Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

The cell-line-derived subcutaneous tumor model in preclinical cancer research

Abstract

Tumor-bearing experimental animals are essential for preclinical cancer drug development. A broad range of tumor models is available, with the simplest and most widely used involving a tumor of mouse or human origin growing beneath the skin of a mouse: the subcutaneous tumor model. Here, we outline the different types of in vivo tumor model, including some of their advantages and disadvantages and how they fit into the drug-development process. We then describe in more detail the subcutaneous tumor model and key steps needed to establish it in the laboratory, namely: choosing the mouse strain and tumor cells; cell culture, preparation and injection of tumor cells; determining tumor volume; mouse welfare; and an appropriate experimental end point. The protocol leads to subcutaneous tumor growth usually within 1–3 weeks of cell injection and is suitable for those with experience in tissue culture and mouse experimentation.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Preclinical cancer drug development.
Fig. 2: Different types of subcutaneous model.
Fig. 3: Noninvasive imaging using bioluminescent tumor cells.
Fig. 4: Setting up and using subcutaneous tumors in mice.
Fig. 5: Converting tumor measurements into tumor volumes.

Similar content being viewed by others

References

  1. Ireson, C. R., Alavijeh, M. S., Palmer, A. M., Fowler, E. R. & Jones, H. J. The role of mouse tumour models in the discovery and development of anticancer drugs. Br. J. Cancer 121, 101–108 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Herter-Sprie, G. S., Kung, A. L. & Wang, K.-K. New cast for a new era: preclinical cancer drug development revisited. J. Clin. Invest. 123, 3639–3645 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Damia, G. & D´Incalci, M. Contemporary pre-clinical development of anticancer agents—what are the optimal preclinical models? Eur. J. Cancer 45, 2768–2781 (2009).

    Article  CAS  PubMed  Google Scholar 

  4. Ahmad, A. S., Ormiston-Smith, N. & Sasieni, P. D. Trends in the lifetime risk of developing cancer in Great Britain: comparison of risk for those born from 1930 to 1960. Br. J. Cancer 112, 943–947 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Morton, C. L. & Houghton, P. J. Establishment of human tumor xenografts in immunodeficient mice. Nat. Protoc. 2, 247–250 (2007).

    Article  CAS  PubMed  Google Scholar 

  6. Gengenbacher, N., Singhal, M. & Augustin, H. G. Preclinical mouse solid tumour models: status quo, challenges and perspectives. Nat. Rev. Cancer 17, 751–765 (2017).

    Article  CAS  PubMed  Google Scholar 

  7. Teicher, B. A. Tumor models for efficacy determination. Mol. Cancer Ther. 5, 2435–2443 (2006).

    Article  CAS  PubMed  Google Scholar 

  8. Carver, B. S. & Pandolfi, P. P. Mouse modelling in oncologic preclinical and translational research. Clin. Cancer Res. 12, 5305–5311 (2006).

    Article  CAS  PubMed  Google Scholar 

  9. Junttila, M. R. & de Sauvage, F. J. Influence of tumour micro-environment heterogeneity on therapeutic response. Nature 501, 346–354 (2013).

    Article  CAS  PubMed  Google Scholar 

  10. Sikder, H. et al. Disruption of ID1 reveals major differences in angiogenesis between transplanted and autochthonous tumours. Cancer Cell 4, 291–299 (2003).

    Article  CAS  PubMed  Google Scholar 

  11. Frese, K. K. & Tuveson, D. A. Maximizing mouse cancer models. Nat. Rev. Cancer 7, 654–658 (2007).

    Article  CAS  Google Scholar 

  12. Klein, C. A. Parallel progression of parallel tumours and metastases. Nat. Rev. Cancer 9, 302–312 (2009).

    Article  CAS  PubMed  Google Scholar 

  13. Sharpless, N. E. & DePinho, R. A. The mighty mouse: genetically engineered mouse models in cancer drug development. Nat. Rev. Drug Discov. 5, 741–754 (2006).

    Article  CAS  PubMed  Google Scholar 

  14. Fidler, I. J. & Kripke, M. L. The challenge of targeting metastasis. Cancer Metastasis Rev. 34, 635–641 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Spano, D., Heck, C., De Antonellis, P., Christofori, G. & Zollo, M. Molecular networks that regulate cancer metastasis. Semin. Cancer Biol. 22, 234–249 (2012).

    Article  CAS  PubMed  Google Scholar 

  16. Bugge, T. H. et al. Growth and dissemination of Lewis lung carcinoma in plasminogen-deficient mice. Blood 90, 4522–4531 (1997).

