Proteomic analyses identify major vault protein as a prognostic biomarker for fatal prostate cancer

Abstract

The demographic shift toward an older population will increase the number of prostate cancer cases. A challenge in the treatment of prostate cancer is to avoid undertreatment of patients at high risk of progression following curative treatment. These men can benefit from early salvage treatment. An explorative cohort consisting of tissue from 16 patients who underwent radical prostatectomy, and were either alive or had died from prostate cancer within 10 years postsurgery, was analyzed by mass spectrometry analysis. Following proteomic and bioinformatic analyses, major vault protein (MVP) was identified as a putative prognostic biomarker. A publicly available tissue proteomics dataset and a retrospective cohort of 368 prostate cancer patients were used for validation. The prognostic value of the MVP was verified by scoring immunohistochemical staining of a tissue microarray. High level of MVP was associated with more than 4-fold higher risk for death from prostate cancer (hazard ratio = 4.41, 95% confidence interval: 1.45–13.38; P = 0.009) in a Cox proportional hazard models, adjusted for Cancer of the Prostate Risk Assessments Post-surgical (CAPRA-S) score and perineural invasion. Decision curve analyses suggested an improved standardized net benefit, ranging from 0.06 to 0.18, of adding MVP onto CAPRA-S score. This observation was confirmed by receiver operator characteristics curve analyses for the CAPRA-S score versus CAPRA-S and MVP score (area under the curve: 0.58 versus 0.73). From these analyses, one can infer that MVP levels in combination with CAPRA-S score might add onto established risk parameters to identify patients with lethal prostate cancer.

Abstract

Mass spectrometry of an explorative cohort identified a promising biomarker, major vault protein. Using two independent validation cohorts, we verified an association between high MVP and adverse outcome. MVP was associated with prostate cancer-specific death independently of a composite risk model.