two media and the IncuCyte analysis. D.L.P., D.C., M.H.F., K.P.M., C.W., A.T., J.V., A.L., K. Sylvester, J. L. and M.B. performed the experiments and analysed the data. D.L.P. and M.C.S. wrote the paper with inputs from all authors. C.M.C., J.F., K. Saha and M.C.S. supervised the research.

Corresponding authors

Correspondence to Krishanu Saha or Melissa C. Skala.

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Competing interests

K. Saha receives honoraria for advisory board membership for Andson Biotech and Notch Therapeutics. C.M.C. receives honoraria for advisory board membership for Bayer, Elephas Biosciences, Nektar Therapeutics, Novartis and WiCell Research Institute. M.C.S., D.L.P., K. Saha and D.C. declare two patents pending based on this work (WO2024229098A3, WO2024229099A1). M.C.S. is an advisory board member for Elephas Biosciences. No other conflicts of interest are reported.

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Extended data

Extended Data Fig. 1 OMI and cofactor/enzyme activity assessment revealed the impact of culture media on activation kinetics and metabolism of T cells stimulated with aCD3/aCD28 Dynabeads.

(a–e) Liquid chromatography-mass spectrometry analysis revealed significantly different composition in ImmunoCult XF and TexMACs media. Concentration of (a) glucose, (b) glutamine, (c) glutamax, (d) pyruvate, and (e) arginine quantified in ImmunoCult XF and TexMACs media. n = 3 replicates, two-sided unpaired t test. (f) Representative NAD(P)H τm images from T cells activated with αCD3/αCD28 Dynabeads at 1:1 and 2:1 bead-to-T cell ratio in ImmunoCult XF and TexMACs media. αCD3/αCD28 Dynabeads were removed immediately prior to imaging. (g, h) T cells activated in ImmunoCult XF and TexMACs media demonstrated different activation kinetics. NAD(P)H α1 quantification of T cells from two healthy donors activated with αCD3/αCD28 Dynabeads in (g) ImmunoCult XF and (h) TexMACs media at 24-, 48-, and 72-hours post activation. For (g) n = 449, 437, and 432 activated T cells from 3 donors in ImmunoCults media at 24, 48, and 72 hours. For (h), n = 475, 446, and 410 activated T cells from 3 donors in TexMACs media at 24, 48, and 72 hours. For (g, h) two-way ANOVA with Tukey’s posthoc test for multiple comparisons. (i, j) UMAP based on Euclidean distances of 11 OMI parameters (NAD(P)H τm, τ1, τ2, α1, intensity, FAD τm, τ1, τ2, α1, intensity, redox ratio) and cell size of T cells from two healthy donors activated with αCD3/αCD28 Dynabeads, color coded based on (i) culture media and (j) bead-to-T cell ratio. n = 2649 cells. (k) NAD/NADH ratio, and fold increase in (l) NADH concentration, (m) ATP production, (n) LDH, o) GAPDH, and p) IDH activity measured from T cells activated with αCD3/αCD28 Dynabeads (at 1:1 and 3:1 bead-to-T cell ratio), StemCell, or TransAct antibodies for 72 hours in ImmunoCult XF or TexMACs media. The fold increase was calculated as compared to quiescent cells. n = 3 replicates/condition, two-way ANOVA with Sidak’s posthoc test for multiple comparisons. Scale bar is 50 μm. Bars are mean ± SD. * p < 0.0001.

Extended Data Fig. 2 T cells progressed through cell cycle and proliferated upon activation.

(a) Experimental design and timeline. CD3 T cells were isolated from 3 healthy donors and activated with StemCell αCD2/αCD3/αCD28 in ImmunoCult XF media (Imm) or TransAct αCD3/αCD28 in TexMACS media (Tex). Cells were divided into 7 groups with duration of activation ranging from 0 hours (quiescent T cells) to 72 hours prior to electroporation to introduce the anti-GD2 CAR transgene. When activated T cells were collected for electroporation, their metabolic features were characterized using OMI. Meanwhile, their cell cycle stage and proliferation capacity were assessed using flow cytometry of Hoechst 33342 and Ki-67 staining. These activated T cells were then electroporated to incorporate the anti-GD2 CAR transgene and expanded in corresponding culture media. Genome editing efficiency was determined after 7 days of expansion with GD2 CAR antibody using flow cytometry. (b, c) T cells progressed through cell cycle upon activation. Density plots of Hoechst MFI in T cells activated with (b) Imm and (c) Tex methods. For each donor, Hoechst MFI was normalized to the average of 12-hour-activated group. n = 393,999 cells and 370,802 cells for Imm and Tex activation methods, respectively. (d) Correlation between NAD(P)H α1 and cell cycle stage (% cells in S/G2/M phase) at electroporation. Each dot represents one sample average, color coded based on the method of activation (Imm or Tex) and duration of activation (0–72 hours). n = 42 samples, Pearson R analysis. (e, f) T cell proliferation (% Ki-67+) following activation with (e) Imm method or (f) Tex method. n = 3 donors, Brown-Forsythe and Welch ANOVA test with Dunnett’s post hoc test for multiple comparisons. Bars are mean ± SD. Color lines connected donor-match averages.

