A prognosis classifier for breast cancer based on conserved gene regulation between mammary gland development and tumorigenesis: a multiscale statistical model.

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 treatm...

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Main Authors: Yingpu Tian, Baozhen Chen, Pengfei Guan, Yujia Kang, Zhongxian Lu
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3614930?pdf=render
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author Yingpu Tian
Baozhen Chen
Pengfei Guan
Yujia Kang
Zhongxian Lu
author_facet Yingpu Tian
Baozhen Chen
Pengfei Guan
Yujia Kang
Zhongxian Lu
author_sort Yingpu Tian
collection DOAJ
description 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∼72%) with a robust prognosis prediction (hazard ratio 3.3∼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.
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spelling doaj.art-b40eba4225b34dd39d8345f9b9fb0d822022-12-22T03:46:12ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0184e6013110.1371/journal.pone.0060131A prognosis classifier for breast cancer based on conserved gene regulation between mammary gland development and tumorigenesis: a multiscale statistical model.Yingpu TianBaozhen ChenPengfei GuanYujia KangZhongxian LuIdentification 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∼72%) with a robust prognosis prediction (hazard ratio 3.3∼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.http://europepmc.org/articles/PMC3614930?pdf=render
spellingShingle Yingpu Tian
Baozhen Chen
Pengfei Guan
Yujia Kang
Zhongxian Lu
A prognosis classifier for breast cancer based on conserved gene regulation between mammary gland development and tumorigenesis: a multiscale statistical model.
PLoS ONE
title A prognosis classifier for breast cancer based on conserved gene regulation between mammary gland development and tumorigenesis: a multiscale statistical model.
title_full A prognosis classifier for breast cancer based on conserved gene regulation between mammary gland development and tumorigenesis: a multiscale statistical model.
title_fullStr A prognosis classifier for breast cancer based on conserved gene regulation between mammary gland development and tumorigenesis: a multiscale statistical model.
title_full_unstemmed A prognosis classifier for breast cancer based on conserved gene regulation between mammary gland development and tumorigenesis: a multiscale statistical model.
title_short A prognosis classifier for breast cancer based on conserved gene regulation between mammary gland development and tumorigenesis: a multiscale statistical model.
title_sort prognosis classifier for breast cancer based on conserved gene regulation between mammary gland development and tumorigenesis a multiscale statistical model
url http://europepmc.org/articles/PMC3614930?pdf=render
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