Cancer and Metastasis Reviews

, Volume 35, Issue 4, pp 547–573 | Cite as

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

  • Lacey E. Dobrolecki
  • Susie D. Airhart
  • Denis G. Alferez
  • Samuel Aparicio
  • Fariba Behbod
  • Mohamed Bentires-Alj
  • Cathrin Brisken
  • Carol J. Bult
  • Shirong Cai
  • Robert B. Clarke
  • Heidi Dowst
  • Matthew J. Ellis
  • Eva Gonzalez-Suarez
  • Richard D. Iggo
  • Peter Kabos
  • Shunqiang Li
  • Geoffrey J. Lindeman
  • Elisabetta Marangoni
  • Aaron McCoy
  • Funda Meric-Bernstam
  • Helen Piwnica-Worms
  • Marie-France Poupon
  • Jorge Reis-Filho
  • Carol A. Sartorius
  • Valentina Scabia
  • George Sflomos
  • Yizheng Tu
  • François Vaillant
  • Jane E. Visvader
  • Alana Welm
  • Max S. Wicha
  • Michael T. Lewis
Article

Abstract

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and “Triple-negative” (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward “credentialing” of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research.

Keywords

Patient-derived xenograft Breast cancer Immunocompromised/immunodeficient mice Translational research PDX consortium 

Notes

Acknowledgements

Samuel Aparicio—Supported by the BC Cancer Foundation, Canadian Breast Cancer Foundation, CIHR, Canadian Foundation for Innovation, Stand Up to Cancer Canada, Canadian Cancer Research Institute, and Terry Fox Research Institute

Fariba Behbod—Supported by R01-NIH/NCI-R01CA172764, NIH/NCI-R21CA187890, AACR-Breast Cancer Research Foundation-2014 Translational Breast Cancer Research, and NIH/NCI-R21CA185460

Cathrin Brisken—The research leading to these results has received support from the Swiss Cancer League, the SNF, and the Innovative Medicines Initiative Joint Undertaking (grant agreement no. 115188) for the PREDECT consortium (www.predect.eu) resources composed of financial contribution from EU-FP7 and EFPIA companies in kind contribution. The Web address of the Innovative Medicines Initiative is http://www.imi.europa.eu/.

Carol J. Bult—This work was supported in part by the Maine Cancer Foundation, The Jackson Laboratory Director’s Innovation Fund, and JAX Cancer Center grant P30 CA034196.

Matthew Ellis—Dr. Ellis is a McNair Medical Institute Scholar and a CPRIT Established Investigator (CPRIT RR140033).

Robert Clarke and Denis Alferez—This work was funded by Cancer Research UK and Breast Cancer Now. We would like to thank all patients who donated tissue to this study and the Manchester Cancer Research Centre Biobank for consenting patients and collecting tissue.

Eva Gonzalez-Suarez—This work was supported in part by grants to Eva González Suárez by the Spanish Ministry of Economy and Competitivity MINECO and from the ISCIII (SAF2008-01975, SAF2011-22893, SAF2014-55997), PIE13/00022, co-funded by FEDER funds/European Regional Development Fund (ERDF—a way to build Europe), by a Career Catalyst grant from the Susan Komen Foundation and by institutional funds provided by the Generalitat de Catalunya.

Richard Iggo—This work was supported by the “Fondation pour la lutte contre le cancer et pour des recherches medico-biologiques,” the INCa-DGOS-INSERM 6046 SIRIC BRIO grant, and the French Cancer League (Comité de la Charente Maritime).

Peter Kabos—NIH grant CA164048, Grohne Cancer Research Fund

Michael T. Lewis—This work was supported in part by the Breast Cancer Research Foundation, the Emma Jacobs Clinical Breast Cancer Fund, the Susan G. Komen Foundation, Cancer Fighters of Houston, BCM Cancer Center grant P30 CA125123, BCM Breast Cancer SPORE P50 CA50183, NIH/NCI grant R01 CA112305, and NIH/NCI grant U54 CA149196. The authors also acknowledge the joint participation by Diana Henry Helis Medical Research Foundation through its direct engagement in the continuous active conduct of medical research in conjunction with Baylor College of Medicine and its “Blood-borne BioMarkers for Detection of Breast Cancer” Program.

Shunqiang Li—Susan G. Komen for the Cure (BCTR0707808, KG090422, and PG12220321), Breast Cancer Research Foundation, CTSA grant UL1 RR024992, and The Fashion Footwear Charitable Foundation, Inc.

Geoffrey J. Lindeman and Jane E. Visvader—Received funding support from the Australian National Health and Medical Research Council (NHMRC; 1016701, 1040978, 1086727, 1085191); NHMRC Independent Research Institute Infrastructure Support Scheme (IRIISS) (to WEHI); the Victorian State Government through the Victorian Cancer Agency and Operational Infrastructure Support; the National Breast Cancer Foundation (Australia); the Cancer Therapeutics CRC; and the Australian Cancer Research Foundation. G.J.L. is supported by an NHMRC Research Fellowship (1078730); J.E.V. is supported by an NHMRC Australia Fellowship (1037230).

Funda Meric-Bernstam—MD Anderson Moon Shots funds and Nellie B. Connally Breast Cancer Research Endowment

Helen Piwnica-Worms—This work was supported in part by the Cazalot Breast Cancer Model Resource, The Susan G. Komen Foundation, and The Cancer Prevention and Research Institute of Texas (CPRIT) RP150148.

Jorge Reis-Filho—Research reported in this publication was supported in part by a grant from the Breast Cancer Research Foundation and a Cancer Center Support grant of the National Institutes of Health/National Cancer Institute (grant no. P30CA008748). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Carol Sartorius—NIH grant CA140985.

Alana Welm—The Noreen Fraser Foundation, METAvivor Foundation, AACR Susan G. Komen Career Catalyst award, DOD Breast Cancer Research Program grants W81XWH-08-1-0109 and BC112623, and NIH/NCI grants 1R01CA166422 and 1R01CA173903

Max Wicha—R35: CA129765; RO1 CA101860, Komen for the Cure Promise grant, and Breast Cancer Research Foundation grant

Compliance with ethical standards

Competing financial interests

Lacey E. Dobrolecki: Compensated part-time employee of StemMed, Ltd.

Susie D. Airhart: No competing financial interests.

Denis G. Alferez: No competing financial interests.

Samuel Aparicio: No competing financial interests.

Fariba Behbod: No competing financial interests.

Mohamed Bentires-Alj: No competing financial interests.

Cathrin Brisken: No competing financial interests.

Carol J. Bult: No competing financial interests.

Robert B. Clarke: No competing financial interests.

Matthew J. Ellis: Receives income from Washington University in St. Louis which has licensed the WHIM series of breast PDX for commercial distribution.

Eva Gonzalez Suarez: No competing financial interests.

Richard Iggo: No competing financial interests.

Peter Kabos: No competing financial interests.

Michael T. Lewis: Receives income from Baylor College of Medicine which has licensed the BCM series of breast PDX for commercial use. Founder and limited partner in StemMed Ltd. and a Manager in StemMed Holdings LLC.

Shunqiang Li: Receives income from Washington University in St. Louis which has licensed the WHIM series of breast PDX for commercial distribution.

Geoffrey J. Lindeman: No competing financial interests.

Elisabetta.Marangoni: No competing financial interests.

Funda Meric-Bernstam: No competing financial interests.

Helen Piwnica-Worms: No competing financial interests.

Marie-France Poupon: Founder and Scientific Advisor to XenTech SA, Genopole, 4 rue Pierre Fontaine, 91000 Evry, France.

Jorge Reis-Filho: No competing financial interests.

Carol Sartorius: No competing financial interests.

Valentina Scabia: No competing financial interests.

George Sflomos: No competing financial interests.

François Vaillant: No competing financial interests.

Jane Visvader: No competing financial interests.

Alana Welm: Receives income if the University of Utah licenses the PDX models for commercial use.

Max S. Wicha: No competing financial interests.

