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Melanoma antigen family A identified by the bimodality index defines a subset of triple negative breast cancers as candidates for immune response augmentation

Abstract Background Molecular markers displaying bimodal expression distribution can reveal distinct disease subsets and may serve as prognostic or predictive markers or represent therapeutic targets. Oestrogen (ER) and human epidermal growth factor receptor 2 (HER2) receptors are strongly bimodally...

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Published in:European journal of cancer (1990) 2012-01, Vol.48 (1), p.12-23
Main Authors: Karn, Thomas, Pusztai, Lajos, Ruckhäberle, Eugen, Liedtke, Cornelia, Müller, Volkmar, Schmidt, Marcus, Metzler, Dirk, Wang, Jing, Coombes, Kevin R, Gätje, Regine, Hanker, Lars, Solbach, Christine, Ahr, Andre, Holtrich, Uwe, Rody, Achim, Kaufmann, Manfred
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cited_by cdi_FETCH-LOGICAL-c539t-4c927c36f92207f02cd44d4878c9b1cbd95a66c974c497e0c78b5ec908875fbc3
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container_title European journal of cancer (1990)
container_volume 48
creator Karn, Thomas
Pusztai, Lajos
Ruckhäberle, Eugen
Liedtke, Cornelia
Müller, Volkmar
Schmidt, Marcus
Metzler, Dirk
Wang, Jing
Coombes, Kevin R
Gätje, Regine
Hanker, Lars
Solbach, Christine
Ahr, Andre
Holtrich, Uwe
Rody, Achim
Kaufmann, Manfred
description Abstract Background Molecular markers displaying bimodal expression distribution can reveal distinct disease subsets and may serve as prognostic or predictive markers or represent therapeutic targets. Oestrogen (ER) and human epidermal growth factor receptor 2 (HER2) receptors are strongly bimodally expressed genes in breast cancer. Material and methods We applied a novel method to identify bimodally expressed genes in 394 triple negative breast cancers (TNBC). We identified 133 bimodally expressed probe sets (128 unique genes), 69 of these correlated to previously reported metagenes that define molecular subtypes within TNBC including basal-like, molecular-apocrine, claudin-low and immune cell rich subgroups but 64 probe sets showed no correlation with these features. Results The single most prominent functional group among these uncorrelated genes was the X chromosome derived Cancer/Testis Antigens (CT-X) including melanoma antigen family A (MAGE-A) and Cancer/Testis Antigens (CTAG). High expression of CT-X genes correlated with worse survival in multivariate analysis (HR 2.02, 95% CI 1.27–3.20; P = 0.003). The only other significant variable was lymph node status. The poor prognosis of patients with high MAGE-A expression was ameliorated by the concomitant high expression of immune cell metagenes (HR 1.87, 95% CI 0.96–3.64; P = 0.060), whereas the same immune metagene had lesser prognostic value in TNBC with low MAGE-A expression. Conclusions MAGE-A antigen defines a very aggressive subgroup of TNBC; particularly in the absence of immune infiltration in the tumour microenvironment. These observations suggest a therapeutic hypothesis; TNBC with MAGE-A expression may benefit the most from further augmentation of the immune response. Novel immune stimulatory drugs such as (anti-cytotoxic T-lymphocyte antigen-4 CTLA-4) directed therapies provide a realistic opportunity to directly test this hypothesis in the clinic.
