Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma

The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damagin...

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Detalles Bibliográficos
Autores principales: Mourikis, Thanos P., Benedetti, Lorena, Foxall, Elizabeth, Temelkovski, Damjan, Nulsen, Joel, Perner, Juliane, Cereda, Matteo, Lagergren, Jesper, Howell, Michael, Yau, Christopher, Fitzgerald, Rebecca C., Scaffidi, Paola, Ciccarelli, Francesca D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6629660/
https://www.ncbi.nlm.nih.gov/pubmed/31308377
http://dx.doi.org/10.1038/s41467-019-10898-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6629660/
https://www.ncbi.nlm.nih.gov/pubmed/31308377
http://dx.doi.org/10.1038/s41467-019-10898-3

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