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Integrating post induction WT1 quantification and flow-cytometry results improves minimal residual disease stratification in acute myeloid leukemia Carlo Marani a,∗ , Marino Clavio a , Raffaella Grasso a , Nicoletta Colombo a , Fabio Guolo a , Annalisa Kunkl b , Filippo Ballerini a , Livia Giannoni a , Chiara Ghiggi a , Giuseppina Fugazza a , Jean-Louis Ravetti b , Marco Gobbi a , Maurizio Miglino a a b
Department of Hematology and Oncology, IRCCS AOU S.Martino-IST, Genova, Italy Department of Pathology, IRCCS AOU S.Martino-IST, Genova, Italy
a r t i c l e
i n f o
Article history: Received 1 February 2013 Accepted 1 July 2013 Available online xxx Keywords: Acute myeloid leukemia Minimal residual disease Flow-cytometry Wilms’ tumor gene Prognosis Early response assessment
a b s t r a c t Fifty uniformly treated adult AML patients were analyzed with respect to pre-treatment and postinduction risk factors. Forty-two patients achieving complete hematological remission were assessed for minimal residual disease (MRD) by WT1 gene expression; 34 by flow-cytometry (flow-MRD). Patients who were flow-MRD negative had a better 3-year disease-free (DFS; 79.5% vs. 27.3%; p = .032) compared with patients who were still positive after induction. Interestingly, DFS of flow-MRD positive patients was not related to the amount of flow-detected clone population (≥ or <1%, p = .41) but to WT1 reduction (WT1, 3-year DFS; 46.2% vs. 0% if WT1 was ≥ or < of 1.5 log, p = .001). In AML, combining MRD results provided by WT1 quantification and flow-cytometry improves the reliability of MRD-based prognostic stratification. Similar analyses by further larger studies should be advocated. © 2013 Elsevier Ltd. All rights reserved.
1. Introduction Although prognostic stratification of AML patients is mainly based on the disease and patient-related pre-treatment work up [1,2] increasing efforts are being made to validate the prognostic value of post-treatment factors. Quantitation of minimal residual disease (MRD) has proven to be useful in evaluating the quality of response and predicting relapse rate in AML patients [3–8]. Flow cytometric methods proved to be useful tools for identifying and quantifying marrow residual clonal cells following chemotherapy [7], but the low inter-laboratory reproducibility of the analysis has prevented it from becoming a standard method for MRD evaluation in AML. Quantitative assessment of fusion transcript (PML-RAR␣, RUNX1-RUNX, CBFB-MYH11) [9,10] and of genetic lesions (NPM1 mutation, FLT3-ITD) have showed to be useful tool as well [11,12]. However, about 30% of AML patients do not present a molecular mutation or a fusion transcript gene that can be monitored. This is why the expression of the Wilms’ tumor gene 1 (WT1) has
∗ Corresponding author at: Clinical Hematology, University of Genova, Viale Benedetto XV, N 6, 16132 Genova, Italy. Tel.: +39 010 3538676; fax: +39 010 3538676. E-mail address:
[email protected] (C. Marani).
