High throughput analysis of renal cell carcinoma using automated quantitative analysis for the discovery of prognostic and predictive protein biomarkers

The incidence of renal cell carcinoma (RCC) (8th most common cancer in the UK) is increasing and outcomes
remain poor. There are currently no molecular tests available to predict which patients who have undergone
‘curative’ surgery will relapse and who will respond to therapy. Proteomic approaches such as automated
quantitative analysis (AQUA), which quantifies protein expression using fluorescently tagged antibodies, yield
information about deregulated biochemical pathways involved. The ultimate aim of the study would be to identify
markers that can be used to predict therapeutic response and be readily applied to the clinic as predictive
molecular tests.