Faculty of Physics, M. V. Lomonosov Moscow State University, 119991 Moscow, Russia.
Institute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 603005 Nizhny Novgorod, Russia.
Proc Natl Acad Sci U S A. 2022 Mar 1;119(9). doi: 10.1073/pnas.2118241119.
Molecular, morphological, and physiological heterogeneity is the inherent property of cells which governs differences in their response to external influence. Tumor cell metabolic heterogeneity is of a special interest due to its clinical relevance to tumor progression and therapeutic outcomes. Rapid, sensitive, and noninvasive assessment of metabolic heterogeneity of cells is a great demand for biomedical sciences. Fluorescence lifetime imaging (FLIM), which is an all-optical technique, is an emerging tool for sensing and quantifying cellular metabolism by measuring fluorescence decay parameters of endogenous fluorophores, such as NAD(P)H. To achieve accurate discrimination between metabolically diverse cellular subpopulations, appropriate approaches to FLIM data collection and analysis are needed. In this paper, the unique capability of FLIM to attain the overarching goal of discriminating metabolic heterogeneity is demonstrated. This has been achieved using an approach to data analysis based on the nonparametric analysis, which revealed a much better sensitivity to the presence of metabolically distinct subpopulations compared to more traditional approaches of FLIM measurements and analysis. The approach was further validated for imaging cultured cancer cells treated with chemotherapy. These results pave the way for accurate detection and quantification of cellular metabolic heterogeneity using FLIM, which will be valuable for assessing therapeutic vulnerabilities and predicting clinical outcomes.
分子、形态和生理异质性是细胞的固有特性，决定了它们对外界影响的反应差异。肿瘤细胞代谢异质性是一个特别值得关注的问题，因为它与肿瘤的进展和治疗效果有临床相关性。快速、敏感和非侵入性地评估细胞代谢异质性是生物医学科学的一大需求。荧光寿命成像（FLIM）是一种全光学技术，是一种新兴的工具，通过测量内源性荧光团（如 NAD(P)H）的荧光衰减参数来感知和量化细胞代谢。为了实现对代谢多样化细胞亚群的准确区分，需要采用适当的 FLIM 数据采集和分析方法。本文展示了 FLIM 实现区分代谢异质性这一总体目标的独特能力。这是通过基于非参数分析的数据分析方法实现的，与更传统的 FLIM 测量和分析方法相比，该方法对代谢不同的亚群的存在具有更高的敏感性。该方法进一步在对接受化疗的培养癌细胞进行成像的实验中得到了验证。这些结果为使用 FLIM 准确检测和量化细胞代谢异质性铺平了道路，这对于评估治疗的脆弱性和预测临床结果将是非常有价值的。
