Xeva

Xeva performs integrative pharmacogenomic analysis of patient-derived tumor xenografts (PDX) to quantify molecular variability, identify pathways and biomarkers associated with drug response, and support preclinical precision oncology.

Key Features:

• Quantification of variability: Quantifies variability in gene expression and pathway activity across different PDX passages to distinguish passage-specific alterations from stable molecular features.
• Pathway analysis: Leverages the largest available pharmacogenomic dataset of PDX models to identify pathways associated with drug response, reporting 87 pathways linked to responses for 51 drugs.
• Biomarker discovery: Identifies predictive biomarkers from gene expression, copy number aberrations, and mutations with reported concordance index greater than 0.60 and FDR less than 0.05.
• Integration of in vivo pharmacogenomics data: Provides a flexible platform for integrative analysis of preclinical in vivo molecular and pharmacologic datasets.

Scientific Applications:

• Prediction of drug response: Enables identification of biomarkers that predict chemotherapeutic and targeted therapy responses in PDX models.
• Validation of predictive biomarkers across passages: Confirms consistent gene and pathway activity across PDX passages to support validation of predictive biomarkers for preclinical drug development and precision medicine.

Methodology:

Performs detailed analysis of high-throughput molecular and pharmacologic profiles from PDX models by quantifying gene expression and pathway activity across passages and filtering out passage-specific variations to identify stable biomarkers associated with drug responses.