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pmid:26981414

Gene expression profiling of the tumor microenvironment in human intrahepatic cholangiocarcinoma.

Laurent Sulpice · Mireille Desille · Bruno Turlin · Alain Fautrel · Karim Boudjema · Bruno Clément · Cédric Coulouarn

Genomics data · 2016 doi:10.1016/j.gdata.2016.01.012

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Gene expression profiling of the tumor microenvironment in human intrahepatic cholangiocarcinoma.
doi
10.1016/j.gdata.2016.01.012
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Laurent Sulpice
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Mireille Desille
[2]
Bruno Turlin
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Alain Fautrel
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Karim Boudjema
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Bruno Clément
[6]
Cédric Coulouarn
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Genomics data
year
2016
abstract
Intrahepatic cholangiocarcinoma (ICC) is the second most common type of malignant primary tumors in the liver. ICC is an aggressive cancer with a poor survival and limited therapeutic options. At the histological level, ICC is characterized by an abundant stroma (i.e. the tumor microenvironment that notably includes components of the extracellular matrix, stromal cells and soluble factors). Tumor microenvironment is known to play a key role in tumor onset and progression but it is poorly characterized at the molecular level. Thus, this study was specifically designed to identify genes that are significantly deregulated in the tumor microenvironment of human ICC. Here we provide a detailed description of the experimental design and methods used to acquire the genomic data deposited into Gene Expression Omnibus (GEO) under the accession number GSE45001. Our genomic dataset provides insights on the molecular pathways altered in the microenvironment of ICC and allows the identification of novel ICC biomarkers, as exemplified previously in Hepatology (PMID: 23775819).
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Differentially expressed genes were identified by a two-sample univariate t-test and a random variance model as described [1]. Permutation P-values for significant genes were computed based on 10,000 random permutations.
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Differentially expressed genes were identified by a two-sample univariate t-test and a random variance model as described [1]. Permutation P-values for significant genes were computed based on 10,000 random permutations.
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Here we provide a detailed description of the experimental design and methods used to acquire the genomic data deposited into Gene Expression Omnibus (GEO) under the accession number GSE45001.
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Differentially expressed genes were identified by a two-sample univariate t-test and a random variance model as described [1].
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Gene expression profiling of tumor stroma in human intrahepatic cholangiocarcinoma
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