Abstract
Immunometabolism within the tumor microenvironment is an appealing target for precision therapy approaches in lung cancer. Interestingly, obesity confers an improved response to immune checkpoint inhibition in non-small cell lung cancer (NSCLC), suggesting intriguing relationships between systemic metabolism and the immunometabolic environment in lung tumors. We hypothesized that visceral fat and 18F-Fluorodeoxyglucose uptake influenced the tumor immunometabolic environment and that these bidirectional relationships differ in NSCLC subtypes, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). By integrating 18F-FDG PET/CT imaging, bulk and single-cell RNA-sequencing, and histology, we observed that LUSC had a greater dependence on glucose than LUAD. In LUAD tumors with high glucose uptake, glutaminase was downregulated, suggesting a tradeoff between glucose and glutamine metabolism, while in LUSC tumors with high glucose uptake, genes related to fatty acid and amino acid metabolism were also increased. We found that tumor-infiltrating T cells had the highest expression of glutaminase, ribosomal protein 37, and cystathionine gamma-lyase in NSCLC, highlighting the metabolic flexibility of this cell type. Further, we demonstrate that visceral adiposity, but not body mass index (BMI), was positively associated with tumor glucose uptake in LUAD and that patients with high BMI had favorable prognostic transcriptional profiles, while tumors of patients with high visceral fat had poor prognostic gene expression. We posit that metabolic adjunct therapy may be more successful in LUSC rather than LUAD due to LUAD’s metabolic flexibility and that visceral adiposity, not BMI alone, should be considered when developing precision medicine approaches for the treatment of NSCLC.
Highlights
Lung cancer is one of the few tumor types that are not commonly associated with systemic metabolic dysregulation
We recently demonstrated in an analysis of positron emission tomography–computed tomography (PET-CT) images from The Cancer Imaging Archive (TCIA) that body mass index (BMI) correlated negatively with the lean body mass-corrected maximum standard uptake value (SUVmax) in NSCLC9, consistent with the prior epidemiologic data
Though we did not observe any differences in tumor-infiltrating leukocytes (TILs) fractions between the two subtypes, we aimed to examine whether any nuclear medicine features could provide insight into the immune cell subfraction in lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) (Fig. 5c–f)
Summary
Lung cancer is one of the few tumor types that are not commonly associated with systemic metabolic dysregulation. Studies of how body composition and tumor metabolism affect lung cancer outcomes have rarely differentiated between the subtypes of lung cancer, and even more rarely have differentiated between the subtypes of non-small cell lung cancer (NSCLC). This knowledge gap limits the possibilities of developing metabolic strategies to combat lung cancer using a precision medicine approach. Most commonly measured by positron emission tomography–computed tomography (PET-CT) with [18F]fluorodeoxyglucose (18F-FDG) in humans, has long been utilized as a marker of metabolic activity. Recent data in NSCLC has suggested that 18F-FDG does not correlate with glycolytic capacity per se but more closely with proliferation index[10], begging both a deeper and more comprehensive analysis of the metabolic pathways related to NSCLC nutrient metabolism
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