Original Article
Metabolomics studies of prostate cancer using gas chromatography-mass spectrometery
Abstract
Background: Metabolomics is a powerful analytical approach that is widely used for early diagnosis of many tumors. In this study, we performed a comparative metabolomics analysis to identify metabolic differences in prostate cancer.
Methods: We applied gas chromatography-mass spectrometry (GC-MS) to analyze the metabolic differences between normal prostate epithelial cells and prostate cancer cells (PC-3, LNCaP, and DU145 cells). We performed pairwise comparisons of the metabolomes for the intracellular and extracellular fluid using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and Student’s t-test.
Results: Our results revealed significantly different expression patterns among the metabolite groups, including amino acids, organic acids, sugars, and cholesterol. Of these four categories, cholesterol showed potential for combination with prostate-specific antigen (PSA) to improve diagnosis of prostate cancer.
Conclusions: GC-MS may be an effective approach to reduce the frequency of invasive biopsies. Analysis of the diagnostic significance of prostate cancer markers will help to identify more meaningful tumor markers for prostate cancer diagnosis and treatment, contribute to the understanding of the pathogenesis of prostate cancer, and provide the basis for new ideas.
Methods: We applied gas chromatography-mass spectrometry (GC-MS) to analyze the metabolic differences between normal prostate epithelial cells and prostate cancer cells (PC-3, LNCaP, and DU145 cells). We performed pairwise comparisons of the metabolomes for the intracellular and extracellular fluid using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and Student’s t-test.
Results: Our results revealed significantly different expression patterns among the metabolite groups, including amino acids, organic acids, sugars, and cholesterol. Of these four categories, cholesterol showed potential for combination with prostate-specific antigen (PSA) to improve diagnosis of prostate cancer.
Conclusions: GC-MS may be an effective approach to reduce the frequency of invasive biopsies. Analysis of the diagnostic significance of prostate cancer markers will help to identify more meaningful tumor markers for prostate cancer diagnosis and treatment, contribute to the understanding of the pathogenesis of prostate cancer, and provide the basis for new ideas.
