光热治疗
铁
转移
化学
乳腺癌
癌症
铁离子
癌症研究
纳米技术
材料科学
生物化学
生物
医学
无机化学
内科学
作者
Mingcheng Wang,Huixi Yi,Qingshan Zheng,Muhammad Adnan Younis,Liyou Guo,Zhixiong Zhan,Muhammad Rizwan Younis,Chengzhi Jin,Dong-Yang Zhang
标识
DOI:10.1016/j.mtbio.2025.102028
摘要
The high metastatic rate of breast tumor is the prominent reason of its poor prognosis, while the inflammatory microenvironment of tumor tissues further promoted tumor metastasis. Although photothermal therapy (PTT) displays high antitumor efficacy, the rise of inflammation-induced reactive oxygen species (ROS) during PTT exacerbate tumor metastasis. To prevent breast tumor metastasis and relieve inflammation-induced oxidative stress during PTT, herein, we developed self-assembled nanodrugs (FCP) consisting of carminic acid, iron ion, and polyvinylpyrrolidone, demonstrating photoacoustic imaging-guided PTT and anti-inflammatory activity to restrict the growth of both primary breast tumor and metastatic tumor. The as designed self-assembled spherical FCP nanoparticles (NPs, 41 nm) exhibited good light to heat conversion and broad-spectrum multienzyme (superoxide dismutase, etc.) mimetic activity to scavenge excess ROS and alleviate oxidative stress. Meanwhile, FCP NPs showed a positive correlation between the photothermal heating and ROS scavenging, allowing the continuous consumption of ROS during PTT. Importantly, owing to the intrinsic bimodal photothermal and photoacoustic imaging abilities, FCP NPs effectively guided and monitored the in vivo treatment process, which facilitated to restrict the growth of both primary and metastatic breast tumor in vivo due to coordinated PTT and anti-inflammation as confirmed by TUNEL, ki67, and matrix metalloproteinase-9 stainings. Whereas FCP NPs did not pose any potential damage to the vital organs, presenting good biosafety in vivo. We envision that self-assembled nanodrugs with concurrent anti-inflammatory and photothermal activities may have great clinical prospects in the treatment of metastatic cancers.
科研通智能强力驱动
Strongly Powered by AbleSci AI