Literature DB >> 26217796

Data supporting the identification of compound for inhibition of survivin of colorectal cancer by using ingenuity pathway analysis of gene expression profiling of colorectal cancer tissues.

Yi-Chao Lee1, Jun-Wei Lee2, Chi-Chen Huang1, Ming-Heng Wu3, Kuen-Haur Lee4.   

Abstract

The data in this article is related to the research article entitled, "Targeting of Multiple Oncogenic Signaling Pathways by Hsp90 Inhibitor Alone or in Combination with Berberine for Treatment of Colorectal Cancer" [1]. Overexpression of survivin induces resistance to various anticancer therapies such as chemotherapy and radiation therapy in colorectal cancer (CRC) cells. To determine significant correlations of biological functions/pathways with survivin, 4567 significant genes were analyzed from the GEO DataSet (GSE21815) of CRC and these were overlaid onto a global molecular network developed from information contained in the Ingenuity Pathway Analysis (IPA) database. The data here present the most significant disease and disordered biological functions, significant molecular/cellular functions and significant categories in physiological development/system functions which were associated with CRC. The top 10 canonical signaling pathways associated with CRC were categorize in order based on the level of statistical significance.

Entities:  

Year:  2015        PMID: 26217796      PMCID: PMC4510466          DOI: 10.1016/j.dib.2015.05.017

Source DB:  PubMed          Journal:  Data Brief        ISSN: 2352-3409


Specifications table

Value of the data

This data provides a comprehensive analysis of CRC patients gene expression profiling and identifies cell death and survival were the top significant molecular and cellular functional categories, EIF2 signaling, the protein ubiquitination pathway, and the eIF4/p70S6K signaling pathway were the most significant pathways in the upregulated CRC gene set. The data are useful for understanding the signaling pathway in the upregulated CRC gene set to be associated with survivin expression. This data may provide insight for determination the drug for combinational treatment of CRC.

Data, experimental design, materials and methods

Acquisition and processing of public microarray data

The public microarray data will be used here were obtained from the NNCBI GEO website (GSE21815). Simple Omminus Format in Text (SOFT) files corresponding to the complete contents of GEO platform GPL6480 will be downloaded via FTP. The sequence information used to design this product was derived from a broad survey of well known sources such as RefSeq, Ensembl and Unigene. The resulting view of the human genome covers 41 K unique genes and transcripts which have been verified and optimized by alignment to the human genome assembly and by Agilent׳s Empirical Validation process. Microarray expression data for the GEO data set will be retrieved for 132 stages I to IV CRC and 9 normal control from the NCBI GEO (GSE21815).

Ingenuity pathway analysis (IPA)

Gene expression data of 132 samples of laser microdissected CRC tumors and 9 normal colon controls of patients with no colorectal neoplasm were retrieved from the GEO DataSet under the accession number GSE21815 and imported into the IPA Tool (Ingenuity H Systems, Redwood City, CA, USA; http://www.ingenuity.com). A fold difference of 2.0-fold (up-regulated) or 0.5-fold (down-regulated) was considered significant and was applied prior to pathway analyses. Based on the Ingenuity Knowledge Base different networks, biological processes and/or diseases were then algorithmically generated based on connectivity of genes within the datasets. Focus molecules were identified by IPA on the basis of highest connectivity. Comparisons will be performed between CRC group or control. The genes showing significant differences in expression levels between groups will be submitted to IPA for human diseases and disorders, molecular and cellular functions categories and pathway analysis. The most significant disease and disordered biological functions associated with CRC-correlated genes were related to cancer (Table 1, upper panel). Cell death and survival were the top significant molecular and cellular functional categories (Table 1, middle panel). Connective tissue development and function were the most significant categories in physiological development and system function (Table 1, bottom panel). To gain further insights into the pathogenesis of CRC, we analyzed CRC-correlated genes to elucidate dominant canonical pathways. The top 10 canonical signaling pathways were categorized in order based on the level of statistical significance (Table 2). Results of the pathway analysis showed that EIF2 signaling, the protein ubiquitination pathway, and the eIF4/p70S6K signaling pathway were the most significant pathways in the upregulated CRC gene set. Hsp90 inhibitors, such as geldanamycin, 17-AAG and NVP-AUY922 have been demonstrated to induce the overexpression of survivin to enhance cell survival and chemotherapy resistance in HT-29 cells [2]. More, mTOR/p70S6K signaling has been identified to be the upstream regulator of survivin [3]. Thus, targeting the mTOR/p70S6K/survivin axis is thus an attractive strategy in developing therapeutic agents against cancer cells with chemoresistance.
Table 1

Biological functions associated with CRC.

