MALDI imaging mass spectrometry is a powerful tool for morphology-based 
proteomic tissue analysis. However, peptide identification is still a major 
challenge due to low S/N ratios, low mass accuracy and difficulties in 
correlating observed m/z species with peptide identities. To address this, we 
have analyzed tryptic digests of formalin-fixed paraffin-embedded tissue 
microarray cores, from 31 ovarian cancer patients, by LC-MS/MS. The sample 
preparation closely resembled the MALDI imaging workflow in order to create 
representative reference data sets containing peptides also observable in MALDI 
imaging experiments. This resulted in 3844 distinct peptide sequences, at a 
false discovery rate of 1%, for the entire cohort and an average of 982 distinct 
peptide sequences per sample. From this, a total of 840 proteins and, on 
average, 297 proteins per sample could be inferred. To support the efforts of 
the Chromosome-centric Human Proteome Project Consortium, we have annotated 
these proteins with their respective chromosome location. In the presented work, 
the benefit of using a large cohort of data sets was exemplified by correct 
identification of several m/z species observed in a MALDI imaging experiment. 
The tryptic peptide data sets generated will facilitate peptide identification 
in future MALDI imaging studies on ovarian cancer.