Quantitative RT-PCR: Prediction Lymphoma Transformation

Award Information
Agency: Department of Health and Human Services
Branch: N/A
Contract: 1R42CA113212-01
Agency Tracking Number: CA113212
Amount: $100,000.00
Phase: Phase I
Program: STTR
Awards Year: 2005
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
390 Wakara Way, Salt Lake City, UT, 84108
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 (801) 581-5854
Business Contact
Phone: (801) 582-5138
Research Institution
 75 South 2000 East
Room 111
 Nonprofit college or university
DESCRIPTION (provided by applicant): Completion of the human genome and the advent of expression profiling have permitted comprehensive characterization of the transcriptional signatures of different disease states. Quantitative fluorescent real-time polymerase chain reaction-based methods have emerged as a powerful tool in molecular diagnostics as they combine extraordinary dynamic range of quantification and superior specificity. Despite the remarkable advances in real-time fluorescence quantification techniques, this technique has yet to gain widespread application in the analysis of gene expression fixed paraffin-embedded tissues, which is the most common way in which biopsy material is archived. In the R41 phase of this fast-track application, we will establish the utility of a simple approach to the performance of quantitative RT-PCR on RNA derived from formalin-fixed paraffinembedded tissue. The technique is advantageous in that it is simple and compatible with the design of PCR for short amplicons, without compromising target specificity. By the end of the R41 phase of this project, we would have established the feasibility, reproducibility and robustness of our quantitative real-time RT-PCR approach on RNA derived from formalin-fixed paraffin embedded tissue material. These studies will serve as the foundation for the gene expression profiling studies evaluating the predictive power of a previously identified set of ~30 genes to predict the transformation of follicular lymphoma to an aggressive large B-cell lymphoma in phase II.

* Information listed above is at the time of submission. *

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