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The influence of cancer tissue sampling on the identification of cancer characteristics

Cancer tissue sampling affects the identification of cancer characteristics. We aimed to clarify the source of differentially expressed genes (DEGs) in macro-dissected cancer tissue and develop a robust prognostic signature against the effects of tissue sampling. For estrogen receptor (ER)+ breast c...

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Autores principales: Xu, Hui, Guo, Xin, Sun, Qiang, Zhang, Mengmeng, Qi, Lishuang, Li, Yang, Chen, Libin, Gu, Yunyan, Guo, Zheng, Zhao, Wenyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4614546/
https://www.ncbi.nlm.nih.gov/pubmed/26490514
http://dx.doi.org/10.1038/srep15474
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author Xu, Hui
Guo, Xin
Sun, Qiang
Zhang, Mengmeng
Qi, Lishuang
Li, Yang
Chen, Libin
Gu, Yunyan
Guo, Zheng
Zhao, Wenyuan
author_facet Xu, Hui
Guo, Xin
Sun, Qiang
Zhang, Mengmeng
Qi, Lishuang
Li, Yang
Chen, Libin
Gu, Yunyan
Guo, Zheng
Zhao, Wenyuan
author_sort Xu, Hui
collection PubMed
description Cancer tissue sampling affects the identification of cancer characteristics. We aimed to clarify the source of differentially expressed genes (DEGs) in macro-dissected cancer tissue and develop a robust prognostic signature against the effects of tissue sampling. For estrogen receptor (ER)+ breast cancer patients, we identified DEGs in macro-dissected cancer tissues, malignant epithelial cells and stromal cells, defined as Macro-Dissected-DEGs, Epithelial-DEGs and Stromal-DEGs, respectively. Comparing Epithelial-DEGs to Stromal-DEGs (false discovery rate (FDR) < 10%), 86% of the overlapping genes exhibited consistent dysregulation (defined as Consistent-DEGs), and the other 14% of genes were dysregulated inconsistently (defined as Inconsistent-DEGs). The consistency score of dysregulation directions between Macro-Dissected-DEGs and Consistent-DEGs was 91% (P-value < 2.2 × 10(−16), binomial test), whereas the score was only 52% between Macro-Dissected-DEGs and Inconsistent-DEGs (P-value = 0.9, binomial test). Among the gene ontology (GO) terms significantly enriched in Macro-Dissected-DEGs (FDR < 10%), 18 immune-related terms were enriched in Inconsistent-DEGs. DEGs associated with proliferation could reflect common changes of malignant epithelial and stromal cells; DEGs associated with immune functions are sensitive to the percentage of malignant epithelial cells in macro-dissected tissues. A prognostic signature which was insensitive to the cellular composition of macro-dissected tissues was developed and validated for ER+ breast patients.
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spelling pubmed-46145462015-10-29 The influence of cancer tissue sampling on the identification of cancer characteristics Xu, Hui Guo, Xin Sun, Qiang Zhang, Mengmeng Qi, Lishuang Li, Yang Chen, Libin Gu, Yunyan Guo, Zheng Zhao, Wenyuan Sci Rep Article Cancer tissue sampling affects the identification of cancer characteristics. We aimed to clarify the source of differentially expressed genes (DEGs) in macro-dissected cancer tissue and develop a robust prognostic signature against the effects of tissue sampling. For estrogen receptor (ER)+ breast cancer patients, we identified DEGs in macro-dissected cancer tissues, malignant epithelial cells and stromal cells, defined as Macro-Dissected-DEGs, Epithelial-DEGs and Stromal-DEGs, respectively. Comparing Epithelial-DEGs to Stromal-DEGs (false discovery rate (FDR) < 10%), 86% of the overlapping genes exhibited consistent dysregulation (defined as Consistent-DEGs), and the other 14% of genes were dysregulated inconsistently (defined as Inconsistent-DEGs). The consistency score of dysregulation directions between Macro-Dissected-DEGs and Consistent-DEGs was 91% (P-value < 2.2 × 10(−16), binomial test), whereas the score was only 52% between Macro-Dissected-DEGs and Inconsistent-DEGs (P-value = 0.9, binomial test). Among the gene ontology (GO) terms significantly enriched in Macro-Dissected-DEGs (FDR < 10%), 18 immune-related terms were enriched in Inconsistent-DEGs. DEGs associated with proliferation could reflect common changes of malignant epithelial and stromal cells; DEGs associated with immune functions are sensitive to the percentage of malignant epithelial cells in macro-dissected tissues. A prognostic signature which was insensitive to the cellular composition of macro-dissected tissues was developed and validated for ER+ breast patients. Nature Publishing Group 2015-10-22 /pmc/articles/PMC4614546/ /pubmed/26490514 http://dx.doi.org/10.1038/srep15474 Text en Copyright © 2015, Macmillan Publishers Limited 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
Xu, Hui
Guo, Xin
Sun, Qiang
Zhang, Mengmeng
Qi, Lishuang
Li, Yang
Chen, Libin
Gu, Yunyan
Guo, Zheng
Zhao, Wenyuan
The influence of cancer tissue sampling on the identification of cancer characteristics
title The influence of cancer tissue sampling on the identification of cancer characteristics
title_full The influence of cancer tissue sampling on the identification of cancer characteristics
title_fullStr The influence of cancer tissue sampling on the identification of cancer characteristics
title_full_unstemmed The influence of cancer tissue sampling on the identification of cancer characteristics
title_short The influence of cancer tissue sampling on the identification of cancer characteristics
title_sort influence of cancer tissue sampling on the identification of cancer characteristics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4614546/
https://www.ncbi.nlm.nih.gov/pubmed/26490514
http://dx.doi.org/10.1038/srep15474
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