Cancers of the urinary bladder are the fifth most commonly diagnosed malignancy in the US. Early clinical diagnosis of bladder cancer remains a major challenge and the development of non-invasive methods for detection and surveillance is desirable for both patients and health care providers.

In order to identify urinary proteins with potential clinical utility we enriched and profiled the glycoprotein component of urine samples using a dual-lectin affinity chromatography and LC-MS/MS platform.

From a primary sample set obtained from 54 cancer patients and 46 controls a total of 265 distinct glycoproteins were identified with high confidence, and changes in glycoprotein abundance between groups were quantified by a label-free spectral counting method. Validation of candidate biomarker alpha-1-antitrypsin (A1AT) for disease association was performed on an independent set of 70 samples (35 cancer cases) using an ELISA. Increased levels of urinary alpha-1-antitrypsin (A1AT) glycoprotein were indicative of the presence of bladder cancer (p value < 0.0001) and augmented voided urine cytology results. A1AT detection classified bladder cancer patients with a sensitivity of 74% and specificity of 80%.

The described strategy can enable higher resolution profiling of the proteome in biological fluids by reducing complexity. Application of glycoprotein enrichment provided novel candidates for further investigation as biomarkers for the non-invasive detection of bladder cancer.

PMID: 21459797 [PubMed - as supplied by publisher] Source: National Library of Medicine.