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Studies of Cancer Heterogeneity Using PDX Models

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Book cover Patient-Derived Xenograft Models of Human Cancer

Part of the book series: Molecular and Translational Medicine ((MOLEMED))

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Abstract

Xenograft models based on cultured cancer cell lines have been used for decades in the discovery and development of anticancer drugs. In the last decade, however, patient-derived xenografts (PDXs), based on engraftment of human cancer tissues, have started to become the preferred tools in drug discovery and preclinical studies as they have clear advantages over the cell line-based models. They include improved predictive power of drug efficacy due to better recapitulation of the complexity of human malignancies such as tumor heterogeneity, an important phenomenon for the design of therapeutic strategies. In this chapter, we review various aspects of tumor heterogeneity in PDXs in the light of recent advances in research.

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Abbreviations

ABC:

Activated B-cell

AI:

Allelic imbalance

BCR:

B-cell receptor

CAF:

Cancer-associated fibroblasts

CCC:

Consensus clustering classification

CNA:

Copy number alterations

DLBCL:

Diffuse large B-cell lymphoma

ECM:

Extracellular matrix

EGFR:

Epidermal growth factor receptor

HNSCC:

Head and neck squamous cell carcinomas

JUND:

Jun D proto-oncogene

LBCL:

Large B-cell lymphoma

PDXs:

Patient-derived xenografts

TAM:

Tumor-associated macrophages

TGFBR3:

Transforming growth factor b receptor 3

TNBCs:

Triple negative breast cancers

Treg :

Regulatory T-cell

References

  1. 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(11):1318–25. doi:10.1038/nm.3954.

    Article  CAS  PubMed  Google Scholar 

  2. Sausville EA, Burger AM. Contributions of human tumor xenografts to anticancer drug development. Cancer Res. 2006;66(7):3351–3354. discussion 4. doi:10.1158/0008-5472.CAN-05-3627.

  3. Siolas D, Hannon GJ. Patient-derived tumor xenografts: transforming clinical samples into mouse models. Cancer Res. 2013;73(17):5315–9. doi:10.1158/0008-5472.CAN-13-1069.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Guenot D, Guerin E, Aguillon-Romain S, Pencreach E, Schneider A, Neuville A, et al. Primary tumour genetic alterations and intra-tumoral heterogeneity are maintained in xenografts of human colon cancers showing chromosome instability. J Pathol. 2006;208(5):643–52. doi:10.1002/path.1936.

    Article  CAS  PubMed  Google Scholar 

  5. Dobbin ZC, Katre AA, Steg AD, Erickson BK, Shah MM, Alvarez RD, et al. Using heterogeneity of the patient-derived xenograft model to identify the chemoresistant population in ovarian cancer. Oncotarget. 2014;5(18):8750–64. doi:10.18632/oncotarget.2373.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Chapuy B, Cheng H, Watahiki A, Ducar MD, Tan Y, Chen L, et al. Diffuse large B-cell lymphoma patient-derived xenograft models capture the molecular and biological heterogeneity of the disease. Blood. 2016;127(18):2203–13. doi:10.1182/blood-2015-09-672352.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Seol HS, Kang HJ, Lee SI, Kim NE, Kim TI, Chun SM, et al. Development and characterization of a colon PDX model that reproduces drug responsiveness and the mutation profiles of its original tumor. Cancer Lett. 2014;345(1):56–64. doi:10.1016/j.canlet.2013.11.010.

    Article  CAS  PubMed  Google Scholar 

  8. Kim MP, Evans DB, Wang H, Abbruzzese JL, Fleming JB, Gallick GE. Generation of orthotopic and heterotopic human pancreatic cancer xenografts in immunodeficient mice. Nat Protoc. 2009;4(11):1670–80. doi:10.1038/nprot.2009.171.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Fleming JM, Miller TC, Meyer MJ, Ginsburg E, Vonderhaar BK. Local regulation of human breast xenograft models. J Cell Physiol. 2010;224(3):795–806. doi:10.1002/jcp.22190.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Petrillo LA, Wolf DM, Kapoun AM, Wang NJ, Barczak A, Xiao Y, et al. Xenografts faithfully recapitulate breast cancer-specific gene expression patterns of parent primary breast tumors. Breast Cancer Res Treat. 2012;135(3):913–22. doi:10.1007/s10549-012-2226-y.

    Article  CAS  PubMed  Google Scholar 

  11. Fichtner I, Rolff J, Soong R, Hoffmann J, Hammer S, Sommer A, et al. Establishment of patient-derived non-small cell lung cancer xenografts as models for the identification of predictive biomarkers. Clin Cancer Res. 2008;14(20):6456–68. doi:10.1158/1078-0432.CCR-08-0138.

