Prediction of clinically significant prostate cancer through urine metabolomic signatures: A large-scale validated study.

PURPOSE: Currently, there are no accurate markers for predicting potentially lethal prostate cancer (PC) before biopsy. This study aimed to develop urine tests to predict clinically significant PC (sPC) in men at risk. METHODS: Urine samples from 928 men, namely, 660 PC patients and 268 benign subjects, were analyzed by gas chromatography/quadrupole time-of-flight mass spectrophotometry (GC/Q-TOF MS) metabolomic profiling to construct four predictive models. Model I discriminated between PC and benign cases. Models II, III, and GS, respectively, predicted sPC in those classified as having favorable intermediate risk or higher, unfavorable intermediate risk or higher (according to the National Comprehensive Cancer Network risk groupings), and a Gleason sum (GS) of ≥ 7. Multivariable logistic regression was used to evaluate the area under the receiver operating characteristic curves (AUC). RESULTS: In Models I, II, III, and GS, the best AUCs (0.94, 0.85, 0.82, and 0.80, respectively; training cohort, N = 603) involved 26, 24, 26, and 22 metabolites, respectively. The addition of five clinical risk factors (serum prostate-specific antigen, patient age, previous negative biopsy, digital rectal examination, and family history) significantly improved the AUCs of the models (0.95, 0.92, 0.92, and 0.87, respectively). At 90% sensitivity, 48%, 47%, 50%, and 36% of unnecessary biopsies could be avoided. These models were successfully validated against an independent validation cohort (N = 325). Decision curve analysis showed a significant clinical net benefit with each combined model at low threshold probabilities. Models II and III were more robust and clinically relevant than Model GS. CONCLUSION: This urine test, which combines urine metabolic markers and clinical factors, may be used to predict sPC and thereby inform the necessity of biopsy in men with an elevated PC risk.

Huntingtin-associated protein 1 interacts with breakpoint cluster region protein to regulate neuronal differentiation.

Alterations in microtubule-dependent trafficking and certain signaling pathways in neuronal cells represent critical pathogenesis in neurodegenerative diseases. Huntingtin (Htt)-associated protein-1 (Hap1) is a brain-enriched protein and plays a key role in the trafficking of neuronal surviving and differentiating cargos. Lack of Hap1 reduces signaling through tropomyosin-related kinases including extracellular signal regulated kinase (ERK), resulting in inhibition of neurite outgrowth, hypothalamic dysfunction and postnatal lethality in mice. To examine how Hap1 is involved in microtubule-dependent trafficking and neuronal differentiation, we performed a proteomic analysis using taxol-precipitated microtubules from Hap1-null and wild-type mouse brains. Breakpoint cluster region protein (Bcr), a Rho GTPase regulator, was identified as a Hap1-interacting partner. Bcr was co-immunoprecipitated with Hap1 from transfected neuro-2a cells and co-localized with Hap1A isoform more in the differentiated than in the nondifferentiated cells. The Bcr downstream effectors, namely ERK and p38, were significantly less activated in Hap1-null than in wild-type mouse hypothalamus. In conclusion, Hap1 interacts with Bcr on microtubules to regulate neuronal differentiation.