    Article  CAS  PubMed  Google Scholar 

  17. Rose, D. P., Connolly, J. M. & Liu, X. H. Effects of linoleic acid on the growth and metastasis of two human breast cancer cell lines in nude mice and the invasive capacity of these cell lines in vitro. Cancer Res. 54, 6557–6562 (1994).

    CAS  PubMed  Google Scholar 

  18. Bailey-Downs, L. C. et al. Development and characterization of a preclinical model of breast cancer lung micrometastatic to macrometastatic progression. PLoS One 9, e98624 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Hidalgo, M. et al. Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov. 4, 998–1013 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Tentler, J. J. et al. Patient-derived tumour xenografts as models for oncology drug development. Nat. Rev. Clin. Oncol. 9, 338–350 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. DeRose, Y. S. et al. Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nat. Med. 17, 1514–1520 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Siolas, D. & Hannon, G. J. Patient-derived tumour xenografts: transforming clinical samples into mouse models. Cancer Res. 73, 5315–5319 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Julien, S. et al. Characterisation of a large panel of patient-derived tumor xenografts representing the clinical heterogeneity of human colorectal cancer. Clin. Cancer Res. 18, 5314–5328 (2012).

    Article  CAS  PubMed  Google Scholar 

  24. Clohessy, J. G. & Pandolfi, P. P. Mouse hospital and co-clinical trial project—from bench to bedside. Nat. Rev. Clin. Oncol. 12, 491–498 (2015).

    Article  PubMed  Google Scholar 

  25. Zitvogel, L., Pitt, J. M., Daillè, R., Smythe, M. J. & Kroemer, G. Mouse models in oncoimmunology. Nat. Rev. Cancer 16, 759–773 (2016).

    Article  CAS  PubMed  Google Scholar 

  26. Simpson-Abelson, M. R. et al. Long-term engraftment and expansion of tumor-derived memory T cells following the implantation of non-disrupted pieces of human lung tumor into NOD-scid IL2Rγnull mice. J. Immunol. 180, 7009–7018 (2008).

    Article  CAS  PubMed  Google Scholar 

  27. Lang, J., Weiss, N., Freed, B. M., Torres, R. & Pelonda, R. Generation of hematopoetic humanized mice in the newborn BALB/c-Rag2null IL2rγnull mouse model: a multivariable optimization approach. Clin. Immunol. 140, 102–116 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Lawrence, M. G. et al. Establishment of primary patient-derived xenografts of palliative TURP specimens to study castrate-resistant prostate cancer. Prostate 75, 1475–1483 (2015).

    Article  CAS  PubMed  Google Scholar 

  29. Couzin-Frankel, J. The littlest patient. Science 346, 24–27 (2014).

    Article  PubMed  Google Scholar 

  30. Delitto, D. et al. Patient-derived xenograft models for pancreatic adenocarcinoma demonstrate retention of tumor morphology through incorporation of murine stromal elements. Am. J. Pathol. 185, 1297–1303 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Eirew, P. et al. Dynamics of genomic clones in breast cancer patient xenografts at single cell resolution. Nature 518, 422–426 (2015).

    Article  CAS  PubMed  Google Scholar 

  32. Baklaushev, V. P. et al. Luciferase expression allows bioluminescence imaging but imposes limitations on the orthotopic mouse (4T1) model of breast cancer. Sci. Rep. 17, 1–17 (2017).

    Google Scholar 

  33. Day, C. P. et al. “Glowing head” mice: a genetic tool enabling reliable preclinical image-based evaluation of cancers in immunocompetent allografts. PLoS One 9, e109956 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Hanahan, D. & Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 144, 647–674 (2011).

    Article  CAS  Google Scholar 

  35. Bray, F. et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 68, 394–424 (2018).

    Article  PubMed  Google Scholar 

  36. Willoughby, C.E. et al. Selective DNA-PKcs inhibition extends the therapeutic index of localized radiotherapy and chemotherapy. J. Clin. Invest. 130, 258–271 (2020).

    Article  CAS  PubMed  Google Scholar 

  37. Jiang, Y., Willmore, E., Wedge, S.R. & Ryan, A.J. DNAPK inhibition preferentially compromises the repair of radiation-induced DNA double-strand breaks in chronically hypoxic tumor cells in xenograft models. Mol. Cancer Ther. 20, 1663–1671 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Byrne, A. T. et al. Interrogating open issues in cancer precision medicine with patient-derived xenografts. Nat. Rev. Cancer 17, 254–268 (2017).

    Article  CAS  PubMed  Google Scholar 

  39. Inoue, T., Terada, N., Kobayashi, T. & Ogawa, O. Patient-derived xenografts as in vivo models for research in urological malignancies. Nat. Rev. Urol. 14, 267–283 (2017).

