Human Proteome Arrays for Auto-Antibody Identification in Clinical Cancer Studies The goal of this project is to develop protein arrays on a proteome scale for high throughput discovery and validation of cancer-specific autoantibody signatures. Early detection of cancer is a critical factor for the successful treatment of cancer patients. The discovery of specific autoantibody signatures in cancer patients has led to the recognition that autoantibody responses may have diagnostic potential. The lack of high throughput methods for rapidly screening and validating multiple antigens of interest has been identified as an important bottleneck for the development of autoantibodies as biomarkers for cancer diagnosis. We will test normal and cancer patient sera against protein arrays generated using a gene library expressing human full-length proteins. Autoantibodies against the proteins in these arrays will be identified using electrochemiluminescence (ECL) detection technology, a proven technology for high throughput array-based measurements that will enable studies with large numbers of patient samples. Our approach will offer key advantages over existing array-based approaches by providing a high throughput, sensitive and specific assay platform. This approach will also facilitate the rapid transition from discovery of antigens using large arrays to clinical validation of the hits using small focused arrays on the same diagnostic platform. In the Phase I portion of the proposed project, we will demonstrate technical feasibility of the approach;in the Phase II portion we will develop and validate the proteome-scale arrays, and use them to screen cancer serum samples to identify a promising subset of autoantigens;the selected subset will then be further tested with a large number of individual samples.
The goal of this project is to develop new clinical diagnostic tools to improve early detection of cancer through the measurement of patients'individual immune responses to cancer. Effective early cancer detection would lead to earlier diagnosis and more successful treatment.
