PLOS ONERESEARCH ARTICLE

Immunoglobulin gene rearrangement in
Koreans with multiple myeloma: Clonality
assessment and repertoire analysis using
next-generation sequencing
Miyoung Kim1, Kibum Jeon2, Kasey Hutt3, Alyssa M. Zlotnicki3, Hyo Jung Kim4,
Jiwon Lee5, Han-Sung Kim6, Hee Jung Kang6, Young Kyung Lee ID6*

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1 Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul,
South Korea, 2 Department of Laboratory Medicine, Hangang Sacred Heart Hospital, Seoul, South Korea,
3 Invivoscribe, Inc., San Diego, California, United States of America, 4 Department of Internal Medicine,
Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, South Korea,
5 Department of Laboratory Medicine, Green Cross Laboratories, Yongin, South Korea, 6 Department ofLaboratory Medicine, Hallym University Sacred Heart Hospital, Hallym University College of Medicine,
Anyang, South Korea* lyoungk@hallym.or.kr

Abstract
OPEN ACCESS
Citation: Kim M, Jeon K, Hutt K, Zlotnicki AM, Kim
HJ, Lee J, et al. (2021) Immunoglobulin generearrangement in Koreans with multiple myeloma:
Clonality assessment and repertoire analysis using
next-generation sequencing. PLoS ONE 16(6):e0253541. https://doi.org/10.1371/journal.
pone.0253541
Editor: Obul Reddy Bandapalli, German Cancer
Research Center (DKFZ), GERMANY
Received: January 25, 2021
Accepted: June 7, 2021

Introduction
We assessed the applicability of next-generation sequencing (NGS)-based IGH/IGK clonality testing and analyzed the repertoire of immunoglobulin heavy chain (IGH) or immunoglobulin kappa light chain (IGK) gene usage in Korean patients with multiple myeloma (MM) for
the first time.

Methods
Fifty-nine bone marrow samples from 57 Korean patients with MM were analyzed, andNGS-based clonality testing that targeted the IGH and IGK genes was performed using IGH
FR1 and IGK primer sets.

Published: June 24, 2021
Copyright: © 2021 Kim et al. This is an open
access article distributed under the terms of theCreative Commons Attribution License, which
permits unrestricted use, distribution, andreproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data arewithin the manuscript and its Supporting
information files.
Funding: Unfunded studies.
Competing interests: No authors have competinginterests.

Results
Clonal IGH and IGK rearrangements were observed in 74.2% and 67.7% of samples from
Korean patients with kappa-restricted MM, respectively (90.3% had one or both), and in
60.7% and 95.5% of samples from those with lambda-restricted MM, respectively (85.7%
had one or both). In total, 88.1% of samples from Koreans with MM had clonal IGH and/or
IGK rearrangement. Clonal rearrangement was not significantly associated with the bonemarrow plasma cells as a proportion of all BM lymphoid cells. IGHV3-9 (11.63%) and
IGHV4-31 (9.30%) were the most frequently reported IGHV genes and were more common
in Koreans with MM than in Western counterparts. IGHD3-10 and IGHD3-3 (13.95% each)were the most frequent IGHD genes; IGHD3-3 was more common in Koreans with MM. No
IGK rearrangement was particularly prevalent, but single IGKV-J rearrangements were less

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1 / 15PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

common in Koreans with kappa-restricted MM than in Western counterparts. IGKV4-1 wasless frequent in Koreans regardless of light chain type. Otherwise, the usages of the IGH V,
D, and J genes and of the IGK gene were like those observed in previous Western studies.

Conclusion
NGS-based IGH/IGK clonality testing ought to be applicable to most Koreans with MM. The
overrepresentation of IGHV3-9, IGHV4-31, and IGHD3-3 along with the underrepresentation of IGKV4-1 and the differences in IGK gene rearrangement types suggest the existenceof ethnicity-specific variations in this disease.

Introduction
Myelomagenesis is a complex multistep process that may involve earlier B-cell precursors [1].
Like other types of B-lymphoid malignancies, immunoglobulin (IG) gene rearrangement
begins at the earliest stages of B-cell development and involves recombination events between
the numerous V, (D), and J genes, which result in the formation of unique V(D)J sequencesthat ultimately encode the antigen-binding region of the IG chain [2, 3]. Random additions or
subtractions of nucleotides at the junctional regions during the process of recombination, as
well as additional, subsequent changes associated with somatic hypermutation, further diversify the antigen-binding regions [4, 5]. Each rearrangement is independent and unique; assuch, the probability that the same sequence would be shared by 2 unrelated cells is negligible[4–9]. This diversity of clonality constitutes the basis of currently used clonality testing strategies [4].
Clonality assessment is pivotal for the correct diagnosis of patients in whom it is difficult todistinguish multiple myeloma (MM) from non-neoplastic processes [4, 10, 11]. After treatment, residual disease can be better identified by tracking the behavior of specific clonal tumor
populations [12–14]. Moreover, the measurement of minimal residual disease can predict
overall and progression-free survival, which helps plan consolidation and maintenance strategies and is also useful in evaluating the comparative efficacy of novel therapies [15]. Indeed,
the International Myeloma Working Group has suggested new criteria for response assessment that emphasize measuring the minimal residual disease using sensitive tools such as
next-generation sequencing (NGS) for IG gene clonality with a high sensitivity (i.e., at least10−5) [16]. However, to successfully perform clonality assessment for MM, the relevance of IG
gene clonality testing to this disease should be assessed.
Assessment of IG gene clonality also provides valuable insight into the pathogenesis andnatural history of lymphoid neoplasms [7]. Antigen stimulation is considered a key environmental driver of malignant transformation [7], and the class switch recombination mechanisms involved in MM-related chromosomal translocations suggest that early events in thedevelopment of this disease occur during germinal center maturation [17]. Furthermore, thepresence of pre-switch B cells that are idiotypically related to malignant plasma cells has beenreported [18]. Thus, evaluating the IG gene repertoire and identifying stereotyped clusters of
IG receptors in patients with MM would allow deeper investigation of the role of antigendriven stimulation in B-lymphoid tumorigenesis [7].
The incidence rate, clinical features, and outcomes of Korean patients with MM differ fromthose of patients belonging to other ethnicities [19–21]. The age-standardized incidence rate of
MM in the United States between 1960 and 1994 was 6.3/100,000, while the associated age-

