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. Author manuscript; available in PMC: 2017 Dec 1.
Published in final edited form as: Br J Haematol. 2016 Oct 6;175(5):841–850. doi: 10.1111/bjh.14311

Next-Generation Sequencing-Based Detection of Circulating Tumour DNA After Allogeneic Stem Cell Transplantation for Lymphoma

Alex F Herrera 1, Haesook T Kim 2, Katherine A Kong 3, Malek Faham 3, Heather Sun 4, Aliyah R Sohani 5, Edwin P Alyea 6, Victoria E Carlton 3, Yi-Bin Chen 7, Corey S Cutler 6, Vincent T Ho 6, John Koreth 6, Chitra Kotwaliwale 3, Sarah Nikiforow 6, Jerome Ritz 6, Scott J Rodig 4, Robert J Soiffer 6, Joseph H Antin 6, Philippe Armand 6
PMCID: PMC5123935  NIHMSID: NIHMS807334  PMID: 27711974

Summary

Next-generation sequencing (NGS)-based circulating tumour DNA (ctDNA) detection is a promising monitoring tool for lymphoid malignancies. We evaluated whether the presence of ctDNA was associated with outcome after allogeneic haematopoietic stem cell transplantation (HSCT) in lymphoma patients. We studied 88 patients drawn from a phase 3 clinical trial of reduced-intensity conditioning HSCT in lymphoma. Conventional restaging and collection of peripheral blood samples occurred at pre-specified time points before and after HSCT and were assayed for ctDNA by sequencing of the immunoglobulin or T-cell receptor genes. Tumour clonotypes were identified in 87% of patients with adequate tumour samples. Sixteen of 19 (84%) patients with disease progression after HSCT had detectable ctDNA prior to progression at a median of 3.7 months prior to relapse/progression. Patients with detectable ctDNA 3 months after HSCT had inferior progression-free survival (PFS) (2-year PFS 58% versus 84% in ctDNA-negative patients, p=0.033). In multivariate models, detectable ctDNA was associated with increased risk of progression/death (Hazard ratio 3.9, p=0.003) and increased risk of relapse/progression (Hazard ratio 10.8, p=0.0006). Detectable ctDNA is associated with an increased risk of relapse/progression, but further validation studies are necessary to confirm these findings and determine the clinical utility of NGS-based minimal residual disease monitoring in lymphoma patients after HSCT.

Keywords: lymphomas, minimal residual disease, stem cell transplantation, CLL, Non-Hodgkin lymphoma

Introduction

Relapse is a main cause of treatment failure after allogeneic haematopoietic stem cell transplantation (HSCT) in patients with lymphoma.(Armand, et al 2008, Bacher, et al 2012, Devetten, et al 2009, Fenske, et al 2014, Robinson, et al 2013, Smith, et al 2013) Reduced intensity conditioning (RIC), which is associated with a lower risk of transplant-related mortality, has extended the availability of HSCT to older and frailer populations, but carries an increased risk of relapse.(Armand, et al 2008, Khouri, et al 1998, Sorror, et al 2008, Thomson, et al 2009) Early detection of relapse after HSCT could potentially be used to guide pre-emptive intervention, but post-HSCT disease monitoring methods in patients with lymphoma are typically restricted to radiological and bone marrow studies, which have limited sensitivity to detect low volume disease.(Barrington, et al 2014) Monitoring for minimal residual disease (MRD) in a range of haematological malignancies can identify patients at high risk of relapse after standard therapy and HSCT.(Bottcher, et al 2011, Bottcher, et al 2012, Ferrero, et al 2011, Radich, et al 1995, Raff, et al 2007, Ritgen, et al 2008, Walter, et al 2013, Zhou, et al 2007) An effective MRD assay that could identify lymphoma patients at increased risk for relapse after HSCT would be a powerful tool for developing relapse prevention strategies. However, MRD monitoring techniques are not available for most lymphoma subtypes, particularly when there is no peripheral blood involvement or characteristic chromosomal rearrangement.(Corradini, et al 2004, Gribben, et al 1991, Gribben, et al 1993, Mancuso, et al 2010)

