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Clinical outcomes based on multigene profiling in metastatic breast cancer patients

BACKGROUND: Identifying the clinical impact of recurrent mutations can help define their role in cancer. Here, we identify frequent hotspot mutations in metastatic breast cancer (MBC) patients and associate them with clinical outcomes. PATIENTS AND METHODS: Hotspot mutation testing was conducted in...

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Autores principales: Basho, Reva K., de Melo Gagliato, Debora, Ueno, Naoto T., Wathoo, Chetna, Chen, Huiqin, Shariati, Maryam, Wei, Caimiao, Alvarez, Ricardo H., Moulder, Stacy L., Sahin, Aysegul A., Roy-Chowdhuri, Sinchita, Chavez-MacGregor, Mariana, Litton, Jennifer K., Valero, Vincent, Luthra, Raja, Zeng, Jia, Shaw, Kenna R., Mendelsohn, John, Mills, Gordon B., Tripathy, Debu, Meric-Bernstam, Funda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5363515/
https://www.ncbi.nlm.nih.gov/pubmed/27806348
http://dx.doi.org/10.18632/oncotarget.12987
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author Basho, Reva K.
de Melo Gagliato, Debora
Ueno, Naoto T.
Wathoo, Chetna
Chen, Huiqin
Shariati, Maryam
Wei, Caimiao
Alvarez, Ricardo H.
Moulder, Stacy L.
Sahin, Aysegul A.
Roy-Chowdhuri, Sinchita
Chavez-MacGregor, Mariana
Litton, Jennifer K.
Valero, Vincent
Luthra, Raja
Zeng, Jia
Shaw, Kenna R.
Mendelsohn, John
Mills, Gordon B.
Tripathy, Debu
Meric-Bernstam, Funda
author_facet Basho, Reva K.
de Melo Gagliato, Debora
Ueno, Naoto T.
Wathoo, Chetna
Chen, Huiqin
Shariati, Maryam
Wei, Caimiao
Alvarez, Ricardo H.
Moulder, Stacy L.
Sahin, Aysegul A.
Roy-Chowdhuri, Sinchita
Chavez-MacGregor, Mariana
Litton, Jennifer K.
Valero, Vincent
Luthra, Raja
Zeng, Jia
Shaw, Kenna R.
Mendelsohn, John
Mills, Gordon B.
Tripathy, Debu
Meric-Bernstam, Funda
author_sort Basho, Reva K.
collection PubMed
description BACKGROUND: Identifying the clinical impact of recurrent mutations can help define their role in cancer. Here, we identify frequent hotspot mutations in metastatic breast cancer (MBC) patients and associate them with clinical outcomes. PATIENTS AND METHODS: Hotspot mutation testing was conducted in 500 MBC patients using an 11 gene (N = 126) and/or 46 or 50 gene (N = 391) panel. Patients were stratified by hormone receptor (HR) and human epidermal growth factor 2 (HER2) status. Clinical outcomes were retrospectively collected. RESULTS: Hotspot mutations were most frequently detected in TP53 (30%), PIK3CA (27%) and AKT1 (4%). Triple-negative breast cancer (TNBC) patients had the highest incidence of TP53 (58%) and the lowest incidence of PIK3CA (9%) mutations. TP53 mutation was associated with shorter relapse-free survival (RFS) (median 22 vs 42months; P < 0.001) and overall survival (OS) from diagnosis of distant metastatic disease (median 26 vs 51months; P < 0.001). Conversely, PIK3CA mutation was associated with a trend towards better clinical outcomes including RFS (median 41 vs 30months; P = 0.074) and OS (52 vs 40months; P = 0.066). In HR-positive patients, TP53 mutation was again associated with shorter RFS (median 30 vs 46months; P = 0.017) and OS (median 30 vs 55months; P = 0.001). When multivariable analysis was performed for RFS and OS, TP53 but not PIK3CA mutation remained a significant predictor of outcomes in the overall cohort and in HR-positive patients. CONCLUSIONS: Clinical hotspot sequencing identifies potentially actionable mutations. In this cohort, TP53 mutation was associated with worse clinical outcomes, while PIK3CA mutation did not remain a significant predictor of outcomes after multivariable analysis.
