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A homing system targets therapeutic T cells to brain cancer

This article was retracted on 20 February 2019

This article has been updated

Abstract

Successful T cell immunotherapy for brain cancer requires that the T cells can access tumour tissues, but this has been difficult to achieve. Here we show that, in contrast to inflammatory brain diseases such as multiple sclerosis, where endothelial cells upregulate ICAM1 and VCAM1 to guide the extravasation of pro-inflammatory cells, cancer endothelium downregulates these molecules to evade immune recognition. By contrast, we found that cancer endothelium upregulates activated leukocyte cell adhesion molecule (ALCAM), which allowed us to overcome this immune-evasion mechanism by creating an ALCAM-restricted homing system (HS). We re-engineered the natural ligand of ALCAM, CD6, in a manner that triggers initial anchorage of T cells to ALCAM and conditionally mediates a secondary wave of adhesion by sensitizing T cells to low-level ICAM1 on the cancer endothelium, thereby creating the adhesion forces necessary to capture T cells from the bloodstream. Cytotoxic HS T cells robustly infiltrated brain cancers after intravenous injection and exhibited potent antitumour activity. We have therefore developed a molecule that targets the delivery of T cells to brain cancer.

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Fig. 1: CAM expression and permeability of cancerous endothelium.
Fig. 2: Rational engineering of the homing system.
Fig. 3: Signalling events downstream of HS molecules.
Fig. 4: Cytoskeletal changes mediated by HS signalling.
Fig. 5: Homing of HS T cells to brain tumours.
Fig. 6: Anti-tumour activity of cytotoxic HS T cells.

Data availability

All relevant data are included in the manuscript linked as source data; more details are available from the corresponding author on reasonable request

Change history

  • 25 October 2018

    Editor’s Note: We would like to alert readers that the reliability of data presented in this manuscript has been the subject of criticisms, which we are currently considering. We will publish an update once our investigation is complete.

  • 20 February 2019

    This Article has been retracted; see accompanying Retraction.

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Acknowledgements

We thank M. K. Brenner and C. Gillespie for scientific advice and linguistic editing, respectively, and S. Roberge and M. Duquette for technical assistance. The D3 antibody was a gift from M. Brown. This work was funded by an SU2C-St. Baldrick’s Pediatric Dream Team Translational Research Grant (SU2C-AACR-DT1113; NA/PS/MDT). SU2C is a program of the Entertainment Industry Foundation administered by the American Association for Cancer Research. Also funded by Alex’s Lemonade Stand, NIH-T32HL092332 (K.F./T.B.; H. Heslop), R01AI067946 (J.S.O.), T32GM08812 (K.F./T.B.; M. Estes), DK56338, CA125123, and 1S10OD020151-01, CPRIT (RP150578), the Dan L. Duncan CCC and P01-CA080124 (R.K.J./D.F.); R35-CA197743, K08-GM123261 (F.L.) and P50-CA165962 (R.K.J.). This content does not necessarily represent the official views of the funding agencies, the Department of Veterans Affairs or the U.S. Government.

Reviewer information

Nature thanks M. Platten and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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Affiliations

Authors

Contributions

N.A. conceived the main study idea, and with H.S. conceived and implemented the study details. N.A., K.F. and A.P. designed HS molecules. H.S., M.D.T., S.P.M., P.S., S.E.-N., M.H., F.S., J.D. and N.A. performed the CAM studies. M.L.B. performed in silico modelling. F.L. and H.S. designed and implemented microfluidic experiments. M.Ma., T.B., S.K.J. and A.Z.G. performed molecular testing. H.S., F.S., J.D., M.Mu. and J.S.O. designed and performed the subcellular imaging experiments. J.R., H.S., V.S.S., A.S., T.S., S.P.M., S.-H.H., D.F., S.K., R.K.J. and N.A. implemented the animal microscopy and experiments. All authors gave final approval.

Corresponding author

Correspondence to Nabil Ahmed.

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The authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 Analysis of CAM expression in primary brain tumours.

a, High-throughput IFC analysis of the endothelial adhesion molecules ICAM1, VCAM1, and ALCAM in 93 primary GBM, 25 primary medulloblastoma and 5 normal brain samples. MATLAB segmentation and masking analysis algorithm of the co-immunofluorescence (co-IFC) of ICAM1 or VCAM (acquired on 647 channel), CD31 (acquired on 594 channel) and ALCAM (acquired on 488 channel), and DAPI (acquired on blue/cyan channel). b, Isolation and characterization of pTECs. Flow cytometry sorting gating strategy of pTECs from freshly excised glioblastoma (GBM; n = 5) based on CD31 positivity. Isolated GBM endothelial cells also expressed the endothelial markers VE-cadherin, von Willebrand Factor (vWF) and ALCAM. Isotype shown in lighter grey and test shown in darker grey in individual histograms. n = 5 surgical samples each interrogated at least twice. At least 100,000 events were acquired per condition.

Source data

Extended Data Fig. 2 ALCAM expression in a panel of human and mouse endothelial cells and their reactivity to inflammatory and cancerous conditioning.

a, Western blot for ALCAM in a panel of human and mouse endothelial cell lines: pTECs, HBMECs, 1ry BMECs, 1ry PVECs, HUVECs, HMVEC-Ls, bEnd.3 (mouse brain tumour EC) and 2-H11 (mouse SV40-transformed axillary lymph node vascular endothelium). Left, basal ALCAM expression except in tumour endothelial cells (pTEC and 2-H11). Right, induction of ALCAMs in all endothelial cells after incubation with TNFα for 6 h. b, Expression of ALCAM at baseline and after 6 h of conditioning in GBM supernatant, TGFβ or IL6. Only tumour endothelial cells expressed ALCAM at baseline while normal endothelial cells did not. c, IFC for ALCAM in 5 × 104 pTECs and HBMECs in the in vitro BBB model at baseline and after culture in GBM supernatant. Scale bars, 50 μm. d, Differential expression of key adhesion molecules at baseline and under the influence of cancer and inflammation in pTECs and HBMECs. Flow cytometry dot plots detailing baseline expression of ALCAM, VCAM1 and ICAM1 on 1 × 104 pTECs and HBMECs and conditioned expression after culture in GBM supernatant, TGFβ or IL6. eh, Expression of adhesion molecules at baseline and under the influence of cancer and inflammation in pTECs (n = 4) acquired from surgically resected samples (pTEC #1 is shown in Fig. 1g).

Source data

Extended Data Fig. 3 In silico design of the prototype and derivative HS molecules, their forced expression and detection on T cells, and studies of their in vitro dynamic interactions with endothelial cells under shear stress.

a, The potential interaction between ALCAM V1 (grey ribbon) and CD6 from computational docking. D1 of CD6 is coloured blue, D2 green and D3 orange. b, Details of the potential interaction interface between ALCAM V1 (grey ribbon) and CD6 D3 (orange ribbon). A rendering of the electrostatic surface of ALCAM V1 (grey ribbon) with the D3 domain of CD6 (orange ribbon) in the same orientation. Potential interacting residues are highlighted in the models and in a diagram generated from PDBe PISA and PDBSum (c). A small region of positively charged residues in ALCAM V1 appears to interact with a negatively charged patch of residues on CD6 D3. d, Structure of the prototype HS molecule. e, HS multimers 3HS and 5HS. f, HS molecules with non-signalling endodomains, HSΔ, 3HSΔ and 5HSΔ. g, Strategy used for surface detection of the HS exodomain using a D3-specific antibody and specific binding of the HS exodomain to soluble ALCAM. h, Flow cytometry confirming HS surface expression (using D3 monoclonal antibody) on T cells. i, Design of the HS–ALCAM PLA experiment. j, Digital rendition of PLA using ImageTool. The ALCAM probe (–) binds to the D3 probe (+) to trigger the PCR generating the red fluorescent signal that is quantified as total signal per region (TSR) in Fig. 2f. k, l, Dynamic microfluidic studies showing still image from Supplementary Video 1 of Bioflux channels with non-transduced control (NT) T cells (top) versus 1 × 106 HS T cells interrogated under shear force over an ALCAM-expressing endothelium (k), and still image from MJtracker demonstrating various T cells under interrogation for various TEM dynamic measures, the standard grid used and the equation used for calculations (l). m, Dynamic adhesion of T cells to endothelial cells per field of view. n, Average dynamic rolling velocity against time; *P < 0.05, **P < 0.01, ***P < 0.001. Two-way ANOVA with Tukey’s test for multiple-comparisons (compared to NT cells).

