Spatio‐Temporally Profiling Human Lung Cancer Surgery With a FRET‐Mediated AIEgen‐Active Nanoprobe

Abstract Fluorescent surgical navigation is a clinically approved modality that has shown great potential for cancer treatment. However, its application in lung tumors still faces long‐standing challenges because the location, size, and shape of lung tumors can fluctuate significantly depending on the lung's gas filling or expulsion state. This leads to a substantial gap between preoperative imaging evaluation and intraoperative imaging feedback. Herein, Förster resonance energy transfer (FRET)‐mediated aggregation‐induced emission (AIE)‐active nanoprobe TCM‐N&Cy&Fe@P is described for spatiotemporally profiling lung cancer surgery through dual‐modal magnetic resonance imaging (MRI)/fluorescent imaging. This strategy, for the first time, effectively addresses the information‐gap across the pre‐, intra‐, and post‐operative stages of lung cancer surgery: MRI provides high spatial resolution soft tissue images for preoperative assessment of lung cancer. After the targeted delivery to the lung tumor site, the disassembly of TCM‐N&Cy&Fe@P resulted in a significant enhancement in near‐infrared fluorescence. Such AIE‐active fluorescence offers high temporal resolution images for precisely recognizing and delineating tumor boundaries in freshly excised lung cancer tissues from patients, and postoperatively pathological fluorescence staining with high tumor‐to‐normal contrast.

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Publication Details

Journal
Advanced Functional Materials
Published
2025-05-15
DOI
https://doi.org/10.1002/adfm.202502087
Citations
5
Primary Topic
Nanoplatforms for cancer theranostics
Type
article
Field-Weighted Citation Impact
3.37

Funders

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article

Spatio‐Temporally Profiling Human Lung Cancer Surgery With a FRET‐Mediated AIEgen‐Active Nanoprobe

Chenxu Yan, Haibo Xiao, Yongkang Yao, Yifan He et al.
5 citations
Advanced Functional Materials
Nanoplatforms for cancer theranostics
3.37
article

Spatio‐Temporally Profiling Human Lung Cancer Surgery With a FRET‐Mediated AIEgen‐Active Nanoprobe

Chenxu Yan, Haibo Xiao, Yongkang Yao, Yifan He, Weihong Zhu, Zhiqian Guo, Dan Li, Ruilong Dai, Zhengwei Yu
article en
5 citations

Abstract

Abstract Fluorescent surgical navigation is a clinically approved modality that has shown great potential for cancer treatment. However, its application in lung tumors still faces long‐standing challenges because the location, size, and shape of lung tumors can fluctuate significantly depending on the lung's gas filling or expulsion state. This leads to a substantial gap between preoperative imaging evaluation and intraoperative imaging feedback. Herein, Förster resonance energy transfer (FRET)‐mediated aggregation‐induced emission (AIE)‐active nanoprobe TCM‐N&Cy&Fe@P is described for spatiotemporally profiling lung cancer surgery through dual‐modal magnetic resonance imaging (MRI)/fluorescent imaging. This strategy, for the first time, effectively addresses the information‐gap across the pre‐, intra‐, and post‐operative stages of lung cancer surgery: MRI provides high spatial resolution soft tissue images for preoperative assessment of lung cancer. After the targeted delivery to the lung tumor site, the disassembly of TCM‐N&Cy&Fe@P resulted in a significant enhancement in near‐infrared fluorescence. Such AIE‐active fluorescence offers high temporal resolution images for precisely recognizing and delineating tumor boundaries in freshly excised lung cancer tissues from patients, and postoperatively pathological fluorescence staining with high tumor‐to‐normal contrast.

Advanced Functional MaterialsVol. 35(44)
East China University of Science and Technology (CN), Shanghai Jiao Tong University (CN), Renji Hospital (CN), XinHua Hospital (CN)
National Natural Science Foundation of China, Shanghai Municipal Education Commission, Shanghai Jiao Tong University, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 8%
Nanoplatforms for cancer theranostics
3.37
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