Next-generation sequencing (NGS)-based MRD detection using the immunoglobulin or T-cell receptor genes (Adaptive Biotechnologies Corp., South San Francisco, CA) can identify circulating tumour DNA (ctDNA) in the peripheral blood mononuclear cells (PBMC) and plasma (cell-free) of patients with lymphoid malignancies. NGS-based ctDNA detection is at least as sensitive as existing MRD detection methods, and can detect MRD not identified by multi-parameter flow cytometry or allele-specific oligonucleotide polymerase chain reaction testing.(Faham, et al 2012, Ladetto, et al 2014, Logan, et al 2013) The NGS-based MRD detection method can identify ctDNA at diagnosis in a range of lymphomas, including classical Hodgkin lymphoma (HL) and diffuse large B-cell lymphoma (DLBCL), subtypes in which MRD detection has previously been challenging.(Armand, et al 2013, Kurtz, et al 2015, Oki, et al 2015, Roschewski, et al 2015) In addition, ctDNA levels track with treatment response in DLBCL, and the persistence or recurrence of ctDNA during and after upfront therapy is associated with subsequent DLBCL relapse.(Kurtz, et al 2015, Roschewski, et al 2015) Following HSCT for acute lymphoblastic leukaemia (ALL) and chronic lymphocytic leukaemia (CLL), ctDNA is associated with subsequent relapse and poorer progression-free survival (PFS).(Logan, et al 2014, Logan, et al 2013) In the present pilot study, we evaluated whether ctDNA detected by the NGS-based MRD assessment method is associated with relapse and survival in patients with lymphoma undergoing RIC HSCT.

Methods

We performed a retrospective study using research samples collected as part of a prospective, multi-centre, open-label, phase III randomized clinical trial evaluating the addition of sirolimus to the graft-versus-host disease (GVHD) prophylaxis regimen of patients with lymphoma undergoing RIC allogeneic HSCT.(Armand, et al 2016a) The clinical trial and this retrospective study were approved by the Institutional Review Board of the Dana-Farber Cancer Institute/Harvard Cancer Center. Informed consent was obtained at the time of clinical trial enrolment in accordance with the Declaration of Helsinki.

Cohort

Adult patients aged 18 to 72 years old with HL, CLL, B- or T-cell non-Hodgkin lymphoma (NHL) (excluding Burkitt lymphoma and MYC-rearranged DLBCL) undergoing their first allogeneic HSCT with an 8/8 human leucocyte antigen (HLA)-matched related or unrelated allogeneic donor were eligible for the clinical trial. Between June 2009 and September 2012, 139 patients were enrolled to the clinical trial, including 118 participants enrolled at the Dana-Farber Cancer Institute and Massachusetts General Hospital who were eligible for this retrospective study. Details of the transplantation regimen are described elsewhere.(Armand, et al 2016a) Participants underwent conventional restaging at 3, 6, 12, 18 and 24 months, as per protocol. Acute and chronic GVHD were graded by the treating physician according to the relevant guidelines.(Przepiorka, et al 1995, Shulman, et al 1980) PBMC and plasma (2–3.6 ml) samples were prospectively collected and banked prior to HSCT and at 1, 2, 3, 6, 9, 12, 18 and 24 months after HSCT, or until relapse. Only patients who consented to optional research specimen collection and use at the time of informed consent and who had available archival biopsy samples containing sufficient tumour for nucleic acid extraction and sequencing analysis (approximately ≥ 15 ng of DNA) were included in this retrospective study.

Immunoglobulin and T cell receptor gene sequencing

Genomic tumour DNA was extracted from archival formalin-fixed paraffin-embedded (FFPE) tissue or bone marrow aspirate mononuclear cells and analysed as previously described.(Faham, et al 2012) In brief, polymerase chain reaction amplification of IGH VDJ, IGH DJ, IGK, TRB (TCR-beta), TRD (TCR-delta) and/or TRG (TCR-gamma) regions was performed using universal consensus primers followed by next-generation sequencing to determine the tumour clonotype(s) (Adaptive Biotechnologies Corp.). A tumour clonotype was defined as a clone with a frequency of > 5% in the tumour specimen. DNA from banked plasma and PBMC samples was extracted using QIAamp Circulating Nucleic Acid Kit (Qiagen, Germantown, MD, USA) for cell-free DNA and the AllPrep kit (Qiagen) for cell-based DNA. DNA was amplified using universal consensus primers and sequenced. The abundance of ctDNA was quantified relative to the total number of sequencing reads in a specimen minus the number of lymphoma molecules per diploid genome sequenced. Both plasma and PBMCs were evaluated in all patients at all time points when specimens were available.