References

  1. 1.
    Allred, D. C., Wu, Y., Mao, S., Nagtegaal, I. D., Lee, S., Perou, C. M., et al. (2008). Ductal carcinoma in situ and the emergence of diversity during breast cancer evolution. Clinical Cancer Research, 14(2), 370–378. doi: 10.1158/1078-0432.CCR-07-1127.PubMedCrossRefGoogle Scholar
  2. 2.
    Shipitsin, M., Campbell, L. L., Argani, P., Weremowicz, S., Bloushtain-Qimron, N., Yao, J., et al. (2007). Molecular definition of breast tumor heterogeneity. Cancer Cell, 11(3), 259–273. doi: 10.1016/j.ccr.2007.01.013.PubMedCrossRefGoogle Scholar
  3. 3.
    Allred, D. C., Harvey, J. M., Berardo, M., & Clark, G. M. (1998). Prognostic and predictive factors in breast cancer by immunohistochemical analysis. Modern Pathology, 11(2), 155–168.PubMedGoogle Scholar
  4. 4.
    Sorlie, T., Perou, C. M., Tibshirani, R., Aas, T., Geisler, S., Johnsen, H., et al. (2001). Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proceedings of the National Academy of Sciences of the United States of America, 98(19), 10869–10874. doi: 10.1073/pnas.191367098 98/19/10869.PubMedPubMedCentralCrossRefGoogle Scholar
  5. 5.
    Prat, A., Parker, J. S., Karginova, O., Fan, C., Livasy, C., Herschkowitz, J. I., et al. (2010). Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Research, 12(5), R68. doi: 10.1186/bcr2635.PubMedPubMedCentralCrossRefGoogle Scholar
  6. 6.
    Parker, J. S., Mullins, M., Cheang, M. C., Leung, S., Voduc, D., Vickery, T., et al. (2009). Supervised risk predictor of breast cancer based on intrinsic subtypes. Journal of Clinical Oncology, 27(8), 1160–1167. doi: 10.1200/JCO.2008.18.1370.PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Perou, C. M., Sorlie, T., Eisen, M. B., van de Rijn, M., Jeffrey, S. S., Rees, C. A., et al. (2000). Molecular portraits of human breast tumours. Nature, 406(6797), 747–752. doi: 10.1038/35021093.PubMedCrossRefGoogle Scholar
  8. 8.
    Hait, W. N. (2010). Anticancer drug development: the grand challenges. Nature Reviews. Drug Discovery, 9(4), 253–254. doi: 10.1038/nrd3144.PubMedCrossRefGoogle Scholar
  9. 9.
    Marusyk, A., & Polyak, K. (2010). Tumor heterogeneity: causes and consequences. [Research support, N.I.H., extramural research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S. Review]. Biochimica et Biophysica Acta, 1805(1), 105–117. doi: 10.1016/j.bbcan.2009.11.002.PubMedGoogle Scholar
  10. 10.
    Park, S. Y., Lee, H. E., Li, H., Shipitsin, M., Gelman, R., & Polyak, K. (2010). Heterogeneity for stem cell-related markers according to tumor subtype and histologic stage in breast cancer. [Research support, N.I.H., extramural research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S.]. Clinical cancer research : an official journal of the American Association for Cancer Research, 16(3), 876–887. doi: 10.1158/1078-0432.CCR-09-1532.CrossRefGoogle Scholar
  11. 11.
    Burstein, H. J., Temin, S., Anderson, H., Buchholz, T. A., Davidson, N. E., Gelmon, K. E., et al. (2014). Adjuvant endocrine therapy for women with hormone receptor-positive breast cancer: American society of clinical oncology clinical practice guideline focused update. [Practice guideline]. Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 32(21), 2255–2269. doi: 10.1200/JCO.2013.54.2258.CrossRefGoogle Scholar
  12. 12.
    Ramakrishna, N., Temin, S., Chandarlapaty, S., Crews, J. R., Davidson, N. E., Esteva, F. J., et al. (2014). Recommendations on disease management for patients with advanced human epidermal growth factor receptor 2-positive breast cancer and brain metastases: American Society of Clinical Oncology clinical practice guideline. [Practice guideline research support, non-U.S. Gov’t review]. Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 32(19), 2100–2108. doi: 10.1200/JCO.2013.54.0955.CrossRefGoogle Scholar
  13. 13.
    Telli, M. L., Timms, K. M., Reid, J., Hennessy, B., Mills, G. B., Jensen, K. C., et al. (2016). Homologous recombination deficiency (HRD) score predicts response to platinum-containing neoadjuvant chemotherapy in patients with triple-negative breast cancer. Clinical cancer research : an official journal of the American Association for Cancer Research, 22(15), 3764–3773. doi: 10.1158/1078-0432.CCR-15-2477.CrossRefGoogle Scholar
  14. 14.
    Herschkowitz, J. I., Simin, K., Weigman, V. J., Mikaelian, I., Usary, J., Hu, Z., et al. (2007). Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors. Genome Biology, 8(5), R76. doi: 10.1186/gb-2007-8-5-r76.PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Lim, E., Vaillant, F., Wu, D., Forrest, N. C., Pal, B., Hart, A. H., et al. (2009). Aberrant luminal progenitors as the candidate target population for basal tumor development in BRCA1 mutation carriers. Nature Medicine, 15(8), 907–913. doi: 10.1038/nm.2000.PubMedCrossRefGoogle Scholar
  16. 16.
    Li, X., Lewis, M. T., Huang, J., Gutierrez, C., Osborne, C. K., Wu, M. F., et al. (2008). Intrinsic resistance of tumorigenic breast cancer cells to chemotherapy. [Research support, N.I.H., extramural research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S.]. Journal of the National Cancer Institute, 100(9), 672–679. doi: 10.1093/jnci/djn123.PubMedCrossRefGoogle Scholar
  17. 17.
    Banerji, S., Cibulskis, K., Rangel-Escareno, C., Brown, K. K., Carter, S. L., Frederick, A. M., et al. (2012). Sequence analysis of mutations and translocations across breast cancer subtypes. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. Nature, 486(7403), 405–409. doi: 10.1038/nature11154.PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Curtis, C., Shah, S. P., Chin, S. F., Turashvili, G., Rueda, O. M., Dunning, M. J., et al. (2012). The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. Nature, 486(7403), 346–352. doi: 10.1038/nature10983.PubMedPubMedCentralGoogle Scholar
  19. 19.
    Network, T. C. G. A. (2012). Comprehensive molecular portraits of human breast tumours. [Research support, N.I.H., extramural research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S.]. Nature, 490(7418), 61–70. doi: 10.1038/nature11412.CrossRefGoogle Scholar
  20. 20.
    Shah, S. P., Roth, A., Goya, R., Oloumi, A., Ha, G., Zhao, Y., et al. (2012). The clonal and mutational evolution spectrum of primary triple-negative breast cancers. [Research support, N.I.H., extramural research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S.]. Nature, 486(7403), 395–399. doi: 10.1038/nature10933.PubMedGoogle Scholar
  21. 21.
    Stephens, P. J., Tarpey, P. S., Davies, H., Van Loo, P., Greenman, C., Wedge, D. C., et al. (2012). The landscape of cancer genes and mutational processes in breast cancer. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. Nature, 486(7403), 400–404. doi: 10.1038/nature11017.PubMedPubMedCentralGoogle Scholar
  22. 22.
    Pereira, B., Chin, S. F., Rueda, O. M., Vollan, H. K., Provenzano, E., Bardwell, H. A., et al. (2016). Erratum: the somatic mutation profiles of 2,433 breast cancers refine their genomic and transcriptomic landscapes. Nature Communications, 7, 11908. doi: 10.1038/ncomms11908.PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Pereira, B., Chin, S. F., Rueda, O. M., Vollan, H. K., Provenzano, E., Bardwell, H. A., et al. (2016). The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Nature Communications, 7, 11479. doi: 10.1038/ncomms11479.PubMedPubMedCentralCrossRefGoogle Scholar
  24. 24.
    Xu, H., Eirew, P., Mullaly, S. C., & Aparicio, S. (2014). The omics of triple-negative breast cancers. [Review]. Clinical Chemistry, 60(1), 122–133. doi: 10.1373/clinchem.2013.207167.PubMedCrossRefGoogle Scholar
  25. 25.
    Lehmann, B. D., Jovanovic, B., Chen, X., Estrada, M. V., Johnson, K. N., Shyr, Y., et al. (2016). Refinement of triple-negative breast cancer molecular subtypes: implications for neoadjuvant chemotherapy selection. PloS One, 11(6), e0157368. doi: 10.1371/journal.pone.0157368.PubMedPubMedCentralCrossRefGoogle Scholar
  26. 26.
    Le Du, F., Eckhardt, B. L., Lim, B., Litton, J. K., Moulder, S., Meric-Bernstam, F., et al. (2015). Is the future of personalized therapy in triple-negative breast cancer based on molecular subtype? [Research support, N.I.H., extramural research support, non-U.S. Gov’t review]. Oncotarget, 6(15), 12890–12908. doi: 10.18632/oncotarget.3849.PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Burstein, M. D., Tsimelzon, A., Poage, G. M., Covington, K. R., Contreras, A., Fuqua, S. A., et al. (2015). Comprehensive genomic analysis identifies novel subtypes and targets of triple-negative breast cancer. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. Clinical Cancer Research, 21(7), 1688–1698. doi: 10.1158/1078-0432.CCR-14-0432.PubMedCrossRefGoogle Scholar
  28. 28.
    Abramson, V. G., Lehmann, B. D., Ballinger, T. J., & Pietenpol, J. A. (2015). Subtyping of triple-negative breast cancer: implications for therapy. [Research support, N.I.H., extramural research support, non-U.S. Gov’t review]. Cancer, 121(1), 8–16. doi: 10.1002/cncr.28914.PubMedCrossRefGoogle Scholar
  29. 29.
    Prabhu, J. S., Korlimarla, A., Desai, K., Alexander, A., Raghavan, R., Anupama, C., et al. (2014). A majority of low (1-10%) ER positive breast cancers behave like hormone receptor negative tumors. Journal of Cancer, 5(2), 156–165. doi: 10.7150/jca.7668.PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Hammond, M. E., Hayes, D. F., Dowsett, M., Allred, D. C., Hagerty, K. L., Badve, S., et al. (2010). American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. Archives of Pathology & Laboratory Medicine, 134(6), 907–922. doi: 10.1043/1543-2165-134.6.907.Google Scholar
  31. 31.
    Allott, E. H., Geradts, J., Sun, X., Cohen, S. M., Zirpoli, G. R., Khoury, T., et al. (2016). Intratumoral heterogeneity as a source of discordance in breast cancer biomarker classification. Breast Cancer Research, 18(1), 68. doi: 10.1186/s13058-016-0725-1.PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Wolff, A. C., Hammond, M. E., Hicks, D. G., Dowsett, M., McShane, L. M., Allison, K. H., et al. (2014). Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. [Practice guideline]. Archives of Pathology & Laboratory Medicine, 138(2), 241–256. doi: 10.5858/arpa.2013-0953-SA.CrossRefGoogle Scholar
  33. 33.
    Nowell, P. C. (1976). The clonal evolution of tumor cell populations. [Research support, U.S. Gov’t, P.H.S.]. Science, 194(4260), 23–28.PubMedCrossRefGoogle Scholar
  34. 34.
    De Luca, F., Rotunno, G., Salvianti, F., Galardi, F., Pestrin, M., Gabellini, S., et al. (2016). Mutational analysis of single circulating tumor cells by next generation sequencing in metastatic breast cancer. Oncotarget. doi: 10.18632/oncotarget.8431.Google Scholar
