A Renewable Tissue Resource of Phenotypically Stable, Biologically and Ethnically Diverse, Patient-Derived Human Breast Cancer Xenograft Models
01 Aug 2013-Cancer Research (American Association for Cancer Research Inc.)-Vol. 73, Iss: 15, pp 4885-4897
TL;DR: Serially passaged xenografts show biologic consistency with the tumor of origin, are phenotypically stable across multiple transplant generations at the histologic, transcriptomic, proteomic, and genomic levels, and show comparable treatment responses as those observed clinically.
Abstract: Breast cancer research is hampered by difficulties in obtaining and studying primary human breast tissue, and by the lack of in vivo preclinical models that reflect patient tumor biology accurately. To overcome these limitations, we propagated a cohort of human breast tumors grown in the epithelium-free mammary fat pad of severe combined immunodeficient (SCID)/Beige and nonobese diabetic (NOD)/SCID/IL-2γ-receptor null (NSG) mice under a series of transplant conditions. Both models yielded stably transplantable xenografts at comparably high rates (∼21% and ∼19%, respectively). Of the conditions tested, xenograft take rate was highest in the presence of a low-dose estradiol pellet. Overall, 32 stably transplantable xenograft lines were established, representing 25 unique patients. Most tumors yielding xenografts were “triple-negative” [estrogen receptor (ER)−progesterone receptor (PR)−HER2+; n = 19]. However, we established lines from 3 ER−PR−HER2+ tumors, one ER+PR−HER2−, one ER+PR+HER2−, and one “triple-positive” (ER+PR+HER2+) tumor. Serially passaged xenografts show biologic consistency with the tumor of origin, are phenotypically stable across multiple transplant generations at the histologic, transcriptomic, proteomic, and genomic levels, and show comparable treatment responses as those observed clinically. Xenografts representing 12 patients, including 2 ER+ lines, showed metastasis to the mouse lung. These models thus serve as a renewable, quality-controlled tissue resource for preclinical studies investigating treatment response and metastasis. Cancer Res; 73(15); 4885–97. ©2013 AACR .
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TL;DR: The current state of the art in this field is summarized, including methodologic issues, available collections, practical applications, challenges and shortcomings, and future directions, and a European consortium of PDX models is introduced.
Abstract: Recently, there has been an increasing interest in the development and characterization of patient-derived tumor xenograft (PDX) models for cancer research. PDX models mostly retain the principal histologic and genetic characteristics of their donor tumor and remain stable across passages. These models have been shown to be predictive of clinical outcomes and are being used for preclinical drug evaluation, biomarker identification, biologic studies, and personalized medicine strategies. This article summarizes the current state of the art in this field, including methodologic issues, available collections, practical applications, challenges and shortcomings, and future directions, and introduces a European consortium of PDX models. Significance: PDX models are increasingly used in translational cancer research. These models are useful for drug screening, biomarker development, and the preclinical evaluation of personalized medicine strategies. This review provides a timely overview of the key characteristics of PDX models and a detailed discussion of future directions in the field. Cancer Discov; 4(9); 998–1013. ©2014 AACR .
1,309 citations
Cites background from "A Renewable Tissue Resource of Phen..."
...(16) HBC Conserved histopathology characteristics between donor and PDX models....
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...Of even greater relevance is the remarkable one-to-one concordance in studies that compare the individual donor patient response to conventional anticancer agents with that of his or her PDX (16, 21, 33, 34)....
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...4%, whereas, for reasons that are unclear, coimplantation with immortalized human fibroblasts decreased engraftment rate (16)....
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...In human breast cancer, for example, hormone receptor–negative tumors have a higher take rate than hormonesensitive tumors and are overrepresented in the existing PDX collections (16, 30, 34)....
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...In human breast cancer PDX models, several studies using gene expression profiles have shown that intrinsic breast cancer phenotypes are well represented and in concordance with the original tumors (16, 30, 31)....
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TL;DR: The results show that measurement of genomically defined clonal population dynamics will be highly informative for functional studies using patient-derived breast cancer xenoengraftment, and indicates that genomic aberrations can be reproducible determinants of evolutionary trajectories.
Abstract: Deep-genome and single-cell sequencing analyses of patient-derived breast cancer xenografts reveal extensive, dynamic and reproducible changes in intra-tumoral mutational clonal composition on engraftment and serial propagation. Xenograft transplantation of primary human cancer cells into mice provides valuable models in which to study mechanisms underlying tumorigenesis, drug response and resistance. This study demonstrates that clonal evolution resembling that seen in human tumours also occurs on engraftment and during subsequent passaging of breast tumours in immunodeficient mice. In addition, similar clonal expansion patterns emerge in independent grafts of the same starting tumour population, indicating that genomic aberrations can be reproducible determinants of evolutionary trajectories. These findings suggest that patient-derived xenografts may be useful for studying patient-specific tumour characteristics such as the response to drugs tailored to specific genomic alterations. Human cancers, including breast cancers, comprise clones differing in mutation content. Clones evolve dynamically in space and time following principles of Darwinian evolution1,2, underpinning important emergent features such as drug resistance and metastasis3,4,5,6,7. Human breast cancer xenoengraftment is used as a means of capturing and studying tumour biology, and breast tumour xenografts are generally assumed to be reasonable models of the originating tumours8,9,10. However, the consequences and reproducibility of engraftment and propagation on the genomic clonal architecture of tumours have not been systematically examined at single-cell resolution. Here we show, using deep-genome and single-cell sequencing methods, the clonal dynamics of initial engraftment and subsequent serial propagation of primary and metastatic human breast cancers in immunodeficient mice. In all 15 cases examined, clonal selection on engraftment was observed in both primary and metastatic breast tumours, varying in degree from extreme selective engraftment of minor (<5% of starting population) clones to moderate, polyclonal engraftment. Furthermore, ongoing clonal dynamics during serial passaging is a feature of tumours experiencing modest initial selection. Through single-cell sequencing, we show that major mutation clusters estimated from tumour population sequencing relate predictably to the most abundant clonal genotypes, even in clonally complex and rapidly evolving cases. Finally, we show that similar clonal expansion patterns can emerge in independent grafts of the same starting tumour population, indicating that genomic aberrations can be reproducible determinants of evolutionary trajectories. Our results show that measurement of genomically defined clonal population dynamics will be highly informative for functional studies using patient-derived breast cancer xenoengraftment.
567 citations
Additional excerpts
...T X1 X2 Cluster (n) 1 (86) 2 (16) 3 (10) 4 (9) 5 (5) SA534 (Prim....
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...Cluster (n) 1 (60) 2 (23) 3 (15) 4 (14) 5 (13) 6 (11) 7 (9) 8 (6) 9 (5) 10 (5) 11 (3) 12 (3) 13 (2) 14 (2) 15 (1) 16 (1) 17 (1) 18 (1) 19 (1) 20 (1) 0....
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...T X1 X2 X3 X4 X5 Cluster (n) 1 (60) 2 (23) 3 (15) 4 (14) 5 (13) 6 (11) 7 (9) 8 (6) 9 (5) 10 (5) 11 (3) 12 (3) 13 (2) 14 (2) SA501 (Prim....
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...Cluster (n) 1 (85) 2 (15) 3 (9) 4 (6) 5 (6) 6 (5) 7 (4) 8 (2) 9 (2) 10 (2) 11 (1)...
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...T X1 X2 X3 X4 X5 Cluster (n) 1 (60) 2 (23) 3 (15) 4 (14) 5 (13) 6 (11) 7 (9) 8 (6) 9 (5) 10 (5) 11 (3) 12 (3) 13 (2) 14 (2)...
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TL;DR: Deep sequenced PDX models are an important resource for the search for genome-forward treatment options and capture endocrine-drug-resistance etiologies that are not observed in standard cell lines.