Statistical Analysis

Baseline characteristics were reported descriptively. Fisher’s exact test or a Chi-square test was used for group comparison of categorical variables. Wilcoxon rank-sum test was used for group comparison of continuous variables. Overall survival (OS) and PFS were calculated using the Kaplan-Meier method. OS was defined as the time from stem cell infusion until death from any cause. Patients who were alive or lost to follow-up were censored at the time last seen alive. PFS was defined as the time from stem cell infusion until progression of disease or death from any cause. Patients who were alive without disease relapse or progression were censored at the time last seen alive and progression-free. Cumulative incidence of non-relapse mortality (NRM) and relapse/progression (CIR) were calculated reflecting time to non-relapse death and time to relapse, respectively, as competing risks. The log-rank test was used to compare OS and PFS between subgroups, while the Gray test (Gray 1988) was used to compare NRM and CIR incidences. A sample was considered positive for ctDNA if there were ANY detectable lymphoma molecules in the specimen. A patient was considered ctDNA positive at a given time point if ctDNA was detected in at least one sample tested from that time point, i.e. PBMC and/or plasma. The endpoints of interest for this study were CIR and PFS. Univariate and multivariate analyses for CIR and PFS were performed using a Cox proportional hazards model treating ctDNA positivity as a time-dependent covariate along with disease status at HSCT and lymphoma histology. All tests were two-sided at the significance level of 0.05. All analyses were performed using SAS version 9.3 (SAS Institute, Cary, NC)

Results

Patients and HSCT Outcomes

Among the 139 patients enrolled on the clinical trial, 88 had paired tumour and blood samples available for analyses. Ten patients did not have sufficient tumour DNA for clonotype analysis and were not included in the study. Among the remaining 78, identification of a tumour clonotype was successful in 68 patients: 63 of 69 (91%) patients with NHL or CLL and 5 of 9 (55%) HL patients. Compared to the 71 patients who were not evaluable for ctDNA, these 68 patients were on average older and more commonly received stem cells from an unrelated donor (data not shown); despite those differences, their outcomes were similar (2-year PFS 61% in evaluable ctDNA cohort versus 58% (p = 0.5), and 2-year OS 71% versus 68% (p = 0.4)). The baseline characteristics of the 68 patients with identifiable tumour clonotypes and paired blood samples for ctDNA analysis are listed in Table I. There were 37 patients (54%) with B-cell NHL, 10 (15%) with T-cell NHL, 5 (7%) with HL and 16 (24%) with CLL. A summary of the clonotype identification rate by lymphoma subtype is included in Table II.

Table I.

Baseline Characteristics of the Patients with Successful Clonotype Identification

Baseline Characteristics N %
Total 68 (100)
Age, years; median (range) 59 (27–69)
Male 43 (63.2)
Lymphoma Subtype
    B-NHL 37 (54.4)
DLBCL 6 (8.8)
TIL 11 (16.2)
FL 11 (16.2)
MCL 8 (11.8)
MZL 1 (1.5)
    T-NHL 10 (14.7)
AITL 5 (7.4)
ALCL 1 (1.5)
PTCL-NOS 1 (1.5)
EATL 1 (1.5)
T-PLL 2 (2.9)
    Hodgkin Lymphoma 5 (7.4)
    CLL 16 (23.5)
Donor Source 8/8 MSD 20 (29.4)
8/8 MUD 48 (70.6)
Disease Status at HSCT CR 31 (45.6)
PR 31 (45.6)
SD 4 (5.9)
PD 2 (2.9)
Median follow-up, months
(range)		 33 (3–60)
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B-NHL: B-cell non-Hodgkin lymphoma, T-NHL: T-cell non-Hodgkin lymphoma, DLBCL: diffuse large B-cell lymphoma, TIL: transformed indolent lymphoma, FL: follicular lymphoma, MCL: mantle cell lymphoma, MZL: marginal zone lymphoma, AITL: angioimmunoblastic T-cell lymphoma, ALCL: anaplastic large cell lymphoma, PTCL-NOS: peripheral T-cell lymphoma, not otherwise specified, EATL: enteropathy-associated T-cell lymphoma, T-PLL: T-prolymphocytic leukaemia, CLL: chronic lymphocytic leukaemia, MSD: matched sibling donor, MUD: matched unrelated donor, HSCT: haematopoietic stem cell transplantation, CR: complete response, PR: partial response, SD: stable disease, PD: progressive disease.

Table II.

