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Surface-Enhanced Raman Scattering Monitoring of Tryptophan Dynamics in 3D Pancreatic Tumor Models
ACS Sensors ( IF 8.2 ) Pub Date : 2024-07-19 , DOI: 10.1021/acssensors.4c01210 Pablo S Valera 1, 2, 3, 4 , Margarida Henriques-Pereira 5 , Marita Wagner 1, 4, 6 , Vítor M Gaspar 5 , João F Mano 5 , Luis M Liz-Marzán 1, 2, 7, 8
ACS Sensors ( IF 8.2 ) Pub Date : 2024-07-19 , DOI: 10.1021/acssensors.4c01210 Pablo S Valera 1, 2, 3, 4 , Margarida Henriques-Pereira 5 , Marita Wagner 1, 4, 6 , Vítor M Gaspar 5 , João F Mano 5 , Luis M Liz-Marzán 1, 2, 7, 8
Affiliation
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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.
中文翻译：
3D 胰腺肿瘤模型中色氨酸动力学的表面增强拉曼散射监测
在复杂的肿瘤微环境中，癌症和基质细胞都会经历快速的代谢适应以支持其生长。鉴于代谢分泌组在促进肿瘤进展中的相关作用，其独特的代谢特征作为潜在的生物标志物和治疗靶点而受到关注。因此，已经开发出快速、准确的工具来以高灵敏度和分辨率追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，已被证明可有效检测生物介质中的代谢物。然而，分析复杂细胞环境（例如肿瘤基质 3D体外模型中的分泌代谢物）仍然具有挑战性。为了解决这一限制，我们采用基于 SERS 的策略来研究 3D 培养物中胰腺肿瘤模型的代谢分泌组。我们的目的是监测分层胰腺癌基质球体与胰腺癌细胞或癌症相关成纤维细胞的 3D 培养物相比的免疫抑制潜力，重点关注 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的动态与球体的大小、时间演化和组成的相关性，并评估针对 IDO-1 机制的不同药物的作用。因此，我们确认 SERS 可以成为优化癌症球体的一个有价值的工具，与它们的色氨酸代谢能力有关，有可能允许高通量球体分析。
更新日期：2024-07-19
中文翻译：
3D 胰腺肿瘤模型中色氨酸动力学的表面增强拉曼散射监测
在复杂的肿瘤微环境中，癌症和基质细胞都会经历快速的代谢适应以支持其生长。鉴于代谢分泌组在促进肿瘤进展中的相关作用，其独特的代谢特征作为潜在的生物标志物和治疗靶点而受到关注。因此，已经开发出快速、准确的工具来以高灵敏度和分辨率追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，已被证明可有效检测生物介质中的代谢物。然而，分析复杂细胞环境（例如肿瘤基质 3D体外模型中的分泌代谢物）仍然具有挑战性。为了解决这一限制，我们采用基于 SERS 的策略来研究 3D 培养物中胰腺肿瘤模型的代谢分泌组。我们的目的是监测分层胰腺癌基质球体与胰腺癌细胞或癌症相关成纤维细胞的 3D 培养物相比的免疫抑制潜力，重点关注 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的动态与球体的大小、时间演化和组成的相关性，并评估针对 IDO-1 机制的不同药物的作用。因此，我们确认 SERS 可以成为优化癌症球体的一个有价值的工具，与它们的色氨酸代谢能力有关，有可能允许高通量球体分析。
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