NEW YORK (GenomeWeb) – Startup PreCyte has received a two-year grant worth nearly $2 million from the National Institutes of Health to validate and optimize a technology that uses cultured cells to detect blood-based biomarkers for Alzheimer's disease.
With the Direct-to-Phase II Small Business Innovation Research grant, PreCyte aims to test the so-called Indicator Cell Assay Platform, or ICAP, in hundreds of blood samples from presymptomatic and early-stage Alzheimer's disease patients, as well as normal controls.
Through this work, the company hopes to refine a disease classifier developed in previous experiments to enable ICAP to differentiate between the these two types of Alzheimer's disease and distinguish the disease from other forms of dementia based on the expression signatures of roughly 100 undisclosed genes.
If it is successful in this phase of developing the classifier, PreCyte aims to then commercialize the test, either through a partnership with a bigger company or on its own, and begin work on additional diagnostics based on the ICAP technology, Co-founder and CEO Robert Lipshutz told GenomeWeb.
Seattle-based PreCyte was founded in early 2014 to commercialize ICAP, which was originally developed at the Institute for Systems Biology in the lab of John Aitchison, a company co-founder and scientific advisory board member. The ISB exclusively licensed the technology to PreCyte.
While specific details about the platform are being kept under wraps pending an upcoming peer-reviewed publication, it essentially involves exposing cultured cells to patient serum, then analyzing the transcriptional effect.
While significant advances have been made in recent years around blood-based biomarkers, most approaches rely on direct detection of these molecules. "But it's turning out that direct detection of biomolecules in serum is a hard problem because many of the biomarkers … are of low abundance," according to PreCyte Co-founder and Principal Scientist Jennifer Smith, who helped develop ICAP while at the ISB.
"With existing instrumentation, it is very difficult to discover molecules at low quantities in a noisy environment, let alone survey all of the molecules at that level for a panel of biomarkers," she said. "Instead of developing a very sensitive instrument, [we are] capitalizing on what nature has already developed."
In preliminary studies using a small number of blood samples, ICAP was able to distinguish either presymptomatic Alzheimer's disease patients or ones with early-stage disease from normal controls with 77 to 82 percent accuracy, according to PreCyte's grant abstract.
Over the next two years, the company aims to improve the assay and the classifier for distinguishing these three sample classes and to validate it in a larger number of prospectively collected serum samples. Doing so will involving identifying the optimal indicator neuronal cells and experimental conditions for their use; using newly generated data to train and test an optimized classifier that can also distinguish Alzheimer's disease from other types of dementia; and testing the new classifier in extended cohorts from different clinical sources.
This work will be done in collaboration with the ISB and various other academic centers.
Smith said that a final classifier is expected to be based around the expression of roughly 100 genes. The company aims to be able to differentiate presymptomatic and early-stage Alzheimer's disease with a predictive accuracy of 90 percent, and 90 percent sensitivity and specificity.
She noted that while ICAP currently uses next-generation sequencing to capture the transcriptional responses of indicator cells, in the future the platform may be adapted to use fluorescent reports to proteins encoded by target genes.