been extensively assayed in patients lacking specific genetic markers [13–16]. Known as a tumor repressor gene, WT1 is found to be overexpressed at diagnosis in 70–80% of AML cases in adults and children [5]. However, in the main European Study on WT1 MRD assessment, Cilloni et al. concluded that only 13–46% of AML patients had a diagnostic WT1 overexpression high enough to allow the use of WT1 as early MRD assessment [4]. In a cohort of 50 nonM3 AML patients undergoing intensive chemotherapy, we studied the prognostic impact of both early WT1 reduction and flow-MRD status. To increase the percentage of patients studied by WT1 assessment we chose to study all patients with a diagnosis WT1 overexpression greater than 1000 copies/ablx104 . 2. Materials and methods At diagnosis, marrow samples of 110 consecutive adult, non M3 AML patients were studied for WT1 expression at our hematological laboratory. To evaluate the impact of MRD kinetics only patients whose WT1 expression was greater than 1000 copies WT1/Ablx104 were analyzed; 81 out of 110 patients (73%) fulfilled this criterion. Among these patients, only those receiving the same therapy (see below) and for whom a post induction bone marrow sample was available were included in the study. Overall, data concerning 50 non M3 AML patients (44 de novo and 6 secondary, 34 patients below 60 years of age and 16 pts above 60, median age 54 years, range 17–81) treated at our institution between March, 2003 and December, 2011 were analyzed. Fourteen out of 50 patients had a high risk (HR) profile at diagnosis based either on cytogenetic risk (5 patients had an adverse karyotype,
0145-2126/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.leukres.2013.07.005
Please cite this article in press as: Marani C, et al. Integrating post induction WT1 quantification and flow-cytometry results improves minimal residual disease stratification in acute myeloid leukemia. Leuk Res (2013), http://dx.doi.org/10.1016/j.leukres.2013.07.005
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2 Table 1 Characteristics of the patient population. Characteristics
n (%)
Age (years) Median Range ≤60 >60
54 17–81 34 (68) 16 (32)
Female/male De novo/secondary Karyotypea Favorable Intermediate Unfavorable No evaluable methaphases Molecular profile FLT3-ITD pos With wild type NPM-A gene With mutated NPM-A gene Mutated NPM-A gene With wild type FLT3 BAALC overexpression (>1000 copies/abl 103 ) WT1 copies/abl 103 Median Range Risk profile at diagnosisb High risk ≤60 years >60 years No high risk ≤60 years >60 years
21/29 44/6 2 (4) 40 (80) 5 (10) 3 (6)
Patients 60 years of age or older received a second, identical course of FLAI and three courses of Ara-C (1 g/sqm every 12 hours for three times), every 3 months. Patients not achieving CR received salvage therapy according to the MEC (mitoxantrone, etoposide, and Ara-C) regimen. 4. Cytogenetic analysis A Q-banded chromosome study was performed on diagnostic BM samples using standard cytogenetic techniques as described previously [19]. Karyotypic findings were classified according to the MRC criteria [17,18]. 5. Flow cytometric analysis
14 (28) 6 8 16 (32) 7 22 (44) 13,540 1060–346,060 14 (28) 7/34 (20) 7/16 (43) 36 (72) 27/34 (80) 9/16 (57)
a
According to Grimwade ASH 2009. See text for more details. High risk (HR) profile at diagnosis was defined as: unfavorable karyotype, intermediate karyotype with Flt3-ITDpos/NPM-Aneg, and AML secondary to therapy or previous hematological disorder. No high risk profile: all the others. b
according to refined MRC criteria [17,18]) or on molecular status (4 patients were FLT3-ITDpos /NPM-Aneg with an intermediate risk karyotype), or on secondary hematological disease (1 therapy-related and 4 to a previous hematological disorder). Patients’ features at diagnosis are summarized in Table 1. Bone marrow samples collected at diagnosis and at post induction evaluation were used for morphological, cytogenetic, flow-cytometric, and molecular characterization. Post induction evaluation was done after hematological recovery from the previous chemotherapy, i.e. at time of hospitalization for the second course of chemotherapy.
3. Therapy 3.1. Induction regimen Patients younger than 60 years of age received FLAI5 regimen including fludarabine (30 mg/sqm on days 1–5), followed four hours later by a 4 h infusion of Ara-C (2 g/sqm on days 1–5) and by a 30 minute infusion of idarubicin (12 mg/sqm on days 1, 3, 5). Patients 60 years of age or older received the FLAI3 regimen including fludarabine (30 mg/sqm on days 1–3), followed 4 h later by a 4 h infusion of Ara-C (1 g/sqm on days 1–3) and by a 30 min infusion of idarubicin (5 mg/sqm on days 1–3). 3.2. Post induction therapy Patients younger than 60 years of age received a 4 hour infusion of Ara-C (2 g/sqm on days 1–5) plus idarubicin (12 mg/sqm on days 1, 3, 5), followed by 3 courses of Ara-C (2 g/sqm on days 1–4) as further consolidation therapy. BMT in first complete remission (CR) was scheduled for patients below 50 years of age who had a familiar human leukocyte antigen (HLA)-matched donor, unfavorable karyotype, or FLT3-ITD. Patients who were eligible for early BMT received only the first consolidation course.
