ABSTRACT: Four molecular classifications of pancreatic ductal adenocarcinoma (PDAC), biologically and clinically relevant and based on gene expression profiles, were established in the recent years, including the Collisson's, Moffitt's ("tumor" and "stroma" classifications), and Bailey's classifications. The aim of this study was to validate the prognostic value of the Moffitt's classifications and to compare the Collisson's, Moffitt's, and Bailey's classifications in a large series of samples. We collected clinical and gene expression data of PDAC samples from 15 public data sets, resulting in a total of 846 primary cancer samples, including 601 with survival annotation. All samples were classified according to each of the four multigene classifiers. We confirmed the independent prognostic value of the Moffitt "tumor", Moffitt "stroma", and Bailey's classifications, but not that of the Collisson's classification. Despite a relatively low gene overlap, all classifications were associated with pathological grade, an important prognostic feature and reflect of intrinsic molecular characteristics of tumors. The concordance rate in term of "good-prognosis" vs. "poor-prognosis" prediction by classifiers was relatively high (from 73 to 86%) between the three "tumor" classifications based on tumor gene lists (Collisson, Moffitt "tumor", Bailey), but low (from 50 to 60%) with the Moffitt's stroma classification based on stroma genes. Multivariate analysis incorporating the four classifiers together retained as significant variables the Moffitt "stroma" and Bailey classifications, highlighting the complementarity of classifiers based on tumor epithelium (Bailey) and tumor stroma (Moffitt stroma). Our results reinforce the clinical validity of subtyping in PDAC, which should be regarded as a collection of separate diseases. Beside their clinical utility that remains to be demonstrated, the clinical interest of the subtypes, notably those from Bailey's and Moffitt's "stroma" classifiers that show independent prognostic value, will be reinforced by the identification of new biomarkers and/or therapeutic targets in each subtype for designing and testing novel specific targeted therapies.
