Romain-David Seban1, John S Nemer2,3, Aurélien Marabelle4,5, Randy Yeh3, Eric Deutsch4, Samy Ammari1, Antoine Moya-Plana6, Fatima-Zohra Mokrane3, Robyn D Gartrell2, Grace Finkel2, Luke Barker2, Amélie E Bigorgne4,5,7,8, Lawrence H Schwartz3, Yvonne Saenger2, Caroline Robert6, Laurent Dercle9,10. 1. Département d'imagerie Médicale, Gustave Roussy, Université Paris-Saclay, 94800, Villejuif, France. 2. Department of Medicine, Division of Hematology Oncology, New York-Presbyterian Hospital/Columbia University Medical Center, New York, NY, USA. 3. Department of Radiology, New York Presbyterian Hospital - Columbia University Medical Center, New York, NY, 10039, USA. 4. Drug Development Department (DITEP), Gustave Roussy, Villejuif, France. 5. UMR1015, Gustave Roussy, Université Paris Saclay, 94800, Villejuif, France. 6. Inserm U981, Melanoma group, Gustave Roussy Cancer Campus, Villejuif, France. 7. Inserm U1163, Imagine Institute, Paris, France. 8. University Paris Descartes, Paris, France. 9. Department of Radiology, New York Presbyterian Hospital - Columbia University Medical Center, New York, NY, 10039, USA. ld2752@cumc.columbia.edu. 10. UMR1015, Gustave Roussy, Université Paris Saclay, 94800, Villejuif, France. ld2752@cumc.columbia.edu.
Abstract
PURPOSE: An imaging-based stratification tool is needed to identify melanoma patients who will benefit from anti Programmed Death-1 antibody (anti-PD1). We aimed at identifying biomarkers for survival and response evaluated in lymphoid tissue metabolism in spleen and bone marrow before initiation of therapy. METHODS: This retrospective study included 55 patients from two institutions who underwent 18F-FDG PET/CT before anti-PD1. Parameters extracted were SUVmax, SUVmean, HISUV (SUV-based Heterogeneity Index), TMTV (total metabolic tumor volume), TLG (total lesion glycolysis), BLR (Bone marrow-to-Liver SUVmax ratio), and SLR (Spleen-to-Liver SUVmax ratio). Each parameter was dichotomized using the median as a threshold. Association with survival, best overall response (BOR), and transcriptomic analyses (NanoString assay) were evaluated using Cox prediction models, Wilcoxon tests, and Spearman's correlation, respectively. RESULTS: At 20.7 months median follow-up, 33 patients had responded, and 29 patients died. Median PFS and OS were 11.4 (95%CI 2.7-20.2) and 28.5 (95%CI 13.4-43.8) months. TMTV (>25cm3), SLR (>0.77), and BLR (>0.79) correlated with shorter survival. High TMTV (>25 cm3), SLR (>0.77), and BLR (>0.79) correlated with shorter survival, with TMTV (HR PFS 2.2, p = 0.02, and HR OS 2.5, p = 0.02) and BLR (HR OS 2.3, p = 0.04) remaining significant in a multivariable analysis. Low TMTV and TLG correlated with BOR (p = 0.03). Increased glucose metabolism in bone marrow (BLR) was associated with transcriptomic profiles including regulatory T cell markers (p < 0.05). CONCLUSION: Low tumor burden correlates with survival and objective response while hematopoietic tissue metabolism correlates inversely with survival. These biomarkers should be further evaluated for potential clinical application.
PURPOSE: An imaging-based stratification tool is needed to identify melanomapatients who will benefit from anti Programmed Death-1 antibody (anti-PD1). We aimed at identifying biomarkers for survival and response evaluated in lymphoid tissue metabolism in spleen and bone marrow before initiation of therapy. METHODS: This retrospective study included 55 patients from two institutions who underwent 18F-FDG PET/CT before anti-PD1. Parameters extracted were SUVmax, SUVmean, HISUV (SUV-based Heterogeneity Index), TMTV (total metabolic tumor volume), TLG (total lesion glycolysis), BLR (Bone marrow-to-Liver SUVmax ratio), and SLR (Spleen-to-Liver SUVmax ratio). Each parameter was dichotomized using the median as a threshold. Association with survival, best overall response (BOR), and transcriptomic analyses (NanoString assay) were evaluated using Cox prediction models, Wilcoxon tests, and Spearman's correlation, respectively. RESULTS: At 20.7 months median follow-up, 33 patients had responded, and 29 patientsdied. Median PFS and OS were 11.4 (95%CI 2.7-20.2) and 28.5 (95%CI 13.4-43.8) months. TMTV (>25cm3), SLR (>0.77), and BLR (>0.79) correlated with shorter survival. High TMTV (>25 cm3), SLR (>0.77), and BLR (>0.79) correlated with shorter survival, with TMTV (HR PFS 2.2, p = 0.02, and HR OS 2.5, p = 0.02) and BLR (HR OS 2.3, p = 0.04) remaining significant in a multivariable analysis. Low TMTV and TLG correlated with BOR (p = 0.03). Increased glucose metabolism in bone marrow (BLR) was associated with transcriptomic profiles including regulatory T cell markers (p < 0.05). CONCLUSION:Low tumor burden correlates with survival and objective response while hematopoietic tissue metabolism correlates inversely with survival. These biomarkers should be further evaluated for potential clinical application.
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