Accurate Discrimination of 23 Major Cancer Types via Whole Genome Somatic Mutation Patterns

Jiao, W.; Polak, P.; Karlic, R.; Getz, G.; Stein, L. D.; PCAWG Pathology and Clinical Correlates Working Gr,; ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net,

doi:10.1101/214494

bioRxiv · 10.1101/214494

Accurate Discrimination of 23 Major Cancer Types via Whole Genome Somatic Mutation Patterns

Jiao, W.·Polak, P.·Karlic, R.·Getz, G.·Stein, L. D.·PCAWG Pathology and Clinical Correlates Working Gr,·ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net,

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Abstract

The two strongest factors predicting a human cancers clinical behaviour are the primary tumours anatomic organ of origin and its histopathology. However, roughly 3% of the time a cancer presents with metastatic disease and no primary can be determined even after a thorough radiological survey. A related dilemma arises when a radiologically defined mass is sampled by cytology yielding cancerous cells, but the cytologist cannot distinguish between a primary tumour and a metastasis from elsewhere.\n\nHere we use whole genome sequencing (WGS) data from the ICGC/TCGA PanCancer Analysis of Whole Genomes (PCAWG) project to develop a machine learning classifier able to accurately distinguish among 23 major cancer types using information derived from somatic mutations alone. This demonstrates the feasibility of automated cancer type discrimination based on next-generation sequencing of clinical samples. In addition, this work opens the possibility of determining the origin of tumours detected by the emerging technology of deep sequencing of circulating cell-free DNA in blood plasma.

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Jiao, W., Polak, P., Karlic, R., Getz, G., Stein, L. D., PCAWG Pathology and Clinical Correlates Working Gr,, ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net,. 2017-11-05. Accurate Discrimination of 23 Major Cancer Types via Whole Genome Somatic Mutation Patterns. https://doi.org/10.1101/214494

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