Hartman Colin J, Mohamed Asmaa O, Shukla Girja S, Pero Stephanie C, Sun Yu-Jing, Rodríguez-Jimenez Roberto S, Genovese Nicholas F, Kohler Nico M, Hemphill Thomas R, Huang Yina H, Krag David N, Ackerman Margaret E
Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, 14 Engineering Drive, Hanover, NH, 03755, USA.
Larner College of Medicine, University of Vermont, Burlington, VT, USA.
Cancer Immunol Immunother. 2025 May 31;74(7):231. doi: 10.1007/s00262-025-04075-3.
Cellular heterogeneity presents a significant challenge to cancer treatment. Antibody therapies targeting individual tumor-associated antigens can be extremely effective but are not suited for all patients and often fail against tumors with heterogeneous expression as tumor cells with low or no antigen expression escape targeting and develop resistance. Simultaneously targeting multiple tumor-specific proteins with multiple antibodies has the potential to overcome this barrier and improve efficacy, but relatively few widely expressed cancer-specific antigens are known. In contrast, neoepitopes, which arise from mutations unique to tumor cells, are considerably more abundant. However, since neoepitopes are not commonly shared between individuals, a patient-customized approach is necessary and motivates efforts to develop an efficient means to identify suitable target mutations and isolate neoepitope-specific monoclonal antibodies. Here, focusing on the latter goal, we use directed evolution in yeast and phage display systems to engineer antibodies from nonimmune, human antibody fragment libraries that are specific for neoepitopes previously reported in the B16F10 melanoma model. We demonstrate proof-of-concept for a pipeline that supports rapid isolation and functional enhancement of multiple neoepitope peptide-targeted monoclonal antibodies and demonstrate their robust binding to B16F10 cells and potent effector functions in vitro. These antibodies were combined and evaluated in vivo for anticancer activity in tumor-bearing mice, where they suppressed B16F10 tumor growth and prolonged survival. These findings emphasize the potential for clinical application of patient-customized antibody cocktails in the treatment of the many cancers poorly addressed by current therapies.
细胞异质性给癌症治疗带来了重大挑战。针对单个肿瘤相关抗原的抗体疗法可能极其有效，但并不适用于所有患者，并且对于具有异质性表达的肿瘤往往无效，因为低表达或无抗原表达的肿瘤细胞会逃避靶向并产生耐药性。同时用多种抗体靶向多种肿瘤特异性蛋白有可能克服这一障碍并提高疗效，但已知的广泛表达的癌症特异性抗原相对较少。相比之下，由肿瘤细胞特有的突变产生的新抗原要丰富得多。然而，由于新抗原通常不会在个体之间共享，因此需要采用针对患者的定制方法，并促使人们努力开发一种有效的方法来识别合适的靶突变并分离新抗原特异性单克隆抗体。在此，着眼于后一个目标，我们利用酵母和噬菌体展示系统中的定向进化，从非免疫的人抗体片段文库中构建针对先前在B16F10黑色素瘤模型中报道的新抗原的抗体。我们证明了一种流程的概念验证，该流程支持快速分离和功能增强多种新抗原肽靶向的单克隆抗体，并证明它们在体外与B16F10细胞具有强大的结合能力和有效的效应功能。这些抗体被组合起来，并在荷瘤小鼠体内评估其抗癌活性，结果显示它们抑制了B16F10肿瘤的生长并延长了生存期。这些发现强调了患者定制抗体鸡尾酒在治疗目前疗法难以应对的多种癌症方面的临床应用潜力。