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2 / 15PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

adjusted mortality rate was 3.3/100,000 [20]. The corresponding rates between 1993 and 2012
for Korean patients with MM were 1.6/100,000 and 1.0/100,000, respectively [21]. Notably, theage-standardized incidence rate of MM in Korea has increased 2-fold over the past 10 years
after having risen 10-fold during the preceding 20 years [22]; this may be attributable to bothbetter detection as well as an actual increase in the number of patients with this disease in
Korea [19].
The incidences of International Staging System (ISS) stages I, II, and III in Western countries are reportedly 28%, 33%, and 39%, respectively. However, an Asian study that included
Korean patients found a higher incidence of advanced disease; the rates of patients with ISS
stages I, II, and III were 19.9%, 36.1%, and 44%, respectively [23]. While the IG repertoire
might be ethnicity-specific, neither this repertoire nor the applicability of NGS-based IG geneclonality testing has ever been reported in Asian populations with MM, including Koreans.
In this study, we aimed to better understand the repertoire of IG gene usage among Koreans
with MM, and to explore the applicability of NGS-based IG gene clonality testing in clinicalpractice. We evaluated the status of IG heavy chain (IGH) and IG kappa light chain (IGK) generearrangement as well as somatic hypermutations (SHMs) in the IGH variable region (IGHV)
among Korean patients with MM via NGS using the only commercially available primer sets
in Korea for the first time. The IG gene repertoire profile and clonality detection rate in ourcohort were compared with those derived in previous Western studies to gain insight into any
Korean-specific features of MM.

Materials and methods
Patients and clinical samples
Fifty-nine cryopreserved bone marrow (BM) buffy coat samples or fresh BM aspirate from 57
patients diagnosed with MM at Hallym University Sacred Heart Hospital, Anyang, Republic ofKorea between February 2007 and January 2020 were analyzed in this study. Clinical and laboratory information was obtained from electronic medical records. The study protocol wasapproved by the Institutional Review Board of Hallym University Sacred Heart Hospital (No.
HALLYM 2018-12-034). The informed consent requirement was waived by the Institutional
Review Board.

NGS-based clonality testing targeting IGH and IGK genes
Genomic DNA (gDNA) was extracted from BM buffy coat samples by using the QIAamp DSPDNA Blood Mini QIAcube Kit (QIAGEN GmbH, Hilden, Germany) and QIAcube instrument (QIAGEN GmbH) or from BM aspirate manually using QIAamp DNA Blood Mini kit(QIAGEN GmbH) according to the manufacturer’s instructions. NGS-based clonality testing
was performed using the LymphoTrack IGH FR1 assay kit A-MiSeq (Invivoscribe, Inc. San
Diego, CA, USA) and LymphoTrack IGK assay kit A-MiSeq (Invivoscribe, Inc.) according to
the manufacturer’s recommendations. Briefly, amplification by PCR was performed using 100
ng of gDNA per each sample, master mixes containing primers designed with barcoded
sequence adaptors. After purification and quantification, libraries were sequenced on a MiSeqDx instrument (Illumina, San Diego, CA, USA) using the MiSeq Reagent Kit version 2 (500cycles) with a length of 2×251 bp for all assays.

NGS data analysis
The FASTQ files were analyzed using the LymphoTrack-MiSeq version 2.4.3. software (Invivoscribe, Inc.) according to the manufacturer’s guideline.

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3 / 15PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

IGH clonal rearrangement was determined in the following situations: (i) when the total
number of reads for each sample was �20,000 and the top merged sequence had �2.5% of thetotal reads, then the percent reads for a suspected clonal merged sequence was twice that for
the third-most frequent merged sequence and the result was interpreted as clonal; and (ii)when the total number of reads for each sample was �10,000 but <20,000 and the top merged
sequence had �5% of the total reads, the percent reads for a suspected clonal merged sequence
was twice that for the third-most frequent merged sequence, and the result was interpreted asclonal. IGK clonal rearrangement was determined based on the same interpretation criteria as
for the IGH gene.
The interpretation of the presence of IGHV SHM was as follows: (i) when there was amerged sequence showing evidence of IGH rearrangement clonality according to the above
criteria, both “in-frame” and “no stop codon” values were observed, and the mutation rate
within a partial V-gene was �2.0%, the result was interpreted as SHM being present, whereas
a mutation rate to the partial V-gene of <2.0% signified the absence of SHM; and (ii) when
there was no merged sequence showing evidence of IGH rearrangement clonality according to
the above criteria or when a merged sequence showing evidence of IGH clonality rearrangement according to the above criteria was present, but neither an “in-frame” nor a “no stopcodon” value was observed, the result was interpreted as inconclusive.

Statistical analysis
The Mann–Whitney U-test was used to compare nonparametric quantitative variables
between 2 groups. The linear regression analysis was used to investigate the relationshipbetween 2 quantitative, continuous variables. The Fisher’s exact test was applied to compare
categorical variables between 2 groups; if not applicable, the Pearson’s chi-square test wasapplied instead. P-values less than 0.05 were considered statistically significant. Data were analyzed using MedCalc Statistical Software version 18.9.1 (MedCalc Software bvba, Ostend, Belgium) and Microsoft Excel 2016 (Microsoft, Redmond, Washington, USA).

Results
Characteristics of patients and samples
The characteristics of 57 patients (59 samples) including age, sex, timing of sample collection,
heavy and light chain type, risk group according to the ISS for myeloma, laboratory findings,
bone lesions, and the proportion of lymphoid cells in the BM that were plasma cells are summarized in Table 1. Fifty-two patients had only 1 sample collected at the time of initial diagnosis, while 3 patients had only 1 sample collected at the time of disease monitoring (PE05 at
relapse; PE12 at disease progression; PE34 at disease progression). The remaining 2 patients
had both samples collected at the time of initial diagnosis and at the time of disease monitoring(relapse or disease progression status): PE10 and PE01 were from 1 patient (at the initial diagnosis and at follow-up, respectively) and PE17 and PE18 were from the other patient (at theinitial diagnosis and at follow-up, respectively).

Detection rate of clonal IGH/IGK rearrangements and IGHV SHM
IGH rearrangement testing was performed in all 59 samples from 57 patients, whereas IGK
rearrangement testing was performed in all 53 samples from 51 patients (31 samples from 29
patients with kappa-restricted MM and 22 samples from 22 patients with lambda-restrictedMM) based on sample availability.

