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Detection of gene pathways with predictive power for breast cancer prognosis

Open access
Ma, Shuangge, Kosorok, Michael R·2010·BMC Bioinformatics

Abstract

BACKGROUND: Prognosis is of critical interest in breast cancer research. Biomedical studies suggest that genomic measurements may have independent predictive power for prognosis. Gene profiling studies have been conducted to search for predictive genomic measurements. Genes have the inherent pathway structure, where pathways are composed of multiple genes with coordinated functions. The goal of this study is to identify gene pathways with predictive power for breast cancer prognosis. Since our goal is fundamentally different from that of existing studies, a new pathway analysis method is proposed. RESULTS: The new method advances beyond existing alternatives along the following aspects. First, it can assess the predictive power of gene pathways, whereas existing methods tend to focus on model fitting accuracy only. Second, it can account for the joint effects of multiple genes in a pathway, whereas existing methods tend to focus on the marginal effects of genes. Third, it can accommodate multiple heterogeneous datasets, whereas existing methods analyze a single dataset only. We analyze four breast cancer prognosis studies and identify 97 pathways with significant predictive power for prognosis. Important pathways missed by alternative methods are identified. CONCLUSIONS: The proposed method provides a useful alternative to existing pathway analysis methods. Identified pathways can provide further insights into breast cancer prognosis.

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Metadata

Authors
Ma, S., & Kosorok, M. R.
Venue
BMC Bioinformatics
Published
2010-01-01
Volume
11
Issue
1
Pages
1-1
ISSN
1471-2105 (ISSN-L)
OpenAlex
W2038492487
Cited by
690
References
5
FWCI
3.31
Type
journal article
Language
en
Open access
gold
Licence
creativecommons.org/licenses/by/2.0 (tdm)

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Ma, S., & Kosorok, M. R. (2010). Detection of gene pathways with predictive power for breast cancer prognosis. BMC Bioinformatics. https://doi.org/10.1186/1471-2105-11-1

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