Advanced SearchSearch Tips
Identification of prognosis-specific network and prediction for estrogen receptor-negative breast cancer using microarray data and PPI data
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Identification of prognosis-specific network and prediction for estrogen receptor-negative breast cancer using microarray data and PPI data
Hwang, Youhyeon; Oh, Min; Yoon, Youngmi;
  PDF(new window)
This study proposes an algorithm for predicting breast cancer prognosis based on genetic network. We identify prognosis-specific network using gene expression data and PPI(protein-protein interaction) data. To acquire the network, we calculate Pearson`s correlation coefficient(PCC) between genes in all PPI pairs using gene expression data. We develop a prediction model for breast cancer patients with estrogen-receptor-negative using the network as a classifier. We compare classification performance of our algorithm with existing algorithms on independent data and shows our algorithm is improved. In addition, we make an functionality analysis on the genes in the prognosis-specific network using GO(Gene Ontology) enrichment validation.
data mining;classification;microarray data;breast cancer;prognosis prediction;PPI;
 Cited by
GARCIA, Maxime, et al. "Interactome- transcriptome integration for predicting distant metastasis in breast cancer." Bioinformatics, 28.5: 672-678, Jan. 2012. crossref(new window)

Ministry of Health and Welfare. "Annual report of the Central Cancer Registry in Korea, Seoul." Ministry of Health and Welfare, 2001

VAN DE VIJVER, Marc J., et al. "A gene-expression signature as a predictor of survival in breast cancer." New England Journal of Medicine, 347.25: 1999-2009, Dec. 2002. crossref(new window)

WANG, Yixin, et al. "Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer." The Lancet, 365.9460: 671-679, Feb. 2005. crossref(new window)

CHUANG, Han-Yu, et al. "Network-based classification of breast cancer metastasis." Molecular systems biology, 3.1, Jan. 2007.

TAYLOR, Ian W., et al. "Dynamic modularity in protein interaction networks predicts breast cancer outcome." Nature biotechnology, 27.2: 199-204, Feb. 2009. crossref(new window)

Taylor CR, et al. "Detection of estrogen receptor in breast and endometrial carcinoma by the immunoperoxidase technique." Cancer 47:2634-2640, June 1981. crossref(new window)

Scottish Cancer Trials Breast Group and ICRF Breast Unit GHL: "Adjuvant ovarian ablation versus CMF chemotherapy in premenopausal women with pathological stage II breast carcinoma: the Scottish trial." Lancet 341: 1293-1298, May 1993

REIS-FILHO, Jorge S.; PUSZTAI, Lajos. "Gene expression profiling in breast cancer: classification, prognostication, and prediction." The Lancet, 378.9805: 1812-1823, Nov. 2011. crossref(new window)

FISHER, Bernard, et al. "Relative worth of estrogen or progesterone receptor and pathologic characteristics of differentiation as indicators of prognosis in node negative breast cancer patients: findings from National Surgical Adjuvant Breast and Bowel Project Protocol B-06." Journal of Clinical Oncology, 6.7: 1076-1087, July 1988. crossref(new window)

MCGUIRE, William L., et al. "How to use prognostic factors in axillary node-negative breast cancer patients." Journal of the National Cancer Institute, 82.12: 1006-1015, June 1990. crossref(new window)

BEZWODA, Werner Robert, et al. "The value of estrogen and progesterone receptor determinations in advanced breast cancer. Estrogen receptor level but not progesterone receptor level correlates with response to tamoxifen." Cancer, 68.4: 867-872, Aug. 1991. crossref(new window)

ABE, O., et al. "Tamoxifen for early breast cancer: an overview of the randomised trials." Lancet, 351.9114: 1451-1467, May 1998. crossref(new window)

MACKAY, Joel P., et al. "Protein interactions: is seeing believing?" Trends in biochemical sciences, 32.12: 530-531, Nov. 2007. crossref(new window)

CHATR-ARYAMONTRI, Andrew, et al. "Protein interactions: integration leads to belief." Trends in biochemical sciences, 33.6: 241-242, May 2008. crossref(new window)

DE LAS RIVAS, Javier; FONTANILLO, Celia. "Protein-protein interactions essentials: key concepts to building and analyzing interactome networks." PLoS computational biology, 6.6: e1000807, June 2010. crossref(new window)

Biomolecular Interaction Network Database,

Biological General Repository for Interaction Datasets,

Human Protein Reference Database,

IntAct Molecular Interaction Database,

Molecular INTeraction database,

Database of Interacting Proteins,

MIPS protein interaction resource on yeast,

Online Predicted Human Interaction Database,

Guo Yu, "Statistical issues in microarray data analysis: Array-to-array normalization, Empirical Bayes batch effect adjustment."

ASHBURNER, Michael, et al. "Gene Ontology: tool for the unification of biology." Nature genetics, 25.1: 25-29, Oct. 2000. crossref(new window)

GENE ONTOLOGY CONSORTIUM, et al. "The gene ontology project in 2008." Nucleic acids research, 36.suppl 1: D440-D444, Nov. 2007. crossref(new window)

DENNIS JR, Glynn, et al. "DAVID: database for annotation, visualization, and integrated discovery." Genome biol, 4.5: P3, Aug. 2003. crossref(new window)

Gene Ontology,

AHN, Jaegyoon, et al. "Integrative gene network construction for predicting a set of complementary prostate cancer genes." Bioinformatics, 27.13: 1846-1853, May 2011. crossref(new window)

LOI, Sherene, et al. "Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade." Journal of clinical oncology, 25.10: 1239-1246, April 2007. crossref(new window)

SCHMIDT, Marcus, et al. "The humoral immune system has a key prognostic impact in node-negative breast cancer." Cancer research, 68.13: 5405-5413, July 2008. crossref(new window)

DESMEDT, Christine, et al. "Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series." Clinical cancer research, 13.11: 3207-3214, June 2007. crossref(new window)

NAGALLA, Srikanth, et al. "Interactions between immunity, proliferation and molecular subtype in breast cancer prognosis." Genome Biol, 14.4: R34, April 2013. crossref(new window)