doi_str_mv 10.1016/j.ejca.2011.06.025
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Oestrogen (ER) and human epidermal growth factor receptor 2 (HER2) receptors are strongly bimodally expressed genes in breast cancer. Material and methods We applied a novel method to identify bimodally expressed genes in 394 triple negative breast cancers (TNBC). We identified 133 bimodally expressed probe sets (128 unique genes), 69 of these correlated to previously reported metagenes that define molecular subtypes within TNBC including basal-like, molecular-apocrine, claudin-low and immune cell rich subgroups but 64 probe sets showed no correlation with these features. Results The single most prominent functional group among these uncorrelated genes was the X chromosome derived Cancer/Testis Antigens (CT-X) including melanoma antigen family A (MAGE-A) and Cancer/Testis Antigens (CTAG). High expression of CT-X genes correlated with worse survival in multivariate analysis (HR 2.02, 95% CI 1.27–3.20; P = 0.003). The only other significant variable was lymph node status. The poor prognosis of patients with high MAGE-A expression was ameliorated by the concomitant high expression of immune cell metagenes (HR 1.87, 95% CI 0.96–3.64; P = 0.060), whereas the same immune metagene had lesser prognostic value in TNBC with low MAGE-A expression. Conclusions MAGE-A antigen defines a very aggressive subgroup of TNBC; particularly in the absence of immune infiltration in the tumour microenvironment. These observations suggest a therapeutic hypothesis; TNBC with MAGE-A expression may benefit the most from further augmentation of the immune response. Novel immune stimulatory drugs such as (anti-cytotoxic T-lymphocyte antigen-4 CTLA-4) directed therapies provide a realistic opportunity to directly test this hypothesis in the clinic.</description><identifier>ISSN: 0959-8049</identifier><identifier>EISSN: 1879-0852</identifier><identifier>DOI: 10.1016/j.ejca.2011.06.025</identifier><identifier>PMID: 21741824</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Algorithms ; Bimodal expression ; Biological and medical sciences ; Breast Neoplasms - classification ; Breast Neoplasms - diagnosis ; Breast Neoplasms - genetics ; Breast Neoplasms - therapy ; Cancer Vaccines - therapeutic use ; Carcinoma - classification ; Carcinoma - diagnosis ; Carcinoma - genetics ; Carcinoma - therapy ; CT-X antigens ; Female ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Health Status Indicators ; Hematology, Oncology and Palliative Medicine ; Humans ; Immune therapy ; Immunotherapy - methods ; Medical sciences ; Melanoma-Specific Antigens - analysis ; Melanoma-Specific Antigens - genetics ; Melanoma-Specific Antigens - physiology ; Microarray Analysis ; Middle Aged ; Pharmacology. Drug treatments ; Prognostic markers ; Receptor, ErbB-2 - genetics ; Receptor, ErbB-2 - metabolism ; Receptors, Estrogen - genetics ; Receptors, Estrogen - metabolism ; Receptors, Progesterone - genetics ; Receptors, Progesterone - metabolism ; Subtypes of breast cancer ; Tumors</subject><ispartof>European journal of cancer (1990), 2012-01, Vol.48 (1), p.12-23</ispartof><rights>Elsevier Ltd</rights><rights>2011 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><rights>Copyright © 2011 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c539t-4c927c36f92207f02cd44d4878c9b1cbd95a66c974c497e0c78b5ec908875fbc3</citedby><cites>FETCH-LOGICAL-c539t-4c927c36f92207f02cd44d4878c9b1cbd95a66c974c497e0c78b5ec908875fbc3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,778,782,27911,27912</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=25403785$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21741824$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Karn, Thomas</creatorcontrib><creatorcontrib>Pusztai, Lajos</creatorcontrib><creatorcontrib>Ruckhäberle, Eugen</creatorcontrib><creatorcontrib>Liedtke, Cornelia</creatorcontrib><creatorcontrib>Müller, Volkmar</creatorcontrib><creatorcontrib>Schmidt, Marcus</creatorcontrib><creatorcontrib>Metzler, Dirk</creatorcontrib><creatorcontrib>Wang, Jing</creatorcontrib><creatorcontrib>Coombes, Kevin