Recurrent somatic mutations reveal new insights into consequences of mutagenic processes in cancer.

ABSTRACT: The sheer size of the human genome makes it improbable that identical somatic mutations at the exact same position are observed in multiple tumours solely by chance. The scarcity of cancer driver mutations also precludes positive selection as the sole explanation. Therefore, recurrent mutations may be highly informative of characteristics of mutational processes. To explore the potential, we use recurrence as a starting point to cluster >2,500 whole genomes of a pan-cancer cohort. We describe each genome with 13 recurrence-based and 29 general mutational features. Using principal component analysis we reduce the dimensionality and create independent features. We apply hierarchical clustering to the first 18 principal components followed by k-means clustering. We show that the resulting 16

SUBMITTER: Stobbe MD 

PROVIDER: S-EPMC6901237 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature