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

Authors :
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
Source :
Nature Communications, Vol 15, Iss 1, Pp 1-21 (2024)
Publication Year :
2024
Publisher :
Nature Portfolio, 2024.

Abstract

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.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723
Volume :
15
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.15a9cb6171ca46d4a07fbfbe6bf74b76
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-024-47547-3