Dataset Information

Integrated DNA Copy Number and Gene Expression Regulatory Network Analysis of Non-small Cell Lung Cancer Metastasis.

ABSTRACT: Integrative analysis of multi-level molecular profiles can distinguish interactions that cannot be revealed based on one kind of data in the analysis of cancer susceptibility and metastasis. DNA copy number variations (CNVs) are common in cancer cells, and their role in cell behaviors and relationship to gene expression (GE) is poorly understood. An integrative analysis of CNV and genome-wide mRNA expression can discover copy number alterations and their possible regulatory effects on GE. This study presents a novel framework to identify important genes and construct potential regulatory networks based on these genes. Using this approach, DNA copy number aberrations and their effects on GE in lung cancer progression were revealed. Specifically, this approach contains the following steps: (1) select a pool of candidate driver genes, which have significant CNV in lung cancer patient tumors or have a significant association with the clinical outcome at the transcriptional level; (2) rank important driver genes in lung cancer patients with good prognosis and poor prognosis, respectively, and use top-ranked driver genes to construct regulatory networks with the COpy Number and EXpression In Cancer (CONEXIC) method; (3) identify experimentally confirmed molecular interactions in the constructed regulatory networks using Ingenuity Pathway Analysis (IPA); and (4) visualize the refined regulatory networks with the software package Genatomy. The constructed CNV/mRNA regulatory networks provide important insights into potential CNV-regulated transcriptional mechanisms in lung cancer metastasis.

SUBMITTER: Iranmanesh SM

PROVIDER: S-EPMC4218678 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Integrated DNA Copy Number and Gene Expression Regulatory Network Analysis of Non-small Cell Lung Cancer Metastasis.

Iranmanesh Seyed M SM Guo Nancy L NL

Cancer informatics 20141014 Suppl 5

Integrative analysis of multi-level molecular profiles can distinguish interactions that cannot be revealed based on one kind of data in the analysis of cancer susceptibility and metastasis. DNA copy number variations (CNVs) are common in cancer cells, and their role in cell behaviors and relationship to gene expression (GE) is poorly understood. An integrative analysis of CNV and genome-wide mRNA expression can discover copy number alterations and their possible regulatory effects on GE. This s ...[more]

PMID: 25392690

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Project description:Background: Lung cancer has the highest mortality rate of all the cancers in the world and asbestos-related lung cancer is one of the leading occupational cancers. The identification of the asbestos-related molecular changes has been a topic of major research interest over the years. The aim of the current study was to identify novel asbestos-related molecular correlates by integrating miRNA expression profiling with previously obtained microarray data (aCGH and mRNA expression) from the same patient material. Results: Twelve novel asbestos-related miRNAs (over-expressed: miR-148b, miR-374a, miR-24-1*, Let-7d, Let-7e, miR-199b-5p, miR-331-3p and under-expressed: miR-939, miR-671-5p, miR-605, miR-1224-5p, miR-202) which inversely correlated with target genes (e.g. GADD45A, LTBP1, FOSB, NCALD, CACNA2D2, MTSS1, EPB41L3) were identified. In addition, several known and new lung cancer-associated miRNAs were identified. DNA copy number alterations were also correlated with the deregulation of four miRNAs in lung cancer. The importance of integrated analysis was highlighted by the interesting finding of linking of the over-expression of well known squamous cell carcinoma-associated miR-205 with the down-regulation of the gene DOK4. Conclusions: Novel deregulated miRNAs and inversely correlating expression of target genes associated with lung cancer etiology and histology were identified. In addition, DNA copy number alterations correlated with the deregulation of some of the miRNAs. The results of the current study could have potential diagnostic implications, but require further investigation. Methods: The patient material used in the study consisted of 26 tumour and normal lung tissue from highly asbestos-exposed (13 samples) and non-exposed (13 samples) patients. Control lung tissue samples were obtained from 7 patients without cancer as well as from a commercial lung tissue RNA. Data analysis on miRNA expression and integration of miRNA and mRNA data were performed using Chipster (http://chipster.csc.fi/). In addition, miRNA and aCGH data were integrated in a separate analysis. *** This submission represents the microRNA component of the study

Dataset Information

Integrated DNA Copy Number and Gene Expression Regulatory Network Analysis of Non-small Cell Lung Cancer Metastasis.

Publications

Integrated DNA Copy Number and Gene Expression Regulatory Network Analysis of Non-small Cell Lung Cancer Metastasis.

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