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Multiple antibodies targeting tumor-specific mutations redirect immune cells to inhibit tumor growth and increase survival in experimental animal models

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Abstract

Background

T cell therapy for cancer involves genetic introduction of a target-binding feature into autologous T cells, ex vivo expansion and single large bolus administration back to the patient. These reprogrammed T cells can be highly effective in killing cells, but tumor heterogeneity results in regrowth of cells that do not sufficiently express the single antigen being targeted. We describe a cell-based therapy that simultaneously targets multiple tumor-specific antigens.

Methods

High-affinity polyclonal rabbit antibodies were generated against nine different surface-related tumor-specific mutations on B16F10 cells. Unsorted splenic effector cells from syngeneic mice were incubated with a cocktail of the nine anti-B16F10 antibodies. These ‘armed’ effector cells were used to treat mice previously inoculated with B16F10 melanoma cells.

Results

The cocktail of nine antibodies resulted in dense homogeneous binding to histological sections of B16F10 cells. Five treatments with the armed effector cells and PD1 inhibition inhibited tumor growth and improved survival. Shortening the interval of the five treatments from every three days to every day increased survival. Arming effector cells with the four antibodies showing best binding to B16F10 cells even further increased survival.

Conclusions

This study demonstrates that ex vivo arming a mixed population of immune effector cells with antibodies targeting multiple tumor-specific mutated proteins in conjunction with PD1 inhibition delayed tumor growth and prolonged survival in mice inoculated with an aggressive melanoma. A remarkably low total antibody dose of less than 5 µg was sufficient to accomplish tumor inhibition. Scaling up to clinical level may be feasible.

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Acknowledgements

This work was supported by the SD Ireland Cancer Research Fund, Cast Off Chemo! Foundation, the Department of Surgery at the University of Vermont Larner College of Medicine internal grant, and the Beat Neuroblastoma Foundation. This work was also supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under Grant Number P20GM103449. Flow cytometry data was obtained at the Harry Hood Bassett Flow Cytometry and Cell Sorting Facility at the University of Vermont Larner College of Medicine.

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Authors and Affiliations

  1. Department of Surgery and University of Vermont Cancer Center, University of Vermont Larner College of Medicine, Burlington, VT, USA

    G. S. Shukla, S. C. Pero, Y. -J. Sun, L. Mei & D. N. Krag

  2. Vermont Genetics Network, University of Vermont, Burlington, VT, USA

    F. Zhang

  3. Department of Biology, University of Vermont, Burlington, VT, USA

    F. Zhang

  4. Pediatric Oncology Research, Helen DeVos Children’s Hospital, Grand Rapids, MI, USA

    G. Sholler

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  1. G. S. Shukla
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  2. S. C. Pero
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  3. Y. -J. Sun
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  4. L. Mei
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  5. F. Zhang
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  6. G. Sholler
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  7. D. N. Krag
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Corresponding author

Correspondence to D. N. Krag.

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Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval and ethical standards

All animal procedures used in the present study were approved by the UVM IACUC (Protocol # 18-002).

Animal source

Mice were obtained from the Jackson Laboratory (Bar Harbor, ME) in the present study.

Cell line authentication

We utilized confirmed sequence data of B16F10 mouse melanoma tumor cell line7 and selected multiple cell surface-related mutated proteins with a single amino acid substitution.

Informed consent

Informed consent is not applicable to this manuscript. We only report on mice and did refer to having the protocol correctly approved. The human sequence information comes from public databases.

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Shukla, G.S., Pero, S.C., Sun, Y.J. et al. Multiple antibodies targeting tumor-specific mutations redirect immune cells to inhibit tumor growth and increase survival in experimental animal models. Clin Transl Oncol 22, 1094–1104 (2020). https://doi.org/10.1007/s12094-019-02235-3

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  • DOI: https://doi.org/10.1007/s12094-019-02235-3

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