T-Cell receptor (TCR) repertoire sequencing by next-generation sequencing (NGS) is a valuable tool for building a deeper understanding of the adaptive immune system. As immunotherapy, particularly T-cell therapies, show increasing potential in treating cancer, the ability to gain a detailed, unbiased view of the TCR repertoire becomes imperative for biomarker discovery, immune response to treatment, and study of tumor microenvironments. A key question the field seeks to understand is the relationship between circulating T-cells and infiltrating T-cells at the tumor site. Here, we present a novel AmpliSeq approach for TCR repertoire sequencing using the Ion Torrent S5 sequencer which leverages simplified workflows and offers up to 600 bp reads which allow for a more complete characterization of the entire V(D)J region of TCRβ. With a unique long read length capability, this method can leverage mRNA as input, which minimizes requirement as starting materials (10-500ng for typical use cases) and focusing sequencing to productive TCRβ arrangements.

1. Read Length (bp)
Counts
For Research Use Only. Not for use in diagnostic procedures. Thermo Fisher Scientific • 5781 Van Allen Way • Carlsbad, CA 92008 • thermofisher.com
Geoffrey Lowman1, Elizabeth Linch1, Lauren Miller1, Denise Topacio-Hall1, Tim Looney2, Yongming Sun2, Mark Andersen1, Fiona Hyland2, Ann Mongan2
(1) Thermo Fisher Scientific, 5781 Van Allen Way, Carlsbad, CA 92008 (2) Thermo Fisher Scientific, 180 Oyster Point Blvd. South San Francisco, CA 94080
Sequencing the circulating and infiltrating T-cell repertoire on the Ion S5TM
Results
Introduction/Background
Abstract
3130
T-Cell receptor (TCR) repertoire sequencing by next-generation
sequencing (NGS) is a valuable tool for building a deeper
understanding of the adaptive immune system. As immunotherapy,
particularly T-cell therapies, show increasing potential in treating
cancer, the ability to gain a detailed, unbiased view of the TCR
repertoire becomes imperative for biomarker discovery, immune
response to treatment, and study of tumor microenvironments. A key
question the field seeks to understand is the relationship between
circulating T-cells and infiltrating T-cells at the tumor site. Here, we
present a novel AmpliSeq approach for TCR repertoire sequencing
using the Ion Torrent S5 sequencer which leverages simplified
workflows and offers up to 600 bp reads which allow for a more
complete characterization of the entire V(D)J region of TCRβ. With a
unique long read length capability, this method can leverage mRNA as
input, which minimizes requirement as starting materials (10-500ng for
typical use cases) and focusing sequencing to productive TCRβ
arrangements. This AmpliSeq approach targets the constant (C) and
the FR1 regions, minimizing the potential for primer bias and greatly
increasing the phylogenetic information content compared to
techniques that exclusively characterize the CDR3 domain. Our results
show that the circulating T-cell repertoire size is approximately 2 orders
of magnitude higher than the infiltrating T-cell repertoire. Accordingly,
while it is difficult to fully capture the complete repertoire of circulating
T-cells due to its vast diversity, we show that it is possible to reliably
capture the complete infiltrating T-cell repertoire with multiplexing as
high as 10 samples on the Ion 530 chip. Replicate runs of infiltrating T-
cells offers correlation of ~0.9, indicating that the results were
reproducible and the samples were sequenced to appropriate depth. In
summary, we believe that this high multiplex workflow and fast turn-
around time (<48 hours RNA-to-answer) will allow researchers to
more routinely characterize infiltrating T-cell repertoire and offer the
field a better understanding of the impact of repertoire diversity on
tumor elimination.
High throughput:
>50,000 clones/
sample from blood,
cell populations, or
fresh-frozen tissue
generated from a
single tube
workflow.
Input cDNA
Amplify targets using
OncomineTM TCR-Seq β
Primer Panel
Partially digest primer sequences
Ligate Adapters
Unbiased output:
AmpliSeqTM V- and
C-region primers
are optimized to
reproduce results
from 600bp 5’-
RACE protocols.
Comprehensive:
400bp read length
offers complete
characterization of
CDR1,2,3.
Highly accurate:
sequencing and
amplification errors are
corrected with
statistical models
leveraging TCR mRNA
as input.
Diversity view
V gene
CDR3length(nt)
Clonotype identification
V-gene identification
Readcount
Proportion of different alleles
Analysis solution:
Complete Ion Reporter
analysis solution
including clonotype
identification and
diversity, CDR3 length,
and multisample
analysis for longitudinal
tracking for clones of
interest.
