Danziger Samuel A, Miller Leslie R, Singh Karanbir, Whitney G Adam, Peskind Elaine R, Li Ge, Lipshutz Robert J, Aitchison John D, Smith Jennifer J
Institute for Systems Biology, Seattle, WA, United States of America.
Center for Infectious Disease Research (formerly Seattle Biomedical Research Institute), Seattle, WA, United States of America.
PLoS One. 2017 Jun 8;12(6):e0178608. doi: 10.1371/journal.pone.0178608. eCollection 2017.
We have established proof of principle for the Indicator Cell Assay Platform™ (iCAP™), a broadly applicable tool for blood-based diagnostics that uses specifically-selected, standardized cells as biosensors, relying on their innate ability to integrate and respond to diverse signals present in patients' blood. To develop an assay, indicator cells are exposed in vitro to serum from case or control subjects and their global differential response patterns are used to train reliable, disease classifiers based on a small number of features. In a feasibility study, the iCAP detected pre-symptomatic disease in a murine model of amyotrophic lateral sclerosis (ALS) with 94% accuracy (p-Value = 3.81E-6) and correctly identified samples from a murine Huntington's disease model as non-carriers of ALS. Beyond the mouse model, in a preliminary human disease study, the iCAP detected early stage Alzheimer's disease with 72% cross-validated accuracy (p-Value = 3.10E-3). For both assays, iCAP features were enriched for disease-related genes, supporting the assay's relevance for disease research.
我们已经确立了指标细胞检测平台(iCAP™)的原理证明,这是一种广泛适用的基于血液诊断的工具,它使用经过特定选择的标准化细胞作为生物传感器,依靠其整合并响应患者血液中各种信号的固有能力。为开发一种检测方法,将指标细胞在体外暴露于病例或对照受试者的血清中,其整体差异反应模式用于基于少量特征训练可靠的疾病分类器。在一项可行性研究中,iCAP在肌萎缩侧索硬化症(ALS)小鼠模型中检测到症状前疾病,准确率达94%(p值=3.81E-6),并正确将来自小鼠亨廷顿病模型的样本鉴定为非ALS携带者。除了小鼠模型,在一项初步的人类疾病研究中,iCAP检测早期阿尔茨海默病的交叉验证准确率为72%(p值=3.10E-3)。对于这两种检测方法,iCAP特征都富集了疾病相关基因,支持该检测方法与疾病研究的相关性。