Mouse Ovarian Cancer Models Recapitulate the Human Tumor Microenvironment and Patient Response to Treatment

Eleni Maniati,Chiara Berlato,Ganga Gopinathan,Owen Heath,Panoraia Kotantaki,Anissa Lakhani,Jacqueline Mcdermott,Colin Pegrum,Robin M Delaine-Smith,Oliver M.T Pearce,Priyanka Hirani,Joash D Joy,Ludmila Szabova,Ruth Perets,Owen J Sansom,Ronny Drapkin,Peter Bailey,Frances R Balkwill

doi:10.1016/j.celrep.2019.12.034

Abstract

SummaryAlthough there are many prospective targets in the tumor microenvironment (TME) of high-grade serous ovarian cancer (HGSOC), pre-clinical testing is challenging, especially as there is limited information on the murine TME. Here, we characterize the TME of six orthotopic, transplantable syngeneic murine HGSOC lines established from genetic models and compare these to patient biopsies. We identify significant correlations between the transcriptome, host cell infiltrates, matrisome, vasculature, and tissue modulus of mouse and human TMEs, with several stromal and malignant targets in common. However, each model shows distinct differences and potential vulnerabilities that enabled us to test predictions about response to chemotherapy and an anti-IL-6 antibody. Using machine learning, the transcriptional profiles of the mouse tumors that differed in chemotherapy response are able to classify chemotherapy-sensitive and -refractory patient tumors. These models provide useful pre-clinical tools and may help identify subgroups of HGSOC patients who are most likely to respond to specific therapies.

Highlights

Human tumors comprise a complex mixture of malignant cells, immune, and other stromal cells regulated by a dynamic network of soluble mediators and adhesion molecules
Mouse high-grade serous ovarian cancer (HGSOC) Models As >98% of HGSOC are TP53 null or have TP53 mutations and $50% have defects in homologous double-stranded DNA repair, we focused on models with key genotypes
We looked in more detail at signaling pathways and found strong correlations between murine and human tumors in terms of the p53 and DNA-damage repair pathways; the mammalian target of rapamycin (mTOR), ErbB, and Hippo pathways; and cell-cell communication and tumor necrosis factor receptor 2 (TNFR2) non-canonical nuclear factor kB (NF-kB) signaling (Figure 2C)

Summary

Introduction

Human tumors comprise a complex mixture of malignant cells, immune, and other stromal cells regulated by a dynamic network of soluble mediators and adhesion molecules All of these components interact in an abnormal extracellular matrix (ECM), often referred to as the tumor matrisome (Socovich and Naba, 2018). We recently conducted multi-layered TME profiling of evolving omental metastases of human high-grade serous ovarian cancer (HGSOC), describing gene and protein profiles that are associated with tissue stiffness, extent of disease, and cellularity (Pearce et al, 2018) During this analysis, we defined a 22gene matrisome signature, the Matrix Index, which predicted the extent of disease, tissue remodeling, and tissue stiffness. As regulators of these matrisome molecules may be important therapeutic targets across many different cancer types, pre-clinical models that replicate the malignant matrisome and immune landscapes are of critical importance

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