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. 2017 Apr 4:5:e3166.
doi: 10.7717/peerj.3166. eCollection 2017.

Prioritisation of structural variant calls in cancer genomes

Miika J Ahdesmäki  1 , Brad A Chapman  2 , Pablo Cingolani  3 , Oliver Hofmann  4 , Aleksandr Sidoruk  5 , Zhongwu Lai  6 , Gennadii Zakharov  7 , Mikhail Rodichenko  8 , Mikhail Alperovich  8 , David Jenkins  9 , T Hedley Carr  1 , Daniel Stetson  6 , Brian Dougherty  6 , J Carl Barrett  6 , Justin H Johnson  6
Affiliations

Prioritisation of structural variant calls in cancer genomes

Miika J Ahdesmäki et al. PeerJ. .

Abstract

Sensitivity of short read DNA-sequencing for gene fusion detection is improving, but is hampered by the significant amount of noise composed of uninteresting or false positive hits in the data. In this paper we describe a tiered prioritisation approach to extract high impact gene fusion events from existing structural variant calls. Using cell line and patient DNA sequence data we improve the annotation and interpretation of structural variant calls to best highlight likely cancer driving fusions. We also considerably improve on the automated visualisation of the high impact structural variants to highlight the effects of the variants on the resulting transcripts. The resulting framework greatly improves on readily detecting clinically actionable structural variants.

Keywords: Annotation; Gene fusion; Oncology; Prioritisation; Structural variation; Visualisation.

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Conflict of interest statement

Miika J. Ahdesmäki, Zhongwu Lai, T. Hedley Carr, Daniel Stetson, Brian Dougherty, J. Carl Barrett and Justin H. Johnson are employees of AstraZeneca Plc. Aleksandr Sidoruk, Gennadii Zakharov, Mikhail Rodichenko and Mikhail Alperovich are employees of EPAM Systems Inc. Pablo Cingolani is an employee of Kew Inc.

Figures

Figure 1
Figure 1. Binning of structural variants into 3 priorities.
Figure 2
Figure 2. Prioritised SV call concordance.
The true positives are concordantly detected in addition to private (non-replicable) false positives. (A), (B) and (C) correspond to HDC134P (EML4-ALK), HDC140P (CCDC6-RET and RET-chr13), and HDC141P (SLC34A2-ROS1), respectively.
Figure 3
Figure 3. Svviz output for the FGFR3-TACC3 fusion (tandem duplication) in the RT4 cell line.
Read evidence is shown for both how the last intron of FGFR3 is fused to an exon of TACC3 as well as for the reference alleles.
Figure 4
Figure 4. FGFR3-TACC3 tandem duplication fusion exon level visualisation in the New Genome Browser.
Protein domains and exons affected by the structural variant are highlighted in colours. (A) shows the effect of the fusion and (B) the read evidence for the event at both breakpoints.
Figure 5
Figure 5. ROS1-SLC34A2 interchromosomal translocation fusion.
(A) shows the effect of the fusion and (B) the read evidence for the event at both breakpoints.
Figure 6
Figure 6. EML4-ALK inversion fusion.
(A) shows the effect of the fusion and (B) the read evidence for the event at both breakpoints.
See this image and copyright information in PMC

References

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