The first visualization of chemotherapy-induced tumor apoptosis via magnetic particle imaging in a mouse model

Authors:
  • KWKun Wang
    Kun Wang
  • JDJiangfeng Du
    Jiangfeng Du
  • JTJie Tian
    Jie Tian
  • HZHui Zhang
    Hui Zhang
Publisher website
Google Scholar
Abstract
Imaging technologies that allow non-radiative visualization and quantification of apoptosis have a great potential for assessing therapy response, early diagnosis, and disease monitoring. Magnetic particle imaging (MPI), the direct imaging of magnetic nanoparticles as positive contrast agent and sole signal source, enables high image contrast (no tissue background signal), potential high sensitivity, and quantifiable signal intensity. These properties confer a great potential for application to tumor apoptosis monitoring. In this study, a simple and robust method was used to conjugate Alexa Fluor 647-AnnexinV (AF647-Anx), which can avidly bind to apoptotic cells, to superparamagnetic iron oxide (SPIO) nanoparticles, termed AF647-Anx-SPIO, which serves as an MPI-detectable tracer. Based on this apoptosis-specific tracer, MPI can accurately and unambiguously detect and quantify apoptotic tumor cells. AF647-Anx-SPIO showed relatively high affinity for apoptotic cells, and differences in binding between treated (apoptotic rate 67.21% ± 1.36%) and untreated (apoptotic rate 10.12 ± 0.11%) cells could be detected by MPI in vitro ( P < 0.05). Moreover, the imaging signal was almost proportional to the number of apoptotic cells determined using an MPI scanner ( R 2 = 0.99). There was a greater accumulation of AF647-Anx-SPIO in tumors of drug-treated animals than in tumors of untreated animals ( P < 0.05), and the difference could be detected by MPI ex vivo , while for in vivo imaging, no MPI imaging signal was detected in either group. Overall, this preliminary study demonstrates that MPI could be a potential imaging modality for tumor apoptosis imaging.
Funding Information
  • National Natural Science Foundation of China (61671449, 81227901)
  • Ministry of Science and Technology of China (2017YFA0205200)
  • Chinese Academy of Sciences (GJJSTD20170004, KFJ-STS-ZDTP-059, QYZDJ-SSW-JSC005, XDB32030200, YJKYYQ20180048)

This publication has 60 references indexed in Scilit: