Cancer is one of the leading causes of death in the modern world. The term cancer is used when cells lose their ability to regulate growth, become immortal, and in most cases migrate from their primary location into a new, unrelated site. Among cancers, prostate cancer is the leading cause of cancer-related death among men in America, second only to lung cancer. Prostate cancer is clinically subdivided into various classes based on its progression. These include benign, localized, and metastatic (spread into other tissues) prostate cancer. Of these, surgical and radiation therapies exist for clinically localized prostate cancer. However, once the cancer becomes metastatic, it becomes incurable. The advent of prostate specific antigen (PSA) screening has led to earlier detection of prostate cancer. However, a major limitation of the serum PSA test is lack of prostate cancer specificity, which has been reported to be only 20% at a sensitivity of 80%, especially in the intermediate range of PSA detection (4-10 ng/ml). Elevated serum PSA levels can be detected in patients with non-malignant conditions. This has resulted in a surge of equivocal prostate needle biopsies and men with the looming threat of prostate cancer. With the population of males 65 years and older expected to increase from 14 million in the year 2000 to 31 million by 2030, it will be increasingly important to identify which men will die with prostate cancer from those requiring aggressive intervention. Thus, development of additional serum and tissue biomarkers to supplement PSA is very important.

The central dogma of any disease state is that the final outcome is regulated by the cohort of proteins it expresses. Thus, many of these proteins could be used to study the occurrence of prostate cancer, classify the various stages of prostate cancer, and design therapeutic strategies to combat prostate cancer. With the advent of protein microarray technology, it has become possible to study global protein profiles. Hence, we propose to take advantage of the protein microarray to profile the circulating repertoire of antibody in different stages of prostate cancer. This proposal is based on the hypothesis that the host immune system can demonstrate genetic alternations in cancer patients; therefore, cancer-specific antibodies that are produced by patients can be detected by reaction to proteins expressed in their prostate tumors and be used as diagnostic biomarker profiles to distinguish the prostate cancer patients from healthy controls. The core of this project rests on a high throughput method to identify large numbers of epitopes that can be used to identify the presence of prostate cancer by detecting the presence of auto-antibodies to tumor proteins in the serum of the test subject. The essential features of the approach are acknowledging the heterogeneous nature of any specific kind of cancer, departing from the reliance on any single marker for disease detection, and using specialized bioinformatics techniques to interpret the results. The concept employs pattern recognition of multiple markers as a diagnostic rather than any single marker.

By analyzing the specific epitope biomarkers in prostate cancer, we also hope to provide a strong rationale to understand the etiology and treatment of prostate cancer. Identification of overexpressed proteins may lead us to further investigate their function and mechanism involving in prostate cancer. Our long-term goal is to identify a panel of diagnostic epitope biomarkers "signaling" humoral response, which can lead to an integrated approach to cancer detection and treatment using specific immunotherapy or imaging reagents personalized to each patient.