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4 / 15PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

Table 1. Characteristics of 59 bone marrow samples from 57 Korean patients with multiple myeloma.
Characteristicn�

No. (%) or median (range)

Sex, M/F

57

32 (56.1%) / 25 (43.9%)

Age (years)

57

70 (44–84)

Timing of sample collection, initial/follow-up (relapse)†

5954 (91.5%) / 5 (8.5%)

Heavy and light chain type: IgG, K / IgG, L / IgA, K / IgA, L /IgD, K / IgD, L / K light chain only / L light chain only57

17 (29.8%) / 10 (17.5%) / 10 (17.5%) / 6(10.5%) / 0 (0.0%) / 3 (5.3%) / 2 (3.5%) / 9(15.8%)

International Scoring System, I/II/III

57

8 (14.0%) / 17 (29.8%) / 32 (56.1%)
5.5 (1.6–22.6)

Beta-2 microglobulin (mg/L)

57

Albumin (g/dL)

57

3.4 (1.7–4.7)

Hemoglobin (mg/dL)

57

8.7 (6.5–13.9)

Creatinine (mg/dL)

57

1.10 (0.27–11.27)

Serum calcium (mg/dL)

57

8.8 (7.7–13.5)

Bone lesions, present/absent

57

44 (77.2%) / 13 (22.8%)

Proportion of plasma cells out of total lymphoid cells in bonemarrow5975.0 (28.5–100.0)

�The number of samples was 59 when analyzing the timing of sample collection and the proportion of plasma cells
among all bone marrow lymphoid cells. The number of patients from whom the samples were derived was 57.
† Two patients had both initial and follow-up samples and another three had only follow-up (relapse) samples.

https://doi.org/10.1371/journal.pone.0253541.t001

The total read counts (median [range]) for IGH rearrangement among the 59 samples andfor IGK rearrangement among 53 samples were 99502 (9234–2146952) and 77399 (21148–
263233), respectively. The coverage of IGHV as determined by the IGHV SHM assay (median[range]) was 99.12% (7.25–100%). The detection rates of clonal IGH/IGK rearrangements and
IGHV SHM according to light chain restriction pattern are summarized in Table 2.
Overall, 52 of 59 samples had clonal IGH and/or IGK rearrangements, which demonstrated
an applicability rate of 88.1% when using the IGH FR1 assay and/or IGK assay in Koreanpatients with MM. Forty of fifty-nine had clonal IGH rearrangements (67.8%) and forty-two offifty-three had clonal IGK rearrangements (79.2%); adding the IGK assay increased the positivity rate of clonal IG gene rearrangement rate from 67.8% to 88.1%. Clonal IGH rearrangements
and clonal IGK rearrangements were observed in 74.2% and 67.7% of samples from patientswith kappa-restricted MM, respectively, and in 60.7% and 95.5% of samples from patients withlambda-restricted MM, respectively. Overall, 90.3% and 85.7% of samples from patients withkappa-restricted MM and lambda-restricted MM, respectively, had clonal IGH and/or IGK
rearrangements. Including the IGK assay increased the positivity rate of clonal IG gene

Table 2. IGH clonality, IGH somatic hypermutation, and IGK clonality according to light chain types in 59 bone marrow samples from 57 Korean patients withmultiple myeloma.
Light chaintype

IGH clonality(+)

IGH SHM (+) among IGH clonality (+)
samples

IGK clonality(+)

Both IGH clonality (+) and IGK
clonality (+)

IGH and/or IGK
clonality

Kappa

23/31 (74.2%)

21/23 (91.3%)

21/31 (67.7%)

16/31 (51.6%)

28/31 (90.3%)

Lambda17/28 (60.7%)

13/17 (76.5%)

21/22 (95.5%)

15/22 (68.2%)

24/28 (85.7%)

Total

40/59 (67.8%)

34/40 (85.0%)42/53 (79.2%)

31/53 (58.5%)

52/59 (88.1%)

SHM, somatic hypermutation; MM, multiple myeloma.
https://doi.org/10.1371/journal.pone.0253541.t002

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5 / 15PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

rearrangement from 74.2 to 90.3% and from 60.7% to 85.7% in kappa-restricted MM andlambda-restricted MM, respectively.
Among all 40 samples exhibiting clonal IGH rearrangements, IGHV SHM was observed in
85.0%, including in 91.3% of samples from patients with kappa-restricted MM and 76.5% of
samples from those with lambda-restricted MM.

Clonal rearrangement versus the proportion of BM plasma cells
Clonal rearrangement was not associated with the BM plasma cells as a proportion of all BM
lymphoid cells as estimated on the BM aspiration slides. The medians (ranges) of BM plasma
cells as a proportion of all BM lymphoid cells were 76.9% (28.5–100.0%) and 67.7% (32.6–
94.5%) in samples with and without clonal IGH rearrangement, respectively (P = 0.227).
When IGH and IGK rearrangements were analyzed together, the medians (ranges) of BM
plasma cells as a proportion of all BM lymphoid cells were 76.4% (28.5–100.0%) and 64.5%(32.6–92.5%) in subjects with clonal IGH and/or IGK rearrangement and in those with norearrangement, respectively (P = 0.138). No or very weak correlation between the quantity of
IGH/IGK rearrangements and the proportion of BM plasma cells as a proportion of all BM
lymphoid cells was observed: y = 0.084x + 70.969 (R = 0.027, P = 0.315) in patients with IGH
rearrangements or y = 0.231x + 59.423 (R = 0.147, P = 0.006) in patients with IGH and/or IGK
rearrangements when only the larger values of the proportion of IGH or IGK rearrangements
were considered.

IGH rearrangement repertoire
To profile the IGH rearrangement repertoire, we analyzed the VDJ gene usage of 43 rearrangements from 39 samples with clonal IGH rearrangement (35 samples with single IGH rearrangement and 4 samples with double IGH rearrangements; a PE18 sample representing a
relapse was excluded because it showed the same result as an initial PE17 sample from thesame patient).
Overall, IGHV3 was the most frequently reported IGHV group gene (67.44%) followed by
IGHV4 (20.93%), IGHV1 (4.65%), IGHV2 (4.65%), and IGHV7 (2.33%). IGHV5 and IGHV6
were not observed in our sample set. Twenty IGHV genes were identified (Table 3); among
them, IGHV3-23 and IGHV3-9 (each of which was observed in 11.63% of the total samples)
were the most frequently reported, followed by IGHV3-30 and IGHV4-31 (each of which wasobserved in 9.30% of the total samples). Comparing IGHV usage between our study and 3 previously published Western studies [7, 8, 24] showed that even though the distribution of the
IGHV gene group in our study was similar to that of Western studies (S1 Table in S2 File, S1
Fig in S1 File), the distribution of IGHV genes was different between ours and Western studies(S2 Table in S2 File, S2 Fig in S1 File). Particularly, IGHV3-9 (11.63%) and IGHV4-31 (9.30%)
were significantly more frequent in our study than in that of Ferrero et al. (4.64%, P = 0.004
and 2.03%, P = 0.024, respectively) [7] and of Medina et al. (4.14%, P < 0.001 and 1.38%,
P = 0.009, respectively) [24]. The overall frequencies of other genes were not significantly different across all 4 studies (including ours).
In the IGHJ group, IGHJ4 was predominant (44.19%) followed by IGHJ6 (25.58%), IGHJ5(16.28%), and IGHJ3 (11.63%). Neither IGHJ1 nor IGHJ2 was reported in our patients. The
IGHJ distribution in our study was similar to that observed in the previous Western studies [7,8, 24] (S3 Table in S2 File, S3 Fig in S1 File).
The most frequently reported IGHD gene group was IGHD3 (34.88%) followed by IGHD2(20.93%), IGHD5 (9.30%), IGHD4 and IGHD6 (4.65% each), and IGHD1 (2.33%). IGHD7 was
not observed in our series. Five samples (11.63%) had D-gene sequences that were not matched

