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A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening
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 stan...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678976/ https://www.ncbi.nlm.nih.gov/pubmed/31336733 http://dx.doi.org/10.3390/cells8070702 |
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author | Stackhouse, Christian T. Rowland, James R. Shevin, Rachael S. Singh, Raj Gillespie, G. Yancey Willey, Christopher D. |
author_facet | Stackhouse, Christian T. Rowland, James R. Shevin, Rachael S. Singh, Raj Gillespie, G. Yancey Willey, Christopher D. |
author_sort | Stackhouse, Christian T. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6678976 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66789762019-08-19 A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening Stackhouse, Christian T. Rowland, James R. Shevin, Rachael S. Singh, Raj Gillespie, G. Yancey Willey, Christopher D. Cells Article 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. MDPI 2019-07-11 /pmc/articles/PMC6678976/ /pubmed/31336733 http://dx.doi.org/10.3390/cells8070702 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article 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 |
title | A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening |
title_full | A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening |
title_fullStr | A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening |
title_full_unstemmed | A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening |
title_short | A Novel Assay for Profiling GBM Cancer Model Heterogeneity and Drug Screening |
title_sort | novel assay for profiling gbm cancer model heterogeneity and drug screening |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678976/ https://www.ncbi.nlm.nih.gov/pubmed/31336733 http://dx.doi.org/10.3390/cells8070702 |
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