    Article  PubMed  Google Scholar 

  40. Olson, B., Li, Y., Lin, Y., Liu, E. T. & Patnai, A. Mouse models for cancer immunotherapy research. Cancer Discov. 8, 1358–1365 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Prochazka, M., Gaskins, H. R., Shiltz, L. D. & Leiter, E. H. The nonobese diabetic scid mouse: model for spontaneous thymomagenesis associated with immunodeficiency. Proc. Natl. Acad. Sci. USA. 89, 3290–3294 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Floersheim, G. L., Nassenstein, D. & Torhorst, J. Growth of human tumours in mice after short-term immunosuppression with procarbazine, cyclophosphamide and antilymphocyte serum. Transplantation 30, 275–280 (1980).

    Article  CAS  PubMed  Google Scholar 

  43. Floersheim, G. L. Comparative growth of human tumors in pharmacologically immunosuppressed, immune-deprived, cyclosporin A-treated and nude mice. Eur. J. Cancer Clin. Oncol. 18, 589–594 (1982).

    Article  CAS  PubMed  Google Scholar 

  44. Jivrajani, M., Shaikh, M. V., Shrivastava, N. & Nivsarkar, M. An improved and versatile immunosuppression protocol for the development of tumor xenograft in mice. Anticancer Res. 34, 7177–7183 (2014).

    PubMed  Google Scholar 

  45. Diehl, R. et al. Immunosuppression for in vivo research: state-of-the-art protocols and experimental approaches. Cell Mol. Immunol. 14, 146–179 (2017).

    Article  CAS  PubMed  Google Scholar 

  46. Sominski, D. D. et al. Development of a squamous cell carcinoma mouse model for immunotoxicity testing. J. Immunotox. 13, 226–234 (2016).

    Article  CAS  Google Scholar 

  47. Bugelski, P. J. et al. Critical review of preclinical approaches to evaluate the potential of immunosuppressive drugs to influence human neoplasia. Int. J. Toxicol. 29, 435–466 (2010).

    Article  CAS  PubMed  Google Scholar 

  48. Miller, L. R. et al. Considering sex as a biological variable in preclinical research. FASEB J. 31, 29–34 (2017).

    Article  CAS  PubMed  Google Scholar 

  49. Bailoo, J. D., Reichlin, T. S. & Wurbel, H. Refinement of experimental design and conduct in laboratory research. ILAR J. 55, 383–391 (2014).

    Article  CAS  PubMed  Google Scholar 

  50. Clayton, J. A. Studying both sexes: a guiding principle for biomedicine. FASEB J. 30, 519–524 (2016).

    Article  CAS  PubMed  Google Scholar 

  51. Reed, M. J. et al. The effects of aging on tumor growth and angiogenesis are tumor-cell dependent. Int. J. Cancer 120, 753–760 (2006).

    Article  CAS  Google Scholar 

  52. Ershler, W. B., Gamelli, R. L., Moore, A. L., Hacker, M. P. & Blow, A. J. Experimental tumors and aging: local factors that may account for the observed age advantage in the B16 murine melanoma model. Exp. Gerontol. 19, 367–376 (1984).

    Article  CAS  PubMed  Google Scholar 

  53. Tsuda, T. et al. Role of the thymus and T-cells in slow growth of B16 melanoma in old mice. Cancer Res. 47, 3097–3100 (1987).

    CAS  PubMed  Google Scholar 

  54. Balducci, L. & Ershler, W. B. Cancer and ageing: a nexus at several levels. Nat. Rev. Cancer 5, 655–662 (2005).

    Article  CAS  PubMed  Google Scholar 

  55. Currer, J. M., Witham, B., Linder, C. and Flurkey, K. in The Jackson Laboratory Handbook on Genetically Standardized Mice Edn. 6 (eds. Flurkey, K., Currer, J. M., Leiter, E. H. & Witham, B.) 149–164 (The Jackson Laboratory, 2009).

  56. Dell, R. B., Holleran, S. & Ramakrishnan, R. Sample size determination. ILAR J. 43, 207–213 (2002).

    Article  CAS  PubMed  Google Scholar 

  57. Prasad, V. V. T. S. & Gopalan, R. O. G. Continued use of MDA-MB-435, a melanoma cell line, as a model for human breast cancer, even in year, 2014. NPJ Breast Cancer 1, 15002 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Holliday, D. L. & Speirs, V. Choosing the right cell line for breast cancer research. Breast Cancer Res. 13, 215–222 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Culture of Animal Cells: A Manual of Basic Techniques and Specialized Applications Edn. 7 (ed. Freshney, R. I.) (John Wiley & Sons, Hoboken, New Jersey, USA, 2010).

