TRG Clonality Interrogation by CE and NGS: Bridging the Gap Between Classicaland Leading Edge Technologies
K. HUTT1, A. ARIAS1, E. FINNEGAN1, J. PANGANIBAN1, D. VISSERS1, N. KHA2, I. DANNER2, D. MEDINA2, D. CAGUIOA2, J. LASSITER2, Y. HUANG1
1 Invivoscribe, Inc., 10222 Barnes Canyon Road, Building 1, San Diego, CA 92121-2711 USA
2 LabPMM LLC, 10222 Barnes Canyon Road, Building 1, San Diego, CA 92121-2711 USA

INTRODUCTION

TRG clonality is a powerful tool to assist in diagnosing numerous lymphoproliferative disorders
and is commonly assessed using PCR-based capillary electrophoresis (CE) assays. CE assays were
popularized by their speed and low cost, but suffer from disadvantages such as subjective
analysis and slow turnaround when using CE results for tracking. Next-generation sequencing(NGS) offers solutions to these disadvantages by producing less subjective results and almost
immediate sequence information that is ready to use for tracking. While it is understandable forlabs to be hesitant about switching to newer, unfamiliar technologies, we present the following
data to show the concordance between CE and NGS in a format familiar to the current
generation.

RESULTS: NGS-E VERSUS CE PLOTS
388 clinical samples were run on both NGS and CE assays. Examples of concordant results
between these two assays are shown in Figures 2 and 3 for negative and positive TRG
clonality, respectively. An example of a discordant result between NGS and CE is shown inFigure 4. As seen in this example, when multiple amplicons have the same size, the CE assay
is not able to differentiate amplicons and the CE electropherograms look positive for TRG
clonality. Alternatively, the NGS-E plot can delineate amplicons within size bins and showsthat this sample should be negative for TRG clonality.

OBJECTIVESFirst, to present TRG clonality results for 388 clinical samples using both CE and NGS.
Second, to transform the NGS data into an in silico, electropherogram format (called NGS-E), toenable more direct comparison to CE outputs.
Third, to present a simple heuristic to demonstrate a key analysis advantage of NGS data.
Namely, elucidating highly complex peaks from what would be considered clonal peaks in CE,revealing false positives in CE.

RESULTS: ENTROPY PLOT

For NGS results, the entropy calculation of the peak chosen for CE analysis was used fordownstream comparison analysis. Of the 388 clinical samples, 256 (66.0%, average entropy
279.7, blue dots in Figure 5) were concordant negatives between the NGS and CE assays, and90 (23.2%, average entropy 51.2, green dots in Figure 5) were concordant positives; theremaining 42 (10.8%) were discordant. Of the discordant samples, 16 were NGS+ (red dots,Figure 5), while 26 were CE+ (yellow dots in Figure 5). 16 of these 42 discordant samples werenear the cut-off. However, an interesting pattern appeared for the discordant, CE+ samples. Ifthe samples are ranked by the entropy value of the target peak from the NGS-E plot, 14 of the26 were highly complex peaks (average entropy of 202.1, yellow dots with blue square, Figure5) that were correctly distinguished in the NGS data as being polyclonal. These 14 represent
missed clonality calls that were clear from the NGS data; comparison of the CE and NGS-E
shows visually how this discordance could happen (example shown in Figure 4). Interestingly,
none of the 16 NGS+ discordant samples could be distinguished by peak diversity. If weassume the 14 CE+ discordant samples are false positives, the NGS data was able to reduce thefalse positive rate by 54% (from 6.7% to 3.1%).
Figure 5: Entropy vs RPR plot
for all 388 samples. RPR isshown in log2 scale tovisually differentiate thedatapoints.
The 256 concordant negativesamples had an average
entropy of 279.7, while the90 concordant positives had
an average entropy of 51.2,demonstrating the ability ofthe entropy heuristic
separate clear positives fromnegatives.

METHODS388 clinical samples representing a variety of suspect T-cell lymphoproliferative diseases
routinely tested using TRG assays were tested using both the LymphoTrack® TRG Dx assay (indevelopment) on the Illumina® MiSeqDx® platform, and the CE-based IdentiClone® assay for
TRG clonality. For NGS results, the %Total Reads (i.e. the percentage of reads an amplicon takesup in the sequencing sample) was used as the metric for calling positives and negatives. For CE
plots, a standard Relative-Peak-Ratio (RPR) calculation was used as a metric for calling positives
and negatives.

Figure 2: Example of a High Entropy NGS-E (top). Matching CE plot withamplicon size ranges aligned (bottom).

Figure 3: Example of a Low Entropy NGS-E (top). Each different color
bar within a column represents a different rearrangement sequence,
and are sorted from largest to smallest contributor, starting at thebottom.
Matching CE plot with amplicon size ranges aligned (bottom). Notethe shoulder peaks at +1 of the clonal peaks. These are common
artefacts of CE. It should also be noted that peak sizes are generally 34nts smaller than detected by sequencing.

The results from the NGS-based assay were converted, in silico, to NGS-E plots, by taking thesizes of the sequenced amplicons and plotting them on a histogram. On CE-based assays,
electropherograms are the standard output. The two different groups were then compared(NGS-E vs CE). The NGS-E plots had an important difference: each size column often contained
multiple different sequences. For any single column, an information-based metric for variability,Shannon entropy (Figure 1), is utilized to define columns as having many different sequences(high entropy, see Results: Figure 2) or few sequences (low entropy, see Results: Figure 3).

CONCLUSIONS
A significant hurdle in switching from CE to NGS for clonality testing is the assurance that theNGS assay gives more accurate results to offset the higher cost and longer time needed togenerate data and results. However, it can be argued that the advantages of sequencing
should be sufficient to offset the cost and time; the subjective nature of CE analysis and theslow turnaround time to obtaining sequence data from CE may nullify the NGS cost and time.
In addition, NGS-E plots, which have the benefit of displaying the results in a manner familiar
to those accustomed to CE results, in combination with a simple metric for complexity (whichgives more accuracy and reduced false positives by 54% in our dataset), adds to theadvantages of NGS over CE for clonality testing. These NGS-E plots can act as a bridge that theCE-centric labs can use to become more accustomed to NGS data, as they address potential
concerns about converting to NGS-based testing.

Figure 1: Shannon Entropy equation

To ensure fair comparisons between samples and size columns that had different numbers ofparticipating amplicons, each size column was initialized with 65 participating amplicons(representing the highest number of participating amplicons across all samples/sizes), and each
initialized amplicon was given a minimum %Total Reads value of 0.0003125. The probability
value used for the entropy calculation was derived from the fraction of %Total reads eachamplicon contributed to its size column. For a size column with only initialized amplicons (i.e. noactual data, only initialized data), each of the 65 participants contribute an equal probability to
the entropy calculation, and the negative sum is maximized (high entropy). For a size column
with a few, high-signal amplicons, these signal amplicons take up the vast majority of theentropy calculation, and the negative sum is minimized (low entropy).

Of the 26 CE+ discordantsamples, 14 demonstrated
high entropy (average of202.1), and are likely missed
polyclonal calls in the CE
assay due to the target peak
containing multiple, different
amplicons of the same size.

Figure 4: Example of a CE+, NGS- sample (NGS-E on top and matching CE bottom). While theelectropherogram looks positive, the amplicon-specific delineation within size bins of the NGS-E plot shows
the peaks are made of multiple, smaller signal amplicons. Therefore, this sample is an example of a false
positive by CE.

CONTACT INFORMATION
Dr. Kasey Hutt
khutt@invivoscribe.com
1 858.224.6600