Dataset Information

Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing.

ABSTRACT:

Summary

Tumour evolution results in progressive cancer phenotypes such as metastatic spread and treatment resistance. To better treat cancers, we must characterize tumour evolution and the genetic events that confer progressive phenotypes. This is facilitated by high coverage genome or exome sequencing. However, the best approach by which, or indeed whether, these data can be used to accurately model and interpret underlying evolutionary dynamics is yet to be confirmed. Establishing this requires sequencing data from appropriately heterogeneous tumours in which the exact trajectory and combination of events occurring throughout its evolution are known. We therefore developed HeteroGenesis: a tool to generate realistically evolved tumour genomes, which can be sequenced using weighted-Wessim (w-Wessim), an in silico exome sequencing tool that we have adapted from previous methods. HeteroGenesis simulates more complex and realistic heterogeneous tumour genomes than existing methods, can model different evolutionary dynamics, and enables the creation of multi-region and longitudinal data.

Availability and implementation

HeteroGenesis and w-Wessim are freely available under the GNU General Public Licence from https://github.com/GeorgetteTanner, implemented in Python and supported on linux and MS Windows.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Tanner G

PROVIDER: S-EPMC6691334 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing.

Tanner Georgette G Westhead David R DR Droop Alastair A Stead Lucy F LF

Bioinformatics (Oxford, England) 20190801 16

<h4>Summary</h4>Tumour evolution results in progressive cancer phenotypes such as metastatic spread and treatment resistance. To better treat cancers, we must characterize tumour evolution and the genetic events that confer progressive phenotypes. This is facilitated by high coverage genome or exome sequencing. However, the best approach by which, or indeed whether, these data can be used to accurately model and interpret underlying evolutionary dynamics is yet to be confirmed. Establishing this ...[more]

PMID: 30615054

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Project description:BackgroundNext-generation sequencing is used in cancer research to identify somatic and germline mutations, which can predict sensitivity or resistance to therapies, and may be a useful tool to reveal drug repurposing opportunities between tumour types. Multigene panels are used in clinical practice for detecting targetable mutations. However, the value of clinical whole-exome sequencing (WES) and whole-genome sequencing (WGS) for cancer care is less defined, specifically as the majority of variants found using these technologies are of uncertain significance.Patients and methodsWe used the Cancer Genome Interpreter and WGS in 726 tumours spanning 10 cancer types to identify drug repurposing opportunities. We compare the ability of WGS to detect actionable variants, tumour mutation burden (TMB) and microsatellite instability (MSI) by using in silico down-sampled data to mimic WES, a comprehensive sequencing panel and a hotspot mutation panel.ResultsWe reveal drug repurposing opportunities as numerous biomarkers are shared across many solid tumour types. Comprehensive panels identify the majority of approved actionable mutations, with WGS detecting more candidate actionable mutations for biomarkers currently in clinical trials. Moreover, estimated values for TMB and MSI vary when calculated from WGS, WES and panel data, and are dependent on whether all mutations or only non-synonymous mutations were used. Our results suggest that TMB and MSI thresholds should not only be tumour-dependent, but also be sequencing platform-dependent.ConclusionsThere is a large opportunity to repurpose cancer drugs, and these data suggest that comprehensive sequencing is an invaluable source of information to guide clinical decisions by facilitating precision medicine and may provide a wealth of information for future studies. Furthermore, the sequencing and analysis approach used to estimate TMB may have clinical implications if a hard threshold is used to indicate which patients may respond to immunotherapy.

Dataset Information

Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing.

Summary

Availability and implementation

Supplementary information

Publications

Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing.

Similar Datasets

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