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6 / 15PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

Table 3. The IGHV gene repertoire in 43 IGH rearrangements from 39 samples with clonal IGH rearrangements.
n

%

2

4.65%

IGHV1-21

2.33%

IGHV1-8

1

2.33%

2

4.65%

IGHV1

IGHV2
IGHV2-5
IGHV3

2

4.65%

29

67.44%

IGHV3-214

9.30%

IGHV3-235

11.63%

IGHV3-30

4

9.30%

IGHV3-30-3

2

4.65%

IGHV3-33

2

4.65%

IGHV3-48

1

2.33%

IGHV3-49

1

2.33%

IGHV3-64

1

2.33%

IGHV3-66

1

2.33%

IGHV3-7

1

2.33%

IGHV3-74

2

4.65%

IGHV3-95

11.63%

920.93%

IGHV4-31

4

9.30%

IGHV4-4

1

2.33%

IGHV4-59

2

4.65%

IGHV4-61

2

4.65%

IGHV5

0

0.00%

IGHV6

0

0.00%

IGHV7

1

2.33%

1

2.33%

IGHV4

IGHV7-4-1
https://doi.org/10.1371/journal.pone.0253541.t003

to the reference set of currently known D-region sequences owing to the sequences being
either too short or too distinct to be matched. Another 5 samples (11.63%) did not exhibit any
D-gene sequences. Twenty-seven IGHD genes were identified (Table 4), the most frequently
occurring of which were IGHD3-10 and IGHD3-3 (13.95% each). A comparison of IGHD
usage between our study and 3 previously published Western studies [7, 8, 24] showed thateven though the distribution of the IGHV gene group was similar (S4 Table in S2 File, S4 Fig
in S1 File), IGHD3-3 was more frequent in our study than in that of Medina et al. (13.95% vs.
5.44%, P = 0.038) [24] (S5 Table in S2 File, S5 Fig in S1 File).

IGK rearrangement repertoire
On IGK rearrangement repertoire analysis, 4 rearrangements from 2 samples (PE01 and PE18,
which represented relapses of PE10 and PE17, respectively) were excluded from the repertoire
analysis given that each showed the same rearrangement pattern as its original pre-relapse
sample. Thus, we analyzed the V(D)J gene usage of 85 rearrangements from 40 samples withclonal IGK rearrangement (10 samples with a single IGK rearrangement, 18 with double IGK
rearrangements, 10 with triple IGK rearrangements, and 2 with 4 or 5 IGK rearrangements).
The distribution of IGK locus rearrangements is summarized in Table 5. Overall, the
IGKV-J rearrangement was the most common (17.50%), followed by IGKV-J + IGKV-KDE

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7 / 15PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

Table 4. The IGHD gene repertoire in 43 IGH rearrangements from 39 samples with clonal IGH rearrangements.
n

%

IGHD1

1

IGHD1-14

1

2.33%

IGHD2

9

20.93%

2.33%

IGHD2-15

1

2.33%

IGHD2-2

4

9.30%

IGHD2-21

1

2.33%

IGHD2-8

3

6.98%

IGHD3

15

34.88%

IGHD3-10

6

13.95%

IGHD3-16

2

4.65%

IGHD3-3

6

13.95%

IGHD3-9

1

2.33%

IGHD4

2

4.65%

IGHD4-17

1

2.33%

IGHD4-23

1

2.33%

IGHD5

4

9.30%

IGHD5-123

6.98%

IGHD5-5

1

2.33%

IGHD6

2

4.65%

IGHD6-13

2

4.65%

Unknown�

5

11.63%

Not found5

11.63%

https://doi.org/10.1371/journal.pone.0253541.t004

and IGKV-J + IGKJ-C-intron-KDE (15.00% each). In kappa-restricted MM, the IGKV-J rearrangement was the most common (31.58%) followed by IGKV-J + IGKV-KDE (26.32%); eachof which was observed only in 4.76% of lambda-restricted MM. In lambda-restricted MM,
IGKV-J + IGKJ-C-intron-KDE and IGKV-J + IGKV-KDE + IGKJ-C-intron-KDE were the mostcommon types (19.05% each). A comparison between our study and a previous Western analysis [24] showed that a lack of IGK rearrangement was significantly more frequent among ourpatients (21.57% vs. 7.06%, P = 0.017), particularly in kappa-restricted MM (34.48% vs. 0.00%,
P < 0.001) (S6 Table in S2 File, S6 Fig in S1 File). Furthermore, single IGKV-J rearrangement
was less frequent in Korean patients with kappa-restricted MM than in their Western counterparts (20.69% vs. 44.19%, P = 0.047).
IGKV1 was the most frequently observed IGKV gene group (32.94%), followed by IGKV2(22.35%), and IGKV3 (12.94%). IGKV4, IGKV5, and IGKV7 were observed in a minority ofthe series (5.56%, 2.78%, and 2.78%, respectively). The remaining 13.89% were observed inrearrangements involving IGKJ-C-intron-KDE.
The most frequently observed IGKV gene was IGKV2-30 (11.76%), followed by IGKV1D-33(10.59%) in the total series, comprising 13.89% each in kappa-restricted MM and 10.20% and8.16% in lambda-restricted MM, respectively (Table 6). A comparison between our study anda previous Western analysis [24] showed that IGKV4-1 was significantly less frequent in ourseries regardless of light chain type than in the Western study (where it was the most frequentgene): 3.53% vs. 22.54% in kappa-restricted MM (P < 0.001), 5.56% vs. 11.54% in lambdarestricted MM (P = 0.037), and 2.04% vs. 21.05% in the total series (P = 0.019) (S7 Table in S2
File, S7 Fig in S1 File).