R</creatorcontrib><creatorcontrib>Gätje, Regine</creatorcontrib><creatorcontrib>Hanker, Lars</creatorcontrib><creatorcontrib>Solbach, Christine</creatorcontrib><creatorcontrib>Ahr, Andre</creatorcontrib><creatorcontrib>Holtrich, Uwe</creatorcontrib><creatorcontrib>Rody, Achim</creatorcontrib><creatorcontrib>Kaufmann, Manfred</creatorcontrib><title>Melanoma antigen family A identified by the bimodality index defines a subset of triple negative breast cancers as candidates for immune response augmentation</title><title>European journal of cancer (1990)</title><addtitle>Eur J Cancer</addtitle><description>Abstract Background Molecular markers displaying bimodal expression distribution can reveal distinct disease subsets and may serve as prognostic or predictive markers or represent therapeutic targets. Oestrogen (ER) and human epidermal growth factor receptor 2 (HER2) receptors are strongly bimodally expressed genes in breast cancer. Material and methods We applied a novel method to identify bimodally expressed genes in 394 triple negative breast cancers (TNBC). We identified 133 bimodally expressed probe sets (128 unique genes), 69 of these correlated to previously reported metagenes that define molecular subtypes within TNBC including basal-like, molecular-apocrine, claudin-low and immune cell rich subgroups but 64 probe sets showed no correlation with these features. Results The single most prominent functional group among these uncorrelated genes was the X chromosome derived Cancer/Testis Antigens (CT-X) including melanoma antigen family A (MAGE-A) and Cancer/Testis Antigens (CTAG). High expression of CT-X genes correlated with worse survival in multivariate analysis (HR 2.02, 95% CI 1.27–3.20; P = 0.003). The only other significant variable was lymph node status. The poor prognosis of patients with high MAGE-A expression was ameliorated by the concomitant high expression of immune cell metagenes (HR 1.87, 95% CI 0.96–3.64; P = 0.060), whereas the same immune metagene had lesser prognostic value in TNBC with low MAGE-A expression. Conclusions MAGE-A antigen defines a very aggressive subgroup of TNBC; particularly in the absence of immune infiltration in the tumour microenvironment. These observations suggest a therapeutic hypothesis; TNBC with MAGE-A expression may benefit the most from further augmentation of the immune response. Novel immune stimulatory drugs such as (anti-cytotoxic T-lymphocyte antigen-4 CTLA-4) directed therapies provide a realistic opportunity to directly test this hypothesis in the clinic.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Algorithms</subject><subject>Bimodal expression</subject><subject>Biological and medical sciences</subject><subject>Breast Neoplasms - classification</subject><subject>Breast Neoplasms - diagnosis</subject><subject>Breast Neoplasms - genetics</subject><subject>Breast Neoplasms - therapy</subject><subject>Cancer Vaccines - therapeutic use</subject><subject>Carcinoma - classification</subject><subject>Carcinoma - diagnosis</subject><subject>Carcinoma - genetics</subject><subject>Carcinoma - therapy</subject><subject>CT-X antigens</subject><subject>Female</subject><subject>Gene Expression Profiling</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Health Status Indicators</subject><subject>Hematology, Oncology and Palliative Medicine</subject><subject>Humans</subject><subject>Immune therapy</subject><subject>Immunotherapy - methods</subject><subject>Medical sciences</subject><subject>Melanoma-Specific Antigens - analysis</subject><subject>Melanoma-Specific Antigens - genetics</subject><subject>Melanoma-Specific Antigens - physiology</subject><subject>Microarray Analysis</subject><subject>Middle Aged</subject><subject>Pharmacology. Drug treatments</subject><subject>Prognostic markers</subject><subject>Receptor, ErbB-2 - genetics</subject><subject>Receptor, ErbB-2 - metabolism</subject><subject>Receptors, Estrogen - genetics</subject><subject>Receptors, Estrogen - metabolism</subject><subject>Receptors, Progesterone - genetics</subject><subject>Receptors, Progesterone - metabolism</subject><subject>Subtypes of breast