Tumor-specific but not nonspecific cell-free circulating DNA
can be used to monitor disease response in lymphoma
Kimberley Jones,1,2 Jamie P. Nourse,1 Colm Keane,1,3 Pauline Crooks,1 David Gottlieb,4
David S. Ritchie,5 Devinder Gill,2,3 and Maher K. Gandhi1,2,3*
Recently, nontumor specific circulating DNA was shown to be elevated in a broad range of lymphomas,
implicating a role as a potential biomarker. Epstein-Barr virus’ (EBV) presence within a proportion of lymphomas implies EBV-DNA has potential as a lymphoma-specific disease response biomarker. However,
application would be restricted to EBV-associated lymphomas. Neither detailed comparison has been
performed of lymphoma-specific versus nonspecific DNA as disease response biomarkers nor have the
kinetics of circulating DNA during treatment been established, and the optimal methodology remains
unknown. We prospectively evaluated DNA levels and clinical response of 63 lymphoma patients. DNA was
measured in paired serum, plasma, and cell samples at five predetermined time-points taken prior, during
and following treatment. Both cell-free (c-f) circulating EBV-DNA (in EBV-associated lymphoma) and nonspecific c-f DNA levels (in all lymphomas) were elevated and discriminatory at presentation compared to
healthy controls. Nonspecific c-f DNA was significantly associated with baseline serum lactate dehydrogenase. Within EBV-associated lymphomas at presentation, there was a strong correlation between specific
and nonspecific circulating c-f DNA (r 5 0.9, P < 0.0001). However, only c-f EBV-DNA correlated with
clinical/radiological response. In addition, c-f EBV-DNA, and not nonspecific c-f DNA, provided an early
marker of relapsed and refractory disease. Serum versus plasma, and single versus multiple-copy EBVgene targets were equivalent. Lymphoma-specific DNA is a disease response biomarker; however,
nonspecific DNA reflected neither lymphoma-specific DNA nor therapeutic response. Lymphoma disease
response can be monitored by blood tests, but new lymphoma-specific biomarkers need to be identified to
C 2011 Wiley Periodicals, Inc.
broaden applicability. Am. J. Hematol. 87:258–265, 2012. V
Introduction
In lymphoma, tumor burden and treatment response are
currently assessed by clinical evaluation supplemented by
computerized tomography or positron emission tomography
(PET) scans. Although invaluable, these methods have
their limitations and interpretation can be difficult [1].
Disease response biomarkers have the potential to enable
clinicians to monitor their patient’s progress by a simple
test. They may also serve as an early predictor of disease
relapse. There are currently no such markers in lymphoma.
It is known that indirect blood markers of biological activity
such as serum lactate dehydrogenase (LDH) are frequently
elevated at baseline in a variety of lymphomas including
Hodgkin lymphoma, diffuse large B-cell lymphoma
(DLBCL), and post-transplant lymphoproliferative disorder
(PTLD) [2–4]. However, once therapy has commenced its
lack of specificity precludes its clinical value as a measure
of disease response. A noninvasive, highly specific biomarker that accurately reflects response to therapy would
greatly assist treatment-related decision making.
Recently, it has been established that nonspecific circulating DNA is elevated in lymphoma patients of various histological subtypes. One study assessing nontumor-specific
circulating cell-free (c-f) DNA levels at presentation found a
significant association with elevated LDH levels [5]. A subsequent study found elevated levels at presentation that
decreased once in remission [6]. Thus, data suggest that
c-f circulating DNA has potential as part of the lymphoma
diagnostic work-up and to evaluate therapeutic response,
with the advantage of wide-spread applicability to various
histological subtypes.
Alternatively, the demonstration that c-f tumor-derived
DNA is elevated in the plasma or serum of cancer patients
raises the possibility of a highly specific blood biomarker
that accurately reflects tumor load [7–9]. Epstein-Barr virus
(EBV) is a ubiquitous herpes-virus that is present within the
malignant tissue of a variety of lymphomas, albeit only in a
proportion of cases [10]. The presence of EBV within the
lymphomatous node and the close proximity of the lymphoid and blood circulation indicates potential as a highly
tumor-specific biomarker. Accordingly, we and other groups
have shown that EBV-DNA is increased in the peripheral
blood of patients with a variety of EBV-associated cancers
including classical Hodgkin lymphoma (cHL), PTLD, extranodal NK-T cell lymphoma, and nasopharyngeal carcinoma
[11–14]. In cHL, plasma EBV-DNA is associated with
adverse biological characteristics [15]. Viral load appears to
become undetectable in remission but remains high in
refractory disease or returns at relapse, supporting the use
of EBV-viral load as a biomarker for EBV-positive lymphoma patients [12,13,16,17]. Importantly, it is yet to be
1
Clinical Immunohaematology Laboratory, Queensland Institute of Medical
Research, Brisbane, Australia; 2School of Medicine, University of Queensland,
Brisbane, Australia; 3Department of Haematology, Princess Alexandra
Hospital, Brisbane, Australia; 4Blood and Marrow Transplant Service, Westmead Hospital, Sydney, New South Wales, Australia; 5Department of Haematology, Peter MacCallum Cancer Centre and University of Melbourne, Melbourne, Australia
Conflict of interest: Nothing to report.
