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 Comparative analysis of mutational signatures in TumorGraft PDX bank and TCGA dataset to improve patient tumor modeling 

One of the major limitations in translational oncology research is the inability to replicate the mutational complexity and etiological diversity observed in patient tumors. Mutational signatures—distinct patterns of DNA alterations—can offer insights into underlying mutagenic processes and DNA repair deficiencies, serving as potential biomarkers for cancer origin and treatment response.

Champions Oncology applied mutational signature profiling to over 1,100 TumorGraft PDX models using whole exome sequencing, aligning the results with clinical and pharmacological annotations to enhance tumor modeling fidelity.

• Signature analysis revealed strong associations between specific mutational signatures and known tumor etiologies—e.g., SBS3 (BRCA mutations), SBS4 (tobacco exposure), and SBS7a (UV light)—demonstrating the biological relevance of Champions’ PDX models across multiple indications.

• Comparative analysis with TCGA data confirmed that PDXs clustered alongside matched patient tumors by cancer type and exposure history, validating the clinical translatability of Champions’ platform.
  

• These findings support the integration of mutational signature data with pharmacologic and molecular profiling to stratify tumors and predict treatment response, advancing personalized therapy strategies and enhancing preclinical drug development pipelines.