Gene expression profiling of 49 human tumor xenografts from in vitro culture through multiple in vivo passages - strategies for data mining in support of therapeutic studies

Hollingshead, Melinda G.; Stockwin, Luke H.; Alcoser, Sergio Y.; Newton, Dianne L.; Orsburn, Benjamin C.; Bonomi, Carrie; Borgel, Suzanne; Divelbiss, Raymond; Dougherty, Kelly; Hager, Eric; Holbeck, Susan L.; Kaur, Gurmeet; Kimmel, David J; Kunkel, Mark W.; Millione, Angelena; Mullendore, Michael E.; Stotler, Howard; Collins, Jerry M.

doi:10.1186/1471-2164-15-393

Cited by 33 publications

(33 citation statements)

References 35 publications

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“…Indeed, previous data suggest that altered genomic signatures due to tumor cell plasticity and/or harsh clonal selection lead to unpredictable behavior of tumor cell lines after being transplanted into mice (Creighton et al, 2003; He et al, 2010; Hollingshead et al, 2014; Shin et al, 2013). Here, we used RNA sequencing to examine the stability of key transcriptomic properties between the parental OS cell lines and their corresponding tumor xenografts.…”

Section: Resultsmentioning

confidence: 99%

Heterotypic models of osteosarcoma recapitulate tumor heterogeneity and biological behavior

Scott

Tomiyasu

Garbe³

et al. 2016

Disease Models &Amp; Mechanisms

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Osteosarcoma (OS) is a heterogeneous and rare disease with a disproportionate impact because it mainly affects children and adolescents. Lamentably, more than half of patients with OS succumb to metastatic disease. Clarification of the etiology of the disease, development of better strategies to manage progression, and methods to guide personalized treatments are among the unmet health needs for OS patients. Progress in managing the disease has been hindered by the extreme heterogeneity of OS; thus, better models that accurately recapitulate the natural heterogeneity of the disease are needed. For this study, we used cell lines derived from two spontaneous canine OS tumors with distinctly different biological behavior (OS-1 and OS-2) for heterotypic in vivo modeling that recapitulates the heterogeneous biology and behavior of this disease. Both cell lines demonstrated stability of the transcriptome when grown as orthotopic xenografts in athymic nude mice. Consistent with the behavior of the original tumors, OS-2 xenografts grew more rapidly at the primary site and had greater propensity to disseminate to lung and establish microscopic metastasis. Moreover, OS-2 promoted formation of a different tumor-associated stromal environment than OS-1 xenografts. OS-2-derived tumors comprised a larger percentage of the xenograft tumors than OS-1-derived tumors. In addition, a robust pro-inflammatory population dominated the stromal cell infiltrates in OS-2 xenografts, whereas a mesenchymal population with a gene signature reflecting myogenic signaling dominated those in the OS-1 xenografts. Our studies show that canine OS cell lines maintain intrinsic features of the tumors from which they were derived and recapitulate the heterogeneous biology and behavior of bone cancer in mouse models. This system provides a resource to understand essential interactions between tumor cells and the stromal environment that drive the progression and metastatic propensity of OS.

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Section: Resultsmentioning

confidence: 99%

Heterotypic models of osteosarcoma recapitulate tumor heterogeneity and biological behavior

Scott

Tomiyasu

Garbe³

et al. 2016

Disease Models &Amp; Mechanisms

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“…Gene expression microarray data from the National Cancer Institute MicroXeno project were downloaded from the GEO repository (http://www.ncbi.nlm.nih.gov/geo), under accession number GSE 48433 (ref 39 ). Data were processed as described above.…”

