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Efficient recovery of potent tumour-infiltrating lymphocytes through quantitative immunomagnetic cell sorting

Nature Biomedical Engineering volume 6, pages 108–117 (2022)Cite this article

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Abstract

Adoptive cell therapies require the recovery and expansion of highly potent tumour-infiltrating lymphocytes (TILs). However, TILs in tumours are rare and difficult to isolate efficiently, which hinders the optimization of therapeutic potency and dose. Here we show that a configurable microfluidic device can efficiently recover potent TILs from solid tumours by leveraging specific expression levels of target cell-surface markers. The device, which is sandwiched by permanent magnets, balances magnetic forces and fluidic drag forces to sort cells labelled with magnetic nanoparticles conjugated with antibodies for the target markers. Compared with conventional cell sorting, immunomagnetic cell sorting recovered up to 30-fold higher numbers of TILs, and the higher levels and diversity of the recovered TILs accelerated TIL expansion and enhanced their therapeutic potency. Immunomagnetic cell sorting also allowed us to identify and isolate potent TIL subpopulations, in particular TILs with moderate levels of CD39 (a marker of T-cell reactivity to tumours and T-cell exhaustion), which we found are tumour-specific, self-renewable and essential for the long-term success of adoptive cell therapies.

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Fig. 1: MATIC assay.
Fig. 2: MATIC enabled rapid and high-yield recovery of highly heterogeneous and potent CD8+ TILs from a mouse melanoma model.
Fig. 3: CD39med TILs isolated by MATIC showed a self-renewable, tumour-specific and non-exhausted progenitor phenotype.
Fig. 4: CD39med TILs isolated by MATIC were highly potent in vivo.

Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. The unprocessed TCR sequencing files are too large to be publicly shared, but they are available from the corresponding author on reasonable request. Source data are provided with this paper.

References

  1. Mellman, I., Coukos, G. & Dranoff, G. Cancer immunotherapy comes of age. Nature 480, 480–489 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Rosenberg, S. A. Cell transfer immunotherapy for metastatic solid cancer—what clinicians need to know. Nat. Rev. Clin. Oncol. 8, 577–585 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Gong, N., Sheppard, N. C., Billingsley, M. M., June, C. H. & Mitchell, M. J. Nanomaterials for T-cell cancer immunotherapy. Nat. Nanotechnol. 16, 25–36 (2021).

    Article  CAS  PubMed  Google Scholar 

  4. Huang, X. et al. DNA scaffolds enable efficient and tunable functionalization of biomaterials for immune cell modulation. Nat. Nanotechnol. 16, 214–223 (2021).

    Article  CAS  PubMed  Google Scholar 

  5. Andersen, R. et al. Long-lasting complete responses in patients with metastatic melanoma after adoptive cell therapy with tumour-infiltrating lymphocytes and an attenuated IL2 regimen. Clin. Cancer Res. 22, 3734–3745 (2016).

    Article  CAS  PubMed  Google Scholar 

  6. Dudley, M. E. Cancer regression and autoimmunity in patients after clonal repopulation with antitumour lymphocytes. Science 298, 850–854 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Rosenberg, S., Spiess, P. & Lafreniere, R. A new approach to the adoptive immunotherapy of cancer with tumour-infiltrating lymphocytes. Science 233, 1318–1321 (1986).

    Article  CAS  PubMed  Google Scholar 

  8. Yamamoto, T. N., Kishton, R. J. & Restifo, N. P. Developing neoantigen-targeted T cell–based treatments for solid tumours. Nat. Med. 25, 1488–1499 (2019).

    Article  CAS  PubMed  Google Scholar 

  9. Tran, E. et al. Cancer immunotherapy based on mutation-specific CD4+ T cells in a patient with epithelial cancer. Science 344, 641–645 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Garber, K. Pursuit of tumour-infiltrating lymphocyte immunotherapy speeds up. Nat. Biotechnol. 37, 969–971 (2019).

    Article  PubMed  Google Scholar 

  11. Borch, T. H. et al. Future role for adoptive T-cell therapy in checkpoint inhibitor-resistant metastatic melanoma. J. Immunother. Cancer 8, 1–7 (2020).

