Automated molecular diagnosis on fine needle aspirates (FNA)

NIH RePORTER · NIH · R43 · $400,000 · view on reporter.nih.gov ↗

Abstract

Molecular analyses of cancer cells are essential in establishing diagnoses and guiding available treatments. Conventional tissue biopsies, while providing key information on tissue architecture, are associated with morbidity and high cost and therefore are not performed as frequently as would be clinically desirable. An alternative to cutting core biopsy guns are fine needle aspirations (FNAs), which can be performed with minimal intervention and allow for less invasive and/or repeated sampling from small lesions. However, workup of FNA specimens remains challenging using conventional cytology and immunohistochemistry. To address these barriers, Aikili Biosystems seeks to enable same-day diagnostic workup of FNA samples using a proprietary “FAST” assay and automated image cytometer. A key component of Aikili's technology is our proprietary cell cycling method (FAST), which builds upon and expands previous assay capabilities (4- channel multiplexing) to over 20-40 biomarkers; it is coupled with our image cytometer, a stand-alone diagnostic platform capable of automated cancer cell classification in <2 hours. Building upon initial development and pre-clinical validation, in Aim 1, we will validate FAST antibody probes in >15 cancer markers, integrate sample processing with Aikili's cytometry system and analyze associated images using the device. In Aim 2, we will evaluate the benefit of the integrated technology for rapid, same-day analysis of clinical samples, specifically lymphoma FNA samples (n = 40) stained with FAST-linker modified antibody probes. Phase I will be deemed successful when Aikili's system reliably detects and classifies lymphoma cells compared to gold standards. Successful completion of Phase I will lay the foundation for a Phase II application for clinical testing and manufacture of cytometry systems and commercial cartridges for multiple cancers. This platform has potential to transform cellular diagnostics and pathology workflows through rapid, same-day analyses of minimally invasive FNAs; its robust analyses of pharmacodynamic markers has potential to enable development of new, clinically meaningful biomarkers that can be used to advance drug development.

Key facts

NIH application ID
10323396
Project number
1R43CA265442-01
Recipient
AIKILI BIOSYSTEMS INC.
Principal Investigator
Laura E Kelley
Activity code
R43
Funding institute
NIH
Fiscal year
2021
Award amount
$400,000
Award type
1
Project period
2021-08-01 → 2024-01-31