JOURNAL ARTICLE
RESEARCH SUPPORT, N.I.H., EXTRAMURAL
RESEARCH SUPPORT, NON-U.S. GOV'T
RESEARCH SUPPORT, U.S. GOV'T, NON-P.H.S.
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Metabolic Profiling in Formalin-Fixed and Paraffin-Embedded Prostate Cancer Tissues.

Metabolite profiling has significantly contributed to a deeper understanding of the biochemical metabolic networks and pathways in cancer cells. Metabolomics-based biomarker discovery would greatly benefit from the ability to interrogate retrospective annotated clinical specimens archived as formalin-fixed, paraffin-embedded (FFPE) material. Mass spectrometry-based metabolomic analysis was performed in matched frozen and FFPE human prostate cancers as well as isogenic prostate cancer cell lines. A total of 352 and 460 metabolites were profiled in human tissues and cell lines, respectively. Classes and physical-chemical characteristics of the metabolites preserved in FFPE material were characterized and related to their preservation or loss following fixation and embedding. Metabolite classes were differentially preserved in archival FFPE tissues, regardless of the age of the block, compared with matched frozen specimen, ranging from maximal preservation of fatty acids (78%) to loss of the majority of peptides and steroids. Generally, FFPE samples showed a decrease of metabolites with functional groups, such as carboxamide. As an adjunct technique, metabolic profiles were also obtained in situ from FFPE tissue sections where metabolites were extracted in a manner that preserves tissue architecture. Despite the fact that selected metabolites were not retained after processing, global metabolic profiles obtained from FFPE can be used to predict biologic states and study biologic pathways. These results pave the way for metabolomics-based biomarker discovery/validation utilizing retrospective and clinically annotated FFPE collections. Implications: Metabolic profiles can be performed in archival tissue and may be used to complement other profiling methods such as gene expression for biomarker discovery or pathway analysis in the assessment of biologic states. Mol Cancer Res; 15(4); 439-47. ©2017 AACR .

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