PurposeAn 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… Click to show full abstract
PurposeAn 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.MethodsThis 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.ResultsAt 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).ConclusionLow 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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