A cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients
Breast cancer comprises a group of distinct subtypes that despite having similar histologic appearances, have very different metastatic potentials. Being able to identify the biological driving force, even for a subset of patients, is crucially important given the large population of women diagnosed...
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| Veröffentlicht in: | Cancer research (Chicago, Ill.) Ill.), 2005-05, Vol.65 (10), p.4059-4066 |
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| creator | HONGYUE DAI VAN'T VEER, Laura STOUGHTON, Roland FRIEND, Stephen LAMB, John HE, Yudong D MAO MAO FINE, Bernard M BERNARDS, Rene VAN DE VIJVER, Marc DEUTSCH, Paul SACHS, Alan |
| description | Breast cancer comprises a group of distinct subtypes that despite having similar histologic appearances, have very different metastatic potentials. Being able to identify the biological driving force, even for a subset of patients, is crucially important given the large population of women diagnosed with breast cancer. Here, we show that within a subset of patients characterized by relatively high estrogen receptor expression for their age, the occurrence of metastases is strongly predicted by a homogeneous gene expression pattern almost entirely consisting of cell cycle genes (5-year odds ratio of metastasis, 24.0; 95% confidence interval, 6.0-95.5). Overexpression of this set of genes is clearly associated with an extremely poor outcome, with the 10-year metastasis-free probability being only 24% for the poor group, compared with 85% for the good group. In contrast, this gene expression pattern is much less correlated with the outcome in other patient subpopulations. The methods described here also illustrate the value of combining clinical variables, biological insight, and machine-learning to dissect biological complexity. Our work presented here may contribute a crucial step towards rational design of personalized treatment. |
| doi_str_mv | 10.1158/0008-5472.can-04-3953 |
| format | Article |
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Being able to identify the biological driving force, even for a subset of patients, is crucially important given the large population of women diagnosed with breast cancer. Here, we show that within a subset of patients characterized by relatively high estrogen receptor expression for their age, the occurrence of metastases is strongly predicted by a homogeneous gene expression pattern almost entirely consisting of cell cycle genes (5-year odds ratio of metastasis, 24.0; 95% confidence interval, 6.0-95.5). Overexpression of this set of genes is clearly associated with an extremely poor outcome, with the 10-year metastasis-free probability being only 24% for the poor group, compared with 85% for the good group. In contrast, this gene expression pattern is much less correlated with the outcome in other patient subpopulations. The methods described here also illustrate the value of combining clinical variables, biological insight, and machine-learning to dissect biological complexity. Our work presented here may contribute a crucial step towards rational design of personalized treatment.</description><identifier>ISSN: 0008-5472</identifier><identifier>EISSN: 1538-7445</identifier><identifier>DOI: 10.1158/0008-5472.can-04-3953</identifier><identifier>PMID: 15899795</identifier><identifier>CODEN: CNREA8</identifier><language>eng</language><publisher>Philadelphia, PA: American Association for Cancer Research</publisher><subject>Age Factors ; Antineoplastic agents ; Biological and medical sciences ; Breast Neoplasms - genetics ; Breast Neoplasms - metabolism ; Breast Neoplasms - pathology ; Cell Cycle - genetics ; Cell Growth Processes - genetics ; Female ; Gene Expression Profiling ; Humans ; Medical sciences ; Neoplasm Metastasis ; Oligonucleotide Array Sequence Analysis ; Pharmacology. Drug treatments ; Prognosis ; Receptors, Estrogen - biosynthesis ; Receptors, Estrogen - genetics ; Tumors</subject><ispartof>Cancer research (Chicago, Ill.), 2005-05, Vol.65 (10), p.4059-4066</ispartof><rights>2005 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c484t-a61c27e4194a7e12b569feadd6cf295681b8c32f94c2d769c71c7cd6fd58d7883</citedby><cites>FETCH-LOGICAL-c484t-a61c27e4194a7e12b569feadd6cf295681b8c32f94c2d769c71c7cd6fd58d7883</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,3343,27901,27902</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16780316$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15899795$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>HONGYUE DAI</creatorcontrib><creatorcontrib>VAN'T VEER, Laura</creatorcontrib><creatorcontrib>STOUGHTON, Roland</creatorcontrib><creatorcontrib>FRIEND, Stephen</creatorcontrib><creatorcontrib>LAMB, John</creatorcontrib><creatorcontrib>HE, Yudong D</creatorcontrib><creatorcontrib>MAO MAO</creatorcontrib><creatorcontrib>FINE, Bernard M</creatorcontrib><creatorcontrib>BERNARDS, Rene</creatorcontrib><creatorcontrib>VAN DE VIJVER, Marc</creatorcontrib><creatorcontrib>DEUTSCH, Paul</creatorcontrib><creatorcontrib>SACHS, Alan</creatorcontrib><title>A cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients</title><title>Cancer research (Chicago, Ill.)