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Patient-derived organoids as a potential model to predict response to PD-1/PD-L1 checkpoint inhibitors.
- Source :
-
British journal of cancer [Br J Cancer] 2019 Nov; Vol. 121 (11), pp. 979-982. Date of Electronic Publication: 2019 Oct 31. - Publication Year :
- 2019
-
Abstract
- Selection of cancer patients for treatment with immune checkpoint inhibitors remains a challenge due to tumour heterogeneity and variable biomarker detection. PD-L1 expression in 24 surgical chordoma specimen was determined immunohistochemically with antibodies 28-8 and E1L3N. The ability of patient-derived organoids to detect treatment effects of nivolumab was explored by quantitative and qualitative immunofluorescence and FACS analysis. The more sensitive antibody, E1L3N (ROC = 0.896, p = 0.001), was associated with greater tumour diameters (p = 0.014) and detected both tumour cells and infiltrating lymphocytes in 54% of patients, but only 1-15% of their cells. Organoids generated from PD-L1-positive patients contained both tumour cells and PD-1/CD8-positive lymphocytes and responded to nivolumab treatment with marked dose-dependent diameter reductions of up to 50% and increased cell death in both PD-L1-positive and negative organoids. Patient-derived organoids may be valuable to predict individual responses to immunotherapy even in patients with low or no immunohistochemical PD-L1 expression.
- Subjects :
- Aged
Aged, 80 and over
Apoptosis drug effects
B7-H1 Antigen immunology
B7-H1 Antigen metabolism
CD8-Positive T-Lymphocytes drug effects
Chordoma pathology
Chordoma surgery
Female
Humans
Immunohistochemistry methods
Lymphocytes, Tumor-Infiltrating immunology
Male
Middle Aged
Models, Biological
Programmed Cell Death 1 Receptor metabolism
B7-H1 Antigen antagonists & inhibitors
Chordoma metabolism
Drug Discovery methods
Immunotherapy methods
Nivolumab pharmacology
Organoids drug effects
Programmed Cell Death 1 Receptor antagonists & inhibitors
Subjects
Details
- Language :
- English
- ISSN :
- 1532-1827
- Volume :
- 121
- Issue :
- 11
- Database :
- MEDLINE
- Journal :
- British journal of cancer
- Publication Type :
- Academic Journal
- Accession number :
- 31666667
- Full Text :
- https://doi.org/10.1038/s41416-019-0616-1