Extended Data Fig. 3 T cell characteristics at the time of CAR gene transfer correlated with transgene incorporation efficiency.

(a) Experimental setup for viral transduction experiment. T cells were isolated from peripheral blood of two healthy donors and activated with Imm method. Activated CD3 T cells underwent electroporation with Cas9 ribonucleoproteins targeting the human TRAC locus to knockout the T cell receptor (TRAC KO) 2 days prior to transduction with retrovirus to express anti-GD2 CAR receptor using two constructs (OX40-CD28-CAR or 41BB-CAR) as previously described9. OMI was performed immediately before transduction. Transduction efficiency was quantified as %CAR+ after 7 days of expansion. (b) Representative NAD(P)H τm images of TCR-intact and TRAC KO T cells at transduction. OMI parameters including (c) NAD(P)H τm, (d) NAD(P)H α1, and (e) cytoplasm size of cells with intact T cell receptor (TCR-intact) and TRAC KO T cells at transduction. n = 480 TCR intact and 374 TRAC KO cells from 2 independent donors, two-sided Mann-Whitney test. (f) Transduction efficiency (% CAR) of TCR-intact and TRAC KO cells at the end of the manufacturing process. n = 17 samples from 2 donors and 2 anti-GD2 CAR constructs, unpaired two-sided T test. (g) Experimental timeline of electroporation experiment. (h–k) Correlation between cell characteristics (h) NAD(P)H α1, (i) normalized redox ratio, (j) %S/G2/M and (k) %Ki-67+ at electroporation and genome editing outcome (% CAR). Each dot represents one sample average, color coded based on the method of activation (Imm or Tex) and duration of activation (0–72 hours). n = 36 samples, Pearson R analysis. Quiescent T cells with 0-hour activation duration did not undergo genome editing. Bars are mean ± SD. Color lines connected donor-match averages. * p < 0.0001.

Extended Data Fig. 4 CAR T cells expanded in Imm and Tex media displayed distinct metabolic and phenotypic features.

(a) Experimental timeline. (b) Quantification of FAD mean lifetime (FAD τm) of CAR T cells expanded in either ImmunoCult XF or TexMACS media. n = 666 and 751 CAR T cells from 3 independent donors expanded in ImmunoCult XF and TexMACs media supplemented with various cytokine combinations, two-sided Mann-Whitney test. (c–e) OMI metabolic profiles of CAR+ T cells differed based on expansion media. (c) Representative image of CAR+ T cells identified based on PerCP conjugated GD-2 CAR antibody (red). (d) UMAP based on 13 OMI parameters of CAR+ T cells expanded in Imm or Tex media. (e) ROC curves and AUCs of three models based on OMI parameters (Table 1) to classify CAR+ T cells by expansion media (Imm vs. Tex); n = 494 cells for training (80%), n = 123 cells for testing (20%). (f) Quantification of NAD(P)H τm from CAR T cells expanded in ImmunoCult XF media supplemented with 500 U/mL IL-2 compared to other cytokine combinations, n = 123, 83, 96, and 129 CAR T cells expanded in IL-2, IL-7, IL-17, and IL-7 + IL-15(high) supplemented media from 2 donors, ANOVA with Kruskal-Wallis test. MFIs of (g) CCR7 and (h) CD62L of CAR+ T cells expanded in either Imm or Tex media supplemented with different cytokine cocktails, normalized by fluorescence-minus-one (FMO) controls. (n = 87,317 cells from 3 independent donors). UMAP based on Euclidean distances of MFIs of 6 surface markers (CD27, CD45RO, CD62L, CD28, CD45RA and CCR7) of CAR+ T cells expanded in Imm and Tex media, color coded based on (i) culture media or (j) supplemented cytokines. Dots are CAR+ T cells. n = 87,317 cells from 3 independent donors. Bars are mean ± SD. * p < 0.0001.

Extended Data Fig. 5 CAR T cell phenotypes and metabolic profile before in vivo treatment course.

