Intelligent α-Cyclodextrin-Based Nanomachines Co-loading Lenalidomide and Au@TPE for NIR-I-Light Programmed Combinatorial Breast Cancer Therapy

Malignant tumors have emerged as a major threat to human health. Micro/nanomachines offer minimally invasive advantages over traditional cancer therapies, making them promising for medical applications. Herein, we designed an α-cyclodextrin-based nanomachine (αALN) encapsulating Au@TPE as a photothermal agent, leveraging cyclodextrins' encapsulation and carrier properties to achieve high Au@TPE loading and targeted delivery to tumor sites for effective photothermal therapy (PTT). Furthermore, the immunomodulatory drug lenalidomide was integrated into this system. Post-administration, αALN delivers lenalidomide to lesions while exerting dual functions: guiding nanomachine accumulation in tumors and activating killer cells to elicit anti-tumor immune responses. The synergy between PTT and immunotherapy significantly enhanced breast cancer therapeutic efficacy. αALN exhibits excellent photothermal conversion efficiency, high stability, and low intrinsic toxicity, minimizing side effects on healthy tissues. Collectively, this study expands the therapeutic framework for breast cancer by combining lenalidomide-mediated immunotherapy with PTT, providing a nanomachine-based strategy for precision oncology.

Authors

Institutions

Publication Details

Journal
ACS Applied Bio Materials
Published
2026-04-07
DOI
https://doi.org/10.1021/acsabm.6c00225
Primary Topic
Nanoplatforms for cancer theranostics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intelligent α-Cyclodextrin-Based Nanomachines Co-loading Lenalidomide and Au@TPE for NIR-I-Light Programmed Combinatorial Breast Cancer Therapy

Bo Cui, Xun Zhang, Juan Xu, Yishan Fang et al.
ACS Applied Bio Materials
Nanoplatforms for cancer theranostics
article

Intelligent α-Cyclodextrin-Based Nanomachines Co-loading Lenalidomide and Au@TPE for NIR-I-Light Programmed Combinatorial Breast Cancer Therapy

Bo Cui, Xun Zhang, Juan Xu, Yishan Fang, Ying Tian, Qianqian Che
article en

Abstract

Malignant tumors have emerged as a major threat to human health. Micro/nanomachines offer minimally invasive advantages over traditional cancer therapies, making them promising for medical applications. Herein, we designed an α-cyclodextrin-based nanomachine (αALN) encapsulating Au@TPE as a photothermal agent, leveraging cyclodextrins' encapsulation and carrier properties to achieve high Au@TPE loading and targeted delivery to tumor sites for effective photothermal therapy (PTT). Furthermore, the immunomodulatory drug lenalidomide was integrated into this system. Post-administration, αALN delivers lenalidomide to lesions while exerting dual functions: guiding nanomachine accumulation in tumors and activating killer cells to elicit anti-tumor immune responses. The synergy between PTT and immunotherapy significantly enhanced breast cancer therapeutic efficacy. αALN exhibits excellent photothermal conversion efficiency, high stability, and low intrinsic toxicity, minimizing side effects on healthy tissues. Collectively, this study expands the therapeutic framework for breast cancer by combining lenalidomide-mediated immunotherapy with PTT, providing a nanomachine-based strategy for precision oncology.

ACS Applied Bio MaterialsVol. 9(8)
Qilu University of Technology (CN), Shandong Academy of Sciences (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 22%
Nanoplatforms for cancer theranostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.