DOI QR코드

DOI QR Code

Validity of patient-derived xenograft mouse models for lung cancer based on exome sequencing data

  • Kim, Jaewon (Department of Bio-information Science, Ewha Womans University) ;
  • Rhee, Hwanseok (Bioinformatics Team, DNA Link) ;
  • Kim, Jhingook (Samsung Biomedical Research Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine) ;
  • Lee, Sanghyuk (Ewha Research Center for Systems Biology (ERCSB) and Department of Life Science, Ewha Womans University)
  • Received : 2019.11.19
  • Accepted : 2019.12.13
  • Published : 2020.03.31

Abstract

Patient-derived xenograft (PDX) mouse models are frequently used to test the drug efficacy in diverse types of cancer. They are known to recapitulate the patient characteristics faithfully, but a systematic survey with a large number of cases is yet missing in lung cancer. Here we report the comparison of genomic characters between mouse and patient tumor tissues in lung cancer based on exome sequencing data. We established PDX mouse models for 132 lung cancer patients and performed whole exome sequencing for trio samples of tumor-normal-xenograft tissues. Then we computed the somatic mutations and copy number variations, which were used to compare the PDX and patient tumor tissues. Genomic and histological conclusions for validity of PDX models agreed in most cases, but we observed eight (~7%) discordant cases. We further examined the changes in mutations and copy number alterations in PDX model production and passage processes, which highlighted the clonal evolution in PDX mouse models. Our study shows that the genomic characterization plays complementary roles to the histological examination in cancer studies utilizing PDX mouse models.

Keywords

References

  1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68:394-424. https://doi.org/10.3322/caac.21492
  2. Sculier JP, Berghmans T, Meert AP. Advances in target therapy in lung cancer. Eur Respir Rev 2015;24:23-29. https://doi.org/10.1183/09059180.00011014
  3. Golding B, Luu A, Jones R, Viloria-Petit AM. The function and therapeutic targeting of anaplastic lymphoma kinase (ALK) in non-small cell lung cancer (NSCLC). Mol Cancer 2018;17:52. https://doi.org/10.1186/s12943-018-0810-4
  4. Lin JJ, Shaw AT. Recent advances in targeting ROS1 in lung cancer. J Thorac Oncol 2017;12:1611-1625. https://doi.org/10.1016/j.jtho.2017.08.002
  5. Ricciuti B, Brambilla M, Metro G, Baglivo S, Matocci R, Pirro M, et al. Targeting NTRK fusion in non-small cell lung cancer: rationale and clinical evidence. Med Oncol 2017;34:105. https://doi.org/10.1007/s12032-017-0967-5
  6. Bruna A, Rueda OM, Greenwood W, Batra AS, Callari M, Batra RN, et al. A biobank of breast cancer explants with preserved intra-tumor heterogeneity to screen anticancer compounds. Cell 2016;167:260-274. https://doi.org/10.1016/j.cell.2016.08.041
  7. Karamboulas C, Bruce JP, Hope AJ, Meens J, Huang SH, Erdmann N, et al. Patient-derived xenografts for prognostication and personalized treatment for head and neck squamous cell carcinoma. Cell Rep 2018;25:1318-1331. https://doi.org/10.1016/j.celrep.2018.10.004
  8. Gao H, Korn JM, Ferretti S, Monahan JE, Wang Y, Singh M, et al. High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response. Nat Med 2015;21:1318-1325. https://doi.org/10.1038/nm.3954
  9. Hammerman PS, Hayes DN, Grandis JR. Therapeutic insights from genomic studies of head and neck squamous cell carcinomas. Cancer Discov 2015;5:239-244. https://doi.org/10.1158/2159-8290.CD-14-1205
  10. Campbell KM, Lin T, Zolkind P, Barnell EK, Skidmore ZL, Winkler AE, et al. Oral cavity squamous cell carcinoma xenografts retain complex genotypes and intertumor molecular heterogeneity. Cell Rep 2018;24:2167-2178. https://doi.org/10.1016/j.celrep.2018.07.058
  11. Shultz LD, Lyons BL, Burzenski LM, Gott B, Chen X, Chaleff S, et al. Human lymphoid and myeloid cell development in NOD/LtSz-scid IL2R gamma null mice engrafted with mobilized human hemopoietic stem cells. J Immunol 2005;174:6477-6489. https://doi.org/10.4049/jimmunol.174.10.6477
  12. Conway T, Wazny J, Bromage A, Tymms M, Sooraj D, Williams ED, et al. Xenome: a tool for classifying reads from xenograft samples. Bioinformatics 2012;28:i172-178.
  13. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at http://arxiv.org/abs/1303.3997 (2013).
  14. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009;25:2078-2079. https://doi.org/10.1093/bioinformatics/btp352
  15. Van der Auwera GA, Carneiro MO, Hartl C, Poplin R, Del Angel G, Levy-Moonshine A, et al. From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr Protoc Bioinformatics 2013;43:11.10.1-11.10.33.
  16. Cibulskis K, Lawrence MS, Carter SL, Sivachenko A, Jaffe D, Sougnez C, et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat Biotechnol 2013;31:213-219. https://doi.org/10.1038/nbt.2514
  17. Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res 2010;38:e164. https://doi.org/10.1093/nar/gkq603
  18. Magi A, Tattini L, Cifola I, D'Aurizio R, Benelli M, Mangano E, et al. EXCAVATOR: detecting copy number variants from whole-exome sequencing data. Genome Biol 2013;14:R120. https://doi.org/10.1186/gb-2013-14-10-r120
  19. Fu S, Zhao J, Bai H, Duan J, Wang Z, An T, et al. High-fidelity of non-small cell lung cancer xenograft models derived from bronchoscopy-guided biopsies. Thorac Cancer 2016;7:100-110. https://doi.org/10.1111/1759-7714.12291
  20. Fujii E, Kato A, Chen YJ, Matsubara K, Ohnishi Y, Suzuki M. Characterization of EBV-related lymphoproliferative lesions arising in donor lymphocytes of transplanted human tumor tissues in the NOG mouse. Exp Anim 2014;63:289-296. https://doi.org/10.1538/expanim.63.289
  21. Dieter SM, Giessler KM, Kriegsmann M, Dubash TD, Mohrmann L, Schulz ER, et al. Patient-derived xenografts of gastrointestinal cancers are susceptible to rapid and delayed B-lymphoproliferation. Int J Cancer 2017;140:1356-1363. https://doi.org/10.1002/ijc.30561
  22. Morgan KM, Riedlinger GM, Rosenfeld J, Ganesan S, Pine SR. Patient-derived xenograft models of non-small cell lung cancer and their potential utility in personalized medicine. Front Oncol 2017;7:2.
  23. Chakravarty D, Gao J, Phillips SM, Kundra R, Zhang H, Wang J, et al. OncoKB: a precision oncology knowledge base. JCO Precis Oncol 2017 May 16 [Epub]. https://doi.org/10.1200/PO.17.00011.
  24. Rhodes DR, Kalyana-Sundaram S, Mahavisno V, Varambally R, Yu J, Briggs BB, et al. Oncomine 3.0: genes, pathways, and net works in a collection of 18,000 cancer gene expression profiles. Neoplasia 2007;9:166-180. https://doi.org/10.1593/neo.07112
  25. Ananda G, Mockus S, Lundquist M, Spotlow V, Simons A, Mitchell T, et al. Development and validation of the JAX Cancer Treatment Profile for detection of clinically actionable mutations in solid tumors. Exp Mol Pathol 2015;98:106-112. https://doi.org/10.1016/j.yexmp.2014.12.009