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8 / 15PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

Table 5. Distribution of 85 IGK locus rearrangements from 40 samples with clonal igk rearrangement.
Kappa-restricted MM

Lambda-restricted MM

n = 19%n = 21%n = 40Total%

IGKV-J6

31.58%

1

4.76%

7

17.50%

IGKV-KDE

1

5.26%

2

9.52%

3

7.50%

IGKJ-C-intron-KDE

0

0.00%

0

0.00%

0

0.00%

IGKV-J + IGKV-J

1

5.26%

2

9.52%

3

7.50%

IGKV-J + IGKV-KDE

526.32%

1

4.76%

6

15.00%

IGKV-J + IGKJ-C-intron-KDE

2

10.53%

4

19.05%

6

15.00%

IGKV-KDE + IGKJ-C-intron-KDE

0

0.00%

2

9.52%

2

5.00%

2 IGKV-KDE

0

0.00%

1

4.76%

1

2.50%

2 IGKV-J + IGKJ-C-intron-KDE

2

10.53%

0

0.00%

2

5.00%

IGKV-J + IGKV-KDE + IGKJ-C-intron-KDE

1

5.26%

4

19.05%

5

12.50%

2 IGKV-KDE + IGKJ-C-intron-KDE

0

0.00%

1

4.76%

1

2.50%

IGKV-J + 2 IGKJ-C-intron-KDE

0

0.00%

2

9.52%

2

5.00%

Others (4 or 5 rearrangements)

1

5.26%

1

4.76%

2

5.00%

https://doi.org/10.1371/journal.pone.0253541.t005

Table 6. The IGKV(D) gene repertoire in 85 igk rearrangements from 40 samples with clonal igk rearrangements.
Kappa-restricted MM

Lambda-restricted MM

%

1

2.78%

IGKV1-52

5.56%

IGKV1-91

2.78%

IGKV1D-12

1

2.78%

1

1.18%

IGKV1D-33

5

13.89%

4

8.16%

9

10.59%

IGKV1-17
IGKV1-27

n = 49%Total

n = 36n = 85

%

2

2.35%

3

6.12%

2

2.35%

1

2.04%

3

3.53%

1

1.18%

IGKV1D-37

1

2.78%

2

4.08%

3

3.53%

IGKV1D-39

3

8.33%

3

6.12%

6

7.06%

1

2.04%

1

1.18%

1

1.18%

IGKV1D-8
IGKV2-24

1

2.78%

IGKV2-29

2

4.08%

2

2.35%

IGKV2-30

513.89%

5

10.20%

10

11.76%

IGKV2D-26

1

2.78%

1

2.04%

2

2.35%

IGKV2D-28

1

2.78%

1

2.04%

2

2.35%

1

2.04%

1

1.18%

1

1.18%

2

2.35%

1

1.18%

IGKV2D-29
IGKV2D-40

1

2.78%

IGKV3-11

1

2.78%

IGKV3-15

1

2.78%

IGKV3-7
IGKV3D-20

2

5.56%

IGKV3D-7

1

2.04%

2

4.08%

2

2.35%

3

6.12%

5

5.88%

1

2.04%

1

1.18%

IGKV4-1

2

5.56%

1

2.04%

3

3.53%

IGKV5-2

1

2.78%

1

2.04%

2

2.35%

IGKV7-3

1

2.78%

Intron-KDE

513.89%

16

32.65%

1

1.18%

21

24.71%

https://doi.org/10.1371/journal.pone.0253541.t006

PLOS ONE | https://doi.org/10.1371/journal.pone.0253541 June 24, 2021

9 / 15PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

IGKJ4 was predominant (20.00%) followed by IGKJ2 (11.76%), IGKJ1 (7.06%), IGKJ3(4.71%), and IGKJ5 (3.53%). The remaining 52.94% were observed in rearrangements involving IGKJ-C-intron-KDE, IGKV-KDE, or rearrangements with no J-gene.

Discussion
We investigated the applicability of the only commercially available NGS-based IG gene rearrangement test and analyzed the repertoire of IGH and IGK gene usage in Korean patientswith MM at baseline for the first time. Clonal IGH and/or IGK rearrangements were observedin 88.1% of the samples. No significant association was observed between clonal rearrangement and the proportion of BM lymphoid cells that were plasma cells. The IGH and IGK repertoires were similar to those found in previous studies of Western patients with the following
exceptions: (i) IGHV3-9 (11.63%) and IGHV4-31 (9.30%) were significantly more frequent inour study than in the Western studies (4.64% and 4.14% vs. 2.03% and 1.38%); (ii) IGHD3-3(13.95%) was more frequent in our study than in a Western study (5.44%); (iii) IGK rearrangements were more frequently absent in our study than in a Western series (21.57% vs. 7.06%),
particularly in kappa-restricted MM (34.48% vs. 0.00%); (iv) single IGKV-J rearrangements
were less frequent in Korean patients with kappa-restricted MM (20.69%) than in their Western counterparts (44.19%); and (v) IGKV4-1 was significantly less frequent in our study but
was the most common rearrangement in Western studies (3.53% vs. 22.54% in kapparestricted MM, 5.56% vs. 11.54% in lambda-restricted MM, and 2.04% vs. 21.05% overall).
NGS-based IG gene rearrangement testing can identify clonality markers in patients withlymphoproliferative conditions, including lymphoid malignancies such as MM. This serves todistinguish such lymphoid malignancies from reactive processes [10, 11], identify any clonalrelationships of recurrent lesions in the same patient [5], and monitor for any minimal residual disease [16]. NGS-based testing also has some advantages over flow cytometry in terms ofthe detection of clonal plasma cells as follows: (i) it does not require immediate analysis offresh samples and can be applied to archived samples, (ii) it provides the sequence informationof the clonal rearrangement, and (iii) it is barely affected by immunophenotypic changes that
occur owing to chemotherapy [25]. Flow cytometry can be universally applied to almost all
patients [26]. The technical feasibility of NGS-based IG gene rearrangement testing for a particular disease depends on the detection rate of clonal rearrangement within IG genes at baseline; however, this has only recently been investigated in very few studies of MM whereas it
has been extensively explored in patients with acute lymphoblastic leukemia. Ours is the firststudy to investigate the applicability of such a test in Koreans with MM. We found that thedetection rate of clonal rearrangements using the NGS-based IGH FR1 assay and/or IGK assay(LymphoTrack1 IGH FR1 and IGK assays) was 88.1%. The detection rates of clonal IGH and/or IGK rearrangements were similar to those from other studies even though the sizes andcompositions of the study populations, the primer sets, and methodologies between them varied. In a study using the LymphoTrack1 IGH FR1, IGH FR2, IGH FR3, IGH leader, and IGK
assays, Rustad et al. reported an overall clonality detection rate of 81% in patients with MM[9]. The detection rates of IGH FR1, IGH FR2, and IGH FR3 were similar (approximately50%). They did not specify the additive values of the FR2 and FR3 primer sets [9]. In anotherstudy using the same primer sets, Arcila et al. reported an overall clonality detection rate of
approximately 95% [4]. However, it was around 70% for MM but around 95% for B-acute lymphoblastic leukemia when only the IGH FR1 primer set was used. They claimed that the leader
assay showed a significant additive value even though they did not specify it; moreover, thesubsequent use of the FR2 and FR3 primers did not significantly increase the clonal detection
rate in their study. Since only the IGH FR1 primer set was available in Korea, we were not able

