A strategy for identifying putative causes of gene expression variation in human cancers

Sampsa Hautaniemi (Corresponding Author), Markus Ringnér, Päivikki Kauraniemi, Reija Autio, Henrik Edgren, Olli Yli-Harja, Jaakko Astola, Anne Kallioniemi, Olli Kallioniemi

Research output: Contribution to journalArticleScientificpeer-review

23 Citations (Scopus)

Abstract

The majority of microarray studies focus on analysis of gene expression differences between various specimens or conditions. However, the causes of this variability from one cancer to another, from one sample to another and from one gene to another often remain unknown. In this study, we present a systematic procedure for finding genes whose expression levels are altered due to an intrinsic or extrinsic explanatory phenomenon. The procedure consists of three stages: preprocessing, data integration and statistical analysis. We tested and verified the utility of this approach in a case study, where expression and copy number levels of 13,824 genes were determined in 14 breast cancer cell lines. The procedure resulted in identification of 92 genes whose expression levels could be explained by the variability of gene copy number. This set includes several genes that are known to be both overexpressed and amplified in breast cancer. Thus, these genes may represent an important set of primary, genetically altered genes that drive cancer progression.
Original languageEnglish
Pages (from-to)77 - 88
Number of pages12
JournalJournal of the Franklin Institute
Volume341
Issue number1-2
DOIs
Publication statusPublished - 2004
MoE publication typeA1 Journal article-refereed

Fingerprint

Gene expression
Gene Expression
Cancer
Genes
Gene
Breast Cancer
Data integration
Data Integration
Microarrays
Progression
Microarray
Statistical Analysis
Preprocessing
Human
Strategy
Statistical methods
Cells
Unknown
Line
Cell

Keywords

  • bioinformatics
  • cancer
  • data analysis
  • statistics

Cite this

Hautaniemi, S., Ringnér, M., Kauraniemi, P., Autio, R., Edgren, H., Yli-Harja, O., ... Kallioniemi, O. (2004). A strategy for identifying putative causes of gene expression variation in human cancers. Journal of the Franklin Institute, 341(1-2), 77 - 88. https://doi.org/10.1016/j.jfranklin.2003.12.005
Hautaniemi, Sampsa ; Ringnér, Markus ; Kauraniemi, Päivikki ; Autio, Reija ; Edgren, Henrik ; Yli-Harja, Olli ; Astola, Jaakko ; Kallioniemi, Anne ; Kallioniemi, Olli. / A strategy for identifying putative causes of gene expression variation in human cancers. In: Journal of the Franklin Institute. 2004 ; Vol. 341, No. 1-2. pp. 77 - 88.
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Hautaniemi, S, Ringnér, M, Kauraniemi, P, Autio, R, Edgren, H, Yli-Harja, O, Astola, J, Kallioniemi, A & Kallioniemi, O 2004, 'A strategy for identifying putative causes of gene expression variation in human cancers', Journal of the Franklin Institute, vol. 341, no. 1-2, pp. 77 - 88. https://doi.org/10.1016/j.jfranklin.2003.12.005

A strategy for identifying putative causes of gene expression variation in human cancers. / Hautaniemi, Sampsa (Corresponding Author); Ringnér, Markus; Kauraniemi, Päivikki; Autio, Reija; Edgren, Henrik; Yli-Harja, Olli; Astola, Jaakko; Kallioniemi, Anne; Kallioniemi, Olli.

In: Journal of the Franklin Institute, Vol. 341, No. 1-2, 2004, p. 77 - 88.

Research output: Contribution to journalArticleScientificpeer-review

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AB - The majority of microarray studies focus on analysis of gene expression differences between various specimens or conditions. However, the causes of this variability from one cancer to another, from one sample to another and from one gene to another often remain unknown. In this study, we present a systematic procedure for finding genes whose expression levels are altered due to an intrinsic or extrinsic explanatory phenomenon. The procedure consists of three stages: preprocessing, data integration and statistical analysis. We tested and verified the utility of this approach in a case study, where expression and copy number levels of 13,824 genes were determined in 14 breast cancer cell lines. The procedure resulted in identification of 92 genes whose expression levels could be explained by the variability of gene copy number. This set includes several genes that are known to be both overexpressed and amplified in breast cancer. Thus, these genes may represent an important set of primary, genetically altered genes that drive cancer progression.

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