Source data

Extended Data Fig. 4 Functional effects of elimination of ALCAM on endothelial cells and knockout of human ALCAM using CRISPR–Cas9 technology and its effect on T cell migration across the BBB.

a, Flow cytometry of ALCAM expression on 1 × 106 wild-type pTECs at base-line, after TGFβ induction of ALCAM and after being transfected with 25 nM ALCAM siRNA for 48 h to knock down (KD) ALCAM. Transmigration assay using pTECs to simulate a cancerous BBB showing percentage of migrant T cells compared with ALCAM-KD is shown in Fig. 2k. b, Highest three scoring guide RNA designs (sgRNA-44, sgRNA-45 and sgRNA-49) as seen on the SnapGene software intended to disrupt ALCAM exons for the extracellular and transmembrane moiety. c, d, CD5-KO (c) and CD19-KO (d) were used as positive and negative experimental controls, respectively. e, Flow cytometry of ALCAM expression on wild-type HUVECs and HUVEC ALCAM-KO using CRISPR–Cas9 (using the guide sgRNA-45) assessed at baseline and after TGFβ incubation. Isotype was used as control. f, Transmigration assay showing percentage of 2 × 106 migrating T cells on wild-type HUVECs before and after ALCAM induction compared to ALCAM-KO HUVECs. Both experiments were done at baseline then after ALCAM induction was confirmed. Data shown as mean ± s.d. (n ≥ 3 experiments; donor T cells n = 3), **P < 0.01, ***P < 0.001. Tukey’s test (compared to wild-type pTECs). g, RT–PCR analysis of representative of 1 × 106 ALCAM-KO HS T cells in comparison to wild-type normal T cells. GAPDH was used as an internal control. h, Flow cytometry showing >90% knockout efficiency of the three sgRNAs on 1 × 105 T cells in comparison to wild-type normal T cells; CRISPR–Cas9 only and isotype were used as experimental controls. i, Sorted ALCAM-negative KO T cells were then successfully transduced with the six HS constructs. j, Transmigration assay showing percentage of 2 × 105 migrating T cells on a cBBB model to compare wild-type with ALCAM-KO T cells in four conditions (ALCAM, ALCAM+ conditioned with TGFβ, after blocking ALCAM, after washing the blocking away). Data in f and j are shown as mean ± s.d. (n ≥ 3 experiments; donors n = 3), *P < 0.05, **P < 0.01. Tukey’s test (compared to ALCAM+ T cells).

Source data

Extended Data Fig. 5 Flow cytometry quantification of nodes downstream of CD6 signalling endodomains and high-throughput analysis of super-resolution imaging using deconvolution microscopy.

ac, Quantification of the flow cytometric data for LFA-1 open configuration (a), pZap70 (b) and talin (c) before (solid bars) and after (dotted bars) TWM of 1 × 105 T cells. ***P < 0.001. d, Characterization of cellular features of migrant T cells using collective quantification of actin MFI, focal adhesions at HS–ALCAM interface, area of spreading, and podosynapse formation by high-throughput microscopy in three donors. n = 200–800 cells. e, Box plot summary representing single-cell data distributions of all replicates between all three donors expressing HS versus NT controls. Centre lines, data median. Boxes, middle quartiles. Whiskers, upper and lower limits.

Source data

Extended Data Fig. 6 Assessment of TILs in GBM explants.

a, Flow cytometry of 1 × 104 TILs; all HS T cell designs compared with normal T cells gated on CD3+CD45+ then D3+ fractions in GBM explants 24 h after intravenous infusion. Representative plots shown. n = 5 animals per group. b, Cranial window on a live mouse bearing U87-GBM tumour (black arrow, right).

