Palmer Scott, Litvinova Karina, Rafailov Edik U, Nabi Ghulam
Division of Imaging and Technology, Ninewells Hospital, University of Dundee, Dundee, DD1 4HN UK.
Photonics and Nanoscience Group, Aston University, Birmingham, UK.
Biomed Opt Express. 2015 Feb 25;6(3):977-86. doi: 10.1364/BOE.6.000977. eCollection 2015 Mar 1.
The optical redox ratio as a measure of cellular metabolism is determined by an altered ratio between endogenous fluorophores NADH and flavin adenine dinucleotide (FAD). Although reported for other cancer sites, differences in optical redox ratio between cancerous and normal urothelial cells have not previously been reported. Here, we report a method for the detection of cellular metabolic states using flow cytometry based on autofluorescence, and a statistically significant increase in the redox ratio of bladder cancer cells compared to healthy controls. Urinary bladder cancer and normal healthy urothelial cell lines were cultured and redox overview was assessed using flow cytometry. Further localisation of fluorescence in the same cells was carried out using confocal microscopy. Multiple experiments show correlation between cell type and redox ratio, clearly differentiating between healthy cells and cancer cells. Based on our preliminary results, therefore, we believe that this data contributes to current understanding of bladder tissue fluorescence and can inform the design of endoscopic probes. This approach also has significant potential as a diagnostic tool for discrimination of cancer cells among shed urothelial cells in voided urine, and could lay the groundwork for an automated system for population screening for bladder cancer.
作为细胞代谢指标的光学氧化还原比，是由内源性荧光团烟酰胺腺嘌呤二核苷酸（NADH）和黄素腺嘌呤二核苷酸（FAD）之间的比例变化所决定的。尽管在其他癌症部位已有相关报道，但癌性与正常尿路上皮细胞之间的光学氧化还原比差异此前尚未见报道。在此，我们报告一种基于自发荧光通过流式细胞术检测细胞代谢状态的方法，以及与健康对照相比膀胱癌细胞氧化还原比有统计学意义的升高。培养膀胱癌细胞系和正常健康尿路上皮细胞系，并使用流式细胞术评估氧化还原概况。使用共聚焦显微镜对同一细胞中的荧光进行进一步定位。多项实验表明细胞类型与氧化还原比之间存在相关性，能清晰区分健康细胞和癌细胞。因此，基于我们的初步结果，我们认为这些数据有助于当前对膀胱组织荧光的理解，并可为内镜探头的设计提供参考。这种方法作为一种诊断工具，在鉴别排出尿液中脱落尿路上皮细胞中的癌细胞方面也具有巨大潜力，并可为膀胱癌群体筛查自动化系统奠定基础。
