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

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

Identifying driver genes in unstable, heterogenous tumour types can be challenging. Here, Mourikis, Benedetti, Foxall and colleagues present a machine learning algorithm to tackle this problem in esophageal adenocarcinoma.

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Bibliographic Details
Main Authors: Thanos P. Mourikis, Lorena Benedetti, Elizabeth Foxall, Damjan Temelkovski, Joel Nulsen, Juliane Perner, Matteo Cereda, Jesper Lagergren, Michael Howell, Christopher Yau, Rebecca C. Fitzgerald, Paola Scaffidi, The Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium, Francesca D. Ciccarelli
Format: article
Language:EN
Published: Nature Portfolio 2019
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Science
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Online Access:https://doaj.org/article/6525c04e989d4f92801eb2e25637bf6b
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Internet

https://doaj.org/article/6525c04e989d4f92801eb2e25637bf6b

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