ABSTRACT
A novel statistically integrated proteometabonomic method has been developed and applied to a human tumor xenograft mouse model of prostate cancer. Parallel 2D-DIGE proteomic and 1H NMR metabolic profile data were collected on blood plasma from mice implanted with a prostate cancer (PC-3) xenograft and from matched control animals. To interpret the xenograft-induced differences in plasma profiles, multivariate statistical algorithms including orthogonal projection to latent structure (OPLS) were applied to generate models characterizing the disease profile. Two approaches to integrating metabonomic data matrices are presented based on OPLS algorithms to provide a framework for generating models relating to the specific and common sources of variation in the metabolite concentrations and protein abundances that can be directly related to the disease model. Multiple correlations between metabolites and proteins were found, including associations between serotransferrin precursor and both tyrosine and 3-D-hydroxybutyrate. Additionally, a correlation between decreased concentration of tyrosine and increased presence of gelsolin was also observed. This approach can provide enhanced recovery of combination candidate biomarkers across multi-omic platforms, thus, enhancing understanding of in vivo model systems studied by multiple omic technologies.
Subject(s)
Biomarkers, Tumor/blood , Blood Proteins/analysis , Prostatic Neoplasms/blood , Prostatic Neoplasms/metabolism , Proteomics/methods , Animals , Cell Line, Tumor , Disease Models, Animal , Electrophoresis, Gel, Two-Dimensional , Gelsolin/blood , Humans , Magnetic Resonance Spectroscopy , Male , Mice , Mice, Inbred C57BL , Transplantation, Heterologous , Tyrosine/bloodABSTRACT
Clinical studies often produce fresh tissue samples, which ideally should be immediately snap frozen for storage and subsequent analysis. However, this is often not practically possible, and there is inevitably a time period during which the sample is stored on ice. The delay in freezing may allow endogenous degradation of proteins to occur, affecting 2-D gel protein profiles. This study aims to investigate the type and extent of this degradation by examining how the time-to-freezing delay alters prostatic tissue protein profile. The prostate carcinoma-3 cell line (PC-3), prostate cancer xenografts and canine prostate were used with fluorescence 2-D DIGE to assess protein degradation. It was found that 30-min processing time had minimal effects on the protein profile. Longer delays had little visible effect, but subtle alterations in protein profile began to accumulate as time increased. These data support the practice of completing tissue processing as rapidly as possible, and indicate that short processing times do not notably perturb the 2-D gel spot pattern from prostatic tissue.
