在复杂的肿瘤微环境中,癌细胞和基质细胞都经历了快速的代谢适应以支持它们的生长。鉴于代谢分泌组在促进肿瘤进展中的相关作用,其独特的代谢特征已成为潜在的生物标志物和治疗靶点。因此,已开发出快速准确的工具,以高灵敏度和高分辨率跟踪肿瘤微环境中的代谢变化。表面增强拉曼散射(SERS)是一种高度灵敏的分析技术,已被证明对检测生物介质中的代谢物有效。然而,在复杂的细胞环境中,例如在肿瘤基质3D体外模型中,分析分泌的代谢物仍然具有挑战性.为了解决这个限制,我们采用了基于SERS的策略来研究3D培养中胰腺肿瘤模型的代谢分泌组.我们旨在监测与胰腺癌细胞或癌症相关成纤维细胞的3D培养物相比,分层胰腺癌基质球体的免疫抑制潜力。专注于通过IDO-1酶将色氨酸代谢转化为犬尿氨酸。我们还试图阐明色氨酸消耗与大小相关的动态,时间演变,和球体的组成,以及评估针对IDO-1机制的不同药物的效果。因此,我们确认SERS可以成为优化癌症球体的有价值的工具,与它们的色氨酸代谢能力有关,可能允许高通量球体分析。
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.