Clonotype Identification Summary

Patients
Calibrated		 Total %
Total 69 88 (78.4)
Patients with sufficient (≥15
ng) DNA		 68 78 (87.1)
Lymphoma Subtype (only patients with sufficient DNA)
    B-NHL 37 41 (90. 2)
DLBCL 6 9 (66.7)
TIL 10 10 (100)
FL 12 13 (92.3)
MCL 8 8 (100)
MZL 1 1 (100)
    T-NHL 10 12 (83.3)
AITL 5 5 (100)
ALCL 1 1 (100)
PTCL-NOS 1 3 (33.3)
EATL 1 1 (100)
T-PLL 2 2 (100)
    Hodgkin Lymphoma 5 9 (55.6)
    CLL 16 16 (100)
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B-NHL: B-cell non-Hodgkin lymphoma, T-NHL: T-cell non-Hodgkin lymphoma, DLBCL: diffuse large B-cell lymphoma, TIL: transformed indolent lymphoma, FL: follicular lymphoma, MCL: mantle cell lymphoma, MZL: marginal zone lymphoma, AITL: angioimmunoblastic T-cell lymphoma, ALCL: anaplastic large cell lymphoma, PTCL-NOS: peripheral T-cell lymphoma, not otherwise specified, EATL: enteropathy-associated T-cell lymphoma, T-PLL: T-prolymphocytic leukaemia, CLL: chronic lymphocytic leukaemia.

The median follow-up time for survivors was 33 months (3–60 months). Estimated 2-year PFS and OS in the cohort of 68 patients were 62% and 71%, respectively. Nineteen patients relapsed during the course of the study, at a median time of 3.9 months (range 1–28 months) from HSCT. The 2-year CIR was 25% and the 2-year incidence of NRM was 13%.

PBMCs versus Plasma Results

Cryopreserved peripheral blood samples (n = 797) were evaluated for ctDNA, including 399 PBMC and 398 plasma samples. The median concentration of cells in PBMC samples was 10.8 × 106 mononuclear cells (range, 1 – 24.8 × 106 cells), and a median of 710,018 PBMC genomes (range, 9,146–3,915,959) and 1,418 plasma genomes (range, 33–237,509) were analysed in each type of specimen. ctDNA was detected in 33% of PBMC and 25% of plasma specimens tested. Discordance between PBMC and plasma samples, defined as detection of ctDNA in one type of specimen but not in the other, occurred at 85 of 386 (22%) time points in which both types of sample were tested. Detection of ctDNA in PBMC with failure to detect ctDNA in plasma (PBMC+/plasma-) from the same time point was more common (14.5%) than detection of ctDNA in plasma but not PBMC (PBMC-/plasma+, 7.5%). PBMC-/plasma+ discordance usually occurred in aggressive lymphoma subtypes: 86% of occurrences were in patients with DLBCL, HL or transformed indolent B-NHL.

ctDNA Positivity and Outcome

ctDNA analysis was performed at ≥ 1 time point in all 68 patients (Figure 1). Prior to HSCT, ctDNA was present in PBMCs or plasma in 55% of patients tested, including 9 of 23 (39%) patients in complete response (CR), 14 of 20 (70%) patients in partial response, 2 of 3 (67%) of patients with stable disease, and 1 (100%) patient with progressive disease. Using conventional staging methods as the gold standard, the sensitivity of the assay was 71% for the detection of residual disease prior to HSCT. Baseline ctDNA status was not significantly associated with outcome: 2-year estimated CIR was 35% in ctDNA-positive versus 20% in ctDNA-negative patients (p = 0.4) and 2-year PFS was 50% versus 71% (p = 0.19).

Figure 1. ctDNA Status, Relapse and GVHD Over Time.

Figure 1

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ctDNA status at each time point assayed, timing of relapse or time of last known follow-up without relapse, and timing of onset of acute or chronic GVHD in each patient through 2 years of follow-up.

ctDNA: circulating tumour DNA, GVHD: graft-versus-host disease, T-NHL: T-cell non-Hodgkin lymphoma, DLBCL: diffuse large B-cell lymphoma, B-NHL: B-cell non-Hodgkin lymphoma, CLL: chronic lymphocytic leukaemia, MRD: minimal residual disease.

ctDNA was detectable in 60% of patients at 1 month, 55% at 2 months and 52% at 3 months. The proportion of patients with detectable ctDNA declined at time points further from HSCT: 36% at 6 months, 21% at 1 year and 10% at 2 years. Receipt of sirolimus did not impact the rates of ctDNA-positivity at baseline (50% ctDNA-positive in sirolimus-receiving patients vs 61% in control, p = 0.6) or 3 months after HSCT (48% sirolimus vs 56% control, p = 0.8). At 1, 2 and 3 months after HSCT, detectable ctDNA had a sensitivity of 69%, 73% and 73%, respectively, for subsequent relapse/disease progression and a specificity of 45%, 55% and 55%, respectively. Among the 52 patients evaluated for ctDNA at 3 months after HSCT, the 2-year estimated CIR was 27% in patients who were ctDNA-positive versus 8% in ctDNA-negative patients (p = 0.12); 2-year NRM was 15% versus 8% (p = 0.3); and 2-year PFS was 58% versus 84% (p = 0.033), respectively (Figure 2).

