A novel method for high-throughput proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissue microarrays (TMA) is described using on-tissue tryptic digestion followed by MALDI imaging MS. A TMA section containing 112 needle core biopsies from lung-tumor patients was analyzed using MS and the data were correlated to a serial hematoxylin and eosin (H&E)-stained section having various histological regions marked, including cancer, non-cancer, and normal ones. By correlating each mass spectrum to a defined histological region, statistical classification models were generated that can sufficiently distinguish biopsies from adenocarcinoma from squamous cell carcinoma biopsies. These classification models were built using a training set of biopsies in the TMA and were then validated on the remaining biopsies. Peptide markers of interest were identified directly from the TMA section using MALDI MS/MS sequence analysis. The ability to detect and characterize tumor marker proteins for a large cohort of FFPE samples in a high-throughput approach will be of significant benefit not only to investigators studying tumor biology, but also to clinicians for diagnostic and prognostic purposes.