Benchmarking mouse contamination removing protocols in patient-derived xenografts genomic profiling

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Depletion of Mouse Cells from Human Tumor Xenografts Significantly Improves Downstream Analysis of Target Cells
07:10

Depletion of Mouse Cells from Human Tumor Xenografts Significantly Improves Downstream Analysis of Target Cells

Published on: July 29, 2016

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Mukund Bhandari1, Funan He1,2, Anna Rogojina1

  • 1Greehey Children's Cancer Research Institute, San Antonio, TX, USA.

NPJ Precision Oncology
|April 17, 2025
PubMed

Insights

Mouse contamination in patient-derived xenograft (PDX) models skews genomic data, inflating mutations and gene expression. New computational tools like Xengsort effectively remove mouse reads, improving PDX model accuracy for cancer research.

Area of Science:

  • Genomics
  • Cancer Research
  • Bioinformatics

Background:

  • Patient-derived xenograft (PDX) models are crucial for cancer research.
  • Genomic and transcriptomic profiling of PDX models are often contaminated by mouse sequencing reads.

Purpose of the Study:

  • To investigate the impact of mouse read contamination on RNA sequencing (RNAseq), Whole Exome Sequencing (WES), and Whole Genome Sequencing (WGS) data from PDX models.
  • To benchmark computational protocols for removing mouse reads from PDX data.

Main Methods:

  • Analysis of RNAseq, WES, and WGS data from 21 PDX models.
  • Systematic benchmarking of 12 computational protocols for mouse read removal.
  • Evaluation using gold standard datasets.

Main Results:

  • Mouse read contamination increases expression of immune and stromal genes and inflates somatic mutation counts.
  • Detection of gene fusions and copy number alterations is minimally affected.
  • Pseudo-alignment protocols showed superior performance and efficiency.
  • Xengsort was identified as the best-performing tool.

Conclusions:

  • Removing mouse reads is essential for accurate genomic and transcriptomic analysis of PDX models.
  • Adopting advanced tools like Xengsort is recommended for PDX genomic studies.

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