Gene signatures from pancreatic cancer tumor and stromal cells predict disease outcome

Pancreatic cancers consist of a heterogeneous amalgam of assorted cell types, making it challenging to develop a classification system that groups these tumors according to common molecular features. A new study tackles this important issue using bioinformatics approaches to decipher gene expression signatures derived specifically from either tumor cells or nonmalignant stromal cells that predict patient outcome and may inform personalized treatments.