Urinary glycoprotein biomarker discovery for bladder cancer detection using LC/MS-MS and label-free quantification

Abstract

Background: Cancers of the urinary bladder are the fifth most commonly diagnosed malignancy in the United States. Early clinical diagnosis of bladder cancer remains a major challenge, and the development of noninvasive methods for detection and surveillance is desirable for both patients and health care providers.

Approach: To identify urinary proteins with potential clinical utility, we enriched and profiled the glycoprotein component of urine samples by using a dual-lectin affinity chromatography and liquid chromatography/tandem mass spectrometry platform.

Results: 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 done on an independent set of 70 samples (35 cancer cases) by using an ELISA. Increased levels of urinary A1AT glycoprotein were indicative of the presence of bladder cancer (P < 0.0001) and augmented voided urine cytology results. A1AT detection classified bladder cancer patients with a sensitivity of 74% and specificity of 80%.

Summary: 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 noninvasive detection of bladder cancer.

Figure 1

Workflow of LC-MS/MS based identification, and immunoassay based validation.

Figure 2

Scatter plots of LTQ replicates across all urine samples based on transformed spectral counts. A) Non-cancer group, B) Cancer group.

Figure 3

Heat map of differentially expressed urinary glycoproteins identified in duplicate analyses of 103 samples. The heat map displays the transformed spectral counts data. Each column represents an independent analysis for each sample. Each row represents a specific glycoprotein identified by LC-MS/MS.

Figure 4

ELISA analysis of urinary A1AT. Left panel shows a scatter-plot of creatinine-normalized urinary A1AT concentration (logarithm M) in study subjects with (Cancer), and without (Control) bladder cancer. Differential levels were significant (p < 0.0001). Error bars denote standard deviation. Right panel shows ROC curve of A1AT data; area under the ROC (AUROC) of 0.82.