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Title: A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening

Abstract

Accurate patient-derived models of cancer are needed for profiling the disease and for testing therapeutics. These models must not only be accurate, but also suitable for high-throughput screening and analysis. Here we compare two derivative cancer models, microtumors and spheroids, to the gold standard model of patient-derived orthotopic xenografts (PDX) in glioblastoma multiforme (GBM). To compare these models, we constructed a custom NanoString panel of 350 genes relevant to GBM biology. This custom assay includes 16 GBM-specific gene signatures including a novel GBM subtyping signature. We profiled 11 GBM-PDX with matched orthotopic cells, derived microtumors, and derived spheroids using the custom NanoString assay. In parallel, these derivative models underwent drug sensitivity screening. We found that expression of certain genes were dependent on the cancer model while others were model-independent. These model-independent genes can be used in profiling tumor-specific biology and in gauging therapeutic response. It remains to be seen whether or not cancer model-specific genes may be directly or indirectly, through changes to tumor microenvironment, manipulated to improve the concordance of in vitro derivative models with in vivo models yielding better prediction of therapeutic response.

Authors:
ORCiD logo; ; ; ORCiD logo; ; ORCiD logo
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1564437
Grant/Contract Number:  
N44CM47014-11
Resource Type:
Published Article
Journal Name:
Cells
Additional Journal Information:
Journal Name: Cells Journal Volume: 8 Journal Issue: 7; Journal ID: ISSN 2073-4409
Publisher:
MDPI AG
Country of Publication:
Country unknown/Code not available
Language:
English

Citation Formats

Stackhouse, Christian T., Rowland, James R., Shevin, Rachael S., Singh, Raj, Gillespie, G. Yancey, and Willey, Christopher D. A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening. Country unknown/Code not available: N. p., 2019. Web. doi:10.3390/cells8070702.
Stackhouse, Christian T., Rowland, James R., Shevin, Rachael S., Singh, Raj, Gillespie, G. Yancey, & Willey, Christopher D. A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening. Country unknown/Code not available. doi:10.3390/cells8070702.
Stackhouse, Christian T., Rowland, James R., Shevin, Rachael S., Singh, Raj, Gillespie, G. Yancey, and Willey, Christopher D. Thu . "A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening". Country unknown/Code not available. doi:10.3390/cells8070702.
@article{osti_1564437,
title = {A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening},
author = {Stackhouse, Christian T. and Rowland, James R. and Shevin, Rachael S. and Singh, Raj and Gillespie, G. Yancey and Willey, Christopher D.},
abstractNote = {Accurate patient-derived models of cancer are needed for profiling the disease and for testing therapeutics. These models must not only be accurate, but also suitable for high-throughput screening and analysis. Here we compare two derivative cancer models, microtumors and spheroids, to the gold standard model of patient-derived orthotopic xenografts (PDX) in glioblastoma multiforme (GBM). To compare these models, we constructed a custom NanoString panel of 350 genes relevant to GBM biology. This custom assay includes 16 GBM-specific gene signatures including a novel GBM subtyping signature. We profiled 11 GBM-PDX with matched orthotopic cells, derived microtumors, and derived spheroids using the custom NanoString assay. In parallel, these derivative models underwent drug sensitivity screening. We found that expression of certain genes were dependent on the cancer model while others were model-independent. These model-independent genes can be used in profiling tumor-specific biology and in gauging therapeutic response. It remains to be seen whether or not cancer model-specific genes may be directly or indirectly, through changes to tumor microenvironment, manipulated to improve the concordance of in vitro derivative models with in vivo models yielding better prediction of therapeutic response.},
doi = {10.3390/cells8070702},
journal = {Cells},
number = 7,
volume = 8,
place = {Country unknown/Code not available},
year = {2019},
month = {7}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.3390/cells8070702

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