  35. 35.
    Martelotto, L. G., Ng, C. K., Piscuoglio, S., Weigelt, B., & Reis-Filho, J. S. (2014). Breast cancer intra-tumor heterogeneity. [Research support, non-U.S. Gov’t review]. Breast Cancer Research, 16(3), 210. doi: 10.1186/bcr3658.PubMedPubMedCentralCrossRefGoogle Scholar
  36. 36.
    Beca, F., & Polyak, K. (2016). Intratumor heterogeneity in breast cancer. Advances in Experimental Medicine and Biology, 882, 169–189. doi: 10.1007/978-3-319-22909-6_7.PubMedCrossRefGoogle Scholar
  37. 37.
    Ding, L., Ellis, M. J., Li, S., Larson, D. E., Chen, K., Wallis, J. W., et al. (2010). Genome remodelling in a basal-like breast cancer metastasis and xenograft. Nature, 464(7291), 999–1005. doi: 10.1038/nature08989.PubMedPubMedCentralCrossRefGoogle Scholar
  38. 38.
    Ha, G., Roth, A., Khattra, J., Ho, J., Yap, D., Prentice, L. M., et al. (2014). TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data. [Research support, non-U.S. Gov’t]. Genome Research, 24(11), 1881–1893. doi: 10.1101/gr.180281.114.PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Nik-Zainal, S., Van Loo, P., Wedge, D. C., Alexandrov, L. B., Greenman, C. D., Lau, K. W., et al. (2012). The life history of 21 breast cancers. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. Cell, 149(5), 994–1007. doi: 10.1016/j.cell.2012.04.023.PubMedPubMedCentralCrossRefGoogle Scholar
  40. 40.
    Roth, A., Khattra, J., Yap, D., Wan, A., Laks, E., Biele, J., et al. (2014). PyClone: statistical inference of clonal population structure in cancer. [Research support, non-U.S. Gov’t]. Nature Methods, 11(4), 396–398. doi: 10.1038/nmeth.2883.PubMedPubMedCentralCrossRefGoogle Scholar
  41. 41.
    Walter, M. J., Shen, D., Ding, L., Shao, J., Koboldt, D. C., Chen, K., et al. (2012). Clonal architecture of secondary acute myeloid leukemia. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. The New England Journal of Medicine, 366(12), 1090–1098. doi: 10.1056/NEJMoa1106968.PubMedPubMedCentralCrossRefGoogle Scholar
  42. 42.
    Baslan, T., Kendall, J., Rodgers, L., Cox, H., Riggs, M., Stepansky, A., et al. (2012). Genome-wide copy number analysis of single cells. [Research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S.]. Nature Protocols, 7(6), 1024–1041. doi: 10.1038/nprot.2012.039.PubMedPubMedCentralCrossRefGoogle Scholar
  43. 43.
    Baslan, T., Kendall, J., Rodgers, L., Cox, H., Riggs, M., Stepansky, A., et al. (2016). Corrigendum: genome-wide copy number analysis of single cells. [Published erratum]. Nature Protocols, 11(3), 616. doi: 10.1038/nprot0316.616b.PubMedCrossRefGoogle Scholar
  44. 44.
    Eirew, P., Steif, A., Khattra, J., Ha, G., Yap, D., Farahani, H., et al. (2015). Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution. [Research support, non-U.S. Gov’t]. Nature, 518(7539), 422–426. doi: 10.1038/nature13952.PubMedCrossRefGoogle Scholar
  45. 45.
    Hou, Y., Song, L., Zhu, P., Zhang, B., Tao, Y., Xu, X., et al. (2012). Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm. [Research support, non-U.S. Gov’t]. Cell, 148(5), 873–885. doi: 10.1016/j.cell.2012.02.028.PubMedCrossRefGoogle Scholar
  46. 46.
    Navin, N., Kendall, J., Troge, J., Andrews, P., Rodgers, L., McIndoo, J., et al. (2011). Tumour evolution inferred by single-cell sequencing. [Research support, N.I.H., extramural research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S.]. Nature, 472(7341), 90–94. doi: 10.1038/nature09807.PubMedPubMedCentralCrossRefGoogle Scholar
  47. 47.
    Potter, N. E., Ermini, L., Papaemmanuil, E., Cazzaniga, G., Vijayaraghavan, G., Titley, I., et al. (2013). Single-cell mutational profiling and clonal phylogeny in cancer. [Research support, non-U.S. Gov’t]. Genome Research, 23(12), 2115–2125. doi: 10.1101/gr.159913.113.PubMedPubMedCentralCrossRefGoogle Scholar
  48. 48.
    Wang, Y., Waters, J., Leung, M. L., Unruh, A., Roh, W., Shi, X., et al. (2014). Clonal evolution in breast cancer revealed by single nucleus genome sequencing. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. Nature, 512(7513), 155–160. doi: 10.1038/nature13600.PubMedPubMedCentralCrossRefGoogle Scholar
  49. 49.
    Shah, S. P., Morin, R. D., Khattra, J., Prentice, L., Pugh, T., Burleigh, A., et al. (2009). Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature, 461(7265), 809–813. doi: 10.1038/nature08489.PubMedCrossRefGoogle Scholar
  50. 50.
    Campbell, P. J., Pleasance, E. D., Stephens, P. J., Dicks, E., Rance, R., Goodhead, I., et al. (2008). Subclonal phylogenetic structures in cancer revealed by ultra-deep sequencing. Proceedings of the National Academy of Sciences of the United States of America, 105(35), 13081–13086. doi: 10.1073/pnas.0801523105.PubMedPubMedCentralCrossRefGoogle Scholar
  51. 51.
    Marusyk, A., Tabassum, D. P., Altrock, P. M., Almendro, V., Michor, F., & Polyak, K. (2014). Non-cell-autonomous driving of tumour growth supports sub-clonal heterogeneity. [Research support, N.I.H., extramural research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S.]. Nature, 514(7520), 54–58. doi: 10.1038/nature13556.PubMedPubMedCentralCrossRefGoogle Scholar
  52. 52.
    Beckhove, P., Schutz, F., Diel, I. J., Solomayer, E. F., Bastert, G., Foerster, J., et al. (2003). Efficient engraftment of human primary breast cancer transplants in nonconditioned NOD/Scid mice. International Journal of Cancer, 105(4), 444–453. doi: 10.1002/ijc.11125.PubMedCrossRefGoogle Scholar
  53. 53.
    Visonneau, S., Cesano, A., Torosian, M. H., Miller, E. J., & Santoli, D. (1998). Growth characteristics and metastatic properties of human breast cancer xenografts in immunodeficient mice. The American Journal of Pathology, 152(5), 1299–1311.PubMedPubMedCentralGoogle Scholar
  54. 54.
    Zhang, X., Claerhout, S., Prat, A., Dobrolecki, L. E., Petrovic, I., Lai, Q., et al. (2013). A renewable tissue resource of phenotypically stable, biologically and ethnically diverse, patient-derived human breast cancer xenograft models. Cancer Research, 73(15), 4885–4897. doi: 10.1158/0008-5472.CAN-12-4081.PubMedPubMedCentralCrossRefGoogle Scholar
  55. 55.
    Fichtner, I., Becker, M., Zeisig, R., & Sommer, A. (2004). In vivo models for endocrine-dependent breast carcinomas: special considerations of clinical relevance. European Journal of Cancer, 40(6), 845–851. doi: 10.1016/j.ejca.2003.11.030.PubMedCrossRefGoogle Scholar
  56. 56.
    McManus, M. J., & Welsch, C. W. (1980). DNA synthesis of benign human breast tumors in the untreated athymic “nude” mouse. An in vivo model to study hormonal influences on growth of human breast tissues. Cancer, 45(8), 2160–2165.PubMedCrossRefGoogle Scholar
  57. 57.
    Murthy, M. S., Scanlon, E. F., Jelachich, M. L., Klipstein, S., & Goldschmidt, R. A. (1995). Growth and metastasis of human breast cancers in athymic nude mice. Clinical & Experimental Metastasis, 13(1), 3–15.CrossRefGoogle Scholar
  58. 58.
    Naundorf, H., Fichtner, I., Buttner, B., & Frege, J. (1992). Establishment and characterization of a new human oestradiol- and progesterone-receptor-positive mammary carcinoma serially transplantable in nude mice. Journal of Cancer Research and Clinical Oncology, 119(1), 35–40.PubMedCrossRefGoogle Scholar
  59. 59.
    Noel, A., Borcy, V., Bracke, M., Gilles, C., Bernard, J., Birembaut, P., et al. (1995). Heterotransplantation of primary and established human tumour cells in nude mice. Anticancer Research, 15(1), 1–7.PubMedGoogle Scholar
  60. 60.
    Outzen, H. C., & Custer, R. P. (1975). Growth of human normal and neoplastic mammary tissues in the cleared mammary fat pad of the nude mouse. Journal of the National Cancer Institute, 55(6), 1461–1466.PubMedGoogle Scholar
  61. 61.
    Rae-Venter, B., & Reid, L. M. (1980). Growth of human breast carcinomas in nude mice and subsequent establishment in tissue culture. Cancer Research, 40(1), 95–100.PubMedGoogle Scholar
  62. 62.
    Sakakibara, T., Xu, Y., Bumpers, H. L., Chen, F. A., Bankert, R. B., Arredondo, M. A., et al. (1996). Growth and metastasis of surgical specimens of human breast carcinomas in SCID mice. The Cancer Journal from Scientific American, 2(5), 291–300.PubMedGoogle Scholar
  63. 63.
    Sebesteny, A., Taylor-Papadimitriou, J., Ceriani, R., Millis, R., Schmitt, C., & Trevan, D. (1979). Primary human breast carcinomas transplantable in the nude mouse. Journal of the National Cancer Institute, 63(6), 1331–1337.PubMedGoogle Scholar
  64. 64.
    Sheffield, L. G., & Welsch, C. W. (1988). Transplantation of human breast epithelia to mammary-gland-free fat-pads of athymic nude mice: influence of mammotrophic hormones on growth of breast epithelia. International Journal of Cancer, 41(5), 713–719.PubMedCrossRefGoogle Scholar
  65. 65.
    Shultz, L. D., Ishikawa, F., & Greiner, D. L. (2007). Humanized mice in translational biomedical research. [Research support, N.I.H., extramural research support, non-U.S. Gov’t review]. Nature Reviews. Immunology, 7(2), 118–130. doi: 10.1038/nri2017.PubMedCrossRefGoogle Scholar
  66. 66.
    Zhang, X., & Lewis, M. T. (2013). Establishment of patient-derived xenograft (PDX) models of human breast cancer. Current Protocols in Mouse Biology, 3, 21–29. doi: 10.1002/9780470942390.mo120140.PubMedGoogle Scholar
  67. 67.
    Zhang, H., Cohen, A. L., Krishnakumar, S., Wapnir, I. L., Veeriah, S., Deng, G., et al. (2014). Patient-derived xenografts of triple-negative breast cancer reproduce molecular features of patient tumors and respond to mTOR inhibition. Breast Cancer Research, 16(2), R36. doi: 10.1186/bcr3640.PubMedPubMedCentralCrossRefGoogle Scholar
  68. 68.
    Marangoni, E., Vincent-Salomon, A., Auger, N., Degeorges, A., Assayag, F., de Cremoux, P., et al. (2007). A new model of patient tumor-derived breast cancer xenografts for preclinical assays. Clinical Cancer Research, 13(13), 3989–3998. doi: 10.1158/1078-0432.CCR-07-0078.PubMedCrossRefGoogle Scholar
  69. 69.
    Kabos, P., Finlay-Schultz, J., Li, C., Kline, E., Finlayson, C., Wisell, J., et al. (2012). Patient-derived luminal breast cancer xenografts retain hormone receptor heterogeneity and help define unique estrogen-dependent gene signatures. Breast Cancer Research and Treatment, 135(2), 415–432. doi: 10.1007/s10549-012-2164-8.PubMedCrossRefGoogle Scholar
  70. 70.
    Al-Hajj, M., Wicha, M. S., Benito-Hernandez, A., Morrison, S. J., & Clarke, M. F. (2003). Prospective identification of tumorigenic breast cancer cells. Proceedings of the National Academy of Sciences of the United States of America, 100(7), 3983–3988. doi: 10.1073/pnas.0530291100.PubMedPubMedCentralCrossRefGoogle Scholar
  71. 71.