  60. Nikfarjam, L. & Farzaneh, P. Prevention and detection of mycoplasma contamination in cell culture. Cell J. 13, 203–212 (2012).

    PubMed  Google Scholar 

  61. Zhang, X. et al. A renewable tissue resource of phenotypically stable, biologically and ethnically diverse, patient-derived human breast cancer xenograft models. Cancer Res. 73, 4885–4897 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Dall, G., Vieusseux, J., Unsworth, A., Anderson, R. & Britt, K. Low dose, low cost estradiol pellets can support MCF-7 tumour growth in nude mice without bladder symptoms. J. Cancer 6, 1331–1336 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Ström, J. O., Theodorsson, A., Ingberg, E., Isaksson, I. M. & Theodorsson, E. Ovariectomy and 17β-estradiol replacement in rats and mice: a visual demonstration. J. Vis. Exp. 2012, e4013 (2012).

    Google Scholar 

  64. Ingberg, E., Theodorsson, A., Theodorsson, E. & Ström, J. O. Methods for long-term17ß-estradiol administration to mice. Gen. Comp. Endocrinol. 175, 188–193 (2012).

    Article  CAS  PubMed  Google Scholar 

  65. Fridman, R. et al. Enhanced tumor growth of both primary and established human and murine tumor cells in athymic mice after coinjection with Matrigel. J. Natl Cancer Inst. 83, 769––774 (1991).

    Article  PubMed  Google Scholar 

  66. Mehta, R. R., Graves, J. M., Hart, G. D., Shilkaitis, A. & DasGupta, T. K. Growth and metastasis of human breast carcinomas with Matrigel in athymic mice. Breast Cancer Res. Treat. 25, 65–71 (1993).

    Article  CAS  PubMed  Google Scholar 

  67. Mullen, P., Ritchie, A., Langdon, S. P. & Miller, W. R. Effect of Matrigel on the tumorigenicity of human breast and ovarian carcinoma cell lines. Int. J. Cancer 67, 816–820 (1996).

    Article  CAS  PubMed  Google Scholar 

  68. Tomayko, M. M. & Reynolds, C. P. Determination of subcutaneous tumour size in athymic (nude) mice. Cancer Chemother. Pharmacol. 24, 148–154 (1989).

    Article  CAS  PubMed  Google Scholar 

  69. Workman, P. et al. Guidelines for the welfare and use of animals in cancer research. Br. J. Cancer 102, 1555–1577 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Shah, S. M., Jain, A. S., Kaushik, R., Nagarsenker, M. S. & Nerurkar, M. J. Preclinical formulations: insight, strategies, and practical considerations. AAPS PharmSciTech 15, 1307–1323 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Hedrich, H. J. (ed.) The Laboratory Mouse Edn. 2 (Academic, 2012).

  72. Benzonana, L. L. et al. Isoflurane, a commonly used volatile anesthetic, enhances renal cancer growth and malignant potential via the hypoxia inducible factor cellular signalling pathway in vitro. Anesthesiology 119, 593–605 (2013).

    Article  CAS  PubMed  Google Scholar 

  73. Huitink, J. M. et al. Volatile anesthetics modulate gene expression in breast and brain tumor cells. Anesth. Analg. 111, 1411–1415 (2010).

    Article  CAS  PubMed  Google Scholar 

  74. Wigmore, T. J., Mohammed, K. & Jhanji, S. Long-term survival for patients undergoing volatile versus IV anesthesia for cancer surgery: a retrospective analysis. Anesthesiology 124, 69–79 (2016).

    Article  CAS  PubMed  Google Scholar 

  75. Tiouririne, M. et al. IV Lidocaine for Patients Undergoing Primary Breast Cancer Surgery: Effects on Postoperative Recovery and Cancer Recurrence. ClinicalTrials.gov Identifier: NCT01204242 (2022).

  76. Wall, T. et al. Influence of perioperative anaesthetic and analgesic interventions on oncological outcomes: a narrative review. Br. J. Anaesth. 123, 135–150 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Bhat, S. A. et al. Long non-coding RNAs: mechanism of action and functional utility. Noncoding RNA Res. 1, 43–50 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  78. Kilkenny, C., Browne, W. J., Cuthill, I. C., Emerson, M. & Altman, D. G. Improving bioscience research reporting: the ARRIVE guidelines for reporting animal research. PLoS Biol. 8, e1000412 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  79. Sugar, E., Pascoe, A. J. & Azad, N. Reporting of preclinical tumor-graft cancer therapeutic studies. Cancer Biol. Ther. 13, 1262–1268 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  80. MacCallum, C. J. Reporting animal studies: good science and a duty of care. PLoS Biol. 8, e1000413 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  81. Drobnitzky, N. Novel Therapeutic Strategies for Targeting EGFR Mutated Non-Small Cell Lung cancer. PhD thesis, Univ. Oxford (2017).

