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

Iranmanesh SM, Guo NL - Cancer Inform (2014)

Bottom Line: An integrative analysis of CNV and genome-wide mRNA expression can discover copy number alterations and their possible regulatory effects on GE.Using this approach, DNA copy number aberrations and their effects on GE in lung cancer progression were revealed.The constructed CNV/mRNA regulatory networks provide important insights into potential CNV-regulated transcriptional mechanisms in lung cancer metastasis.

View Article: PubMed Central - PubMed

Affiliation: Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, USA.

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.

No MeSH data available.


Related in: MedlinePlus

Overview of integrative analysis of DNA copy number and GE.
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Related In: Results  -  Collection


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f1-cin-suppl.5-2014-013: Overview of integrative analysis of DNA copy number and GE.

Mentions: The scheme to perform integrative analysis of CNV and GE contains the following steps (Fig. 1). First, candidate driver genes were selected using DNA copy number information and mRNA prognostic genes. CGHcall34 was used to detect the aberrant regions of DNA copy numbers. Genes that showed consistent copy number aberrations in NSCLC compared with normal tissues in both datasets were selected. In addition, genes that had a significant association with patient survival time based on their copy number status were selected. The remaining candidate driver genes were mRNA prognostic genes identified in our previous studies. Second, after identifying candidate driver genes, CONEXIC was used to construct regulatory networks for good prognosis and poor prognosis NSCLC patients, respectively. Third, as the constructed regulatory networks were large, IPA was used to reduce the gene interactions to only experimentally validated ones. Finally, the Genatomy package was used to visualize the refined regulatory networks.


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

Iranmanesh SM, Guo NL - Cancer Inform (2014)

Overview of integrative analysis of DNA copy number and GE.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4218678&req=5

f1-cin-suppl.5-2014-013: Overview of integrative analysis of DNA copy number and GE.
Mentions: The scheme to perform integrative analysis of CNV and GE contains the following steps (Fig. 1). First, candidate driver genes were selected using DNA copy number information and mRNA prognostic genes. CGHcall34 was used to detect the aberrant regions of DNA copy numbers. Genes that showed consistent copy number aberrations in NSCLC compared with normal tissues in both datasets were selected. In addition, genes that had a significant association with patient survival time based on their copy number status were selected. The remaining candidate driver genes were mRNA prognostic genes identified in our previous studies. Second, after identifying candidate driver genes, CONEXIC was used to construct regulatory networks for good prognosis and poor prognosis NSCLC patients, respectively. Third, as the constructed regulatory networks were large, IPA was used to reduce the gene interactions to only experimentally validated ones. Finally, the Genatomy package was used to visualize the refined regulatory networks.

Bottom Line: An integrative analysis of CNV and genome-wide mRNA expression can discover copy number alterations and their possible regulatory effects on GE.Using this approach, DNA copy number aberrations and their effects on GE in lung cancer progression were revealed.The constructed CNV/mRNA regulatory networks provide important insights into potential CNV-regulated transcriptional mechanisms in lung cancer metastasis.

View Article: PubMed Central - PubMed

Affiliation: Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, USA.

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.

No MeSH data available.


Related in: MedlinePlus