Mapping Preclinical Model Transcriptomes to Patient Tumor Profiles to Improve Translational Predictability
- Comparing isogenic, PDX, and other oncology models against TCGA patient transcriptomes to identify which preclinical systems accurately represent tumor biology and subsequently predict drug efficacy in clinical trials
- Highlighting gaps in fibroblast, stromal, and immune-related gene expression to understand limitations of standard models for translational oncology research
- Applying transcriptomic-guided model prioritization to reduce the number of screened models while ensuring broad coverage of clinically relevant patient profiles