化学
细胞外
免疫系统
癌症免疫疗法
降级(电信)
免疫疗法
癌症
癌症研究
膜
细胞生物学
癌症治疗
癌细胞
细胞内
癌症治疗
生物化学
细胞膜
地址1
细胞外基质
免疫学
抗体
膜蛋白
作者
Qingyu Dong,Zhuoying He,Youmei Xiao,Xiaoshuang Niu,Xin Yang,Danhong Chen,Xiaoyun Ye,Yang Li,Xueqin Zhu,Yuzhen Qian,Yixuan Sun,Xinghua Sui,Xiuman Zhou,Yanfeng Gao
标识
DOI:10.1016/j.apsb.2026.03.041
摘要
The shed extracellular domain (ECD) of discoidin domain receptor 1 (DDR1) aligns collagen to form a persistent shedding-derived matrix barrier that drive immune exclusion, remaining refractory to current kinase inhibitors and intracellular degraders. Herein, we report the rational design of DTPC (DDR1-TFRC peptide chimera), a novel peptide-based lysosome-targeting chimera (LYTAC). DTPC was engineered by conjugating a TFRC-targeting peptide with CDP-2, a novel high-affinity DDR1 blocker identified herein via structure-based virtual screening. Leveraging its compact architecture, DTPC achieves deep stromal penetration. Mechanistically, DTPC hijacks the transferrin receptor (TFRC) recycling to execute a dual-degradation strategy that triggers the endocytosis of membrane-bound DDR1 while uniquely scavenging shed DDR1-ECD from the extracellular space. In an orthotopic 4T1 breast cancer model characterized by PD-1 resistance and dense stroma, DTPC successfully degraded both membrane and extracellular DDR1, leading to matrix normalization and the restoration of CD8 + T cell infiltration. This structural and immunological reprogramming sensitized refractory tumors to anti-PD-1 therapy, significantly suppressing tumor growth and metastasis. Our findings establish a potent pharmacological strategy for dismantling the pathogenic physical barrier and validate a versatile peptide-based LYTAC paradigm for targeting the extracellular proteome to overcome immune exclusion for cancer immunotherapy. The peptide-based LYTAC (DTPC) simultaneously degrades membrane-bound and extracellular DDR1, dismantling the collagen barrier to restore CD8 + T cell infiltration and sensitize tumors to anti-PD-1 therapy.
科研通智能强力驱动
Strongly Powered by AbleSci AI