Additional Supporting Information may be found in the online version of this
article.
*Correspondence to: Maher K. Gandhi, Clinical Immunohaematology Laboratory, Queensland Institute of Medical Research, 300 Herston Rd., Brisbane,
QLD, 4006, Australia. E-mail: maher.gandhi@qimr.edu.au
Contract grant sponsors: NHMRC (Australia), the Leukaemia Foundation,
the Cancer Council of Queensland, the Queensland Smart State, Leukaemia
Foundation Scholarship, the Australian Centre for Vaccine Development,
Boehringer Ingelheim Fonds.
Received for publication 19 October 2011; Revised 2 November 2011;
Accepted 4 November 2011
Am. J. Hematol. 87:258–265, 2012.
Published online 8 November 2011 in Wiley Online Library (wileyonlinelibrary.com).
DOI: 10.1002/ajh.22252
C 2011 Wiley Periodicals, Inc.
V
American Journal of Hematology
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Research Article
Histology
EBER-ISH
No. of patients
Gender
Mean age
LDH (Mean; Range)
No. of stage I/II
B-Symptoms
NEGATIVE
POSITIVE
5
8
3F:2M
6F:2M
57
45
258; 193–347
274; 102–708
2
4
4 Yes: 1 No
3 Yes: 5 No
NEGATIVE
POSITIVE
23
13
11F:12M
5F:8M
37
37
350; 109–1331
291; 178–551
10
7
10 Yes: 13 No
4 Yes: 9 No
NEGATIVE
POSITIVE
5
4
2F:3M
2F:2M
71
58
421; 184–784
486; 143–1217
2
2
2 Yes: 3 No
1 Yes: 3 No
NEGATIVE
POSITIVE
0
4
–
4F
–
42
–
536; 212–1102
–
1
–
1 Yes: 3 No
NEGATIVE
POSITIVE
0
1
–
1M
–
58
–
238
–
0
–
1 Yes
NEGATIVE
POSITIVE
33
30
16F:17M
17F:13M
45
43
348; 109–1331
343; 102–1102
14
14
16 Yes: 17 No
10 Yes: 20 No
PTLD
Hodgkin Lymphoma
Diffuse Large B-cell Lymphoma
Lymphomatoid Granulomatosis
Angioimmunoblastic T-cell lymphoma
Total
established if the viral load mimics tumor burden during
treatment. This data are essential to assess the role of
EBV-DNA as a disease response biomarker.
Neither detailed comparison has been performed of
tumor-specific versus nonspecific DNA as biomarkers in
lymphoma nor have the kinetics of circulating DNA during
treatment or the optimal methodology been established.
With this in mind, we prospectively evaluated and compared EBV-viral load and c-f human genomic DNA levels
(using albumin as the target gene) with clinical response in
63 lymphoma patients. DNA was measured in paired
serum, plasma, and cellular samples at five predetermined
time-points taken prior, during and following treatment, and
results stratified by EBV-tissue status.
Methods
Patients. Newly diagnosed lymphoma adult patients (aged = 18
years), classified according to the World Health Organization classification criteria [18], were eligible. All patients were enrolled before therapy.
To provide a histologically relevant EBV-tissue negative control population, both EBV-tissue positive and negative patients were recruited.
Inclusion was restricted to lymphoma patients with specific morphological subtypes. These were HL, DLBCL, B-cell PTLD, lymphomatoid
granulomatosis (LYG), and angioblastic T-cell lymphoma (AITL). HL,
DLBCL, and B-cell PTLD accounted for 92% of patients. The histologies were chosen as it was known that in a proportion of patients,
EBV-positivity would likely be present within B-cells in the malignant
tissue. With respect to HL, DLBCL, PTLD, and LYG, EBV-positivity is
found within the malignant B-cell. By contrast, AITL is characterized by
a malignant T-cell population surrounded by infiltrating B-cells that
are typically EBV-positive. EBV-tissue positivity was confirmed by
EBV-encoded RNA in situ hybridization (EBER-ISH) in conjunction with
hematoxylin and eosin staining, as previously described [12]. Patients
with EBV-positive tissue are hence forth referred to as having EBVassociated lymphoma, and EBV-negative tissue patients are referred to
as having non-EBV-associated lymphoma. Patients that were positive
for human immunodeficiency virus or with active Hepatitis B or C infection were excluded. Full clinical annotation was prospectively recorded.
This was a noninterventional study in which therapy was applied as per
clinician’s preference and varied by histological subtype. HL patients
were treated with ‘‘ABVD’’ [19], DLBCL and LYG received ‘‘CHOP-R’’ or
‘‘Hyper-CVAD’’ [20,21] and PTLD with reduction in immunosuppression
(RIS) combined with rituximab either as monotherapy or in combination
with chemotherapy (‘‘CHOP-R’’) [22].
