The prognostic impact of age in different molecular subtypes of breast cancer
Breast cancer is a heterogeneous entity composed of distinct molecular subgroups with different molecular and clinical features. We analyzed the association between molecular breast cancer subgroups, age at diagnosis, and prognosis in a compilation of publicly available gene expression datasets. Aff...
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| Veröffentlicht in: | Breast cancer research and treatment 2015-08, Vol.152 (3), p.667-673 |
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| creator | Liedtke, Cornelia Rody, Achim Gluz, Oleg Baumann, Kristin Beyer, Daniel Kohls, Eva-Beatrice Lausen, Kerstin Hanker, Lars Holtrich, Uwe Becker, Sven Karn, Thomas |
| description | Breast cancer is a heterogeneous entity composed of distinct molecular subgroups with different molecular and clinical features. We analyzed the association between molecular breast cancer subgroups, age at diagnosis, and prognosis in a compilation of publicly available gene expression datasets. Affymetrix gene expression data (U133A or U133Plus2.0 arrays) of 4467 breast cancers from 40 datasets were compiled and homogenized. Breast cancer subgroups were defined based on expression of ESR1, PR, HER2, and Ki67. Event-free survival was calculated as recurrence-free survival or distant metastasis-free survival if recurrence-free survival was not available. Young age at diagnosis is associated with higher frequency of triple negative and HER2 subtypes and lower frequency of luminal A breast cancers. The 5-year event-free survival rates of patients aged less than 40, between 40 and 50, and >50 years were 54.3 ± 3.5, 68.5 ± 1.9, and 70.4 ± 1.3 %, respectively. When controlling for breast cancer subtype, we found that age |
| doi_str_mv | 10.1007/s10549-015-3491-3 |
| format | Article |
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We analyzed the association between molecular breast cancer subgroups, age at diagnosis, and prognosis in a compilation of publicly available gene expression datasets. Affymetrix gene expression data (U133A or U133Plus2.0 arrays) of 4467 breast cancers from 40 datasets were compiled and homogenized. Breast cancer subgroups were defined based on expression of ESR1, PR, HER2, and Ki67. Event-free survival was calculated as recurrence-free survival or distant metastasis-free survival if recurrence-free survival was not available. Young age at diagnosis is associated with higher frequency of triple negative and HER2 subtypes and lower frequency of luminal A breast cancers. The 5-year event-free survival rates of patients aged less than 40, between 40 and 50, and >50 years were 54.3 ± 3.5, 68.5 ± 1.9, and 70.4 ± 1.3 %, respectively. When controlling for breast cancer subtype, we found that age <40 years remained significantly associated with poor prognosis in triple negative breast cancer. The effect was modest in luminal tumors and not found in HER2 subtype. Both subtypes and age retained their significances in multivariate analysis. Association of age at diagnosis with molecular breast cancer subtype contributes to its important role as prognostic factor among patients with breast cancer. Still, within the group of triple negative breast cancer, young age <40 years has a significant prognostic value which was retained in multivariate analysis.