Correct classification of cancer patients into subtypes is a prerequisite for 
acute diagnosis and effective treatment. Currently this classification relies 
mainly on histological assessment, but gene expression analysis by microarrays 
has shown great promise. Here we show that high accuracy, quantitative 
proteomics can robustly segregate cancer subtypes directly at the level of 
expressed proteins. We investigated two histologically indistinguishable 
subtypes of diffuse large B-cell lymphoma (DLBCL): activated B-cell-like (ABC) 
and germinal-center B-cell-like (GCB) subtypes, by first developing a general 
lymphoma stable isotope labeling with amino acids in cell culture (SILAC) mix 
from heavy stable isotope-labeled cell lines. This super-SILAC mix was combined 
with cell lysates from five ABC-DLBCL and five GCB-DLBCL cell lines. Shotgun 
proteomic analysis on a linear ion trap Orbitrap mass spectrometer with high 
mass accuracy at the MS and MS/MS levels yielded a proteome of more than 7,500 
identified proteins. High accuracy of quantification allowed robust separation 
of subtypes by principal component analysis. The main contributors to the 
classification included proteins known to be differentially expressed between 
the subtypes such as the transcription factors IRF4 and SPI1/PU.1, cell surface 
markers CD44 and CD27, as well as novel candidates. We extracted a signature of 
55 proteins that segregated subtypes and contained proteins connected to 
functional differences between the ABC and GCB-DLBCL subtypes, including many 
NF-κB-regulated genes. Shortening the analysis time to single-shot analysis 
combined with use of the new linear quadrupole Orbitrap analyzer (Q Exactive) 
also clearly differentiated between the subtypes. These results show that high 
resolution shotgun proteomics combined with super-SILAC-based quantification is 
a promising new technology for tumor characterization and classification.