Extended Data Fig. 7 Analysis of T cell infiltrates in vital organs and normal brain after infusion of HS T cells.

a, CD3 immunohistochemistry (IHC) staining of normal vital tissues from animals receiving HS T cells or NT control cells. n = 3 mice per group. Scale bars, 40 μm. b, IHC showing HS T cell infiltrate in micro-dissected GBM xenograft. Scoring of CD3+ DAB signal was analysed using IHC-Profiler plugin in ImageJ. Respective image analysis output and the score assigned using IHC-Profiler are also shown for each image. Total percentage of CD3+ DAB signal was more 66% in all mouse brain with HS T cells (scores 3–4) and percentages in control mice were less than 20% (scores 0–1). Scale bars, 50 μm. n = 3 mice per group.

Extended Data Fig. 8 Characterization of therapeutic T cells after transmigration through an in vitro BBB model.

a, Flow cytometry assessing HER2-CAR and HS molecule expression in HS HER2-CAR T cells. bd, 1 × 105 T cells were collected from the bottom chamber after transmigration on ALCAM-expressing endothelium and analysed for CD45RO and CCR7 to assess their centrality (b), expression of the exhaustion markers PD-1 (black), TIM-3 (red) and LAG3 (orange) (before transmigration is shown in grey) (c), and proliferative capacity before (red) and after (blue) transmigration, using efLuor 670 (d).

Extended Data Fig. 9 Analysis of TILs isolated from tumour xenografts and normal brain for HER2-CAR HS T cells.

a, Flow cytometry of TILs isolated from orthotopic tumour xenografts 24 h after intravenous injection of HS T cell products, HER2-CAR T cells and NT control T cells. Xenografts were micro-dissected and TILs were isolated and enriched on a percoll/ficoll gradient. Cells were gated on D3+ subset inside a gate of D3+CD45+. A subset of HER2-CAR inside a gate of CD3+CD45+D3+ was used to detect HER2-CAR HS T cells specifically. n = 5 mice per group, representative data shown. b, Flow cytometry following the same gating strategy indicating the absence of HS T cells in the contralateral lobe to the tumour xenograft; data representative of three mice.

Extended Data Fig. 10 Overexpression of full-length native CD6 and its phenotypic and functional effects on T cells.

a, Cloning strategy of native CD6 in an SFG retroviral backbone. b, Flow cytometry showing the transduction of 1 × 105 native CD6 relative to HS constructs on T cells. c, Flow cytometry of the activation marker CD69 on day 8 after transduction without additional stimulation. d, Flow cytometry of the activation and exhaustion marker PD-1 stained with PD-1 PerCP on day 8 transduction at basal level without additional stimulation. e, Expansion plot of T cells expressing the native CD6 relative to NT and various HS T cells; cells were grown in IL-7/IL-15 and collected at day 2 and day 12 post transduction. f, Transmigration of 2 × 105 T cells through a cancerous BBB model showing the percentage of migrant T cells expressing native CD6 relative to various HS T cells, and the response to blocking ALCAM and its restitution. Data shown as mean ± s.d. (n ≥ 3 experiments; donor T cells, n = 3) ***P < 0.001 compared to migration of CD6 through ALCAM+ BBB. ANOVA with Tukeys post-hoc analysis.

Source data

Supplementary information

Supplementary Methods

This file contains Supplementary Methods and additional references.

Reporting Summary

Supplementary Video 1

Microfluidics studies of HS and NT T-cells.

Supplementary Video 2

Representative flowing and adherence of 5HS T-cells in the brain tumour vascular bed.

Supplementary Video 3

Representative rolling and extravasation of 5HS T-cells in the brain tumour vascular bed.

Supplementary Video 4

Representative flowing and adherence of NT T-cells in the brain tumour vascular bed.

Supplementary Video 5

Representative rolling of NT T-cells in the brain tumour vascular bed.

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Samaha, H., Pignata, A., Fousek, K. et al. A homing system targets therapeutic T cells to brain cancer. Nature 561, 331–337 (2018). https://doi.org/10.1038/s41586-018-0499-y

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Keywords

  • Activated Leukocyte Cell Adhesion Molecule (ALCAM)
  • Cancer Endothelium
  • ALCAM Expression
  • Human Brain Microvascular Endothelial Cells (HBMECs)
  • FlowJo Data Analysis Software

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