Novel molecular tumour classification using MALDI-mass spectrometry imaging of tissue micro-array.
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.
Djidja
Marie-Claude
MC
Biomedical Research Centre, Sheffield Hallam University, Howard Street, Sheffield, S1 1WB, UK.
Claude
Emmanuelle
E
Snel
Marten F
MF
Francese
Simona
S
Scriven
Peter
P
Carolan
Vikki
V
Clench
Malcolm R
MR
D000230:Adenocarcinoma / Q000473:pathology*; D000595:Amino Acid Sequence; D006801:Humans; D008969:Molecular Sequence Data; D010190:Pancreatic Neoplasms / Q000473:pathology*; D011506:Proteins / Q000032:analysis; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods*; D046888:Tissue Array Analysis / Q000379:methods*
D011506:Proteins