High Throughput Method to Assess SNP Functionality in Prostate Cancer

Award Information
Agency:
Department of Health and Human Services
Branch
n/a
Amount:
$297,818.00
Award Year:
2011
Program:
SBIR
Phase:
Phase I
Contract:
1R43CA163405-01
Agency Tracking Number:
R43CA163405
Solicitation Year:
2011
Solicitation Topic Code:
NCI
Solicitation Number:
CA10-013
Small Business Information
ILLUMAVISTA BIOSCIENCES, LLC
510 Charmany Drive Suite 57, MADISON, WI, 53719-1266
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
Y
Duns:
832458363
Principal Investigator:
CHRISTOPHER WARREN
(608) 206-1226
cwarren@illumavista.com
Business Contact:
SXATKOWSKI MARY
(608) 206-1226
mozers@illumavista.com
Research Institution:
Stub




Abstract
DESCRIPTION (provided by applicant): A critical unmet need in implementing personalized medicine is the ability to sort through the millions of single nucleotide polymorphisms (SNPs) present in the human genome and to pinpoint which of these DNA variations are causative in disease. A key under-studied function of SNPs is their ability to generate or disrupt genomic binding sites for transcription factors involved in cancer. Toward this goal, we are inventing the SNP-SNAP (Specificity and Affinity for Proteins) microarray as a prototype high throughput device to evaluate SNP function. The SNP-SNAP arrays will be used to display a quarter-million prostate cancer- related SNPs as double-stranded DNA molecules and to assay transcription factors (i.e., drug targets) for their binding to these SNP DNA sequences. The resulting data will be correlated with prostate cancer incidence. The million-plus data points from the SNP-SNAP arrays will be analyzed using SNP-Sequence Specificity Landscapes, creating a prostate cancer molecular signature that relates transcription factor binding, SNP preferences, and chromosomal position of the nearest genes. Our findings will also relate prostate cancer-associated SNP function with cancer stage and aggressiveness. UnderstandingSNP function will have a major impact on personalized medicine, by providing individualized disease risk assessment, identifying new personalized therapeutic targets, and predicting efficacy and potential off- target side effects of common therapeutics. The goals of this Phase I project are to: 1. Design and synthesize a customized SNP-SNAP DNA microarray to tile across a quarter-million SNPs that are associated with prostate cancer. 2. Examine the DNA binding specificity and affinity of 5 prostate cancer-related transcription factors, as purified proteins and from cell lysates, on the SNP-SNAP array and annotate the human genome with the transcription factor binding differences due to SNPs. Verify results with chromatin immunoprecipitation in prostate cancer cells. 3. Obtain SNP data from patients with prostate cancer and determine if there is a statistically significant association of functional SNPs, which yielded differential binding of prostate cancer specific transcription factors on the SNP-SNAP array, with prostate cancer incidence. This technology can assay millions of SNPs and multiple transcription factors simultaneously, thus representing one of the first methods to evaluate SNP functionality in a high throughput manner. Our SNP- SNAP technology,by virtue of the array custom design and ability to examine millions of DNA permutations, is also broadly applicable to any cancer type and disease model. PUBLIC HEALTH RELEVANCE: A critical unmet need in implementing personalized medicine is the ability to sort through the millions of single nucleotide polymorphisms (SNPs) present in the human genome and to pinpoint which of these DNA variations are causative in disease. A key under-studied function of SNPs is their ability to generate or disrupt genomic binding sites for transcription factors which regulate genes involved in cancer. Toward this goal, we are inventing the SNP-SNAP (Specificity and Affinity for Proteins) microarray as a prototype high throughput device to evaluate SNP function by displaying a quarter-million prostate cancer-related SNPs as double-stranded DNA molecules, assaying transcription factors (i.e. drug targets) for their binding to these SNP DNA sequences, and correlating these findings with prostate cancer incidence.

* information listed above is at the time of submission.

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