Stefan Dentro | PhD Student

Dentro, Stefan

I am a PhD student shared between the Experimental Cancer Genetics and Cancer Genome Project at the Sanger Institute and Cancer Genomics at the Francis Crick Institute. My project revolves around understanding tumour evolution through sequencing data. I mainly work on computational and statistical methods that allow for reconstruction of the evolutionairy story contained within a tumour sequencing sample. These methods are applied within the International Cancer Genome Consortium pancancer project, as well as smaller data sets.

A tumour can be thought of as the result of a Darwinian evolutionary process. Over time changes in the genome and epigenome occur that allow certain cells to outcompete others in their local environment. When a tumour is sequenced it's genome contains most of these changes, but without the order in which they occurred. I work on methods that allow us to reconstruct the evolutionary story and with a tumours life history in hand one can perform tumour archeology to dig into the changes that shaped it.

My project consists of method development and subsequent application to large scale sequencing data sets. I work on a method called DPClust that can reconstruct tumour subpopulations (subclones) and order them in a phylogenetic tree. This involves Markov Chain Monte Carlo simulations where we iteratively obtain a model that explains the variant allele frequencies of observed point mutations. A pre-requisite of performing subclonal reconstruction is having accurate copy number. I'm therefore involved in the development of a subclonal copy number caller Battenberg.

I apply these methods to the 2750 genomes in the International Cancer Genome Consortium (ICGC) Pancancer Analysis of Whole Genomes project. I am part of the Tumour Heterogeneity and Evolution working group which consists of about 50 people representing 12 different labs from all over the globe. The 2750 genomes represent about 30 cancer types and have been submitted from all over the world to create the largest cancer sequencing data set to date. The aim of our working group is to profile heterogeneity in search of key events during cancer development within a cancer type and across cancer types.

Apart from the ICGC project I am involved in various other projects. These involve copy number analysis in Breast, Pancreatic and Prostate cancer, single cell analysis in Breast cancer and application of our evoltionary reconstruction to new Breast cancer genomes.

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Stefan's Timeline

Started Ph.D. at Wellcome Trust Sanger Institute


Obtained M.Sc. Computer Science - Bioinformatics from Delft University of Technology


Obtained B.Sc. Computer Science from Delft University of Technology


Bioinformatician at Free University Medical Center in Amsterdam