NetworkTop functionspvalueFocus genes
Diseases and disorders
1Cancer2.09E−13 to 2.16E−031795
2Infectious diseases1.50E−22 to 1.50E−05754
3Renal and urological diseases8.10E−18 to 8.01E−05228
4Organismal injury and abnormalities1.62E−18 to 1.62E−18164
5Dermatological diseases and conditions4.43E−18 to 4.43E−18163



Molecular and cellular functions
1Cell death and survival7.64E−18 to 2.46E−031427
2Gene expression2.37E−20 to 2.51E−041013
3Cell cycle2.82E−22 to 2.57E−03801
4DNA replication, recombination, and repair8.36E−23 to 2.46E−03648
5RNA post-transcriptional modifications1.22E−37 to 9.81E−04214



Physiological system development and function
1Connective tissue development and functions2.64E−10 to 2.46E−03333
2Embryonic development3.37E−12 to 1.73E−03323
3Tissue morphology8.40E−07 to 2.39E−03255
4Organismal development2.27E−07 to 1.73E−03220
5Tissue development6.03E−08 to 2.07E−03119
Table 2

Top 10 significantly changed canonical signaling pathways between CRC patients and normal controls.

Canonical pathway−log (pvalue)
EIF2 signaling3.03E01
Protein ubiquitination pathway2.38E01
Regulation of eIF4 and p70S6K signaling1.64E01
Hereditary breast cancer signaling1.19E01
Role of BRCA1 in DNA damage response1.16E01
Mitotic roles of polo-like kinase1.13E01
tRNA charging1E01
mTOR signaling9.18E00
Cell cycle control of chromosomal replication9.02E00
Role of CHK proteins in cell cycle checkpoint control8.09E00
Subject areaMedicine, biology
More specific subject areaMolecular biology, Cancer biology
Type of dataTable
How data was acquiredMicroarray data were obtained from the Gene Expression Omnibus (GEO) repository at the NCBI were analyzed using the Ingenuity pathway analysis (IPA) database
Data formatAnalyzed
Experimental factorsNone
Experimental featuresGene expression data of 132 samples of laser microdissected CRC tumors and nine normal colon controls were retrieved from the GEO DataSet under the accession number GSE21815 and imported into the IPA Tool to determine significant correlations of biological functions/pathways with survivin
Data source locationTaipei, Taiwan
Data accessibilityThe data are supplied with this article
  3 in total

1.  Regulation of survivin by PI3K/Akt/p70S6K1 pathway.

Authors:  Peng Zhao; Qiao Meng; Ling-Zhi Liu; You-Ping You; Ning Liu; Bing-Hua Jiang
Journal:  Biochem Biophys Res Commun       Date:  2010-03-31       Impact factor: 3.575

2.  Targeting of multiple oncogenic signaling pathways by Hsp90 inhibitor alone or in combination with berberine for treatment of colorectal cancer.

Authors:  Yen-Hao Su; Wan-Chun Tang; Ya-Wen Cheng; Peik Sia; Chi-Chen Huang; Yi-Chao Lee; Hsin-Yi Jiang; Ming-Heng Wu; I-Lu Lai; Jun-Wei Lee; Kuen-Haur Lee
Journal:  Biochim Biophys Acta       Date:  2015-05-14

3.  Targeting Hsp90 with small molecule inhibitors induces the over-expression of the anti-apoptotic molecule, survivin, in human A549, HONE-1 and HT-29 cancer cells.

Authors:  Chun Hei Antonio Cheung; Huang-Hui Chen; Li-Ting Cheng; Kevin W Lyu; Jagat R Kanwar; Jang-Yang Chang
Journal:  Mol Cancer       Date:  2010-04-15       Impact factor: 27.401

  3 in total
  1 in total

1.  Berberine induces autophagy in glioblastoma by targeting the AMPK/mTOR/ULK1-pathway.

Authors:  Jiwei Wang; Qichao Qi; Zichao Feng; Xin Zhang; Bin Huang; Anjing Chen; Lars Prestegarden; Xingang Li; Jian Wang
Journal:  Oncotarget       Date:  2016-10-11
  1 in total

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