Peripheral blood samples (30 to 50 ml in EDTA tubes and 8 ml in
serum tubes) were taken at five defined time-points: at diagnosis,
immediately before second and third therapy, 1 month post-therapy,
and 6 months post-therapy [23]. The response to therapy was clinically
evaluated at each time-point. Radiological assessment was performed
at diagnosis, at an interim time-point, 1 month and 3 to 6 months after
completion of all therapy, and responses classified as per standard
criteria [24].
Serum, plasma, and peripheral blood mononuclear cells (PBMC)
were processed as previously outlined [23]. EBV-seropositive healthy
American Journal of Hematology
subjects served as a healthy control population. The study was performed under the auspices of the Australasian Leukaemia and Lymphoma Group. This study conformed to the Declaration of Helsinki and
written informed consent was provided by all donors in accordance with
participating hospitals/research institute Human Research Ethics Committee guidelines.
DNA extraction and quantitative real-time PCR determination of the
EBV-DNA load in the plasma and PBMC. DNA from plasma and serum (850–1000 ll) and PBMC (<5 3 106 cells) was extracted using
the QIAamp DNA Blood Mini Kit (Qiagen, Valencia, USA). EBV-PCR
primer sets were used from two different gene sequences; the singlecopy BALF5 (90 base-pair amplicon) and the multiple but variable copy
number BAMH1W (115 base-pair amplicon) both described previously
[25,26]. Primers and probe for the human albumin gene were also
used as previously described [27]. PCR primers were synthesized by
Sigma Aldrich (Castle Hill, Australia) and probes by Biosearch Technologies (Novato, USA). Rotorgene 3000 real-time PCR machine (Corbett
Research, Sydney, Australia) was used to run the 20 ll reactions with
Platinum Quantitative PCR SuperMix-UDG (Invitrogen, Carlsbad, USA).
For each real-time run, levels were quantified against a standard curve
with serially diluted EBV-DNA extracted from the Namalwa cell line (six
standards, 1:5 dilutions) or from Human genomic DNA (four standards,
1:2 dilutions; Roche Diagnostics, Indianapolis, USA). For plasma and
serum samples, results were expressed as either Human genome (diploid) or EBV genome copies per ml. For PBMC samples, the EBV-DNA
load was normalized to albumin level and was expressed as the number of EBV copies per 106 PBMC.
Statistics. Accuracy of circulating c-f nonspecific DNA and EBV-viral
load as biomarkers at diagnosis and of disease response was measured by receiver operating characteristic (ROC) curves. ROC curve
analysis was also used to define cut-off thresholds for c-f nonspecific
DNA and c-f EBV-DNA. The Mann-Whitney test was used to compare
groups, and Wilcoxon matched-pairs signed rank test was used to
compare paired samples. We defined accurate results as the values
within 10% of the expected value and used two-tailed Fisher’s exact
test to compare accuracy, sensitivity, and specificity. The correlation of
results was assessed using Pearson analysis and the agreement
between matched values was assessed using Bland-Altman plot analysis. The statistical analysis was performed using Graphpad Prism 5.0
(Graphpad Software Inc, California).
Results
Patient characteristics
Sixty-three lymphoma patients were accrued from three
centers. There were 30 EBV-associated lymphoma patients
(mean age: 43 years, range: 18–89; female/male ratio 17/
13) and 33 non-EBV-associated lymphoma patients (mean
age: 45 years, range: 18–89; female/male ratio 16/17).
Patient characteristics are provided in Table I. In addition,
17 healthy control PBMC samples and 13 healthy control
plasma samples were collected (26 healthy donors in
total, mean age: 41 years, range: 20–62; female/male ratio
16/10).
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TABLE I. Patient Characteristics
Figure 1. Circulating cell-free nonspecific DNA in complete responders. (A) Circulating cell-free (c-f) nonspecific DNA in 42 lymphoma patients, regardless of EBER-ISH
status, with a full time-course and who achieved complete response by the 1 month post-treatment time-point. Lymphoma patient c-f nonspecific DNA was significantly
elevated at presentation compared to 13 healthy controls (P > 0.0001). No significant differences were seen between paired samples at all subsequent time-points,
including remission samples at 1 month and 6 months post-treatment. Line and error bars represent the mean and SEM. (B–D) Sequential circulating cell-free nonspecific
DNA in (B) HL complete responders, (C) B-cell PTLD complete responders, and (D) DLBCL complete responders. No significant differences were seen between paired
samples at all time-points. * A 6months post-treatment time-point was available in only one DLBCL patient.