    Article  CAS  PubMed  Google Scholar 

  12. Zhao X, Liu Z, Yu L, Zhang Y, Baxter P, Voicu H, et al. Global gene expression profiling confirms the molecular fidelity of primary tumor-based orthotopic xenograft mouse models of medulloblastoma. Neuro-Oncology. 2012;14(5):574–83. doi:10.1093/neuonc/nos061.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Gu Q, Zhang B, Sun H, Xu Q, Tan Y, Wang G, et al. Genomic characterization of a large panel of patient-derived hepatocellular carcinoma xenograft tumor models for preclinical development. Oncotarget. 2015;6(24):20160–76. doi:10.18632/oncotarget.3969.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Ding L, Ellis MJ, Li S, Larson DE, Chen K, Wallis JW, et al. Genome remodelling in a basal-like breast cancer metastasis and xenograft. Nature. 2010;464(7291):999–1005. doi:10.1038/nature08989.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Li H, Wheeler S, Park Y, Ju Z, Thomas SM, Fichera M, et al. Proteomic characterization of head and neck cancer patient-derived xenografts. Mol Cancer Res. 2016;14(3):278–86. doi:10.1158/1541-7786.MCR-15-0354.

    Article  CAS  PubMed  Google Scholar 

  16. Kabos P, Finlay-Schultz J, Li C, Kline E, Finlayson C, Wisell J, et al. Patient-derived luminal breast cancer xenografts retain hormone receptor heterogeneity and help define unique estrogen-dependent gene signatures. Breast Cancer Res Treat. 2012;135(2):415–32. doi:10.1007/s10549-012-2164-8.

    Article  CAS  PubMed  Google Scholar 

  17. Kanaya N, Somlo G, Wu J, Frankel P, Kai M, Liu X et al. Characterization of patient-derived tumor xenografts (PDXs) as models for estrogen receptor positive (ER+HER2− and ER+HER2+) breast cancers. J Steroid Biochem Mol Biol. 2016. doi:10.1016/j.jsbmb.2016.05.001.

  18. Burgenske DM, Monsma DJ, Dylewski D, Scott SB, Sayfie AD, Kim DG, et al. Establishment of genetically diverse patient-derived xenografts of colorectal cancer. Am J Cancer Res. 2014;4(6):824–37.

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Lengyel E. Ovarian cancer development and metastasis. Am J Pathol. 2010;177(3):1053–64. doi:10.2353/ajpath.2010.100105.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Lengyel E, Burdette JE, Kenny HA, Matei D, Pilrose J, Haluska P, et al. Epithelial ovarian cancer experimental models. Oncogene. 2014;33(28):3619–33. doi:10.1038/onc.2013.321.

    Article  CAS  PubMed  Google Scholar 

  21. Domcke S, Sinha R, Levine DA, Sander C, Schultz N. Evaluating cell lines as tumour models by comparison of genomic profiles. Nat Commun. 2013;4:2126. doi:10.1038/ncomms3126.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Rasmussen AA, Cullen KJ. Paracrine/autocrine regulation of breast cancer by the insulin-like growth factors. Breast Cancer Res Treat. 1998;47(3):219–33.

    Article  CAS  PubMed  Google Scholar 

  23. van Roozendaal CE, Gillis AJ, Klijn JG, van Ooijen B, Claassen CJ, Eggermont AM, et al. Loss of imprinting of IGF2 and not H19 in breast cancer, adjacent normal tissue and derived fibroblast cultures. FEBS Lett. 1998;437(1–2):107–11.

    Article  PubMed  Google Scholar 

  24. Vermeulen L, De Sousa EMF, van der Heijden M, Cameron K, de Jong JH, Borovski T, et al. Wnt activity defines colon cancer stem cells and is regulated by the microenvironment. Nat Cell Biol. 2010;12(5):468–76. doi:10.1038/ncb2048.

    Article  CAS  PubMed  Google Scholar 

  25. Williams SA, Anderson WC, Santaguida MT, Dylla SJ. Patient-derived xenografts, the cancer stem cell paradigm, and cancer pathobiology in the 21st century. Lab Invest. 2013;93(9):970–82. doi:10.1038/labinvest.2013.92.

    Article  PubMed  Google Scholar 

  26. Scott CL, Becker MA, Haluska P, Samimi G. Patient-derived xenograft models to improve targeted therapy in epithelial ovarian cancer treatment. Front Oncol. 2013;3:295. doi:10.3389/fonc.2013.00295.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Stordal B, Timms K, Farrelly A, Gallagher D, Busschots S, Renaud M, et al. BRCA1/2 mutation analysis in 41 ovarian cell lines reveals only one functionally deleterious BRCA1 mutation. Mol Oncol. 2013;7(3):567–79. doi:10.1016/j.molonc.2012.12.007.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Diaz Jr LA, Williams RT, Wu J, Kinde I, Hecht JR, Berlin J, et al. The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers. Nature. 2012;486(7404):537–40. doi:10.1038/nature11219.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012;486(7403):346–52. doi:10.1038/nature10983.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Bashashati A, Ha G, Tone A, Ding J, Prentice LM, Roth A, et al. Distinct evolutionary trajectories of primary high-grade serous ovarian cancers revealed through spatial mutational profiling. J Pathol. 2013;231(1):21–34. doi:10.1002/path.4230.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Maley CC, Galipeau PC, Finley JC, Wongsurawat VJ, Li X, Sanchez CA, et al. Genetic clonal diversity predicts progression to esophageal adenocarcinoma. Nat Genet. 2006;38(4):468–73. doi:10.1038/ng1768.

