In recent years, advances in next-generation sequencing (NGS) technologies have enabled faster and cheaper methods for uncovering the genetic basis of disease. For cancer, NGS based screening for known tumor subtypes may inform diagnosis and allow the clinician to tailor a specific therapeutic approach in the future. Here, we present the testing results of one such NGS based kit used to detect specific chromosomal translocations in retrospective non-small cell lung cancer (NSCLC) samples by targeting specific breakpoints in known fusion transcripts.

1. Each clinical research site performed all required sequencing runs
using their own instrumentation including the Ion PGM™ sequencer.
Sequencing reagents such as Ion 318™ chips, sequencing, and
templating kits we supplied to each site by Thermo Fisher Scientific.
RecoverAll™ Total Nucleic Acid Isolation Kit for FFPE was used to
extract RNA from all FFPE embedded tumour samples.
Completed sequencing runs contained sequence data for 16 (15 for
reproducibility runs) barcoded samples. Each data set was uploaded to
an Ion Reporter™ Server running locally at each site. Once transfer
was complete, operators from each site executed the lung fusion, single
sample workflow available in Ion Reporter™ Software. Final reports
including sequence read count data for all targets was then sent to the
NAMSA5 analysis team for statistical analysis and final summary
generation. Results of which are provided in tables 1 and 2 in the
Results section to the right.
Clinical research results for a NGS based kit for targeted detection of relevant gene rearrangements in lung
tumor samples
MATERIALS AND METHODS
In recent years, advances in next-generation sequencing (NGS) technologies have
enabled faster and cheaper methods for uncovering the genetic basis of disease. For
cancer, NGS based screening for known tumor subtypes may inform diagnosis and
allow the clinician to tailor a specific therapeutic approach in the future. Here, we
present the testing results of one such NGS based kit used to detect specific
chromosomal translocations in retrospective non-small cell lung cancer (NSCLC)
samples by targeting specific breakpoints in known fusion transcripts.
The included panel tested consists of a single primer pool containing amplicon
designs to simultaneously screen for over 75 specific rearrangements involving the
receptor tyrosine kinase (RTK) genes ALK, RET and ROS1 as well as NTRK1. The
panel was compatible with formalin-fixed paraffin-embedded (FFPE) lung tumor
research samples and achieved high-sensitivity down to 10 ng of RNA input. In
addition, amplicon assays designed at the 5’ and 3’ ends the RTK genes provide non-
specific evidence that a translocation exists in a sample by comparing expression
imbalance between the two ends.
Testing was carried out at three external clinical research laboratories. In addition to
positive and negative control samples, each site contributed FFPE lung tumor
research samples for which ALK fusion status was known prior to NGS library
preparation carried out using the Ion AmpliSeq™ workflow. For site-specific samples
(n=144, 16 samples per sequencing run), high concordance, sensitivity and specificity
were measured at 97.2%, 90.5% and 98.4%, respectively.
A more succinct description for what has traditionally been labeled ‘personalized
medicine’ has emerged -- and now referred to by clinicians as ‘precision medicine.’
The term implies a more targeted approach in diagnostic and therapeutic contexts.
A central goal of which is to identify drugs which can pinpoint a certain cancer type
while reducing the need for traditional and generalized approaches such as
chemotherapy.
Now, molecular biomarkers in the form of specific gene mutations have been well
associated with therapies and clinical outcomes1. In the case of non-small cell
lung cancer (NSCLC), these biomarkers are associated with targeted therapeutic
approaches which are described in clinical guidance provided by the National
Comprehensive Cancer network (NCCN) 2. These include treatment algorithms
for ALK and EGFR testing as well as for therapies in development for ROS-1,
BRAF, MET, Her2, and RET.
Some of these mutations come in the form of chromosomal translocations
(structural variants) which give rise to aberrant fusion proteins. For NSCLC,
protein kinase domains from ALK, RET, ROS-1 and NTRK make be fused to
multiple gene partners3. Since therapeutic options exist for patients who are
positive for these fusion proteins, it is essential that the detection technology is
robust and sensitive. Conventionally, fluorescence in situ hybridization (FISH) is
utilized to detect fusions of fusion genes but suffers from lower sensitivity for
detecting EML4-ALK fusions relative to other techniques such as reverse
transcription polymerase chain reaction (RT-PCR) 4.
Since NGS technologies enable analysis of mutations down to the nucleotide level,
it may as a sensitive alternative to current practices used to detect fusion genes
from tumour samples. Here, we present the analyses from the testing of one such
NGS based technology. This set of kit reagents included for these analyses include
an oligonucleotide panel which will simultaneously measure the presence of >75
possible fusion targets containing ALK, RET, ROS-1, and NTRK1 driver genes.
Verification of this kit was carried out using the Ion Torrent™ Personal Genome
Machine (PGM™) NGS platform and was accomplished through collaboration with
three external clinical laboratories located in Portugal, Ireland and the United
States.
INTRODUCTION
Sample Sets
Reproducibility
Each site generated 15 libraries with 5 pre-extracted control RNA
samples (three libraries each) with known ALK, RET and ROS-1
fusion status. RNA was extracted from positive control cell lines as
well as a positive and a negative control cell line embedded in FFPE.
