Cano Álvaro, Yubero Marina L, Millá Carmen, Puerto-Belda Verónica, Ruz Jose J, Kosaka Priscila M, Calleja Montserrat, Malumbres Marcos, Tamayo Javier
Bionanomechanics Lab, Instituto de Micro y Nanotecnología, IMN-CNM (CSIC), Tres Cantos, Madrid, Spain.
Cancer Cell Cycle Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain.
iScience. 2024 Oct 4;27(11):110960. doi: 10.1016/j.isci.2024.110960. eCollection 2024 Nov 15.
Predicting the phenotypic impact of genetic variants and treatments is crucial in cancer genetics and precision oncology. Here, we have developed a noise decorrelation method that enables quantitative phase imaging (QPI) with the capability for label-free noninvasive mapping of intracellular dry mass fluctuations within the millisecond-to-second timescale regime, previously inaccessible due to temporal phase noise. Applied to breast cancer cells, this method revealed regions driven by thermal forces and regions of intense activity fueled by ATP hydrolysis. Intriguingly, as malignancy increases, the cells strategically expand these active regions to satisfy increasing energy demands. We propose parameters encapsulating key information about the spatiotemporal distribution of intracellular fluctuations, enabling precise phenotyping. This technique addresses the need for accurate, rapid functional screening methods in cancer medicine.
预测基因变异和治疗的表型影响在癌症遗传学和精准肿瘤学中至关重要。在此,我们开发了一种噪声去相关方法,该方法能够实现定量相位成像(QPI),具备在毫秒到秒的时间尺度范围内对细胞内干质量波动进行无标记非侵入性映射的能力,而此前由于时间相位噪声,这一范围是无法实现的。将该方法应用于乳腺癌细胞时,发现了由热力驱动的区域以及由ATP水解提供能量的活跃区域。有趣的是,随着恶性程度增加,细胞会策略性地扩展这些活跃区域以满足不断增长的能量需求。我们提出了一些参数,这些参数封装了有关细胞内波动时空分布的关键信息,从而能够进行精确的表型分析。这项技术满足了癌症医学中对准确、快速功能筛选方法的需求。