Abstract 5158: Serological autoantibody profiling in bladder cancer using protein arrays

Abstract

Abstract Cancer cells might release at least part of their contents into the blood stream directly or through extracellular fluids upon cell damage or death. Cancer proteins not present in non-neoplastic cell subpopulations might then elicit a host immune response. The serum autoantibody repertoire from cancer patients might therefore, be exploited for the identification of tumor-associated antigens (TAAs). The recognition that human tumors stimulate the production of autoantibodies against such autologous cellular proteins (TAAs) has opened the door to the possibility that autoantibodies could be translated into serological tools for early diagnosis and/or disease management. In this report, we attempt at exploring the serum proteome of patients with bladder cancer using protein arrays. The serum autoantibody profiles of 18 patients with bladder cancer and 6 control specimens including cases affected with other neoplasias, benign urological diseases and healthy individuals was investigated using protein arrays containing more than 12,000 proteins. Data analyses included T-test as well as clustering strategies using the Prospector and CIMMiner softwares. Supervised clustered heatmaps served to highlight identified biological differences among autoantibody profiles arrays of bladder cancer cases and controls. Moreover, protein expression patterns of the identified immunogenic TAAs were assessed by immunohistochemistry on tissue microarrays (n=92). Supervised clustering analysis segregated bladder cancer patients from controls. A panel of 171 autoantibodies was identified to be differentially expressed in bladder cancer patients as compared to control individuals in a significant manner. Bladder cancer TAAs included proteins involved in cell proliferation, signal transduction, apoptosis, DNA-binding and transcription factors, among others. Immunohistochemical analyses on tissue arrays served to validate the increased protein expression of identified TAAs in bladder tumors. Moreover they revealed the relevance of expression patterns of proteins such as clusterin for bladder cancer diagnostics, staging and outcome prognosis. Protein expression patterns of clusterin were significantly associated with clinico-pathological variables such as tumor size (P=0.034), T1 substaging (P=0.013) or progression into muscle invasive disease (P=0.020). Thus, the novel application of high-throughput protein arrays for serum autoantibody profiling is providing critical information not only to identify TAAs candidate biomarkers for bladder cancer diagnostics and potential immunological therapeutic targets, such as clusterin, but also to further characterize bladder cancer progression.