A Prognosis Classifier for Breast Cancer Based on Conserved Gene Regulation between Mammary Gland Development and Tumorigenesis: A Multiscale Statistical Model

CORC > 厦门大学 > 生物医学－已发表论文

	A Prognosis Classifier for Breast Cancer Based on Conserved Gene Regulation between Mammary Gland Development and Tumorigenesis: A Multiscale Statistical Model
	Tian, Yingpu ; Chen, Baozhen ; Guan, Pengfei ; Kang, Yujia ; Lu, Zhongxian ; Lv ZX(吕忠显)
刊名	http://dx.doi.org/10.1371/journal.pone.0060131
	2013
关键词	EXPRESSION PATTERNS EPITHELIAL-CELLS MOLECULAR PORTRAITS MICROARRAY ANALYSIS GRADE INDEX THERAPY REVEALS GROWTH TUMORS CHEMOTHERAPY
英文摘要	National Basic Research Program of China [2010CB945004]; National Natural Science Foundation of China [30772546]; Identification of novel cancer genes for molecular therapy and diagnosis is a current focus of breast cancer research. Although a few small gene sets were identified as prognosis classifiers, more powerful models are still needed for the definition of effective gene sets for the diagnosis and treatment guidance in breast cancer. In the present study, we have developed a novel statistical approach for systematic analysis of intrinsic correlations of gene expression between development and tumorigenesis in mammary gland. Based on this analysis, we constructed a predictive model for prognosis in breast cancer that may be useful for therapy decisions. We first defined developmentally associated genes from a mouse mammary gland epithelial gene expression database. Then, we found that the cancer modulated genes were enriched in this developmentally associated genes list. Furthermore, the developmentally associated genes had a specific expression profile, which associated with the molecular characteristics and histological grade of the tumor. These result suggested that the processes of mammary gland development and tumorigenesis share gene regulatory mechanisms. Then, the list of regulatory genes both on the developmental and tumorigenesis process was defined an 835-member prognosis classifier, which showed an exciting ability to predict clinical outcome of three groups of breast cancer patients (the predictive accuracy 64 similar to 72%) with a robust prognosis prediction (hazard ratio 3.3 similar to 3.8, higher than that of other clinical risk factors (around 2.0-2.8)). In conclusion, our results identified the conserved molecular mechanisms between mammary gland development and neoplasia, and provided a unique potential model for mining unknown cancer genes and predicting the clinical status of breast tumors. These findings also suggested that developmental roles of genes may be important criteria for selecting genes for prognosis prediction in breast cancer.
语种	英语
出版者	PUBLIC LIBRARY SCIENCE
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/90931]
专题	生物医学－已发表论文
推荐引用方式 GB/T 7714	Tian, Yingpu,Chen, Baozhen,Guan, Pengfei,et al. A Prognosis Classifier for Breast Cancer Based on Conserved Gene Regulation between Mammary Gland Development and Tumorigenesis: A Multiscale Statistical Model[J]. http://dx.doi.org/10.1371/journal.pone.0060131,2013.
APA	Tian, Yingpu,Chen, Baozhen,Guan, Pengfei,Kang, Yujia,Lu, Zhongxian,&吕忠显.(2013).A Prognosis Classifier for Breast Cancer Based on Conserved Gene Regulation between Mammary Gland Development and Tumorigenesis: A Multiscale Statistical Model.http://dx.doi.org/10.1371/journal.pone.0060131.
MLA	Tian, Yingpu,et al."A Prognosis Classifier for Breast Cancer Based on Conserved Gene Regulation between Mammary Gland Development and Tumorigenesis: A Multiscale Statistical Model".http://dx.doi.org/10.1371/journal.pone.0060131 (2013).