Refining patient selection for breast cancer immunotherapy: beyond PD-L1.
PD-L1
biomarkers
breast cancer
immune checkpoint inhibitors
immunotherapy
Journal
ESMO open
ISSN: 2059-7029
Titre abrégé: ESMO Open
Pays: England
ID NLM: 101690685
Informations de publication
Date de publication:
10 2021
10 2021
Historique:
received:
22
03
2021
revised:
27
07
2021
accepted:
03
08
2021
pubmed:
7
9
2021
medline:
30
10
2021
entrez:
6
9
2021
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 34487970
pii: S2059-7029(21)00219-2
doi: 10.1016/j.esmoop.2021.100257
pmc: PMC8426207
pii:
doi:
Substances chimiques
B7-H1 Antigen
0
Biomarkers, Tumor
0
Immunologic Factors
0
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
100257Informations de copyright
Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Disclosure FP-L declares that her institution (Centre Jean Perrin) has received grants or contracts from Roche, AstraZeneca, Bristol Myers Squibb (BMS), Merck Sharp & Dohme (MSD) and Pfizer in the past 36 months. During the same period, she or her institution has received consulting fees from the same biopharmaceutical companies. She also received payment or honoraria for lectures, presentations, speaker bureaus, manuscript writing or educational events from Roche and AstraZeneca during the mentioned period. MK and NR-R have no competing interests to declare.