</description><identifier>ISSN: 0167-6806</identifier><identifier>EISSN: 1573-7217</identifier><identifier>DOI: 10.1007/s10549-015-3491-3</identifier><identifier>PMID: 26195120</identifier><identifier>CODEN: BCTRD6</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Adult ; Age Factors ; Analysis ; Biomarkers, Tumor - analysis ; Biomarkers, Tumor - genetics ; Biomarkers, Tumor - metabolism ; Breast cancer ; Breast Neoplasms - drug therapy ; Breast Neoplasms - metabolism ; Breast Neoplasms - mortality ; Breast Neoplasms - pathology ; Cancer research ; Cancer therapies ; Disease-Free Survival ; Epidemiology ; Estrogen Receptor alpha - genetics ; Estrogen Receptor alpha - metabolism ; Female ; Gene expression ; Gene Expression Profiling ; Humans ; Ki-67 Antigen - genetics ; Ki-67 Antigen - metabolism ; Lymphatic Metastasis - pathology ; Medicine ; Medicine & Public Health ; Middle Aged ; Molecular biology ; Multivariate Analysis ; Oncology ; Prognosis ; Receptor, ErbB-2 - genetics ; Receptor, ErbB-2 - metabolism ; Receptors, Progesterone - genetics ; Receptors, Progesterone - metabolism ; Studies ; Tissue Array Analysis</subject><ispartof>Breast cancer research and treatment, 2015-08, Vol.152 (3), p.667-673</ispartof><rights>Springer Science+Business Media New York 2015</rights><rights>COPYRIGHT 2015 Springer</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c470t-869b6c4b1983d28887d700fda7267ffc588cf12daa1095974ed6bd669e38d3493</citedby><cites>FETCH-LOGICAL-c470t-869b6c4b1983d28887d700fda7267ffc588cf12daa1095974ed6bd669e38d3493</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10549-015-3491-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10549-015-3491-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26195120$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liedtke, Cornelia</creatorcontrib><creatorcontrib>Rody, Achim</creatorcontrib><creatorcontrib>Gluz, Oleg</creatorcontrib><creatorcontrib>Baumann, Kristin</creatorcontrib><creatorcontrib>Beyer, Daniel</creatorcontrib><creatorcontrib>Kohls, Eva-Beatrice</creatorcontrib><creatorcontrib>Lausen, Kerstin</creatorcontrib><creatorcontrib>Hanker, Lars</creatorcontrib><creatorcontrib>Holtrich, Uwe</creatorcontrib><creatorcontrib>Becker, Sven</creatorcontrib><creatorcontrib>Karn, Thomas</creatorcontrib><title>The prognostic impact of age in different molecular subtypes of breast cancer</title><title>Breast cancer research and treatment</title><addtitle>Breast Cancer Res Treat</addtitle><addtitle>Breast Cancer Res Treat</addtitle><description>Breast cancer is a heterogeneous entity composed of distinct molecular subgroups with different molecular and clinical features. We analyzed the association between molecular breast cancer subgroups, age at diagnosis, and prognosis in a compilation of publicly available gene expression datasets. Affymetrix gene expression data (U133A or U133Plus2.0 arrays) of 4467 breast cancers from 40 datasets were compiled and homogenized. Breast cancer subgroups were defined based on expression of ESR1, PR, HER2, and Ki67. Event-free survival was calculated as recurrence-free survival or distant metastasis-free survival if recurrence-free survival was not available. Young age at diagnosis is associated with higher frequency of triple negative and HER2 subtypes and lower frequency of luminal A breast cancers. The 5-year event-free survival rates of patients aged less than 40, between 40 and 50, and >50 years were 54.3 ± 3.5, 68.5 ± 1.9, and 70.4 ± 1.3 %, respectively. When controlling for breast cancer subtype, we found that age <40 years remained significantly associated with poor prognosis in triple negative breast cancer. The effect was modest in luminal tumors and not found in HER2 subtype. Both subtypes and age retained their significances in multivariate analysis. Association of age at diagnosis with molecular breast cancer subtype contributes to its important role as prognostic factor among patients with breast cancer. Still, within the group of triple negative breast cancer, young age <40 years has a significant prognostic value which was retained in multivariate analysis.