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PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

to compare our results directly to those of studies in which other IGH primer sets including
IGH FR2 and IGH FR3 were tested.
We used the IGK primer sets to investigate whether there were any additional benefits totesting light chain gene rearrangement. Adding the IGK test increased the detection rate from
67.8% to 88.1% in the total series (from 74.2% to 90.3% in kappa-restricted MM and from
60.7% to 85.7% in lambda-restricted MM); illustrating that an additional benefit indeed exists.
As only a few studies evaluated the usefulness of the IGK rearrangement test with different setsof primers, we were not able to compare our results directly to those of previous studies. Rustad et al. reported an overall clonal IGK rearrangement rate of 55% using the LymphoTrack1
IGK assay but did not specify the value of adding the IGK assay to IGH assays [9]. They
reported V–J and KDEL rearrangements in 78% and 16% of kappa-restricted samples, respectively; these rates were 57.1% and 35.7%, respectively, in our study. Arcila et al. [4] reported
that the IGK assay help maximize detection [27, 28] in approximately 6–7% of diffuse large B
cell lymphomas and that plasma cell neoplasms remain without a detectable clones when only
IGH is targeted. Interestingly, Rustad et al. found that the success rate of the IGK assay inpatients with lambda-restricted MM (72%) was significantly higher than that in patients withkappa-restricted MM (45%) [9]. This was attributed to lambda light chain expression requiring
a functional lambda light chain gene, which happens only after both IGK alleles have been
inactivated through the rearrangement of the KDE region to partner with either Vk in naïve
IGK alleles or with the intronic region between Jk and Ck. A similar phenomenon was observedin our study in that clonal IGK rearrangements were observed in 67.7% of samples frompatients with kappa-restricted MM and 95.5% of those with lambda-restricted MM, demonstrating the benefit of IGK testing in addition to IGH in such patients.
The presence and extent of clonal rearrangement and the proportion of BM plasma cells as
a proportion of all BM lymphoid cells were not significantly correlated in our study. There wasa huge overlap in BM plasma cells as a proportion of all BM lymphoid cells between patientswith clonal IGH and/or IGK rearrangement and those without any statistical significance(median [range]: 76.4 [28.5–100.0%] and 64.5 [32.6–92.5%]). Most previous studies did notinvestigate the association between clonal IG gene rearrangement and the proportion of BM
plasma cells. Rustad et al. suggested that low tumor cell content was the main reason for the
failure to identify a clonal V(D)J sequence; while samples with more than 5% plasma cells had
a 97% clonality detection rate, those with less than 5% plasma cells had a detection rate of~70% [9]. However, they also acknowledged an extensive overlap between groups with andwithout clonal rearrangement, which was consistent with our own findings. In a study of Bcell neoplasm samples that included MM, Arcila et al. reported that some samples with 5–68%
tumor content remained nonclonal when tested using IGH primer sets [4], suggesting that thetumor cell proportion itself does not necessarily influence the detection of clonal rearrangement. Similar to the BIOMED-2/EuroClonality approach, NGS-based clonality assessment
also relies on an initial multiplex PCR step, which could still be hampered by somatic hypermutation and specific polymorphisms that might prevent primer annealing [5]. Indeed, studies
aimed at validating the limit of detection and linearity of NGS-based IG gene rearrangement
tests found that clonal rearrangements could be traced to dilutions as low as 2.5% [4, 5]. Additional studies with a larger number of samples and with variable plasma cell percentages would
be helpful for clarifying the impact of the plasma cell proportion on clonality detection.
The repertoire of IGH and IGK gene usage in Korean patients with MM has not beenreported to date; although data from few Western studies exist [7, 8, 24], there are no datafrom studies on Asian patients. Notably, a comparison between our findings and those of previous Western studies revealed that IGHV3-9, IGHV4-31, and IGHD3-3 were common in
Korean patients with MM but not in Western patients; no IGK rearrangement was found to be

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PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

more frequent in Korean patients than in Western counterparts, particularly among thosewith kappa-restricted MM. Moreover, the single IGKV-J rearrangement type was more frequent in Western patients with kappa-restricted MM than in Korean counterparts; IGKV4-1
was more frequent in Western than in Korean patients regardless of light chain type. These
data suggested the existence of ethnicity-based differences in disease risk and manifestation [7,8, 24]. Otherwise, the IGH and IGK repertoire distribution in our study showed a similar pattern to those of Western studies [7, 8, 24]. Ferrero et al. found that IGH gene usage in MM was
similar to that of normal plasma cells [7]. Hadzidimitriou et al. reported that the IGH repertoire followed a similar pattern to that of the normal repertoire [8]. They also reported that the
IGHV4-34 gene was rarely observed in MM, which was consistent with older IG profiling studies in patients with this disease [29–31]; in contrast, the IGHV4-34 gene is common in B-lymphoid malignancies, particularly chronic lymphocytic leukemia [8]. Medina et al. reported thatgene selection was biased in MM, with a significant overrepresentation of IGHV3, IGHD2, andIGHD3, as well as of the IGHJ4 gene group, compared to the normal B-cell repertoire [24].
IGKV-J rearrangement was the most common (8 of 14, 57.1%), followed by KDE (5 of 14,
35.7%). IGKJ4 was the most predominant (5 of 14, 35.7%), and the distribution of the IGK
gene usage in our study was similar to those found in previous studies except that the most frequent IGK gene observed in the only available Western study that analyzed the IGK repertoire,
IGKV4-1, was not observed among our patients [8]. This also could be attributed to ethnicitybased or risk group differences. Further studies involving a larger number of Korean patientswith MM would be helpful for confirming our observations.
The strengths of our study include that (i) we investigated the applicability of the NGSbased IGH/IGK rearrangement test for the detection of clonality in Asians with MM for the
first time, (ii) we analyzed the profiles of IGH and IGK gene usage in Asians with MM andcompared them with those from previous Western studies for the first time, and (iii) we investigated the association between clonal IGH/IGK rearrangement and the proportion of BM lymphoid cells that were plasma cells. Nevertheless, there were a few limitations, some
aforementioned, as follows: (i) the number of samples was relatively small, (ii) the majority ofsamples were from high-risk patients with a relatively high percentage of BM plasma cells, and(iii) IGH FR2 and IGH FR3 tests were not performed.
In summary, we showed that clonal IGH and/or IGK rearrangements were detected in
88.1% of Koreans with MM at baseline, indicating that such tests are applicable to most Koreanpatients with this disease to determine clonality and to monitor those under treatment. The
profile of IGH and IGK gene usage in Koreans with MM was similar to those found in Western
MM studies. However, IGHV3-9, IGHV4-31, and IGHD3-3 were overrepresented among
Korean patients, whereas IGKV4-1 was underrepresented. No IGK rearrangement was foundto be more common in Koreans with kappa-restricted MM, although the IGKV-J rearrangement type was more frequent in Western counterparts. This implied the existence of certain
ethnicity-based differences in the characteristics of patients with MM.

