Letter

A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy

Received:
Accepted:
Published online:

Abstract

Checkpoint blockade immunotherapies enable the host immune system to recognize and destroy tumour cells1. Their clinical activity has been correlated with activated T-cell recognition of neoantigens, which are tumour-specific, mutated peptides presented on the surface of cancer cells2,3. Here we present a fitness model for tumours based on immune interactions of neoantigens that predicts response to immunotherapy. Two main factors determine neoantigen fitness: the likelihood of neoantigen presentation by the major histocompatibility complex (MHC) and subsequent recognition by T cells. We estimate these components using the relative MHC binding affinity of each neoantigen to its wild type and a nonlinear dependence on sequence similarity of neoantigens to known antigens. To describe the evolution of a heterogeneous tumour, we evaluate its fitness as a weighted effect of dominant neoantigens in the subclones of the tumour. Our model predicts survival in anti-CTLA-4-treated patients with melanoma4,5 and anti-PD-1-treated patients with lung cancer6. Importantly, low-fitness neoantigens identified by our method may be leveraged for developing novel immunotherapies. By using an immune fitness model to study immunotherapy, we reveal broad similarities between the evolution of tumours and rapidly evolving pathogens7,8,9.

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Acknowledgements

We thank N. Bhardwaj, C. Callan, S. Cocco, Y. Elhanati, J. Finnegan, D. Krotov, M. Lässig, S. Leach, S. Leibler, A. Libchaber, R. Monasson, A. Nourmohammad, V. Roudko, Z. Sethna, A. Snyder-Charen, P. Sulc, D. T. Ting and the members of the Chan, Greenbaum and Wolchok laboratories for discussions; M. Lässig for suggestions regarding the biophysical model and comments on the manuscript; A. Snyder-Charen and D. T. Ting for their reading of the manuscript. Research was supported by a Stand Up To Cancer–American Cancer Society Lung Cancer Dream Team Translational Research Grant (SU2C-AACR-DT17-15) (M.D.H., T.M., T.A.C. and J.D.W.), a Stand Up To Cancer–National Science Foundation–Lustgarten Foundation Convergence Dream Team Grant (V.P.B., A.S., J.D.W., and B.D.G.), a Phillip A. Sharp Innovation in Collaboration Award from Stand Up To Cancer (B.D.G. and J.D.W.), the Janssen Research & Development LLC (M.Ł.), the STARR Cancer Consortium (T.A.C.), the Pershing Square Sohn Cancer Research Alliance (T.A.C.), the NIH R01 CA205426 (N.A.R. and T.A.C.), the V Foundation (V.P.B., A.S., J.D.W. and B.D.G), the Lustgarten Foundation (V.P.B., A.S., J.D.W. and B.D.G.), the National Science Foundation (NSF) 1545935 (B.D.G. and J.D.W.), the Swim Across America (V.P.B., T.M. and J.D.W.), Ludwig Institute for Cancer Research, the Parker Institute for Cancer Immunotherapy, the NCI K12 Paul Calabresi Career Development Award for Clinical Oncology K12CA184746-01A1 (V.P.B.). The work was also supported in part by the MSKCC Core Grant (P30 CA008748).

Author information

Affiliations

  1. The Simons Center for Systems Biology, Institute for Advanced Study, Princeton, New Jersey, USA

    • Marta Łuksza
    •  & Arnold J. Levine
  2. Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA

    • Nadeem Riaz
    •  & Timothy A. Chan
  3. Immunogenomics and Precision Oncology Platform, Memorial Sloan Kettering Cancer Center, New York, New York, USA

    • Nadeem Riaz
    • , Vladimir Makarov
    •  & Timothy A. Chan
  4. Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Vladimir Makarov
    •  & Timothy A. Chan
  5. Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Vinod P. Balachandran
  6. David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Vinod P. Balachandran
  7. Parker Institute for Cancer Immunotherapy, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Vinod P. Balachandran
    • , Matthew D. Hellmann
    • , Taha Merghoub
    • , Timothy A. Chan
    •  & Jedd D. Wolchok
  8. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Matthew D. Hellmann
    •  & Jedd D. Wolchok
  9. Department of Medicine, Weill Cornell Medical College, Cornell University, New York, New York, USA.

    • Matthew D. Hellmann
  10. Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Alexander Solovyov
    •  & Benjamin D. Greenbaum
  11. Department of Medicine, Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, New York, USA

    • Alexander Solovyov
    •  & Benjamin D. Greenbaum
  12. Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Alexander Solovyov
    •  & Benjamin D. Greenbaum
  13. Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Alexander Solovyov
    •  & Benjamin D. Greenbaum
  14. Department of Medicine, Columbia University Medical Center, New York, New York, USA.

    • Naiyer A. Rizvi
  15. Ludwig Collaborative and Swim Across America Laboratory, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Taha Merghoub
    •  & Jedd D. Wolchok
  16. Melanoma and Immunotherapeutics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA.

    • Taha Merghoub
    •  & Jedd D. Wolchok

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Contributions

M.Ł. and B.D.G. designed the mathematical model, analysed data and wrote the manuscript with critical comments from all the authors. N.R., V.M., V.P.B., M.D.H., A.S., N.A.R., T.M., A.J.L., T.A.C. and J.D.W. contributed to data acquisition and analysis. M.Ł., T.A.C., J.D.W. and B.D.G. contributed to study conception and design. M.Ł., N.R., V.M., V.P.B., M.D.H., A.S., N.A.R., T.M., A.J.L., T.A.C., J.D.W. and B.D.G. interpreted the data and provided a critical reading of the manuscript.

Competing interests

M.Ł. has consulted for Merck. V.P.B. has received research funding from Bristol-Myers Squibb. A.J.L. is on the board of directors for Adaptive Biotechnologies and has consulted for Jansen Pharmaceuticals and Merck. T.A.C. is a co-founder of Gritstone Oncology and holds equity. T.A.C. receives grant funding from Bristol Myers Squibb. N.A.R is co-founder and shareholder of Gritstone Oncology. M.D.H. has consulted for Genentech, BMS, Merck, AstraZeneca, Janssen and Novartis. B.D.G. has consulted for Merck.

Corresponding authors

Correspondence to Marta Łuksza or Benjamin D. Greenbaum.

Reviewer Information Nature thanks R. Simon, S. van den Burg and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Supplementary information

PDF files

  1. 1.

    Life Sciences Reporting Summary

  2. 2.

    Supplementary Information

    This file contains Supplementary Text and Data and additional references.

Zip files

  1. 1.

    Supplementary Data 1

    Mutations in tumour samples in all 3 cohorts.

  2. 2.

    Supplementary Data 5

    IEDB sequences validated by positive T-cell assays (positive) and IEDB sequences not validated by positive T-cell assays (negative).

  3. 3.

    Supplementary Data 7

    Source code example to compute neoantigen fitness cost.

Excel files

  1. 1.

    Supplementary Data 2

    Putative neoantigens predicted with NetMHC 3.4 in all 3 cohorts.

  2. 2.

    Supplementary Data 3

    Overall survival data for patients in the 3 cohorts.

  3. 3.

    Supplementary Data 4

    Reconstructed tumour clones from the highest scoring tree with PhyloWGS and their neoantigens with computed fitness cost.

  4. 4.

    Supplementary Data 6

    Cytolytic score for a subset of 40 Van Allen et al. samples used in Extended Data Fig. 7