Abstract
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.
Highlights
Prognostic and diagnostic blood biomarkers will cost-effectively and with limited patient risk, enable early detection, disease stratification, and assessment of response to treatment; but, their low abundance and the complexity of blood make their discovery challenging [1]
An indicator cell assay was developed for pre-symptomatic detection of amyotrophic lateral sclerosis (ALS) in a transgenic SOD1 (G93A) mouse model of the disease [6]
Motor neurons were chosen as indicator cells because they are selectively degraded by ALS and have known responses to extrinsic signals of the disease [25]
Summary
Prognostic and diagnostic blood biomarkers will cost-effectively and with limited patient risk, enable early detection, disease stratification, and assessment of response to treatment; but, their low abundance and the complexity of blood make their discovery challenging [1]. We have established proof of concept for the iCAP (Fig 1), a platform that circumvents these issues by using cultured cells as biosensors, avoiding the need to directly analyze molecules in serum by capitalizing on the natural ability of cells to detect and integrate weak biological signals in noisy environments. Patient serum or plasma is applied to cultured indicator cells, the cells’ transcriptional response is measured, and computational models are used to identify disease state. Indicator cells are selected for each application and generally are related to the disease being detected.
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