Department of Pathology, SUNY Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, 11203, USA.
Photon Migration Technologies Corp, 15 Cherry Lane, Glen Head, NY, 11545, USA.
Sci Rep. 2023 Oct 25;13(1):18257. doi: 10.1038/s41598-023-43694-7.
Precision medicine currently relies on a mix of deep phenotyping strategies to guide more individualized healthcare. Despite being widely available and information-rich, physiological time-series measures are often overlooked as a resource to extend insights gained from such measures. Here we have explored resting-state hemoglobin measures applied to intact whole breasts for two subject groups - women with confirmed breast cancer and control subjects - with the goal of achieving a more detailed assessment of the cancer phenotype from a non-invasive measure. Invoked is a novel ordinal partition network method applied to multivariate measures that generates a Markov chain, thereby providing access to quantitative descriptions of short-term dynamics in the form of several classes of adjacency matrices. Exploration of these and their associated co-dependent behaviors unexpectedly reveals features of structured dynamics, some of which are shown to exhibit enzyme-like behaviors and sensitivity to recognized molecular markers of disease. Thus, findings obtained strongly indicate that despite the use of a macroscale sensing method, features more typical of molecular-cellular processes can be identified. Discussed are factors unique to our approach that favor a deeper depiction of tissue phenotypes, its extension to other forms of physiological time-series measures, and its expected utility to advance goals of precision medicine.
精准医学目前依赖于混合的深度表型策略来指导更个体化的医疗。尽管广泛可用且信息丰富，但生理时间序列测量通常被忽视为一种资源，可以扩展从这些测量中获得的见解。在这里，我们探索了应用于完整乳房的静息状态血红蛋白测量，针对两个实验组 - 确诊乳腺癌的女性和对照组 - 旨在从非侵入性测量中更详细地评估癌症表型。我们引入了一种应用于多变量测量的新颖有序分区网络方法，该方法生成了一个马尔可夫链，从而可以以几种邻接矩阵的形式获取短期动力学的定量描述。对这些邻接矩阵及其相关的相依行为的探索出人意料地揭示了结构动力学的特征，其中一些特征表现出酶样行为，并且对疾病的公认分子标记物敏感。因此，研究结果强烈表明，尽管使用了宏观传感方法，但仍可以识别出更典型的分子-细胞过程的特征。本文讨论了我们方法中特有的有利于更深入描述组织表型的因素，将其扩展到其他形式的生理时间序列测量的因素，以及它在推进精准医学目标方面的预期效用。
