Biomarkers of residual disease, disseminated tumor cells, and metastases in the MMTV-PyMT breast cancer model.
Cancer metastases arise in part from disseminated tumor cells originating from the primary tumor and from residual disease persisting after therapy. The identification of biomarkers on micro-metastases, disseminated tumors, and residual disease may yield novel tools for early detection and treatment...
Guardado en:
Autores principales: | Christian Franci, Jenny Zhou, Zhaoshi Jiang, Zora Modrusan, Zinaida Good, Erica Jackson, Hosein Kouros-Mehr |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2013
|
Materias: | |
Acceso en línea: | https://doaj.org/article/82ac3cf886084e00ac9dd826fcb44bab |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Loss of sphingosine kinase 1 increases lung metastases in the MMTV-PyMT mouse model of breast cancer.
por: Fabiola N Velazquez, et al.
Publicado: (2021) -
Apc mutation enhances PyMT-induced mammary tumorigenesis.
por: Jenifer R Prosperi, et al.
Publicado: (2011) -
Author Correction: PyMT-1099, a versatile murine cell model for EMT in breast cancer
por: Meera Saxena, et al.
Publicado: (2020) -
pyProGA-A PyMOL plugin for protein residue network analysis.
por: Vladimir Sladek, et al.
Publicado: (2021) -
pyGRETA, pyCLARA, pyPRIMA: A pre-processing suite to generate flexible model regions for energy system models
por: Kais Siala, et al.
Publicado: (2021)