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Title 

A gene sets approach for identifying prognostic gene signatures for outcome prediction

 

예후 예측을 위한 유전자 발현 패턴을 찾는 유전자 세트 접근 방법

Authors 

Seon-Young KimYong Sung Kim

Publisher 

BioMed Central

Issue Date 

2008

Citation 

BMC Genomics, vol. 9, no. 1, pp. 177-177

Keywords 

breast cancercancer gradingcell proliferationdiagnostic accuracygene expression profilinggenetic analysisgenetic identificationhumanhuman cellhuman tissue

Abstract 

Background: Gene expression profiling is a promising approach to better estimate patient prognosis; however, there are still unresolved problems, including little overlap among similarly developed gene sets and poor performance of a developed gene set in other datasets. Results: We applied a gene sets approach to develop a prognostic gene set from multiple gene expression datasets. By analyzing 12 independent breast cancer gene expression datasets comprising 1,756 tissues with 2,411 pre-defined gene sets including gene ontology categories and pathways, we found many gene sets that were prognostic in most of the analyzed datasets. Those prognostic gene sets were related to biological processes such as cell cycle and proliferation and had additional prognostic values over conventional clinical parameters such as tumor grade, lymph node status, estrogen receptor (ER) status, and tumor size. We then estimated the prediction accuracy of each gene set by performing external validation using six large datasets and identified a gene set with an average prediction accuracy of 67.55%. Conclusion: A gene sets approach is an effective method to develop prognostic gene sets to predict patient outcome and to understand the underlying biology of the developed gene set. Using the gene sets approach we identified many prognostic gene sets in breast cancer.

ISSN 

1471-2164

Link 

http://dx.doi.org/10.1186/1471-2164-9-177

Appears in Collections

1. Journal Articles > Journal Articles

Registered Date

2017-04-19


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