561 citations
Cites background from "A Renewable Tissue Resource of Phen..."
...and recapitulate the chemotherapy response (DeRose et al., 2011; Fleming et al., 2010; Kabos et al., 2012; Marangoni et al., 2007; Zhang et al., 2013)....
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...…Revealed by Genomic Characterization of Breast-CancerDerived Xenografts, Cell Reports (2013), http://dx.doi.org/10.1016/j.celrep.2013.08.022 and recapitulate the chemotherapy response (DeRose et al., 2011; Fleming et al., 2010; Kabos et al., 2012; Marangoni et al., 2007; Zhang et al., 2013)....
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TL;DR: 3D- Cultured cells forming dense MCSs may be better than 2D-cultured cells in simulating important tumor characteristics in vivo, namely hypoxia, dormancy, anti-apoptotic features and their resulting drug resistance.
Abstract: It is becoming recognized that screening of oncology drugs on a platform using two-dimensionally (2D)-cultured cell lines is unable to precisely select clinically active drugs; therefore three-dimensional (3D)-culture systems are emerging and show potential for better simulating the in vivo tumor microenvironment. The purpose of this study was to reveal the differential effects of chemotherapeutic drugs between 2D- and 3D-cultures and to explore their underlying mechanisms. We evaluated differences between 2D- and 3D-cultured breast cancer cell lines by assessing drug sensitivity, oxygen status and expression of Ki-67 and caspases. Three cell lines (BT-549, BT-474 and T-47D) developed dense multicellular spheroids (MCSs) in 3D-culture, and showed greater resistance to paclitaxel and doxorubicin compared to the 2D-cultured cells. An additional three cell lines (MCF-7, HCC-1954, and MDA-MB‑231) developed only loose MCSs in 3D, and showed drug sensitivities similar to those found in the 2D-culture. Treatment with paclitaxel resulted in greater increases in cleaved-PARP expression in the 2D-culture compared with the 3D-culture, but only in cell lines forming dense 3D-MCSs, suggesting that MCS formation protected the cells from paclitaxel-induced apoptosis. Hypoxia was observed only in the dense 3D-MCSs. BT-549 had fewer cells positive for Ki-67 in 3D- than in 2D-culture, suggesting that the greater G0-dormant subpopulation was responsible for its drug resistance in the 3D-culture. BT-474 had a lower level of caspase-3 in the 3D- than in the 2D-culture, suggesting that the 3D-environment was anti-apoptotic. Finally, we compared staining for Ki-67 and caspases in the 2D- and 3D-primary‑cultured cells originating from a patient-derived xenograft (PDX), fresh PDX tumor, and the patient's original tumor; 2D-cultured cells showed greater proportions of Ki-67-positive and caspase-3-positive cells, in agreement with the view that 3D-primary culture better represents characteristics of tumors in vivo. In conclusion, 3D-cultured cells forming dense MCSs may be better than 2D-cultured cells in simulating important tumor characteristics in vivo, namely hypoxia, dormancy, anti-apoptotic features and their resulting drug resistance.
561 citations
Royal College of Surgeons in Ireland1, University of Manchester2, Netherlands Cancer Institute3, Autonomous University of Barcelona4, Katholieke Universiteit Leuven5, University of Glasgow6, University of Cambridge7, Masaryk University8, Utrecht University9, University of Lausanne10, Curie Institute11, University of Paris12, University of Colorado Denver13, Harvard University14, University of Groningen15, University of Oslo16, Catalan Institution for Research and Advanced Studies17, University of Turin18
TL;DR: Patient derived xenografts (PDXs) have emerged as an important platform to elucidate new treatments and biomarkers in oncology as mentioned in this paper, and the ability of PDX models to predict clinical outcomes is being improved through mouse humanization strategies and the implementation of co-clinical trials, within which patients and PDXs reciprocally inform therapeutic decisions.
