Determination of the Intra-individual Variability of Protein Expression in Benign/Cancerous Prostate Tissue via LC-MS – Efforts Towards Molecular Classification

With a 1 in 6 lifetime risk and over 200,000 diagnoses per year in United States, prostate cancer is the most common noncutaneous cancer in men. The discrepancy between the number of diagnoses and the mortality risk (1 in 35) has led to scrutiny in the clinical management of the disease. The incidence of the disease has more than doubled since the FDA approval of prostate specific antigen test. Despite its low specificity, it has decreased the proportion of metastatic cancers at diagnosis. However, it has also increased the total number of cancers diagnosed with a majority of them having either indolent disease or completely benign conditions. This discrepancy between increased treatment and decreased disease aggressiveness has lead to much criticism that prostate cancer is “overdiagnosed” leading to unnecessary treatment. To this end, it is of interest to develop protein markers or panels of markers that are more indicative/specific of disease severity than currently available. Herein, we begin this endeavor by determining the precision of protein expression from different regions of benign tissue and Gleason 6 grade cancer tissue within the same individual using laser capture microdissection coupled to LC-MS. After LCM, tissue were lysed and digested using established laboratory procedures. 500ng of protein was separated by LC and analyzed by a velos orbitrap mass spectrometer operating in a top 10 data dependent mode. Data was searched using Sequest and imported into skyline for differential abundance determination. Statistical design of experiments was used to optimized data dependent settings and afforded a 33% increase in unique peptide identifications from our current default DDA settings. 2000 proteins were identified including prostate specific antigen and prostatic acid phophatase. Label free methods will be used to develop an intra individual variability index of both benign and cancerous tissue which will aid in statistically identifying differences.