Erythrocyte-lysed whole BM samples obtained at diagnosis were analyzed with a broad panel of monoclonal antibodies to define lineage and to identify the most relevant aberrations described in blasts. [20,21] EDTA blood (2 ml) was bulk lysed with 1× BD Pharm LyseTM Lysing buffer (30 ml) for 5 min, centrifuged at 1500 rpm for 7 min and washed once in Dulbecco’s PBS. Cells (50 l at 10–20 × 106 /ml) were stained for cell surface markers with 20 l antibody combinations for 15 min at RT. Intracellular nuclear (n) and cytoplasmic (cy) staining were performed after cell fixation and permeabilization using Intrastain kit by DAKO (Milan, Italy). After staining, cells were washed using a BD FACS Lyse Wash Assistant, acquired with a flow cytometer (FACSCaliburTM and FACSCantoTM II, Becton Dickinson, Mountain View, CA, USA) and analyzed with BD CellQuest and FACSDiva software. The following combinations of monoclonal antibodies in four color staining – fluorescein isothiocyanate/phycoerythrin/peridin chlorophyll protein/allophycocyanin – were used at diagnosis: CD34/CD38/CD45/CD117, CD45RA, CD45RO/CD45/CD34, CD34/ CD13/CD45/CD2, CD7/CD33/CD45/CD34 or CD117, CD15/ HLADR/CD45/CD34 or CD117, CD5/CD10/CD45/CD34, CD64/ CD14/CD45/CD34 or CD117, CD36/CD14/CD45/CD34 or CD117, HLADR/CD11b/CD45/CD34, cyCD3/cyCD79a/CD45/CD34, cylisozima/cyMPO/CD45/CD34 or CD117, nTdT/cyMPO/CD45/CD34. All antibodies were purchased from BD Biosciences (San Jose, CA, USA) except for TdT (Pool)-FITC from Beckman Coulter (Immunotech, Marseille, France) and Polyclonal Rabbit Anti-Human lysozyme from DAKO (Milan, Italy). Leukemia-associated immunophenotypes (LAPs) were identified and used to track residual leukemic cells during follow up by staining them with at least two relevant 4-color antibody combinations and acquiring 100–300 × 103 nucleated cells. The strategy recommended by the Dutch/Belgium Task Force for MRD detection in AML in cooperation with The European working group on Clinical Cell Analysis was used [22]. A positive flow MRD was defined by the presence of no less than 25 clustered leukemic cells/105 total events (threshold of 2.5 × 10−4 residual leukemic cells). 6. Molecular analysis At diagnosis, molecular parameters were evaluated (FLT3-ITD, NPM1 gene mutation A, WT1 and BAALC expression) according to standard techniques, as detailed elsewhere [4,23,24]. Ranges of BM WT1 expression between 0 and 500/Ablx104 were assumed to be physiological on the basis of previous studies on healthy bone marrow donor WT1 expression analysis (21 donor bone marrow samples, average values 328.9, standard deviation (SD) 177.6, cutoff 506.4 WT1 copy number/Abl copy number x104 ). To be sure that only patients with WT1 “over-expression” would be studied, we then arbitrarily chose a cut-off of 1000 copies WT1/Ablx104 (i.e.
