细胞因子网络作为跨癌症免疫治疗平台反应、耐药性和毒性的决定因素

摘要(中文译文)

癌症免疫治疗已显著改善了实体瘤和血液系统恶性肿瘤的治疗格局；然而，持久的临床获益仍受限于原发性和获得性治疗耐药、免疫相关毒性以及患者间显著的异质性。尽管细胞因子、趋化因子和生长因子作为预测性和预后性生物标志物已被广泛研究，但其在动态免疫网络中的协同功能仍未充分整合到当前的转化和临床框架中。本综述旨在批判性评估支持细胞因子网络动态的新兴证据，并引入适应性细胞因子回路（adaptive cytokine circuitries）这一概念框架，以理解相互连接的细胞因子信号如何在免疫检查点阻断、嵌合抗原受体T细胞治疗、T细胞受体工程化疗法、双特异性抗体及新兴细胞免疫治疗中调控治疗反应、耐药和毒性。现有证据表明，细胞因子相互作用通过空间和时间上组织化的信号网络发挥作用，影响T细胞功能状态、髓系细胞重编程、免疫逃逸和组织特异性炎症反应，同时凸显了重要的生物学不确定性以及前瞻性临床验证的必要性。本综述进一步探讨了纵向免疫监测、多重细胞因子谱分析、空间和单细胞多组学技术、计算网络重建以及生物标志物指导的患者分层在精准免疫治疗中的转化潜力。总体而言，现有证据支持从静态细胞因子测量向动态细胞因子网络分析的转变，同时强调了在细胞因子回路指导的策略能够在精准免疫肿瘤学中实施之前必须解决的科学和临床挑战。

Abstract

Cancer immunotherapy has substantially improved the management of solid tumors and hematologic malignancies; however, durable clinical benefit remains limited by primary and acquired therapeutic resistance, immune-related toxicities, and considerable interpatient heterogeneity. Although cytokines, chemokines, and growth factors have been extensively investigated as predictive and prognostic biomarkers, their coordinated functions within dynamic immune networks remain insufficiently integrated into current translational and clinical frameworks. The purpose of this review is to critically evaluate emerging evidence supporting cytokine network dynamics and to introduce adaptive cytokine circuitries as a conceptual framework for understanding how interconnected cytokine signaling regulates therapeutic response, resistance, and toxicity across immune checkpoint blockade, chimeric antigen receptor T-cell therapy, T-cell receptor-engineered therapies, bispecific antibodies, and emerging cellular immunotherapies. Current evidence indicates that cytokine interactions operate through spatially and temporally organized signaling networks that influence T-cell functional states, myeloid cell reprogramming, immune escape, and tissue-specific inflammatory responses, while highlighting important biological uncertainties and the need for prospective clinical validation. The review further examines the translational potential of longitudinal immune monitoring, multiplex cytokine profiling, spatial and single-cell multi-omic technologies, computational network reconstruction, and biomarker-guided patient stratification for precision immunotherapy. Collectively, the available evidence supports a transition from static cytokine measurements toward dynamic cytokine network analysis while underscoring the scientific and clinical challenges that must be addressed before cytokine circuitry-informed strategies can be implemented in precision immuno-oncology.

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