Prediction of recurrence of non muscle‐invasive bladder cancer by means of a protein signature identified by antibody microarray analyses

Abstract

About 70% of newly diagnosed cases of bladder cancer are low-stage, low-grade, non muscle-invasive. Standard treatment is transurethral resection. About 60% of the tumors will recur, however, and in part progress to become invasive. Therefore, surveillance cystoscopy is performed after resection. However, in the USA and Europe alone, about 54 000 new patients per year undergo repeated cystoscopies over several years, who do not experience recurrence. Analysing in a pilot study resected tumors from patients with (n = 19) and without local recurrence (n = 6) after a period of 5 years by means of an antibody microarray that targeted 724 cancer-related proteins, we identified 255 proteins with significantly differential abundance. Most are involved in the regulation and execution of apoptosis and cell proliferation. A multivariate classifier was constructed based on 20 proteins. It facilitates the prediction of recurrence with a sensitivity of 80% and a specificity of 100%. As a measure of overall accuracy, the area under the curve value was found to be 91%. After validation in additional sample cohorts with a similarly long follow-up, such a signature could support decision making about the stringency of surveillance or even different treatment options.