</title><addtitle>Cancer Res</addtitle><description>Breast cancer comprises a group of distinct subtypes that despite having similar histologic appearances, have very different metastatic potentials. Being able to identify the biological driving force, even for a subset of patients, is crucially important given the large population of women diagnosed with breast cancer. Here, we show that within a subset of patients characterized by relatively high estrogen receptor expression for their age, the occurrence of metastases is strongly predicted by a homogeneous gene expression pattern almost entirely consisting of cell cycle genes (5-year odds ratio of metastasis, 24.0; 95% confidence interval, 6.0-95.5). Overexpression of this set of genes is clearly associated with an extremely poor outcome, with the 10-year metastasis-free probability being only 24% for the poor group, compared with 85% for the good group. In contrast, this gene expression pattern is much less correlated with the outcome in other patient subpopulations. The methods described here also illustrate the value of combining clinical variables, biological insight, and machine-learning to dissect biological complexity. Our work presented here may contribute a crucial step towards rational design of personalized treatment.</description><subject>Age Factors</subject><subject>Antineoplastic agents</subject><subject>Biological and medical sciences</subject><subject>Breast Neoplasms - genetics</subject><subject>Breast Neoplasms - metabolism</subject><subject>Breast Neoplasms - pathology</subject><subject>Cell Cycle - genetics</subject><subject>Cell Growth Processes - genetics</subject><subject>Female</subject><subject>Gene Expression Profiling</subject><subject>Humans</subject><subject>Medical sciences</subject><subject>Neoplasm Metastasis</subject><subject>Oligonucleotide Array Sequence Analysis</subject><subject>Pharmacology. Drug treatments</subject><subject>Prognosis</subject><subject>Receptors, Estrogen - biosynthesis</subject><subject>Receptors, Estrogen - genetics</subject><subject>Tumors</subject><issn>0008-5472</issn><issn>1538-7445</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpFkEtPxCAUhYnR6Pj4CRo2uusILRRYTia-koludE0ovZhqWyq0if57aabRFbk33znccxC6pGRNKZe3hBCZcSbytTV9RlhWKF4coBXlhcwEY_wQrf6YE3Qa40caOSX8GJ0kA6WE4iv0tcEW2hYPwbeNg2DGxvc4Nu-9GacAuInY4M6ETwjYOwzfY4AO2h88eJ8202h9l6g-UXGqBj9M7d4iwVUAE0ec7rNJPaQ99GM8R0fOtBEulvcMvd3fvW4fs93Lw9N2s8ssk2zMTEltLoBRxYwAmle8VA5MXZfW5YqXklbSFrlTzOa1KJUV1Apbl67mshZSFmfoZu-bon1NEEfdNXHOanrwU9SlkIWkhCaQ70EbfIwBnB5CkyL_aEr03LWee9Rzj3q7edaE6bnrpLtaPpiqDup_1VJuAq4XwERrWhdSEU3859IFpKBl8QvZyYnB</recordid><startdate>20050515</startdate><enddate>20050515</enddate><creator>HONGYUE DAI</creator><creator>VAN'T VEER, Laura</creator><creator>STOUGHTON, Roland</creator><creator>FRIEND, Stephen</creator><creator>LAMB, John</creator><creator>HE, Yudong D</creator><creator>MAO MAO</creator><creator>FINE, Bernard M</creator><creator>BERNARDS, Rene</creator><creator>VAN DE VIJVER, Marc</creator><creator>DEUTSCH, Paul</creator><creator>SACHS, Alan</creator><general>American Association for Cancer Research</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20050515</creationdate><title>A cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients</title><author>HONGYUE DAI ; VAN'T VEER, Laura ; STOUGHTON, Roland ; FRIEND, Stephen ; LAMB, John ; HE, Yudong D ; MAO MAO ; FINE, Bernard M ; BERNARDS, Rene ; VAN DE VIJVER, Marc ; DEUTSCH, Paul ; SACHS, Alan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c484t-a61c27e4194a7e12b569feadd6cf295681b8c32f94c2d769c71c7cd6fd58d7883</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Age Factors</topic><topic>Antineoplastic agents</topic><topic>Biological and medical sciences</topic><topic>Breast Neoplasms - genetics</topic><topic>Breast Neoplasms - metabolism</topic><topic>Breast Neoplasms - pathology</topic><topic>Cell Cycle - genetics</topic><topic>Cell Growth Processes - genetics</topic><topic>Female</topic><topic>Gene Expression Profiling</topic><topic>Humans</topic><topic>Medical sciences</topic><topic>Neoplasm Metastasis</topic><topic>Oligonucleotide Array Sequence Analysis</topic><topic>Pharmacology. 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| subjects | Age Factors Antineoplastic agents Biological and medical sciences Breast Neoplasms - genetics Breast Neoplasms - metabolism Breast Neoplasms - pathology Cell Cycle - genetics Cell Growth Processes - genetics Female Gene Expression Profiling Humans Medical sciences Neoplasm Metastasis Oligonucleotide Array Sequence Analysis Pharmacology. Drug treatments Prognosis Receptors, Estrogen - biosynthesis Receptors, Estrogen - genetics Tumors |
| title | A cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients |
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