TY - JOUR
T1 - Prognostic and theranostic 18F-FDG PET biomarkers for anti-PD1 immunotherapy in metastatic melanoma
T2 - association with outcome and transcriptomics
AU - Seban, Romain David
AU - Nemer, John S.
AU - Marabelle, Aurélien
AU - Yeh, Randy
AU - Deutsch, Eric
AU - Ammari, Samy
AU - Moya-Plana, Antoine
AU - Mokrane, Fatima Zohra
AU - Gartrell, Robyn D.
AU - Finkel, Grace
AU - Barker, Luke
AU - Bigorgne, Amélie E.
AU - Schwartz, Lawrence H.
AU - Saenger, Yvonne
AU - Robert, Caroline
AU - Dercle, Laurent
N1 - Funding Information:
Patients Recruitment (CM, JCS, LHS, YS, CR). Clinical Data Collection (SA, AMP, FZM, GR, LB, LD). Imaging Data Collection (RDS, JSN, RY, LD). Transcriptomics Data Cost (AM, YS). Transcriptomics Data Collection (AM, RG, AB, YS, LD). Data analysis (RDS, LD). Manuscript writing (RDS, LD). Manuscript editing (RDS, JSN, YS, LD). Manuscript final approval (all authors). L Dercle work is funded by a grant from Fondation Philanthropia, Geneva, Switzerland and the Fondation Nuovo-Soldati.
Funding Information:
Patients Recruitment (CM, JCS, LHS, YS, CR). Clinical Data Collection (SA, AMP, FZM, GR, LB, LD). Imaging Data Collection (RDS, JSN, RY, LD). Transcriptomics Data Cost (AM, YS). Transcriptomics Data Collection (AM, RG, AB, YS, LD). Data analysis (RDS, LD). Manuscript writing (RDS, LD). Manuscript editing (RDS, JSN, YS, LD). Manuscript final approval (all authors). L Dercle work is funded by a grant from Fondation Philanthropia, Geneva, Switzerland and the Fondation Nuovo-Soldati.
Publisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2019/10/1
Y1 - 2019/10/1
N2 - 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.
AB - 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.
KW - FDG-PET/CT
KW - Immune checkpoint inhibitors
KW - Metabolic tumor burden
KW - Metastatic melanoma
KW - Prognosis
KW - Systemic inflammatory response
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UR - http://www.scopus.com/inward/citedby.url?scp=85069644192&partnerID=8YFLogxK
U2 - 10.1007/s00259-019-04411-7
DO - 10.1007/s00259-019-04411-7
M3 - Article
C2 - 31346755
AN - SCOPUS:85069644192
SN - 1619-7070
VL - 46
SP - 2298
EP - 2310
JO - European Journal of Nuclear Medicine and Molecular Imaging
JF - European Journal of Nuclear Medicine and Molecular Imaging
IS - 11
ER -