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Molecular imaging for cancer immunotherapy

Immunotherapy has changed the treatment landscape for many cancers; however, not all patients treated have a favorable response and others can develop immune-related adverse events. A method to predict the treatment response to immunotherapeutic agents could allow for improved selection of patients...

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Detalles Bibliográficos
Autores principales: Lim, E.A., Drake, C.G., Mintz, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9216415/
https://www.ncbi.nlm.nih.gov/pubmed/35756142
http://dx.doi.org/10.1016/j.iotech.2020.03.001
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author Lim, E.A.
Drake, C.G.
Mintz, A.
author_facet Lim, E.A.
Drake, C.G.
Mintz, A.
author_sort Lim, E.A.
collection PubMed
description Immunotherapy has changed the treatment landscape for many cancers; however, not all patients treated have a favorable response and others can develop immune-related adverse events. A method to predict the treatment response to immunotherapeutic agents could allow for improved selection of patients more likely to benefit from treatment while sparing those who would suffer serious complications. While this has been an active area of research and has resulted in significant insights, current proposed mechanisms do not fully explain responses to therapy. One problem is that our understanding relies mostly on tumor biopsy samples that do not account for the complex spatiotemporal heterogeneity of cancers and their microenvironment. Radiolabeled probes targeting immune biomarkers and imaged using positron emission tomography with computed tomography could provide in vivo, real-time and non-invasive imaging of these biomarkers. Here we review the current field of functional nuclear imaging agents in immuno-oncology including antibodies and small molecule tracers to image PD-1, PD-L1, CTLA-4, T-cell markers and other targets being studied for potential therapies.
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spelling pubmed-92164152022-06-24 Molecular imaging for cancer immunotherapy Lim, E.A. Drake, C.G. Mintz, A. Immunooncol Technol Review Immunotherapy has changed the treatment landscape for many cancers; however, not all patients treated have a favorable response and others can develop immune-related adverse events. A method to predict the treatment response to immunotherapeutic agents could allow for improved selection of patients more likely to benefit from treatment while sparing those who would suffer serious complications. While this has been an active area of research and has resulted in significant insights, current proposed mechanisms do not fully explain responses to therapy. One problem is that our understanding relies mostly on tumor biopsy samples that do not account for the complex spatiotemporal heterogeneity of cancers and their microenvironment. Radiolabeled probes targeting immune biomarkers and imaged using positron emission tomography with computed tomography could provide in vivo, real-time and non-invasive imaging of these biomarkers. Here we review the current field of functional nuclear imaging agents in immuno-oncology including antibodies and small molecule tracers to image PD-1, PD-L1, CTLA-4, T-cell markers and other targets being studied for potential therapies. Elsevier 2020-03-27 /pmc/articles/PMC9216415/ /pubmed/35756142 http://dx.doi.org/10.1016/j.iotech.2020.03.001 Text en © 2020 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review
Lim, E.A.
Drake, C.G.
Mintz, A.
Molecular imaging for cancer immunotherapy
title Molecular imaging for cancer immunotherapy
title_full Molecular imaging for cancer immunotherapy
title_fullStr Molecular imaging for cancer immunotherapy
title_full_unstemmed Molecular imaging for cancer immunotherapy
title_short Molecular imaging for cancer immunotherapy
title_sort molecular imaging for cancer immunotherapy
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9216415/
https://www.ncbi.nlm.nih.gov/pubmed/35756142
http://dx.doi.org/10.1016/j.iotech.2020.03.001
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