    DeRose, Y. S., Wang, G., Lin, Y. C., Bernard, P. S., Buys, S. S., Ebbert, M. T., et al. (2011). Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nature Medicine, 17(11), 1514–1520. doi: 10.1038/nm.2454.PubMedPubMedCentralCrossRefGoogle Scholar
  72. 72.
    DeRose, Y. S., Gligorich, K. M., Wang, G., Georgelas, A., Bowman, P., Courdy, S. J., et al. (2013). Patient-derived models of human breast cancer: protocols for in vitro and in vivo applications in tumor biology and translational medicine. Curr Protoc Pharmacol, Chapter 14(Unit14), 23. doi: 10.1002/0471141755.ph1423s60.PubMedGoogle Scholar
  73. 73.
    Li, S., Shen, D., Shao, J., Crowder, R., Liu, W., Prat, A., et al. (2013). Endocrine-therapy-resistant ESR1 variants revealed by genomic characterization of breast-cancer-derived xenografts. Cell Reports, 4(6), 1116–1130. doi: 10.1016/j.celrep.2013.08.022.PubMedCrossRefGoogle Scholar
  74. 74.
    Vaillant, F., Merino, D., Lee, L., Breslin, K., Pal, B., Ritchie, M. E., et al. (2013). Targeting BCL-2 with the BH3 mimetic ABT-199 in estrogen receptor-positive breast cancer. Cancer Cell, 24(1), 120–129. doi: 10.1016/j.ccr.2013.06.002.PubMedCrossRefGoogle Scholar
  75. 75.
    Kuperwasser, C., Chavarria, T., Wu, M., Magrane, G., Gray, J. W., Carey, L., et al. (2004). Reconstruction of functionally normal and malignant human breast tissues in mice. Proceedings of the National Academy of Sciences of the United States of America, 101(14), 4966–4971.PubMedPubMedCentralCrossRefGoogle Scholar
  76. 76.
    Lewis, M. T. (2012). Xenograft models of the normal and malignant human breast. In X. Wang (Ed.), Translational animal models in drug discovery and development (pp. 122–138). Sharjah: Bentham Science Publishers.Google Scholar
  77. 77.
    Whittle, J. R., Lewis, M. T., Lindeman, G. J., & Visvader, J. E. (2015). Patient-derived xenograft models of breast cancer and their predictive power. [Research support, N.I.H., extramural research support, non-U.S. Gov’t review]. Breast Cancer Research, 17, 17. doi: 10.1186/s13058-015-0523-1.PubMedPubMedCentralCrossRefGoogle Scholar
  78. 78.
    Lum, D. H., Matsen, C., Welm, A. L., & Welm, B. E. (2012). Overview of human primary tumorgraft models: comparisons with traditional oncology preclinical models and the clinical relevance and utility of primary tumorgrafts in basic and translational oncology research. [Research support, N.I.H., extramural research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S.]. Curr Protoc Pharmacol, Chapter 14(Unit 14), 22. doi: 10.1002/0471141755.ph1422s59.PubMedGoogle Scholar
  79. 79.
    Hidalgo, M., Amant, F., Biankin, A. V., Budinska, E., Byrne, A. T., Caldas, C., et al. (2014). Patient-derived xenograft models: an emerging platform for translational cancer research. [Review]. Cancer Discovery, 4(9), 998–1013. doi: 10.1158/2159-8290.CD-14-0001.PubMedPubMedCentralCrossRefGoogle Scholar
  80. 80.
    Neve, R. M., Chin, K., Fridlyand, J., Yeh, J., Baehner, F. L., Fevr, T., et al. (2006). A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell, 10(6), 515–527. doi: 10.1016/j.ccr.2006.10.008.PubMedPubMedCentralCrossRefGoogle Scholar
  81. 81.
    Hollestelle, A., Nagel, J. H., Smid, M., Lam, S., Elstrodt, F., Wasielewski, M., et al. (2009). Distinct gene mutation profiles among luminal-type and basal-type breast cancer cell lines. Breast Cancer Research and Treatment. doi: 10.1007/s10549-009-0460-8.Google Scholar
  82. 82.
    Chin, K., DeVries, S., Fridlyand, J., Spellman, P. T., Roydasgupta, R., Kuo, W. L., et al. (2006). Genomic and transcriptional aberrations linked to breast cancer pathophysiologies. Cancer Cell, 10(6), 529–541. doi: 10.1016/j.ccr.2006.10.009.PubMedCrossRefGoogle Scholar
  83. 83.
    Bonnefoi, H., Potti, A., Delorenzi, M., Mauriac, L., Campone, M., Tubiana-Hulin, M., et al. (2007). Validation of gene signatures that predict the response of breast cancer to neoadjuvant chemotherapy: a substudy of the EORTC 10994/BIG 00-01 clinical trial. The Lancet Oncology, 8(12), 1071–1078. doi: 10.1016/S1470-2045(07)70345-5.PubMedCrossRefGoogle Scholar
  84. 84.
    Potti, A., Dressman, H. K., Bild, A., Riedel, R. F., Chan, G., Sayer, R., et al. (2006). Genomic signatures to guide the use of chemotherapeutics. Nature Medicine, 12(11), 1294–1300. doi: 10.1038/nm1491.PubMedCrossRefGoogle Scholar
  85. 85.
    Salter, K. H., Acharya, C. R., Walters, K. S., Redman, R., Anguiano, A., Garman, K. S., et al. (2008). An integrated approach to the prediction of chemotherapeutic response in patients with breast cancer. PloS One, 3(4), e1908. doi: 10.1371/journal.pone.0001908.PubMedPubMedCentralCrossRefGoogle Scholar
  86. 86.
    Liedtke, C., Wang, J., Tordai, A., Symmans, W. F., Hortobagyi, G. N., Kiesel, L., et al. (2009). Clinical evaluation of chemotherapy response predictors developed from breast cancer cell lines. Breast Cancer Research and Treatment. doi: 10.1007/s10549-009-0445-7.PubMedGoogle Scholar
  87. 87.
    Wu, M., & Robinson, M. O. (2009). Human-in-mouse breast cancer model. Cell Cycle, 8(15), 2317–2318.PubMedCrossRefGoogle Scholar
  88. 88.
    Rottenberg, S., Pajic, M., & Jonkers, J. (2010). Studying drug resistance using genetically engineered mouse models for breast cancer. [Research support, non-U.S. Gov’t]. Methods in Molecular Biology, 596, 33–45. doi: 10.1007/978-1-60761-416-6_3.PubMedCrossRefGoogle Scholar
  89. 89.
    Cardiff, R. D. (2001). Validity of mouse mammary tumour models for human breast cancer: comparative pathology. Microscopy Research and Technique, 52(2), 224–230. doi: 10.1002/1097-0029(20010115)52:2<224::AID-JEMT1007>3.0.CO;2-A.PubMedCrossRefGoogle Scholar
  90. 90.
    Kim, J. B., O’Hare, M. J., & Stein, R. (2004). Models of breast cancer: is merging human and animal models the future? Breast Cancer Research, 6(1), 22–30. doi: 10.1186/bcr645 bcr645.PubMedCrossRefGoogle Scholar
  91. 91.
    Clarke, R. (1996). Human breast cancer cell line xenografts as models of breast cancer. The immunobiologies of recipient mice and the characteristics of several tumorigenic cell lines. Breast Cancer Research and Treatment, 39(1), 69–86.PubMedCrossRefGoogle Scholar
  92. 92.
    Kenny, P. A., Lee, G. Y., Myers, C. A., Neve, R. M., Semeiks, J. R., Spellman, P. T., et al. (2007). The morphologies of breast cancer cell lines in three-dimensional assays correlate with their profiles of gene expression. Molecular Oncology, 1(1), 84–96. doi: 10.1016/j.molonc.2007.02.004.PubMedPubMedCentralCrossRefGoogle Scholar
  93. 93.
    Weigelt, B., Lo, A. T., Park, C. C., Gray, J. W., & Bissell, M. J. (2009). HER2 signaling pathway activation and response of breast cancer cells to HER2-targeting agents is dependent strongly on the 3D microenvironment. Breast Cancer Research and Treatment. doi: 10.1007/s10549-009-0502-2.PubMedCentralGoogle Scholar
  94. 94.
    Gillet, J. P., Calcagno, A. M., Varma, S., Marino, M., Green, L. J., Vora, M. I., et al. (2011). Redefining the relevance of established cancer cell lines to the study of mechanisms of clinical anti-cancer drug resistance. Proceedings of the National Academy of Sciences of the United States of America, 108(46), 18708–18713. doi: 10.1073/pnas.1111840108.PubMedPubMedCentralCrossRefGoogle Scholar
  95. 95.
    Johnson, J. I., Decker, S., Zaharevitz, D., Rubinstein, L. V., Venditti, J. M., Schepartz, S., et al. (2001). Relationships between drug activity in NCI preclinical in vitro and in vivo models and early clinical trials. British Journal of Cancer, 84(10), 1424–1431. doi: 10.1054/bjoc.2001.1796.PubMedPubMedCentralCrossRefGoogle Scholar
  96. 96.
    Ellis, L. M., & Fidler, I. J. (2010). Finding the tumor copycat. Therapy fails, patients don’t. Nature Medicine, 16(9), 974–975. doi: 10.1038/nm0910-974.PubMedCrossRefGoogle Scholar
  97. 97.
    Hampton, O. A., Den Hollander, P., Miller, C. A., Delgado, D. A., Li, J., Coarfa, C., et al. (2009). A sequence-level map of chromosomal breakpoints in the MCF-7 breast cancer cell line yields insights into the evolution of a cancer genome. Genome Research, 19(2), 167–177. doi: 10.1101/gr.080259.108.PubMedPubMedCentralCrossRefGoogle Scholar
  98. 98.
    Nugoli, M., Chuchana, P., Vendrell, J., Orsetti, B., Ursule, L., Nguyen, C., et al. (2003). Genetic variability in MCF-7 sublines: evidence of rapid genomic and RNA expression profile modifications. BMC Cancer, 3, 13. doi: 10.1186/1471-2407-3-13.PubMedPubMedCentralCrossRefGoogle Scholar
  99. 99.
    du Manoir, S., Orsetti, B., Bras-Goncalves, R., Nguyen, T. T., Lasorsa, L., Boissiere, F., et al. (2014). Breast tumor PDXs are genetically plastic and correspond to a subset of aggressive cancers prone to relapse. Molecular Oncology, 8(2), 431–443. doi: 10.1016/j.molonc.2013.11.010.PubMedCrossRefGoogle Scholar
  100. 100.
    Prat, A., & Perou, C. M. (2011). Deconstructing the molecular portraits of breast cancer. Molecular Oncology, 5(1), 5–23. doi: 10.1016/j.molonc.2010.11.003.PubMedCrossRefGoogle Scholar
  101. 101.
    Petrillo, L. A., Wolf, D. M., Kapoun, A. M., Wang, N. J., Barczak, A., Xiao, Y., et al. (2012). Xenografts faithfully recapitulate breast cancer-specific gene expression patterns of parent primary breast tumors. Breast Cancer Research and Treatment, 135(3), 913–922. doi: 10.1007/s10549-012-2226-y.PubMedCrossRefGoogle Scholar
  102. 102.
    Giuliano, M., Herrera, S., Christiny, P., Shaw, C., Creighton, C. J., Mitchell, T., et al. (2015). Circulating and disseminated tumor cells from breast cancer patient-derived xenograft-bearing mice as a novel model to study metastasis. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. Breast Cancer Research, 17(3). doi: 10.1186/s13058-014-0508-5.
  103. 103.
    Powell, E., Shao, J., Yuan, Y., Chen, H. C., Cai, S., Echeverria, G. V., et al. (2016). p53 deficiency linked to B cell translocation gene 2 (BTG2) loss enhances metastatic potential by promoting tumor growth in primary and metastatic sites in patient-derived xenograft (PDX) models of triple-negative breast cancer. Breast Cancer Research, 18(1), 13. doi: 10.1186/s13058-016-0673-9.PubMedPubMedCentralCrossRefGoogle Scholar
  104. 104.
    Flanagan, S. P. (1966). ‘Nude’, a new hairless gene with pleiotropic effects in the mouse. Genetical Research, 8(3), 295–309.PubMedCrossRefGoogle Scholar
  105. 105.
    Kaushik, A., Kelsoe, G., & Jaton, J. C. (1995). The nude mutation results in impaired primary antibody repertoire. European Journal of Immunology, 25(2), 631–634. doi: 10.1002/eji.1830250249.PubMedCrossRefGoogle Scholar
  106. 106.
    Wortis, H. H., Nehlsen, S., & Owen, J. J. (1971). Abnormal development of the thymus in “nude” mice. The Journal of Experimental Medicine, 134(3 Pt 1), 681–692.PubMedPubMedCentralCrossRefGoogle Scholar