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spelling pubmed-53635152017-03-29 Clinical outcomes based on multigene profiling in metastatic breast cancer patients Basho, Reva K. de Melo Gagliato, Debora Ueno, Naoto T. Wathoo, Chetna Chen, Huiqin Shariati, Maryam Wei, Caimiao Alvarez, Ricardo H. Moulder, Stacy L. Sahin, Aysegul A. Roy-Chowdhuri, Sinchita Chavez-MacGregor, Mariana Litton, Jennifer K. Valero, Vincent Luthra, Raja Zeng, Jia Shaw, Kenna R. Mendelsohn, John Mills, Gordon B. Tripathy, Debu Meric-Bernstam, Funda Oncotarget Priority Research Paper BACKGROUND: Identifying the clinical impact of recurrent mutations can help define their role in cancer. Here, we identify frequent hotspot mutations in metastatic breast cancer (MBC) patients and associate them with clinical outcomes. PATIENTS AND METHODS: Hotspot mutation testing was conducted in 500 MBC patients using an 11 gene (N = 126) and/or 46 or 50 gene (N = 391) panel. Patients were stratified by hormone receptor (HR) and human epidermal growth factor 2 (HER2) status. Clinical outcomes were retrospectively collected. RESULTS: Hotspot mutations were most frequently detected in TP53 (30%), PIK3CA (27%) and AKT1 (4%). Triple-negative breast cancer (TNBC) patients had the highest incidence of TP53 (58%) and the lowest incidence of PIK3CA (9%) mutations. TP53 mutation was associated with shorter relapse-free survival (RFS) (median 22 vs 42months; P < 0.001) and overall survival (OS) from diagnosis of distant metastatic disease (median 26 vs 51months; P < 0.001). Conversely, PIK3CA mutation was associated with a trend towards better clinical outcomes including RFS (median 41 vs 30months; P = 0.074) and OS (52 vs 40months; P = 0.066). In HR-positive patients, TP53 mutation was again associated with shorter RFS (median 30 vs 46months; P = 0.017) and OS (median 30 vs 55months; P = 0.001). When multivariable analysis was performed for RFS and OS, TP53 but not PIK3CA mutation remained a significant predictor of outcomes in the overall cohort and in HR-positive patients. CONCLUSIONS: Clinical hotspot sequencing identifies potentially actionable mutations. In this cohort, TP53 mutation was associated with worse clinical outcomes, while PIK3CA mutation did not remain a significant predictor of outcomes after multivariable analysis. Impact Journals LLC 2016-10-28 /pmc/articles/PMC5363515/ /pubmed/27806348 http://dx.doi.org/10.18632/oncotarget.12987 Text en Copyright: © 2016 Basho et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Priority Research Paper
Basho, Reva K.
de Melo Gagliato, Debora
Ueno, Naoto T.
Wathoo, Chetna
Chen, Huiqin
Shariati, Maryam
Wei, Caimiao
Alvarez, Ricardo H.
Moulder, Stacy L.
Sahin, Aysegul A.
Roy-Chowdhuri, Sinchita
Chavez-MacGregor, Mariana
Litton, Jennifer K.
Valero, Vincent
Luthra, Raja
Zeng, Jia
Shaw, Kenna R.
Mendelsohn, John
Mills, Gordon B.
Tripathy, Debu
Meric-Bernstam, Funda
Clinical outcomes based on multigene profiling in metastatic breast cancer patients
title Clinical outcomes based on multigene profiling in metastatic breast cancer patients
title_full Clinical outcomes based on multigene profiling in metastatic breast cancer patients
title_fullStr Clinical outcomes based on multigene profiling in metastatic breast cancer patients
title_full_unstemmed Clinical outcomes based on multigene profiling in metastatic breast cancer patients
title_short Clinical outcomes based on multigene profiling in metastatic breast cancer patients
title_sort clinical outcomes based on multigene profiling in metastatic breast cancer patients
topic Priority Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5363515/
https://www.ncbi.nlm.nih.gov/pubmed/27806348
http://dx.doi.org/10.18632/oncotarget.12987
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