Sequencing lung tumor
biopsy revealed 589
unique TCR clones.
• Oligoclonal repertoire
with a small number
of dominating clones
• Shannon Diversity -
6.78.
Sequencing PBL revealed
45305 unique TCR clones.
• Diverse, polyclonal
repertoire with few
highly expanded T
cells.
• Shannon Diversity -
13.95.
Figure 2. Sequencing read length histogram from library generated
using the OncomineTM TCR-Seq β assay run on an S5-530 chip. Total
read counts are typically between 15-20M reads, of which 70-80% are
“productive” (blue+light blue) when run through our analysis pipeline.
For Research Use Only. Not for use in diagnostic procedures.
© 2017 Thermo Fisher Scientific Inc. All rights reserved.
All trademarks are the property of Thermo Fisher Scientific
and its subsidiaries unless otherwise specified.
2-day workflow using the OncomineTM TCR-Seq β assay - Immune Repertoire sequencing using AmpliSeqTM library construction
Variable Diversity Joining Constant
N1 N2
A. Adult IGH or TCRBeta chain rearrangement
In adult B and T cells, the process of VDJ rearrangement very often involves
exonucleotide chewback of VDJ genes and the addition of
non-templated bases, forming N1 and N2 regions in the B cell receptor
heavy chain CDR3 and the T cell receptor Beta chain CDR3.
These processes vastly increase IGH and TCRB CDR3 diversity.
Variable Diversity Joining Constant
B. Fetal IGH or TCRBeta chain rearrangement
In the fetus, the process of VDJ rearrangement often occurs without
exonucleotide chewback of VDJ genes and addition of non-templated
bases, resulting in a restricted IGH and TCRB CDR3 repertoire that is
distinct from the adult repertoire.
These structural differences can be used to distinguish fetal B and T cell
CDR3 receptors from maternal B and T cell CDR3 receptors in cell free
DNA present in maternal peripheral blood. In this way, fetal B and T
cell health and development may be monitored in a non-invasive
manner.
Figure 1. Structural differences between fetal and adult B and T cell receptors
Variable Diversity Joining Constant
N1 N2
A. Adult IGH or TCRBeta chain rearrangement
In adult B and T cells, the process of VDJ rearrangement very often involves
exonucleotide chewback of VDJ genes and the addition of
non-templated bases, forming N1 and N2 regions in the B cell receptor
heavy chain CDR3 and the T cell receptor Beta chain CDR3.
These processes vastly increase IGH and TCRB CDR3 diversity.
Variable Diversity Joining Constant
B. Fetal IGH or TCRBeta chain rearrangement
In the fetus, the process of VDJ rearrangement often occurs without
exonucleotide chewback of VDJ genes and addition of non-templated
bases, resulting in a restricted IGH and TCRB CDR3 repertoire that is
distinct from the adult repertoire.
These structural differences can be used to distinguish fetal B and T cell
CDR3 receptors from maternal B and T cell CDR3 receptors in cell free
DNA present in maternal peripheral blood. In this way, fetal B and T
cell health and development may be monitored in a non-invasive
manner.
Figure 1. Structural differences between fetal and adult B and T cell receptors
FR1
FR2
Diversity
(D)
Joining
(J)
Constant
(C)
Variable
gene
(V)
CDR3
FR3
CDR1
CDR2
Figure 1. Schematic of a section of T-cell receptor which has undergone
V(D)J rearrangement, identifying the CDR1, 2, and 3 regions, and the
Framework (FR1, 2, and 3) regions. Using RNA/cDNA as input allows design
of primers targeting the (V) and (C) regions.
Figure 3. 10 FF tumor infiltrating
lymphocyte (TIL) samples (NSCLC)
sequenced on 530 chips. We see high
concordance between identified clones
(95.8-99.6%) comparing sequencing
replicates – which indicates sequencing to
adequate depth.
The OncomineTM TCR-Seq β assay harnesses the power of
AmpliSeqTM library construction chemistry which allows for primer
design targeting the FR1 region, and includes primers targeting all
known (V) region rearrangements. The resulting sequencing libraries
are generally 325-350bp in length. The AmpliSeqTM workflow allows for
library construction in under 5 hours with 30 minutes of hands on time.
The OncomineTM TCR-Seq β assay enables sequencing on the Ion
S5TM 530 chip. The capacity of this sequencing arrangement allows for
multiplexing of up to 16 samples per chip for samples with limited repertoire
size (cultured cells, tissue). The ability to multiplex also enables
sequencing runs which contain sample comparisons, i.e. – tissue and
blood samples run on the same sequencing run (Figures 4-6). Figure 3
above depicts correlation plots generated for technical sequencing
replicates for 10 fresh-frozen tumor infiltrating leukocyte (TIL) samples
taken from non-small cell lung carcinoma (NSCLC) biopsies. High
concordance between identified clones (95.8-99.6%) indicates sequencing
to adequate depth.