Nonspecific circulating DNA correlates with
LDH levels at diagnosis but has no value
as a disease response biomarker
Using albumin as the target gene and plasma as the
DNA source, we quantified circulating c-f nonspecific DNA
levels in 63 lymphoma patients at all available time-points
and on 13 healthy control plasma samples. We found that
circulating nonspecific c-f DNA levels were increased in
patient samples at diagnosis compared to healthy controls
(patient mean 5 1622 genomes/ml, range 89–8603
genomes/ml; healthy mean 5 297 genomes/ml, range 16–
2108 genomes/ml, P < 0.0001, Fig. 1A). Pretreatment nonspecific c-f DNA levels were elevated in HL (P < 0.0001),
PTLD (P 5 0.0007), and DLBCL (P 5 0.0021) when compared with healthy subjects. There was no difference in
nonspecific c-f DNA levels between HL, PTLD, and DLBCL
samples pretherapy. ROC analysis was used to test the
diagnostic performance of real-time quantitative PCR to discriminate between healthy controls and lymphoma patients.
The area under the curve (AUC) was 0.8901 (95% C.I.
0.77–1.01). We chose a baseline cut-off threshold for c-f
nonspecific DNA of 150 human genomes/ml of plasma.
This value provided optimal sensitivity and specificity using
ROC analysis of pretreatment compared to healthy control
samples (95% sensitivity and 69% specificity).
Comparison of diagnostic nonspecific circulating c-f DNA
load revealed a correlation with LDH levels (P 5 0.0024).
However no correlation was seen with other clinical parameters, including age, gender, stage, and B-symptoms.
Despite elevated nonspecific circulating DNA at presentation, sequential assays taken within the same patient at
defined time-points did not reflect response to treatment.
Using a paired analysis, circulating nonspecific c-f DNA
levels at all time-points were compared for patients who
260
were in complete remission (as defined by radiological and
clinical assessment at the 1 month post-treatment timepoint) (Fig. 1A shows results in 42 patients with complete
time-courses, and Fig. 1B–D shows paired analysis for
PTLD, HL, and DLBCL, respectively). No significant differences were seen for all comparisons between time-points.
In addition, ROC analysis between diagnostic and 1 month
post-treatment remission samples was not significant with
poor sensitivity and specificity ratios [area under the curve
(AUC) 5 0.6043], CI% 0.47–0.73, 5% sensitivity, and 100%
specificity. Further studies are required to definitively establish if circulating c-f DNA has a potential role as a baseline
screen. However, sequential circulating c-f DNA did not
reflect therapeutic response.
Single-copy EBV-DNA gene targets are equally
sensitive and specific as multiple copy genes targets
Initially, we determined the optimum methodology for
EBV-DNA by real-time PCR. We compared the sensitivity,
precision, and accuracy of two EBV primers from eight separate PCR runs using fivefold dilutions of Namalwa DNA
ranging from 25,000 to 8 EBV genome copies, run in triplicate. As shown in Fig. 2A, the mean and standard error of
BALF5 and BAMH1W were similar. Two-tailed Fisher’s
exact test was used to compare the accuracy of BALF5
and BAMH1W amplification at a level of 10% variation from
the expected value. We found no difference between the
two primers.
We then compared BAMH1W and BALF5 results in 113
plasma samples from our patient cohort (Fig. 2B). ROC
analysis was used to choose the optimum cut-off threshold
of 100 EBV genomes/ml of plasma. This gave 94% sensitivity and 67% specificity when comparing samples from
before treatment EBV-associated lymphomas to before
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Figure 2. Comparison of multicopy and single-copy EBV-gene targets, as well as plasma and serum as a source of circulating cell-free EBV-DNA (A) Accuracy and
precision of BAMH1W and BALF5. Results of eight separate PCR runs using diluted Namalwa EBV-DNA samples are presented as fold change from expected value. The
circles and triangles represent the mean of BALF5 and BAMH1W, respectively. The error bars represent the SD. No significant differences were seen. (B) Correlation of
BAMH1W and BALF5 results from 113 patients samples. The results strongly correlated (r 5 0.9694, P > 0.0001). The data are presented on a log 10 scale; thus, nil values
are not shown. (C) Correlation of BAMH1W and BALF5 results above and below the cut-off threshold of 100 copies/ml. A poor correlation (0.4721) was found below the
cut-off threshold, whereas values above the threshold remained strongly correlated (0.9610). (D) No significant difference was seen between plasma and serum EBV-DNA
load from 105 paired patient samples. Line and error bars represent the mean and SEM. (E) Plasma and serum EBV-DNA strongly correlated (r 5 0.9639, P < 0.0001).
treatment non-EBV-associated lymphoma controls. Interestingly, the multiple-copy gene BAMH1W was not more sensitive than the single-copy gene BALF5.
Primer specificity was analyzed based on false positives
(non-EBV-associated lymphoma patients with positive viral
loads) and on false negatives (EBV-positive lymphoma
patients with negative viral loads at diagnosis). No significant differences were seen between specificity of BAMH1W
and BALF5. The false positive rates for values above the
cut-off for BAMH1W and BALF5 were 1% and 0%, respectively. The false negative rates for values below the cut-off
of BAMH1W and BALF5 were both 2%. The BALF5 and
BAMH1W results strongly correlated (r 5 0.9694, P <
0.0001); however, the Bland-Altman analysis showed poor
agreement between the samples (Bias of 200.4 ± 924.8
SD). This is not surprising considering the variability in
BAMH1W copy number between different EBV strains [28].
