Whole transcriptome profiling of patient-derived xenograft models as a tool to identify both tumor and stromal specific biomarkers.

// James R. Bradford 1 , Mark Wappett 2 , Garry Beran 2 , Armelle Logie 2 , Oona Delpuech 2 , Henry Brown 2 , Joanna Boros2 , Nicola J. Camp 3 , Robert McEwen 2 , Anne Marie Mazzola 4 , Celina D’Cruz 4 , Simon T. Barry 2 1 Department of Oncology and Metabolism, University of Sheffield, Sheffield, South Yorkshire, UK 2 Oncology iMED, AstraZeneca Pharmaceuticals, Alderley Park, Cheshire, UK 3 Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA 4 Oncology iMED, AstraZeneca Pharmaceuticals, GatehousePark, Massachusetts, USA Correspondence to: James R. Bradford, e-mail: J.R.Bradford@sheffield.ac.uk Keywords: patient-derived xenograft, RNA-Seq, tumor stroma, biomarker discovery, pre-clinical research Received: November 09, 2015 Accepted: February 18, 2016 Published: March 09, 2016 ABSTRACT The tumor microenvironment is emerging as a key regulator of cancer growth and progression, however the exact mechanisms of interaction with the tumor are poorly understood. Whilst the majority of genomic profiling efforts thus far have focused on the tumor, here we investigate RNA-Seqas a hypothesis-free tool to generate independent tumor and stromal biomarkers, and explore tumor- stromainteractions by exploiting the human-murine compartment specificity of patient-derived xenografts (PDX). Across a pan-cancer cohort of 79 PDX models, we determine that mouse stromacan be separated into distinct clusters, each corresponding to a specific stromal cell type. This implies heterogeneous recruitment of mouse stromato the xenograft independent of tumor type. We then generate cross-species expression networks to recapitulate a known association between tumor epithelial cells and fibroblast activation, and propose a potentially novel relationship between two hypoxia-associated genes, human MIF and mouse Ddx6 . Assessment of disease subtype also reveals MMP12 as a putative stromal marker of triple-negative breast cancer. Finally, we establish that our ability to dissect recruited stromafrom trans-differentiated tumor cells is crucial to identifying stem-like poor-prognosis signatures in the tumor compartment. In conclusion, RNA-Seqis a powerful, cost-effective solution to global analysisof human tumor and mouse stromasimultaneously, providing new insights into mouse stromal heterogeneity and compartment-specific disease markers that are otherwise overlooked by alternative technologies. The study represents the first comprehensive analysis of its kind across multiple PDX models, and supports adoption of the approach in pre-clinical drug efficacy studies, and compartment-specific biomarker discovery.