    Article  Google Scholar 

  12. Kverneland, A. H. et al. Adoptive cell therapy in combination with checkpoint inhibitors in ovarian cancer. Oncotarget 11, 2092–2105 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Valpione, S. et al. Immune awakening revealed by peripheral T cell dynamics after one cycle of immunotherapy. Nat. Cancer 1, 210–221 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Guo, X. et al. Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing. Nat. Med. 24, 978–985 (2018).

    Article  CAS  PubMed  Google Scholar 

  15. Simoni, Y. et al. Bystander CD8+ T cells are abundant and phenotypically distinct in human tumour infiltrates. Nature 557, 575–579 (2018).

    Article  CAS  PubMed  Google Scholar 

  16. Duhen, T. et al. Co-expression of CD39 and CD103 identifies tumour-reactive CD8 T cells in human solid tumours. Nat. Commun. 9, 2724 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Krishna, S. et al. Stem-like CD8 T cells mediate response of adoptive cell immunotherapy against human cancer. Science 370, 1328–1334 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Poschke, I. et al. A phase I clinical trial combining dendritic cell vaccination with adoptive T cell transfer in patients with stage IV melanoma. Cancer Immunol. Immunother. 63, 1061–1071 (2014).

    Article  CAS  PubMed  Google Scholar 

  19. Stevanović, S. et al. A phase II study of tumour-infiltrating lymphocyte therapy for human papillomavirus-associated epithelial cancers. Clin. Cancer Res. 25, 1486–1493 (2019).

    Article  PubMed  Google Scholar 

  20. Mishra, A. et al. Ultrahigh-throughput magnetic sorting of large blood volumes for epitope-agnostic isolation of circulating tumour cells. Proc. Natl Acad. Sci. USA 117, 16839–16847 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Individualized treatments for the many. Nat. Biomed. Eng. 3, 755–756 (2019).

  22. Dong, M. B. et al. Systematic immunotherapy target discovery using genome-scale in vivo CRISPR screens in CD8 T cells. Cell 178, 1189–1204.e23 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Hall, M. L. et al. Expansion of tumour-infiltrating lymphocytes (TIL) from human pancreatic tumours. J. Immunother. Cancer 4, 1–12 (2016).

    Article  PubMed Central  Google Scholar 

  24. Garaud, S. et al. Tumour-infiltrating B cells signal functional humoral immune responses in breast cancer. JCI Insight 4, e129641 (2019).

    Article  PubMed Central  Google Scholar 

  25. Wagner, P. et al. Detection and functional analysis of tumour infiltrating T-lymphocytes (TIL) in liver metastases from colorectal cancer. Ann. Surg. Oncol. 15, 2310–2317 (2008).

    Article  PubMed  Google Scholar 

  26. Salot, S. et al. Large scale expansion of Vγ9Vδ2 T lymphocytes from human peripheral blood mononuclear cells after a positive selection using MACS ‘TCR γ/δ + T cell isolation kit’. J. Immunol. Methods 347, 12–18 (2009).

    Article  CAS  PubMed  Google Scholar 

  27. Geens, M. et al. The efficiency of magnetic-activated cell sorting and fluorescence-activated cell sorting in the decontamination of testicular cell suspensions in cancer patients. Hum. Reprod. 22, 733–742 (2007).

    Article  CAS  PubMed  Google Scholar 

  28. Faraghat, S. A. et al. High-throughput, low-loss, low-cost, and label-free cell separation using electrophysiology-activated cell enrichment. Proc. Natl Acad. Sci. USA 114, 4591–4596 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Sutermaster, B. A. & Darling, E. M. Considerations for high-yield, high-throughput cell enrichment: fluorescence versus magnetic sorting. Sci. Rep. 9, 227 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Mair, B. et al. High-throughput genome-wide phenotypic screening via immunomagnetic cell sorting. Nat. Biomed. Eng. 3, 796–805 (2019).

    Article  CAS  PubMed  Google Scholar 

  31. Moore, D. K. et al. Isolation of B-cells using Miltenyi MACS bead isolation kits. PLoS ONE 14, e0213832 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Witek, M. A., Freed, I. M. & Soper, S. A. Cell separations and sorting. Anal. Chem. 92, 105–131 (2020).