Figure 2. Progression-Free Survival by ctDNA Status at 3 Months After HSCT.

Figure 2

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Landmark analysis to assess relationship between circulating tumour DNA (ctDNA) status and progression-free survival in patients free from death or relapse at 3 months after haematopoietic stem cell transplantation.

Overall, among the 19 patients who had progression or relapse after HSCT, ctDNA was detected prior to or at the time of relapse/progression in 17 (89%) patients. One patient with HL was ctDNA-negative prior to relapse, but had detectable ctDNA at the time of relapse. Thus, ctDNA was detected overall in 16 of 19 (84%) patients prior to documented relapse or progression (Figure 1). In patients with detectable ctDNA prior to relapse, ctDNA was detected at a median of 3.7 months (range, 1–26 months) prior to relapse/progression.

We examined the concordance between ctDNA and conventional restaging in patients who relapsed/progressed (Figure 1). Seven patients had detectable ctDNA in the setting of negative imaging at ≥ 1 time point prior to the documented relapse/progression event. One of these patients later had imaging confirmation of isolated central nervous system relapse of DLBCL and negative ctDNA at that time. Only one patient had imaging consistent with relapsed systemic lymphoma but undetectable ctDNA. Another patient was ctDNA-negative at the only time point evaluated (1 month), but did not have a sample evaluable for ctDNA when imaging demonstrated relapse 3.5 months after HSCT. In the remaining 10 patients, detectable ctDNA either occurred between disease reassessment time points (i.e. 1, 2 or 9 months after HSCT) prior to subsequent concordant ctDNA-positive documented relapse (n = 6) or ctDNA-positivity was concordant with active, stable or relapsed disease determined by conventional restaging methods (n = 4).

Kinetic Patterns of ctDNA after HSCT

In patients with more than one ctDNA sampling time point prior to relapse, death or data censoring (n = 64), we observed kinetic patterns to describe the presence or absence of ctDNA before and after HSCT. Thirteen patients had detectable ctDNA at all time points tested, and nine (69%) of these patients had relapse/progression after HSCT. Two persistently ctDNA-positive CLL patients did not have disease progression but actually had evidence of persistent active disease after HSCT and had detectable ctDNA at all time points tested. These patients were not formally considered as having relapse/progression because there was no overt progression of disease prior to non-relapse deaths. An additional persistently ctDNA-positive patient had early non-relapse death and never had formal restaging studies. Therefore, among the 12 patients who had conventional restaging performed and ctDNA present at all time points tested, 11 (92%) had relapse/progression or evidence of stable, active disease after HSCT. Eighteen patients were ctDNA-negative at all time points measured, and only 2 (11%) of these persistently ctDNA-negative patients relapsed. Eight patients had a mixed ctDNA pattern with alternating periods of ctDNA-positivity and ctDNA clearance, among who 2 relapsed.

Three patients who were initially ctDNA-negative subsequently became ctDNA-positive after HSCT without subsequent ctDNA clearance. Two of these were DLBCL patients who became ctDNA-positive late after HSCT, at 9 months and 18 months, and subsequently relapsed at 10 and 24 months, respectively. An HL patient was ctDNA-negative prior to HSCT and then became ctDNA positive 1 month after HSCT and remained ctDNA-positive until relapse 3 months after HSCT.

Twenty-two patients were consistently ctDNA-positive at ≥ 1 time point followed by permanent clearance of ctDNA. No patient with delayed, permanent ctDNA clearance had relapse or progression. Overall, among these patients, 8 (36%) were ctDNA-negative by 3 months after HSCT, 12 (55%) were ctDNA-negative by 6 months and 20 (91%) were ctDNA-negative by 1 year. Of note, GVHD occurred in 21 of 22 (95%, 19 chronic, 5 acute) of patients with delayed ctDNA clearance, but only in 4 of 13 (31%, 2 chronic, 3 acute) patients who were persistently ctDNA-positive at all time points. In 68% of patients with delayed ctDNA clearance, the onset of GVHD occurred before or within 3 months after the transition from ctDNA-positive to ctDNA-negative (Figure 1). All 21 patients with permanent ctDNA clearance who had GVHD remained free from relapse. The proportions of patients who had delayed ctDNA clearance, or were persistently ctDNA positive or negative, were similar among patients who received sirolimus as GVHD prophylaxis compared to patients in the control group (p = 0.2).