Repeatability
Each site produced 16 libraries per day on each of three separate
days, starting with the RNA extracted from site-provided FFPE
samples acquired within and unique to each site. To evaluate
variability associated with day-to-day and reagent lot-to-lot testing,
the sites generated 16 libraries using each of three different lots of
the targeted fusion detection kits. All libraries were quantitated using
qPCR to confirm that the final library concentrations were ≥ 20 pM
Fusion status for all site-specific samples was determined prior to
verification testing using FISH.
Participating Clinical Sites
Reagents Used for Testing
Sequencing Library Kit Description
ABSTRACT
RESULTS
CONCLUSION
Fusion Panel Targets and Controls
*
Table 1. Cross-site reproducibility: Performance characteristics of
concordance, sensitivity and specificity for each of the gene
fusions of interest which contain ALK, RET and ROS-1. ‘CI’
values in parentheses refer to 95% confidence intervals.
*ALK Positive Predictive Value (PPV) = 100%, n=18
Table 2. Within-site repeatability: All of the clinical research study sites
had previously evaluated the samples they selected for the
repeatability study for ALK fusions. As a result, the performance of this
fusion detection kit with respect to concordance with an orthogonal
measure, as well as sensitivity and specificity, could be assessed for
the ALK gene. ‘CI’ values in parentheses refer to 95% confidence
intervals.
*ALK Positive Predictive Value (PPV) = 90.5%, n=19
Figure 1. Fusion Detection Readout from Ion Reporter™ Software:
The example heat map below depicts relative gene expression for
fusion, control, and 3’-5’ imbalance amplicon targets. Darker blue
colours indicate higher sequence read counts being allocated to a
particular target. These are scaled to the total number of mapped
reads per sample (total signal) then log transformed resulting in a
normalized detection fraction (NDF). In the example below, EML4-
ALK was strongly detected in samples 5, 15 and 16 while sample 5
indicates detection of 2 different isoforms of the EZR-ROS1 fusion
gene. Numbers in parenthesis to the right of each gene symbol
indicate exon numbers which contain the fusion junction in each RNA
transcript.
**>75 specific designs for cancer relevant fusions according to PubMed
RNA quality control: amplification of housekeeping genes MYC, ITGB7,
LMNA, HMBS, TBP
3’ and 5’ imbalance assays are included in the panel to provide non-
specific evidence that an ALK, RET, ROS-1 related translocation
are present when no specific fusion is detected. For example, if the
3’ assay for ALK is measured at a level 50 greater than the 5’ assay
for the same sample, this indicates that reflex testing is
recommended via FISH or other orthogonal method to provide
secondary evidence for ALK fusion detection.
When developing acceptance criteria for evaluating concordance,
specificity, sensitivity, and positive predictive value, minimum
detection thresholds for read counts were set according to Ion
Reporter™ default settings. Thus, a minimum of 20 reads must be
allocated to an fusion target to be detected. For expression
controls, this was slightly more liberal at 15 read counts.
• Molecular tests, such as those developed using sequencing
technology, are now providing results to clinical researchers that
open the door for development of additional precision medicine
based approaches in the future.
• We have developed and tested NGS approach for detecting
known fusion transcripts in FFPE embedded lung tumour
research samples with high sensitivity and reproducibility
• Fusion panel includes in kit includes assays for detecting
specific ALK, RET, ROS-1 and NTRK1 fusion break points
which are interrogated simultaneously
• Detection specificity and sensitivity at a high level (>90%) when
multiplexing up to 16 samples per run with as 10 ng of RNA
input
• Detection specificity for detection of ALK fusions was >98%.
1. Brief Communications. Nature Medicine, volume 18, number 3, March 2012
2. www.NCCN.org
3. Beyond ALK-RET, ROS1 and other oncogene fusions in lung cancer. Takashi Kohno, Takashi
Nakaoku, Koji Tsuta, Katsuya Tsuchihara, Shingo Matsumoto, Kiyotaka Yoh, Koichi Goto. Transl
Lung Cancer Res. 2015 April; 4(2): 156–164.
4. Detection of EML4-ALK in lung adenocarcinoma using pleural effusion with FISH, IHC, and RT-
PCR methods. Liu L, Zhan P, Zhou X, Song Y, Zhou X, Yu L, Wang J. PLoS One. 2015 Mar
18;10(3)
5. www.NAMSA.com
ACKNOWLEGMENTS
We would like to thank all extended teams both from the external clinical laboratories and Thermo
Fisher Scientific for assist us in accomplishing a vast number of goals to make this verification testing
possible.
Conflict of interest statement
All authors disclose that there is no actual or potential conflict of interest.
TRADEMARKS/LICENSING
© 2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of Thermo
Fisher Scientific and its subsidiaries unless otherwise specified.
REFERENCES
Jeoffrey J. Schageman§, José Luis Costa†, Orla Sheils††, John E. Glasscov, David Chiv, Janine Coocv, Efren Ballesteros-Villagrana§, Jon Sherlock§, John Bishop§, Rosella P. Petraroli§ and Kelli S. Bramlett§
†Institute of Molecular Pathology and Immunology, University of Porto, Porto Portugal, ††Sir Patrick Dun Research Laboratory, St. James Hospital, Dublin, Ireland, vLife Technologies Clinical Services Lab, West Sacramento, California U.S.A., §Thermo Fisher Scientific, UK, Italy,
Netherlands, U.S.A.