  82. Staton, C. A. et al. Identification of key residues involved in mediating the in vivo anti-tumor/anti-endothelial activity of Alphastatin. J. Thromb. Haemost. 5, 846–854 (2007).

    Article  CAS  PubMed  Google Scholar 

  83. Osada, T. et al. In vivo detection of HSP90 identifies breast cancers with aggressive behaviour. Clin. Cancer Res. 23, 7531–7542 (2017).

    Article  CAS  PubMed  Google Scholar 

  84. Harnoss, J. M. et al. IRE1α disruption in triple-negative breast cancer cooperates with antiangiogenic therapy by reversing ER stress adaptation and remodeling the tumor microenvironment. Cancer Res. 80, 2368–2379 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Masiero, M. et al. Development of therapeutic anti-JAGGED1 antibodies for cancer therapy. Mol. Cancer Ther. 18, 2030–2042 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Sudhan, D. R. et al. Extended adjuvant therapy with neratinib plus fulvestrant blocks ER/HER2 crosstalk and maintains complete responses of ER+/HER2+ breast cancers: implications to the ExteNET trial. Clin. Cancer Res. 25, 771–783 (2019).

    Article  CAS  PubMed  Google Scholar 

  87. Stribbling, S. M. et al. Regressions of established breast carcinoma xenografts by carboxypeptidase G2 suicide gene therapy and the prodrug CMDA are due to a bystander effect. Hum. Gene Ther. 11, 285–292 (2000).

    Article  CAS  PubMed  Google Scholar 

  88. Kennedy, S. P. et al. Preclinical evaluation of a novel triple-acting PIM/PI3K/mTOR inhibitor, IBL-302, in breast cancer. Oncogene 39, 3028–3040 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Chen, F. et al. Ultrasmall targeted nanoparticles with engineered antibody fragments for imaging detection of HER2-overexpressing breast cancer. Nat. Commun. 9, 4141–4152 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  90. Hiraki, M. et al. Targeting MUC1-C suppresses BCL2A1 in triple-negative breast cancer. Sig. Transduct. Target Ther. 3, 13–20 (2018).

    Article  CAS  Google Scholar 

  91. Kumar, M., Yigit, M., Dai, G., Moore, A. & Medarova, Z. Image-guided breast tumor therapy using a small interfering RNA nanodrug. Cancer Res. 70, 7553–7561 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Sultan, A. S. et al. Stat5 promotes homotypic adhesion and inhibits invasive characteristics of human breast cancer cells. Oncogene 24, 746–760 (2005).

    Article  CAS  PubMed  Google Scholar 

  93. Ayan, D., Maltais, R., Roy, J. & Poirier, D. A new nonestrogenic steroidal inhibitor of 17β-hydroxysteroid dehydrogenase type I blocks the estrogen-dependent breast cancer tumor growth induced by estrone. Mol. Cancer Ther. 11, 2096–2104 (2012).

    Article  CAS  PubMed  Google Scholar 

  94. Theodossiou, T. A. et al. Simultaneous defeat of MCF7 and MDA-MB-231 resistances by a hypericin PDT–tamoxifen hybrid therapy. NPJ Breast Cancer 5, 13–22 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  95. Elmi, A. et al. Cell-proliferation imaging for monitoring response to CDK4/6 inhibition combined with endocrine-therapy in breast cancer: comparison of [18F]FLT and [18F]ISO-1 PET/CT. Clin. Cancer Res. 25, 3063–3073 (2019).

    Article  CAS  PubMed  Google Scholar 

  96. Cappuccini, F., Stribbling, S., Pollock, E., Hill, A. V. S. & Redchenko, I. Immunogenicity and efficacy of the novel cancer vaccine based on simian adenovirus and MVA vectors alone and in combination with PD-1 mAb in a mouse model of prostate cancer. Cancer Immunol. Immunother. 65, 701–713 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Philippou, Y. et al. Impacts of combining anti-PD-L1 immunotherapy and radiotherapy on the tumour immune microenvironment in a murine prostate cancer model. Br. J. Cancer 123, 1089–1100 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Zheng, X. et al. Atorvastatin and celecoxib inhibit prostate PC-3 tumors in immunodeficient mice. Clin. Cancer Res. 13, 5480–5487 (2007).

