The document presents a framework developed to detect clinically actionable somatic structural aberrations from targeted sequencing data, utilizing algorithms like delly for high sensitivity and specificity. The study highlights the ability to identify various structural genetic alterations in tumors, which could serve as targets for personalized cancer therapies. A significant number of functional structural aberrations were found across numerous clinical samples, demonstrating the potential of the method in enhancing molecular diagnostics.

1. Detecting clinically actionable somatic structural
aberrations from targeted sequencing data
Ronak H. Shah1, Ahmet Zehir1, Raghu Chandramohan1, Talia Mitchell3, Wei Song1, Alifya Oultache1, Ryma Benayed1, Meera Hameed1,
Khedoudja Nafa1, Donavan T. Cheng1, Maria E. Arcila1, Marc Ladanyi1,2, Michael F. Berger1,2
1Department of Pathology, 2Human Oncology and Pathogenesis Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065,
USA, 3The Jackson Laboratory, Farmington, CT 06032, USA
Background Results
Structural aberrations including deletions, insertions, inversions,
tandem duplications, translocations, and more complex
rearrangements constitute a frequent type of alteration in human
tumors. Here, we sought to explore the potential to discover such
events from targeted DNA sequence data in our CLIA-compliant
molecular diagnostics laboratory. To detect somatic structural
aberrations in individual tumors, we have developed an analytic
framework in Perl & Python to detect these events in data
generated by a hybridization capture-based, targeted sequencing
clinical assay (MSK-IMPACT1), which can reveal structural
rearrangements as small as 500bp.
Multiple Structural Variant (SV) calling algorithms such as DELLY2,
PeSV-Fisher3, Meerkat4, GASV5, GASV-Pro6 & Break-Dancer7 were
tested against a true positive data set generated using MSK-IMPACT,
a custom capture-based test involving all coding exons
and selected introns of 341 cancer associated genes, for
assessment of sensitivity and specificity. MSK-IMPACT includes
probes designed to capture 33 introns of 14 recurrently
rearranged genes in solid tumors. Algorithms were chosen for
their ability to call structural aberrations using a tumor-normal
pair approach, where a tumor sample is processed with its
matched normal to distinguish somatic structural alterations from
germline variants as well as false positive events, such as
systematic sequencing and mapping artifacts. We selected DELLY
for our final pipeline, which utilizes paired-read & split-read
support to nominate rearrangement breakpoints. Candidate
structural aberrations were filtered, annotated using in-house
tools, and manually reviewed using Integrated Genomics Viewer
(IGV).
Targeted Sequencing
Results
translocatio
n
translocatio
n
chr 6 chr 4
SLC34A2 ROS1
SLC34A2 30 31 32 ROS1
Image 5: ROS1-SLC34A2 fusion detected as translocation and ROS1
inversion, with 3% of reads supporting the fusion in patient.
Conclusion
Hybridize & select
(NimbleGen SeqCap:
IMPACT Assay)
Overview of the Framework
Crizotinib
initiated
02/2014
We have developed a framework capable of calling structural
aberrations from capture-based targeted sequencing data with
high sensitivity and specificity. Some of these structural
aberrations represent important targets for personalized cancer
therapies.
1. Won HH, Scott SN, Brannon AR, Shah RH, Berger MF. Detecting
somatic genetic alterations in tumor specimens by exon capture
and massively parallel sequencing. J Vis Exp 2013:e50710.
2. Rausch T, Zichner T, Schlattl A, Stutz AM, Benes V, Korbel JO.
DELLY: structural variant discovery by integrated paired-end and
split-read analysis. Bioinformatics 2012; 28:i333-i9.
3. Escaramis G, Tornador C, Bassaganyas L, Rabionet R, Tubio JM,
Martinez-Fundichely A, et al. PeSV-Fisher: identification of
somatic and non-somatic structural variants using next
generation sequencing data. PLoS One 2013; 8:e63377.
4. Yang L, Luquette LJ, Gehlenborg N, Xi R, Haseley PS, Hsieh CH,
et al. Diverse mechanisms of somatic structural variations in
human cancer genomes. Cell 2013; 153:919-29.
5. Sindi S, Helman E, Bashir A, Raphael BJ. A geometric approach
for classification and comparison of structural variants.
Bioinformatics 2009; 25:i222-30.
6. Sindi SS, Onal S, Peng LC, Wu HT, Raphael BJ. An integrative
probabilistic model for identification of structural variation in
sequencing data. Genome Biol 2012; 13:R22.
7. Chen K, Wallis JW, McLellan MD, Larson DE, Kalicki JM, Pohl CS,
et al. BreakDancer: an algorithm for high-resolution mapping of
genomic structural variation. Nat Methods 2009; 6:677-81.
Acknowledgements
Introduction
Methods
Prepare 24-
48 libraries
Probes for 341
cancer genes
Sequence to 500-
1000X (HiSeq 2500)
Align to genome & analyze
98% of targets at
>50% of median
99% of targets at
>20% of median
References
Berger Lab & Diagnostic Molecular Pathology Laboratory
Validation
Gene Events Partners
ALK 14 EML4
RET 4 KIF5B
ROS 3 CD74,SLC34A2
FGFR3 2 TACC3
EWSR1 7 FLI1, WT1
EGFR vIII Deletion 14
In total we found 118 functional and non-functional structural
aberrations out of 270 unique validation samples.
Examples
Tumor
Normal
Image 1: EML4-Alk fusion detected as inversion with 3% of reads supporting
the fusion in patient having lung cancer.
Tumor
Normal
Image 2: RET-CCDC6 fusion detected as inversion with 10% of reads
supporting the fusion in patient having thyroid cancer.
Tumor
Normal
Image 3: CD74-ROS1 fusion detected as translocation with 5% of reads
supporting the in-frame fusion in patient having lung cancer.
Tumor
Normal
Image 4: EGFR vIII deletion detected 10% of reads supporting the deletion
of exon 2 to exon 8 in-frame in patient having glioblastoma.
Clinical
Gene Events Partners
ALK 3 EML4
RET 10 CCD6, KIF5B
ROS 9 CD74,SLC34A2
FGFR3 2 TACC3
EWSR1 9 FLI1, WT1
TMPRSS2 5 ERG
EGFR vIII Deletion 6
In total we have found > 70 functional structural aberrations out
of > 1300 clinical samples.
Clinical Example
• 58/F never smoker
• Metastatic cancer involving liver, bone, brain: diagnosed 6/2013
• Treatment 7/2013-12/2013
• carboplatin/pemetrexed/bevacizumab x 4 cycles
• pemetrexed/bevacizumab maintenance
• Previous molecular testing negative for known drivers
• Sequenom negative
• Sizing assays for EGFR/ERBB2 negative
• Tissue quality inadequate for FISH testing
inversion
ROS1 SLC34A2
1 2 3 4
28 29 30
1 2 3 4
25 26 27 28 29 30
3’ probe ROS1 5’ probe ROS1 break
apart
Image 6: FISH Confirmation: ROS1
6q22 rearrangement in 54% of
interphase cells analyzed
0 weeks
4 weeks
Image 7: Minor radiographic
response: decreased right lower lobe
mass. Clinical Response:
Improvement in bone pain and
shortness of breath
Table 1: Number of known events found in current validation datasets.
Table 2: Number of known events found in current clinical datasets.
Median Coverage for the
target regions
Median Normalized Coverage
Fraction of Exons