Please cite this article in press as: Marani C, et al. Integrating post induction WT1 quantification and flow-cytometry results improves minimal residual disease stratification in acute myeloid leukemia. Leuk Res (2013), http://dx.doi.org/10.1016/j.leukres.2013.07.005
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more than the average value plus 2SD). To evaluate the kinetics of reduction of WT1 expression, we calculated the difference between the logarithm of the WT1 value at diagnosis and the WT1 level after induction (WT1 = logWT1 at diagnosis – logWT1 post induction). 7. Outcome definition and statistical analyses CR and relapse were defined as previously reported in the literature [1]. Disease-free survival (DFS) was evaluated as the time from achievement of CR to the date of the last follow-up for patients in CR or to the date of relapse or death by any cause. For patients undergoing BMT, DFS was censored at the time of BMT. Overall Survival (OS) was calculated as the time from diagnosis until last followup or death. DFS and OS were calculated using the Kaplan–Meier method. Only patients who achieved CR after induction therapy were included in the comparison of DFS or OS between MRD groups. Univariate survival analysis was performed using the logrank test, survival percentages were calculated using the Kaplan Meier method. A Cox regression model was built for multivariate survival analysis. Dichotomous variables were compared using Chi Square test, or Fisher’s exact test when necessary. Continuous variables were compared using Student’s T-test, or, if normal distribution could not be confirmed, the Mann–Whitney rank test was used. All factors were considered statistically significant if they had a two-tailed p-value <.05. All data were analyzed using IBM SPSS v.19. 8. Results 8.1. Response and outcome according to prognostic profile at diagnosis After the first induction regimen, CR was achieved in 42 out of 50 (84%) patients. All 8 non-responding patients had died at the time of the analysis, median OS 9.5 months (range 2–24). Among 42 responding patients, 7 received only a first consolidation cycle and then underwent BMT, whereas 35 received the scheduled consolidation program. Overall, 24 out of 42 patients relapsed (57%), 20 (57%) after chemotherapy (median duration of CR 6 months, range 1–34 months) and 4 after BMT. Eighteen patients were alive and disease free at the date of follow-up analysis (overall survival: median 32 months, range 9–88 months). Six of 14 HR profile patients failed to respond to the first induction course, 7 relapsed, 1 is still in remission after BMT (projected DFS 4.2 months). Only 2 (14%) were still alive at the time of analyses. Patients older than 60 years and those having a HR profile showed poor outcome (see Table 2). NPMpos /FLT3pos and NPMneg /FLT3pos patients had a 3-year OS of 44.4%, and 0%, respectively (p < .001); 3-year DFS rates were 57.1% and 0%, respectively (p < .001).
Fig. 1. DFS according to post induction flow-MRD (positive vs. negative, p = .032).
was flow-MRDneg but relapsed after BMT. In the 23 flow MRDpos patients, DFS was not affected by the amount of residual neoplastic population, above or below 1% (p = .41, Fig. 2). All 42 responding patients were assessed for WT1-based MRD after induction. Seventeen out of 42 patients displayed a WT1 greater than 2 logs, 16 had a WT1 ranging between 1 and 2, while 9 had less than 1 log WT1. Three-year DFS was significantly affected by the degree of WT1 reached after the first induction course: it was 65.5% vs. 35.7% vs. 0% in patients with WT1 >2 log, between 1 and 2 log, and <1 log, respectively (p < .001). Statistical analysis proved WT1 <1.5 log to be the best cut-off level associated with an increased relapse risk. Out of 42 patients, 27 had a WT1 ≥1.5 log and 15 had a WT1 <1.5 log: 3-year DFS was 58.3% and 0%, respectively (p < .001), Fig. 3. Thirteen out 14 HR profile patients had WT1 <1.5 log; only one achieved WT1 ≥1.5 log but relapsed 6 months after. Combining flow-based and WT1-based MRD results, we found that among 11 flow-MRDneg patients, 10 had a WT1 ≥1.5 log (in 9 it was greater than 2 logs), whereas only one patient had WT1 <1.5 log: this patient had an adverse cytogenetic risk at diagnosis
8.2. Outcome according to post induction MRD analysis BM assessment was made at a median time of 37 days after the end of induction (range 31–42). Data on post induction flowMRD were available for 34 out of 42 responding patients. Eleven of them (32%) were flow-MRDneg and 23 (68%) were flow-MRDpos , Table 2. Among flow-MRDpos patients, the residual clonal population ranged between .025% and 1% in 12 patients, and between 1% and 5% in the remaining 11 patients. The post induction residual clonal population detected by flow had a strong prognostic value: 3-year DFS was indeed 79.5% and 27.3% in flow MRDneg and flow MRDpos patients, respectively, (p = .032), as shown in Fig. 1. None of the patients older than 60 years of age reached a negative postinduction flow-MRD, while among 14 HR profile patients, only one
Fig. 2. DFS in 23 flow-MRD positive patients according to the amount of residual neoplastic population (< or >1%, p = .41).
