Rapid Electronic Detection of Cell Surface Proteins

Period of Performance: 01/01/2000 - 12/31/2000

$130K

Phase 1 SBIR

Recipient Firm

Minerva Biotechnologies Corporation
Waltham, MA 02451
Principal Investigator

Abstract

Minerva Biotechnologies will develop MEMS (microelectronic micromechanical systems) technology to electronically detect and quantitate proteins on the surface of an intact cell and screen for drugs to block them. Preliminary results indicate that the technology can be used to quantitate proteins on the surface of a single cell (100 molecule detection): a level not possible with existing technology. Our approach would allow more accurate assessment of how protein expression is altered, on the surface of cancer cells, and eliminate uncertainties introduced by large heterogeneous cell populations. We will extend the system so that proteins on the surface of cells embedded in a tumor section can be electronically analyzed, in situ. Each sector (dimensions similar to a cell) of the, tissue specimen could be analyzed for protein content and expression level, then correlated with histopathology. This capability will ensure the relevance of single cell analysis because it will enable the researcher to identify protein patterns that are associated with cancer cells and discard random aberrant protein expression. Capability to quantitate tumor markers will help clinicians assess prognosis and predict response to therapy. The electronics of the technology are inexpensive and miniaturizable, making it compatible with either basic research or clinical settings. PROPOSED COMMERCIAL APPLICATIONS: The technology we are seeking SBIR funding to develop will allow for the cheap, rapid and ultra-sensitive detection of proteins on the surface of intact cells. The technology is immediately applicable to cancer diagnosis and the monitoring of response to therapy . The same technology can be massively multiplexed using computer microelectronics for screening of anti-cancer drug candidates on cells and for the identification of likely anti-cancer drug targets by identifying interacting receptors and ligands.