SMS scnews item created by Dario Strbenac at Fri 8 May 2020 0930
Type: Seminar
Distribution: World
Expiry: 12 May 2020
Calendar1: 11 May 2020 1300-1330
CalLoc1: Zoom https://uni-sydney.zoom.us/j/2706664626
Auth: dario@210-1-221-196-cpe.spintel.net.au (dstr7320) in SMS-WASM

# Statistical Bioinformatics Webinar: Vergara -- Evolution of Late-stage Metastatic Melanoma is Dominated by Tetraploidization and Aneuploidy

Australia has one of the highest incidences of melanoma in the world and it has been
referred to as our national cancer.  Survival rates for melanoma are poor if not caught
early.  Recently, understanding of the molecular events that dominate the landscape of
early disease has benefited from genomic sequencing, but how melanoma evolves into its
metastatic and lethal form is poorly understood.

To help rectify this, a rapid autopsy program, CASCADE (CAncer tiSsue Collection After
DEath) was established at the Peter MacCallum Cancer Centre that provides multi-region
sampling of metastases from patients at time of death.  We obtained sequencing data from
more than 70 samples from 13 patients, including WES and WGS.  The matricial nature of
this dataset prompted us to apply an analysis approach that builds on existing methods
and makes use of the multiple samples from each patient.

Our analysis reveals striking patterns in the evolution of lethal melanoma.  While early
melanomas have large numbers of single nucleotide variants, we generally observed
limited subsequent SNV and indel gain.  Rather, evolution was dominated by large-scale
copy number change including a remarkable level of loss of heterozygosity in some
patients.  In one case, multicore sampling revealed spatial heterogeneity in copy number
of the primary tumour.  Patterns of copy number change hinted that two mutational
processes, aneuploidy and genome doubling, were operating universally.  To test this we
developed a novel method that models these mechanisms using branching processes.

Our findings in lethal melanoma suggest possible biomarkers that might be useful
clinically in challenging settings where patients present significant clinical
heterogeneity such as stage III disease.  We are further developing these using a
training set of 55 sequencing datasets from primary disease.


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