Abstract: Patient-derived xenografts (PDXs) have emerged as an important platform to elucidate new treatments and biomarkers in oncology. PDX models are used to address clinically relevant questions, including the contribution of tumour heterogeneity to therapeutic responsiveness, the patterns of cancer evolutionary dynamics during tumour progression and under drug pressure, and the mechanisms of resistance to treatment. The ability of PDX models to predict clinical outcomes is being improved through mouse humanization strategies and the implementation of co-clinical trials, within which patients and PDXs reciprocally inform therapeutic decisions. This Opinion article discusses aspects of PDX modelling that are relevant to these questions and highlights the merits of shared PDX resources to advance cancer medicine from the perspective of EurOPDX, an international initiative devoted to PDX-based research.
506 citations
References
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TL;DR: The ability to prospectively identify tumorigenic cancer cells will facilitate the elucidation of pathways that regulate their growth and survival and strategies designed to target this population may lead to more effective therapies.
Abstract: Breast cancer is the most common malignancy in United States women, accounting for >40,000 deaths each year. These breast tumors are comprised of phenotypically diverse populations of breast cancer cells. Using a model in which human breast cancer cells were grown in immunocompromised mice, we found that only a minority of breast cancer cells had the ability to form new tumors. We were able to distinguish the tumorigenic (tumor initiating) from the nontumorigenic cancer cells based on cell surface marker expression. We prospectively identified and isolated the tumorigenic cells as CD44+CD24−/lowLineage− in eight of nine patients. As few as 100 cells with this phenotype were able to form tumors in mice, whereas tens of thousands of cells with alternate phenotypes failed to form tumors. The tumorigenic subpopulation could be serially passaged: each time cells within this population generated new tumors containing additional CD44+CD24−/lowLineage− tumorigenic cells as well as the phenotypically diverse mixed populations of nontumorigenic cells present in the initial tumor. The ability to prospectively identify tumorigenic cancer cells will facilitate the elucidation of pathways that regulate their growth and survival. Furthermore, because these cells drive tumor development, strategies designed to target this population may lead to more effective therapies.
10,058 citations
Additional excerpts
...6) 2 Scid/Beige þ 70 28/70 (40) 15/70 (21....
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TL;DR: D diagnosis by intrinsic subtype adds significant prognostic and predictive information to standard parameters for patients with breast cancer.
Abstract: Purpose To improve on current standards for breast cancer prognosis and prediction of chemotherapy benefit by developing a risk model that incorporates the gene expression–based “intrinsic” subtypes luminal A, luminal B, HER2-enriched, and basal-like. Methods A 50-gene subtype predictor was developed using microarray and quantitative reverse transcriptase polymerase chain reaction data from 189 prototype samples. Test sets from 761 patients (no systemic therapy) were evaluated for prognosis, and 133 patients were evaluated for prediction of pathologic complete response (pCR) to a taxane and anthracycline regimen. Results The intrinsic subtypes as discrete entities showed prognostic significance (P = 2.26E-12) and remained significant in multivariable analyses that incorporated standard parameters (estrogen receptor status, histologic grade, tumor size, and node status). A prognostic model for node-negative breast cancer was built using intrinsic subtype and clinical information. The C-index estimate for t...
3,913 citations
"A Renewable Tissue Resource of Phen..." refers background or methods in this paper
...Intrinsic subtype classification was conducted in the combined BCM xenograft and UNC337 dataset using the PAM50 algorithm (24) and the 9-Cell Line Claudin-low Predictor (25; Table 2 and Supplementary Table S3)....
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...Using approximately 1,900 intrinsic gene list (24), we Zhang et al....
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TL;DR: It is demonstrated that bone-marrow-derived human mesenchymal stem cells, when mixed with otherwise weakly metastatic human breast carcinoma cells, cause the cancer cells to increase their metastatic potency greatly when this cell mixture is introduced into a subcutaneous site and allowed to form a tumour xenograft.