Importantly, when Pearson correlation was limited to values
below 100 EBV genome copies/ml of plasma, the correlation was poor (r 5 0.4721) but remained strong above this
threshold (r 5 0.9610, Fig. 2C), supporting the previously
defined cut-off of 100 EBV genomes/ml. Our results indicate that the multiple-copy gene BAMH1W was not more
sensitive than BALF5. We concluded that the risk of
American Journal of Hematology
increased variability between patient results by using the
multiple-copy BAMH1W gene was not outweighed by any
significant increase in sensitivity and used the BALF5
primer for the remainder of our study.
Serum and plasma are equivalent but not
interchangeable sources of c-f EBV-DNA
To determine the optimal source of c-f EBV-DNA, we
used the BALF5 primers in 105 matched serum
and plasma samples from our patient cohort. These were
chosen from 28 EBV-associated and non-EBV-associated
B-cell PTLD and cHL patients with complete time-courses
(three EBV-PTLD, eight EBV1 PLTD, eight EBV-HL, and
nine EBV1HL). We found no significant difference between
the paired samples (P 5 0.7641) and a strong correlation
(r 5 0.9639, P < 0.0001, Fig. 2D,E). Sensitivity and specificity were analyzed using the two-tailed Fisher’s exact test.
Plasma was found to be significantly more sensitive than
serum when comparing values above zero (total positive values P 5 0.0488, comparison of positive values in one source
versus zero values in the other source P 5 0.0026). However, when the sensitivity analysis was restricted to values
above a 100 copies/ml cut-off, no significant difference in
sensitivity was found. No significant differences were seen
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between specificity of plasma and serum. The false positive
rates for values above the cut-off for plasma and serum are
2.3% and 4.5%, respectively. The false negative for values
below the cut-off of plasma and serum were 41% and 47%.
Bland-Altman plots were used to assess the agreement of
values between paired serum and plasma viral loads. These
illustrate relatively poor agreement between serum and
plasma (Bias 5 345.6, SD of Bias 2666). Thus, although
plasma and serum were equally sensitive and specific and
strongly correlated, values were not identical. This demonstrates that although plasma and serum are equivalent
sources, they cannot be used interchangeably. To permit
comparison with nonspecific c-f DNA, EBV-DNA was measured in plasma for the remaining components of the study.
In untreated EBV-associated lymphoma patients,
plasma EBV-DNA was elevated and correlated with
nonspecific circulating plasma DNA
Pretherapy c-f (plasma) and cell-associated viral loads
were compared between EBV-associated and non-EBVassociated lymphoma patients of matching histologies. In
addition, EBV-associated lymphoma pretherapy viral loads
were compared with healthy control samples. As illustrated
in Supporting Information Figure S1, c-f but not cell-associated viral loads were significantly elevated at presentation.
EBV-associated lymphoma c-f EBV-DNA loads were significantly different from both non-EBV-associated lymphoma
and healthy control samples (P < 0.0001 and P 5 0.0002,
respectively). The majority of the EBV-associated lymphoma patients had c-f EBV-DNA above the cut-off threshold (67%, 20 out of 30), as opposed to 6% (2 out of 33) of
the non-EBV-associated lymphoma samples and none of
the healthy controls. In contrast, pretherapy cell-associated
EBV-associated lymphoma viral loads were not significantly
different from non-EBV-associated and healthy controls
(P 5 0.3078 and P 5 0.7120, respectively). To assess sensitivity and specificity of cell-associated and c-f EBV-DNA
load as a biomarker of disease at presentation, ROC
curves were generated. Plasma viral loads distinguished
EBV-associated from non-EBV-associated lymphoma
patients (AUC 5 0.8182, P < 0.0001, 95% CI 0.70–0.93
and using a 100 copies/ml cut-off 94% sensitivity and 67%
specificity) and from healthy control subjects (AUC 5
0.8727, P 5 0.00029, 95% CI 0.77–0.98, with 67% sensitivity and 100% specificity). For cell-associated viral loads,
ROC analysis showed that EBV-DNA did not distinguish
pretherapy EBV-associated lymphoma blood when
compared with non-EBV-associated lymphoma and healthy
control samples (AUC 5 0.5938, 95% CI 0.40–0.79, P 5
0.3023 and AUC 5 0.5386, 95% CI 0.33–0.75, P 5
0.7053, respectively). In addition, cell-associated viral loads
had a false positive rate of 60% when compared with the
6% false positive rate for plasma.
Interestingly, paired analysis showed that EBV-associated
lymphoma patient EBV-DNA loads strongly correlated with
matched nonspecific circulating c-f DNA values (r 5 0.6301,
P 5 0.0002). EBV-associated lymphoma patient viral loads
were also compared with clinical parameters, including age,
gender, stage, B-symptoms LDH, and relevant prognostic
score. No association was found between these and either
cell-associated or c-f diagnostic viral loads.
