Prostate cancer is a leading cause of cancer deaths for men in the U.S., with around 1 in 9 being diagnosed with the disease each year. Numerous OMIC-based studies into the disease have been conducted, proposing potential markers. However, in order to provide a comprehensive and statistically valid data set, samples from a large cohort of individuals are required. This ultimately provides an analytical challenge, particularly for proteomics research, where nanoscale chromatography is routinely adopted.
Samples of E.Coli and Human K562 tryptic digests were analysed using nanoscale LC at a flow rate of 300nL/min for optimisation. Eight pooled samples were created from 520 prostate cancer patients, with the pools corresponding to different disease states or treatments. These plasma samples were subjected to reduction, alkylation and trypsin digestion. Plasma digest samples were separated using 2.1mm scale chromatography at a flow rate of 150uL/min with a turnaround time of 25 minutes. IMS oa-QTof mass spectrometer was used for mass detection using HDMSE. Data were processed using a variety of informatic tools and searched with respective databases.
Optimum nano scale loading amounts were found to be 50 to 75ng, identifying approximately 4500 proteins in each injection and resulting in >4300 identifications for two out of three injections for the Human K562 sample at 1% FDR.
Pooled plasma samples, based on 250ng of digest loaded on column, were analysed in a randomised manner and as technical triplicates on UPLC scale. A significant number of proteins with differential regulation were found between the sample groups. Proteins occurring in a minimum of two of the biological replicates and with ANOVA p <0.05 were considered as significant. Adoption of the high throughput schema demonstrated highly reproducible chromatography. Curated data was then subjected to pathway analysis in order to provide their biological significance.