Clinical performance and utility of a NNMT-based urine test for bladder cancer.

BACKGROUND: Bladder cancer (BC) represents the most common neoplasm of the urinary tract. Although cystoscopy and urine cytology represent the gold standard methods to monitor BC, both procedures have limitations. Therefore, the identification of reliable biomarkers for early and noninvasive detection of BC is urgently required. METHODS: In this study, we analyzed nicotinamide N-methyltransferase (NNMT) expression in urine samples from 55 BC patients and 107 controls, using real-time polymerase chain reaction (PCR). Receiver operating characteristic (ROC) analysis was used to identify the best cutoff value to discriminate BC patients from healthy donors, and to evaluate the diagnostic accuracy of a urine-based NNMT test. RESULTS: The results demonstrated that urinary NNMT expression was significantly (p<0.05) higher in BC patients. Moreover, a significant (p<0.05) inverse correlation was found between NNMT expression and histological grade. The ROC analysis revealed that a ΔCq of 13.3 was the best cutoff value, since it was associated with the highest combination of sensitivity and specificity. Moreover, the area under the curve (AUC) value was 0.913 (p<0.05), indicating the excellent diagnostic accuracy of a urine-based NNMT test. CONCLUSIONS: Our data indicate that NNMT is a promising biomarker that could be used to support the early and noninvasive diagnosis of BC.

The p53 codon 72 (Arg72Pro) polymorphism is associated with the degree of insulin resistance in type 2 diabetic subjects: a cross-sectional study.

Tumor suppressor protein p53 has been demonstrated to regulate genes involved in energy generating metabolic pathways and apoptosis. To date, a new field of research is the involvement of TP53 codon 72 (Arg72Pro) polymorphism in the diabetic disease. The aim of this study was to evaluate whether the genotype and the related genetic models of Arg72Pro polymorphism of TP53 (rs1042522) are associated with insulin resistance and its metabolic parameters in diabetic and non-diabetic subjects. We examined 335 type 2 diabetic patients (65.5 ± 8.4 years) and 367 non-diabetic subjects (60.5 ± 11.7 years). The results were validated in a validation sample consisting of 199 type 2 diabetic (66.2 ± 8.5 years) and 224 non-diabetic subjects (61.2 ± 12.7 years). In the study sample, the analysis of covariance, adjusted for the effects of age, gender and BMI, showed a significant genotype-diabetes effect on insulin resistance evaluated by HOMA-IR (p = 0.038). This result was mediated by variations in fasting plasma insulin (p = 0.027), as no TP53 genotype-diabetes effects were detected for fasting plasma glucose. In particular, in the diabetic subjects, Pro/Pro genotype was associated with lower values of HOMA-IR with respect to Arg/Arg (p = 0.013) and Arg/Pro (p = 0.006) carriers. No difference in HOMA-IR between diabetic and non-diabetic Pro/Pro carriers was found. Significant recessive model-diabetes interaction effects on fasting insulin and HOMA-IR adjusted for age, sex and BMI were found (p = 0.007 and p = 0.029, respectively). Linear regression analyses, based on the assumption of an additive genetic model adjusted for age, sex and BMI, highlight p53 gene-diabetes interaction effects on fasting insulin (ß = -1.27; p = 0.001) and HOMA-IR (ß = -0.22; p = 0.006). The results of statistical analyses on fasting insulin and HOMA-IR were all confirmed in the validation sample. Furthermore, the logistic regression models confirmed that the effect of HOMA-IR levels on diabetes was moderated by Pro/Pro genotype in both study and validation samples (OR = 0.29, p = 0.034, 95 % CI = 0.09-0.91, OR = 0.37, p = 0.035, 95 % CI = 0.15-0.93, respectively). Our findings suggest that p53 codon 72 (Arg72Pro) polymorphism influences insulin resistance in type 2 diabetic patients independently of body mass.