Amoozgar Behzad, Bangolo Ayrton, Habibi Maryam, Cho Christina, Goy Andre
Department of Hematology and Oncology, John Theurer Cancer Center, Hackensack University Medical Center, Hackensack, NJ 07601, USA .
Tulane National Primate Research Center, Tulane University, New Orleans, LA 70118, USA.
Int J Mol Sci. 2025 Jun 1;26(11):5319. doi: 10.3390/ijms26115319.
Multispecific antibodies have redefined the immunotherapeutic landscape in hematologic malignancies. Bispecific antibodies (BsAbs), which redirect cytotoxic T cells toward malignant targets via dual antigen engagement, are now established components of treatment for diseases such as acute lymphoblastic leukemia (ALL), diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and multiple myeloma (MM). Clinical trials of agents like blinatumomab, glofitamab, mosunetuzumab, and teclistamab have demonstrated deep and durable responses in heavily pretreated populations. Trispecific antibodies (TsAbs), although still investigational, represent the next generation of immune redirection therapies, incorporating additional tumor antigens or co-stimulatory domains (e.g., CD28, 4-1BB) to mitigate antigen escape and enhance T-cell persistence. This review provides a comprehensive evaluation of BsAbs and TsAbs across hematologic malignancies, detailing molecular designs, mechanisms of action, therapeutic indications, resistance pathways, and toxicity profiles including cytokine release syndrome (CRS), immune effector cell-associated neurotoxicity syndrome (ICANS), cytopenias, and infections. We further discuss strategies to mitigate adverse effects and resistance, such as antigen switching, checkpoint blockade combinations, CELMoDs, and construct optimization. Notably, emerging platforms such as tetrafunctional constructs, checkpoint-integrated multispecifics, and protease-cleavable masking designs are expanding the therapeutic index of these agents. Early clinical evidence also supports the feasibility of applying multispecific antibodies to solid tumors. Finally, we highlight the transformative role of artificial intelligence (AI) and machine learning (ML) in multispecific antibody development, including antigen discovery, biomarker-driven treatment selection, toxicity prediction, and therapeutic optimization. Together, BsAbs and TsAbs illustrate the convergence of molecular precision, clinical innovation, and AI-driven personalization, establishing a new paradigm for immune-based therapy across hematologic and potentially solid tumor malignancies.
多特异性抗体重新定义了血液系统恶性肿瘤的免疫治疗格局。双特异性抗体(BsAbs)通过双重抗原结合将细胞毒性T细胞重定向至恶性靶点,现已成为急性淋巴细胞白血病(ALL)、弥漫性大B细胞淋巴瘤(DLBCL)、滤泡性淋巴瘤(FL)和多发性骨髓瘤(MM)等疾病治疗的既定组成部分。诸如贝林妥欧单抗、格罗菲妥单抗、莫苏奈妥单抗和替西利单抗等药物的临床试验已在大量经预处理的患者中显示出深度且持久的反应。三特异性抗体(TsAbs)尽管仍处于研究阶段,但代表了下一代免疫重定向疗法,其纳入了额外的肿瘤抗原或共刺激结构域(如CD28、4-1BB)以减轻抗原逃逸并增强T细胞持久性。本综述全面评估了BsAbs和TsAbs在血液系统恶性肿瘤中的应用,详细阐述了分子设计、作用机制、治疗适应症、耐药途径以及毒性特征,包括细胞因子释放综合征(CRS)、免疫效应细胞相关神经毒性综合征(ICANS)、血细胞减少和感染。我们还讨论了减轻不良反应和耐药性的策略,如抗原转换、检查点阻断联合、免疫调节剂(CELMoDs)和构建体优化。值得注意的是,四功能构建体、检查点整合多特异性抗体和蛋白酶可裂解掩蔽设计等新兴平台正在扩大这些药物的治疗指数。早期临床证据也支持将多特异性抗体应用于实体瘤的可行性。最后,我们强调了人工智能(AI)和机器学习(ML)在多特异性抗体开发中的变革性作用,包括抗原发现、生物标志物驱动的治疗选择、毒性预测和治疗优化。总之,BsAbs和TsAbs体现了分子精准性、临床创新和AI驱动的个性化的融合,为血液系统以及潜在的实体瘤恶性肿瘤的免疫治疗建立了新的范例。
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