(a) Experimental timeline. (b) Phenotypes of CAR+ T cells expanded in Imm, Tex→Imm, and Tex conditions based on expression of 7 surface markers. (c) Extracellular flux analysis of baseline oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) from CD3 T cells that were unactivated (quiescent) or activated and expanded in Imm or Tex→Imm condition. n = 9–18 samples/condition. Brown-Forsythe and Welch ANOVA tests with Dunnett’s T3 post hoc test for multiple comparisons. Bars are mean ± SD. * p < 0.0001.

Extended Data Fig. 6 Expansion conditions shaped T cell expansion capacity and metabolism.

(a, b) Imm and Tex-Imm T cells exhibited high expansion capacity. Fold expansion of T cells from two healthy donors under various expansion conditions (a) throughout and (b) on day 8 of the expansion process n = 4-6 replicates/condition across two donors, two way ANOVA test with Tukey’s posthoc test for multiple comparisons. (c) ATP production by T cells under several expansion conditions. (d–m) Media transition from TexMACs to ImmunoCult XF (Tex-Imm) shifted T cell metabolism towards balanced oxidative phosphorylation while maintaining ATP production. (d) Representative NAD(P)H τm images of T cells on day 9. (e) Quantification of NAD(P)H τm and (f) normalized NAD(P)H intensity of expanded T cells from two healthy donors on day 9. n = 361-580 cells/conditions across 2 donors, color coded by donors. (g, h) Metabolic cofactors, (i–m) dehydrogenases activity measured from expanded T cells of two healthy donors on day 9. n = 6 replicates across 2 donors. Brown-Forsythe and Welch ANOVA test with Dunnett’s T3 post hoc test for multiple comparisons. Bars are mean ± SD. * p < 0.0001.

Extended Data Fig. 7 In vivo treatment response and phenotyping analysis of CAR T cells post in vivo treatment.

(a) Experimental timeline. (b) Fold change in tumor flux (measured with IVIS imaging) in NSG tumor-bearing mice after CAR T cell treatment. Dash line represents no change in tumor flux (fold change = 1). (c) CAR T treatment outcomes on day 17 post treatment. (d–g) Expression of stem central memory (d, e) and exhaustion phenotypes (f, g) in CAR T cells isolated from treated NSG mouse spleen at day 21 post-treatment. (d, f) Representative flow histograms from one individual mouse in each treatment group. (e, g) Quantification of stem central memory (CD62 + CCR7+) and exhausted (PD-1 + TIGIT+) populations in treated mouse spleen. n = 12 mice, color coded by CAR T treatment groups. Two-sided non-parametric Mann-Whitney test. Bars are mean ± SD.

Extended Data Fig. 8 Tex→Imm CAR T cells demonstrated higher in vitro cytotoxicity than Imm CAR T cells against two cancer models at low effector-to-target ratios.

(a) Representative NAD(P)H τm images of donor-matched CAR T cells expanded in Imm and Tex-Imm conditions. (b, c) Quantification of NAD(P)H α1 and NAD(P)H τm from Imm and Tex-Imm CAR T cells at the end of manufacturing. (d–g) GFP + GD2 + M21 melanoma and (h–k) GFP + GD2 + MG63 osteosarcoma were cocultured with donor-matched GD2-CAR Imm and CAR Tex-Imm T cells at various effector-to-target ratios (1:1, 1:2, 1:5, and 1:10) for 72 hours. (d, e) Normalized GFP intensity and percentage of GFP+ cells in the coculture of CAR T cells and M21 melanoma throughout 72 hours and (f, g) at 72-hour timepoint. (h, i) Normalized GFP intensity and percentage of GFP+ cells in the coculture of CAR T cells and MG63 osteosarcoma throughout 72 hours and (j, k) at 72-hour timepoint. For (d, e) and (h, i) n = 2 well/condition x 72 time points, Friedman test (one-way repeated measures analysis of variance by ranks) with Dunn’s posthoc test for multiple comparisons. For (f, g) and (j, k), n = 2 replicates/condition, unpaired t-test. Bars are mean ± SD. * p < 0.0001. Scale bar is 50 μm.

Extended Data Fig. 9

Gating strategy for analysis of spectral immunophenotyping flow cytometry of CAR T cells post-manufacturing (a) or isolated from treated NSG mouse spleen post-treatment (b).

Extended Data Table 1 Glass’s deltas (Δ) showing maximal effect sizes of Imm and Tex activation methods on T cell metabolism (NAD(P)H τm and NAD(P)H α1)
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Pham, D.L., Cappabianca, D., Forsberg, M.H. et al. Label-free metabolic imaging monitors the fitness of chimeric antigen receptor T cells. Nat. Biomed. Eng (2025). https://doi.org/10.1038/s41551-025-01504-7

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