Skip to main content
SpringerLink
Log in

Assessing Protein Expression in Patient-Derived Xenografts Using Western Blotting

  • Protocol
  • First Online:
Patient-Derived Xenografts

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2806))

  • 150 Accesses

Abstract

The use of patient-derived xenografts (PDXs) in cancer research is increasing due to their ability to closely mimic the features of patient tumors. The ability to quickly and robustly measure protein expression levels in these tissues is a key methodology required in a broad range of experimental designs. Western blotting (WB) is a cost effective and simple tool that is highly specific and sensitive for detecting and quantifying individual proteins, posttranslational modifications and aberrant signaling pathways. Here, we described a method to assess protein expression in PDX tissues using WB to detect proteins involved in cell growth signaling pathways.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Abdolahi S, Ghazvinian Z, Muhammadnejad S et al (2022) Patient-derived xenograft (PDX) models, applications and challenges in cancer research. J Transl Med 20(1):206. https://doi.org/10.1186/s12967-022-03405-8

    Article  PubMed  PubMed Central  Google Scholar 

  2. Hidalgo M, Amant F, Biankin AV et al (2014) Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov 4(9):998–1013. https://doi.org/10.1158/2159-8290.Cd-14-0001

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Bhimani J, Ball K, Stebbing J (2020) Patient-derived xenograft models—the future of personalised cancer treatment. Br J Cancer 122(5):601–602. https://doi.org/10.1038/s41416-019-0678-0

    Article  PubMed  PubMed Central  Google Scholar 

  4. DeRose YS, Wang G, Lin Y-C et al (2011) Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nat Med 17(11):1514–1520. https://doi.org/10.1038/nm.2454

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Tentler JJ, Tan AC, Weekes CD et al (2012) Patient-derived tumour xenografts as models for oncology drug development. Nat Rev Clin Oncol 9(6):338–350. https://doi.org/10.1038/nrclinonc.2012.61

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Reyal F, Guyader C, Decraene C et al (2012) Molecular profiling of patient-derived breast cancer xenografts. Breast Cancer Res 14(1):R11. https://doi.org/10.1186/bcr3095

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Wang D, Pham N-A, Tong J et al (2017) Molecular heterogeneity of non-small cell lung carcinoma patient-derived xenografts closely reflect their primary tumors. Int J Cancer 140(3):662–673. https://doi.org/10.1002/ijc.30472

    Article  CAS  PubMed  Google Scholar 

  8. Yoshida GJ (2020) Applications of patient-derived tumor xenograft models and tumor organoids. J Hematol Oncol 13(1):4. https://doi.org/10.1186/s13045-019-0829-z

    Article  PubMed  PubMed Central  Google Scholar 

  9. Lundy J, Jenkins BJ, Saad MI (2021) A method for the establishment of human lung adenocarcinoma patient-derived xenografts in mice. In: Santiago-Cardona PG (ed) Lung cancer: methods and protocols. Springer US, New York, pp 165–173. https://doi.org/10.1007/978-1-0716-1278-1_13

    Chapter  Google Scholar 

  10. Jung J, Seol HS, Chang S (2018) The generation and application of patient-derived xenograft model for cancer research. Cancer Res Treat 50(1):1–10. https://doi.org/10.4143/crt.2017.307

    Article  CAS  PubMed  Google Scholar 

  11. Sugiura R, Satoh R, Takasaki T (2021) ERK: a double-edged sword in cancer. ERK-dependent apoptosis as a potential therapeutic strategy for cancer. Cells 10(10). https://doi.org/10.3390/cells10102509

  12. Ma JH, Qin L, Li X (2020) Role of STAT3 signaling pathway in breast cancer. Cell Commun Signal 18(1):33. https://doi.org/10.1186/s12964-020-0527-z

    Article  PubMed  PubMed Central  Google Scholar 

  13. Revathidevi S, Munirajan AK (2019) Akt in cancer: mediator and more. Semin Cancer Biol 59:80–91. https://doi.org/10.1016/j.semcancer.2019.06.002

    Article  CAS  PubMed  Google Scholar 

  14. Vogelstein B, Kinzler KW (2004) Cancer genes and the pathways they control. Nat Med 10(8):789–799. https://doi.org/10.1038/nm1087

    Article  CAS  PubMed  Google Scholar 

  15. Sanchez-Vega F, Mina M, Armenia J et al (2018) Oncogenic signaling pathways in the cancer genome atlas. Cell 173(2):321–337.e310. https://doi.org/10.1016/j.cell.2018.03.035

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Xiang Y, Zheng Y, Liu S et al (2021) Comparison of the sensitivity of Western blotting between PVDF and NC membranes. Sci Rep 11(1):12022. https://doi.org/10.1038/s41598-021-91521-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Vallejo-Illarramendi A, Marciano DK, Reichardt LF (2013) A novel method that improves sensitivity of protein detection in PAGE and Western blot. Electrophoresis 34(8):1148–1150. https://doi.org/10.1002/elps.201200534

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Mishra M, Tiwari S, Gomes AV (2017) Protein purification and analysis: next generation Western blotting techniques. Exp Rev Proteomics 14(11):1037–1053. https://doi.org/10.1080/14789450.2017.1388167

    Article  CAS  Google Scholar 

  19. Cohen P, Cross D, Jänne PA (2021) Kinase drug discovery 20 years after imatinib: progress and future directions. Nat Rev Drug Discov 20(7):551–569. https://doi.org/10.1038/s41573-021-00195-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Drug Delivery Disposition & Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia

    Bruna Rossi Herling, Moore Zhe Chen & Victoria M. McLeod

Authors
  1. Bruna Rossi Herling
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Moore Zhe Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Victoria M. McLeod
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bruna Rossi Herling .

Editor information

Editors and Affiliations

  1. South Australian immunoGENomics Cancer Institute (SAiGENCI), University of Adelaide, Adelaide, SA, Australia

    Mohamed I. Saad

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Rossi Herling, B., Chen, M.Z., McLeod, V.M. (2024). Assessing Protein Expression in Patient-Derived Xenografts Using Western Blotting. In: Saad, M.I. (eds) Patient-Derived Xenografts. Methods in Molecular Biology, vol 2806. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3858-3_15

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-3858-3_15

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3857-6

  • Online ISBN: 978-1-0716-3858-3

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation