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In vivo quantitative proteomics for the study of oncometabolism

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The active reprograming of cellular metabolism is a primary driver of oncogenesis and a hallmark of established neoplastic lesions. Much of this reprogramming depends on the expression levels and posttranslational modifications (PTMs) of metabolic enzymes. Stable isotope labeling of amino acids in culture (SILAC) is an amino acid-based labeling technique that can be used both in vitro and in vivo to comparatively assess the levels and PTMs of proteins. To this aim, SILAC-labeled cell lysates can be spiked into each sample as a standard, followed by the analysis of specimens by mass spectrometry (MS). Combined with appropriate protocols for the lysis and preparation of samples for MS, this technique allows for the accurate and in-depth quantification of the proteome of a wide variety of cell and tissue samples. In particular, SILAC can be employed to infer the metabolic state of neoplastic lesions and obtain a profound understanding of the proteomic alterations that accompany oncogenesis and tumor progression. Here, we describe a proteomic approach based on SILAC, high-resolution chromatography and high-accuracy MS for comparing levels and phosphorylation status of proteins between the samples of interest. This method can be applied not only to the proteomic study of oncometabolism in murine tissues, but also to the study of cellular samples and human specimens.

Original languageEnglish (US)
Title of host publicationCell-wide Metabolic Alterations Associated with Malignancy
PublisherAcademic Press Inc.
Pages235-259
Number of pages25
ISBN (Print)9780128013298
DOIs
StatePublished - 2014
Externally publishedYes

Publication series

NameMethods in Enzymology
Volume543
ISSN (Print)0076-6879
ISSN (Electronic)1557-7988

Keywords

  • Label-free
  • Mass spectrometry
  • Metabolism
  • Proteomics
  • SILAC
  • Tumor tissue

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology

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