SBIR Phase I: SERS Enhanced Ligase Detection Reaction Chip for the Molecular Diagnosis of Cancer

Period of Performance: 01/01/2011 - 12/31/2011


Phase 1 SBIR

Recipient Firm

2438 Slaterville Road
Slaterville Springs, NY 14881
Principal Investigator


This Small Business Innovation Research (SBIR) Phase I project proposes to develop an entirely new platform for the molecular diagnostics of cancer exploiting a new Surface Enhanced Raman Scattering (SERS) enhanced Ligase Detection Reaction (LDR) and an optically active microfluidic chip. Since every dye has a unique Raman fingerprint, the number of single nucleotide polymorphisms (SNPs) that can be screened for in parallel is dramatically increased due to lower spectral overlap. The goal for the Phase I work is to develop a set of target-specific LDR probes in a 6-plex format that would match the current state-of-the-art. For future work, we will develop an assay for a 12-plex format that will double the number of targets that can be screened in one sample using this fluorescence-based technology. In parallel with the development of the screening reaction, we will create a novel "optofluidic" chip that addresses the challenges with on-chip Raman signal detection. The primary advantage of the proposed approach is that it avoids the fundamental limitation of the existing state-of-the-art, Real-Time Polymerase Chain Reaction, by detecting the Raman fingerprint of the dye rather than the florescence emission. The broader impact/commercial potential of this project is the ability to screen for a greater number of single nucleotide polymorphisms (SNPs) without sacrificing speed and ease-of-use, which may enable more rapid molecular diagnosis of cancer and other genetic diseases. In some cases, SNPs are biomarkers implied in the cause of cancer while in others they represent markers indicative of an increased risk of cancer. In either case, SNPs have been shown to be good biomarkers for many classes of cancer and have further been shown to correlate with various clinicopathological features of different cancer subtypes. Of the many technologies available for SNP diagnostics, Real-Time PCR (RT-PCR) is the most appropriate for clinical diagnosis in that it requires the smallest amount of physical sample and sample preparation; however, it is limited in terms of the number of SNPs that can be screened at one time. The approach we propose will potentially double the number of SNPs that can be screened in a single sample. This advantage is particularly important in cases where the biopsied sample is not homogeneous.