Plasma EBV-DNA load reflects therapeutic response
in EBV-associated lymphoma
We analyzed the viral load during treatment and compared this with disease response as defined by radiological
and clinical assessment. Supporting Information Figure S2
is a schematic diagram of the EBV-associated lymphoma
patients. Of the 30 EBV-associated lymphoma patients, we
262
had a full time-course on 22 (at least four sequential samples including at presentation and a post-treatment timepoint), all of whom achieved complete remission by the 1
month post-treatment time-point and all but one remain in
clinical/radiological remission. Of the 21 in complete remission, eight patients had nil/below cut-off viral loads at presentation and remained nil/below cut-off throughout treatment (two HL, four B-cell PTLD, and one DLBCL). The
remaining 13 patients had viral loads above threshold at
presentation. Of these 13 patients, nine had a nil/below
cut-off viral load at the pre-second treatment time-point. All
of these nine, except one, remained nil/below cut-off for the
subsequent time-points. The one patient who did not
remain nil/below cut-off had a spike of EBV-DNA at the
pre-third treatment time-point which occurred within the
context of an episode of sepsis requiring hospitalization.
Following convalescence, the viral load dropped to nil by
the 1 month post time-point and remained nil/below cut-off
thereafter. Of the four patients with positive viral loads at
the pre-second time-point, one had nil/below cut-off viral
load by the pre-third time-point, one achieved nil/below cutoff viral load by the 1 month post time-point and the other
two did not achieve nil/below cut off viral loads until the 6
months post-treatment time-point. Of note, the two patients
with positive viral loads at the 1 month post-treatment timepoints had viral loads only modestly above threshold (137
copies/ml and 112 copies/ml). Figure S3 illustrates that at
corresponding time-points, there was no association
between c-f viral load and c-f nonspecific DNA changes in
the 21 sustained complete response patients with a complete time-course. Figure 3 is restricted to the EBV-associated lymphoma patients with raised EBV-DNA at presentation and shows that individual viral load time-courses correspond to therapeutic response, whereas circulating
nonspecific plasma DNA does not (10 individual viral load
time courses shown in Fig. 3, the remaining three are
shown in Fig. 4). In the remaining eight of thirty EBV-associated lymphoma patients in whom only a partial timecourse was available, EBV-DNA was elevated in seven at
presentation. In these patients, available EBV-DNA values
at subsequent time-points were consistent with therapeutic
response (data not shown).
To compare cellular with plasma EBV-DNA as a disease
response biomarker, paired diagnostic and 1 month posttreatment samples were assayed in patients in complete
remission at the 1 month post-treatment time-point (Supporting Information Fig. S4). Paired c-f EBV-positive patient
viral loads at diagnosis significantly differed from remission
samples (P 5 0.0005). ROC analysis of paired samples
illustrated that plasma EBV-DNA could be used to indicate
disease response (AUC 5 0.7872, 95% CI 0.65–0.93, P 5
0.0011 with 64% sensitivity and 91% specificity above
cut-off). In keeping with the reduction of circulating B-cell
numbers with therapy, cell-associated EBV viral loads were
reduced (P 5 0.0117). However, ROC analysis plots were
not significant (AUC 5 0.7041, 95% CI 0.48–0.90, P 5
0.076912), indicating that cell-associated EBV loads were
not a useful disease response biomarker.
In patients with refractory/relapsed disease or with persistent low-grade FDG-PET avidity, tumor-specific but
not nonspecific c-f DNA is a biomarker of disease
response
Of the 30 EBV-associated lymphoma patients, one
patient (patient 23) had refractory disease and one patient
relapsed (patient 70). The patient with refractory disease
(AITL) died before the 6 months post-treatment evaluation.
This patient had a high viral load at diagnosis (15,000 copies/ml) and continued to have a high viral load at the 1
month post-treatment time-point (885 copies/ml). Pre-sec-
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Figure 3. Plasma EBV-DNA load reflects therapeutic response in EBV-associated lymphoma patients with elevated viral load at presentation, whereas circulating nonspecific plasma DNA does not. Comparison of therapeutic response, cell-free nonspecific DNA and EBV-DNA in EBV-associated lymphoma patients that had elevated
EBV-DNA at presentation. Dotted lines represent cell-free nonspecific DNA, whereas solid lines represent EBV-DNA. The arrows represent the timing of the radiological
assessment. (A) Patient 14, HL treated with ABVD; (B) Patient 25, PTLD treated with RIS, methotrexate and radiotherapy; (C) Patient 27, HL treated with ABVD; (D)
Patient 29, HL treated with ABVD; (E) Patient 41, PTLD treated with RIS and Rituximab; (F) Patient 45 PTLD treated with RIS and Rituximab; (G) Patient 53, LYG treated
with CHOP-R; (H) Patient 54, HL treated with ABVD; (I) Patient 63, HL treated with ABVD; and (J) Patient 78, LYG treated with Hyper-CVAD.
ond and pre-third treatment time-points were not available.