    Article  CAS  PubMed  Google Scholar 

  33. Zhou, Y. et al. Evaluation of single-cell cytokine secretion and cell–cell interactions with a hierarchical loading microwell chip. Cell Rep. 31, 107574 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Segaliny, A. I. et al. Functional TCR T cell screening using single-cell droplet microfluidics. Lab Chip 18, 3733–3749 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Lin, E. et al. High-throughput microfluidic labyrinth for the label-free isolation of circulating tumour cells. Cell Syst. 5, 295–304.e4 (2017).

    Article  CAS  PubMed  Google Scholar 

  36. Fachin, F. et al. Monolithic chip for high-throughput blood cell depletion to sort rare circulating tumour cells. Sci. Rep. 7, 10936 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Zhao, W. et al. Tumour antigen-independent and cell size variation-inclusive enrichment of viable circulating tumour cells. Lab Chip 19, 1860–1876 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Alix-Panabières, C. & Pantel, K. Challenges in circulating tumour cell research. Nat. Rev. Cancer 14, 623–631 (2014).

    Article  PubMed  Google Scholar 

  39. Li, P. & Ai, Y. Label-free multivariate biophysical phenotyping-activated acoustic sorting at the single-cell level. Anal. Chem. 93, 4108–4117 (2021).

    Article  CAS  PubMed  Google Scholar 

  40. Nawaz, A. A. et al. Acoustofluidic fluorescence activated cell sorter. Anal. Chem. 87, 12051–12058 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Cheng, Z., Wu, X., Cheng, J. & Liu, P. Microfluidic fluorescence-activated cell sorting (μFACS) chip with integrated piezoelectric actuators for low-cost mammalian cell enrichment. Microfluid. Nanofluidics 21, 9 (2017).

    Article  Google Scholar 

  42. Nie, X. et al. High-throughput dielectrophoretic cell sorting assisted by cell sliding on scalable electrode tracks made ofconducting-PDMS. Sens. Actuators B 327, 128873 (2021).

    Article  Google Scholar 

  43. de Wijs, K. et al. Micro vapor bubble jet flow for safe and high-rate fluorescence-activated cell sorting. Lab Chip 17, 1287–1296 (2017).

    Article  PubMed  Google Scholar 

  44. Jing, Y. et al. Negative selection of hematopoietic progenitor cells by continuous magnetophoresis. Exp. Hematol. 35, 662–672 (2007).

    Article  PubMed  Google Scholar 

  45. Lin, S. et al. A flyover style microfluidic chip for highly purified magnetic cell separation. Biosens. Bioelectron. 129, 175–181 (2019).

    Article  CAS  PubMed  Google Scholar 

  46. Murray, C. et al. Unsupervised capture and profiling of rare immune cells using multi-directional magnetic ratcheting. Lab Chip 18, 2396–2409 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Wang, Z. et al. Ultrasensitive and rapid quantification of rare tumourigenic stem cells in hPSC-derived cardiomyocyte populations. Sci. Adv. 6, eaay7629 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Labib, M. et al. Tracking the expression of therapeutic protein targets in rare cells by antibody-mediated nanoparticle labelling and magnetic sorting. Nat. Biomed. Eng. 5, 41–52 (2021).

    Article  CAS  PubMed  Google Scholar 

  49. Mirzaei, H. R., Rodriguez, A., Shepphird, J., Brown, C. E. & Badie, B. Chimeric antigen receptors T cell therapy in solid tumour: challenges and clinical applications. Front. Immunol. 8, 1850 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Ma, Q., Wang, Y., Lo, A. S. Y., Gomes, E. M. & Junghans, R. P. Cell density plays a critical role in ex vivo expansion of T cells for adoptive immunotherapy. J. Biomed. Biotechnol. 2010, 386545 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Canale, F. P. et al. CD39 expression defines cell exhaustion in tumour-infiltrating CD8+ T cells. Cancer Res. 78, 115–128 (2018).

    Article  CAS  PubMed  Google Scholar 

  52. Blank, C. U. et al. Defining ‘T cell exhaustion’. Nat. Rev. Immunol. 19, 665–674 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Kortekaas, K. E. et al. CD39 identifies the CD4+ tumour-specific T-cell population in human cancer. Cancer Immunol. Res. 8, 1311–1321 (2020).

