Patient-matched analysis identifies deregulated networks in prostate cancer to guide personalized therapeutic intervention

Abstract

Prostate cancer (PrCa) is the second most common malignancy in men1. More than 50% of advanced prostate cancers display the TMPRSS2-ERG fusion2. Despite extensive cancer genome/transcriptome2-4 and phosphoproteome5 data, little is known about the impact of mutations and altered transcription on regulatory networks in the PrCa of individual patients. Using patient-matched normal and tumor samples, we established somatic variations and differential transcriptome profiles of primary ERG-positive prostate cancers. Integration of protein-protein interaction and gene-regulatory network databases6, 7 defined highly diverse patient-specific network alterations. We found that different components of a given regulatory pathway were altered by novel and known mutations and/or aberrant gene expression, including deregulated ERG targets, such that different sets of pathways were altered in each individual PrCa. In a given PrCa, several deregulated pathways share common factors, predicting synergistic effects on cancer progression. Our integrated analysis provides a paradigm to identify key deregulated factors within regulatory networks to guide personalized therapies.