Adipose tissue metabolic profile and the correlation with cachexia in patients with gastric cancer.

• Grant number: 25/02631-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: April 01, 2025
• End date: March 31, 2026
• Field of knowledge: Health Sciences - Medicine - Medical Clinics
• Principal Investigator: José Barreto Campello Carvalheira
• Grantee: Bárbara Zanette Cipriano
• Host Institution: Centro de Hematologia e Hemoterapia (HEMOCENTRO). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 21/10265-8 - Cancer Theranostics Innovation Center (CancerThera), AP.CEPID

Abstract

Body composition is a key determinant in the prognosis of patients with gastric cancer and is often associated with cachexia, a complex metabolic syndrome. Adipose tissue radiodensity, measured by computed tomography (CT), has been identified as an emerging biomarker in cancer prognosis. Additionally, the uptake of 18F-fluorodeoxyglucose (FDG) by positron emission tomography combined with CT (PET/CT-FDG) reflects the metabolic activity of adipose tissue and may be related to inflammation and glucose metabolism. Our group has demonstrated that adipose tissue radiodensity positively correlates with glucose uptake in subcutaneous adipose tissue in patients with multiple myeloma. Based on this, we hypothesize that metabolically more active adipocytes and the browning of white adipose tissue may contribute to increased radiodensity and FDG uptake, potentially serving as biomarkers of cancer cachexia. This cross-sectional study will evaluate patients with gastric cancer treated at the Hospital de Clínicas da Unicamp, correlating cachexia criteria (GLIM and Fearon) with the metabolic characteristics of adipose tissue, including radiodensity (CT) and glucose uptake (PET/CT-FDG). Clinical, anthropometric, and laboratory data will be collected, along with assessments of body composition and systemic inflammation. Statistical analysis will include group comparison tests and univariate and multivariate regression models to identify correlations between the evaluated parameters. This study may contribute to the identification of new cachexia biomarkers and a better understanding of the metabolic mechanisms underlying gastric cancer progression.