    Article  CAS  PubMed  Google Scholar 

  99. Chan, Q. K. Y. et al. Activation of GPR30 inhibits the growth of prostate cancer cells through sustained activation of Erk1/2, c-jun/c-fos-dependent upregulation of p21, and induction of G2 cell-cycle arrest. Cell Death Differ. 17, 1511–1523 (2010).

    Article  CAS  PubMed  Google Scholar 

  100. Bansal, N. et al. Darinaparsin inhibits prostate tumor–initiating cells and Du145 xenografts and is an inhibitor of hedgehog signaling. Mol. Cancer Ther. 14, 23–30 (2015).

    Article  CAS  PubMed  Google Scholar 

  101. Yan, J., De Melo, J., Cutz., J.-C., Aziz, T. & Tang, D. Aldehyde dehydrogenase 3A1 associates with prostate tumorigenesis. Br. J. Cancer 110, 2593–2603 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Tang, Y. et al. Docetaxel followed by castration improves outcomes in LNCaP prostate cancer–bearing severe combined immunodeficient mice. Clin. Cancer Res. 12, 169–174 (2006).

    Article  CAS  PubMed  Google Scholar 

  103. Welén, K., Jennbacken, K., Tes̆an, T. & Damber, J.-E. Pericyte coverage decreases invasion of tumour cells into blood vessels in prostate cancer xenografts. Prostate Cancer Prostatic Dis. 12, 41–46 (2009).

    Article  PubMed  CAS  Google Scholar 

  104. Marshall, N. A. et al. Immunotherapy with PI3K inhibitor and toll-like receptor agonist induces IFN-γ+IL-17+ polyfunctional T cells that mediate rejection of murine tumors. Cancer Res. 72, 581–591 (2012).

    Article  CAS  PubMed  Google Scholar 

  105. Kim, D. H. et al. Exosomal PD-L1 promotes tumor growth through immune escape in non-small cell lung cancer. Exp. Mol. Med. 51, 1–13 (2019).

    PubMed  PubMed Central  Google Scholar 

  106. Zhang, X. et al. Targeting CD47 and autophagy elicited enhanced antitumor effects in non–small cell lung cancer. Cancer Immunol. Res. 5, 363–375 (2017).

    Article  CAS  PubMed  Google Scholar 

  107. Fan, J. et al. Bruceine D induces lung cancer cell apoptosis and autophagy via the ROS/MAPK signaling pathway in vitro and in vivo. Cell Death Dis. 11, 126–140 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Rho, J. K. et al. Combined treatment with silibinin and epidermal growth factor receptor tyrosine kinase inhibitors overcomes drug resistance caused by T790M mutation. Mol. Cancer Ther. 9, 323–343 (2010).

    Article  CAS  Google Scholar 

  109. Yamaoka, T. et al. Distinct afatinib resistance mechanisms identified in lung adenocarcinoma harboring an EGFR mutation. Mol. Cancer Res. 15, 915–928 (2017).

    Article  CAS  PubMed  Google Scholar 

  110. Whalen, K. A. et al. Targeting the somatostatin receptor 2 with the miniaturized drug conjugate, PEN-221: a potent and novel therapeutic for the treatment of small cell lung cancer. Mol. Cancer Ther. 18, 1926–1936 (2019).

    Article  CAS  PubMed  Google Scholar 

  111. Hirt, U. A. et al. Efficacy of the highly selective focal adhesion kinase inhibitor BI 853520 in adenocarcinoma xenograft models is linked to a mesenchymal tumor phenotype. Oncogenesis 7, 21–31 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  112. Iwata, T. N. et al. A HER2-targeting antibody-drug conjugate, trastuzumab deruxtecan (DS-8201a), enhances antitumor immunity in a mouse model. Mol. Cancer Ther. 17, 1494–1503 (2018).

    Article  CAS  PubMed  Google Scholar 

  113. de Almeida, P. E. et al. Anti-VEGF treatment enhances CD8+ T-cell antitumor activity by amplifying hypoxia. Cancer Immunol. Res. 8, 806–818 (2020).

    Article  PubMed  Google Scholar 

  114. Govindan, S. V., Cardillo, T. M., Moon, S. J., Hansen, H. J. & Goldenberg, D. M. CEACAM5-targeted therapy of human colonic and pancreatic cancer xenografts with potent labetuzumab-SN-38 immunoconjugates. Clin. Cancer Res. 15, 6052–6061 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Chiacchiera, F. et al. p38α blockade inhibits colorectal cancer growth in vivo by inducing a switch from HIF1α- to FoxO-dependent transcription. Cell Death Differ. 16, 1203–1214 (2009).

