Predictive value of angiogenesis-related gene profiling in patients with HER2-negative metastatic breast cancer treated with bevacizumab and weekly paclitaxel
Author
Mendiola, Marta; Martínez-Marín, Virginia; Herranz Barrera, Jesús




Entity
UAM. Departamento de Anatomía Patológica; UAM. Departamento de Medicina; Instituto de Investigación Sanitaria Hospital Universitario de La Paz (IdiPAZ)Publisher
Impact Journals LLCDate
2016-03-16Citation
Oncotarget 7.17 (2016): 24217-24227ISSN
1949-2553Funded by
This work was supported by a grant from the Independent Clinical Research Program (EC10-342), Independent Clinical Research Program (EC10-342), ISCIII (Instituto de Salud Carlos III), Spanish Ministry of Health, and funded also from Roche Farma S.A.U.Subjects
Metastatic breast carcinoma; Bevacizumab and weekly paclitaxel; Predictive; Angiogenesis; Gene expression; MedicinaAbstract
Bevacizumab plus weekly paclitaxel improves progression-free survival (PFS)
in HER2-negative metastatic breast cancer (mBC), but its use has been questioned
due to the absence of a predictive biomarker, lack of benefit in overall survival (OS)
and increased toxicity. We examined the baseline tumor angiogenic-related gene
expression of 60 patients with mBC with the aim of finding a signature that predicts
benefit from this drug.
Multivariate analysis by Lasso-penalized Cox regression generated two predictive
models: one, named G-model, including 11 genes, and the other one, named GCmodel,
including 13 genes plus 5 clinical covariates. Both models identified patients
with improved PFS (HR (Hazard Ratio) 2.57 and 4.04, respectively) and OS (HR 3.29
and 3.43, respectively). The G-model distinguished low and high risk patients in the
first 6 months, whereas the GC-model maintained significance over time
Files in this item
Google Scholar:Mendiola, Marta
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Martínez-Marín, Virginia
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Herranz Barrera, Jesús
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Heredia, Victoria
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Yébenes, Laura
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Zamora, Pilar
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Castelo Fernández, Beatriz
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Pinto, Álvaro
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Miguel, María
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Díaz, Esther
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Gámez, Angelo
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Fresno, Juan Ángel
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Ramírez de Molina, Ana
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Hardisson Hernáez, David Alonso
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Espinosa Arranz, Enrique
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Redondo Sánchez, Andrés
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