Surface-Enhanced Raman Scattering Monitoring of Tryptophan Dynamics in 3D Pancreatic Tumor Models

In the intricate landscape of the tumor microenvironment, both cancer and stromal cells undergo rapid metabolic adaptations to support their growth. Given the relevant role of the metabolic secretome in fueling tumor progression, its unique metabolic characteristics have gained prominence as potential biomarkers and therapeutic targets. As a result, rapid and accurate tools have been developed to track metabolic changes in the tumor microenvironment with high sensitivity and resolution. Surface-enhanced Raman scattering (SERS) is a highly sensitive analytical technique and has been proven efficient toward the detection of metabolites in biological media. However, profiling secreted metabolites in complex cellular environments such as those in tumor-stroma 3D in vitro models remains challenging. To address this limitation, we employed a SERS-based strategy to investigate the metabolic secretome of pancreatic tumor models within 3D cultures. We aimed to monitor the immunosuppressive potential of stratified pancreatic cancer-stroma spheroids as compared to 3D cultures of either pancreatic cancer cells or cancer-associated fibroblasts, focusing on the metabolic conversion of tryptophan into kynurenine by the IDO-1 enzyme. We additionally sought to elucidate the dynamics of tryptophan consumption in correlation with the size, temporal evolution, and composition of the spheroids, as well as assessing the effects of different drugs targeting the IDO-1 machinery. As a result, we confirm that SERS can be a valuable tool toward the optimization of cancer spheroids, in connection with their tryptophan metabolizing capacity, potentially allowing high-throughput spheroid analysis.