Immune repertoire sequencing using Ion Torrent sequencing includes
a full analysis suite which outputs highly accurate assignment of clonotype
populations. Repertoire sequencing is sensitive to base-call (substitution)
sequencing errors, which can mimic the natural variation in the repertoire,
making error correction strategies very difficult to implement. Ion Torrent
sequencing has a very low substitution error rate, and the errors that are
produced are predominantly InDel errors. This error type allows for
correction using the knowledge that by using mRNA as an input to the
assay, all reads should code for productive amino acid sequences, and
InDel errors will present as frame shift errors. This permits for the
streamlined identification of sequencing errors, and in most cases, error
correction, leading to higher rates of productive reads from each sample.
For more information on the OncomineTM TCR-Seq β assay please see
poster #3567:
“Sequencing the human TCRβ repertoire on the Ion S5™ System”
Session Category: Bioinformatics and Systems Biology
Session Title: Sequencing Analysis and Algorithms
Session Date and Time: Tuesday Apr 4, 2017 8:00 AM - 12:00 PM
Location: Convention Center, Halls A-C, Poster Section 23
Poster Board Number: 3
Acknowledgements
Figure 5. Spectratype plot of V-gene primer usage versus CDR3 length,
showing a comparison of TCRβ clones identified to be unique to the PBL
(left panel – 91.78% of all clones identified) and TCRβ clones shared in
both the PBL and tumor repertoire (right panel – 8.22% of total). Circle size
denotes level of clonal expansion.
Figure 4. Diagram outlining sample comparison between FF tumor infiltrating
leukocyte and peripheral blood leukocytes from a patient with NSCLC sequenced
on a single 530 chip.
Unique to peripheral
blood: 91.78%
Shared with tumor
repertoire: 8.22%
CDR3length(nt)
V-gene primer V-gene primer
Figure 6. Correlation plot showing the
same dataset shown in Figure 5. Data
along the x-axis represents clones
unique to the PBL, data along the y-
axis shows those unique to tumor, as
well as 219 clones that are shared
between PBL and tumor.
To test the ability of the assay to differentiate repertoire sample types,
total RNA was extracted from peripheral blood leukocytes (PBL) and fresh-
frozen tumor biopsy from an individual with Stage 1B squamous cell
carcinoma of lung. 100ng of total RNA from each sample was used as
template input for TCRβ sequencing on a single Ion 530TM Chip. The results
of this study are outlined in Figure 4; sequencing of the tumor biopsy revealed
589 unique TCR clones, an oligoclonal repertoire with a small number of
dominant clones, resulting in a Shannon Diversity value of 6.78. Sequencing
PBL led to 45305 unique TCR clones. Next, we carried out correlation to
determine the populations of clones that were unique to either the tumor
biopsy or the PBL, and which clonal populations are shared between sample
types. Correlation data is presented using two views shown in Figures 5 and
6. Figure 5 displays a spectratype plot of V-gene primer useage versus CDR3
length, split into two windows: L) clones unique to the PBL and R) clones
shared between the PBL and the tumor biopsy. The spectratype plot allows
for a fast view of the differences between repertoires unique to PBL versus the
shared clone population. Namely, the expected size and diversity of the PBL
repertoire compared to the relatively less diverse repertoire of the tumor
biopsy which includes fewer, more highly expanded clones. Figure 6 displays
the same data which separates into three natural populations; along the x-
axis, clones unique to the PBL, along the y-axis, clones unique to the tumor
biopsy, and along the diagonal, clones which are shared between sample
types. This view allows quick identification of clonal populations which may
be interesting routes for further experiments, for instance, tracking of clones
from the blood which are identified in the solid tumor, or expansion of tumors
which are found only in the tumor sample.
log10 clone frequency in PBL
log10clonefrequencyintumor
370 clones unique to tumor
45086 clones unique to PBL
219 shared clones
The authors would like to acknowledge the work of all who participated in this
program: Xinzhan Peng, Alice Zheng, Alex Pankov, Lifeng Lin, Grace Lui,
Gauri Ganpule, Sonny Sovan, Larry Fang, Tyler Stine, Laura Nucci, Matthew
Cato, Yuan-Chieh (Jeffrey) Ku, Janice Au-Young, Rob Bennett, and Jim
Godsey.