Multivariate Analysis

A multivariate model was constructed with histology and disease status at HSCT as covariates, and ctDNA-positivity included as a time-dependent covariate. ctDNA-positivity was associated with an increased risk of progression or death, with a hazard ratio (HR) of 3.9 (95% confidence interval [CI] 1.6–9.5; p=0.003), as well as an increased risk of disease relapse/progression (HR 10.8, 95% CI 2.8–42.2, p=0.0006). Histology and disease status were not significantly associated with either outcome in the model. When acute and chronic GVHD were entered into the proportional hazards model as time-dependent covariates, along with remission status and ctDNA-positivity; chronic GVHD was associated with a lower risk of disease relapse/progression (HR 0.2, 95% CI 0.05–0.96, p = 0.045), while ctDNA-positivity remained associated with an increased risk of disease relapse/progression (HR 8.2, 95% CI 2.5–26.6, p = 0.0004).

ctDNA and Chimerism

In surviving patients with available chimerism, the median total and T-cell donor chimerism at 3 months after HSCT were 97% (n = 60, range, 32–100%) and 90% (n = 49, range, 8–100), respectively. Bivariate landmark analyses at 3 months after HSCT with ctDNA-positivity and total or T-cell chimerism as covariates showed that the presence of ctDNA was independently associated with an increased risk of progression or death (HR 2.9, 95% CI 1.02–8.4, p=0.046), as was total donor chimerism < 90% (HR 3.6, 95% CI 1.13–11.4, p=0.030). T-cell chimerism was not significantly associated with outcome in the model when ctDNA-positivity was considered.

Discussion

NGS-based MRD assessment by immunoglobulin or T cell receptor gene sequencing is highly sensitive and has shown promise in a range of lymphoid malignancies.(Armand, et al 2013, Armand, et al 2016b, Faham, et al 2012, Gawad, et al 2012, Kurtz, et al 2015, Ladetto, et al 2014, Logan, et al 2014, Logan, et al 2013, Oki, et al 2015, Roschewski, et al 2015) In the present study, we report the first use of NGS-based MRD detection of lymphoma after allogeneic RIC HSCT in a cohort of patients with a large variety of histologies, including HL, CLL, B-cell NHL and T-cell NHL. With a successful clonotype identification rate of 91% in NHL and CLL patients with adequate archival tumour samples, this technique is readily applicable to the majority of lymphoma patients undergoing HSCT. The exception was the clonotype identification rate (55%) in HL patients with adequate tumour samples, which is lower than was observed in a previous report. (Oki, et al 2015) This may be explained by the histological characteristics of HL, in which there are few malignant cells among many reactive, inflammatory cells. Thus, in some patients with HL and the small proportion of patients with NHL and CLL in whom no clonotype can be identified, this technique may not be applicable.

Overall, ctDNA was detected in 55% of patients prior to HSCT, including 39% of patients considered to be in CR at the time of HSCT. Some patients with persistent disease prior to HSCT by conventional restaging did not have detectable ctDNA, which may reflect limitations of the assay but also probably reflects the common occurrence of false positive fluorodeoxyglucose positron emission tomography (FDG-PET) after standard therapy.(Moskowitz, et al 2010) Some degree of discordance between conventional restaging and this technique is expected, as other studies have reported a ctDNA-positivity rate of 81–92% at the time of diagnosis in patients with DLBCL.(Armand, et al 2013, Kurtz, et al 2015, Roschewski, et al 2015) Therefore, in a small proportion of patients in whom a clonotype can be identified, the assay may not be useful for tracking disease. In addition to discordance between conventional restaging methods and ctDNA assessment, discordance between the presence of ctDNA in PBMC versus plasma samples from the same patient assessed at the same time point was common. In aggressive lymphomas, evaluation of plasma appeared more sensitive for the detection of ctDNA, which may reflect higher cell turnover and shedding of cell-free ctDNA in these subtypes. Furthermore, testing for ctDNA in the PBMC compartment may be impacted by persistent leucopenia after HSCT, which could potentially limit sensitivity. This may be especially true in patients who receive more intensive conditioning or grafts from alternative donors, in whom engraftment may be slower. Therefore, in future studies, evaluation of both PBMC and plasma should be performed when possible to maximize the sensitivity of the assay.