Abstract: Mesenchymal stem cells have been recently described to localize to breast carcinomas, where they integrate into the tumour-associated stroma. However, the involvement of mesenchymal stem cells (or their derivatives) in tumour pathophysiology has not been addressed. Here, we demonstrate that bone-marrow-derived human mesenchymal stem cells, when mixed with otherwise weakly metastatic human breast carcinoma cells, cause the cancer cells to increase their metastatic potency greatly when this cell mixture is introduced into a subcutaneous site and allowed to form a tumour xenograft. The breast cancer cells stimulate de novo secretion of the chemokine CCL5 (also called RANTES) from mesenchymal stem cells, which then acts in a paracrine fashion on the cancer cells to enhance their motility, invasion and metastasis. This enhanced metastatic ability is reversible and is dependent on CCL5 signalling through the chemokine receptor CCR5. Collectively, these data demonstrate that the tumour microenvironment facilitates metastatic spread by eliciting reversible changes in the phenotype of cancer cells.
2,997 citations
TL;DR: It is confirmed that a prognostically relevant differentiation hierarchy exists across all breast cancers in which the claudin-low subtype most closely resembles the mammary epithelial stem cell.
Abstract: Introduction
In breast cancer, gene expression analyses have defined five tumor subtypes (luminal A, luminal B, HER2-enriched, basal-like and claudin-low), each of which has unique biologic and prognostic features. Here, we comprehensively characterize the recently identified claudin-low tumor subtype.
1,991 citations
"A Renewable Tissue Resource of Phen..." refers methods in this paper
...A, semiunsupervised hierarchical clustering of 31 BCMxenografts and 337 breast samples using the 1,900 intrinsic list (25, 26)....
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TL;DR: This study validates the "breast tumor intrinsic" subtype classification as an objective means of tumor classification that should be translated into a clinical assay for further retrospective and prospective validation.
Abstract: Validation of a novel gene expression signature in independent data sets is a critical step in the development of a clinically useful test for cancer patient risk-stratification. However, validation is often unconvincing because the size of the test set is typically small. To overcome this problem we used publicly available breast cancer gene expression data sets and a novel approach to data fusion, in order to validate a new breast tumor intrinsic list. A 105-tumor training set containing 26 sample pairs was used to derive a new breast tumor intrinsic gene list. This intrinsic list contained 1300 genes and a proliferation signature that was not present in previous breast intrinsic gene sets. We tested this list as a survival predictor on a data set of 311 tumors compiled from three independent microarray studies that were fused into a single data set using Distance Weighted Discrimination. When the new intrinsic gene set was used to hierarchically cluster this combined test set, tumors were grouped into LumA, LumB, Basal-like, HER2+/ER-, and Normal Breast-like tumor subtypes that we demonstrated in previous datasets. These subtypes were associated with significant differences in Relapse-Free and Overall Survival. Multivariate Cox analysis of the combined test set showed that the intrinsic subtype classifications added significant prognostic information that was independent of standard clinical predictors. From the combined test set, we developed an objective and unchanging classifier based upon five intrinsic subtype mean expression profiles (i.e. centroids), which is designed for single sample predictions (SSP). The SSP approach was applied to two additional independent data sets and consistently predicted survival in both systemically treated and untreated patient groups. This study validates the "breast tumor intrinsic" subtype classification as an objective means of tumor classification that should be translated into a clinical assay for further retrospective and prospective validation. In addition, our method of combining existing data sets can be used to robustly validate the potential clinical value of any new gene expression profile.
1,425 citations
"A Renewable Tissue Resource of Phen..." refers methods in this paper
...Xenografts were profiled as described previously using 244K human oligo microarrays (Agilent Technologies, Santa Clara, CA, USA) [23]....
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...To determine the tumor subtype that these xenograft lines best resemble, we performed global gene expression analyses using 244K human oligo microarrays [23] (Agilent Technologies)....
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