Obesity is strongly linked with increased risk and poorer prognosis of endometrial cancer (EC). Cancer-associated fibroblasts (CAFs) are activated fibroblasts that form a large component of the tumor microenvironment and undergo metabolic reprogramming to provide critical metabolites for tumor growth. However, it is still unknown how obesity, characterized by a surplus of free fatty acids drives the modifications of CAFs lipid metabolism which may provide the mechanistic link between obesity and EC progression. The present study aims to evaluate the utility of Raman spectroscopy, an emerging nondestructive analytical tool to detect signature changes in lipid metabolites of CAFs from EC patients with varying body mass index. We established primary cultures of fibroblasts from human EC tissues, and CAFs of overweight/obese and nonobese women using antibody-conjugated magnetic beads isolation. These homogeneous fibroblast cultures expressed fibroblast markers, including α-smooth muscle actin and vimentin. Analysis was made in the Raman spectra region best associated with cancer progression biochemical changes in lipids (600-1800 cm and 2800-3200 cm). Direct band analysis and ratiometric analysis were conducted to extract information from the Raman spectrum. Present results demonstrated minor shifts in the CH symmetric stretch of lipids at 2879 cm and CH asymmetric stretching from protein at 2932 cm in the overweight/obese CAFS compared to nonobese CAFs, indicating increased lipid content and a higher degree of lipid saturation. Principal component analysis showed that CAFs from overweight/obese and nonobese EC patients can be clearly distinguished indicating the capability of Raman spectroscopy to detect changes in biochemical components. Our results suggest Raman spectroscopy supported by chemometric analysis is a reliable technique for characterizing metabolic changes in clinical samples, providing an insight into obesity-driven alteration in CAFs, a critical stromal component during EC tumorigenesis.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1177/00037028231182721 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!