Exploitation of CD133 for the Targeted Imaging of Lethal Prostate Cancer

Paige M. Glumac, Joseph P. Gallant, Mariya Shapovalova, Yingming Li, Paari Murugan, Shilpa Gupta, Ilsa M. Coleman, Peter S. Nelson, Scott M. Dehm, Aaron M. Lebeau

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


Purpose: Aggressive variant prostate cancer (AVPC) is a non-androgen receptor-driven form of disease that arises in men in whom standard-of-care therapies have failed. Therapeutic options for AVPC are limited, and the development of novel therapeutics is significantly hindered by the inability to accurately quantify patient response to therapy by imaging. Imaging modalities that accurately and sensitively detect the bone and visceral metastases associated with AVPC do not exist. Experimental Design: This study investigated the transmembrane protein CD133 as a targetable cell surface antigen in AVPC. We evaluated the expression of CD133 by microarray and IHC analysis. The imaging potential of the CD133-targeted IgG (HA10 IgG) was evaluated in preclinical prostate cancer models using two different imaging modalities: near-infrared and PET imaging. Results: Evaluation of the patient data demonstrated that CD133 is overexpressed in a specific phenotype of AVPC that is androgen receptor indifferent and neuroendocrine differentiated. In addition, HA10 IgG was selective for CD133-expressing tumors in all preclinical imaging studies. PET imaging with [ 89Zr]Zr-HA10 IgG revealed a mean %ID/g of 24.30 ∓ 3.19 in CD133-positive metastatic lesions as compared with 11.82 ∓ 0.57 in CD133-negative lesions after 72 hours (P ¼ 0.0069). Ex vivo biodistribution showed similar trends as signals were increased by nearly 3-fold in CD133-positive tumors (P < 0.0001). Conclusions: To our knowledge, this is the first study to define CD133 as a targetable marker of AVPC. Similarly, we have developed a novel imaging agent, which is selective for CD133-expressing tumors, resulting in a noninvasive PET imaging approach to more effectively detect and monitor AVPC.

Original languageEnglish (US)
Pages (from-to)1054-1064
Number of pages11
JournalClinical Cancer Research
Issue number5
StatePublished - Mar 1 2020

Bibliographical note

Funding Information:
The authors acknowledge the University Imaging Centers at the University of Minnesota (Minneapolis, MN) for their technical advice and coordination of various imaging equipment. In particular, the authors thank Adrienne Sherman for her confocal microscopy assistance and Dr. Thomas Pengo for his advice and training regarding the medical imaging data analysis. They thank the University of Minnesota's Research Animal Resources Staff for assisting with research animal maintenance and include a special thanks to Dr. Nathan Koewler for his help in producing their intracardiac mouse model. They are also grateful to Colleen Forster and the rest of the Biorepository and Laboratory Services Division at the University of Minnesota (Minneapolis, MN) for their histology and pathology support. The authors are extremely grateful to Dr. Joshua M. Lang of the Carbone Cancer Center at the University of Wisconsin (Madison, WI) and Dr. John K. Lee of the Fred Hutchinson Cancer Research Center (Seattle, WA) for their assistance with this project. This work was supported by a Prostate Cancer Foundation Young Investigator Award (to A.M. LeBeau), Prostate Cancer Foundation Challenge Awards (to A.M. LeBeau and S.M. Dehm), the Minnesota Partnership for Biotechnology and Medical Genomics Infrastructure Award (MNP IF 16.05; to A.M. LeBeau), NIH/NCI CA090628 Paul Calabresi K12 Award (to A.M. LeBeau), NIH/ NCI R01 CA237272 (to A.M LeBeau), NIH/NCI R01 CA233562 (to A.M LeBeau), and NIH/NCI R01 CA174777 (to S.M. Dehm). The Prostate Cancer Biorepository Network is funded by the Department of Defense Prostate Cancer Research Program Awards (W81XWH-14-2-0182, W81XWH-14-2-0183, W81XWH-14-2-0185, W81XWH-14-2-0186, and W81XWH-15-2-0062).

Publisher Copyright:
© 2020 American Association for Cancer Research Inc.. All rights reserved.

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.


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