J Clin Invest. 2019 Mar 5;129(5):2056-2070. doi: 10.1172/JCI99538. Print 2019 May 1.
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 one of the major obstacles to using personalized neoantigen-based cancer immunotherapy.
Two different pipelines of neoantigens identification were established in this study: (1) 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 de novo synthesized. (2) 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 six patients.
Immunogenic neo-epitopes were recognized by autologous T cells in 3 of 4 patients who utilized the de novo synthesis mode and in 6 of 13 patients who performed shared neoantigen peptide library, respectively. 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 four patients achieved the prolonged stabilization of disease with a median PFS of 8.6 months.
The current study provided feasible pipelines for neoantigen identification. Implementing these strategies to individually tailor neoantigens could facilitate the neoantigen-based translational immunotherapy research.TRIAL REGSITRATION. ChiCTR.org ChiCTR-OIC-16010092, ChiCTR-OIC-17011275, ChiCTR-OIC-17011913; ClinicalTrials.gov NCT03171220.
This work was funded by grants from the National Key Research and Development Program of China (Grant No. 2017YFC1308900), the National Major Projects for "Major New Drugs Innovation and Development" (Grant No.2018ZX09301048-003), the National Natural Science Foundation of China (Grant No. 81672367, 81572329, 81572601), and the Key Research and Development Program of Jiangsu Province (No. BE2017607).
最近的基因组学和生物信息学技术进步使得剖析针对肿瘤特异性突变的个体化新抗原的免疫反应成为可能。然而，及时有效地鉴定新抗原仍然是使用基于个体化新抗原的癌症免疫治疗的主要障碍之一。
本研究建立了两种不同的新抗原鉴定管道：（1）对难治性实体瘤患者进行临床级靶向测序，并从头合成具有高变异等位基因频率和预测高 HLA 结合亲和力的突变肽。（2）构建常见实体瘤的共享新抗原肽文库，并将患者的热点突变与新抗原肽文库相匹配。通过体外回忆记忆 T 细胞反应鉴定候选新表位。随后，在 6 名患者中生成负载新抗原的树突状细胞疫苗和新抗原反应性 T 细胞，进行个体化免疫治疗。
在分别采用从头合成模式的 4 名患者中的 3 名和采用共享新抗原肽文库的 13 名患者中的 6 名中，自体 T 细胞识别出免疫原性新表位。一名转移性胸腺瘤患者在治疗后 29 个月以上获得完全和持久缓解。另一名转移性胰腺癌患者出现免疫相关部分缓解。其余 4 名患者的疾病稳定时间延长，中位 PFS 为 8.6 个月。
本研究提供了可行的新抗原鉴定管道。实施这些策略来个体化定制新抗原，可以促进基于新抗原的转化免疫治疗研究。
ChiCTR.org ChiCTR-OIC-16010092、ChiCTR-OIC-17011275、ChiCTR-OIC-17011913；ClinicalTrials.gov NCT03171220。
本工作得到国家重点研发计划（项目编号：2017YFC1308900）、国家重大新药创制专项（项目编号：2018ZX09301048-003）、国家自然科学基金（项目编号：81672367、81572329、81572601）和江苏省重点研发计划（项目编号：BE2017607）的资助。