    Article  CAS  PubMed  Google Scholar 

  54. Miller, B. C. et al. Subsets of exhausted CD8+ T cells differentially mediate tumour control and respond to checkpoint blockade. Nat. Immunol. 20, 326–336 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Siddiqui, I. et al. Intratumoural Tcf1 + PD-1 + CD8 + T cells with stem-like properties promote tumour control in response to vaccination and checkpoint blockade immunotherapy. Immunity 50, 195–211.e10 (2019).

    Article  CAS  PubMed  Google Scholar 

  56. Han, J. et al. Resident and circulating memory T cells persist for years in melanoma patients with durable responses to immunotherapy. Nat. Cancer 2, 300–311 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Jiang, P. et al. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat. Med. 24, 1550–1558 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Carmona, S. J., Siddiqui, I., Bilous, M., Held, W. & Gfeller, D. Deciphering the transcriptomic landscape of tumour-infiltrating CD8 lymphocytes in B16 melanoma tumours with single-cell RNA-Seq. OncoImmunology 9, 1737369 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Galletti, G. et al. Two subsets of stem-like CD8+ memory T cell progenitors with distinct fate commitments in humans. Nat. Immunol. 21, 1552–1562 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Im, S. J. et al. Defining CD8+ T cells that provide the proliferative burst after PD-1 therapy. Nature 537, 417–421 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Jansen, C. S. et al. An intra-tumoural niche maintains and differentiates stem-like CD8 T cells. Nature 576, 465–470 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Held, W., Siddiqui, I., Schaeuble, K. & Speiser, D. E. Intratumoural CD8+ T cells with stem cell–like properties: implications for cancer immunotherapy. Sci. Transl. Med. 11, eaay6863 (2019).

    Article  CAS  PubMed  Google Scholar 

  63. Chen, Z. et al. TCF-1-centered transcriptional network drives an effector versus exhausted CD8 T cell-fate decision. Immunity 51, 840–855.e5 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Moesta, A. K., Li, X.-Y. & Smyth, M. J. Targeting CD39 in cancer. Nat. Rev. Immunol. 20, 739–755 (2020).

    Article  CAS  PubMed  Google Scholar 

  65. Takenaka, M. C., Robson, S. & Quintana, F. J. Regulation of the T cell response by CD39. Trends Immunol. 37, 427–439 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Nihei, O. K., de Carvalho, A. C. C., Savino, W. & Alves, L. A. Pharmacologic properties of P2Z/P2X7receptor characterized in murine dendritic cells: role on the induction of apoptosis. Blood 96, 996–1005 (2000).

    Article  CAS  PubMed  Google Scholar 

  67. Perrot, I. et al. Blocking antibodies targeting the CD39/CD73 immunosuppressive pathway unleash immune responses in combination cancer therapies. Cell Rep. 27, 2411–2425.e9 (2019).

    Article  CAS  PubMed  Google Scholar 

  68. Kuhny, M., Hochdörfer, T., Ayata, C. K., Idzko, M. & Huber, M. CD39 is a negative regulator of P2X7-mediated inflammatory cell death in mast cells. Cell Commun. Signal. 12, 40 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Clarke, J. et al. Single-cell transcriptomic analysis of tissue-resident memory T cells in human lung cancer. J. Exp. Med. 216, 2128–2149 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Bono, M. R., Fernández, D., Flores-Santibáñez, F., Rosemblatt, M. & Sauma, D. CD73 and CD39 ectonucleotidases in T cell differentiation: beyond immunosuppression. FEBS Lett. 589, 3454–3460 (2015).

    Article  CAS  PubMed  Google Scholar 

  71. Ganesan, A.-P. et al. Tissue-resident memory features are linked to the magnitude of cytotoxic T cell responses in human lung cancer. Nat. Immunol. 18, 940–950 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Pallett, L. J. et al. IL-2high tissue-resident T cells in the human liver: sentinels for hepatotropic infection. J. Exp. Med. 214, 1567–1580 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Sun, X. et al. Disordered purinergic signaling and abnormal cellular metabolism are associated with development of liver cancer in Cd39/Entpd1 null mice. Hepatology 57, 205–216 (2013).