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Table 2 Outcome according to pre-treatment risk factors and post-induction MRD assessment. n Profile risk at diagnosisa Low-intermediate High Age <60 years >60 years WT1 at diagnosis <2400 >2400 Flow MRD Negative Positive WT1 ≥1.5 log <1.5 log Flowpos WT1 ≥ 1.5 log WT1 < 1.5 log New class risk No HR, WT1 ≤ 1.5 and Flowneg No HR, WT1 ≥ 1.5 and flowpos HR or WT1 < 1.5
50 36 14 50 34 16 50 32 18 34 11 23 42 27 15 23 13 10 42 10 16 16
3 years-DFS (%)
p univ.
48.8 0
.002
49.3 20
OS (mean, months)
p univ.
.227
52.3 15.4
.000
.293
.072
.899
53.1 20.1
.003
.280
20.7 66.1
.047
.237
24.4 54.7
.133
.853
79.5 27.3
.032
.351
68.3 27.4
.023
.272
58.3 0
.000
.001
63.7 16.4
.000
.001
46.2 0
.001
–
39.6 15.5
.010
.000
–
80.1 42.8 16.5
.000
78.8 51.6 0
p multiv.
p multiv.
–
a See text for more details. High risk (HR) profile at diagnosis was defined as: unfavorable karyotype, intermediate karyotype with Flt3-ITDpos/NPM-Aneg, and AML secondary to therapy or previous hematological disorder. Low-intermediate: all the others.
and relapsed after BMT. On the other hand, all patients with WT1 <1.5 log were flow-MRDpos as well. Since the amount of neoplastic residual population detected by flow had no prognostic value, and since about 40% of flow-MRDpos patients maintained CR despite the persistence of residual clonal population, we decided to stratify flow-MRDpos patients according to WT1 kinetics. In this subgroup, 13 patients with a WT1 ≥1.5 log had a better outcome compared to 10 with WT1 <1.5 log (3 year DFS was 46.2% vs. 0%, respectively, p < .001). Combining profile risk at diagnosis with MRD assessment using both flow and WT1 allowed us to classify patients into three prognostic groups: good (no-HR and flow-MRDneg ), intermediate (no-HR, flow-MRDpos and WT1 ≥1.5 log) and adverse prognosis (HR or WT1 <1.5 log) with a 3-year DFS of 78.8%, 51.6% and 0%, respectively, (p < .001) Fig. 4.
Fig. 3. DFS according to post induction WT1 reduction (< or ≥1.5 log, p < .001).
9. Discussion Our study highlights the prognostic value of early MRD assessment in AML patients in the post induction setting. Being flow-MRDneg was associated with the lowest relapse rate whereas WT1 <1.5 log identified a new unfavorable subgroup of patients whose survival was comparable to that of the HR profile patients. On Cox regression model WT1 <1.5 log resulted as independent risk factor of relapse and no patient with WT1 <1.5 log was disease-free at 3 year after CR. The strong correlation between low WT1 reduction and relapse risk allowed a better stratification of flow-MRDpos patients, increasing MRD assessment prognostic value and reliability. Unlike results of other studies [6,8], outcome of flow-MRDpos patients was not affected by the amount of residual neoplastic population, but it was by the WT1 achieved. In relation to WT1, flow-MRDpos patients were split into an intermediate prognosis group (WT1 >1.5, median DFS 34.0 months, 3 yearprojected DFS 46.2%) and a poor prognosis group (WT1 ≤1.5 log
Fig. 4. DFS according to profile risk at diagnosis, flow- and WT1-based MRD.
