We have developed an amplicon-based NGS approach for FFPE samples that can detect SNVs, small mutations and LRs simultaneously. We have implemented a comprehensive bioinformatics algorithm that detects LRs at high sensitivity, even in the absence of control sample(s). This significantly reduces the cost and labor for BRCA1/2 genetic analyses.

1. MATERIALS AND METHODS – continued
The Oncomine™ BRCA Research Assay was designed to cover 100% of all 23 exons
of BRCA1 and 27 exons of BRCA2 with 263 different amplicons (targeted regions).
We have implemented a comprehensive bioinformatics algorithm that
detects LRs at high sensitivity, even in the absence of control
sample(s).
Qi, Rongsu., Scafe, Charles., Nistala, Goutam., Bee, G., Garg, N., Manivannan, M., Broomer, A., Mittal, V., Williams, P., Brinza, D., Hyland, F., Bishop, J., Sadis, S., Passkiewicz, B., Sherlock, J.
Thermo Fisher Scientific, 180 Oyster Point Blvd, South San Francisco, CA 94080
RESULTS
We implemented additional sample QC step to detect samples with large
overall amplicon coverage variations.
Table 1. Performance on simulation data.
Simulation of exon deletions: Of all exons of all samples, pick randomly 10% or 20%
of exons, divide counts for all the amplicons of that exon by 2.
Table 2. Performance on blood samples.
100% exon coverage across both BRCA 1 and 2 genes, with high uniformity and
read counts across all exons, allowing for over 99% confidence of detecting 5%
somatic variant.
A total of 10 cell line samples purchased from Coriell were tested. From all exons of all samples,
10% or 20% of exons were selected randomly to simulate heterozygous deletion. For exon
deletion simulation, the raw counts of all amplicons from that exon were divided by 2.
Performance was measured by per exon per sample.
Figure 3. Visualization plots showing large deletions, single exon
deletion, and multiple exon deletion from blood samples.
Boxplot of normalized count from all amplicons of each exon after re-normalization.
Boxplot of normalized count from all amplicons of each exon before and after re-normalization.
ABSTRACT
We have developed an amplicon-based NGS approach for FFPE
samples that can detect SNVs, small mutations and LRs
simultaneously. We have implemented a comprehensive
bioinformatics algorithm that detects LRs at high sensitivity, even in
the absence of control sample(s). This significantly reduces the cost
and labor for BRCA1/2 genetic analyses.
INTRODUCTION
Germline and somatic mutations in the BRCA1 and BRCA2 genes are
highly involved in hereditary and non-hereditary breast and ovarian
cancers. A test that detects these mutations from relevant FFPE
samples is tremendously. Large rearrangements (LRs) represent a
small, yet important portion of BRCA1/2 mutations, in addition to
single nucleotide mutations and small insertion/deletions. The sizes of
LRs make them difficult to detect using traditional sequencing
approaches thereby requiring additional tests such as multiplex
ligation dependent probe amplification (MLPA). Recently, several
reports have shown feasibility using amplicon-based massively
parallel sequencing methods to detect LRs simultaneous to small
mutations. However, these tests were either not designed for use with
FFPE samples, or lack data analysis methods optimized for such an
application and therefore fail to achieve the necessary sensitivity.
MATERIALS AND METHODS
Ion AmpliSeq™, a targeted, multiplexed amplification technology for
developing sequencing libraries, was used in combination with the Ion
PGM and Ion S5 sequencing platform.
CONCLUSIONS
We have developed an NGS assay and comprehensive data analysis
approach capable of detecting both small mutations and LRs
simultaneously from FFPE samples with high sensitivity and specificity.
REFERENCES
1. Ava Kwong, Jiawei Chen, Vivian Y. Shin, John C.W. Ho,
Fian B.F. Law, Chun Hang Au, Tsun-Leung Chan, Edmond S.K. Ma,
James M. Ford: The importance of analysis of long-range
rearrangement of BRCA1 and BRCA2 in genetic
diagnosis of familial breast cancer. Cancer Genetics 2015, 208:448–454
2. Lídia Feliubadaló, Adriana Lopez-Doriga, Ester Castellsagué, Jesús del Valle,
Mireia Menéndez, Eva Tornero, Eva Montes, Raquel Cuesta, Carolina Gómez,
Olga Campos, Marta Pineda, Sara González, Victor Moreno, Joan Brunet,
Ignacio Blanco, Eduard Serra, Gabriel Capellá and Conxi Lázaro:, Next-generation
sequencing meets genetic diagnostics: development of a comprehensive workflow for
the analysis of BRCA1 and BRCA2 genes, European Journal of Human Genetics 2013,
21:864–870
ACKNOWLEDGEMENTS
We thank our early access customers for sharing data with us.