cancer</subject><subject>Tumors</subject><issn>0959-8049</issn><issn>1879-0852</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNp9ksGOFCEURStG4_SM_oALw8boplugqAISM8lk4qjJGBfqmlDwaGmroAVqYv-M3yqVbjVxMSsIOfc-cu9rmmcEbwgm_evdBnZGbygmZIP7Dabdg2ZFBJdrLDr6sFlh2cm1wEyeNec57zDGXDD8uDmjhDMiKFs1vz7CqEOcNNKh-C0E5PTkxwO6Qt5CfXIeLBoOqHwDNPgpWj36ckA-WPiJLDgfICON8jxkKCg6VJLfj4ACbHXxd1WUQOeCjA4GUkXzcrXe6lKFLibkp2kOgBLkfQwZkJ63U51c1TE8aR45PWZ4ejovmq83b79cv1_ffnr34frqdm26VpY1M5Jy0_ZOUoq5w9RYxiwTXBg5EDNY2em-N5IzwyQHbLgYOjASC8E7N5j2onl59N2n-GOGXNTks4GxZgNxzkoSIlvMO17JV_eSBFdTxrnoKkqPqEkx5wRO7ZOfdDpUSC0Nqp1aGlRLgwr3qjZYRc9P_vMwgf0r-VNZBV6cAJ2NHl2qwfr8j-sYbo_T3xw5qLndeUgqGw-1BOsTmKJs9Pf_4_I_uRl98HXidzhA3sU5hdqIIipThdXnZdeWVSM1AEYlaX8DitTQ3w</recordid><startdate>20120101</startdate><enddate>20120101</enddate><creator>Karn, Thomas</creator><creator>Pusztai, Lajos</creator><creator>Ruckhäberle, Eugen</creator><creator>Liedtke, Cornelia</creator><creator>Müller, Volkmar</creator><creator>Schmidt, Marcus</creator><creator>Metzler, Dirk</creator><creator>Wang, Jing</creator><creator>Coombes, Kevin R</creator><creator>Gätje, Regine</creator><creator>Hanker, Lars</creator><creator>Solbach, Christine</creator><creator>Ahr, Andre</creator><creator>Holtrich, Uwe</creator><creator>Rody, Achim</creator><creator>Kaufmann, Manfred</creator><general>Elsevier Ltd</general><general>Elsevier</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>7T5</scope><scope>H94</scope><scope>7X8</scope></search><sort><creationdate>20120101</creationdate><title>Melanoma antigen family A identified by the bimodality index defines a subset of triple negative breast cancers as candidates for immune response augmentation</title><author>Karn, Thomas ; Pusztai, Lajos ; Ruckhäberle, Eugen ; Liedtke, Cornelia ; Müller, Volkmar ; Schmidt, Marcus ; Metzler, Dirk ; Wang, Jing ; Coombes, Kevin R ; Gätje, Regine ; Hanker, Lars ; Solbach, Christine ; Ahr, Andre ; Holtrich, Uwe ; Rody, Achim ; Kaufmann, Manfred</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c539t-4c927c36f92207f02cd44d4878c9b1cbd95a66c974c497e0c78b5ec908875fbc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Algorithms</topic><topic>Bimodal expression</topic><topic>Biological and medical sciences</topic><topic>Breast Neoplasms - classification</topic><topic>Breast Neoplasms - diagnosis</topic><topic>Breast Neoplasms - genetics</topic><topic>Breast Neoplasms - therapy</topic><topic>Cancer Vaccines - therapeutic use</topic><topic>Carcinoma - classification</topic><topic>Carcinoma - diagnosis</topic><topic>Carcinoma - genetics</topic><topic>Carcinoma - therapy</topic><topic>CT-X antigens</topic><topic>Female</topic><topic>Gene Expression Profiling</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Health Status Indicators</topic><topic>Hematology, Oncology and Palliative Medicine</topic><topic>Humans</topic><topic>Immune therapy</topic><topic>Immunotherapy - methods</topic><topic>Medical sciences</topic><topic>Melanoma-Specific Antigens - analysis</topic><topic>Melanoma-Specific Antigens - genetics</topic><topic>Melanoma-Specific Antigens - physiology</topic><topic>Microarray Analysis</topic><topic>Middle Aged</topic><topic>Pharmacology. Drug treatments</topic><topic>Prognostic markers</topic><topic>Receptor, ErbB-2 - genetics</topic><topic>Receptor, ErbB-2 - metabolism</topic><topic>Receptors, Estrogen - genetics</topic><topic>Receptors, Estrogen - metabolism</topic><topic>Receptors, Progesterone - genetics</topic><topic>Receptors, Progesterone - metabolism</topic><topic>Subtypes of breast cancer</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Karn, Thomas</creatorcontrib><creatorcontrib>Pusztai, Lajos</creatorcontrib><creatorcontrib>Ruckhäberle, Eugen</creatorcontrib><creatorcontrib>Liedtke, Cornelia</creatorcontrib><creatorcontrib>Müller, Volkmar</creatorcontrib><creatorcontrib>Schmidt, Marcus</creatorcontrib><creatorcontrib>Metzler, Dirk</creatorcontrib><creatorcontrib>Wang, Jing</creatorcontrib><creatorcontrib>Coombes, Kevin R</creatorcontrib><creatorcontrib>Gätje, Regine</creatorcontrib><creatorcontrib>Hanker, Lars</creatorcontrib><creatorcontrib>Solbach, Christine</creatorcontrib><creatorcontrib>Ahr, Andre</creatorcontrib><creatorcontrib>Holtrich, Uwe</creatorcontrib><creatorcontrib>Rody, Achim</creatorcontrib><creatorcontrib>Kaufmann, Manfred</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Immunology Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>European