Supporting information
S1 File.
(DOCX)
S2 File.
(DOCX)
S3 File.
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PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

Author Contributions
Conceptualization: Hyo Jung Kim, Hee Jung Kang, Young Kyung Lee.
Data curation: Miyoung Kim, Kibum Jeon, Kasey Hutt, Alyssa M. Zlotnicki, Jiwon Lee.
Formal analysis: Miyoung Kim, Kibum Jeon, Kasey Hutt, Alyssa M. Zlotnicki, Jiwon Lee.
Investigation: Miyoung Kim, Kibum Jeon, Kasey Hutt, Alyssa M. Zlotnicki, Hyo Jung Kim,
Hee Jung Kang.
Methodology: Kibum Jeon, Kasey Hutt, Alyssa M. Zlotnicki, Hyo Jung Kim, Jiwon Lee, HanSung Kim, Young Kyung Lee.
Project administration: Han-Sung Kim, Hee Jung Kang.
Resources: Jiwon Lee, Han-Sung Kim, Hee Jung Kang.
Supervision: Hyo Jung Kim, Young Kyung Lee.
Visualization: Miyoung Kim.
Writing – original draft: Miyoung Kim.
Writing – review & editing: Miyoung Kim, Young Kyung Lee.

References
1.

Hideshima T, Bergsagel PL, Kuehl WM, Anderson KC. Advances in biology of multiple myeloma: clinical applications. Blood. 2004; 104(3):607–18. https://doi.org/10.1182/blood-2004-01-0037 PMID:
15090448

2.

van Zelm MC, van der Burg M, de Ridder D, Barendregt BH, de Haas EF, Reinders MJ, et al. Ig generearrangement steps are initiated in early human precursor B cell subsets and correlate with specifictranscription factor expression. J Immunol. 2005; 175(9):5912–22. https://doi.org/10.4049/jimmunol.
175.9.5912 PMID: 16237084

3.

Dik WA, Pike-Overzet K, Weerkamp F, de Ridder D, de Haas EF, Baert MR, et al. New insights onhuman T cell development by quantitative T cell receptor gene rearrangement studies and gene expression profiling. J Exp Med. 2005; 201(11):1715–23. https://doi.org/10.1084/jem.20042524 PMID:
15928199

4.

Arcila ME, Yu W, Syed M, Kim H, Maciag L, Yao J, et al. Establishment of immunoglobulin Heavy (IGH)
chain clonality testing by next-generation sequencing for routine characterization of B-cell and plasma
cell neoplasms. J Mol Diagn. 2019; 21(2):330–342. https://doi.org/10.1016/j.jmoldx.2018.10.008 PMID:
30590126

5.

Scheijen B, Meijers RWJ, Rijntjes J, van der Klift MY, Möbs M, Steinhilber J, et al. Next-generation
sequencing of immunoglobulin gene rearrangements for clonality assessment: a technical feasibility
study by EuroClonality-NGS. Leukemia. 2019; 33(9):2227–2240. https://doi.org/10.1038/s41375-0190508-7 PMID: 31197258

6.

Langerak AW, Groenen PJ, Brüggemann M, Beldjord K, Bellan C, Bonello L, et al. EuroClonality/
BIOMED-2 guidelines for interpretation and reporting of Ig/TCR clonality testing in suspected lymphoproliferations. Leukemia. 2012; 26(10):2159–71. https://doi.org/10.1038/leu.2012.246 PMID: 22918122

7.

Ferrero S, Capello D, Svaldi M, Boi M, Gatti D, Drandi D, et al. Multiple myeloma shows no intra-disease
clustering of immunoglobulin heavy chain genes. Haematologica. 2012; 97(6):849–53. https://doi.org/
10.3324/haematol.2011.052852 PMID: 22207685

8.

Hadzidimitriou A, Stamatopoulos K, Belessi C, Lalayianni C, Stavroyianni N, Smilevska T, et al. Immunoglobulin genes in multiple myeloma: expressed and non-expressed repertoires, heavy and light chain
pairings and somatic mutation patterns in a series of 101 cases. Haematologica. 2006; 91(6):781–7.
PMID: 16769580

9.

Rustad EH, Hultcrantz M, Yellapantula VD, Akhlaghi T, Ho C, Arcila ME, et al. Baseline identification of
clonal V(D)J sequences for DNA-based minimal residual disease detection in multiple myeloma. PLoS
One. 2019; 14(3):e0211600. https://doi.org/10.1371/journal.pone.0211600 PMID: 30901326

10.

Arber DA. Molecular diagnostic approach to non-Hodgkin’s lymphoma. J Mol Diagn. 2000; 2(4):178–90.
https://doi.org/10.1016/S1525-1578(10)60636-8 PMID: 11232108

PLOS ONE | https://doi.org/10.1371/journal.pone.0253541 June 24, 2021

13 / 15

PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

11.

Gazzola A, Mannu C, Rossi M, Laginestra MA, Sapienza MR, Fuligni F, et al. The evolution of clonality
testing in the diagnosis and monitoring of hematological malignancies. Ther Adv Hematol. 2014; 5(2):35–47 https://doi.org/10.1177/2040620713519729 PMID: 24688753

12.

Boyd SD, Marshall EL, Merker JD, Maniar JM, Zhang LN, Sahaf B, et al. Measurement and clinical monitoring of human lymphocyte clonality by massively parallel VDJ pyrosequencing. Sci Transl Med. 2009;
1(12):12ra23. https://doi.org/10.1126/scitranslmed.3000540 PMID: 20161664

13.

