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从表达数据推断肿瘤纯度以及基质和免疫细胞的混合物。

Inferring tumour purity and stromal and immune cell admixture from expression data.

机构信息

1] Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Centre, Houston, Texas 77030, USA [2] Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8510, Japan.

出版信息

Nat Commun. 2013;4:2612. doi: 10.1038/ncomms3612.

DOI:10.1038/ncomms3612
PMID:24113773
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3826632/
Abstract

Infiltrating stromal and immune cells form the major fraction of normal cells in tumour tissue and not only perturb the tumour signal in molecular studies but also have an important role in cancer biology. Here we describe 'Estimation of STromal and Immune cells in MAlignant Tumours using Expression data' (ESTIMATE)--a method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumour samples. ESTIMATE scores correlate with DNA copy number-based tumour purity across samples from 11 different tumour types, profiled on Agilent, Affymetrix platforms or based on RNA sequencing and available through The Cancer Genome Atlas. The prediction accuracy is further corroborated using 3,809 transcriptional profiles available elsewhere in the public domain. The ESTIMATE method allows consideration of tumour-associated normal cells in genomic and transcriptomic studies. An R-library is available on https://sourceforge.net/projects/estimateproject/.

摘要

浸润性基质和免疫细胞构成肿瘤组织中正常细胞的主要部分，它们不仅在分子研究中扰乱肿瘤信号，而且在癌症生物学中具有重要作用。在这里，我们描述了“使用表达数据估计恶性肿瘤中的基质和免疫细胞”（ESTIMATE）——一种使用基因表达特征推断肿瘤样本中基质和免疫细胞分数的方法。ESTIMATE 评分与来自 11 种不同肿瘤类型的样本的基于 DNA 拷贝数的肿瘤纯度相关，这些样本在安捷伦、Affymetrix 平台上进行了分析，或者基于 RNA 测序，并可通过癌症基因组图谱获得。通过使用其他公共领域提供的 3809 个转录谱进一步证实了预测的准确性。ESTIMATE 方法允许在基因组和转录组研究中考虑与肿瘤相关的正常细胞。一个 R 库可在 https://sourceforge.net/projects/estimateproject/ 上获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/c5885a90edd3/ncomms3612-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/69dd834abadb/ncomms3612-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/5aedf9a899c7/ncomms3612-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/b645c1598101/ncomms3612-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/530d57b8e0d2/ncomms3612-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/c2630ecee546/ncomms3612-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/c5885a90edd3/ncomms3612-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/69dd834abadb/ncomms3612-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/5aedf9a899c7/ncomms3612-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/b645c1598101/ncomms3612-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/530d57b8e0d2/ncomms3612-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/c2630ecee546/ncomms3612-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d51b/3826632/c5885a90edd3/ncomms3612-f6.jpg

相似文献

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Inferring tumour purity and stromal and immune cell admixture from expression data.

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[7]
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本文引用的文献

[1]
Integrated genomic characterization of endometrial carcinoma.

Nature. 2013-5-2

[2]
Prognostically relevant gene signatures of high-grade serous ovarian carcinoma.

J Clin Invest. 2012-12-21

[3]
ArrayExpress update--trends in database growth and links to data analysis tools.

Nucleic Acids Res. 2012-11-27

[4]
Interobserver agreement among pathologists for semiquantitative hormone receptor scoring in breast carcinoma.

Am J Clin Pathol. 2012-12

[5]
Comprehensive molecular portraits of human breast tumours.

Nature. 2012-9-23

[6]
Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing.

Cell. 2012-9-14

[7]
Comprehensive genomic characterization of squamous cell lung cancers.

Nature. 2012-9-9

[8]
CTen: a web-based platform for identifying enriched cell types from heterogeneous microarray data.

BMC Genomics. 2012-9-6

[9]
Comprehensive molecular characterization of human colon and rectal cancer.

Nature. 2012-7-18

[10]
Tumour micro-environment elicits innate resistance to RAF inhibitors through HGF secretion.

Nature. 2012-7-26

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