Stroma vs epithelium-enhanced prognostics through histologic stratification in pancreatic ductal adenocarcinoma.

Abstract

The mixture of epithelial and stromal components in pancreatic ductal adenocarcinoma (PDAC) may confound sequencing-based studies of tumor gene expression. Virtual microdissection has been suggested as a bioinformatics approach to segment the aforementioned components, and subsequent prognostic gene sets have emerged from this research. We examined the prognostic signature from the epithelial gene set of one such study using laser capture microdissected (LCM) epithelial samples. We also examined this gene set in matched stromal samples to determine whether prognostic findings were specific to the epithelium. LCM samples from 48 long-term and 48 short-term PDAC survivors were obtained. The resultant epithelial and stromal components were subjected to direct mRNA quantification using a 49 gene published PDAC classifier. Component-specific unsupervised hierarchical clustering was used to derive groups and survival differences were quantified. Immunohistochemical validation of particular genes was performed in an independent cohort. Clustering in the epithelial component yielded prognostic differences in univariable analysis (P = .02), but those differences were not significant when controlled for other clinicopathologic covariates (P = .06). Clustering in the stromal component yielded prognostic differences that persisted in the presence of other clinicopathologic covariates (P = .0005). Validation of selected genes in the epithelium (KRT6A-negative prognostic [P = .004]) and stroma (LY6D-improved prognostic [P = .01] and CTSV-negative prognostic [P = .0002]) demonstrated statistical independence in multivariable analysis. Although the genes used in this study were originally identified as being representative of the epithelial component of PDAC, their expression in the stroma appears to provide additional information that may aid in improved prognostication.