Abstract
Background: Cancer screening with highly sensitive, specific biomarkers that reflect molecular phenotypic alterations is an attractive strategy for cancer control. We examined whether biomarker profiles could be used for risk assessment and cancer detection in a cohort of Chinese workers occupationally exposed to benzidine and at risk for bladder cancer. Methods: The cohort consisted of 1788 exposed and 373 nonexposed workers, followed from 1991 through 1997. We assayed urothelial cells from voided urine samples for DNA ploidy (expressed as the 5C-exceeding rate [DNA 5CER]), the bladder tumor-associated antigen p300, and a cytoskeletal protein (G-actin). Workers were stratified into different risk groups (high, moderate, and low risk) at each examination based on a predefined biomarker profile. For workers who developed bladder cancer, tumor risk assessment was analyzed from samples collected 6–12 months before the cancer diagnosis. The associations between risk group and subsequent development of bladder cancer were analyzed by Cox proportional hazards regression analysis and logistic analysis, after adjustment. All statistical tests were two-sided. Results: Twenty-eight bladder cancers were diagnosed in exposed workers and two in nonexposed workers. For risk assessment, DNA 5CER had 87.5% sensitivity, 86.5% specificity, an odds ratio (OR) of 46.2 (95% confidence interval [CI] = 8.1 to 867.0), and a risk ratio (RR) of 16.2 (95% CI = 7.1 to 37.0); p300 had 50.0% sensitivity, 97.9% specificity, an OR of 40.0 (95% CI = 9.0 to 177.8), and an RR of 37.9 (95% CI = 16.8 to 85.3). The risk of developing bladder cancer was 19.6 (95% CI = 8.0 to 47.9) times higher in workers positive for either the DNA 5CER or p300 biomarkers than in workers negative for both biomarkers and 81.4 (95% CI = 33.3 to 199.3) times higher in workers positive for both biomarkers. G-actin was a poor marker of individual risk. Conclusions: Occupationally exposed workers at risk for bladder cancer can be individually stratified, screened, monitored, and diagnosed based on predefined molecular biomarker profiles.