scholarly journals Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review

2012 ◽  
Vol 14 (1) ◽  
pp. 27-35 ◽  
Author(s):  
L. Lahti ◽  
M. Schafer ◽  
H.-U. Klein ◽  
S. Bicciato ◽  
M. Dugas
Keyword(s):  
Mrna Expression ◽  
Copy Number ◽  
Gene Prioritization ◽  
Integrative Analysis ◽  
Copy Number Data ◽  
Cancer Gene ◽  
Dna Copy Number ◽  
Comparative Review

scholarly journals Insights into impact of DNA copy number alteration and methylation on the proteogenomic landscape of human ovarian cancer via a multi-omics integrative analysis

2018 ◽  
Author(s):  
Xiaoyu Song ◽  
Jiayi Ji ◽  
Kevin J. Gleason ◽  
John A. Martignetti ◽  
Lin S. Chen ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Mrna Expression ◽  
Copy Number ◽  
Quantitative Traits ◽  
Integrative Analysis ◽  
Omics Data ◽  
Dna Copy Number ◽  
Expression Levels ◽  
Dna Methylations ◽  
Mrna Expression Levels

In this work, we propose iProFun, an integrative analysis tool to screen for Proteogenomic Functional traits perturbed by DNA copy number alterations (CNA) and DNA methylations. The goal is to characterize functional consequences of DNA copy number and methylation alterations in tumors and to facilitate screening for cancer drivers contributing to tumor initiation and progression. Specifically, we consider three functional molecular quantitative traits: mRNA expression levels, global protein abundances, and phosphoprotein abundances. We aim to identify those genes whose CNAs and/or DNA methylations have cis-associations with either some or all three types of molecular traits. In comparison with analyzing each molecular trait separately, the joint modeling of multi-omics data enjoys several benefits: iProFun experienced enhanced power for detecting significant cis-associations shared across different omics data types; and it also achieved better accuracy in inferring cis-associations unique to certain type(s) of molecular trait(s). For example, unique associations of CNA/methylations to global/phospho protein abundances may imply post-translational regulations. We applied iProFun to ovarian high-grade serous carcinoma tumor data from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium, and identified CNAs and methylations of 500 and 122 genes, respectively, affecting the cis-functional molecular quantitative traits of the corresponding genes. We observed substantial power gain via the joint analysis of iProFun. For example, iProFun identified 130 genes whose CNAs were associated with phosphoprotein abundances by leveraging mRNA expression levels and global protein abundances. By comparison, analyses based on phosphoprotein data alone identified none. A group of these 130 genes clustered in a small region on Chromosome 14q, harboring the known oncogene, AKT1. In addition, iProFun identified one gene, CANX, whose DNA methylation has a cis-association with its global protein abundances but not its mRNA expression levels. These and other genes identified by iProFun could serve as potential drug targets for ovarian cancer.

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

2014 ◽  
Vol 13s5 ◽  
pp. CIN.S14055 ◽  
Author(s):  
Seyed M. Iranmanesh ◽  
Nancy L. Guo
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Copy Number ◽  
Regulatory Networks ◽  
Cancer Metastasis ◽  
Integrative Analysis ◽  
Transcriptional Level ◽  
Dna Copy Number ◽  
Driver Genes ◽  
Lung Cancer Metastasis

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.

scholarly journals Integrative Analysis in Oral Squamous Cell Carcinoma Reveals DNA Copy Number–Associated miRNAs Dysregulating Target Genes

2012 ◽  
Vol 147 (3) ◽  
pp. 501-508 ◽  
Author(s):  
Nicholas A. Serrano ◽  
Chang Xu ◽  
Yan Liu ◽  
Pei Wang ◽  
Wenhong Fan ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Copy Number ◽  
Target Genes ◽  
Integrative Analysis ◽  
Dna Copy Number
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