A HIGH THROUGHPUT DIAGNOSTIC ASSAY FOR LUNG CANCER


Year of Award:
2005
Award Type:
R21
Project Number:
CA114157
RFA Number:
RFA-CA-05-002
Technology Track:
Molecular & Cellular Analysis Technologies
PI/Project Leader:
BROWN, KATHLYNN C
Other PI or Project Leader:
N/A
Institution:
UNIVERSITY OF TEXAS SW MED CTR/DALLAS
Within the United States, 170,000 new cases of lung cancer are diagnosed per year. Over 60% of these patients will die within one year, making lung cancer the largest cancer killer of both men and women. The correct histopathological diagnosis of a tumor is critical in determining the appropriate treatment. However, precise classification of tumors remains a significant biomedical challenge. Furthermore, tumors of similar histology can have different clinical outcomes, stressing the need for more detailed molecular classifications. Generation of ligands specific to receptor(s) on a surface of a lung cancer cell will impact clinical issues including functional diagnosis. Our overall goal is to generate a panel of cell-specific molecules that could be used to classify tumor types and utilize these cancer specific reagents in a high throughput diagnostic assay. Using phage display technologies, my laboratory has developed platform methodologies to isolate peptides that bind to and mediate uptake into specific cell lines. We have identified cell-specific targeting peptides for 25 different cell types, including 4 lung cancer cell lines. The isolated peptides display remarkable cell specificities, even among similar cells, and are able to discriminate between normal and cancerous cells as well as different lung tumor cells. This high discriminating power suggests that peptides could be identified that selectively bind to different tumor types, even those with similar classifications. We propose to expand this panel of lung specific reagents by isolating cell targeting peptides for 4 different lung cancer lines and then utilize these peptides as diagnostic reagents. These peptides will be assayed for affinity and cell-specificity. We will remove the peptides from the phage backbone and synthesize peptide scaffolds that retain their affinity and cell-specificity. We will develop a high throughput fluorescent assay based on peptide binding that will allow for a more molecular classification of lung cancer samples. The assay can be multiplexed so that multiple binding events can be examined on a single sample. At the end of this pilot project we will have developed a novel diagnostic platform that can be expanded to clinical samples. Furthermore, the technologies developed here can be applied to other forms of cancer.