journal of cancer (1990)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Karn, Thomas</au><au>Pusztai, Lajos</au><au>Ruckhäberle, Eugen</au><au>Liedtke, Cornelia</au><au>Müller, Volkmar</au><au>Schmidt, Marcus</au><au>Metzler, Dirk</au><au>Wang, Jing</au><au>Coombes, Kevin R</au><au>Gätje, Regine</au><au>Hanker, Lars</au><au>Solbach, Christine</au><au>Ahr, Andre</au><au>Holtrich, Uwe</au><au>Rody, Achim</au><au>Kaufmann, Manfred</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Melanoma antigen family A identified by the bimodality index defines a subset of triple negative breast cancers as candidates for immune response augmentation</atitle><jtitle>European journal of cancer (1990)</jtitle><addtitle>Eur J Cancer</addtitle><date>2012-01-01</date><risdate>2012</risdate><volume>48</volume><issue>1</issue><spage>12</spage><epage>23</epage><pages>12-23</pages><issn>0959-8049</issn><eissn>1879-0852</eissn><abstract>Abstract Background Molecular markers displaying bimodal expression distribution can reveal distinct disease subsets and may serve as prognostic or predictive markers or represent therapeutic targets. Oestrogen (ER) and human epidermal growth factor receptor 2 (HER2) receptors are strongly bimodally expressed genes in breast cancer. Material and methods We applied a novel method to identify bimodally expressed genes in 394 triple negative breast cancers (TNBC). We identified 133 bimodally expressed probe sets (128 unique genes), 69 of these correlated to previously reported metagenes that define molecular subtypes within TNBC including basal-like, molecular-apocrine, claudin-low and immune cell rich subgroups but 64 probe sets showed no correlation with these features. Results The single most prominent functional group among these uncorrelated genes was the X chromosome derived Cancer/Testis Antigens (CT-X) including melanoma antigen family A (MAGE-A) and Cancer/Testis Antigens (CTAG). High expression of CT-X genes correlated with worse survival in multivariate analysis (HR 2.02, 95% CI 1.27–3.20; P = 0.003). The only other significant variable was lymph node status. The poor prognosis of patients with high MAGE-A expression was ameliorated by the concomitant high expression of immune cell metagenes (HR 1.87, 95% CI 0.96–3.64; P = 0.060), whereas the same immune metagene had lesser prognostic value in TNBC with low MAGE-A expression. Conclusions MAGE-A antigen defines a very aggressive subgroup of TNBC; particularly in the absence of immune infiltration in the tumour microenvironment. These observations suggest a therapeutic hypothesis; TNBC with MAGE-A expression may benefit the most from further augmentation of the immune response. Novel immune stimulatory drugs such as (anti-cytotoxic T-lymphocyte antigen-4 CTLA-4) directed therapies provide a realistic opportunity to directly test this hypothesis in the clinic.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>21741824</pmid><doi>10.1016/j.ejca.2011.06.025</doi><tpages>12</tpages></addata></record>
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subjects Adult
Aged
Aged, 80 and over
Algorithms
Bimodal expression
Biological and medical sciences
Breast Neoplasms - classification
Breast Neoplasms - diagnosis
Breast Neoplasms - genetics
Breast Neoplasms - therapy
Cancer Vaccines - therapeutic use
Carcinoma - classification
Carcinoma - diagnosis
Carcinoma - genetics
Carcinoma - therapy
CT-X antigens
Female
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Health Status Indicators
Hematology, Oncology and Palliative Medicine
Humans
Immune therapy
Immunotherapy - methods
Medical sciences
Melanoma-Specific Antigens - analysis
Melanoma-Specific Antigens - genetics
Melanoma-Specific Antigens - physiology
Microarray Analysis
Middle Aged
Pharmacology. Drug treatments
Prognostic markers
Receptor, ErbB-2 - genetics
Receptor, ErbB-2 - metabolism
Receptors, Estrogen - genetics
Receptors, Estrogen - metabolism
Receptors, Progesterone - genetics
Receptors, Progesterone - metabolism
Subtypes of breast cancer
Tumors
title Melanoma antigen family A identified by the bimodality index defines a subset of triple negative breast cancers as candidates for immune response augmentation
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