In parallel to the high rates of MRD-positivity observed early after HSCT in other studies of MRD monitoring after RIC HSCT, many patients had detectable ctDNA in the early post-HSCT period.(Dreger, et al 2010, Logan, et al 2013) The proportion of patients with detectable ctDNA remained relatively stable until 3 months after HSCT then declined steadily. The decreasing proportion of ctDNA-positive patients was partially due to drop out of patients with relapse/progression. However, approximately one-third of patients had permanent clearance of ctDNA after initial ctDNA-positivity. This kinetic pattern of ctDNA clearance was associated with freedom from relapse (no relapses in our cohort) and similar patterns of delayed MRD clearance have been observed in studies of MRD monitoring after HSCT in other diseases.(Dreger, et al 2010, Farina, et al 2009, Miglino, et al 2002, Moreno, et al 2006, Ritgen, et al 2008) Delayed ctDNA clearance may have been temporally related with immunosuppression taper, which started at day +100 per protocol. Most patients (68%) with delayed ctDNA clearance developed GVHD prior to or around the time of the transition between ctDNA-positive to ctDNA-negative. Furthermore, in some patients with a mixed ctDNA pattern, periods of ctDNA clearance were immediately preceded by the onset of GVHD. In other studies of MRD monitoring after RIC HSCT, clearance of MRD was often associated with the onset of GVHD or immunosuppression taper.(Dreger, et al 2010, Farina, et al 2009, Moreno, et al 2006, Ritgen, et al 2008) The relationship between GVHD and disappearance of ctDNA observed in this study is evidence of a graft-versus-lymphoma effect.

In our study, nearly all (89%) patients with relapse or progression of disease after HSCT had detectable ctDNA prior to or at the time of relapse/progression. Eighty-four per cent of patients had detectable ctDNA at 1 or more time point prior to relapse/progression, and the median lead-time of ctDNA-positivity prior to relapse/progression was more than 3 months. Many relapses were detected radiographically as part of the protocol-specified disease reassessments rather than clinically-detected relapses; therefore, the lead-time interval we observed was partly a function of the protocol-driven timing of blood draws and disease reassessments. Notably, prior to the time point of confirmed relapse, several patients who ultimately relapsed had detectable ctDNA in the setting of negative imaging, while ctDNA-negativity with positive imaging occurred less frequently. Our findings suggest that NGS-based assessment of ctDNA after HSCT is very sensitive for relapse. This high sensitivity could possibly allow more judicious use of routine restaging scans, which are associated with significant costs and radiation exposure. (Berrington de Gonzalez, et al 2009, Brenner and Hall 2007) Because we evaluated the assay as a method of predicting future relapse/progression, we calculated the sensitivity and specificity of the assay to be reflective of subsequent relapse, rather than active disease at a particular time point. Therefore, the calculated sensitivity at early post-HSCT time points was relatively lower, as there were patients who had no detectable ctDNA and negative imaging early after HSCT but later became ctDNA positive at at least 1 time point prior to subsequent relapse/progression, which has been observed in other studies using this technique.(Roschewski, et al 2015)

Although NGS-based ctDNA detection appeared sensitive for relapse, there were patients who had detectable ctDNA after HSCT who did not relapse. This apparent lack of specificity of the assay is at least partly explained by the distinction between residual disease and relapse/progression in the clinical trial. Some patients enrolled in the clinical trial had residual disease prior to and after HSCT but were never classified as having frank relapse or progression. As a result, there were patients with evidence of active, stable disease by conventional restaging methods after HSCT in whom the assay appropriately detected ctDNA, but appeared to have falsely positive MRD status because they did not relapse or progress. More generally, this high early “false positive” rate reflects the realities of RIC HSCT – less intensive conditioning therapy results in more macro- or microscopic residual disease in the early post-HSCT period, with graft-versus-tumour effects developing over time. Thus, the presence of ctDNA after HSCT in many patients who do not ultimately relapse or progress would be expected. Nevertheless, ctDNA positivity at 3 months after HSCT was significantly associated with inferior PFS. In addition, multivariate analyses confirmed that detectable ctDNA was independently associated with an increased risk of relapse/progression and progression/death, even when incidental GVHD and total or T-cell donor chimerism were taken into account. If these findings can be validated in other studies and the specificity for subsequent relapse could be improved, detectable ctDNA after HSCT may provide an actionable result for therapeutic intervention to forestall clinically overt relapse.