Section: Methodsmentioning

confidence: 99%

Patient-derived xenografts undergo murine-specific tumor evolution

Ben‐David

Tseng

et al. 2017

Preprint

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Patient-derived xenografts (PDXs) have become a prominent model for studying human cancer in vivo. The underlying assumption is that PDXs faithfully represent the genomic features of primary tumors, retaining their molecular characteristics throughout propagation. However, the genomic stability of PDXs during passaging has not yet been evaluated systematically. Here we monitored the dynamics of copy number alterations (CNAs) in 1,110 PDX samples across 24 cancer types. We found that new CNAs accumulated quickly, such that within four passages an average of 12% of the genome was affected by newly acquired CNAs. Selection for preexisting minor clones was a major contributor to these changes, leading to both gains and losses of CNAs. The rate of CNA acquisition in PDX models was correlated with the extent of both aneuploidy and genetic heterogeneity observed in primary tumors of the same tissue. However, the specific CNAs acquired during PDX passaging differed from those acquired during tumor evolution in patients, suggesting that PDX tumors are subjected to distinct selection pressures compared to those that exist in human hosts. Specifically, several recurrent CNAs observed in primary tumors gradually disappeared in PDXs, indicating that events undergoing positive selection in humans can become dispensable during propagation in mice. Finally, we found that the genomic stability of PDX models also affected their responses to chemotherapy and targeted drugs. Our findings thus highlight the need to couple the timing of PDX molecular characterization to that of drug testing experiments. These results suggest that while PDX models are powerful tools, they should be used with caution.peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/167767 doi: bioRxiv preprint first posted online Jul. 24, 2017; Cancer research relies on interrogating model systems that mirror the biology of human tumors. Cell lines cultured from human tumors have been the workhorse of cancer research for many years, but the marked differences between the in vitro cell line environment and the in vivo tumor environment raise concerns that cell lines may not be fully representative of human tumors. Recently, there have been increasing efforts to utilize patient-derived xenografts (PDXs) as models to study drug response [1][2][3][4] . These in vivo models are assumed to capture the cellular and molecular characteristics of human cancer better than simpler cancer model systems such as established cell lines grown in vitro and in vivo as xenografts 1,2 . The value of PDX models for cancer research thus depends on their faithfulness in representing the biological features of primary tumors.There are reasons to suspect PDX models might deviate from human tumor biology, as they must be serially transplanted for multiple generations in the murine microenvironment. Therefore, it is important to assess whether PDXs retain their...

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“…Often more aggressive tumours with high proliferation rates are easier to propagate, resulting in a population of PDX mouse models skewed towards these phenotypes ( Zhao et al, 2012 ). Past issues with clonal selection and genetic drift have been largely overcome by the use of low-passage number grafts ( Hollingshead et al, 2014 ). However, this means that primary engraftment is carried out more often, requiring more animals as well as increased amounts of human tissue, which may be wasted if tumours fail to engraft.…”

Section: The Problem With Pdx Micementioning

confidence: 99%

Human tissue models in cancer research: looking beyond the mouse

Jackson

Thomas

2017

Disease Models &Amp; Mechanisms

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Mouse models, including patient-derived xenograft mice, are widely used to address questions in cancer research. However, there are documented flaws in these models that can result in the misrepresentation of human tumour biology and limit the suitability of the model for translational research. A coordinated effort to promote the more widespread development and use of ‘non-animal human tissue’ models could provide a clinically relevant platform for many cancer studies, maximising the opportunities presented by human tissue resources such as biobanks. A number of key factors limit the wide adoption of non-animal human tissue models in cancer research, including deficiencies in the infrastructure and the technical tools required to collect, transport, store and maintain human tissue for lab use. Another obstacle is the long-standing cultural reliance on animal models, which can make researchers resistant to change, often because of concerns about historical data compatibility and losing ground in a competitive environment while new approaches are embedded in lab practice. There are a wide range of initiatives that aim to address these issues by facilitating data sharing and promoting collaborations between organisations and researchers who work with human tissue. The importance of coordinating biobanks and introducing quality standards is gaining momentum. There is an exciting opportunity to transform cancer drug discovery by optimising the use of human tissue and reducing the reliance on potentially less predictive animal models.

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Gene expression profiling of 49 human tumor xenografts from in vitro culture through multiple in vivo passages - strategies for data mining in support of therapeutic studies

Cited by 33 publications

References 35 publications

Heterotypic models of osteosarcoma recapitulate tumor heterogeneity and biological behavior

Heterotypic models of osteosarcoma recapitulate tumor heterogeneity and biological behavior

Patient-derived xenografts undergo murine-specific tumor evolution

Human tissue models in cancer research: looking beyond the mouse

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