  107. 107.
    Kaestner, K. H., Knochel, W., & Martinez, D. E. (2000). Unified nomenclature for the winged helix/forkhead transcription factors. Genes & Development, 14(2), 142–146.Google Scholar
  108. 108.
    Nehls, M., Pfeifer, D., Schorpp, M., Hedrich, H., & Boehm, T. (1994). New member of the winged-helix protein family disrupted in mouse and rat nude mutations. Nature, 372(6501), 103–107. doi: 10.1038/372103a0.PubMedCrossRefGoogle Scholar
  109. 109.
    Osborne, C. K., Hobbs, K., & Clark, G. M. (1985). Effect of estrogens and antiestrogens on growth of human breast cancer cells in athymic nude mice. Cancer Research, 45(2), 584–590.PubMedGoogle Scholar
  110. 110.
    Seibert, K., Shafie, S. M., Triche, T. J., Whang-Peng, J. J., O’Brien, S. J., Toney, J. H., et al. (1983). Clonal variation of MCF-7 breast cancer cells in vitro and in athymic nude mice. Cancer Research, 43(5), 2223–2239.PubMedGoogle Scholar
  111. 111.
    Popnikolov, N. K., Yang, J., Guzman, R. C., Swanson, S. M., Thordarson, G., Collins, G., et al. (1995). In vivo growth stimulation of collagen gel embedded normal human and mouse primary mammary epithelial cells. Journal of Cellular Physiology, 163(1), 51–60. doi: 10.1002/jcp.1041630107.PubMedCrossRefGoogle Scholar
  112. 112.
    Soule, H. D., & McGrath, C. M. (1980). Estrogen responsive proliferation of clonal human breast carcinoma cells in athymic mice. Cancer Letters, 10(2), 177–189.PubMedCrossRefGoogle Scholar
  113. 113.
    McAuliffe, P. F., Evans, K. W., Akcakanat, A., Chen, K., Zheng, X., Zhao, H., et al. (2016). Correction: ability to generate patient-derived breast cancer xenografts is enhanced in chemoresistant disease and predicts poor patient outcomes. [published erratum]. PloS One, 11(3), e0151121. doi: 10.1371/journal.pone.0151121.PubMedPubMedCentralCrossRefGoogle Scholar
  114. 114.
    McAuliffe, P. F., Evans, K. W., Akcakanat, A., Chen, K., Zheng, X., Zhao, H., et al. (2015). Ability to generate patient-derived breast cancer xenografts is enhanced in chemoresistant disease and predicts poor patient outcomes. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. PloS One, 10(9), e0136851. doi: 10.1371/journal.pone.0136851.PubMedPubMedCentralCrossRefGoogle Scholar
  115. 115.
    Mombaerts, P., Iacomini, J., Johnson, R. S., Herrup, K., Tonegawa, S., & Papaioannou, V. E. (1992). RAG-1-deficient mice have no mature B and T lymphocytes. Cell, 68(5), 869–877.PubMedCrossRefGoogle Scholar
  116. 116.
    Wunderlich, M., Mizukawa, B., Chou, F. S., Sexton, C., Shrestha, M., Saunthararajah, Y., et al. (2013). AML cells are differentially sensitive to chemotherapy treatment in a human xenograft model. [Research support, N.I.H., extramural research support, U.S. Gov’t, non-P.H.S.]. Blood, 121(12), e90–e97. doi: 10.1182/blood-2012-10-464677.PubMedPubMedCentralCrossRefGoogle Scholar
  117. 117.
    Bosma, G. C., Fried, M., Custer, R. P., Carroll, A., Gibson, D. M., & Bosma, M. J. (1988). Evidence of functional lymphocytes in some (leaky) scid mice. The Journal of Experimental Medicine, 167(3), 1016–1033.PubMedCrossRefGoogle Scholar
  118. 118.
    Bosma, G. C., Custer, R. P., & Bosma, M. J. (1983). A severe combined immunodeficiency mutation in the mouse. Nature, 301(5900), 527–530.PubMedCrossRefGoogle Scholar
  119. 119.
    Blunt, T., Finnie, N. J., Taccioli, G. E., Smith, G. C., Demengeot, J., Gottlieb, T. M., et al. (1995). Defective DNA-dependent protein kinase activity is linked to V(D)J recombination and DNA repair defects associated with the murine scid mutation. Cell, 80(5), 813–823.PubMedCrossRefGoogle Scholar
  120. 120.
    Nonoyama, S., Smith, F. O., Bernstein, I. D., & Ochs, H. D. (1993). Strain-dependent leakiness of mice with severe combined immune deficiency. Journal of Immunology, 150(9), 3817–3824.Google Scholar
  121. 121.
    Custer, R. P., Bosma, G. C., & Bosma, M. J. (1985). Severe combined immunodeficiency (SCID) in the mouse. Pathology, reconstitution, neoplasms. [Research support, non-U.S. Gov’t research support, U.S. Gov’t, P.H.S.]. The American Journal of Pathology, 120(3), 464–477.PubMedPubMedCentralGoogle Scholar
  122. 122.
    Christianson, S. W., Greiner, D. L., Schweitzer, I. B., Gott, B., Beamer, G. L., Schweitzer, P. A., et al. (1996). Role of natural killer cells on engraftment of human lymphoid cells and on metastasis of human T-lymphoblastoid leukemia cells in C57BL/6J-scid mice and in C57BL/6J-scid bg mice. Cellular Immunology, 171(2), 186–199. doi: 10.1006/cimm.1996.0193.PubMedCrossRefGoogle Scholar
  123. 123.
    Greiner, D. L., Shultz, L. D., Yates, J., Appel, M. C., Perdrizet, G., Hesselton, R. M., et al. (1995). Improved engraftment of human spleen cells in NOD/LtSz-scid/scid mice as compared with C.B-17-scid/scid mice. The American Journal of Pathology, 146(4), 888–902.PubMedPubMedCentralGoogle Scholar
  124. 124.
    Hudson, W. A., Li, Q., Le, C., & Kersey, J. H. (1998). Xenotransplantation of human lymphoid malignancies is optimized in mice with multiple immunologic defects. Leukemia, 12(12), 2029–2033.PubMedCrossRefGoogle Scholar
  125. 125.
    Dewan, M. Z., Terunuma, H., Ahmed, S., Ohba, K., Takada, M., Tanaka, Y., et al. (2005). Natural killer cells in breast cancer cell growth and metastasis in SCID mice. Biomedicine & Pharmacotherapy, 59(Suppl 2), S375–S379.CrossRefGoogle Scholar
  126. 126.
    Roder, J., & Duwe, A. (1979). The beige mutation in the mouse selectively impairs natural killer cell function. Nature, 278(5703), 451–453.PubMedCrossRefGoogle Scholar
  127. 127.
    Xia, Z., Taylor, P. R., Locklin, R. M., Gordon, S., Cui, Z., & Triffitt, J. T. (2006). Innate immune response to human bone marrow fibroblastic cell implantation in CB17 scid/beige mice. Journal of Cellular Biochemistry, 98(4), 966–980.PubMedCrossRefGoogle Scholar
  128. 128.
    Gouon-Evans, V., Lin, E. Y., & Pollard, J. W. (2002). Requirement of macrophages and eosinophils and their cytokines/chemokines for mammary gland development. Breast Cancer Research, 4(4), 155–164.PubMedPubMedCentralCrossRefGoogle Scholar
  129. 129.
    Gouon-Evans, V., Rothenberg, M. E., & Pollard, J. W. (2000). Postnatal mammary gland development requires macrophages and eosinophils. Development, 127(11), 2269–2282.PubMedGoogle Scholar
  130. 130.
    Yang, L., Huang, J., Ren, X., Gorska, A. E., Chytil, A., Aakre, M., et al. (2008). Abrogation of TGF beta signaling in mammary carcinomas recruits Gr-1+CD11b+ myeloid cells that promote metastasis. Cancer Cell, 13(1), 23–35. doi: 10.1016/j.ccr.2007.12.004.PubMedPubMedCentralCrossRefGoogle Scholar
  131. 131.
    Iyer, V., Klebba, I., McCready, J., Arendt, L. M., Betancur-Boissel, M., Wu, M. F., et al. (2012). Estrogen promotes ER-negative tumor growth and angiogenesis through mobilization of bone marrow-derived monocytes. Cancer Research, 72(11), 2705–2713. doi: 10.1158/0008-5472.CAN-11-3287.PubMedCrossRefGoogle Scholar
  132. 132.
    Shultz, L. D., Schweitzer, P. A., Christianson, S. W., Gott, B., Schweitzer, I. B., Tennent, B., et al. (1995). Multiple defects in innate and adaptive immunologic function in NOD/LtSz-scid mice. Journal of Immunology, 154(1), 180–191.Google Scholar
  133. 133.
    Pflumio, F., Izac, B., Katz, A., Shultz, L. D., Vainchenker, W., & Coulombel, L. (1996). Phenotype and function of human hematopoietic cells engrafting immune-deficient CB17-severe combined immunodeficiency mice and nonobese diabetic-severe combined immunodeficiency mice after transplantation of human cord blood mononuclear cells. Blood, 88(10), 3731–3740.PubMedGoogle Scholar
  134. 134.
    Cashman, J. D., Lapidot, T., Wang, J. C., Doedens, M., Shultz, L. D., Lansdorp, P., et al. (1997). Kinetic evidence of the regeneration of multilineage hematopoiesis from primitive cells in normal human bone marrow transplanted into immunodeficient mice. Blood, 89(12), 4307–4316.PubMedGoogle Scholar
  135. 135.
    Sikora, M. J., Cooper, K. L., Bahreini, A., Luthra, S., Wang, G., Chandran, U. R., et al. (2014). Invasive lobular carcinoma cell lines are characterized by unique estrogen-mediated gene expression patterns and altered tamoxifen response. [Research support, N.I.H., extramural research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S.]. Cancer Research, 74(5), 1463–1474. doi: 10.1158/0008-5472.CAN-13-2779.PubMedPubMedCentralCrossRefGoogle Scholar
  136. 136.
    Eyre, R., Alferez, D. G., & Clarke, R. B. (2016). Journal of Mammary Gland Biology and Neoplasia, (in press).Google Scholar
  137. 137.
    Shultz, L. D., Lyons, B. L., Burzenski, L. M., Gott, B., Chen, X., Chaleff, S., et al. (2005). Human lymphoid and myeloid cell development in NOD/LtSz-scid IL2R gamma null mice engrafted with mobilized human hemopoietic stem cells. Journal of Immunology, 174(10), 6477–6489.CrossRefGoogle Scholar
  138. 138.
    Ito, M., Hiramatsu, H., Kobayashi, K., Suzue, K., Kawahata, M., Hioki, K., et al. (2002). NOD/SCID/gamma(c)(null) mouse: an excellent recipient mouse model for engraftment of human cells. Blood, 100(9), 3175–3182. doi: 10.1182/blood-2001-12-0207.PubMedCrossRefGoogle Scholar
  139. 139.
    Oakes, S. R., Vaillant, F., Lim, E., Lee, L., Breslin, K., Feleppa, F., et al. (2012). Sensitization of BCL-2-expressing breast tumors to chemotherapy by the BH3 mimetic ABT-737. [Research support, non-U.S. Gov’t]. Proceedings of the National Academy of Sciences of the United States of America, 109(8), 2766–2771. doi: 10.1073/pnas.1104778108.PubMedCrossRefGoogle Scholar
  140. 140.
    Nolan, E., Vaillant, F., Branstetter, D., Pal, B., Giner, G., Whitehead, L., et al. (2016). RANK ligand as a potential target for breast cancer prevention in BRCA1-mutation carriers. Nature Medicine, 22(8), 933–939. doi: 10.1038/nm.4118.PubMedCrossRefGoogle Scholar
  141. 141.
    Richard, E., Grellety, T., Velasco, V., MacGrogan, G., Bonnefoi, H., & Iggo, R. (2016). The mammary ducts create a favourable microenvironment for xenografting of luminal and molecular apocrine breast tumours. The Journal of Pathology. doi: 10.1002/path.4772.PubMedGoogle Scholar
  142. 142.
    McDermott, S. P., Eppert, K., Lechman, E. R., Doedens, M., & Dick, J. E. (2010). Comparison of human cord blood engraftment between immunocompromised mouse strains. [Comparative study research support, non-U.S. Gov’t]. Blood, 116(2), 193–200. doi: 10.1182/blood-2010-02-271841.PubMedCrossRefGoogle Scholar
  143. 143.
    Bondarenko, G., Ugolkov, A., Rohan, S., Kulesza, P., Dubrovskyi, O., Gursel, D., et al. (2015). Patient-derived tumor xenografts are susceptible to formation of human lymphocytic tumors. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. Neoplasia, 17(9), 735–741. doi: 10.1016/j.neo.2015.09.004.PubMedPubMedCentralCrossRefGoogle Scholar
