Novel molecular tumour classification using MALDI-mass spectrometry imaging of tissue micro-array

Marie Claude Djidja, Emmanuelle Claude, Marten F. Snel, Simona Francese, Peter Scriven, Vikki Carolan, Malcolm R. Clench

Research output: Contribution to journalArticle

103 Citations (Scopus)

Abstract

The development of tissue micro-array (TMA) technologies provides insights into high-throughput analysis of proteomics patterns from a large number of archived tumour samples. In the work reported here, matrix-assisted laser desorption/ionisation-ion mobility separation-mass spectrometry (MALDI-IMS-MS) profiling and imaging methodology has been used to visualise the distribution of several peptides and identify them directly from TMA sections after on-tissue tryptic digestion. A novel approach that combines MALDI-IMS-MSI and principal component analysis-discriminant analysis (PCA-DA) is described, which has the aim of generating tumour classification models based on protein profile patterns. The molecular classification models obtained by PCA-DA have been validated by applying the same statistical analysis to other tissue cores and patient samples. The ability to correlate proteomic information obtained from samples with known and/or unknown clinical outcome by statistical analysis is of great importance, since it may lead to a better understanding of tumour progression and aggressiveness and hence improve diagnosis, prognosis as well as therapeutic treatments. The selectivity, robustness and current limitations of the methodology are discussed.

Original languageEnglish
Pages (from-to)587-601
Number of pages15
JournalAnalytical and Bioanalytical Chemistry
Volume397
Issue number2
DOIs
Publication statusPublished - 1 May 2010
Externally publishedYes

Keywords

  • Ion mobility separation
  • MALDI imaging
  • Pancreatic cancer
  • Tissue micro-array
  • Tumour classification

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry

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