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Metabolic, pathologic, and genetic analysis of prostate tissues: quantitative evaluation of histopathologic and mRNA integrity after HR-MAS spectroscopy.

ABSTRACT: The impact of high-resolution magic angle spinning (HR-MAS) spectroscopy on the histopathologic and mRNA integrity of human prostate tissues was evaluated. Forty prostate tissues were harvested at transrectal ultrasound (TRUS) guided biopsy (n = 20) or radical prostatectomy surgery (n = 20), snap-frozen on dry ice, and stored at -80°C until use. Twenty-one samples (n = 11 biopsy, n = 10 surgical) underwent HR-MAS spectroscopy prior to histopathologic and cDNA microarray analysis, while 19 control samples (n = 9 biopsy, n = 10 surgical) underwent only histopathologic and microarray analysis. Frozen tissues were sectioned at 14-µm intervals and placed on individual histopathology slides. Every 8th slide was stained with hematoxylin and eosin (H&E) and used to target areas of predominantly epithelial tissue on the remaining slides for mRNA integrity and cDNA microarray analysis. Histopathologic integrity was graded from 1 (best) to 5 (worst) by two 'blinded' pathologists. Histopathologic integrity scores were not significantly different for post-surgical tissues (HR-MAS vs controls); however, one pathologist's scores were significantly lower for biopsy tissues following HR-MAS while the other pathologist's scores were not. mRNA integrity assays were performed using an Agilent 2100 Bioanalyzer and the electrophoretic traces were scored with an RNA integrity number (RIN) from 1 (degraded) to 10 (intact). RIN scores were not significantly different for surgical tissues, but were significantly lower for biopsy tissues following HR-MAS spectroscopy. The isolated mRNA then underwent two rounds of amplification, conversion to cDNA, coupling to Cy3 and Cy5 dyes, microarray hybridization, imaging, and analysis. Significance analysis of microarrays (SAM) identified no significantly over- or under-expressed genes, including 14 housekeeping genes, between HR-MAS and control samples of surgical and biopsy tissues (5% false discovery rate). This study demonstrates that histopathologic and genetic microarray analysis can be successfully performed on prostate surgical and biopsy tissues following HR-MAS analysis; however, biopsy tissues are more fragile than surgical tissues.

SUBMITTER: Santos CF

PROVIDER: S-EPMC2891902 | biostudies-other | 2010 May

REPOSITORIES: biostudies-other

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Project description:High Resolution--Magic Angle Spinning (HR-MAS) spectroscopy provides rich biochemical profiles that require accurate quantification to permit biomarker identification and to understand the underlying pathological mechanisms. Meanwhile, quantification of HR-MAS data from prostate tissue samples is challenging due to significant overlap between the resonant peaks, the presence of short T₂* metabolites such as citrate or polyamines (T₂ from 25 to 100 msec) and macromolecules, and variations in chemical shifts and T₂*s within a metabolite's spin systems. Since existing methods do not address these challenges completely, a new quantification method was developed and optimized for HR-MAS data acquired with an ultra short T(E) and over 30,000 data points. The proposed method, named HR-QUEST (High Resolution--QUEST), iteratively employs the QUEST time-domain semi-parametric strategy with a new model function that incorporates prior knowledge from whole and subdivided metabolite signals. With these features, HR-QUEST is able to independently fit the chemical shifts and T₂*s of a metabolite's spin systems, a necessity for HR-MAS data. By using the iterative fitting approach, it is able to account for significant contributions from macromolecules and to handle shorter T₂ metabolites, such as citrate and polyamines. After subdividing the necessary metabolite basis signals, the root mean square (RMS) of the residual was reduced by 52% for measured HR-MAS data from prostate tissue. Monte Carlo studies on simulated spectra with varied macromolecular contributions showed that the iterative fitting approach (6 iterations) coupled with inclusion of long T₂ macromolecule components in the basis set improve the quality of the fit, as assessed by the reduction of the RMS of the residual and of the RMS error of the metabolite signal estimate, by 27% and 71% respectively. With this optimized configuration, HR-QUEST was applied to measured HR-MAS prostate data and reliably quantified 16 metabolites and reference signals with estimated Cramér Rao Bounds ≤5%.

Project description:(1) Background: The ability to determine the age of ginseng is very important because the price of ginseng depends on the cultivation period. Since morphological observation is subjective, a new scientific and systematic method for determining the age of ginseng is required. (2) Methods: Three techniques were used for a metabolomics approach. High-resolution magic-angle-spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy was used to analyze powdered ginseng samples without extraction. Ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) and gas chromatography quadrupole time-of-fight mass spectrometry (GC-TOF/MS) were used to analyze the extracts of 4-, 5-, and 6-year-old ginseng. (3) Results: A metabolomics approach has the potential to discriminate the age of ginseng. Among the primary metabolites detected from NMR spectroscopy, the levels of fumarate and choline showed moderate prediction with an area under the curve (AUC) value of more than 0.7. As a result of UPLC-QTOF/MS-based profiling, 61 metabolites referring to the VIP (variable importance in the projection) score contributed to discriminating the age of ginseng. The results of GC×GC-TOF/MS showed clear discrimination of 4-, 5-, and 6-year-old ginseng using orthogonal partial least-squares discriminant analysis (OPLS-DA) to 100% of the discrimination rate. The results of receiver operating characteristic (ROC) analysis, 16 metabolites between 4- and 5-year-old ginseng, and 18 metabolites between 5- and 6-year-old ginseng contributed to age discrimination in all regions. (4) Conclusions: These results showed that metabolic profiling and multivariate statistical analyses can distinguish the age of ginseng. Especially, it is meaningful that ginseng samples from different areas had the same metabolites for age discrimination. In future studies, it will be necessary to identify the unknown variables and to collaboratively study with other fields the biochemistry of aging in ginseng.

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Metabolic, pathologic, and genetic analysis of prostate tissues: quantitative evaluation of histopathologic and mRNA integrity after HR-MAS spectroscopy.

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