A complete time-course was available for patient 70. This
patient (DLBCL) had a high viral load at diagnosis (13,460
copies/ml) and achieved complete clinical/radiological
remission by 1 month post-treatment. The viral load
dropped to nil at the pre-second therapy time-point and
remained nil for the pre-third therapy and 1 month posttherapy samples. The viral load returned to high levels at 6
months post-therapy (2020 copies/ml) preceding clinical/radiological evidence of relapse. Clinical examination and radiological imaging confirmed a relapse at 9 months posttreatment, at which time an additional sample was taken
and a very high viral load was observed (30,100 copies/
ml). In addition to the two EBV-associated relapse/refractory patients, one non-EBV associated lymphoma patient
had refractory disease at the end of therapy, which then
progressed. The viral load was nil at all time-points; however, the nonspecific DNA load did not reflect progressive
disease (Fig. 4).
Importantly, plasma EBV-DNA was also a useful
biomarker in patients with persistent low-grade FDG-PET
avidity at 1 month following treatment. Three of the 13
EBV-associated lymphoma patients who had viral loads at
presentation and dropped to nil by the pre-second therapy
time-point, had persistent low-grade FDG-PET avidity at the
1 month post-therapy time-point. With ongoing clinical
follow-up, these patients did not relapse, indicating that
they were in complete remission at the end of therapy,
which was accurately reflected by their 1 month posttherapy EBV-DNA values (Fig. 4).
Discussion
A noninvasive biomarker that accurately reflects lymphomas response to therapy would be of great clinical benefit.
However, the study of disease response biomarkers in
lymphoma has been relatively neglected. Our aim was to
compare lymphoma-specific with nonspecific circulating
American Journal of Hematology
DNA. We prospectively evaluated the kinetics of tumor-specific and nonspecific circulating c-f DNA at fixed sequential
time-points taken prior, during and following therapy in 63
lymphoma patients. Values were compared with clinical and
radiological response. Our results indicate that although
circulating nonspecific DNA loads were elevated at presentation, levels were not indicative of lymphoma burden
once therapy had commenced. In contrast, circulating c-f
EBV-DNA (but not cell-associated EBV-DNA) did reflect
therapeutic response in EBV-associated lymphomas.
A prior study that quantified genomic DNA in lymphoma
using primers to the b-globin housekeeping gene found
that elevated nonspecific DNA was associated with
increased lymphoma risk and that nonspecific circulating
c-f DNA was raised in HL and DLBCL compared to healthy
controls [5]. Notably, Hohaus et al. also observed significant associations with advanced stage disease, presence
of B-symptoms, elevated LDH levels, and increased age
[5]. The most significant association seen was with elevated
LDH. LDH level has previously been used for assessing
lymphoma burden, prognosis, and stratifying treatment [3].
We also found a strong correlation between nonspecific
circulating c-f DNA load and LDH levels at presentation but
not with other clinical parameters. Further prospective studies with larger patient numbers are required to definitely
clarify the role of nonspecific circulating c-f DNA as part
of the diagnostic screen in specific lymphoma histological
subtypes.
The elevation of nonspecific circulating c-f DNA at presentation suggested the assay had potential as a disease
response biomarker. Unlike highly tumor-specific based
assays, nonspecific DNA would have broad applicability to
a variety of lymphomas. To test this, a study was conducted
in pediatric aggressive (predominantly Burkitts) lymphoma,
but the results were inconclusive [6]. Blood was taken
before and at the end of (but not during) therapy. In
11 evaluable patients, the authors found that following
263
10968652, 2012, 3, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/ajh.22252, Wiley Online Library on [17/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
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Figure 4. Tumor-specific but not nonspecific cell-free DNA load reflects therapeutic response in patients with refractory/relapsed disease or with persistent low-grade
FDG-PET avidity. Dotted lines represent the cell-free nonspecific DNA, whereas solid lines represent the EBV-DNA. The arrows represent the timing of the radiological
assessment. (A–C) Comparison of cell-free nonspecific DNA and EBV-DNA in EBV-associated lymphoma patients that had persistent low-grade FDG-PET avidity of
uncertain significance at 1 month post-treatment. All three patients were in clinical complete remission at the 1 month post-treatment time-point, and remain disease free
with ongoing follow-up. (A) Patient 75, HL treated with ABVD; (B) Patient 77, LYG treated with CHOP-R; (C) Patient 84, HL treated with ABVD. (D–F) Comparison of cellfree nonspecific DNA and EBV-DNA in EBV-associated and non-EBV-associated lymphoma patients that had relapsed/ refractory disease. (D) Patient 70, EBV-associated
DLBCL treated with CHOP-R; (E) Patient 23, EBV-associated AITL treated with CHOP; and (F) Patient 81, non-EBV-associated HL treated with ABVD.
cessation of chemotherapy nonspecific circulating c-f DNA
significantly declined to levels comparable with healthy subjects in seven responders but remained above controls or
even rose above presentation levels in the remaining three
despite ongoing remission [6]. Our approach was to compare nonspecific with tumor-specific circulating c-f DNA.
We prospectively obtained sequential blood samples at five
defined time-points prior, during and following therapy.
