Year of Award:
Molecular & Cellular Analysis Technologies
TAINSKY, MICHAEL A
Other PI or Project Leader:
WAYNE STATE UNIVERSITY
When cancer is identified at the earliest stages, cancer survival rates dramatically increase and therefore diagnostic screening tests that can detect early stage cancer are crucial. The overall goal of our research is to develop such an early detection screening test. We intend to prospectively accrue a large well-defined independent cohort of colorectal cancer (CRC) cases where we collect extensive data on this cohort at the time of diagnosis. We will generate a comprehensive database that includes data on demographics, personal and family history, tumor characteristics, and comorbidities. Our preliminary research efforts have been to develop a detection assay utilizing the sera of our discovery cohort of CRC patients and healthy controls. We have developed a high throughput method to isolated cDNA clones of antigens which can be used to identify cancer cases by detecting the presence of auto-antibodies to tumor proteins in the serum of the test subject. Our first aim is to identify the minimal number of antigen clones that are critical in distinguishing sera from patients with colorectal cancer from healthy controls utilizing our initial discovery cohort. We will eliminate antigen clones from our discovery set of 3800 clones that react with sera from patients with other cancers, benign gastrointestinal conditions, duplicates or do not react with any CRC sera. Our second aim is to determine the test characteristics (sensitivity, specificity, accuracy) on these newly selected antigen markers for distinguishing colorectal cancer cases using newly acquired sera samples not previously used in the development of the marker set. Lastly, we intend to determine the test characteristics of these antigen markers on a large independent well-defined cohort of colorectal cancer patients and healthy controls. In addition, due to the size, racial/ethnic makeup of the study population, and captured patient data, we will be able to evaluate the expression of these markers in relationship to important subgroups.