pH响应性PEG化抗体实现肿瘤特异性激活并减轻免疫相关不良事件

Immune checkpoint blockade using monoclonal antibodies (mAbs) has achieved durable antitumor efficacy but is often limited by immune-related adverse events (irAEs) resulting from systemic immune activation. To decouple antitumor activity from off-target toxicity, a pH-responsive masking approach was developed to suppress mAb function at physiological pH while selectively restoring activity in the mildly acidic tumor microenvironment (TME). A cleavable poly(ethylene glycol) (PEG) coating was synthesized by reacting carboxy-dimethylmaleic anhydride (CDM) with vacuum-dried PEG-methyl ether in dichloromethane to generate PEG-CDM. Anti-CD47, anti-CTLA-4, and anti-PD-1 antibodies were buffer-exchanged and reacted with a 300-fold molar excess of PEG-CDM to obtain PEG-CDM-modified mAbs. The modified antibodies were characterized for conjugation efficiency, physicochemical stability, and rheological behavior. Their pH-dependent masking and cleavage kinetics were examined under physiological and mildly acidic conditions (pH 7.4 and 6.4-6.8, respectively). Functional recovery was analyzed through in vitro binding and immune cell assays, followed by in vivo evaluation in MC38 and B16F10 tumor-bearing C57BL/6 mice. PEG-CDM modification effectively masked antibody activity at neutral pH, confirming successful suppression of checkpoint engagement. Under TME-mimicking acidic conditions, PEG-CDM rapidly hydrolyzed, restoring antibody binding and effector functions in a pH-dependent manner. In vivo, PEG-CDM-modified mAbs demonstrated tumor-specific activation and retained antitumor potency comparable to unmodified antibodies while markedly reducing off-tumor immune activation in both MC38 and B16F10 models. This pH-responsive PEG-CDM masking platform enables conditional activation of immune checkpoint antibodies within the acidic TME while minimizing systemic immune stimulation. The strategy offers a modular and tunable approach to enhance the therapeutic window of checkpoint blockade by balancing efficacy with improved safety, providing a translational path toward next-generation cancer immunotherapies. AI Disclosure (optional): A generative AI tool was utilized to assist in grammar refinement and structural consistency; all scientific content has been verified by the authors.