Kotrova M, Muzikova K, Mejstrikova E, Novakova M, Bakardjieva-Mihaylova V, Fiser K, et al. The predictive strength of next-generation sequencing MRD detection for relapse compared with current methods in childhood ALL. Blood. 2015; 126(8):1045–7. https://doi.org/10.1182/blood-2015-07-655159
PMID: 26294720

14.

Langerak AW, Bruggemann M, Davi F, Darzentas N, van Dongen JJM, Gonzalez D, et al. EuroClonality-NGS Consortium: High-throughput immunogenetics for clinical and research applications in immunohematology: potential and challenges. J Immunol. 2017; 198(10):3765–3774. https://doi.org/10.
4049/jimmunol.1602050 PMID: 28416603

15.

Munshi NC, Anderson KC. Minimal residual disease in multiple myeloma. J Clin Oncol. 2013; 31(20):2523–2526. https://doi.org/10.1200/JCO.2013.49.2124 PMID: 23733782

16.

Kumar S, Paiva B, Anderson KC, Durie B, Landgren O, Moreau P, et al. International Myeloma Working
Group consensus criteria for response and minimal residual disease assessment in multiple myeloma.
Lancet Oncol. 2016; 17(8):e328–e346. https://doi.org/10.1016/S1470-2045(16)30206-6 PMID:
27511158

17.

González D, van der Burg M, Garcı́a-Sanz R, Fenton JA, Langerak AW, González M, et al. Immunoglobulin gene rearrangements and the pathogenesis of multiple myeloma. Blood. 2007; 110(9):3112–
21. https://doi.org/10.1182/blood-2007-02-069625 PMID: 17634408

18.

Bakkus MH, Van Riet I, Van Camp B, Thielemans K. Evidence that the clonogenic cell in multiple myeloma originates from a pre-switched but somatically mutated B cell. Br J Haematol. 1994; 87(1):68–74.
https://doi.org/10.1111/j.1365-2141.1994.tb04872.x PMID: 7947257

19.

Hong J, Lee JH. Recent advances in multiple myeloma: a Korean perspective. Korean J Intern Med.
2016; 31(5):820–34. https://doi.org/10.3904/kjim.2015.408 PMID: 27604794

20.

Kyle RA, Therneau TM, Rajkumar SV, Offord JR, Larson DR, Plevak MF, et al. A long-term study ofprognosis in monoclonal gammopathy of undetermined significance. N Engl J Med. 2002; 346(8):564–
9. https://doi.org/10.1056/NEJMoa01133202 PMID: 11856795

21.

Jung KW, Won YJ, Kong HJ, Oh CM, Cho H, Lee DH, et al. Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2012. Cancer Res Treat. 2015; 47(2):127–41. https://doi.org/10.4143/
crt.2015.060 PMID: 25761484

22.

Lee JH, Lee DS, Lee JJ, Chang YH, Jin JY, Jo DY, et al. Multiple myeloma in Korea: past, present, andfuture perspectives. Experience of the Korean Multiple Myeloma Working Party. Int J Hematol. 2010; 92(1):52–7. https://doi.org/10.1007/s12185-010-0617-6 PMID: 20544403

23.

Kim SJ, Kim K, Kim BS, Jo DY, Kang HJ, Kim JS, et al. Clinical features and survival outcomes inpatients with multiple myeloma: analysis of web-based data from the Korean Myeloma Registry. Acta
Haematol. 2009; 122(4):200–10. https://doi.org/10.1159/000253027 PMID: 19887776

24.

Medina A, Jiménez C, Sarasquete ME, González M, Chillón MC, Balanzategui A, et al. Molecular profiling of immunoglobulin heavy-chain gene rearrangements unveils new potential prognostic markers for
multiple myeloma patients. Blood Cancer J. 2020 Feb 6; 10(2):14. https://doi.org/10.1038/s41408-0200283-8 PMID: 32029700

25.

Romano A, Palumbo GA, Parrinello NL, Conticello C, Martello M, Terragna C. Minimal Residual Disease Assessment Within the Bone Marrow of Multiple Myeloma: A Review of Caveats, Clinical Significance and Future Perspectives. Front Oncol. 2019; 9:699. https://doi.org/10.3389/fonc.2019.00699
PMID: 31482061

26.

Paiva B, Martinez-Lopez J, Vidriales MB, Mateos MV, Montalban MA, Fernandez-Redondo E, et al.
Comparison of immunofixation, serum free light chain, and immunophenotyping for response evaluationand prognostication in multiple myeloma. J Clin Oncol. 2011; 29(12):1627–33. https://doi.org/10.1200/
JCO.2010.33.1967 PMID: 21402611

27.

Evans PA, Pott C, Groenen PJ, Salles G, Davi F, Berger F, et al. Significantly improved PCR based
clonality testing in B-cell malignancies by use of multiple immunoglobulin gene targets: Report of the
BIOMED-2 Concerted Action BHM4-CT98-3936. Leukemia. 2007; 21(2):207–14. https://doi.org/10.
1038/sj.leu.2404479 PMID: 17170731

28.

Liu H, Bench AJ, Bacon CM, Payne K, Huang Y, Scott MA, et al. A practical strategy for the routine useof BIOMED-2 PCR assays for detection of B- and T-cell clonality in diagnostic haematopathology. Br J
Haematol. 2007; 138(1):31–43. https://doi.org/10.1111/j.1365-2141.2007.06618.x PMID: 17555445

PLOS ONE | https://doi.org/10.1371/journal.pone.0253541 June 24, 2021

14 / 15

PLOS ONEIGH/IGK repertoire in Korean patients with multiple myeloma

29.

Rettig MB, Vescio RA, Cao J, Wu CH, Lee JC, Han E, et al. H gene usage is multiple myeloma: complete absence of the VH4.21 (VH4-34) gene. Blood. 1996; 87(7):2846–52. PMID: 8639903

30.

Vescio RA, Cao J, Hong CH, Lee JC, Wu CH, Der Danielian M, et al. Myeloma Ig heavy chain V region
sequences reveal prior antigenic selection and marked somatic mutation but no intraclonal diversity. J
Immunol. 1995; 155(5):2487–97. PMID: 7650379

31.

González D, González M, Balanzategui A, Sarasquete ME, López-Pérez R, Chillón MC, et al. Molecularcharacteristics and gene segment usage in IGH gene rearrangements in multiple myeloma. Haematologica. 2005; 90(7):906–13. PMID: 15996928

PLOS ONE | https://doi.org/10.1371/journal.pone.0253541 June 24, 2021

15 / 15