LAUSR

Purpose The computed tomography fat attenuation index (FAI) is an ideal quantifiable imaging factor to identify the inflammation degree of peri-tumor adipose tissue. We aimed to verify whether FAI could reflect peri-tumor adipose inflammation, predict the survival outcome of renal cell carcinoma (RCC), and discover transcriptomic features of tumor tissues and adjacent adipocytes. Materials and Methods Two clinical cohorts (Fudan University Shanghai Cancer Center [FUSCC] cohort [n=129] and TCGA cohort [n=218]) were used to explore the association between FAI and clinical outcome. A prospective cohort (n = 19) was used to discover the molecular phenotyping of peri-tumor adipose tissue and tumor tissue according to their FAI value. A clinical cohort (n = 32) in which patients received cyto-reductive surgery was used to reveal the dynamic change of FAI. Results A high peri-tumor FAI was significantly associated with a worse outcome in both the FUSCC (HR = 2.28, p = 0.01) and the TCGA cohort (HR = 2.24, p <0.001). The analysis of the RNA expression of paired RCC tissue and peri-tumor fat tissue showed synchronized alterations in pathways such as cytokine–cytokine receptor interaction and complement and coagulation cascades. RCC tissues showed significant alterations in the neuroactive ligand–receptor interaction pathway. Immune deconvolution analysis showed enhanced infiltration of macrophages in high FAI tumor tissues with a lower angiogenesis level. We also observed synchronous dynamic changes in FAI and tumor size after targeted therapy. Conclusion In summary, FAI could be used in RCC to reflect the biological characteristics and tumor immune micro-environment of both the tumor and the peri-tumor adipose. High peri-tumor FAI had the potential to predict a worse survival outcome in various cohorts. This study demonstrates that the crosstalk exists between a tumor and its micro-environment and could be reflected easily by imaging procedures, which could facilitate clinical decision making.