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Analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection
The utility of cancer cell lines is affected by the similarity to endogenous tumour cells. Here we compare genomic data from 65 kidney-derived cell lines from the Cancer Cell Line Encyclopedia and the COSMIC Cell Lines Project to three renal cancer subtypes from The Cancer Genome Atlas: clear cell r...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5436135/ https://www.ncbi.nlm.nih.gov/pubmed/28489074 http://dx.doi.org/10.1038/ncomms15165 |
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author | Sinha, Rileen Winer, Andrew G. Chevinsky, Michael Jakubowski, Christopher Chen, Ying-Bei Dong, Yiyu Tickoo, Satish K. Reuter, Victor E. Russo, Paul Coleman, Jonathan A. Sander, Chris Hsieh, James J. Hakimi, A. Ari |
author_facet | Sinha, Rileen Winer, Andrew G. Chevinsky, Michael Jakubowski, Christopher Chen, Ying-Bei Dong, Yiyu Tickoo, Satish K. Reuter, Victor E. Russo, Paul Coleman, Jonathan A. Sander, Chris Hsieh, James J. Hakimi, A. Ari |
author_sort | Sinha, Rileen |
collection | PubMed |
description | The utility of cancer cell lines is affected by the similarity to endogenous tumour cells. Here we compare genomic data from 65 kidney-derived cell lines from the Cancer Cell Line Encyclopedia and the COSMIC Cell Lines Project to three renal cancer subtypes from The Cancer Genome Atlas: clear cell renal cell carcinoma (ccRCC, also known as kidney renal clear cell carcinoma), papillary (pRCC, also known as kidney papillary) and chromophobe (chRCC, also known as kidney chromophobe) renal cell carcinoma. Clustering copy number alterations shows that most cell lines resemble ccRCC, a few (including some often used as models of ccRCC) resemble pRCC, and none resemble chRCC. Human ccRCC tumours clustering with cell lines display clinical and genomic features of more aggressive disease, suggesting that cell lines best represent aggressive tumours. We stratify mutations and copy number alterations for important kidney cancer genes by the consistency between databases, and classify cell lines into established gene expression-based indolent and aggressive subtypes. Our results could aid investigators in analysing appropriate renal cancer cell lines. |
format | Online Article Text |
id | pubmed-5436135 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-54361352017-05-25 Analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection Sinha, Rileen Winer, Andrew G. Chevinsky, Michael Jakubowski, Christopher Chen, Ying-Bei Dong, Yiyu Tickoo, Satish K. Reuter, Victor E. Russo, Paul Coleman, Jonathan A. Sander, Chris Hsieh, James J. Hakimi, A. Ari Nat Commun Article The utility of cancer cell lines is affected by the similarity to endogenous tumour cells. Here we compare genomic data from 65 kidney-derived cell lines from the Cancer Cell Line Encyclopedia and the COSMIC Cell Lines Project to three renal cancer subtypes from The Cancer Genome Atlas: clear cell renal cell carcinoma (ccRCC, also known as kidney renal clear cell carcinoma), papillary (pRCC, also known as kidney papillary) and chromophobe (chRCC, also known as kidney chromophobe) renal cell carcinoma. Clustering copy number alterations shows that most cell lines resemble ccRCC, a few (including some often used as models of ccRCC) resemble pRCC, and none resemble chRCC. Human ccRCC tumours clustering with cell lines display clinical and genomic features of more aggressive disease, suggesting that cell lines best represent aggressive tumours. We stratify mutations and copy number alterations for important kidney cancer genes by the consistency between databases, and classify cell lines into established gene expression-based indolent and aggressive subtypes. Our results could aid investigators in analysing appropriate renal cancer cell lines. Nature Publishing Group 2017-05-10 /pmc/articles/PMC5436135/ /pubmed/28489074 http://dx.doi.org/10.1038/ncomms15165 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Sinha, Rileen Winer, Andrew G. Chevinsky, Michael Jakubowski, Christopher Chen, Ying-Bei Dong, Yiyu Tickoo, Satish K. Reuter, Victor E. Russo, Paul Coleman, Jonathan A. Sander, Chris Hsieh, James J. Hakimi, A. Ari Analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection |
title | Analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection |
title_full | Analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection |
title_fullStr | Analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection |
title_full_unstemmed | Analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection |
title_short | Analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection |
title_sort | analysis of renal cancer cell lines from two major resources enables genomics-guided cell line selection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5436135/ https://www.ncbi.nlm.nih.gov/pubmed/28489074 http://dx.doi.org/10.1038/ncomms15165 |
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