    Article  CAS  PubMed  Google Scholar 

  32. Shah SP, Roth A, Goya R, Oloumi A, Ha G, Zhao Y, et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature. 2012;486(7403):395–9. doi:10.1038/nature10933.

    CAS  PubMed  Google Scholar 

  33. Anderson K, Lutz C, van Delft FW, Bateman CM, Guo Y, Colman SM, et al. Genetic variegation of clonal architecture and propagating cells in leukaemia. Nature. 2011;469(7330):356–61. doi:10.1038/nature09650.

    Article  CAS  PubMed  Google Scholar 

  34. Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med. 2012;366(10):883–92. doi:10.1056/NEJMoa1113205.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Eirew P, Steif A, Khattra J, Ha G, Yap D, Farahani H, et al. Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution. Nature. 2015;518(7539):422–6. doi:10.1038/nature13952.

    Article  CAS  PubMed  Google Scholar 

  36. Aparicio S, Hidalgo M, Kung AL. Examining the utility of patient-derived xenograft mouse models. Nat Rev Cancer. 2015;15(5):311–6. doi:10.1038/nrc3944.

    Article  CAS  PubMed  Google Scholar 

  37. Rosfjord E, Lucas J, Li G, Gerber HP. Advances in patient-derived tumor xenografts: from target identification to predicting clinical response rates in oncology. Biochem Pharmacol. 2014;91(2):135–43. doi:10.1016/j.bcp.2014.06.008.

    Article  CAS  PubMed  Google Scholar 

  38. Quail DF, Joyce JA. Microenvironmental regulation of tumor progression and metastasis. Nat Med. 2013;19(11):1423–37. doi:10.1038/nm.3394.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Straussman R, Morikawa T, Shee K, Barzily-Rokni M, Qian ZR, Du J, et al. Tumour micro-environment elicits innate resistance to RAF inhibitors through HGF secretion. Nature. 2012;487(7408):500–4. doi:10.1038/nature11183.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Michor F, Weaver VM. Understanding tissue context influences on intratumour heterogeneity. Nat Cell Biol. 2014;16(4):301–2. doi:10.1038/ncb2942.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Wang CC, Bajikar SS, Jamal L, Atkins KA, Janes KA. A time- and matrix-dependent TGFBR3-JUND-KRT5 regulatory circuit in single breast epithelial cells and basal-like premalignancies. Nat Cell Biol. 2014;16(4):345–56. doi:10.1038/ncb2930.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Cassidy JW. Nanotechnology in the regeneration of complex tissues. Bone Tissue Reg Insights. 2014;5:25–35. doi:10.4137/BTRI.S12331.

    Article  CAS  Google Scholar 

  43. Gubin MM, Zhang X, Schuster H, Caron E, Ward JP, Noguchi T, et al. Checkpoint blockade cancer immunotherapy targets tumour-specific mutant antigens. Nature. 2014;515(7528):577–81. doi:10.1038/nature13988.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Schmidt M, Bohm D, von Torne C, Steiner E, Puhl A, Pilch H, et al. The humoral immune system has a key prognostic impact in node-negative breast cancer. Cancer Res. 2008;68(13):5405–13. doi:10.1158/0008-5472.CAN-07-5206.

    Article  CAS  PubMed  Google Scholar 

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Author information

Authors and Affiliations

  1. Shanghai LIDE Biotech, Co. Ltd., Pudong, Shanghai, 201203, People’s Republic of China

    Danyi Wen M.D., M.B.A., Feifei Zhang & Yuan Long

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  1. Danyi Wen M.D., M.B.A.
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  2. Feifei Zhang
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  3. Yuan Long
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Corresponding author

Correspondence to Danyi Wen M.D., M.B.A. .

Editor information

Editors and Affiliations

  1. Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada

    Yuzhuo Wang

  2. Department of Experimental Therapeutics, BC Cancer Research Centre, Vancouver, British Columbia, Canada

    Dong Lin

  3. Living Tumor Laboratory, BC Cancer Agency/Vancouver Prostate Centre, Vancouver, British Columbia, Canada

    Peter W. Gout

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Wen, D., Zhang, F., Long, Y. (2017). Studies of Cancer Heterogeneity Using PDX Models. In: Wang, Y., Lin, D., Gout, P. (eds) Patient-Derived Xenograft Models of Human Cancer . Molecular and Translational Medicine. Humana Press, Cham. https://doi.org/10.1007/978-3-319-55825-7_5

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  • DOI: https://doi.org/10.1007/978-3-319-55825-7_5

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  • Publisher Name: Humana Press, Cham

  • Print ISBN: 978-3-319-55824-0

  • Online ISBN: 978-3-319-55825-7

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