Comparison of gene expression and DNA copy number changes in a murine model of lung cancer

2005 ◽  
Vol 45 (4) ◽  
pp. 338-348 ◽  
Author(s):  
Alejandro Sweet-Cordero ◽  
George C. Tseng ◽  
Han You ◽  
Margaret Douglass ◽  
Bing Huey ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Murine Model ◽  
Copy Number ◽  
Dna Copy Number ◽  
Copy Number Changes

scholarly journals Genes with Relevance for Early to Late Progression of Colon Carcinoma Based on Combined Genomic and Transcriptomic Information from the Same Patients

2010 ◽  
Vol 9 ◽  
pp. CIN.S4545 ◽  
Author(s):  
Kristina K. Lagerstedt ◽  
Erik Kristiansson ◽  
Christina Lönnroth ◽  
Marianne Andersson ◽  
Britt-Marie IresjÖ ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Tumor Progression ◽  
Cancer Progression ◽  
Copy Number ◽  
Dna Copy Number ◽  
Colon Cancer Progression ◽  
Dna Alterations ◽  
Copy Number Changes ◽  
Dukes C

Background Genetic and epigenetic alterations in colorectal cancer are numerous. However, it is difficult to judge whether such changes are primary or secondary to the appearance and progression of tumors. Therefore, the aim of the present study was to identify altered DNA regions with significant covariation to transcription alterations along colon cancer progression. Methods Tumor and normal colon tissue were obtained at primary operations from 24 patients selected by chance. DNA, RNA and microRNAs were extracted from the same biopsy material in all individuals and analyzed by oligo-nucleotide array-based comparative genomic hybridization (CGH), mRNA- and microRNA oligo-arrays. Statistical analyses were performed to assess statistical interactions (correlations, co-variations) between DNA copy number changes and significant alterations in gene and microRNA expression using appropriate parametric and non-parametric statistics. Results Main DNA alterations were located on chromosome 7, 8, 13 and 20. Tumor DNA copy number gain increased with tumor progression, significantly related to increased gene expression. Copy number loss was not observed in Dukes A tumors. There was no significant relationship between expressed genes and tumor progression across Dukes A–D tumors; and no relationship between tumor stage and the number of microRNAs with significantly altered expression. Interaction analyses identified overall 41 genes, which discriminated early Dukes A plus B tumors from late Dukes C plus D tumor; 28 of these genes remained with correlations between genomic and transcriptomic alterations in Dukes C plus D tumors and 17 in Dukes D. One microRNA (microR-663) showed interactions with DNA alterations in all Dukes A-D tumors. Conclusions Our modeling confirms that colon cancer progression is related to genomic instability and altered gene expression. However, early invasive tumor growth seemed rather related to transcriptomic alterations, where changes in microRNA may be an early phenomenon, and less to DNA copy number changes.

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 An Integrated Approach for RNA-seq Data Normalization

2016 ◽  
Vol 15 ◽  
pp. CIN.S39781 ◽  
Author(s):  
Shengping Yang ◽  
Donald E. Mercante ◽  
Kun Zhang ◽  
Zhide Fang
Keyword(s):  
Gene Expression ◽  
Dna Sequences ◽  
Copy Number ◽  
Differentially Expressed Gene ◽  
Integrated Approach ◽  
Gene Profiling ◽  
Data Normalization ◽  
Rna Seq ◽  
Dna Copy Number ◽  
Copy Number Changes

Background DNA copy number alteration is common in many cancers. Studies have shown that insertion or deletion of DNA sequences can directly alter gene expression, and significant correlation exists between DNA copy number and gene expression. Data normalization is a critical step in the analysis of gene expression generated by RNA-seq technology. Successful normalization reduces/removes unwanted nonbiological variations in the data, while keeping meaningful information intact. However, as far as we know, no attempt has been made to adjust for the variation due to DNA copy number changes in RNA-seq data normalization. Results In this article, we propose an integrated approach for RNA-seq data normalization. Comparisons show that the proposed normalization can improve power for downstream differentially expressed gene detection and generate more biologically meaningful results in gene profiling. In addition, our findings show that due to the effects of copy number changes, some housekeeping genes are not always suitable internal controls for studying gene expression. Conclusions Using information from DNA copy number, integrated approach is successful in reducing noises due to both biological and nonbiological causes in RNA-seq data, thus increasing the accuracy of gene profiling.

AML/MDS with 11q/MLLamplification show characteristic gene expression signature and interplay of DNA copy number changes

2009 ◽  
Vol 48 (6) ◽  
pp. 510-520 ◽  
Author(s):  
Andrea Zatkova ◽  
Sylvia Merk ◽  
Melanie Wendehack ◽  
Martin Bilban ◽  
Eva Maria Muzik ◽  
...  
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
Gene Expression Signature ◽  
Dna Copy Number ◽  
Expression Signature ◽  
Copy Number Changes
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