TOP

Research Article

Split Viewer

Mol. Cells 2012; 34(4): 393-398

Published online September 13, 2012

https://doi.org/10.1007/s10059-012-0177-0

© The Korean Society for Molecular and Cellular Biology

A Pathway-Based Classification of Breast Cancer Integrating Data on Differentially Expressed Genes, Copy Number Variations and MicroRNA Target Genes

Hae-Seok Eo, Jee Yeon Heo, Yongjin Choi, Youngdon Hwang, and Hyung-Seok Choi*

Bio&Health Team, Future IT R&D Laboratory, LGE Advanced Research Institute, Seoul 137-724, Korea

Correspondence to : *Correspondence: hyungseok.choi@lge.com

Received: July 11, 2012; Revised: August 9, 2012; Accepted: August 10, 2012

Abstract

Breast cancer is a clinically heterogeneous disease char-acterized by distinct molecular aberrations. Under-standing the heterogeneity and identifying subgroups of breast cancer are essential to improving diagnoses and predicting therapeutic responses. In this paper, we pro-pose a classification scheme for breast cancer which integrates data on differentially expressed genes (DEGs), copy number variations (CNVs) and microRNAs (miRNAs)-regulated mRNAs. Pathway information based on the estimation of molecular pathway activity is also applied as a postprocessor to optimize the classifier. A total of 250 malignant breast tumors were analyzed by k-means clustering based on the patterns of the expression profiles of 215 intrinsic genes, and the classification performances were compared with existing breast cancer classifiers including the BluePrint and the 625-gene classifier. We show that a classification scheme which incorporates pathway information with various genetic variations achieves better per-formance than classifiers based on the expression levels of individual genes, and propose that the identified signature serves as a basic tool for identifying rational therapeutic opportunities for breast cancer patients.

Keywords breast cancer, classification, copy number variation, differentially expressed gene, microRNA, pathway

Article

Research Article

Mol. Cells 2012; 34(4): 393-398

Published online October 31, 2012 https://doi.org/10.1007/s10059-012-0177-0

Copyright © The Korean Society for Molecular and Cellular Biology.

A Pathway-Based Classification of Breast Cancer Integrating Data on Differentially Expressed Genes, Copy Number Variations and MicroRNA Target Genes

Hae-Seok Eo, Jee Yeon Heo, Yongjin Choi, Youngdon Hwang, and Hyung-Seok Choi*

Bio&Health Team, Future IT R&D Laboratory, LGE Advanced Research Institute, Seoul 137-724, Korea

Correspondence to:*Correspondence: hyungseok.choi@lge.com

Received: July 11, 2012; Revised: August 9, 2012; Accepted: August 10, 2012

Abstract

Breast cancer is a clinically heterogeneous disease char-acterized by distinct molecular aberrations. Under-standing the heterogeneity and identifying subgroups of breast cancer are essential to improving diagnoses and predicting therapeutic responses. In this paper, we pro-pose a classification scheme for breast cancer which integrates data on differentially expressed genes (DEGs), copy number variations (CNVs) and microRNAs (miRNAs)-regulated mRNAs. Pathway information based on the estimation of molecular pathway activity is also applied as a postprocessor to optimize the classifier. A total of 250 malignant breast tumors were analyzed by k-means clustering based on the patterns of the expression profiles of 215 intrinsic genes, and the classification performances were compared with existing breast cancer classifiers including the BluePrint and the 625-gene classifier. We show that a classification scheme which incorporates pathway information with various genetic variations achieves better per-formance than classifiers based on the expression levels of individual genes, and propose that the identified signature serves as a basic tool for identifying rational therapeutic opportunities for breast cancer patients.

Keywords: breast cancer, classification, copy number variation, differentially expressed gene, microRNA, pathway

Mol. Cells
May 31, 2023 Vol.46 No.5, pp. 259~328
COVER PICTURE
The alpha-helices in the lamin filaments are depicted as coils, with different subdomains distinguished by various colors. Coil 1a is represented by magenta, coil 1b by yellow, L2 by green, coil 2a by white, coil 2b by brown, stutter by cyan, coil 2c by dark blue, and the lamin Ig-like domain by grey. In the background, cells are displayed, with the cytosol depicted in green and the nucleus in blue (Ahn et al., pp. 309-318).

Supplementary File

Share this article on

  • line
  • mail

Related articles in Mol. Cells

Molecules and Cells

eISSN 0219-1032
qr-code Download