A Novel Gene Signature predicting fibroblast composition in the TME allows for an improved selection of PDX models for preclinical studies

The Tumor Microenvironment (TME) plays a pivotal role in driving tumor progression, metastasis, and therapeutic resistance through diverse mechanisms. Notably, the TME influences the response to therapy by regulating immune surveillance evasion in tumor cells. Fibroblasts can play a significant role in resistance to therapy. In the context of cancer cancer-associated fibroblasts (CAFs) in the TME have been associated with resistance to various therapeutic approaches. CAFs can contribute to therapy resistance through multiple mechanisms, including extracellular matrix remodeling, immune modulation, angiogenesis, and paracrine signaling. Understanding the intricate interactions between fibroblasts and cancer cells is crucial for developing more effective therapeutic strategies and overcoming resistance to cancer treatment.

In the pre-clinical stages of therapy testing, the use of clinically and biologically relevant models is essential. However, current preclinical tumor models often lack a comprehensive characterization of the TME. To address this limitation, Champions Oncology utilized transcriptomic data from its exclusive (TumorGraft) PDX models bank and analyzed the data with the xCell computational method to identify molecular signatures predictive of fibroblast presence. PDX models are recognized as accurate and clinically relevant for preclinical studies.