© 2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are
the property of Thermo Fisher Scientific and its subsidiaries unless
otherwise specified.
A next Generation Sequencing Approach to Detect Large Rearrangements in BRCA1/2
Simultaneous to Small Mutation Detection from FFPE Research Samples
Thermo Fisher Scientific • 5791 Van Allen Way • Carlsbad, CA 92008 • www.lifetechnologies.com.
% exons
with deletion
TP FP TN FN
MISS-
NOCALL
NOCALL
%NOCAL
L
Sensi-vit
y
PPV
0 Original data 0 1 441 0 0 8 1.78% NA NA
10%
Simulation 1 43 2 400 1 1 4 0.89% 0.977 0.956
Simulation 2 45 0 395 0 0 0 0.00% 1 1
Simulation 3 44 3 395 0 1 8 1.78% 1 0.936
Simulation 4 44 3 392 0 0 1 0.23% 1 0.936
20 %
Simulation 1 82 4 347 4 2 3 0.68% 0.954 0.953
Simulation 2 88 0 353 1 1 8 1.78% 0.989 1
Simulation 3 75 4 343 9 3 9 2.05% 0.893 0.949
Simulation 4 85 1 352 1 1 1 0.23% 0.988 0.988
Sample
type
Total
sampl
es
Total
exons
TP FP TN FN
MISSN
OCALL
NOCA
LL
Sensiti
vity
PPV
NOCA
LL_
Rate
QCFail
_sampl
es
Site A blood 21 990 43 14 759 1 0 38 0.977 0.754 0.047 3
Site B blood 8 360 12 2 345 0 0 1 1 0.858 0.003 0
Figure 4. Normalized counts before and after renormalization.
Before renormalization:
miscalled BRCA1 del, BRCA2 dup
After renormalization:
BRCA1 del, BRCA2 normal
Boxplot of normalized count from all amplicons of each exon.
log2(NormalizedCount)
log2(NormalizedCount)
When whole gene deletions are present, normalization by total
number of reads is not sufficient. Re-normalization after detection of
whole gene or large deletions can improve accuracy.
RESULTS - continued
We first tested the performance of the pipeline using simulation data from
cell lines. We achieved high sensitivity and PPV, and low No Call rate.
We then tested the assay with blood samples for germline exon
deletions. Two early access customer sites provided us data from
blood sample with known exon deletions. We detected a variety of
single exon, multiple exon, and whole gene deletions.
For Research Use Only. Not for use in diagnostic procedures.
Figure 3. Sample QC
Low variation,
passed sample QC
Large variation,
Failed sample QC
log2(NormalizedCount)
log2(NormalizedCount)
Boxplot of normalized count from all amplicons of each exon.
Before re-normalization: detected
E7-13 del and somatic whole gene
deletion of BRCA1
Performance was measured by per exon per sample.
RESULTS - continued
We then tested the assay with FFPE tumor and normal samples. We have
observed in general high variability compared to blood and cell line
samples. However, we were able to detect exon deletions previously
detected by other methods, such as MLPA. Furthermore, our visualization
tool aids manual examination for somatic deletions.
BRCA1 exons 23- 24 deletion
log2(NormalizedCount)
FP TP
BRCA1 exon 24 deletion
log2(NormalizedCount)
TP
BRCA2 exons 3-14 deletion
log2(NormalizedCount)
TP
BRCA1 Exons 2 duplication
log2(NormalizedCount)
TP
FP
Before re-normalization: detected
somatic deletion of BRCA1
After re-normalization: detected
germline deletion of BRCA1 Exon 12
log2(NormalizedCount)
log2(NormalizedCount)0
log2(NormalizedCount)
log2(NormalizedCount)
Before re-normalization: high
variability sample that failed QC.
Visualization suggests BRCA1 Exon
22 deletion.
Figure 1. Exon coverage of BRCA1 and 2 genes by the
Oncomine™ BRCA Research Assay
BRCA1 BRCA2