EBV-DNA was chosen as the lymphoma-specific marker,
because EBV is known to be present within the malignant
lymph nodes in a proportion of patients with specific histologies [10]. Our and others previous work indicates that
EBV-DNA may have a role as a disease response biomarker in EBV-associated lymphomas [12,13,29,30]. To our
knowledge, ours is the first detailed comparison of lymphoma-specific and nonspecific circulating c-f DNA as a
disease response biomarker. At presentation, we found a
strong correlation between specific and nonspecific circulating c-f DNA. The timing of the second and third samples
was on the day of but immediately before second and third
therapy cycles, so as to minimize release of nonspecific
DNA into the circulation from chemotherapy induced
destruction of nonmalignant cells. However, once therapy
had commenced, nonspecific c-f DNA levels remained
equivalent to presentation at all subsequent time-points. In
contrast, c-f EBV-DNA did reflect clinical and radiological
response in all of the EBV-associated lymphoma patients in
whom EBV-DNA was elevated at presentation. In these
patients, viral load cleared in patients obtaining remission,
264
generally before cessation of therapy. In several cases,
values declined but remained marginally elevated above
threshold but reduced to below threshold with continued
surveillance. Circulating c-f EBV-DNA remained elevated in
an EBV-associated lymphoma patient with refractory disease and returned to elevated levels in an EBV-associated
lymphoma patient who relapsed at 9 months post-treatment. In addition, c-f viral loads reflected disease response
in EBV-associated lymphoma patients with persistent lowgrade FDG-PET avidity that was not associated with subsequent relapse. Furthermore, c-f viral loads distinguished
EBV-associated from non-EBV-associated lymphoma
patients and from healthy control subjects. Thus, it appears
that lymphoma-specific DNA has a role as a disease
response biomarker, at least in those patients with elevated
loads at presentation, within the HL, LYG, DLBCL, and
PTLD lymphoma subtypes included within our study.
There is currently a lack of protocol consistency between
laboratories assaying EBV-DNA. Although quantitative realtime PCR is widely used, most methods are developed in
house and there is a large degree of deviation between
protocols. A study comparing interlaboratory results from
28 laboratories using a panel of samples found significant
variation [31]. Although a universal viral load quantification
method would permit standardized interpretation of results,
the optimal choice of DNA source (serum, plasma, or cellassociated) and amplified gene remains to be determined.
We, therefore, utilized the opportunity that the clinical samples provided to compare these parameters. Ours is the
American Journal of Hematology
10968652, 2012, 3, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/ajh.22252, Wiley Online Library on [17/12/2022]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
research article
first large series to compare serum and plasma as sources
of circulating c-f EBV-DNA. Our results are conclusive that
the two are equivalent but not interchangeable. By contrast,
cell-associated EBV-DNA did not distinguish pretherapy
EBV-associated lymphoma samples from non-EBV-associated lymphoma and healthy control samples, nor was it of
value as a disease response biomarker. This latter finding
is in line with our previous data and that of other groups’
findings using measurements of cell-associated or whole
blood EBV-DNA [12,15,32–35]. To our knowledge, we also
present the first large scale comparison of multiple versus
single-copy EBV-gene targets as a disease response biomarker. BALF5 is consistently present as a single-copy
gene in the EBV genome. In contrast, BAMH1W is a multiple-copy gene with varying copy numbers between EBV
strains, ranging from 7 to 11 copies per genome [28].
Studies have suggested that a multiple-copy gene may be
more sensitive, enabling detection of lower levels of
virus and superior detection of early stage disease or any
residual disease post-therapy [36]. The disadvantage is
that the variable copy number of BAMH1W limits the
ability to precisely quantify the number of viral genomes.
Our data demonstrates that sensitivity was not enhanced
by the use of multiple versus single-copy EBV-gene targets.
As both genes provided equivalent results, we propose that
single, nonvariable copy genes are likely to be the optimal
choice as this permits precise quantification regardless of
the viral strain. In addition, ROC analysis confirmed that
the optimal cut-off value (to minimize false positives)
was above the limits of the assay, thus, increased sensitivity would not increase the precision of EBV-DNA as a
biomarker.
To our knowledge, this is the first detailed comparison of
lymphoma-specific versus nonspecific DNA as disease
response biomarkers in lymphoma. Our results indicate
that both circulating c-f nonspecific DNA and lymphomaspecific DNA are elevated at presentation. However, only
lymphoma-specific DNA reflected therapeutic response.
Lymphoma disease response can be monitored by blood
tests, but new lymphoma-specific biomarkers need to be
identified to broaden applicability.
Acknowledgments
The authors thank the Australasian Leukaemia and
Lymphoma Group, under whose auspices this study was
conducted. MKG and KJ designed this study, interpreted
the data, and wrote the manuscript; KJ collected and
processed the samples, conducted the experimental studies, analyzed the data, and performed statistical analysis;
PC assisted processing the samples; JPN, CK, D Gottlieb,
DSR, and D Gill contributed to study design and the writing
of this manuscript.
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