A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

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Detalles Bibliográficos
Autores principales: Wei Jiao, Gurnit Atwal, Paz Polak, Rosa Karlic, Edwin Cuppen, PCAWG Tumor Subtypes and Clinical Translation Working Group, Alexandra Danyi, Jeroen de Ridder, Carla van Herpen, Martijn P. Lolkema, Neeltje Steeghs, Gad Getz, Quaid Morris, Lincoln D. Stein, PCAWG Consortium
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/1eb66053b1d54801a9b93093526fbf22
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Descripción
Sumario:Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.