Nature Communications (May 2024)

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

  • Robert E. Hynds,
  • Ariana Huebner,
  • David R. Pearce,
  • Mark S. Hill,
  • Ayse U. Akarca,
  • David A. Moore,
  • Sophia Ward,
  • Kate H. C. Gowers,
  • Takahiro Karasaki,
  • Maise Al Bakir,
  • Gareth A. Wilson,
  • Oriol Pich,
  • Carlos Martínez-Ruiz,
  • A. S. Md Mukarram Hossain,
  • Simon P. Pearce,
  • Monica Sivakumar,
  • Assma Ben Aissa,
  • Eva Grönroos,
  • Deepak Chandrasekharan,
  • Krishna K. Kolluri,
  • Rebecca Towns,
  • Kaiwen Wang,
  • Daniel E. Cook,
  • Leticia Bosshard-Carter,
  • Cristina Naceur-Lombardelli,
  • Andrew J. Rowan,
  • Selvaraju Veeriah,
  • Kevin Litchfield,
  • Philip A. J. Crosbie,
  • Caroline Dive,
  • Sergio A. Quezada,
  • Sam M. Janes,
  • Mariam Jamal-Hanjani,
  • Teresa Marafioti,
  • TRACERx consortium,
  • Nicholas McGranahan,
  • Charles Swanton

DOI
https://doi.org/10.1038/s41467-024-47547-3
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 21

Abstract

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Abstract Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling.