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Salani, F.; Guerri, V.; Cesario, S.; Sammuri, P.; Genovesi, V.; Pratesi, F.; Massa, V.; Catanese, S.; Vivaldi, C.; Fornaro, L.; Crea, F.; Migliorini, P.; Galimberti, S. and Masi, G.
(2023).
DOI: https://doi.org/10.1016/j.annonc.2023.04.110
Abstract
Background: Atezolizumab/Bevacizumab (AtezoBv) is a reference EMA-approved combination superior to sorafenib in aHCC. Nonetheless, primary resistance rate is as high as 20% and no circulating biomarkers of treatment benefit prediction are known. Flow-cytometry allows for a non-invasive, dynamic evaluation of peripheral immunitary status. In aHCC, it successfully stratified anti-PDL1 plus anti-CTLA4 treatment activity, whilst this is the first report of its application to AtezoBv.
Methods: Consecutive aHCC patients treated with AtezoBv at Pisa Medical Oncology were prospectively enrolled from March 2021 to August 2022. Six-ml EDTA wholeblood were drawn predose at baseline (B), early on-treatment (E, cycles2/3 day1), and at first radiological evaluation (R). Four Flow-cytometry assays were designed to quantify the following cell subsets: T, B, NK, CD4+, CD8+, TIM+/LAG+/Ki67+ CD4+ and CD8+, T regulatory (TReg), classical and alternative monocytes, and neutrophils. Patients were dichotomized into primary-progressors (PP, if progressive disease was evident at first CT scan) and disease-controlled (DC, if partial response or stable disease was achieved). A cohort of healthy controls (HC) was enrolled. Distribution of immune cells concentration (cells/uL) was compared between HC and aHCC and between PP and DC with independent samples T-test or Mann-Whitney test (if normally and non-normally distributed, respectively). Cell subsets’ longitudinal trend from B to E to R was compared within and among the two groups (PP and DC) with
repeated measures ANOVA. Progression-free survival (PFS) and overall-survival (OS) were estimated with Kaplan Meier curves.
Results: Eleven aHCC patients (4 PP and 7 DC) and 9 HC were evaluated. AHCC cohort showed a prevalence of male gender (63.6%) and of extra-hepatic spread or macrovascular invasion (72.7%), a median age of 68.9 (42,1-81,0) years and an even distribution between viral (HCV and/or HBV, 54.5%) and non-viral etiologies (dismetabolic or healthy livers, 45.5%). Compared to HC, aHCC patients had higher neutrophils-to-lymphocytes ratio (p¼0.02), lower T (p¼0.02), CD4+ (p¼0.03), B (p < 0.01) and Ki67+CD8+ (p¼0.05) cells, whilts higher LAG+CD4+ (p < 0.01) and LAG+CD8+ (p¼0.03). Despite non-significantly different vs HC, TIM+CD4+ and TIM+CD8+ were positively correlated with LAG+ T lymphocytes (p for R2 0.04 and < 0.01, respectively) among aHCC. After treatment with AtezoBv, a DC rate of 63.7% was observed (2 PR and 5 SD) along with a PP rate of 36.3%, leading to a mPFS of 4,01
months (95% IC 2,27-10,56) and mOS of 13,03 months (95% IC 9,01-15,76; mOS for PP vs DC: 6.45 vs 15.76 months, p¼0.08), at 11.09 months (95% IC 8,82-23,22) of median follow-up. Compared to DC, PP had lower NK at B (p¼0.05) and E (p¼0.03). Among PP, TReg increased from B to R (p¼0.03), while NK increased from B to E (p¼0.01), to R (p¼0.03) in DC. A non-significant trend toward LAG+CD8+ decrease was seen from B to E to R in DC (3 subjects evaluable: 60.8 vs 22.1 vs 1.6 mean cells/uL).
Conclusions: Despite hampered by low numerosity of the case-series, peripheral cells flow-cytometry identified aHCC patients as “immune down-regulated” if compared to HC, as known at tissue-level. Furthermore, NK and Treg dynamics might be a promising tool to predict AtezoBev activity
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)
