TY - JOUR
T1 - Prospective development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with recurrent/metastatic cancer to immune checkpoint inhibitors
AU - Zhou, Jian Guo
AU - Donaubauer, Anna Jasmina
AU - Frey, Benjamin
AU - Becker, Ina
AU - Rutzner, Sandra
AU - Eckstein, Markus
AU - Sun, Roger
AU - Ma, Hu
AU - Schubert, Philipp
AU - Schweizer, Claudia
AU - Fietkau, Rainer
AU - Deutsch, Eric
AU - Gaipl, Udo
AU - Hecht, Markus
N1 - Publisher Copyright:
©
PY - 2021/2/16
Y1 - 2021/2/16
N2 - Background The predictive power of novel biological markers for treatment response to immune checkpoint inhibitors (ICI) is still not satisfactory for the majority of patients with cancer. One should identify valid predictive markers in the peripheral blood, as this is easily available before and during treatment. The current interim analysis of patients of the ST-ICI cohort therefore focuses on the development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with metastatic cancer to ICI targeting the programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) axis. Methods A total of 104 patients were prospectively enrolled. 54 immune cell subsets were prospectively analyzed in patients' peripheral blood by multicolor flow cytometry before treatment with ICI (pre-ICI; n=89), and after the first application of ICI (n=65). Pre-ICI, patients were randomly allocated to a training (n=56) and a validation cohort (n=33). Univariate Cox proportional hazards regression analysis and least absolute shrinkage and selection operator Cox model were used to create a predictive immune signature, which was also checked after the first ICI, to consider the dynamics of changes in the immune status. Results Whole blood samples were provided by 89 patients pre-ICI and by 65 patients after the first ICI. We identified a LIPS which is based on five immune cell subtypes: CD14 high monocytes, CD8+/PD-1 + T cells, plasmacytoid dendritic cells, neutrophils, and CD3 + /CD56 + /CD16 + natural killer (NK)T cells. The signature achieved a high accuracy (C-index 0.74 vs 0.71) for predicting overall survival (OS) benefit in both the training and the validation cohort. In both cohorts, the low-risk group had significantly longer OS than the high-risk group (HR 0.26, 95% CI 0.12 to 0.56, p=0.00025; HR 0.30, 95% CI 0.10 to 0.91, p=0.024, respectively). Regarding the whole cohort, LIPS also predicted progression-free survival (PFS). The identified LIPS was not affected by clinicopathological features with the exception of brain metastases. NKT cells and neutrophils of the LIPS can be used as dynamic predictive biomarkers for OS and PFS after first administration of the ICI. Conclusion Our study identified a predictive LIPS for survival of patients with cancer treated with PD-1/PD-L1 ICI, which is based on immune cell subsets in the peripheral whole blood. Trial registration number NCT03453892.
AB - Background The predictive power of novel biological markers for treatment response to immune checkpoint inhibitors (ICI) is still not satisfactory for the majority of patients with cancer. One should identify valid predictive markers in the peripheral blood, as this is easily available before and during treatment. The current interim analysis of patients of the ST-ICI cohort therefore focuses on the development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with metastatic cancer to ICI targeting the programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) axis. Methods A total of 104 patients were prospectively enrolled. 54 immune cell subsets were prospectively analyzed in patients' peripheral blood by multicolor flow cytometry before treatment with ICI (pre-ICI; n=89), and after the first application of ICI (n=65). Pre-ICI, patients were randomly allocated to a training (n=56) and a validation cohort (n=33). Univariate Cox proportional hazards regression analysis and least absolute shrinkage and selection operator Cox model were used to create a predictive immune signature, which was also checked after the first ICI, to consider the dynamics of changes in the immune status. Results Whole blood samples were provided by 89 patients pre-ICI and by 65 patients after the first ICI. We identified a LIPS which is based on five immune cell subtypes: CD14 high monocytes, CD8+/PD-1 + T cells, plasmacytoid dendritic cells, neutrophils, and CD3 + /CD56 + /CD16 + natural killer (NK)T cells. The signature achieved a high accuracy (C-index 0.74 vs 0.71) for predicting overall survival (OS) benefit in both the training and the validation cohort. In both cohorts, the low-risk group had significantly longer OS than the high-risk group (HR 0.26, 95% CI 0.12 to 0.56, p=0.00025; HR 0.30, 95% CI 0.10 to 0.91, p=0.024, respectively). Regarding the whole cohort, LIPS also predicted progression-free survival (PFS). The identified LIPS was not affected by clinicopathological features with the exception of brain metastases. NKT cells and neutrophils of the LIPS can be used as dynamic predictive biomarkers for OS and PFS after first administration of the ICI. Conclusion Our study identified a predictive LIPS for survival of patients with cancer treated with PD-1/PD-L1 ICI, which is based on immune cell subsets in the peripheral whole blood. Trial registration number NCT03453892.
KW - biomarkers
KW - immunotherapy
KW - programmed cell death 1 receptor
KW - tumor
KW - tumor biomarkers
KW - tumor microenvironment
UR - http://www.scopus.com/inward/record.url?scp=85100924051&partnerID=8YFLogxK
U2 - 10.1136/jitc-2020-001845
DO - 10.1136/jitc-2020-001845
M3 - Review article
C2 - 33593828
AN - SCOPUS:85100924051
SN - 2051-1426
VL - 9
JO - Journal for ImmunoTherapy of Cancer
JF - Journal for ImmunoTherapy of Cancer
IS - 2
M1 - e001845
ER -