American Association for Cancer Research
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00085472can190349-sup-216275_3_supp_5522714_prjj63.xlsx (586.68 kB)

Supplementary Data File 6 from Integrative Pharmacogenomics Analysis of Patient-Derived Xenografts

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posted on 2023-03-31, 02:24 authored by Arvind S. Mer, Wail Ba-Alawi, Petr Smirnov, Yi X. Wang, Ben Brew, Janosch Ortmann, Ming-Sound Tsao, David W. Cescon, Anna Goldenberg, Benjamin Haibe-Kains

Association between drug class and pathways in PDXs. Drugs have been classified into categories according to their known target and association is computed using gene set enrichment analysis.

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SU2C

Ontario Institute for Cancer Research

Stand Up To Cancer

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ARTICLE ABSTRACT

Identifying robust biomarkers of drug response constitutes a key challenge in precision medicine. Patient-derived tumor xenografts (PDX) have emerged as reliable preclinical models that more accurately recapitulate tumor response to chemo- and targeted therapies. However, the lack of computational tools makes it difficult to analyze high-throughput molecular and pharmacologic profiles of PDX. We have developed Xenograft Visualization & Analysis (Xeva), an open-source software package for in vivo pharmacogenomic datasets that allows for quantification of variability in gene expression and pathway activity across PDX passages. We found that only a few genes and pathways exhibited passage-specific alterations and were therefore not suitable for biomarker discovery. Using the largest PDX pharmacogenomic dataset to date, we identified 87 pathways that are significantly associated with response to 51 drugs (FDR < 0.05). We found novel biomarkers based on gene expressions, copy number aberrations, and mutations predictive of drug response (concordance index > 0.60; FDR < 0.05). Our study demonstrates that Xeva provides a flexible platform for integrative analysis of preclinical in vivo pharmacogenomics data to identify biomarkers predictive of drug response, representing a major step forward in precision oncology. A computational platform for PDX data analysis reveals consistent gene and pathway activity across passages and confirms drug response prediction biomarkers in PDX.See related commentary by Meehan, p. 4324