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Improved mouse models to assess tumour immunity and irAEs after combination cancer immunotherapies

The current excitement surrounding cancer immunotherapy stems particularly from clinical data involving agents mediating immune checkpoint receptor blockade, which have induced unprecedented efficacy against a range of tumours compared with previous immunotherapeutic approaches. However, an importan...

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Autores principales: Liu, Jing, Blake, Stephen J, Smyth, Mark J, Teng, Michele WL
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4232074/
https://www.ncbi.nlm.nih.gov/pubmed/25505970
http://dx.doi.org/10.1038/cti.2014.18
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author Liu, Jing
Blake, Stephen J
Smyth, Mark J
Teng, Michele WL
author_facet Liu, Jing
Blake, Stephen J
Smyth, Mark J
Teng, Michele WL
author_sort Liu, Jing
collection PubMed
description The current excitement surrounding cancer immunotherapy stems particularly from clinical data involving agents mediating immune checkpoint receptor blockade, which have induced unprecedented efficacy against a range of tumours compared with previous immunotherapeutic approaches. However, an important consideration in targeting checkpoint receptors has been the emergence of associated toxicities termed immune-related adverse events (irAEs). In light of the clinical benefits observed after co-blockade of checkpoint receptors and data from preclinical mouse models, there is now a strong rationale to combine different checkpoint receptors together, with other immunotherapies or more conventional therapies to assess if clinical benefits to cancer patients can be further improved. However, one may predict the frequency and severity of irAEs will increase with combinations, which may result in premature therapy cessation, thus limiting the realization of such an approach. In addition, there is a limit to how many different combination therapies that can be tested in a timely manner given the legal, regulatory and budgetary issues associated with conducting clinical trials. Thus, there is a need to develop preclinical mouse models that more accurately inform us as to which immunotherapies might combine best to provide the optimal therapeutic index (maximal anti-tumour efficacy and low level irAEs) in different cancer settings. In this review we will discuss the irAEs observed in patients after checkpoint blockade and discuss which mouse models of cancer can be appropriate to assess the development of tumour immunity and irAEs following combination cancer immunotherapies.
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spelling pubmed-42320742014-12-11 Improved mouse models to assess tumour immunity and irAEs after combination cancer immunotherapies Liu, Jing Blake, Stephen J Smyth, Mark J Teng, Michele WL Clin Transl Immunology Review The current excitement surrounding cancer immunotherapy stems particularly from clinical data involving agents mediating immune checkpoint receptor blockade, which have induced unprecedented efficacy against a range of tumours compared with previous immunotherapeutic approaches. However, an important consideration in targeting checkpoint receptors has been the emergence of associated toxicities termed immune-related adverse events (irAEs). In light of the clinical benefits observed after co-blockade of checkpoint receptors and data from preclinical mouse models, there is now a strong rationale to combine different checkpoint receptors together, with other immunotherapies or more conventional therapies to assess if clinical benefits to cancer patients can be further improved. However, one may predict the frequency and severity of irAEs will increase with combinations, which may result in premature therapy cessation, thus limiting the realization of such an approach. In addition, there is a limit to how many different combination therapies that can be tested in a timely manner given the legal, regulatory and budgetary issues associated with conducting clinical trials. Thus, there is a need to develop preclinical mouse models that more accurately inform us as to which immunotherapies might combine best to provide the optimal therapeutic index (maximal anti-tumour efficacy and low level irAEs) in different cancer settings. In this review we will discuss the irAEs observed in patients after checkpoint blockade and discuss which mouse models of cancer can be appropriate to assess the development of tumour immunity and irAEs following combination cancer immunotherapies. Nature Publishing Group 2014-08-01 /pmc/articles/PMC4232074/ /pubmed/25505970 http://dx.doi.org/10.1038/cti.2014.18 Text en Copyright © 2014 Australasian Society for Immunology Inc. http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Review
Liu, Jing
Blake, Stephen J
Smyth, Mark J
Teng, Michele WL
Improved mouse models to assess tumour immunity and irAEs after combination cancer immunotherapies
title Improved mouse models to assess tumour immunity and irAEs after combination cancer immunotherapies
title_full Improved mouse models to assess tumour immunity and irAEs after combination cancer immunotherapies
title_fullStr Improved mouse models to assess tumour immunity and irAEs after combination cancer immunotherapies
title_full_unstemmed Improved mouse models to assess tumour immunity and irAEs after combination cancer immunotherapies
title_short Improved mouse models to assess tumour immunity and irAEs after combination cancer immunotherapies
title_sort improved mouse models to assess tumour immunity and iraes after combination cancer immunotherapies
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4232074/
https://www.ncbi.nlm.nih.gov/pubmed/25505970
http://dx.doi.org/10.1038/cti.2014.18
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