G Mazzaschi1, R Minari2, A Zecca3, A Cavazzoni4, V Ferri5, C Mori3, A Squadrilli5, P Bordi5, S Buti5, M Bersanelli5, A Leonetti5, A Cosenza5, L Ferri5, E Rapacchi5, G Missale6, P G Petronini4, F Quaini4, M Tiseo1. 1. Medical Oncology Unit, University Hospital of Parma, Parma, Italy; Department of Medicine & Surgery, University of Parma, Italy. 2. Medical Oncology Unit, University Hospital of Parma, Parma, Italy. Electronic address: rominari@ao.pr.it. 3. Infectious Diseases and Hepatology Unit, Laboratory of Viral Immunopathology, University Hospital of Parma, Italy. 4. Department of Medicine & Surgery, University of Parma, Italy. 5. Medical Oncology Unit, University Hospital of Parma, Parma, Italy. 6. Department of Medicine & Surgery, University of Parma, Italy; Infectious Diseases and Hepatology Unit, Laboratory of Viral Immunopathology, University Hospital of Parma, Italy.
Abstract
INTRODUCTION: Upfront criteria to foresee immune checkpoint inhibitors (ICIs) efficacy are far from being identified. Thus, we integrated blood descriptors of pro-inflammatory/immunosuppressive or effective anti-tumor response to non-invasively define predictive immune profiles in ICI-treated advanced non-small cell lung cancer (NSCLC). METHODS: Peripheral blood (PB) was prospectively collected at baseline from 109 consecutive NSCLC patients undergoing ICIs as first or more line treatment. Soluble PD-L1 (sPD-L1) (immunoassay), CD8+PD-1+ and NK (FACS) cells were assessed and interlaced to generate an Immune effector Score (IeffS). Lung Immune Prognostic Index (LIPI) was computed by LDH levels and derived Neutrophil-to-Lymphocyte Ratio (dNLR). All these parameters were correlated with survival outcome and treatment response. RESULTS: High sPD-L1 and low CD8+PD-1+ and NK number had negative impact on PFS (P < 0.001), OS (P < 0.01) and ICI-response (P < 0.05). Thus, sPD-L1high, CD8+PD-1+low and NKlow were considered as risk factors encompassing IeffS, whose prognostic power outperformed that of individual features and slightly exceeded that of LIPI. Accordingly, the absence of these risk factors portrayed a favorable IeffS characterizing patients with significantly (P < 0.001) prolonged PFS (median NR vs 2.3 months) and OS (median NR vs 4.1) and greater benefit from ICIs (P < 0.01). We then combined each risk parameter composing IeffS and LIPI (LDHhigh, dNLRhigh), thus defining three distinct prognostic classes. A remarkable impact of IeffS-LIPI integration was documented on survival outcome (PFS, HR = 4.61; 95%CI = 2.32-9.18; P < 0.001; OS, HR=4.03; 95%CI=1.91-8.67; P < 0.001) and ICI-response (AUC=0.90, 95%CI=0.81-0.97, P < 0.001). CONCLUSION: Composite risk models based on blood parameters featuring the tumor-host interaction might provide accurate prognostic scores able to predict ICI benefit in NSCLC patients.
INTRODUCTION: Upfront criteria to foresee immune checkpoint inhibitors (ICIs) efficacy are far from being identified. Thus, we integrated blood descriptors of pro-inflammatory/immunosuppressive or effective anti-tumor response to non-invasively define predictive immune profiles in ICI-treated advanced non-small cell lung cancer (NSCLC). METHODS: Peripheral blood (PB) was prospectively collected at baseline from 109 consecutive NSCLC patients undergoing ICIs as first or more line treatment. Soluble PD-L1 (sPD-L1) (immunoassay), CD8+PD-1+ and NK (FACS) cells were assessed and interlaced to generate an Immune effector Score (IeffS). Lung Immune Prognostic Index (LIPI) was computed by LDH levels and derived Neutrophil-to-Lymphocyte Ratio (dNLR). All these parameters were correlated with survival outcome and treatment response. RESULTS: High sPD-L1 and low CD8+PD-1+ and NK number had negative impact on PFS (P < 0.001), OS (P < 0.01) and ICI-response (P < 0.05). Thus, sPD-L1high, CD8+PD-1+low and NKlow were considered as risk factors encompassing IeffS, whose prognostic power outperformed that of individual features and slightly exceeded that of LIPI. Accordingly, the absence of these risk factors portrayed a favorable IeffS characterizing patients with significantly (P < 0.001) prolonged PFS (median NR vs 2.3 months) and OS (median NR vs 4.1) and greater benefit from ICIs (P < 0.01). We then combined each risk parameter composing IeffS and LIPI (LDHhigh, dNLRhigh), thus defining three distinct prognostic classes. A remarkable impact of IeffS-LIPI integration was documented on survival outcome (PFS, HR = 4.61; 95%CI = 2.32-9.18; P < 0.001; OS, HR=4.03; 95%CI=1.91-8.67; P < 0.001) and ICI-response (AUC=0.90, 95%CI=0.81-0.97, P < 0.001). CONCLUSION: Composite risk models based on blood parameters featuring the tumor-host interaction might provide accurate prognostic scores able to predict ICI benefit in NSCLC patients.
Authors: Verena Boschert; Jonas Teusch; Anwar Aljasem; Philipp Schmucker; Nicola Klenk; Anton Straub; Max Bittrich; Axel Seher; Christian Linz; Urs D A Müller-Richter; Stefan Hartmann Journal: Int J Mol Sci Date: 2020-11-20 Impact factor: 5.923
Authors: Brendan D Curti; Yoshinobu Koguchi; Rom S Leidner; Annah S Rolig; Elizabeth R Sturgill; Zhaoyu Sun; Yaping Wu; Venkatesh Rajamanickam; Brady Bernard; Ian Hilgart-Martiszus; Christopher B Fountain; George Morris; Noriko Iwamoto; Takashi Shimada; ShuChing Chang; Peter G Traber; Eliezer Zomer; J Rex Horton; Harold Shlevin; William L Redmond Journal: J Immunother Cancer Date: 2021-04 Impact factor: 13.751