  144. 144.
    Wetterauer, C., Vlajnic, T., Schuler, J., Gsponer, J. R., Thalmann, G. N., Cecchini, M., et al. (2015). Early development of human lymphomas in a prostate cancer xenograft program using triple knock-out immunocompromised mice. [Research support, non-U.S. Gov’t]. The Prostate, 75(6), 585–592. doi: 10.1002/pros.22939.PubMedCrossRefGoogle Scholar
  145. 145.
    Moon, H. G., Oh, K., Lee, J., Lee, M., Kim, J. Y., Yoo, T. K., et al. (2015). Prognostic and functional importance of the engraftment-associated genes in the patient-derived xenograft models of triple-negative breast cancers. [Research support, non-U.S. Gov’t]. Breast Cancer Research and Treatment, 154(1), 13–22. doi: 10.1007/s10549-015-3585-y.PubMedCrossRefGoogle Scholar
  146. 146.
    Gullino, P. M. (1977). Considerations on the preneoplastic lesions of the mammary gland. The American Journal of Pathology, 89(2), 413–430.PubMedPubMedCentralGoogle Scholar
  147. 147.
    Brem, S. S., Jensen, H. M., & Gullino, P. M. (1978). Angiogenesis as a marker of preneoplastic lesions of the human breast. Cancer, 41, 239–244.PubMedCrossRefGoogle Scholar
  148. 148.
    Bogden, A. E., Haskell, P. M., LePage, D. J., Kelton, D. E., Cobb, W. R., & Esber, H. J. (1979). Growth of human tumor xenografts implanted under the renal capsule of normal immunocompetent mice. Experimental Cell Biology, 47(4), 281–293.PubMedGoogle Scholar
  149. 149.
    Bogden, A. E., Kelton, D. E., Cobb, W. B., & Esber, H. J.. 1978. A rapid screening method for testing chemotherapeutic agents against human tumor xenografts. In Houchens, & Ovejera (Eds.), Symposium on the use of athymic (nude) mice in cancer research, (pp. 231). New York.Google Scholar
  150. 150.
    Aamdal, S., Fodstad, O., Nesland, J. M., & Pihl, A. (1985). Characteristics of human tumour xenografts transplanted under the renal capsule of immunocompetent mice. British Journal of Cancer, 51(3), 347–356.PubMedPubMedCentralCrossRefGoogle Scholar
  151. 151.
    Eirew, P., Stingl, J., Raouf, A., Turashvili, G., Aparicio, S., Emerman, J. T., et al. (2008). A method for quantifying normal human mammary epithelial stem cells with in vivo regenerative ability. Nature Medicine, 14(12), 1384–1389. doi: 10.1038/nm.1791.PubMedCrossRefGoogle Scholar
  152. 152.
    DeOme, K. B., Faulkin, L. J. J., & Bern, H. (1958). Development of mammary tumors from hyperplastic alveolar nodules transplanted into gland-free mammary fat pads of female C3H mice. Cancer Research, 19, 515–520.Google Scholar
  153. 153.
    Behbod, F., Kittrell, F. S., LaMarca, H., Edwards, D., Kerbawy, S., Heestand, J. C., et al. (2009). An intraductal human-in-mouse transplantation model mimics the subtypes of ductal carcinoma in situ. Breast Cancer Research, 11(5), R66. doi: 10.1186/bcr2358.PubMedPubMedCentralCrossRefGoogle Scholar
  154. 154.
    Sflomos, G., Dormoy, V., Metsalu, T., Jeitziner, R., Battista, L., Scabia, V., et al. (2016). A preclinical model for ERalpha-positive breast cancer points to the epithelial microenvironment as determinant of luminal phenotype and hormone response. [Research support, non-U.S. Gov’t]. Cancer Cell, 29(3), 407–422. doi: 10.1016/j.ccell.2016.02.002.PubMedCrossRefGoogle Scholar
  155. 155.
    Kang, Y., Siegel, P. M., Shu, W., Drobnjak, M., Kakonen, S. M., Cordon-Cardo, C., et al. (2003). A multigenic program mediating breast cancer metastasis to bone. Cancer Cell, 3(6), 537–549.PubMedCrossRefGoogle Scholar
  156. 156.
    Palmieri, D., Smith, Q. R., Lockman, P. R., Bronder, J., Gril, B., Chambers, A. F., et al. (2006). Brain metastases of breast cancer. Breast Disease, 26, 139–147.PubMedCrossRefGoogle Scholar
  157. 157.
    Bos, P. D., Zhang, X. H., Nadal, C., Shu, W., Gomis, R. R., Nguyen, D. X., et al. (2009). Genes that mediate breast cancer metastasis to the brain. Nature, 459(7249), 1005–1009. doi: 10.1038/nature08021.PubMedPubMedCentralCrossRefGoogle Scholar
  158. 158.
    Minn, A. J., Gupta, G. P., Siegel, P. M., Bos, P. D., Shu, W., Giri, D. D., et al. (2005). Genes that mediate breast cancer metastasis to lung. Nature, 436(7050), 518–524. doi: 10.1038/nature03799.PubMedPubMedCentralCrossRefGoogle Scholar
  159. 159.
    Murphy, P., Alexander, P., Senior, P. V., Fleming, J., Kirkham, N., & Taylor, I. (1988). Mechanisms of organ selective tumour growth by bloodborne cancer cells. British Journal of Cancer, 57(1), 19–31.PubMedPubMedCentralCrossRefGoogle Scholar
  160. 160.
    Yi, B., Williams, P. J., Niewolna, M., Wang, Y., & Yoneda, T. (2002). Tumor-derived platelet-derived growth factor-BB plays a critical role in osteosclerotic bone metastasis in an animal model of human breast cancer. Cancer Research, 62(3), 917–923.PubMedGoogle Scholar
  161. 161.
    Lam, P., Yang, W., Amemiya, Y., Kahn, H., Yee, A., Holloway, C., et al. (2009). A human bone NOD/SCID mouse model to distinguish metastatic potential in primary breast cancers. Cancer Biology & Therapy, 8(11), 1010–1017.CrossRefGoogle Scholar
  162. 162.
    Faulkin Jr., L. J., & Deome, K. B. (1960). Regulation of growth and spacing of gland elements in the mammary fat pad of the C3H mouse. Journal of the National Cancer Institute, 24, 953–969.PubMedGoogle Scholar
  163. 163.
    Deome, K. B., Faulkin Jr., L. J., Bern, H. A., & Blair, P. B. (1959). Development of mammary tumors from hyperplastic alveolar nodules transplanted into gland-free mammary fat pads of female C3H mice. Cancer Research, 19(5), 515–520.PubMedGoogle Scholar
  164. 164.
    Bailey, M. J., Gazet, J. C., & Peckham, M. J. (1980). Human breast-cancer xenografts in immune-suppressed mice. British Journal of Cancer, 42(4), 524–529.PubMedPubMedCentralCrossRefGoogle Scholar
  165. 165.
    Levin-Allerhand, J. A., Sokol, K., & Smith, J. D. (2003). Safe and effective method for chronic 17beta-estradiol administration to mice. [Comparative StudyResearch support, non-U.S. Gov’t]. (2016). Contemporary topics in laboratory animal science / American Association for Laboratory Animal Science, 42(6), 33–35.Google Scholar
  166. 166.
    Welsch, C. W., Swim, E. L., McManus, M. J., White, A. C., & McGrath, C. M. (1981). Estrogen induced growth of human breast cancer cells (MCF-7) in athymic nude mice is enhanced by secretions from a transplantable pituitary tumor. [Research support, non-U.S. Gov’tResearch support, U.S. Gov’t, P.H.S.]. Cancer Letters, 14(3), 309–316.PubMedCrossRefGoogle Scholar
  167. 167.
    Cottu, P., Marangoni, E., Assayag, F., de Cremoux, P., Vincent-Salomon, A., Guyader, C., et al. (2012). Modeling of response to endocrine therapy in a panel of human luminal breast cancer xenografts. [Research support, non-U.S. Gov’t]. Breast Cancer Research and Treatment, 133(2), 595–606. doi: 10.1007/s10549-011-1815-5.PubMedCrossRefGoogle Scholar
  168. 168.
    Hatem, R., El Botty, R., Chateau-Joubert, S., Servely, J. L., Labiod, D., de Plater, L., et al. (2016). Targeting mTOR pathway inhibits tumor growth in different molecular subtypes of triple-negative breast cancers. Oncotarget. doi: 10.18632/oncotarget.10195.PubMedGoogle Scholar
  169. 169.
    Gupta, P. B., & Kuperwasser, C. (2006). Contributions of estrogen to ER-negative breast tumor growth. The Journal of Steroid Biochemistry and Molecular Biology, 102(1–5), 71–78. doi: 10.1016/j.jsbmb.2006.09.025.PubMedCrossRefGoogle Scholar
  170. 170.
    Gupta, P. B., Proia, D., Cingoz, O., Weremowicz, J., Naber, S. P., Weinberg, R. A., et al. (2007). Systemic stromal effects of estrogen promote the growth of estrogen receptor-negative cancers. Cancer Research, 67(5), 2062–2071. doi: 10.1158/0008-5472.CAN-06-3895.PubMedCrossRefGoogle Scholar
  171. 171.
    Pequeux, C., Raymond-Letron, I., Blacher, S., Boudou, F., Adlanmerini, M., Fouque, M. J., et al. (2012). Stromal estrogen receptor-alpha promotes tumor growth by normalizing an increased angiogenesis. [Research support, non-U.S. Gov’t]. Cancer Research, 72(12), 3010–3019. doi: 10.1158/0008-5472.CAN-11-3768.PubMedCrossRefGoogle Scholar
  172. 172.
    Pece, S., Tosoni, D., Confalonieri, S., Mazzarol, G., Vecchi, M., Ronzoni, S., et al. (2010). Biological and molecular heterogeneity of breast cancers correlates with their cancer stem cell content. [Research support, non-U.S. Gov’t]. Cell, 140(1), 62–73. doi: 10.1016/j.cell.2009.12.007.PubMedCrossRefGoogle Scholar
  173. 173.
    Charafe-Jauffret, E., Ginestier, C., Bertucci, F., Cabaud, O., Wicinski, J., Finetti, P., et al. (2013). ALDH1-positive cancer stem cells predict engraftment of primary breast tumors and are governed by a common stem cell program. [Research support, non-U.S. Gov’t]. Cancer Research, 73(24), 7290–7300. doi: 10.1158/0008-5472.CAN-12-4704.PubMedCrossRefGoogle Scholar
  174. 174.
    Rong, S., Oskarsson, M., Faletto, D., Tsarfaty, I., Resau, J. H., Nakamura, T., et al. (1993). Tumorigenesis induced by coexpression of human hepatocyte growth factor and the human met protooncogene leads to high levels of expression of the ligand and receptor. Cell Growth & Differentiation, 4(7), 563–569.Google Scholar
  175. 175.
    Utama, F. E., LeBaron, M. J., Neilson, L. M., Sultan, A. S., Parlow, A. F., Wagner, K. U., et al. (2006). Human prolactin receptors are insensitive to mouse prolactin: implications for xenotransplant modeling of human breast cancer in mice. The Journal of Endocrinology, 188(3), 589–601. doi: 10.1677/joe.1.06560.PubMedCrossRefGoogle Scholar
  176. 176.
    Rong, S., Bodescot, M., Blair, D., Dunn, J., Nakamura, T., Mizuno, K., et al. (1992). Tumorigenicity of the met proto-oncogene and the gene for hepatocyte growth factor. Molecular and Cellular Biology, 12(11), 5152–5158.PubMedPubMedCentralCrossRefGoogle Scholar
  177. 177.
    Kaur, H., Mao, S., Shah, S., Gorski, D. H., Krawetz, S. A., Sloane, B. F., et al. (2013). Next-generation sequencing: a powerful tool for the discovery of molecular markers in breast ductal carcinoma in situ. Expert Review of Molecular Diagnostics, 13(2), 151–165. doi: 10.1586/erm.13.4.PubMedPubMedCentralCrossRefGoogle Scholar
  178. 178.
    Miller, F. R. (2000). Xenograft models of premalignant breast disease. Journal of Mammary Gland Biology and Neoplasia, 5(4), 379–391.PubMedCrossRefGoogle Scholar
  179. 179.
    Holland, P. A., Knox, W. F., Potten, C. S., Howell, A., Anderson, E., Baildam, A. D., et al. (1997). Assessment of hormone dependence of comedo ductal carcinoma in situ of the breast. Journal of the National Cancer Institute, 89(14), 1059–1065.PubMedCrossRefGoogle Scholar
  180. 180.
