Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications

Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study...
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Autor*in:	Jézéquel, Pascal [verfasserIn] Kerdraon, Olivier Hondermarck, Hubert Guérin-Charbonnel, Catherine Lasla, Hamza Gouraud, Wilfried Canon, Jean-Luc Gombos, Andrea Dalenc, Florence Delaloge, Suzette Lemonnier, Jérôme Loussouarn, Delphine Verrièle, Véronique Campone, Mario

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Breast cancer Triple-negative Transcriptomics Molecular subtypes Immunome Tertiary lymphoid structures Neurogenesis

Anmerkung:	© The Author(s). 2019

Übergeordnetes Werk:	Enthalten in: Breast cancer research - London : BioMed Central, 1999, 21(2019), 1 vom: 17. Mai
Übergeordnetes Werk:	volume:21 ; year:2019 ; number:1 ; day:17 ; month:05

Links:	Volltext

DOI / URN:	10.1186/s13058-019-1148-6

Katalog-ID:	SPR029962056

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520			\|a Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Conclusion Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies.
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allfields	10.1186/s13058-019-1148-6 doi (DE-627)SPR029962056 (SPR)s13058-019-1148-6-e DE-627 ger DE-627 rakwb eng Jézéquel, Pascal verfasserin aut Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Conclusion Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies. Breast cancer (dpeaa)DE-He213 Triple-negative (dpeaa)DE-He213 Transcriptomics (dpeaa)DE-He213 Molecular subtypes (dpeaa)DE-He213 Immunome (dpeaa)DE-He213 Tertiary lymphoid structures (dpeaa)DE-He213 Neurogenesis (dpeaa)DE-He213 Kerdraon, Olivier aut Hondermarck, Hubert aut Guérin-Charbonnel, Catherine aut Lasla, Hamza aut Gouraud, Wilfried aut Canon, Jean-Luc aut Gombos, Andrea aut Dalenc, Florence aut Delaloge, Suzette aut Lemonnier, Jérôme aut Loussouarn, Delphine aut Verrièle, Véronique aut Campone, Mario aut Enthalten in Breast cancer research London : BioMed Central, 1999 21(2019), 1 vom: 17. Mai (DE-627)326645950 (DE-600)2041618-0 1465-542X nnns volume:21 year:2019 number:1 day:17 month:05 https://dx.doi.org/10.1186/s13058-019-1148-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2106 GBV_ILN_2232 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 21 2019 1 17 05
spelling	10.1186/s13058-019-1148-6 doi (DE-627)SPR029962056 (SPR)s13058-019-1148-6-e DE-627 ger DE-627 rakwb eng Jézéquel, Pascal verfasserin aut Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Conclusion Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies. Breast cancer (dpeaa)DE-He213 Triple-negative (dpeaa)DE-He213 Transcriptomics (dpeaa)DE-He213 Molecular subtypes (dpeaa)DE-He213 Immunome (dpeaa)DE-He213 Tertiary lymphoid structures (dpeaa)DE-He213 Neurogenesis (dpeaa)DE-He213 Kerdraon, Olivier aut Hondermarck, Hubert aut Guérin-Charbonnel, Catherine aut Lasla, Hamza aut Gouraud, Wilfried aut Canon, Jean-Luc aut Gombos, Andrea aut Dalenc, Florence aut Delaloge, Suzette aut Lemonnier, Jérôme aut Loussouarn, Delphine aut Verrièle, Véronique aut Campone, Mario aut Enthalten in Breast cancer research London : BioMed Central, 1999 21(2019), 1 vom: 17. Mai (DE-627)326645950 (DE-600)2041618-0 1465-542X nnns volume:21 year:2019 number:1 day:17 month:05 https://dx.doi.org/10.1186/s13058-019-1148-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2106 GBV_ILN_2232 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 21 2019 1 17 05
allfields_unstemmed	10.1186/s13058-019-1148-6 doi (DE-627)SPR029962056 (SPR)s13058-019-1148-6-e DE-627 ger DE-627 rakwb eng Jézéquel, Pascal verfasserin aut Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Conclusion Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies. Breast cancer (dpeaa)DE-He213 Triple-negative (dpeaa)DE-He213 Transcriptomics (dpeaa)DE-He213 Molecular subtypes (dpeaa)DE-He213 Immunome (dpeaa)DE-He213 Tertiary lymphoid structures (dpeaa)DE-He213 Neurogenesis (dpeaa)DE-He213 Kerdraon, Olivier aut Hondermarck, Hubert aut Guérin-Charbonnel, Catherine aut Lasla, Hamza aut Gouraud, Wilfried aut Canon, Jean-Luc aut Gombos, Andrea aut Dalenc, Florence aut Delaloge, Suzette aut Lemonnier, Jérôme aut Loussouarn, Delphine aut Verrièle, Véronique aut Campone, Mario aut Enthalten in Breast cancer research London : BioMed Central, 1999 21(2019), 1 vom: 17. Mai (DE-627)326645950 (DE-600)2041618-0 1465-542X nnns volume:21 year:2019 number:1 day:17 month:05 https://dx.doi.org/10.1186/s13058-019-1148-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2106 GBV_ILN_2232 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 21 2019 1 17 05