    Article  CAS  PubMed  Google Scholar 

  116. Ruiz de Sabando, A. et al. ML264, A novel small-molecule compound that potently inhibits growth of colorectal cancer. Mol. Cancer Ther. 15, 72–83 (2016).

    Article  CAS  PubMed  Google Scholar 

  117. Takahashi, T., Kanazawa, J., Akinaga, S., Tamaoki, T. & Okabe, M. Antitumor activity of 2-chloro-9-(2-deoxy-2-fluoro-β-D-arabinofuranosyl) adenine, a novel deoxyadenosine analog, against human colon tumor xenografts by oral administration. Cancer Chemother. Pharmacol. 43, 233–240 (1999).

    Article  CAS  PubMed  Google Scholar 

  118. Englinger, B. et al. Loss of CUL4A expression is underlying cisplatin hypersensitivity in colorectal carcinoma cells with acquired trabectedin resistance. Br. J. Cancer 116, 489–500 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Hingorani, D. V. et al. Precision chemoradiotherapy for HER2 tumors using antibody conjugates of an auristatin derivative with reduced cell permeability. Mol. Cancer Ther. 19, 157–167 (2020).

    Article  CAS  PubMed  Google Scholar 

  120. Rebecca, V. W. et al. PPT1 promotes tumor growth and is the molecular target of chloroquine derivatives in cancer. Cancer Discov. 9, 396–415 (2019).

    Article  PubMed  Google Scholar 

  121. Shepelytskyi, Y. et al. In-vivo retention of 5-fluorouracil using 19F magnetic resonance chemical shift imaging in colorectal cancer in a murine model. Sci. Rep. 9, 13244 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  122. Byth, K. F. et al. AZD5438, a potent oral inhibitor of cyclin-dependent kinases 1, 2, and 9, leads to pharmacodynamic changes and potent antitumor effects in human tumor xenografts. Mol. Cancer Ther. 8, 1856–1866 (2009).

    Article  CAS  PubMed  Google Scholar 

  123. Papaevangelou, E., Almeida, G. S., Jamin, Y., Robinson, S. P. & deSouza, N. M. Diffusion-weighted MRI for imaging cell death after cytotoxic or apoptosis-inducing therapy. Br. J. Cancer 112, 1471–1479 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Singhal, S. S. et al. A target for kidney cancer therapy. Cancer Res. 69, 4244–4251 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Kumar, R. et al. Pharmacokinetic-pharmacodynamic correlation from mouse to human with pazopanib, a multikinase angiogenesis inhibitor with potent antitumor and antiangiogenic activity. Mol. Cancer Ther. 6, 2012–2021 (2007).

    Article  CAS  PubMed  Google Scholar 

  126. Dasgupta, P. et al. MicroRNA-203 inhibits long noncoding RNA HOTAIR and regulates tumorigenesis through epithelial-to-mesenchymal transition pathway in renal cell carcinoma. Mol. Cancer Ther. 17, 1061–1069 (2108).

    Article  CAS  Google Scholar 

  127. Gerdes, C. A. et al. GA201 (RG7160): a novel, humanized glycoengineered anti-EGFR antibody with enhanced ADCC and superior in vivo efficacy compared with cetuximab. Clin. Cancer Res. 19, 1126–1138 (2006).

    Article  CAS  Google Scholar 

  128. Matsuki, M. et al. Lenvatinib inhibits angiogenesis and tumor fibroblast growth factor signalling pathways in human hepatocellular carcinoma models. Cancer Med. 7, 2641–2653 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Pu, J. et al. ADORA2A-AS1 restricts hepatocellular carcinoma progression via binding HuR and repressing FSCN1/AKT axis. Front. Oncol. 11, 754835 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  130. Eng, C. H. et al. Macroautophagy is dispensable for growth of KRAS mutant tumors and chloroquine efficacy. Proc. Natl. Acad. Sci. USA. 113, 182–187 (2016).

    Article  CAS  PubMed  Google Scholar 

  131. Xiao, Q. et al. Cancer-associated fibroblasts in pancreatic cancer are reprogrammed by tumor-induced alterations in genomic DNA methylation. Cancer Res. 76, 5395–5404 (2021).

    Article  CAS  Google Scholar 

  132. Yang, L. et al. Targeting interleukin-4 receptor a with hybrid peptide for effective cancer therapy. Mol. Cancer Ther. 11, 235–243 (2011).

    Article  PubMed  CAS  Google Scholar 

  133. Tonra, J. R. et al. Synergistic antitumor effects of combined epidermal growth factor receptor and vascular endothelial growth factor receptor-2 targeted therapy. Clin. Cancer Res. 12, 2197–2207 (2006).

