Neoantigen identification strategies enable personalized immunotherapy in refractory solid tumors

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Abstract

BACKGROUND. Recent genomic and bioinformatic technological advances have made it possible to dissect the immune response to personalized neoantigens encoded by tumor-specific mutations. However, timely and efficient identification of neoantigens is still a major obstacle to personalized neoantigen-based cancer immunotherapy. METHODS. Two different pipelines of neoantigen identification were established in this study: (a) Clinical-grade targeted sequencing was performed in patients with refractory solid tumor, and mutant peptides with high variant allele frequency and predicted high HLA-binding affinity were synthesized de novo. (b) An inventory-shared neoantigen peptide library of common solid tumors was constructed, and patients’ hotspot mutations were matched to the neoantigen peptide library. The candidate neoepitopes were identified by recalling memory T cell responses in vitro. Subsequently, neoantigen-loaded dendritic cell vaccines and neoantigen-reactive T cells were generated for personalized immunotherapy in 6 patients. RESULTS. Immunogenic neoepitopes were recognized by autologous T cells in 3 of 4 patients who used the de novo synthesis mode and in 6 of 13 patients who used the shared neoantigen peptide library. A metastatic thymoma patient achieved a complete and durable response beyond 29 months after treatment. Immune-related partial response was observed in another patient with metastatic pancreatic cancer. The remaining 4 patients achieved prolonged stabilization of disease with a median progression-free survival of 8.6 months. CONCLUSION. The current study provides feasible pipelines for neoantigen identification. Implementing these strategies to individually tailor neoantigens could facilitate neoantigen-based translational immunotherapy research. TRIAL REGISTRATION. ChiCTR.org ChiCTR-OIC-16010092, ChiCTR-OIC-17011275, ChiCTR-OIC-17011913; ClinicalTrials.gov NCT03171220. FUNDING. This work was funded by grants from the National Key Research and Development Program of China (2017YFC1308900), the National Major Projects for “Major New Drugs Innovation and Development” (2018ZX09301048-003), the National Natural Science Foundation of China (81672367, 81572329, 81572601), and the Key Research and Development Program of Jiangsu Province (BE2017607).

Authors

Fangjun Chen, Zhengyun Zou, Juan Du, Shu Su, Jie Shao, Fanyan Meng, Ju Yang, Qiuping Xu, Naiqing Ding, Yang Yang, Qin Liu, Qin Wang, Zhichen Sun, Shujuan Zhou, Shiyao Du, Jia Wei, Baorui Liu