| Literature DB >> 29483136 |
Benjamin J Drapkin1, Julie George2, Camilla L Christensen3, Mari Mino-Kenudson4, Ruben Dries3, Tilak Sundaresan1,5, Sarah Phat1, David T Myers1, Jun Zhong1, Peter Igo1, Mehlika H Hazar-Rethinam1, Joseph A Licausi1,5, Maria Gomez-Caraballo1, Marina Kem1,4, Kandarp N Jani3, Roxana Azimi1, Nima Abedpour2,6, Roopika Menon7, Sotirios Lakis7, Rebecca S Heist1,5,8, Reinhard Büttner9, Stefan Haas10, Lecia V Sequist1,5,8, Alice T Shaw1,5,8, Kwok-Kin Wong11, Aaron N Hata1,5,8, Mehmet Toner5,12,13,14, Shyamala Maheswaran1,5,13, Daniel A Haber1,5,8,15, Martin Peifer2,6, Nicholas Dyson1,5, Roman K Thomas16,9,17, Anna F Farago18,5,8.
Abstract
Small cell lung cancer (SCLC) patient-derived xenografts (PDX) can be generated from biopsies or circulating tumor cells (CTC), though scarcity of tissue and low efficiency of tumor growth have previously limited these approaches. Applying an established clinical-translational pipeline for tissue collection and an automated microfluidic platform for CTC enrichment, we generated 17 biopsy-derived PDXs and 17 CTC-derived PDXs in a 2-year timeframe, at 89% and 38% efficiency, respectively. Whole-exome sequencing showed that somatic alterations are stably maintained between patient tumors and PDXs. Early-passage PDXs maintain the genomic and transcriptional profiles of the founder PDX. In vivo treatment with etoposide and platinum (EP) in 30 PDX models demonstrated greater sensitivity in PDXs from EP-naïve patients, and resistance to EP corresponded to increased expression of a MYC gene signature. Finally, serial CTC-derived PDXs generated from an individual patient at multiple time points accurately recapitulated the evolving drug sensitivities of that patient's disease. Collectively, this work highlights the translational potential of this strategy.Significance: Effective translational research utilizing SCLC PDX models requires both efficient generation of models from patients and fidelity of those models in representing patient tumor characteristics. We present approaches for efficient generation of PDXs from both biopsies and CTCs, and demonstrate that these models capture the mutational landscape and functional features of the donor tumors. Cancer Discov; 8(5); 600-15. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 517. ©2018 American Association for Cancer Research.Entities:
Mesh:
Year: 2018 PMID: 29483136 PMCID: PMC6369413 DOI: 10.1158/2159-8290.CD-17-0935
Source DB: PubMed Journal: Cancer Discov ISSN: 2159-8274 Impact factor: 39.397