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Updated: Apr 12, 2026
Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Integrated analysis of transcriptome in cancer patient-derived xenografts
Hong Li1, Yinjie Zhu2, Xiaoyan Tang3
1Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, SIBS, CAS, 320 Yueyang Road, Shanghai, 200031, China; Shanghai Center for Bioinformation Technology, 1278 Keyuan Road, Shanghai, 201203, China.
Abstract:
Patient-derived xenograft (PDX) tumor model is a powerful technology in evaluating anti-cancer drugs and facilitating personalized medicines. Multiple research centers and commercial companies have put huge efforts into building PDX mouse models. However, PDX models have not been widely available and their molecular features have not been systematically characterized. In this study, we provided a comprehensive survey of PDX transcriptome by integrating analysis of 58 patients involving 8 different tumors. The median correlation coefficient between patients and xenografts is 0.94, which is higher than that between patients and cell line panel or between patients with the same tumor. Major differential gene expressions in PDX occur in the engraftment of human tumor tissue into mice, while gene expressions are relatively stable over passages. 48 genes are frequently differentially expressed in PDX mice of multiple cancers. They are enriched in extracellular matrix and immune response, and some are reported as targets for anticancer drugs. A simulation study showed that expression change between PDX and patient tumor (6%) would result in acceptable change in drug sensitivity (3%). Our findings demonstrate that PDX mice represent the gene-expression and drug-response features of primary tumors effectively, and it is recommended to monitoring the overall expression profiles and drug target genes in clinical application.
Insights
Patient-derived xenograft (PDX) models effectively mirror patient tumors for anti-cancer drug evaluation. Gene expression in PDX models remains stable, accurately reflecting primary tumor features for personalized medicine.
Area of Science:
- Oncology
- Genomics
- Translational Medicine
Background:
- Patient-derived xenograft (PDX) models are crucial for anti-cancer drug development and personalized medicine.
- Despite their potential, PDX models lack widespread availability and systematic molecular characterization.
- Building and validating robust PDX models is a significant research and commercial effort.
Purpose of the Study:
- To conduct a comprehensive survey of PDX tumor transcriptomes across multiple cancer types.
- To systematically characterize the molecular features and reliability of PDX models.
- To assess the fidelity of PDX models in representing primary tumor gene expression and drug response.
Main Methods:
- Integrated transcriptome analysis of 58 patients and their corresponding PDX models across 8 tumor types.
- Comparative analysis of gene expression correlation between patients and PDX models, cell line panels, and patient-to-patient variability.
- Evaluation of gene expression stability across PDX passages and identification of frequently differentially expressed genes.
Main Results:
- High median correlation (0.94) between patient and PDX tumor transcriptomes, surpassing other models.
- Gene expression differences primarily occur during initial engraftment, with relative stability over passages.
- Identified 48 frequently differentially expressed genes in PDX models, enriched in extracellular matrix and immune response pathways, including potential drug targets.
Conclusions:
- PDX models effectively represent the gene expression and drug response characteristics of primary human tumors.
- The observed gene expression changes between PDX and patient tumors have minimal impact on drug sensitivity predictions.
- Monitoring PDX expression profiles and drug target genes is recommended for clinical applications in personalized oncology.