    Warnberg, F., White, D., Anderson, E., Knox, F., Clarke, R. B., Morris, J., et al. (2006). Effect of a farnesyl transferase inhibitor (R115777) on ductal carcinoma in situ of the breast in a human xenograft model and on breast and ovarian cancer cell growth in vitro and in vivo. Breast Cancer Research, 8(2), R21. doi: 10.1186/bcr1395.PubMedPubMedCentralCrossRefGoogle Scholar
  181. 181.
    Miller, F. R., Soule, H. D., Tait, L., Pauley, R. J., Wolman, S. R., Dawson, P. J., et al. (1993). Xenograft model of progressive human proliferative breast disease. Journal of the National Cancer Institute, 85(21), 1725–1732.PubMedCrossRefGoogle Scholar
  182. 182.
    Dawson, P. J., Wolman, S. R., Tait, L., Heppner, G. H., & Miller, F. R. (1996). MCF10AT: a model for the evolution of cancer from proliferative breast disease. The American Journal of Pathology, 148(1), 313–319.PubMedPubMedCentralGoogle Scholar
  183. 183.
    Hu, M., Yao, J., Carroll, D. K., Weremowicz, S., Chen, H., Carrasco, D., et al. (2008). Regulation of in situ to invasive breast carcinoma transition. Cancer Cell, 13(5), 394–406. doi: 10.1016/j.ccr.2008.03.007.PubMedPubMedCentralCrossRefGoogle Scholar
  184. 184.
    Forozan, F., Veldman, R., Ammerman, C. A., Parsa, N. Z., Kallioniemi, A., Kallioniemi, O. P., et al. (1999). Molecular cytogenetic analysis of 11 new breast cancer cell lines. British Journal of Cancer, 81(8), 1328–1334. doi: 10.1038/sj.bjc.6695007.PubMedPubMedCentralCrossRefGoogle Scholar
  185. 185.
    Gupta, P. B., & Kuperwasser, C. (2004). Disease models of breast cancer. [Review]. Drug Discovery Today: Disease Models, 1(1), 9–16.Google Scholar
  186. 186.
    Proia, D. A., & Kuperwasser, C. (2006). Reconstruction of human mammary tissues in a mouse model. Nature Protocols, 1(1), 206–214. doi: 10.1038/nprot.2006.31.PubMedCrossRefGoogle Scholar
  187. 187.
    Klopp, A. H., Gupta, A., Spaeth, E., Andreeff, M., & Marini 3rd, F. (2011). Concise review: dissecting a discrepancy in the literature: do mesenchymal stem cells support or suppress tumor growth? [Research support, N.I.H., extramural research support, non-U.S. Gov’tReview]. Stem Cells, 29(1), 11–19. doi: 10.1002/stem.559.PubMedCrossRefGoogle Scholar
  188. 188.
    Klopp, A. H., Lacerda, L., Gupta, A., Debeb, B. G., Solley, T., Li, L., et al. (2010). Mesenchymal stem cells promote mammosphere formation and decrease E-cadherin in normal and malignant breast cells. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. PloS One, 5(8), e12180. doi: 10.1371/journal.pone.0012180.PubMedPubMedCentralCrossRefGoogle Scholar
  189. 189.
    Karnoub, A. E., Dash, A. B., Vo, A. P., Sullivan, A., Brooks, M. W., Bell, G. W., et al. (2007). Mesenchymal stem cells within tumour stroma promote breast cancer metastasis. Nature, 449(7162), 557–563. doi: 10.1038/nature06188.PubMedCrossRefGoogle Scholar
  190. 190.
    Liu, S., Ginestier, C., Ou, S. J., Clouthier, S. G., Patel, S. H., Monville, F., et al. (2011). Breast cancer stem cells are regulated by mesenchymal stem cells through cytokine networks. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. Cancer Research, 71(2), 614–624. doi: 10.1158/0008-5472.CAN-10-0538.PubMedPubMedCentralCrossRefGoogle Scholar
  191. 191.
    Smyth, M. J., Dunn, G. P., & Schreiber, R. D. (2006). Cancer immunosurveillance and immunoediting: the roles of immunity in suppressing tumor development and shaping tumor immunogenicity. [Research support, N.I.H., extramural research support, non-U.S. Gov’t review]. Advances in Immunology, 90, 1–50. doi: 10.1016/S0065-2776(06)90001-7.PubMedCrossRefGoogle Scholar
  192. 192.
    Condeelis, J., & Pollard, J. W. (2006). Macrophages: obligate partners for tumor cell migration, invasion, and metastasis. [Research support, N.I.H., extramural research support, non-U.S. Gov’t review]. Cell, 124(2), 263–266. doi: 10.1016/j.cell.2006.01.007.PubMedCrossRefGoogle Scholar
  193. 193.
    DeNardo, D. G., Andreu, P., & Coussens, L. M. (2010). Interactions between lymphocytes and myeloid cells regulate pro- versus anti-tumor immunity. [Research support, N.I.H., extramural research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S. Review]. Cancer Metastasis Reviews, 29(2), 309–316. doi: 10.1007/s10555-010-9223-6.PubMedPubMedCentralCrossRefGoogle Scholar
  194. 194.
    Mantovani, A., & Sica, A. (2010). Macrophages, innate immunity and cancer: balance, tolerance, and diversity. [Review]. Current Opinion in Immunology, 22(2), 231–237. doi: 10.1016/j.coi.2010.01.009.PubMedCrossRefGoogle Scholar
  195. 195.
    Wyckoff, J. B., Wang, Y., Lin, E. Y., Li, J. F., Goswami, S., Stanley, E. R., et al. (2007). Direct visualization of macrophage-assisted tumor cell intravasation in mammary tumors. [Research support, N.I.H., extramural]. Cancer Research, 67(6), 2649–2656. doi: 10.1158/0008-5472.CAN-06-1823.PubMedCrossRefGoogle Scholar
  196. 196.
    Mantovani, A., Sica, A., Allavena, P., Garlanda, C., & Locati, M. (2009). Tumor-associated macrophages and the related myeloid-derived suppressor cells as a paradigm of the diversity of macrophage activation. [Research support, non-U.S. Gov’t review]. Human Immunology, 70(5), 325–330, doi:  10.1016/j.humimm.2009.02.008.
  197. 197.
    Knutson, K. L., Disis, M. L., & Salazar, L. G. (2007). CD4 regulatory T cells in human cancer pathogenesis. [Research support, N.I.H., extramural review]. Cancer Immunology, Immunotherapy, 56(3), 271–285. doi: 10.1007/s00262-006-0194-y.PubMedCrossRefGoogle Scholar
  198. 198.
    Hughes, P. E., Caenepeel, S., & Wu, L. C. (2016). Targeted therapy and checkpoint immunotherapy combinations for the treatment of cancer. [Review]. Trends in Immunology, 37(7), 462–476. doi: 10.1016/j.it.2016.04.010.PubMedCrossRefGoogle Scholar
  199. 199.
    Postow, M. A., Callahan, M. K., & Wolchok, J. D. (2015). Immune checkpoint blockade in cancer therapy. [Review]. Journal of Clinical Oncology, 33(17), 1974–1982. doi: 10.1200/JCO.2014.59.4358.PubMedPubMedCentralCrossRefGoogle Scholar
  200. 200.
    Rakhra, K., Bachireddy, P., Zabuawala, T., Zeiser, R., Xu, L., Kopelman, A., et al. (2010). CD4(+) T cells contribute to the remodeling of the microenvironment required for sustained tumor regression upon oncogene inactivation. [Comment research support, N.I.H., extramural research support, non-U.S. Gov’t]. Cancer Cell, 18(5), 485–498. doi: 10.1016/j.ccr.2010.10.002.PubMedPubMedCentralCrossRefGoogle Scholar
  201. 201.
    Mosier, D. E., Gulizia, R. J., Baird, S. M., & Wilson, D. B. (1988). Transfer of a functional human immune system to mice with severe combined immunodeficiency. Nature, 335(6187), 256–259. doi: 10.1038/335256a0.PubMedCrossRefGoogle Scholar
  202. 202.
    Wege, A. K., Ernst, W., Eckl, J., Frankenberger, B., Vollmann-Zwerenz, A., Mannel, D. N., et al. (2011). Humanized tumor mice--a new model to study and manipulate the immune response in advanced cancer therapy. [Research support, non-U.S. Gov’t]. International Journal of Cancer, 129(9), 2194–2206. doi: 10.1002/ijc.26159.PubMedCrossRefGoogle Scholar
  203. 203.
    Sanmamed, M. F., Chester, C., Melero, I., & Kohrt, H. (2016). Defining the optimal murine models to investigate immune checkpoint blockers and their combination with other immunotherapies. [Review]. Annals of Oncology, 27(7), 1190–1198. doi: 10.1093/annonc/mdw041.PubMedCrossRefGoogle Scholar
  204. 204.
    Holzapfel, B. M., Wagner, F., Thibaudeau, L., Levesque, J. P., & Hutmacher, D. W. (2015). Concise review: humanized models of tumor immunology in the twenty-first century: convergence of cancer research and tissue engineering. [Review]. Stem Cells, 33(6), 1696–1704. doi: 10.1002/stem.1978.PubMedCrossRefGoogle Scholar
  205. 205.
    Zhou, Q., Facciponte, J., Jin, M., Shen, Q., & Lin, Q. (2014). Humanized NOD-SCID IL2rg−/− mice as a preclinical model for cancer research and its potential use for individualized cancer therapies. [Review]. Cancer Letters, 344(1), 13–19. doi: 10.1016/j.canlet.2013.10.015.PubMedCrossRefGoogle Scholar
  206. 206.
    Brehm, M. A., Shultz, L. D., Luban, J., & Greiner, D. L. (2013). Overcoming current limitations in humanized mouse research. [Research support, N.I.H., extramural research support, non-U.S. Gov’t review]. The Journal of Infectious Diseases, 208(Suppl 2), S125–S130. doi: 10.1093/infdis/jit319.PubMedPubMedCentralCrossRefGoogle Scholar
  207. 207.
    Vargo-Gogola, T. (2010). Putting the brakes on breast cancer: therapeutic opportunities to bring cancer stem cells and the tumor microenvironment to a screeching halt. [Editorial introductory]. Current Drug Targets, 11(9), 1041–1042.PubMedCrossRefGoogle Scholar
  208. 208.
    Shumway, N. M., Ibrahim, N., Ponniah, S., Peoples, G. E., & Murray, J. L. (2009). Therapeutic breast cancer vaccines: a new strategy for early-stage disease. [Review]. BioDrugs, 23(5), 277–287. doi: 10.2165/11313490-000000000-00000.PubMedCrossRefGoogle Scholar
  209. 209.
    DeNardo, D. G., Brennan, D. J., Rexhepaj, E., Ruffell, B., Shiao, S. L., Madden, S. F., et al. (2011). Leukocyte complexity predicts breast cancer survival and functionally regulates response to chemotherapy. [Research support, N.I.H., extramural research support, non-U.S. Gov’t research support, U.S. Gov’t, non-P.H.S.]. Cancer Discovery, 1(1), 54–67. doi: 10.1158/2159-8274.CD-10-0028.PubMedPubMedCentralCrossRefGoogle Scholar
  210. 210.
    Bedognetti, D., Maccalli, C., Bader, S. B., Marincola, F. M., & Seliger, B. (2016). Checkpoint inhibitors and their application in breast cancer. [Review]. Breast Care (Basel), 11(2), 108–115. doi: 10.1159/000445335.CrossRefGoogle Scholar
  211. 211.
    Garcia, S., & Freitas, A. A. (2012). Humanized mice: current states and perspectives. [Review]. Immunology Letters, 146(1–2), 1–7. doi: 10.1016/j.imlet.2012.03.009.PubMedCrossRefGoogle Scholar
  212. 212.
    Rongvaux, A., Willinger, T., Martinek, J., Strowig, T., Gearty, S. V., Teichmann, L. L., et al. (2014). Development and function of human innate immune cells in a humanized mouse model. [Research support, N.I.H., extramural research support, non-U.S. Gov’t]. Nature Biotechnology, 32(4), 364–372. doi: 10.1038/nbt.2858.PubMedPubMedCentralCrossRefGoogle Scholar
  213. 213.
    Bertotti, A., Migliardi, G., Galimi, F., Sassi, F., Torti, D., Isella, C., et al. (2011). A molecularly annotated platform of patient-derived xenografts (“xenopatients”) identifies HER2 as an effective therapeutic target in cetuximab-resistant colorectal cancer. [Research support, non-U.S. Gov’t]. Cancer Discovery, 1(6), 508–523. doi: 10.1158/2159-8290.CD-11-0109.PubMedCrossRefGoogle Scholar
  214. 214.
    Gao, H., Korn, J. M., Ferretti, S., Monahan, J. E., Wang, Y., Singh, M., et al. (2015). High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response. Nature Medicine, 21(11), 1318–1325, doi: 10.1038/nm.3954.