    Article  CAS  PubMed  Google Scholar 

  134. Lee, S. J. et al. Curcumin-induced HDAC inhibition and attenuation of medulloblastoma growth in vitro and in vivo. BMC Cancer 11, 144–156 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Li, X.-N. et al. Valproic acid induces growth arrest, apoptosis, and senescence in medulloblastomas by increasing histone hyperacetylation and regulating. Mol. Cancer Ther. 4, 1912–1922 (2005).

    Article  CAS  PubMed  Google Scholar 

  136. Lee, S. Y. et al. Characterization of a novel anti-cancer compound for astrocytomas. PLoS One 9, e108166 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  137. Li, T. et al. Phospholipase Cγ1 (PLCG1) overexpression is associated with tumor growth and poor survival in IDH wild-type lower-grade gliomas in adult patients. Lab Invest. 102, 143–153 (2022).

    Article  CAS  PubMed  Google Scholar 

  138. Sanchez, I. M. et al. In vivo ERK 1/2 reporter predictively models response and resistance to combined BRAF and MEK inhibitors in melanoma. Mol. Cancer Ther. 18, 1637–1648 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Segat, G. C. et al. A new series of acetohydroxamates shows in vitro and in vivo anticancer activity against melanoma. Invest. N. Drugs 38, 977–989 (2020).

    Article  CAS  Google Scholar 

  140. Garton, A. J. et al. OSI-930: a novel selective inhibitor of Kit and kinase insert domain receptor tyrosine kinases with antitumor activity in mouse xenograft models. Cancer Res. 66, 1015–1024 (2006).

    Article  CAS  PubMed  Google Scholar 

  141. Beitz, J. G. et al. Antitumor activity of basic fibroblast growth factor-saporin mitotoxin in vitro and in vivo. Cancer Res. 52, 227–230 (1992).

    CAS  PubMed  Google Scholar 

  142. Fung, A. S., Yu, M., Ye, Q. J. & Tannock, I. F. Scheduling of paclitaxel and gefitinib to inhibit repopulation for optimal treatment of human cancer cells and xenografts that overexpress the epidermal growth factor receptor. Cancer Chemother. Pharmacol. 72, 585–595 (2013).

    Article  CAS  PubMed  Google Scholar 

  143. Anand, S. et al. Fluorouracil enhances photodynamic therapy of squamous cell carcinoma via a p53-independent mechanism that increases protoporphyrin IX levels and tumor cell death. Mol. Cancer Ther. 16, 1092–1101 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Morris, J. et al. F-aza-T-dCyd (NSC801845), a novel cytidine analog, in comparative cell culture and xenograft studies with the clinical candidates T-dCyd, F-T-dCyd, and Aza-T-dCyd. Mol. Cancer Ther. 20, 625–631 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Molthoff, C. F. M., Pinedo, H. M., Schluper, H. M. M., Rutgers, D. H. & Boven, E. Comparison of 131I-labelled anti-episialin 139H2 with cisplatin, cyclophosphamide or external-beam radiation for anti-tumor efficacy in human ovarian cancer xenografts. Int. J. Cancer 51, 108–115 (1992).

    Article  CAS  PubMed  Google Scholar 

  146. Yao, S. et al. Development and evaluation of novel tumor-targeting paclitaxel-loaded nano-carriers for ovarian cancer treatment: in vitro and in vivo. J. Exp. Clin. Cancer Res. 37, 29 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  147. Bardella, C. et al. The therapeutic potential of hepatocyte growth factor to sensitize ovarian cancer cells to cisplatin and paclitaxel in vivo. Clin. Cancer Res. 13, 2191–2198 (2007).

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

Both S.M.S. and A.J.R. contributed to the preparation and writing of the manuscript.

Corresponding authors

Correspondence to Stephen M. Stribbling or Anderson J. Ryan.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Protocols thanks Sing Leng Chan and Nicolas Skuli for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Key references using this protocol

Willoughby, C. E. et al. J. Clin. Invest. 130, 258–271 (2020): https://doi.org/10.1172/JCI127483

Masiero, M. et al. Mol. Cancer Ther. 18, 2030–2042 (2019): https://doi.org/10.1158/1535-7163.MCT-18-1176

Jiang, Y. et al. Mol. Cancer Ther. 20, 1663–1671 (2021): https://doi.org/10.1158/1535-7163.MCT-20-085

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Stribbling, S.M., Ryan, A.J. The cell-line-derived subcutaneous tumor model in preclinical cancer research. Nat Protoc 17, 2108–2128 (2022). https://doi.org/10.1038/s41596-022-00709-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41596-022-00709-3

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer