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. 2012 Jan 16;14(1):R11.
doi: 10.1186/bcr3095.

Molecular profiling of patient-derived breast cancer xenografts

Fabien Reyal  1 , Charlotte Guyader, Charles Decraene, Carlo Lucchesi, Nathalie Auger, Franck Assayag, Ludmilla De Plater, David Gentien, Marie-France Poupon, Paul Cottu, Patricia De Cremoux, Pierre Gestraud, Anne Vincent-Salomon, Jean-Jacques Fontaine, Sergio Roman-Roman, Olivier Delattre, Didier Decaudin, Elisabetta Marangoni
Affiliations

Molecular profiling of patient-derived breast cancer xenografts

Fabien Reyal et al. Breast Cancer Res. .

Abstract

Introduction: Identification of new therapeutic agents for breast cancer (BC) requires preclinical models that reproduce the molecular characteristics of their respective clinical tumors. In this work, we analyzed the genomic and gene expression profiles of human BC xenografts and the corresponding patient tumors. VSports手机版.

Methods: Eighteen BC xenografts were obtained by grafting tumor fragments from patients into Swiss nude mice. Molecular characterization of patient tumors and xenografts was performed by DNA copy number analysis and gene expression analysis using Affymetrix Microarrays. V体育安卓版.

Results: Comparison analysis showed that 14/18 pairs of tumors shared more than 56% of copy number alterations (CNA). Unsupervised hierarchical clustering analysis showed that 16/18 pairs segregated together, confirming the similarity between tumor pairs. Analysis of recurrent CNA changes between patient tumors and xenografts showed losses in 176 chromosomal regions and gains in 202 chromosomal regions. Gene expression profile analysis showed that less than 5% of genes had recurrent variations between patient tumors and their respective xenografts; these genes largely corresponded to human stromal compartment genes. Finally, analysis of different passages of the same tumor showed that sequential mouse-to-mouse tumor grafts did not affect genomic rearrangements or gene expression profiles, suggesting genetic stability of these models over time. V体育ios版.

Conclusions: This panel of human BC xenografts maintains the overall genomic and gene expression profile of the corresponding patient tumors and remains stable throughout sequential in vivo generations. The observed genomic profile and gene expression differences appear to be due to the loss of human stromal genes. These xenografts, therefore, represent a validated model for preclinical investigation of new therapeutic agents. VSports最新版本.

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V体育官网入口 - Figures

Figure 1
Figure 1
Histology and IHC analysis of primary tumors and xenografts. Representative hematoxylin-eosin or hematoxylin-eosin-saffron stained sections of patient tumors and xenografts. A, luminal tumor HBC(x)-3. B, lobular tumor HBCx-19. C, triple-negative tumor HBC(x)-12A. D, HER2+ tumor HBCx-5. E, triple-negative tumor HBC(x)-10. F, triple-negative tumor HBC(x)-8. HBC, human breast cancer, HBC-n, HBC primary tumor n, HBCx-n, HBC xenograft tumor n, HER2+, human epidermal growth factor receptor 2 positive, IHC, immunohistochemistry.
Figure 2
Figure 2
Array CGH profiles of patient tumors (top) and xenografts (bottom) compared with normal DNA. Recurrence of copy number alterations is plotted on the y-axis and each probe is aligned along the x-axis in chromosomal order. Loss, gain or amplification of gene copy numbers are depicted in green, red and blue, respectively. A, array CGH profile of a luminal tumor. B, array CGH profile of a triple-negative tumor. CGH, comparative genomic hybridization, HBC, human breast cancer, HBC-n, HBC primary tumor n, HBCx-n, HBC xenograft tumor n.
Figure 3
Figure 3
Clustering of array CGH data set. The length of each horizontal dendrogram arm indicates the degree of correlation between the various specimens, ranging from 0% to 100% correlation. The shorter the dendrogram arm, the greater the degree of correlation. A, unsupervised hierarchical clustering analysis of copy number alterations on the whole sample set (18 pairs of primary tumors and corresponding xenografts). B, hierarchical clustering analysis, including the metastasis-derived xenografts HBCx-13B and HBCx-12B (indicated with circles). CGH, comparative genomic hybridization, HBC, human breast cancer, HBC-n, HBC primary tumor n, HBCx-n, HBC xenograft tumor n, HER2+, human epidermal growth factor receptor 2 positive. Red, luminal tumors; black, triple-negative tumors; green, HER2+ tumors.
Figure 4
Figure 4
Stability of CGH profiles between primary and metastasis profiles and throughout successive xenograft generations. A, aCGH profile of the HBCx-13 tumors derived from a patient's primary breast tumor (upper), breast tumor-derived xenograft (middle), and axillary metastasis-derived xenograft (bottom). B, details of the aCGH profile of chromosome 17 amplicon (containing the HER2 oncogene amplification and chromosome 8 amplicon. C, aCGH profiles of the luminal HBC-21 patient tumor and xenografts from different in vivo tumor passages (p6 corresponding to a time lapse of 30 months after the first tumor engraftment). aCGH, array comparative genomic hybridization; HBC, human breast cancer; HBC-n, HBC primary tumor n; HBCx-n, HBC xenograft tumor n; HER2, human epidermal growth factor receptor 2.
Figure 5
Figure 5
Representation of differences in CNA between patient tumors and xenografts. A, frequencies of genome copy number gains and losses plotted as a function of genome location in the patient tumors (left) and xenografts (right). Frequencies are based on GNL status and colors are calculated from the proportions of profiles without missing values. B, Frequency distributions plots of unchanged, positive and negative GNL differences. C, Frequency of CNA alterations distributed along chromosomes. Frequencies were calculated as the difference between patient tumor and xenograft GNLs. Negative frequencies represent DNA losses, while positive frequencies represent gains in xenografts. Only segments present in 10 or more pairs are shown (n = 992). D, Distribution of recurrent CNA gains (lower figure) and losses (upper figure) along chromosomes (frequency calculated for GNL differences occurring in at least 30% of pairs, n = 202 and 176, respectively). CAN, copy number alteration; FrAGL, Frequency of Amplicon, Gain and Loss; GNL, gain, normal, loss.
Figure 6
Figure 6
Gene expression analysis by Affymetrix GeneChip probe arrays. A, Variation of gene expression between the primary HBC-12B tumor and the corresponding xenograft. Scatter plot representing the gene expression of 29,683 probe sets (primary tumor versus xenograft p3). red dot, probe sets with high residual values. B, Variation of gene expression between xenograft at passage 3 and passage 6. C, Number of overexpressed (red) and underexpressed (green) genes between patient tumor/xenograft pairs HBC, human breast cancer; HBC-n, HBC primary tumor n; HBCx-n, HBC xenograft tumor n.
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References

    1. Kamangar F, Dores GM, Anderson WF. Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world. J Clin Oncol. 2006;24:2137–2150. doi: 10.1200/JCO.2005.05.2308. - DOI - PubMed
    1. Perou CM, Sørlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, Fluge O, Pergamenschikov A, Williams C, Zhu SX, Lønning PE, Børresen-Dale AL, Brown PO, Botstein D. Molecular portraits of human breast tumours. Nature. 2000;406:747–752. doi: 10.1038/35021093. - DOI (VSports app下载) - PubMed
    1. Sørlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, Eystein Lønning P, Børresen-Dale AL. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA. 2001;98:10869–10874. doi: 10.1073/pnas.191367098. - VSports - DOI - PMC - PubMed
    1. Garber K. From human to mouse and back: 'tumorgraft' models surge in popularity. J Natl Cancer Inst. 2009;101:6–8. - PubMed
    1. Fiebig HH, Maier A, Burger AM. Clonogenic assay with established human tumour xenografts: correlation of in vitro to in vivo activity as a basis for anticancer drug discovery. Eur J Cancer. 2004;40:802–820. doi: 10.1016/j.ejca.2004.01.009. - DOI - PubMed

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