Prostate cancer (PCa) treatment remains challenging, especially in advanced stages, where the lack of sensitivity and specificity of available biomarkers makes it difficult to establish an accurate prognosis. Therefore, it is imperative to study PCa biology to identify key molecules that can improve PCa management. In this study, eight prostate tumor tissues and paired normal tissues were analyzed using two approaches-Fourier-transform infrared (FT-IR) spectroscopy for spectroscopic profiling of biomolecules and antibody microarray for signaling proteins-with the main goal of identifying metabolic and proteomic changes that enable the distinction between normal and tumor conditions. Principal component analysis of FT-IR spectra revealed different spectroscopic signals for each condition. The most relevant changes in prostate tumor tissues identified by FT-IR were dysregulation in lipid metabolism, lower polysaccharide and glycogen content, higher nucleic acid content, and increased protein phosphorylation. Using an antibody microarray, 42 proteins were identified as differentially regulated between the two conditions; 14 of those revealed changes in their phosphorylation status. These proteins include transcription factors and kinases and constitute a highly-interconnected interaction network. Altogether, our data reveal metabolic and proteomic alterations that may be of interest in future translational studies aimed at establishing PCa prognosis and treatment. SIGNIFICANCE: Prostate tumor tissues and adjacent benign tissues were analyzed using two approaches-Fourier-transform infrared (FT-IR) spectroscopy for biomolecules and an antibody microarray for signaling proteins, which allowed to identify a panel of metabolic and proteomic alterations that may be of interest in future translational studies to enable the distinction between normal and tumor conditions.
Copyright © 2019. Published by Elsevier B.V.

References

PubMed