Development of a Flow Cytometry-Based Whole-Blood Prognostic Immune Signature in Metastatic Cancer Patients treated with immune checkpoint inhibitors

Abstract

Recent biomarker research focuses on early immunological changes to predict treatment response to immune checkpoint inhibitors (ICI). Within this prospective ST-ICI trial, pre-planned biomarker analysis was performed and we developed a flow cytometry-based whole-blood prognostic immune signature (FCBPS) to predict overall survival (OS) benefit of cancer patients treated with ICI. For this, fifty-four immune cell subsets were analyzed in the patients peripheral blood before the second administration of the ICI. Patients were randomly allocated to a training and validation cohort. Univariate Cox proportional hazards regression analysis and LASSO Cox model were used to develop a predictive and prognostic signature. 104 patients were prospectively enrolled. 89 patients provided blood samples. The identified FCBPS signature bases on five immune cell subtypes: neutrophils, plasmacytoid dendritic cells (pDCs), natural killer (NK)T cells (CD56+/CD16+), monocytes (CD14high) and CD8+ T cells (PD-1+). This signature achieved a high accuracy (C-index 0.74 vs 0.71) for predicting OS benefit in the training and validation cohort. Both in the training and validation cohort, the low-risk group had significantly longer OS than the high-risk group (HR 0.26, 95% CI: 0.12-0.56, p=0.00025; HR 0.30, 95% CI: 0.10 -0.91, p=0.024, respectively). In the whole cohort, FCBPS is a predictor of OS (HROS=0.28, 95% CI: 0.15-0.52) and progression-free survival (HRPFS=0.22, 95% CI: 0.12-0.39) that remained independent in multivariate analyses and subgroup analyses after adjusting for clinical and pathological factors. The identified flow cytometry-based whole-blood prognostic signature (FCBPS) is a powerful predictor for metastatic cancer patients who benefit from ICI treatment.