One of the strengths of this study – the variety of histologies included – is also a limitation. The heterogeneous mixture of patients with different subtypes of NHL and HL limits our ability to draw conclusions about the assay’s performance in individual lymphoma subtypes. In addition, although we started with a possible study population of 118 patients, only 88 patients had archival tissue available for tumour clonotype identification, only 78 had sufficient tumour DNA for evaluation, and 68 patients with an adequate tumour sample had a tumour clonotype successfully identified. Differing tissue fixation techniques utilized at the various institutions from which tumour tissue was obtained and originally processed may have impacted tumour clonotype identification. Even among patients with an identifiable clonotype, there were missing blood samples despite the prospectively planned sample collection within the context of a clinical trial. The missing time points decrease the power of the study, particularly in patients with early relapse and few opportunities to detect ctDNA prior to progression. More generally, these issues highlight the importance of prospectively archiving tumour samples and of routinely and frequently collecting PBMC and plasma samples whenever possible in patients in whom MRD measurement may become desirable at some point in their treatment course. Finally, as this study only examined patients who underwent RIC HSCT using fully HLA-matched or single mismatched donors, we are unable to comment about the assay’s utility in patients who receive more intensive conditioning or a graft from other donor types.

In this pilot study of NGS-based ctDNA detection in patients with lymphoma undergoing HSCT, we observed that the presence of ctDNA after HSCT was associated with an increased risk of relapse and inferior PFS. Although our findings are promising, validation studies with pre-defined endpoints are necessary. With further validation, the detection of ctDNA in the setting of radiographic disease progression could also potentially serve to confirm disease recurrence without the need for a tissue biopsy. Further studies are required to establish the clinical utility of NGS-based ctDNA detection after HSCT, including how best to prospectively incorporate this assay into post-HSCT monitoring, the utility of the test in specific lymphoma subtypes, and whether the test is sufficiently specific to justify MRD-based intervention. We have identified specific situations that appear to be promising targets for further exploration, including ctDNA status in conjunction with GVHD status and ctDNA-positivity 3 months after HSCT. As interest grows in novel approaches for preventing relapse after HSCT, NGS-based MRD detection should be incorporated into prospective clinical trials to further study and optimize the use of this potentially promising technique in this patient population.

Supplementary Material

Supp Table S1

Acknowledgments

We would like to thank the patients who participated in the clinical trial and their families, as well as the nursing and research staff involved in the study. This study would not have been possible without the dedication of Doreen Hearsey and the staff of the Dana-Farber Cancer Institute Pasquarello Tissue Bank. We would like to thank the Ted and Eileen Pasquarello Research Fund and the Jock and Bunny Adams Education and Research Fund. A.F.H was supported by a Conquer Cancer Foundation/ASCO Young Investigator Award and by the National Cancer Institute of the National Institutes of Health under award number NIH 2K12CA001727-21. The content is solely the responsibility of A.F.H. and does not necessarily represent the official views of the National Institutes of Health. P.A. was supported by an ASH Scholar Award, an ASCO Career Development Award, an ASBMT/Genentech Young Investigator Award, and a Dunkin’ Donuts Rising Star award for this work. H.T.K was supported by National Institutes of Health award, R01CA183559-03. This work was also supported by National Institutes of Health awards P01CA142106, R01CA183559, and R01CA183560.

Footnotes

The interim analysis of this study was presented at the Annual Meeting of the American Society of Hematology meeting in December 2014 in San Francisco, CA.

AUTHOR CONTRIBUTIONS

A.F.H. designed the research, collected and analysed the data and wrote the manuscript.

H.T.K. designed the research, analysed the data and edited the paper.

K.A.K. collected data and edited the paper.

M.K. collected data and edited the paper.

H.S. collected data and edited the paper.

A.R.S. collected data and edited the paper.

E.P.A. collected data and edited the paper.

V.E.C. collected data and edited the paper.

Y.-B.C. collected data and edited the paper.

C.S.C. collected data and edited the paper.

V.T.H. collected data and edited the paper.

C.K. collected data and edited the paper.

J.K. collected data and edited the paper.

S.N. collected data and edited the paper.

J.R. collected data and edited the paper.

S.J.R. collected data and edited the paper.

R.J.S. designed the research, collected data and edited the paper.

J.H.A. designed the research, collected data and edited the paper.

P.A. designed the research, collected and analysed the data, and edited the paper.

CONFLICT OF INTEREST DISCLOSURES

K.A.K., M.F., V.E.C., and C.K. are employees of and have equity ownership in Adaptive Biotechnologies, Inc.

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