Giampaolo Tortora1,2, Emilio Bria1,2, Vincenzo Di Noia3,4, Ettore D'Argento2, Sara Pilotto5, Emanuele Vita1, Miriam Grazia Ferrara1, Paola Damiano1, Marta Ribelli1, Antonella Cannella1, Antonella Virtuoso1, Andrea Fattorossi6, Giovanni Luca Ceresoli7, Michele Milella5, Giordano Domenico Beretta7. 1. Medical Oncology, Università Cattolica del Sacro Cuore, Rome, Italy. 2. Comprehensive Cancer Center, Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Rome, Italy. 3. Medical Oncology, Università Cattolica del Sacro Cuore, Rome, Italy. vincenzo.dinoia@gavazzeni.it. 4. Department of Medical Oncology, Cliniche Humanitas Gavazzeni, Bergamo, Italy. vincenzo.dinoia@gavazzeni.it. 5. U.O.C. of Oncology, Azienda Ospedaliera Universitaria Integrata, University of Verona, Verona, Italy. 6. Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy. 7. Department of Medical Oncology, Cliniche Humanitas Gavazzeni, Bergamo, Italy.
Abstract
BACKGROUND: Identifying the patients who may benefit the most from immune checkpoints inhibitors remains a great challenge for clinicians. Here we investigate on blood serum amyloid A (SAA) as biomarker of response to upfront pembrolizumab in patients with advanced non-small-cell lung cancer (NSCLC). METHODS: Patients with PD-L1 ≥ 50% receiving upfront pembrolizumab (P cohort) and with PD-L1 0-49% treated with chemotherapy (CT cohort) were evaluated for blood SAA and radiological response at baseline and every 9 weeks. Endpoints were response rate (RR) according to RECIST1.1, progression-free (PFS) and overall survival (OS). The most accurate SAA cut-off to predict response was established with ROC analysis in the P cohort. RESULTS: In the P Cohort (n = 42), the overall RR was 38%. After a median follow-up of 18.5 months (mo), baseline SAA ≤ the ROC-derived cut-off (29.9 mg/L; n = 28/42.67%) was significantly associated with higher RR (53.6 versus 7.1%; OR15, 95% CI 1.72-130.7, p = 0.009), longer PFS (17.4 versus 2.1 mo; p < 0.0001) and OS (not reached versus 7.2mo; p < 0.0001) compared with SAA > 29.9 mg/L. In multivariate analysis, low SAA positively affects PFS (p = 0.001) and OS (p = 0.048) irrespective of ECOG PS, number of metastatic sites and pleural effusion. SAA monitoring (n = 40) was also significantly associated with survival endpoints: median PFS 17.4 versus 2.1 mo and median OS not reached versus 7.2 mo when SAA remained low (n = 14) and high (n = 12), respectively. In the CT Cohort (n = 30), RR was not affected by SAA level (p > 0.05) while low SAA at baseline (n = 17) was associated with better PFS (HR 0.38, 95% CI 0.16-0.90, p = 0.006) and OS (HR 0.25, 95% CI 0.09-0.67, p < 0.001). CONCLUSION: Low SAA predicts good survival outcomes irrespective of treatment for advanced NSCLC patients and higher likelihood of response to upfront pembrolizumab only. The strong prognostic value might be exploited to easily identify patients most likely to benefit from immunotherapy. A further study (FoRECATT-2) is ongoing to confirm results in a larger sample size and to investigate the effect of SAA on immune response in vitro assays.
BACKGROUND: Identifying the patients who may benefit the most from immune checkpoints inhibitors remains a great challenge for clinicians. Here we investigate on blood serum amyloid A (SAA) as biomarker of response to upfront pembrolizumab in patients with advanced non-small-cell lung cancer (NSCLC). METHODS:Patients with PD-L1 ≥ 50% receiving upfront pembrolizumab (P cohort) and with PD-L1 0-49% treated with chemotherapy (CT cohort) were evaluated for blood SAA and radiological response at baseline and every 9 weeks. Endpoints were response rate (RR) according to RECIST1.1, progression-free (PFS) and overall survival (OS). The most accurate SAA cut-off to predict response was established with ROC analysis in the P cohort. RESULTS: In the P Cohort (n = 42), the overall RR was 38%. After a median follow-up of 18.5 months (mo), baseline SAA ≤ the ROC-derived cut-off (29.9 mg/L; n = 28/42.67%) was significantly associated with higher RR (53.6 versus 7.1%; OR15, 95% CI 1.72-130.7, p = 0.009), longer PFS (17.4 versus 2.1 mo; p < 0.0001) and OS (not reached versus 7.2mo; p < 0.0001) compared with SAA > 29.9 mg/L. In multivariate analysis, low SAA positively affects PFS (p = 0.001) and OS (p = 0.048) irrespective of ECOG PS, number of metastatic sites and pleural effusion. SAA monitoring (n = 40) was also significantly associated with survival endpoints: median PFS 17.4 versus 2.1 mo and median OS not reached versus 7.2 mo when SAA remained low (n = 14) and high (n = 12), respectively. In the CT Cohort (n = 30), RR was not affected by SAA level (p > 0.05) while low SAA at baseline (n = 17) was associated with better PFS (HR 0.38, 95% CI 0.16-0.90, p = 0.006) and OS (HR 0.25, 95% CI 0.09-0.67, p < 0.001). CONCLUSION: Low SAA predicts good survival outcomes irrespective of treatment for advanced NSCLCpatients and higher likelihood of response to upfront pembrolizumab only. The strong prognostic value might be exploited to easily identify patients most likely to benefit from immunotherapy. A further study (FoRECATT-2) is ongoing to confirm results in a larger sample size and to investigate the effect of SAA on immune response in vitro assays.
Entities:
Keywords:
Biomarker of response; NSCLC; Pembrolizumab; Predictive/prognostic factors to immune-checkpoint inhibitors; Serum amyloid A
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