ArticleScientific reports2016
Metabolite Analysis and Histology on the Exact Same Tissue: Comprehensive Metabolomic Profiling and Metabolic Classification of Prostate Cancer.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Metabolic profiling of amniotic fluid by differentialMetabolomics : Official journal of the Metabolomic Society · 2025Article
- Comparison of methanol fixation versus cryopreservation of the placenta for metabolomics analysis.Scientific reports · 2023Article
- New Advances in Tissue Metabolomics: A Review.Metabolites · 2021Review
- Advances and Perspectives in Prostate Cancer Biomarker Discovery in the Last 5 Years through Tissue and Urine Metabolomics.Metabolites · 2021Review
- Untargeted GC-MS investigation of serum metabolomics of coronary artery disease patients.Saudi journal of biological sciences · 2020Article
- Comprehensive metabolomics analysis of prostate cancer tissue in relation to tumor aggressiveness and TMPRSS2-ERG fusion status.BMC cancer · 2020Article
- Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources.Metabolites · 2020Review
- Metabolic control of gene transcription in non-alcoholic fatty liver disease: the role of the epigenome.Clinical epigenetics · 2019Review
- A systemic workflow for profiling metabolome and lipidome in tissue.Journal of chromatography. A · 2019Article
- Metabolomics Biomarkers of Prostate Cancer: A Systematic Review.Diagnostics (Basel, Switzerland) · 2019Review
- Article
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3 authors.
Funding
Abstract
We report a method of metabolomic profiling of intact tissue based on molecular preservation by extraction and fixation (mPREF) and high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). mPREF extracts metabolites by aqueous methanol from tissue biopsies without altering tissue architecture and thus conventional histology can be performed on the same tissue. In a proof-of-principle study, we applied dansylation LC-MS to profile the amine/phenol submetabolome of prostate needle biopsies from 25 patient samples derived from 16 subjects. 2900 metabolites were consistently detected in more than 50% of the samples. This unprecedented coverage allowed us to identify significant metabolites for differentiating tumor and normal tissues. The panel of significant metabolites was refined using 36 additional samples from 18 subjects. Receiver Operating Characteristic (ROC) analysis showed area-under-the-curve (AUC) of 0.896 with sensitivity of 84.6% and specificity of 83.3% using 7 metabolites. A blind study of 24 additional validation samples gave a specificity of 90.9% at the same sensitivity of 84.6%. The mPREF extraction can be readily implemented into the existing clinical workflow. Our method of combining mPREF with CIL LC-MS offers a powerful and convenient means of performing histopathology and discovering or detecting metabolite biomarkers in the same tissue biopsy.
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