Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Dec 20:17:122.
doi: 10.1186/s12935-017-0497-4. eCollection 2017.

Establishment and evaluation of four different types of patient-derived xenograft models

Affiliations

Establishment and evaluation of four different types of patient-derived xenograft models

Xiaoqian Ji et al. Cancer Cell Int. .

Abstract

Background: Patient-derived xenografts (PDX) have a biologically stable in tumor architecture, drug responsiveness, mutational status and global gene-expression patterns. Numerous PDX models have been established to date, however their thorough characterization regarding the tumor formation and rates of tumor growth in the established models remains a challenging task. Our study aimed to provide more detailed information for establishing the PDX models successfully and effectively.

Methods: We transplanted four different types of solid tumors from 108 Chinese patients, including 21 glioblastoma (GBM), 11 lung cancers (LC), 54 gastric cancers (GC) and 21 colorectal cancers (CRC), and took tumor tissues passaged for three successive generations. Here we report the rate of tumor formation, tumor-forming times, tumor growth curves and mortality of mice in PDX model. We also report H&E staining and immunohistochemistry for HLA-A, CD45, Ki67, GFAP, and CEA protein expression between patient cancer tissues and PDX models.

Results: Tumor formation rate increased significantly in subsequent tumor generations. Also, the survival rates of GC and CRC were remarkably higher than GBM and LC. As for the time required for the formation of tumors, which reflects the tumor growth rate, indicated that tumor growth rate always increased as the generation number increased. The tumor growth curves also illustrate this law. Similarly, the survival rate of PDX mice gradually improved with the increased generation number in GC and CRC. And generally, there was more proliferation (Ki67+) in the PDX models than in the patient tumors, which was in accordance with the results of tumor growth rate. The histological findings confirm similar histological architecture and degrees of differentiation between patient cancer tissues and PDX models with statistical analysis by GraphPad Prism 5.0.

Conclusion: We established four different types of PDX models successfully, and our results add to the current understanding of the establishment of PDX models and may contribute to the extension of application of different types of PDX models.

Keywords: Colorectal cancer (CRC); Gastric cancer (GC); Glioblastoma (GBM); Lung cancer (LC); Patient derived xenograft (PDX).

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Patient-derived xenograft (PDX) mice model. a Schematic outline of the generation of four different cancer PDXs. b Tumor transplanting site. c The distribution of tumor cases. d The tumor formation rate of F0. e The tumor formation rate of F1–F3. f The survival rate of F1
Fig. 2
Fig. 2
Time of tumor growth. a Time of GBM growth. b Time of LC growth. c Time of GC growth. d Time of CRC growth
Fig. 3
Fig. 3
Histopathological comparison of patient tissue with transplanted tumors and the tumor growth curves of GBM-16. a H&E and immunohistochemistry staining of HLA-A, CD45, Ki67, GFAP on (F0) patient tumor and derived (F1–F3) transplanted tumors. b The tumor growth curve of GBM-16. c, d, f The positive area of HLA-A, CD45 and GFAP was quantified. e Quantification of cells positive for Ki67. *p < 0.05, ****p < 0.0001 vs F0
Fig. 4
Fig. 4
Histopathological comparison of patient tissues with transplanted tumors and the tumor growth curves of LC-9. a H&E and immunohistochemistry staining of HLA-A, CD45, Ki67, CEA on (F0) patient tumor and derived (F1-F3) transplanted tumors. b The tumor growth curve of LC-9. c, d, f Areas positive for HLA-A, CD45, CEA were quantified. e Quantification of cells positive for Ki67
Fig. 5
Fig. 5
Histopathological comparison of patient tissue with transplanted tumor tissues and the tumor growth curves of GC-28. a H&E and immunohistochemistry staining for HLA-A, CD45, Ki67 on (F0) patient tumor and derived (F1-F3) transplanted tumors. b The tumor growth curves of GC-28. c, d The areas positive for HLA-A, CD45 was quantified. e Cells positive for Ki67 were quantified. *p < 0.05, **p < 0.01, ****p < 0.0001 vs F0
Fig. 6
Fig. 6
Histopathological comparison of patient tissue with transplanted tumors and the tumor growth curves of CRC-12. a H&E and immunohistochemistry staining for HLA-A, CD45, Ki67 in patient tumor (F0) and derived (F1–F3) transplanted tumors. b Tumor growth curve of CRC-12. c, d HLA-A positive areas and, CD45 positive areas were quantified. e Cells positive for Ki67 were quantified. ****p < 0.0001 vs F0

Similar articles

Cited by

References

    1. Jin K, Teng L, Shen Y, et al. Patient-derived human tumour tissue xenografts in immunodeficient mice: a systematic review. Clin Transl Oncol. 2010;12:473–480. doi: 10.1007/s12094-010-0540-6. - DOI - PubMed
    1. Tentler JJ, Tan AC, Weekes CD, et al. Patient-derived tumour xenografts as models for oncology drug development. Nat Rev Clin Oncol. 2012;9:338–350. doi: 10.1038/nrclinonc.2012.61. - DOI - PMC - PubMed
    1. Daniel VC, Marchionni L, Hierman JS, et al. A primary xenograft model of small-cell lung cancer reveals irreversible changes in gene expression imposed by culture in vitro. Cancer Res. 2009;69:3364–3373. doi: 10.1158/0008-5472.CAN-08-4210. - DOI - PMC - PubMed
    1. Herrmann D, Conway JR, Vennin C, et al. Three-dimensional cancer models mimic cell-matrix interactions in the tumour microenvironment. Carcinogenesis. 2014;35:1671–1679. doi: 10.1093/carcin/bgu108. - DOI - PubMed
    1. Mishra DK, Creighton CJ, Zhang Y, et al. Gene expression profile of A549 cells from tissue of 4D model predicts poor prognosis in lung cancer patients. Int J Cancer. 2014;134:789–798. doi: 10.1002/ijc.28428. - DOI - PMC - PubMed