Advertisement

Urine pp 105-117 | Cite as

Changes in the Urinary Proteome in a Patient-Derived Xenograft (PDX) Nude Mouse Model of Colorectal Tumor

  • Yongtao Liu
Chapter

Abstract

In this report, the urinary proteome from a patient-derived xenograft (PDX) model was examined at the peptide level to study the origins of urinary proteins in tumor-bearing nude mice. Urine was collected from PDX mice before and after colorectal tumor implantation. A total of 4318 unique peptides were identified, and 78 unambiguous human-origin peptides were discerned in the PDX model urine. Unlike the differential urinary protein composition of tumor-bearing immunocompetent rat models, the differential urinary proteins in the PDX model did not include host immune response proteins. This study demonstrates that tumor-secreted proteins can be observed in the urine proteome of the PDX model. However, immune response proteins, which are very early candidate tumor biomarkers, are not present in the urine of PDX model mice; this absence is due to immune deficiency. Therefore, immunodeficient animals may not be suitable models for searching for early immunity-associated tumor biomarkers in the urine.

Keywords

Proteomics PDX model Urine Cancer biomarkers 

Notes

Acknowledgment

Part of this chapter is based on published article: [1] Yongtao Liu, Youzhu Wang, Zhixiang Cao, Youhe Gao. Changes in the urinary proteome in a patient-derived xenograft (PDX) nude mouse model of colorectal tumor. Scientific report, 2019, 9(1): 4975.

References

  1. Emmink BL, et al. The secretome of colon cancer stem cells contains drug-metabolizing enzymes. J Proteome. 2013;91:84–96.CrossRefGoogle Scholar
  2. Fernandez-Olavarria A, et al. The role of serum biomarkers in the diagnosis and prognosis of oral cancer: a systematic review. J Clin Exp Dent. 2016;8:e184–93.PubMedPubMedCentralGoogle Scholar
  3. Gao Y. Urine-an untapped goldmine for biomarker discovery? Sci China Life Sci. 2013;56:1145–6.CrossRefGoogle Scholar
  4. Gao Y. Patient-derived xenograft models for urinary biomarker discovery. Med Crave. 2016;1Google Scholar
  5. Hidalgo M, et al. Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov. 2014;4:998–1013.CrossRefGoogle Scholar
  6. Nandy SK, Seal A. Structural dynamics investigation of human family 1 & 2 Cystatin-Cathepsin L1 interaction: a comparison of binding modes. PLoS One. 2016;11Google Scholar
  7. Ni Y, Zhang F, An M, Yin W, Gao Y. Early candidate biomarkers found from urine of glioblastoma multiforme rat before changes in MRI. Sci China Life Sci. 2018;61:982–7.CrossRefGoogle Scholar
  8. Siolas D, Hannon GJ. Patient-derived tumor xenografts: transforming clinical samples into mouse models. Cancer Res. 2013;73:5315–9.CrossRefGoogle Scholar
  9. Sun W, et al. Human urine proteome analysis by three separation approaches. Proteomics. 2005;5:4994–5001.CrossRefGoogle Scholar
  10. Tentler JJ, et al. Patient-derived tumour xenografts as models for oncology drug development. Nat Rev Clin Oncol. 2012;9:338–50.CrossRefGoogle Scholar
  11. Wu J, Guo Z, Gao Y. Dynamic changes of urine proteome in a Walker 256 tumor-bearing rat model. Cancer Med. 2017;6:2713–22.CrossRefGoogle Scholar
  12. Yin J, Shao C, Jia L, Gao Y. Comparison at the peptide level with post-translational modification consideration reveals more differences between two unenriched samples. Rapid Commun Mass Spectrom. 2014;28:1364–70.CrossRefGoogle Scholar
  13. Zaman U, Urlaub H, Abbasi A. Protein profiling of non-model plant Cuminum cyminum by gel-based proteomic approach. Phytochem Anal. 2018;29:242–9.CrossRefGoogle Scholar
  14. Zhao M, et al. A comprehensive analysis and annotation of human normal urinary proteome. Sci Rep. 2016;7:3024.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Yongtao Liu
    • 1
  1. 1.Beijing Key Laboratory of Genetic Engineering Drugs and Biotechnology, Department of Biochemistry and Molecular BiologyBeijing Normal UniversityBeijingPeople’s Republic of China

Personalised recommendations