Your browser doesn't support javascript.
loading
Gold nanorods with iron oxide dual-modal bioprobes in SERS-MRI enable accurate programmed cell death ligand-1 expression detection in triple-negative breast cancer.
Pan, Ting; Zhang, Dinghu; Wu, Xiaoxia; Li, Zihou; Zeng, Hui; Xu, Xiawei; Zhang, Chenguang; He, Yiwei; Gong, Yuanchuan; Wang, Pin; Mao, Quanliang; Yao, Junlie; Lin, Jie; Wu, Aiguo; Shao, Guoliang.
Afiliación
  • Zhang D; Department of Interventional Radiology, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, People's Republic of China.
  • Wu X; Department of Interventional Radiology, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, People's Republic of China.
  • Li Z; Cixi Institute of Biomedical Engineering, International Cooperation Base of Biomedical Materials Technology and Application, Chinese Academy of Science (CAS) Key Laboratory of Magnetic Materials and Devices and Zhejiang Engineering Research Center for Biomedical Materials, Ningbo Institute of Materi
  • Zeng H; Department of Interventional Radiology, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, People's Republic of China.
  • He Y; Department of Interventional Radiology, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, People's Republic of China.
  • Gong Y; Department of Interventional Radiology, Zhejiang Cancer Hospital, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, People's Republic of China.
  • Mao Q; Cixi Institute of Biomedical Engineering, International Cooperation Base of Biomedical Materials Technology and Application, Chinese Academy of Science (CAS) Key Laboratory of Magnetic Materials and Devices and Zhejiang Engineering Research Center for Biomedical Materials, Ningbo Institute of Materi
APL Bioeng ; 7(2): 026106, 2023 Jun.
Article en En | MEDLINE | ID: mdl-37274628
ABSTRACT
The efficiency of immunotherapy for triple-negative breast cancer (TNBC) is relatively low due to the difficulty in accurately detecting immune checkpoints. The detection of TNBC-related programmed cell death ligand-1 (PD-L1) expression is important to guide immunotherapy and improve treatment efficiency. Surface-enhanced Raman spectroscopy (SERS) and magnetic resonance (MR) imaging exhibit great potential for early TNBC diagnosis. SERS, an optical imaging mode, has the advantages of high detection sensitivity, good spatial resolution, and "fingerprint" spectral characteristics; however, the shallow detection penetration of SERS bioprobes limits its application in vivo. MR has the advantages of allowing deep penetration with no radiation; however, its spatial resolution needs to be improved. SERS and MR have complementary imaging features for tumor marker detection. In this study, gold nanorod and ultrasmall iron oxide nanoparticle composites were developed as dual-modal bioprobes for SERS-MRI to detect PD-L1 expression. Anti-PD-L1 (aPD-L1) was utilized to improve the targeting ability and specificity of PD-L1 expression detection. TNBC cells expressing PD-L1 were accurately detected via the SERS imaging mode in vitro, which can image at the single-cell level. In addition, bioprobe accumulation in PD-L1 expression-related tumor-bearing mice was simply and dynamically monitored and analyzed in vivo using MR and SERS. To the best of our knowledge, this is the first time a SERS-MRI dual-modal bioprobe combined with a PD-L1 antibody has been successfully used to detect PD-L1 expression in TNBC. This work paves the way for the design of high-performance bioprobe-based contrast agents for the clinical immunotherapy of TNBC.

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: APL Bioeng Año: 2023 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: APL Bioeng Año: 2023 Tipo del documento: Article