Details

Autor(en) / Beteiligte

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

Titel

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

Ist Teil von

• Nature communications, 2024-05, Vol.15 (1), p.4653-21, Article 4653

Ort / Verlag

England: Nature Publishing Group

Erscheinungsjahr

2024

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• 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.