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Refining patient selection for breast cancer immunotherapy: beyond PD-L1

Therapies that modulate immune response to cancer, such as immune checkpoint inhibitors, began an intense development a few years ago; however, in breast cancer (BC), the results have been relatively disappointing so far. Finding biomarkers for better selection of BC patients for various immunothera...

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Autores principales: Kossai, M., Radosevic-Robin, N., Penault-Llorca, F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426207/
https://www.ncbi.nlm.nih.gov/pubmed/34487970
http://dx.doi.org/10.1016/j.esmoop.2021.100257
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author Kossai, M.
Radosevic-Robin, N.
Penault-Llorca, F.
author_facet Kossai, M.
Radosevic-Robin, N.
Penault-Llorca, F.
author_sort Kossai, M.
collection PubMed
description Therapies that modulate immune response to cancer, such as immune checkpoint inhibitors, began an intense development a few years ago; however, in breast cancer (BC), the results have been relatively disappointing so far. Finding biomarkers for better selection of BC patients for various immunotherapies remains a significant unmet medical need. At present, only tumour tissue programmed death-ligand 1 (PD-L1) and mismatch repair deficiency status are approved as theranostic biomarkers for programmed cell death-1 (PD-1)/PD-L1 inhibitors in BC. However, due to the complexity of tumour microenvironment (TME) and cancer response to immunomodulators, none of them is a perfect selector. Therefore, an intense quest is ongoing for complementary tumour- or host-related predictive biomarkers in breast immuno-oncology. Among the upcoming biomarkers, quantity, immunophenotype and spatial distribution of tumour-infiltrating lymphocytes and other TME cells as well as immune gene signatures emerge as most promising and are being increasingly tested in clinical trials. Biomarkers or strategies allowing dynamic assessment of BC response to immunotherapy, such as circulating/exosomal PD-L1, quantity of white/immune blood cell subpopulations and molecular imaging are particularly suitable for immunotreatment monitoring. Finally, host-related factors, such as microbiome and lifestyle, should also be taken into account when planning integration of immunomodulating therapies into BC management. As none of the biomarkers taken separately is accurate enough, the solution could come from composite biomarkers, which would combine clinical, molecular and immunological features of the disease, possibly powered by artificial intelligence.
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spelling pubmed-84262072021-09-13 Refining patient selection for breast cancer immunotherapy: beyond PD-L1 Kossai, M. Radosevic-Robin, N. Penault-Llorca, F. ESMO Open Review Therapies that modulate immune response to cancer, such as immune checkpoint inhibitors, began an intense development a few years ago; however, in breast cancer (BC), the results have been relatively disappointing so far. Finding biomarkers for better selection of BC patients for various immunotherapies remains a significant unmet medical need. At present, only tumour tissue programmed death-ligand 1 (PD-L1) and mismatch repair deficiency status are approved as theranostic biomarkers for programmed cell death-1 (PD-1)/PD-L1 inhibitors in BC. However, due to the complexity of tumour microenvironment (TME) and cancer response to immunomodulators, none of them is a perfect selector. Therefore, an intense quest is ongoing for complementary tumour- or host-related predictive biomarkers in breast immuno-oncology. Among the upcoming biomarkers, quantity, immunophenotype and spatial distribution of tumour-infiltrating lymphocytes and other TME cells as well as immune gene signatures emerge as most promising and are being increasingly tested in clinical trials. Biomarkers or strategies allowing dynamic assessment of BC response to immunotherapy, such as circulating/exosomal PD-L1, quantity of white/immune blood cell subpopulations and molecular imaging are particularly suitable for immunotreatment monitoring. Finally, host-related factors, such as microbiome and lifestyle, should also be taken into account when planning integration of immunomodulating therapies into BC management. As none of the biomarkers taken separately is accurate enough, the solution could come from composite biomarkers, which would combine clinical, molecular and immunological features of the disease, possibly powered by artificial intelligence. Elsevier 2021-09-03 /pmc/articles/PMC8426207/ /pubmed/34487970 http://dx.doi.org/10.1016/j.esmoop.2021.100257 Text en © 2021 The Authors 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
Kossai, M.
Radosevic-Robin, N.
Penault-Llorca, F.
Refining patient selection for breast cancer immunotherapy: beyond PD-L1
title Refining patient selection for breast cancer immunotherapy: beyond PD-L1
title_full Refining patient selection for breast cancer immunotherapy: beyond PD-L1
title_fullStr Refining patient selection for breast cancer immunotherapy: beyond PD-L1
title_full_unstemmed Refining patient selection for breast cancer immunotherapy: beyond PD-L1
title_short Refining patient selection for breast cancer immunotherapy: beyond PD-L1
title_sort refining patient selection for breast cancer immunotherapy: beyond pd-l1
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8426207/
https://www.ncbi.nlm.nih.gov/pubmed/34487970
http://dx.doi.org/10.1016/j.esmoop.2021.100257
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