Please cite this article in press as: Marani C, et al. Integrating post induction WT1 quantification and flow-cytometry results improves minimal residual disease stratification in acute myeloid leukemia. Leuk Res (2013), http://dx.doi.org/10.1016/j.leukres.2013.07.005
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median DFS 5.8 months, 3 year-projected DFS 0%). This observation reflects concerns about the use of a single-methodology approach to MRD assessment in AML patients. Patient-specific antibody combinations used for flow-MRD assessment are still defined on subjective grounds resulting in a low reproducibility of results and in a hard-to-resolve standardization issue [25]. At the present, integrating different approaches may corroborate the results provided by one methodology and help the clinician in making decisions about chemotherapy shifts and BMT allocation. Furthermore, our study pointed out that early WT1-MRD assessment might be used in a wider AML population than that was assumed so far [4]. Choosing 1000 copies WT1/Ablx104 as diagnosis cut-off increased the percentage of evaluable AML patients to 73% of the AML population, compared to 13–46% of ELN study [4]. Our lower cut-off implied that in a substantial proportion of patients post induction WT1 expression levels fell into the so-called “physiological range”. For instance, in a patient with a 10,000 WT1 expression, a reduction of 2 logarithms is indeed split into two parts; the first part is in the “pathological range” (log 10,000–log 500 = 1.3 log) and the second part is in the “physiological range” (log 500–log 100 = .7 log). However, since the biological and clinical meaning of WT1 reduction in the physiological range has, to date, never been clarified, we decided to take it into account of WT1 calculation. The second reason for defining a lower WT1 cut off level is to avoid a possible bias by selecting patients with a more favorable outcome [24]. Within our series, three groups of patients can be identified at diagnosis; those with a WT1 expression level of at least 2 log greater than the upper physiological range limit (group 1; 8 patients), between 1 and 2 log above it (group 2; 30 patients), and less than 1 log above it (group 3; 12 patients). The probability of achieving ≥1.5 log reduction of WT1 level was 87.5%, 63% and 8% in groups 1, 2 and 3, respectively. In the last decade, MRD evaluation has been given a relevant prognostic value, although consensus on timing (after consolidation, induction or during chemotherapy) and type of technique (immunophenotypic or molecular based) has not been reached yet. According to Buccisano et al. [26], major prognostic information is obtained when flow MRD assessment is performed after the end of consolidation therapy. Gianfaldoni et al. [27] highlighted the relevant prognostic impact of WT1 expression reduction during induction chemotherapy, evaluating the WT1 kinetic on day 5 after induction. Rossi et al. employed both cytofluorimetric and WT1 based techniques in 23 patients who achieved CR after induction course, but without disclosing any advantage by the integration of two techniques [28]. In conclusion, our study supports the use of early MRD assessment in the prognostic stratification of AML patients, steering patient allocation to individually tailored therapeutic approaches. However, efforts should still be made in order achieve a consensus on the methodology and on the choice of time-point sampling. In this respect, integrating results from different methodologies might increase the reliance on the results and the clinician’s confidence in planning treatment on the basis of MRD results. High risk profile patients at diagnosis and patients not achieving post induction flow-MRDneg status or WT1 ≥1.5 log form a unique poor risk subgroup of patients that should receive alternative treatments including BMT in an upfront setting. Since the clinical impact of MRD assessment is closely related to treatment, clinical setting and time-point evaluation, further results from prospective studies are strongly needed.
Conflict of interest The authors declare no competing financial interests.
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Acknowledgements We are grateful to the all physicians and nurses who contributed to this study assisting our patients at the Clinic of Hematology. We are grateful to prof. Valeria Perricone for language support. This work was partially supported by Ministero dell ’Istruzione, dell ’Università e della Ricerca (PRIN n◦ 2007WEYB3A)Contributions. C.M. and M.M. provided the conception and design; M.M. supplied the financial support; F.B., C.G., C.M., R.G., N.C., A.K., and J.-L.R. submitted study materials and/or patients; C.M., F.G. and L.G. collected and assembled the data; C.M., M.C. and M.M. wrote the manuscript and C.M., M.C., A.K, M.M. and M.G. gave final approval of manuscript submitted. References [1] Döhner H, Estey EH, Amadori S, Appelbaum FR, Büchner T, Burnett AK, et al. Diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet. Blood 2010;115:453–74. 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Please cite this article in press as: Marani C, et al. Integrating post induction WT1 quantification and flow-cytometry results improves minimal residual disease stratification in acute myeloid leukemia. Leuk Res (2013), http://dx.doi.org/10.1016/j.leukres.2013.07.005