Bioinformatics Seminar
Time:
Venue: Na
6 June 2017
NaSVclone: inferring structural variant cancer cell fraction
Marek CmeroWEHI Bioinformatics
Understanding intra-tumour heterogeneity has fundamental implications for the treatment and prognostication of cancer. Many approaches have arisen for inferring the evolutionary dynamics and clonality of tumour cell populations from point-mutation and copy-number data. However ; currently no methods exist that fully incorporate structural variation (SV) and thus balanced rearrangements are not considered ; despite being important drivers in particular cancers such as prostate.
To address this gap ; we present SVclone ; a computational method for inferring the cancer cell fraction of structural variant breakpoints from whole-genome sequencing data. We validate our approach using simulated and real tumour samples ; and demonstrate its utility on 2 ;658 whole-genome sequenced tumours. We find a subset of cases with decreased overall survival that have subclonally enriched copy-number neutral rearrangements ; an observation that could not have been discovered with currently available methods.;