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Introduction: Preclinical evidence suggests that host obesity is associated with tumor progression due to immuno-metabolic dysfunction, but the impact of obesity on immunity and clinical outcomes in patients is poorly understood, with some studies suggesting an obesity paradox. We recently reported that high-adiposity and low-muscle body composition phenotypes are associated with striking increases in epithelial ovarian cancer (EOC) mortality and we observed no evidence of an obesity paradox. However, whether at-risk versus optimal body composition phenotypes are associated with distinct immuno-metabolic milieus remains a fundamental gap in knowledge. Herein, we defined differentially abundant circulating immuno-metabolic biomarkers according to body composition phenotypes in EOC. Methods: Muscle and adiposity cross-sectional area (cm2) was assessed using CT images from 200 EOC patients in The Body Composition and Epithelial Ovarian Cancer Survival Study at Roswell Park. Adiposity was dichotomized as low versus high; patients with skeletal muscle index (SMI) <38.5 (muscle cm2/height m2) were classified as low SMI (sarcopenia). Joint-exposure phenotypes were categorized as: Fit (normal SMI/low-adiposity), Overweight/Obese (normal SMI/high-adiposity), Sarcopenia/Obese (low SMI/high adiposity), and Sarcopenia/Cachexia (low SMI/low-adiposity). Treatment-naïve serum samples were assessed using Biocrates MxP Quant 500 for targeted metabolomics and commercially available Luminex kits for adipokines and Th1/Th2 cytokines. Limma moderated T-tests were used to identify differentially abundant metabolites and cytokines according to body composition phenotypes. Results: Patients with 'risk' phenotypes had significantly increased abundance of metabolites and cytokines that were unique according to body composition phenotype. Specifically, the metabolites and cytokines in increased abundance in the at-risk phenotypes are implicated in immune suppression and tumor progression. Conversely, increased abundance of lauric acid, IL-1β, and IL-2 in the Fit phenotype was observed, which have been previously implicated in tumor suppression and anti-tumor immunity. Conclusion: In this pilot study, we identified several significantly differentially abundant metabolites according to body composition phenotypes, confirming that clinically significant joint-exposure body composition phenotypes are also biologically distinct. Although we observed evidence that at-risk phenotypes were associated with increased abundance of immuno-metabolic biomarkers indicated in immune suppression, additional confirmatory studies focused on defining the link between body composition and immune cell composition and spatial relationships in the EOC tumor microenvironment are warranted. [ABSTRACT FROM AUTHOR]

Background: The effect of differing post-contrast phases on CT body composition measurements is not yet known. Methods: A fully automated AI-based body composition analysis using DAFS was performed on a retrospective cohort of 278 subjects undergoing pre-treatment triple-phase CT for pancreatic intraductal papillary mucinous neoplasm. The CT contrast phases included noncontrast (NON), arterial (ART), and venous (VEN) phases. The software selected a single axial CT image at mid-L3 on each phase for body compartment segmentation. The areas (cm2) were calculated for skeletal muscle (SM), intermuscular adipose tissue (IMAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). The mean Hounsfield units of skeletal muscle (SMHU) within the segmented regions were calculated. Bland–Altman and Chi Square analyses were performed. Results: SM-NON had a lower percentage of bias [LOA] than SM-ART, −0.7 [−7.6, 6.2], and SM-VEN, −0.3 [−7.6, 7.0]; VAT-NON had a higher percentage of bias than ART, 3.4 [−18.2, 25.0], and VEN, 5.8 [−15.0, 26.6]; and this value was lower for SAT-NON than ART, −0.4 [−14.9, 14.2], and VEN, −0.5 [−14.3, 13.4]; and higher for IMAT-NON than ART, 5.9 [−17.9, 29.7], and VEN, 9.5 [−17.0, 36.1]. The bias in SMHU NON [LOA] was lower than that in ART, −3.8 HU [−9.8, 2.1], and VEN, −7.8 HU [−14.8, −0.8]. Conclusions: IV contrast affects the voxel HU of fat and muscle, impacting CT analysis of body composition. We noted a relatively smaller bias in the SM, VAT, and SAT areas across the contrast phases. However, SMHU and IMAT experienced larger bias. During threshold risk stratification for CT-based measurements of SMHU and IMAT, the IV contrast phase should be taken into consideration. [ABSTRACT FROM AUTHOR]

Background The association of body composition with epithelial ovarian carcinoma (EOC) mortality is poorly understood. To date, evidence suggests that high adiposity is associated with decreased mortality (an obesity paradox), but the impact of muscle on this association has not been investigated. Herein, we define associations of muscle and adiposity joint-exposure body composition phenotypes with EOC mortality. Methods Body composition from 500 women in the Body Composition and Epithelial Ovarian Cancer Survival Study was dichotomized as normal or low skeletal muscle index (SMI), a proxy for sarcopenia, and high or low adiposity. Four phenotypes were classified as fit (normal SMI and low adiposity; reference; 16.2%), overweight or obese (normal SMI and high adiposity; 51.2%), sarcopenia and overweight or obese (low SMI and high adiposity; 15.6%), and sarcopenia or cachexia (low SMI and low adiposity; 17%). We used multivariable Cox models to estimate associations of each phenotype with mortality for EOC overall and high-grade serous ovarian carcinoma (HGSOC). Results Overweight or obesity was associated with up to 51% and 104% increased mortality in EOC and HGSOC [Hazard Ratio (HR)] = 1.51, 95% CI = 1.05 to 2.19 and HR = 2.04, 95% CI = 1.29 to 3.21). Sarcopenia and overweight or obesity was associated with up to 66% and 67% increased mortality in EOC and HGSOC (HR = 1.66, 95% CI = 1.13 to 2.45 and HR = 1.67, 95% CI = 1.05 to 2.68). Sarcopenia or cachexia was associated with up to 73% and 109% increased mortality in EOC and HGSOC (HR = 1.73, 95% CI = 1.14 to 2.63 and HR = 2.09, 95% CI = 1.25 to 3.50). Conclusions Overweight or obesity, sarcopenia and overweight or obesity, and sarcopenia or cachexia phenotypes were each associated with increased mortality in EOC and HGSOC. Exercise and dietary interventions could be leveraged as ancillary treatment strategies for improving outcomes in the most fatal gynecological malignancy with no previously established modifiable prognostic factors. [ABSTRACT FROM AUTHOR]