Next-generation sequence analysis of cancer xenograft models

PLoS One. 2013 Sep 26;8(9):e74432. doi: 10.1371/journal.pone.0074432. eCollection 2013.


Next-generation sequencing (NGS) studies in cancer are limited by the amount, quality and purity of tissue samples. In this situation, primary xenografts have proven useful preclinical models. However, the presence of mouse-derived stromal cells represents a technical challenge to their use in NGS studies. We examined this problem in an established primary xenograft model of small cell lung cancer (SCLC), a malignancy often diagnosed from small biopsy or needle aspirate samples. Using an in silico strategy that assign reads according to species-of-origin, we prospectively compared NGS data from primary xenograft models with matched cell lines and with published datasets. We show here that low-coverage whole-genome analysis demonstrated remarkable concordance between published genome data and internal controls, despite the presence of mouse genomic DNA. Exome capture sequencing revealed that this enrichment procedure was highly species-specific, with less than 4% of reads aligning to the mouse genome. Human-specific expression profiling with RNA-Seq replicated array-based gene expression experiments, whereas mouse-specific transcript profiles correlated with published datasets from human cancer stroma. We conclude that primary xenografts represent a useful platform for complex NGS analysis in cancer research for tumours with limited sample resources, or those with prominent stromal cell populations.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cell Line, Tumor
  • DNA Copy Number Variations / genetics
  • Disease Models, Animal*
  • Exome / genetics
  • Gene Expression Profiling
  • Genome, Human / genetics
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Mice
  • Mice, Nude
  • Neoplasms / genetics*
  • Oligonucleotide Array Sequence Analysis
  • Species Specificity
  • Xenograft Model Antitumor Assays*

Grant support

Funding for this work was provided by the National Health and Medical Research Council of Australia (Project Grant 546204), the Victorian Government Operational Infrastructure Support Program, and the Victorian Cancer Agency. Funding for open access charge: Victorian Cancer Agency. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.