The DOI matches its Crossref record; 717 of the 717 references it cites were found in a registry or an index.
ImmunoPET: Concept, Design, and Applications
Open accessAbstract
Immuno-positron emission tomography (immunoPET) is a paradigm-shifting molecular imaging modality combining the superior targeting specificity of monoclonal antibody (mAb) and the inherent sensitivity of PET technique. A variety of radionuclides and mAbs have been exploited to develop immunoPET probes, which has been driven by the development and optimization of radiochemistry and conjugation strategies. In addition, tumor-targeting vectors with a short circulation time (e.g., Nanobody) or with an enhanced binding affinity (e.g., bispecific antibody) are being used to design novel immunoPET probes. Accordingly, several immunoPET probes, such as 89 Zr-Df-pertuzumab and 89 Zr-atezolizumab, have been successfully translated for clinical use. By noninvasively and dynamically revealing the expression of heterogeneous tumor antigens, immunoPET imaging is gradually changing the theranostic landscape of several types of malignancies. ImmunoPET is the method of choice for imaging specific tumor markers, immune cells, immune checkpoints, and inflammatory processes. Furthermore, the integration of immunoPET imaging in antibody drug development is of substantial significance because it provides pivotal information regarding antibody targeting abilities and distribution profiles. Herein, we present the latest immunoPET imaging strategies and their preclinical and clinical applications. We also emphasize current conjugation strategies that can be leveraged to develop next-generation immunoPET probes. Lastly, we discuss practical considerations to tune the development and translation of immunoPET imaging strategies.
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Immunity, Inflammation, and Cancer
Grivennikov, S. I., Greten, F. R., & Karin, M. (2010) · Cell · doi:10.1016/j.cell.2010.01.025 · Cited by 10,755
Cell Signaling by Receptor Tyrosine Kinases
Lemmon, M. A., & Schlessinger, J. (2010) · Cell · doi:10.1016/j.cell.2010.06.011 · Cited by 7,929
IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for 2015 and 2040
Ogurtsova, K., da Rocha Fernandes, J. D., Huang, Y., Linnenkamp, U., Guariguata, L., Cho, N. H., Cavan, D., Shaw, J. E., & Makaroff, L. E. (2017) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2017.03.024 · Cited by 6,966
Cancer immunotherapy using checkpoint blockade
Ribas, A., & Wolchok, J. D. (2018) · Science · doi:10.1126/science.aar4060 · Cited by 6,791
Matrix Metalloproteinases: Regulators of the Tumor Microenvironment
Kessenbrock, K., Plaks, V., & Werb, Z. (2010) · Cell · doi:10.1016/j.cell.2010.03.015 · Cited by 5,151
IDF Diabetes Atlas: Global estimates of the prevalence of diabetes for 2011 and 2030
Whiting, D. R., Guariguata, L., Weil, C., & Shaw, J. (2011) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2011.10.029 · Cited by 3,994
Batlle, E., & Clevers, H. (2017) · Nature Medicine · doi:10.1038/nm.4409 · Cited by 2,769
VEGF in signaling and disease: beyond discovery and development
Apte, R. S., Chen, D. S., & Ferrara, N. (2019) · Cell · doi:10.1016/j.cell.2019.01.021 · Cited by 2,721
Discovery and development of bevacizumab, an anti-VEGF antibody for treating cancer
Ferrara, N., Hillan, K. J., Gerber, H.-P., & Novotny, W. (2004) · Nature Reviews Drug Discovery · doi:10.1038/nrd1381 · Cited by 2,625
HaloTag: A Novel Protein Labeling Technology for Cell Imaging and Protein Analysis
Los, G. V., Encell, L. P., McDougall, M. G., Hartzell, D. D., Karassina, N., Zimprich, C., Wood, M. G., Learish, R., Ohana, R. F., Urh, M., et al. (2008) · ACS Chemical Biology · doi:10.1021/cb800025k · Cited by 2,624
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Rong, J., Haider, A., Jeppesen, T. E., Josephson, L., & Liang, S. H. (2023) · Nature Communications · doi:10.1038/s41467-023-36377-4 · Cited by 294
Adverse Events Following Cancer Immunotherapy: Obstacles and Opportunities
Pauken, K. E., Dougan, M., Rose, N. R., Lichtman, A. H., & Sharpe, A. H. (2019) · Trends in Immunology · doi:10.1016/j.it.2019.04.002 · Cited by 280
Biomarkers for immunotherapy of hepatocellular carcinoma
Greten, T. F., Villanueva, A., Korangy, F., Ruf, B., Yarchoan, M., Ma, L., Ruppin, E., & Wang, X. W. (2023) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-023-00816-4 · Cited by 227
The Dawn of a New Era: Targeting the “Undruggables” with Antibody-Based Therapeutics
Qian, L., Lin, X., Gao, X., Khan, R. U., Liao, J.-Y., Du, S., Ge, J., Zeng, S., & Yao, S. Q. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.2c00915 · Cited by 155
Hypoxia and the phenomenon of immune exclusion
Pietrobon, V., & Marincola, F. M. (2021) · Journal of Translational Medicine · doi:10.1186/s12967-020-02667-4 · Cited by 119
Metadata
- Authors
- Wei, W., Rosenkrans, Z. T., Liu, J., Huang, G., Luo, Q.-Y., & Cai, W.
- Venue
- Chemical Reviews
- Publisher
- American Chemical Society (ACS)
- Published
- 2020-03-23
- Volume
- 120
- Issue
- 8
- Pages
- 3787-3851
- ISSN
- 0009-2665 (ISSN-L)
- 1520-6890
- OpenAlex
- W3012903956
- Cited by
- 484
- References
- 717
- FWCI
- 12.53
- Type
- journal article
- Language
- en
- Open access
- green
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