Abstract With the accumulation of ADC-related knowledge and technological advancement, ADCs have experienced rapid development over the past decade. However, due to the overly concentrated of certain types of payloads, resistance to the payload has become a significant concern that cannot be ignored. The combination of chemotherapeutic drugs with DDR inhibitors (such as ATR inhibitors) to overcome resistance and achieve better efficacy has been validated and applied at the small molecule level. However, this approach also faces limitations such as systemic exposure and complex dosing regimens. Combining this concept with ADCs to create a dual-payload ADC represents a rational solution. Here we present our research work on PLB-015, an ADC obtained using a HER2 antibody as the target to validate our dual-payload ADC platform. Through optimization of different payload ratios and conjugation methods, we obtained the most effective molecular, PLB-015. PLB-015 demonstrated strong in vitro efficacy in several different HER2 positive cell lines correlating with HER2 expression levels. This ADC also exhibited potent and durable antitumor effects in cell line-derived and patient-derived xenograft models, and exhibited favorable pharmacokinetic profiles. The result of the toxicity study of PLB-015 in cynomolgus monkeys indicates PLB-015 is well tolerated. These preclinical results support PLB-015 as a potential candidate for the treatment of HER2-positive tumors. Citation Format: Yingdong Lu, Guangchao Zhang, Junqi Zhu, Ya Zhang, Haobo Tang, Haitao Pan, Zhengli Xu, Huixia Zhang, Shasha Li, Kia Joo Puan, Ling Xu, Xinhao Zhao, Zhengquan Zhang, Wei Lu, Yarong Qu, Mao Yin. PLB-015 a novel anti-HER2 dual payload ADC for the treatment of HER2 positive solid tumors abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts) ; 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86 (8Suppl): Abstract nr LB069.
Building similarity graph...
Analyzing shared references across papers
Loading...
Lu et al. (Fri,) studied this question.
www.synapsesocial.com/papers/69e47250010ef96374d8e619 — DOI: https://doi.org/10.1158/1538-7445.am2026-lb069
Yingdong Lu
Guangchao Zhang
Junqi Zhu
Cancer Research
Nanotherapeutics (United States)
Building similarity graph...
Analyzing shared references across papers
Loading...