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Lacey E. Dobrolecki
    • 1
  • Susie D. Airhart
    • 2
  • Denis G. Alferez
    • 3
  • Samuel Aparicio
    • 4
  • Fariba Behbod
    • 5
  • Mohamed Bentires-Alj
    • 6
  • Cathrin Brisken
    • 7
  • Carol J. Bult
    • 2
  • Shirong Cai
    • 8
  • Robert B. Clarke
    • 3
  • Heidi Dowst
    • 9
  • Matthew J. Ellis
    • 1
  • Eva Gonzalez-Suarez
    • 10
  • Richard D. Iggo
    • 11
  • Peter Kabos
    • 12
  • Shunqiang Li
    • 13
  • Geoffrey J. Lindeman
    • 14
    • 15
    • 16
  • Elisabetta Marangoni
    • 17
  • Aaron McCoy
    • 8
  • Funda Meric-Bernstam
    • 18
  • Helen Piwnica-Worms
    • 8
  • Marie-France Poupon
    • 19
  • Jorge Reis-Filho
    • 20
  • Carol A. Sartorius
    • 21
  • Valentina Scabia
    • 7
  • George Sflomos
    • 7
  • Yizheng Tu
    • 8
  • François Vaillant
    • 14
    • 22
  • Jane E. Visvader
    • 14
    • 22
  • Alana Welm
    • 23
  • Max S. Wicha
    • 24
  • Michael T. Lewis
    • 1
  1. 1.The Lester and Sue Smith Breast Center, Departments of Molecular and Cellular Biology and RadiologyBaylor College of MedicineHouston,USA
  2. 2.The Jackson LaboratoryBar HarborUSA
  3. 3.Breast Cancer Now Research Unit, Division of Molecular and Clinical Cancer Sciences, Manchester Cancer Research CentreUniversity of ManchesterManchesterUK
  4. 4.Department of Pathology and Laboratory MedicineBC Cancer AgencyVancouverCanada
  5. 5.Department of PathologyUniversity of Kansas Medical CenterKansas CityUSA
  6. 6.Department of BiomedicineUniversity of Basel, University Hospital BaselBaselSwitzerland
  7. 7.School of Life SciencesEcole Polytechnique Fédérale de Lausanne (EPFL), ISREC—Swiss Institute for Experimental Cancer ResearchLausanneSwitzerland
  8. 8.Department of Experimental Radiation OncologyUniversity of Texas MD Anderson Cancer CenterHoustonUSA
  9. 9.Dan L. Duncan Cancer CenterBaylor College of MedicineHoustonUSA
  10. 10.Cancer Epigenetics and Biology ProgramPEBC, Bellvitge Institute for Biomedical Research, IDIBELL, Av. Gran Via de L’HospitaletBarcelonaSpain
  11. 11.INSERM U1218Bergonié Cancer InstituteBordeauxFrance
  12. 12.Division of Medical Oncology, Department of MedicineUniversity of Colorado Anschutz Medical CampusAuroraUSA
  13. 13.Department of Internal MedicineWashington UniversitySt. LouisUSA
  14. 14.Stem Cells and Cancer DivisionWalter and Eliza Hall Institute of Medical ResearchParkvilleAustralia
  15. 15.Department of MedicineThe University of MelbourneParkvilleAustralia
  16. 16.Familial Cancer CentreRoyal Melbourne Hospital, Peter MacCallum Cancer CentreParkvilleAustralia
  17. 17.Translational Research DepartmentInstitut CurieParisFrance
  18. 18.Departments of Investigational Cancer Therapeutics and Breast Surgical OncologyUT M. D. Anderson Cancer CenterHoustonUSA
  19. 19.Founder and Scientific AdvisorXenTech SA, GenopoleEvryFrance
  20. 20.Director of Experimental Pathology, Department of Pathology, Affiliate Member, Human Oncology and Pathogenesis Program, and Center for Computational BiologyMemorial Sloan Kettering Cancer CenterNew YorkUSA
  21. 21.Department of PathologyUniversity of Colorado Anschutz Medical CampusAuroraUSA
  22. 22.Department of Medical BiologyUniversity of MelbourneParkvilleAustralia
  23. 23.Huntsman Cancer InstituteUniversity of UtahSalt Lake CityUSA
  24. 24.Madeline and Sidney Forbes Professor of Oncology, DirectorForbes Institute for Cancer DiscoveryAnn ArborUSA

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