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PMID: 42520640 已发表 · ppublish 英语

Ultrasmall nanosonocatalyst induces PANoptosis to suppress ovarian cancer: From patient-derived organoids to in vivo models.

Biomaterials ·第 336 卷 ·2027-01-00

Xia L, Yuan C, Duan Y, Huang W, Yang Z, Wang M, Xu M, Chen Z, Chen Y, Li X, Huang Y

摘要

Ovarian cancer represents one of the most lethal gynecological malignancies, marked by a high recurrence rate and dismal prognosis. Existing targeted treatments face challenges such as limited applicability, modest effectiveness, and considerable costs, underscoring the demand for novel therapeutic alternatives. Growing research suggests that triggering a significant intracellular reactive oxygen species (ROS) surge can selectively induce oxidative destruction and death in tumor cells with compromised redox balance, while largely sparing normal cells. In this work, we designed lanthanum-doped zinc sulfide (ZnS:La) nanocrystals as an efficient sonocatalyst to augment sonodynamic treatment for ovarian cancer. Under ultrasound exposure, ZnS:La demonstrated improved charge separation and a notable boost in ROS generation, leading to substantial oxidative injury in cancer cells. Concurrently, the slow release of La3+ ions contributed to lysosomal membrane disruption, increasing cellular susceptibility to oxidative stress. These processes promoted the formation of PANoptosomes and initiated PANoptosis-a synergistic type of programmed cell death encompassing apoptosis, pyroptosis, and necroptosis. In evaluations using patient-derived organoids, subcutaneous grafts, and orthotopic ovarian tumor models, ultrasound-activated ZnS:La consistently inhibited tumor progression and spread. This study introduces a powerful sonocatalyst-based approach to engage multiple programmed cell death mechanisms, highlighting a potential new direction for ovarian cancer therapy.

关键词
Organoids Ovarian cancer PANoptosis Patient-derived tumor xenograft Sonodynamic therapy
文献信息
期刊
Biomaterials
期刊简称
Biomaterials
ISSN
1878-5905
发表日期
2027-01-00
语言
英语
国家/地区
Netherlands
NLM ID
8100316
分析服务
分析服务

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