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.
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).
Putative neoantigens predicted with NetMHC 3.4 in all 3 cohorts.
Overall survival data for patients in the 3 cohorts.
Reconstructed tumour clones from the highest scoring tree with PhyloWGS and their neoantigens with computed fitness cost.
Cytolytic score for a subset of 40 Van Allen et al. samples used in Extended Data Fig. 7