    Article  CAS  PubMed  Google Scholar 

  74. Scholz, G. et al. Modulation of mTOR signalling triggers the formation of stem cell-like memory T cells. EBioMedicine 4, 50–61 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Li, Q. et al. A central role for mTOR kinase in homeostatic proliferation induced CD8+ T cell memory and tumour immunity. Immunity 34, 541–553 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Biasco, L. et al. In vivo tracking of T cells in humans unveils decade-long survival and activity of genetically modified T memory stem cells. Sci. Transl. Med. 7, 273ra13 (2015).

    Article  PubMed  Google Scholar 

  77. Rohaan, M. W., van den Berg, J. H., Kvistborg, P. & Haanen, J. B. A. G. Adoptive transfer of tumour-infiltrating lymphocytes in melanoma: a viable treatment option. J. Immunother. Cancer 6, 102 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  78. Seliktar-Ofir, S. et al. Selection of shared and neoantigen-reactive T cells for adoptive cell therapy based on CD137 separation. Front. Immunol. 8, 1211 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  79. Lee, H. J. et al. Expansion of tumour-infiltrating lymphocytes and their potential for application as adoptive cell transfer therapy in human breast cancer. Oncotarget 8, 113345–113359 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Hurtado, M. O. et al. Tumour infiltrating lymphocytes expanded from pediatric neuroblastoma display heterogeneity of phenotype and function. PLoS ONE 14, e0216373 (2019).

    Article  Google Scholar 

  81. Lindenberg, M. A. et al. Treatment with tumour-infiltrating lymphocytes in advanced melanoma: evaluation of early clinical implementation of an advanced therapy medicinal product. J. Immunother. 41, 413–425 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  82. Lindenberg, M. et al. Evaluating different adoption scenarios for TIL-therapy and the influence on its (early) cost-effectiveness. BMC Cancer 20, 712 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  83. Lopes, A. G., Noel, R. & Sinclair, A. Cost analysis of vein-to-vein CAR T-cell therapy: automated manufacturing and supply chain. Cell Gene Ther. Insights 6, 487–510 (2020).

    Article  Google Scholar 

  84. ten Ham, R. M. T. et al. What does cell therapy manufacturing cost? A framework and methodology to facilitate academic and other small-scale cell therapy manufacturing costings. Cytotherapy 22, 388–397 (2020).

    Article  PubMed  Google Scholar 

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Acknowledgements

We thank J. Charron and N. Simard at the Temerty Faculty of Medicine, University of Toronto for help in FACS sorting; T. Chen at the Sick Children Hospital, Toronto for help in tumour dissociation; M. Peralta at the University Health Network (UHN) for help in immunohistochemistry; W. Xiao at UHN for help in intravascular injection; J. Henderson at the Faculty of Pharmacy, University of Toronto; J. Cathcart and J. Jonkman at UHN for help in image quantitation; and anonymous technician(s) at Miltenyi Biotec for information regarding the MACSQuant Tyto system. This research was supported in part by the Canadian Institutes of Health Research (grant no. FDN-148415) and the Collaborative Health Research Projects program (CIHR/NSERC partnered). This research is part of the University of Toronto’s Medicine by Design initiative, which receives funding from the Canada First Research Excellence Fund. Z.W. was supported by an Alexander Graham Bell Canada Graduate Scholarship and a Centre for Pharmaceutical Oncology Graduate Student Scholarship.

Author information

Authors and Affiliations

  1. The Edward S. Rogers Sr Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada

    Zongjie Wang & Edward H. Sargent

  2. Institute for Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada

    Zongjie Wang & Shana O. Kelley

  3. Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada

    Sharif Ahmed, Mahmoud Labib, Hansen Wang, Xiyue Hu & Shana O. Kelley

  4. Department of Molecular Genetics, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada

    Jiarun Wei, Yuxi Yao & Jason Moffat

  5. Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada

    Jiarun Wei, Yuxi Yao & Jason Moffat

  6. Department of Biochemistry, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada

    Shana O. Kelley

  7. Department of Chemistry, Northwestern University, Evanston, IL, USA

    Shana O. Kelley

  8. Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA

    Shana O. Kelley

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  1. Zongjie Wang
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Contributions

Z.W. and S.O.K. conceived and designed the experiments. Z.W. performed the device characterization, cell isolation and in vitro phenotyping. S.A. performed the in vivo experiments. M.L. performed qPCR. H.W. performed the western blot and dot blot. X.H. assisted with cell isolation. J.W. and Y.Y. maintained the clones of OT-1 mice and isolated OT-1 CD8+ T cells. All authors discussed the results, analysed the data and contributed to the preparation and editing of the manuscript.

