Correlation of 18F-FDG PET/CT metabolic parameters with the expression of immune biomarkers in the tumour microenvironment in lung adenocarcinoma

Abstract

To explore the association between metabolic parameters evaluated by integrated 2-[18F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET)/computed tomography (CT) and the expression of immune biomarkers in the tumour microenvironment in lung adenocarcinoma. This study included 134 patients. Metabolic parameters were obtained by PET/CT. Immunohistochemistry analysis was used for FOXP3-TILs (transcription factor forkhead box protein 3 tumour-infiltrating lymphocytes), CD8-TILs, CD4-TILs, CD68-TAMs (tumour-associated macrophages) and galectin-1 (Gal-1) tumour expression. There were significant positive associations between FDG PET metabolic parameters and the median percentage of immune reactive areas (IRA%) covered by FOXP3-TILs and CD68-TAMs. Negative associations with the median IRA% covered by CD4-TILs and CD8-TILs were observed: maximal standardised uptake value (SUVmax), metabolic tumour volume (MTV), total lesion glycolysis (TLG), and IRA% for FOXP3-TILs (rho=0.437, 0.400, 0.414; p<0.0001 for all parameters); SUVmax, MTV, TLG, and IRA% for CD68-TAMs (rho=0.356, 0.355, 0.354; p<0.0001 for all parameters); SUVmax, MTV, TLG, and IRA% for CD4-TILs (rho=-0.164, -0.190, -0.191; p=0.059, 0.028, 0.027, respectively); SUVmax, MTV, TLG, and IRA% for CD8-TILs (rho=-0.305, -0.316, -0.322; p<0.0001 for all parameters). There were significant positive associations between tumour Gal-1 expression and the median IRA% covered by FOXP3-TILs and CD68-TAMs (rho=0.379; p<0.0001; rho=0.370; p<0.0001, respectively), and a significant negative association with the median IRA% covered by CD8-TILs (rho=-0.347; p<0.0001) was observed. Tumour stage (p=0.008), Gal-1 expression (p=0.008), and median IRA% covered by CD8-TILs (p=0.054) were independent risk factors for overall survival. FDG PET may facilitate a comprehensive evaluation of the tumour microenvironment and predict response to immunotherapy.