基于脂质纳米颗粒的多尺度系统性免疫编程用于癌症治疗
Lipid nanoparticle-based multi-scale systemic immune programming for cancer therapy.
目前,肿瘤免疫治疗的临床适用范围受到脱靶毒性、实体瘤中的物理屏障以及个性化细胞疗法复杂制造工艺的限制。
英文原题:Beyond the Generic Tumor: Engineering Patient-Specific Immune Ecosystems for Cancer.
肿瘤免疫治疗已经改变了恶性肿瘤的治疗格局;然而,持久的临床应答仍受限于患者间异质性、肿瘤演化、抗原丢失以及免疫识别变异性。
癌症免疫治疗已改变了恶性肿瘤的治疗格局;然而,持久的临床缓解仍受限于患者间异质性、肿瘤进化、抗原丢失以及免疫识别变异性。基因组测序、新抗原发现、免疫肽组学、基于mRNA的治疗和细胞工程方面的进展,拓展了基于患者特异性肿瘤和免疫特征开发个体化免疫治疗策略的机会。本综述审视了个体化癌症免疫治疗的现状,重点关注个体化新抗原特异性疗法(iNeST)、新抗原疫苗、基于mRNA的抗原递送平台、工程化T细胞方法以及用于抗原优先级排序和免疫应答预测的计算方法。我们总结了这些方法的生物学依据、临床前和临床证据及其局限性,同时考量其转化潜力和临床可行性。我们探讨了肿瘤突变景观、新抗原免疫原性、抗原加工与呈递、HLA限制性、免疫细胞工程和计算免疫学之间的关系。我们进一步评估了临床实施的关键障碍,包括新抗原预测和验证的局限性、瘤内异质性、抗原进化和丢失、生产复杂性、可扩展性、监管要求以及前瞻性临床验证的需求。总体而言,当前证据支持个体化免疫治疗作为一种有前景的方法来提高癌症治疗的精准性,但其临床应用仍受到生物学、技术、生产、监管和临床挑战的制约。未来的进展将需要更准确且经实验验证的新抗原鉴定、改进的计算和免疫学建模、稳健的生产和质量控制流程,以及证明安全性、可行性和治疗获益的前瞻性临床研究。本综述评估当前证据,识别知识空白,并概述个体化癌症免疫治疗负责任临床开发的优先事项。
Cancer immunotherapy has transformed the treatment landscape of malignancies; however, durable clinical responses remain limited by interpatient heterogeneity, tumor evolution, antigen loss, and variability in immune recognition. Advances in genomic sequencing, neoantigen discovery, immunopeptidomics, mRNA-based therapeutics, and cellular engineering have expanded opportunities for developing individualized immunotherapeutic strategies based on patient-specific tumor and immune characteristics. This review examines the state of personalized cancer immunotherapy, with emphasis on individualized neoantigen-specific therapies (iNeST), neoantigen vaccines, mRNA-based antigen delivery platforms, engineered T-cell approaches, and computational methods for antigen prioritization and immune-response prediction. We summarize the biological rationale, preclinical and clinical evidence, and limitations of these approaches, while considering their translational potential and clinical feasibility. We examine the relationships among tumor mutational landscapes, neoantigen immunogenicity, antigen processing and presentation, HLA restriction, immune-cell engineering, and computational immunology. We further assess key barriers to clinical implementation, including limitations in neoantigen prediction and validation, intratumoral heterogeneity, antigen evolution and loss, manufacturing complexity, scalability, regulatory requirements, and the need for prospective clinical validation. Overall, current evidence supports personalized immunotherapy as a promising approach for improving the precision of cancer treatment, but its clinical application remains constrained by biological, technical, manufacturing, regulatory, and clinical challenges. Future progress will require more accurate and experimentally validated neoantigen identification, improved computational and immunologic modeling, robust manufacturing and quality-control processes, and prospective clinical studies demonstrating safety, feasibility, and therapeutic benefit. This review evaluates the current evidence, identifies knowledge gaps, and outlines priorities for the responsible clinical development of individualized cancer immunotherapy.
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