Corresponding author

Correspondence to Shana O. Kelley.

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Competing interests

S.O.K., Z.W. and S.A. have a filed patent application (number 63/183,350) using parts of the data reported in this article. S.O.K. has a patent titled ‘Device for capture of particles in a flow’ (US10073079) licensed to Cellular Analytics. S.O.K. received research funds from Amgen through a sponsored research agreement. J.M. is a shareholder of Century Therapeutics and Aelian Biotechnology.

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Peer review information Nature Biomedical Engineering thanks Paul Robbins and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Principle, fabrication and assembly of modular devices for configurable microfluidic cell sorting.

a, Simulated flow velocity distribution within the devices with different heights, unit of colour bar (m·s-1). Capture pockets were form nearly the middle of ‘X’-shaped structures spatially. b, Quantitation of the simulated flow velocity in different cross-sections. In a cross-section that travel through the middle of the ‘X’-shaped structures, the flow velocity in the capture pocket was extremely low (<1% of the maximal) to favour the cell capture. In a cross-section that did travel through the X, the flow velocity remains high and no capture pocket was formed. c, Representative SEM images of various printed ‘X’-shaped structures with heights up to 800 µm. All designed features were printed properly without any major defects. d, Representative pictures showing the fabricated modular devices. A red food dye was used to visualize the change of heights. All ‘X’-shaped structures were properly bonded to the cover glass, as shown in the zoom-in picture. e, Representative pictures showing the key components of configurable microfluidic sorting, including the fabricated modular chips, magnetic scaffolds, and a finished quantitative sorting setup.

Source data

Extended Data Fig. 2 Cytotoxicity and cytokine profile of different TILs through in vitro co-culture killing assay.

a, Quantitation of cytotoxic killing of TILs against B16F10OVA cells in vitro. b, Cytokine profile of the supernatant collected from in vitro killing assay. Pure B16F10-OVA is used as an internal control.

Source data

Extended Data Fig. 3 MATIC TILs are more potent in treating rapidly developing melanoma in vivo.

a, Workflow of the study comparing the therapeutic efficacy of TILs isolated by different methods, at the optimal dosage ~5 ×105 at its earliest (D5 for MATIC, D10 for MACS, D15 for FACS, for FACS, lower number (5 ×104) of TILs were injected as it fails to reach desired concentration before mouse of mice developed large tumours). b, Representative tumour size of each group on D18. c, Quantitation of tumour size and survival curve treated by the TILs isolated by MATIC, MACS and FACS (n = 5, **P < 0.01). Log-rank test was used to determine the statistical significance. d, Representative images of infiltrated T cells in solid tumours (Blue: nuclei, Red: CD8α, Brown: melanin). e, Quantitation of the number of CD8+ TILs in the tumours treated by MATIC, MACS and FACS TILs (n = 3, 2 - 3 slices per tumour). f, Tumour growth curves for each mice presented in Supplementary Fig. 14C. PFS: Progression-free survival.

Source data

Extended Data Fig. 4 Flow cytometric analysis of TILs from different CD39 populations in a MC-38 mouse model.

a, MC-38 model has about 1% CD8 + TILs within the tumours according to CD8/CD45 gating. b, Representative cytometric profile and quantitation of exhaustion markers (PD-1, TIM3, TIGIT). c, Representative cytometric profile and quantitation of intracellular cytokines (IFN, TNF, IL-2). d, Representative cytometric profile of stemness markers (TCF7, CD27). e, Western blotting confirmation of TCF7 expression. f, Representative cytometric profile of cell proliferation based on Ki67 expression. The profiles were used to generate Fig. 2f. g, Representative CD45RA/CCR7 profile of different CD39 populations. The profiles were used to generate Fig. 2g. (*p < 0.05, **p < 0.01, ***p < 0.001, unpaired t-test).

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Wang, Z., Ahmed, S., Labib, M. et al. Efficient recovery of potent tumour-infiltrating lymphocytes through quantitative immunomagnetic cell sorting. Nat Biomed Eng 6, 108–117 (2022). https://doi.org/10.1038/s41551-021-00820-y

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