Integrated Analysis of DNA Copy Number and Gene Expression Microarray Data Using Gene Sets

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2009 Jul 1

PMID 19563656

Citations 36

Authors

Renee X Menezes

Marten Boetzer

Melle Sieswerda

Gert-Jan B van Ommen

Judith M Boer

Affiliations

Soon will be listed here.

Abstract

Background: Genes that play an important role in tumorigenesis are expected to show association between DNA copy number and RNA expression. Optimal power to find such associations can only be achieved if analysing copy number and gene expression jointly. Furthermore, some copy number changes extend over larger chromosomal regions affecting the expression levels of multiple resident genes.

Results: We propose to analyse copy number and expression array data using gene sets, rather than individual genes. The proposed model is robust and sensitive. We re-analysed two publicly available datasets as illustration. These two independent breast cancer datasets yielded similar patterns of association between gene dosage and gene expression levels, in spite of different platforms having been used. Our comparisons show a clear advantage to using sets of genes' expressions to detect associations with long-spanning, low-amplitude copy number aberrations. In addition, our model allows for using additional explanatory variables and does not require mapping between copy number and expression probes.

Conclusion: We developed a general and flexible tool for integration of multiple microarray data sets, and showed how the identification of genes whose expression is affected by copy number aberrations provides a powerful approach to prioritize putative targets for functional validation.

Citing Articles

CiberAMP: An Package to Identify Differential mRNA Expression Linked to Somatic Copy Number Variations in Cancer Datasets.

Caloto R, Lorenzo-Martin L, Quesada V, Carracedo A, Bustelo X Biology (Basel). 2022; 11(10).

PMID: 36290315 PMC: 9598370. DOI: 10.3390/biology11101411.

Pan-cancer evaluation of gene expression and somatic alteration data for cancer prognosis prediction.

Zheng X, Amos C, Frost H BMC Cancer. 2021; 21(1):1053.

PMID: 34563154 PMC: 8467202. DOI: 10.1186/s12885-021-08796-3.

High prevalence of APOA1/C3/A4/A5 alterations in luminal breast cancers among young women in East Asia.

Lin C, Huang R, Lu T, Kuo K, Lo K, Chen C NPJ Breast Cancer. 2021; 7(1):88.

PMID: 34226567 PMC: 8257799. DOI: 10.1038/s41523-021-00299-5.

Targeted Treatment of Head and Neck (Pre)Cancer: Preclinical Target Identification and Development of Novel Therapeutic Applications.

van Harten A, Brakenhoff R Cancers (Basel). 2021; 13(11).

PMID: 34204886 PMC: 8199752. DOI: 10.3390/cancers13112774.

Set-Wise Differential Interaction Between Copy Number Alterations and Gene Expressions of Lower-Grade Glioma Reveals Prognosis-Associated Pathways.

Cho S Entropy (Basel). 2020; 22(12).

PMID: 33353229 PMC: 7765960. DOI: 10.3390/e22121434.

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