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

Wei Jiao, Gurnit Atwal, Paz Polak, Rosa Karlic, Edwin Cuppen, Fatima Al-Shahrour, Peter J Bailey, Andrew V Biankin, Paul C Boutros, Peter J Campbell, David K Chang, Susanna L Cooke, Vikram Deshpande, Bishoy M Faltas, William C Faquin, Levi Garraway, Gad Getz, Sean M Grimmond, Syed Haider, Katherine A Hoadley, Vera B Kaiser, Mamoru Kato, Kirsten Kübler, Alexander J Lazar, Constance H Li … & Christian von Mering
In cancer, the primary tumour’s organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24...
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