bioRxiv | 2021

Multimodal Analysis Reveals Differential Immuno-Metabolic Features in Lung Squamous Cell Carcinoma and Adenocarcinoma

 
 
 
 
 
 

Abstract


Background The relationship between systemic metabolism, immune function, and lung cancer is complex and remains poorly defined. Seemingly paradoxically, overweight and obesity confer an improved response to immune checkpoint inhibition in non-small cell lung cancer (NSCLC); however, it is not known whether excess body weight or adiposity impacts the immunometabolic tumor microenvironment. Methods Utilizing three complementary National Cancer Institute-funded open-source databases containing 18F-fluorodeoxyglucose positron-emission tomography/computed tomography (PET-CT) images for tumor and tissue glucose uptake, adipose tissue and skeletal muscle mass, histology annotated with tumor infiltrating leukocytes, and tumor RNA sequencing, we performed a retrospective cross-sectional analysis to examine phenotypic, metabolic, and genomic intersections of adiposity and tumor immune-metabolism in patients with lung adenocarcinoma (LUAD) versus squamous cell carcinoma (LUSC). Results Our data reveal distinct immunometabolomic features of LUSC as compared to LUAD: visceral fat content was negatively correlated with both tumor glucose uptake and leukocyte infiltration. Subcutaneous and visceral adiposity conferred different effects on the tumor genetic landscapes in both tumor types. LUSC tumors showed greater gene expression pathways related to pyruvate, glucose, amino acid, and lipid metabolism, in addition to significantly greater 18F-FDG uptake compared with LUAD, suggesting deeper metabolic regulation within the LUSC tumor microenvironment. Conclusions Several immunometabolomic characteristics of LUSC and LUAD differ, including tumor glucose uptake and the associated metabolic pathways in the tumor, as well as the impact of visceral adiposity on tumor metabolism. These data may highlight opportunities to advance mechanistically targeted precision medicine approaches by better understanding the interplay between metabolic, immunologic, and genomic factors in lung cancer treatment.

Volume None
Pages None
DOI 10.1101/2021.05.09.443240
Language English
Journal bioRxiv

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