allfieldsGer	10.1186/s13058-019-1148-6 doi (DE-627)SPR029962056 (SPR)s13058-019-1148-6-e DE-627 ger DE-627 rakwb eng Jézéquel, Pascal verfasserin aut Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Conclusion Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies. Breast cancer (dpeaa)DE-He213 Triple-negative (dpeaa)DE-He213 Transcriptomics (dpeaa)DE-He213 Molecular subtypes (dpeaa)DE-He213 Immunome (dpeaa)DE-He213 Tertiary lymphoid structures (dpeaa)DE-He213 Neurogenesis (dpeaa)DE-He213 Kerdraon, Olivier aut Hondermarck, Hubert aut Guérin-Charbonnel, Catherine aut Lasla, Hamza aut Gouraud, Wilfried aut Canon, Jean-Luc aut Gombos, Andrea aut Dalenc, Florence aut Delaloge, Suzette aut Lemonnier, Jérôme aut Loussouarn, Delphine aut Verrièle, Véronique aut Campone, Mario aut Enthalten in Breast cancer research London : BioMed Central, 1999 21(2019), 1 vom: 17. Mai (DE-627)326645950 (DE-600)2041618-0 1465-542X nnns volume:21 year:2019 number:1 day:17 month:05 https://dx.doi.org/10.1186/s13058-019-1148-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2106 GBV_ILN_2232 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 21 2019 1 17 05
allfieldsSound	10.1186/s13058-019-1148-6 doi (DE-627)SPR029962056 (SPR)s13058-019-1148-6-e DE-627 ger DE-627 rakwb eng Jézéquel, Pascal verfasserin aut Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Conclusion Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies. Breast cancer (dpeaa)DE-He213 Triple-negative (dpeaa)DE-He213 Transcriptomics (dpeaa)DE-He213 Molecular subtypes (dpeaa)DE-He213 Immunome (dpeaa)DE-He213 Tertiary lymphoid structures (dpeaa)DE-He213 Neurogenesis (dpeaa)DE-He213 Kerdraon, Olivier aut Hondermarck, Hubert aut Guérin-Charbonnel, Catherine aut Lasla, Hamza aut Gouraud, Wilfried aut Canon, Jean-Luc aut Gombos, Andrea aut Dalenc, Florence aut Delaloge, Suzette aut Lemonnier, Jérôme aut Loussouarn, Delphine aut Verrièle, Véronique aut Campone, Mario aut Enthalten in Breast cancer research London : BioMed Central, 1999 21(2019), 1 vom: 17. Mai (DE-627)326645950 (DE-600)2041618-0 1465-542X nnns volume:21 year:2019 number:1 day:17 month:05 https://dx.doi.org/10.1186/s13058-019-1148-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2106 GBV_ILN_2232 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 21 2019 1 17 05
language	English
source	Enthalten in Breast cancer research 21(2019), 1 vom: 17. Mai volume:21 year:2019 number:1 day:17 month:05
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author	Jézéquel, Pascal
spellingShingle	Jézéquel, Pascal misc Breast cancer misc Triple-negative misc Transcriptomics misc Molecular subtypes misc Immunome misc Tertiary lymphoid structures misc Neurogenesis Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications
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topic_title	Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications Breast cancer (dpeaa)DE-He213 Triple-negative (dpeaa)DE-He213 Transcriptomics (dpeaa)DE-He213 Molecular subtypes (dpeaa)DE-He213 Immunome (dpeaa)DE-He213 Tertiary lymphoid structures (dpeaa)DE-He213 Neurogenesis (dpeaa)DE-He213
topic	misc Breast cancer misc Triple-negative misc Transcriptomics misc Molecular subtypes misc Immunome misc Tertiary lymphoid structures misc Neurogenesis
topic_unstemmed	misc Breast cancer misc Triple-negative misc Transcriptomics misc Molecular subtypes misc Immunome misc Tertiary lymphoid structures misc Neurogenesis
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title	Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications
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title_full	Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications
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title_sort	identification of three subtypes of triple-negative breast cancer with potential therapeutic implications
title_auth	Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications
abstract	Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Conclusion Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies. © The Author(s). 2019
abstractGer	Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Conclusion Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies. © The Author(s). 2019
abstract_unstemmed	Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Conclusion Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies. © The Author(s). 2019
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The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data (n = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. 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Identification of three subtypes of triple-negative breast cancer with potential therapeutic implications

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