</description><subject>Adult</subject><subject>Age Factors</subject><subject>Analysis</subject><subject>Biomarkers, Tumor - analysis</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Biomarkers, Tumor - metabolism</subject><subject>Breast cancer</subject><subject>Breast Neoplasms - drug therapy</subject><subject>Breast Neoplasms - metabolism</subject><subject>Breast Neoplasms - mortality</subject><subject>Breast Neoplasms - pathology</subject><subject>Cancer research</subject><subject>Cancer therapies</subject><subject>Disease-Free Survival</subject><subject>Epidemiology</subject><subject>Estrogen Receptor alpha - genetics</subject><subject>Estrogen Receptor alpha - metabolism</subject><subject>Female</subject><subject>Gene expression</subject><subject>Gene Expression Profiling</subject><subject>Humans</subject><subject>Ki-67 Antigen - genetics</subject><subject>Ki-67 Antigen - metabolism</subject><subject>Lymphatic Metastasis - pathology</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Middle Aged</subject><subject>Molecular biology</subject><subject>Multivariate Analysis</subject><subject>Oncology</subject><subject>Prognosis</subject><subject>Receptor, ErbB-2 - genetics</subject><subject>Receptor, ErbB-2 - metabolism</subject><subject>Receptors, Progesterone - genetics</subject><subject>Receptors, Progesterone - metabolism</subject><subject>Studies</subject><subject>Tissue Array Analysis</subject><issn>0167-6806</issn><issn>1573-7217</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1kUFvFSEUhYnR2Gf1B7gxk5iYbqZehhlglk2j1aTGTV0TBi7v0czAE5hF_708X9XWaFiQwHfOvSeHkNcUzimAeJ8pDP3YAh1a1o-0ZU_Ihg6CtaKj4inZAOWi5RL4CXmR8y0AjALG5-Sk43QcaAcb8uVmh80-xW2IuXjT-GWvTWmia_QWGx8a653DhKE0S5zRrLNOTV6ncrfHfMCmhDqXxuhgML0kz5yeM766v0_Jt48fbi4_tddfrz5fXly3phdQWsnHiZt-oqNktpNSCisAnNWi48I5M0hpHO2s1hTGYRQ9Wj5Zzkdk0tak7JScHX3r5t9XzEUtPhucZx0wrlnRasclE4xW9O1f6G1cU6jb_aSA1_nwh9rqGZUPLpakzcFUXfRMSCFhOFDn_6Dqsbh4EwM6X98fCd49EOxQz2WX47wWH0N-DNIjaFLMOaFT--QXne4UBXXoWh27VrVrdehasap5c59snRa0vxW_yq1AdwRy_QpbTA-i_9f1B8WesEE</recordid><startdate>20150801</startdate><enddate>20150801</enddate><creator>Liedtke, Cornelia</creator><creator>Rody, Achim</creator><creator>Gluz, Oleg</creator><creator>Baumann, Kristin</creator><creator>Beyer, Daniel</creator><creator>Kohls, Eva-Beatrice</creator><creator>Lausen, Kerstin</creator><creator>Hanker, Lars</creator><creator>Holtrich, Uwe</creator><creator>Becker, Sven</creator><creator>Karn, Thomas</creator><general>Springer US</general><general>Springer</general><general>Springer Nature B.V</general><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>3V.</scope><scope>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>K9-</scope><scope>K9.</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20150801</creationdate><title>The prognostic impact of age in different molecular subtypes of breast cancer</title><author>Liedtke, Cornelia ; Rody, Achim ; Gluz, Oleg ; Baumann, Kristin ; Beyer, Daniel ; Kohls, Eva-Beatrice ; Lausen, Kerstin ; Hanker, Lars ; Holtrich, Uwe ; Becker, Sven ; Karn, Thomas</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c470t-869b6c4b1983d28887d700fda7267ffc588cf12daa1095974ed6bd669e38d3493</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adult</topic><topic>Age Factors</topic><topic>Analysis</topic><topic>Biomarkers, Tumor - analysis</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Biomarkers, Tumor - metabolism</topic><topic>Breast cancer</topic><topic>Breast Neoplasms - drug therapy</topic><topic>Breast Neoplasms - metabolism</topic><topic>Breast Neoplasms - mortality</topic><topic>Breast Neoplasms - pathology</topic><topic>Cancer research</topic><topic>Cancer therapies</topic><topic>Disease-Free Survival</topic><topic>Epidemiology</topic><topic>Estrogen Receptor alpha - genetics</topic><topic>Estrogen Receptor alpha - metabolism</topic><topic>Female</topic><topic>Gene expression</topic><topic>Gene Expression Profiling</topic><topic>Humans</topic><topic>Ki-67 Antigen - genetics</topic><topic>Ki-67 Antigen - metabolism</topic><topic>Lymphatic Metastasis - pathology</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Middle Aged</topic><topic>Molecular biology</topic><topic>Multivariate Analysis</topic><topic>Oncology</topic><topic>Prognosis</topic><topic>Receptor, ErbB-2 - 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Academic</collection><jtitle>Breast cancer research and treatment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liedtke, Cornelia</au><au>Rody, Achim</au><au>Gluz, Oleg</au><au>Baumann, Kristin</au><au>Beyer, Daniel</au><au>Kohls, Eva-Beatrice</au><au>Lausen, Kerstin</au><au>Hanker, Lars</au><au>Holtrich, Uwe</au><au>Becker, Sven</au><au>Karn, Thomas</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The prognostic impact of age in different molecular subtypes of breast cancer</atitle><jtitle>Breast cancer research and treatment</jtitle><stitle>Breast Cancer Res Treat</stitle><addtitle>Breast Cancer Res Treat</addtitle><date>2015-08-01</date><risdate>2015</risdate><volume>152</volume><issue>3</issue><spage>667</spage><epage>673</epage><pages>667-673</pages><issn>0167-6806</issn><eissn>1573-7217</eissn><coden>BCTRD6</coden><abstract>Breast cancer is a heterogeneous entity composed of distinct molecular subgroups with different molecular and clinical features. We analyzed the association between molecular breast cancer subgroups, age at diagnosis, and prognosis in a compilation of publicly available gene expression datasets. Affymetrix gene expression data (U133A or U133Plus2.0 arrays) of 4467 breast cancers from 40 datasets were compiled and homogenized. Breast cancer subgroups were defined based on expression of ESR1, PR, HER2, and Ki67. Event-free survival was calculated as recurrence-free survival or distant metastasis-free survival if recurrence-free survival was not available. Young age at diagnosis is associated with higher frequency of triple negative and HER2 subtypes and lower frequency of luminal A breast cancers. The 5-year event-free survival rates of patients aged less than 40, between 40 and 50, and >50 years were 54.3 ± 3.5, 68.5 ± 1.9, and 70.4 ± 1.3 %, respectively. When controlling for breast cancer subtype, we found that age <40 years remained significantly associated with poor prognosis in triple negative breast cancer. The effect was modest in luminal tumors and not found in HER2 subtype. Both subtypes and age retained their significances in multivariate analysis. Association of age at diagnosis with molecular breast cancer subtype contributes to its important role as prognostic factor among patients with breast cancer. Still, within the group of triple negative breast cancer, young age <40 years has a significant prognostic value which was retained in multivariate analysis.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>26195120</pmid><doi>10.1007/s10549-015-3491-3</doi><tpages>7</tpages></addata></record> |
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| subjects | Adult Age Factors Analysis Biomarkers, Tumor - analysis Biomarkers, Tumor - genetics Biomarkers, Tumor - metabolism Breast cancer Breast Neoplasms - drug therapy Breast Neoplasms - metabolism Breast Neoplasms - mortality Breast Neoplasms - pathology Cancer research Cancer therapies Disease-Free Survival Epidemiology Estrogen Receptor alpha - genetics Estrogen Receptor alpha - metabolism Female Gene expression Gene Expression Profiling Humans Ki-67 Antigen - genetics Ki-67 Antigen - metabolism Lymphatic Metastasis - pathology Medicine Medicine & Public Health Middle Aged Molecular biology Multivariate Analysis Oncology Prognosis Receptor, ErbB-2 - genetics Receptor, ErbB-2 - metabolism Receptors, Progesterone - genetics Receptors, Progesterone - metabolism Studies Tissue Array Analysis |
| title | The prognostic impact of age in different molecular subtypes of breast cancer |
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