Pancreatic ductal adenocarcinoma is a lethal cancer with fewer than 7% of patients surviving past 5 years. T-cell immunity has been linked to the exceptional outcome of the few long-term survivors1,2, yet the relevant antigens remain unknown. Here we use genetic, immunohistochemical and transcriptional immunoprofiling, computational biophysics, and functional assays to identify T-cell antigens in long-term survivors of pancreatic cancer. Using whole-exome sequencing and in silico neoantigen prediction, we found that tumours with both the highest neoantigen number and the most abundant CD8+ T-cell infiltrates, but neither alone, stratified patients with the longest survival. Investigating the specific neoantigen qualities promoting T-cell activation in long-term survivors, we discovered that these individuals were enriched in neoantigen qualities defined by a fitness model, and neoantigens in the tumour antigen MUC16 (also known as CA125). A neoantigen quality fitness model conferring greater immunogenicity to neoantigens with differential presentation and homology to infectious disease-derived peptides identified long-term survivors in two independent datasets, whereas a neoantigen quantity model ascribing greater immunogenicity to increasing neoantigen number alone did not. We detected intratumoural and lasting circulating T-cell reactivity to both high-quality and MUC16 neoantigens in long-term survivors of pancreatic cancer, including clones with specificity to both high-quality neoantigens and predicted cross-reactive microbial epitopes, consistent with neoantigen molecular mimicry. Notably, we observed selective loss of high-quality and MUC16 neoantigenic clones on metastatic progression, suggesting neoantigen immunoediting. Our results identify neoantigens with unique qualities as T-cell targets in pancreatic ductal adenocarcinoma. More broadly, we identify neoantigen quality as a biomarker for immunogenic tumours that may guide the application of immunotherapies.
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Gene Expression Omnibus
We thank A. Rudensky, A. Snyder-Charan, C. Callan, Y. Elhanati, Z. Sethna, J. Leung, J. Ruan, C. Crabtree, P. Garcia, M. Singh, A. McNeil, D. Haviland, J. Melchor and J. Tsoi for discussions, technical and editorial assistance. This work was supported by National Institutes of Health (NIH) R01DK097087-01 Pancreatic Cancer Action Network-AACR Research Acceleration Network Grant (S.D.L.), P30 CA008748-50S4 administrative supplement (S.D.L., V.P.B.), Suzanne Cohn Simon Pancreatic Cancer Research Fund (S.D.L.), National Cancer Institute K12CA184746-01A1 (V.P.B.), Damon Runyon Clinical Investigator Award (V.P.B.), Stand Up to Cancer, Lustgarden Foundation, and the National Science Foundation (J.D.W., B.D.G.), the V Foundation (V.P.B., J.A.M., J.D.W., B.D.G.), the Phil A. Sharp Innovation Award (B.D.G., J.D.W.), Swim Across America, and the Ludwig Institute for Cancer Research (J.D.W., T.M.), and the Parker Institute for Cancer Immunotherapy (D.K.W., C.I.O.C., J.D.W., T.M.). Services by the Integrated Genomics Core were funded by the National Cancer Institute Cancer Center Support Grant (P30 CA08748), Cycle for Survival, and the Marie-Josée and Henry R. Kravis Center for Molecular Oncology.
Extended data figures
This folder contains the source code for the neoantigen quality assessment performed in this manuscript. A text file of Supplementary Table 1 is included to enable code execution.
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