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Leukemia Research
journal homepage:www.elsevier.com/locate/leukres
Research paper
Post-remissional and pre-transplant role of minimal residual disease
detected by WT1 in acute myeloid leukemia: A retrospective cohort study
Chiara Frairia
a,⁎, Semra Aydin
a, Ernesta Audisio
a, Ludovica Riera
b, Sabrina Aliberti
b,
Bernardino Allione
a, Alessandro Busca
c, Stefano D'Ardia
a, Chiara Maria Dellacasa
c,
Anna Demurtas
b, Andrea Evangelista
d, Giovannino Ciccone
d, Paola Francia di Celle
b,
Barbara Nicolino
a, Alessandra Stacchini
b, Filippo Marmont
a, Umberto Vitolo
aaDepartment of Hematology, University-Hospital Città della Salute e della Scienza, Torino, Italy bDepartment of Pathology, University-Hospital Città della Salute e della Scienza, Torino, Italy cBone Marrow Transplant Center, University-Hospital Città della Salute e della Scienza, Torino, Italy
dUnit of Clinical Epidemiology, University-Hospital Città della Salute e della Scienza, Torino, Italy and CPO Piemonte, Italy
A R T I C L E I N F O
Keywords:
Acute myeloid leukemia Minimal residual disease WT1 overexpression Induction treatment
Allogeneic stem cell transplantation
A B S T R A C T
In acute myeloid leukemia (AML), the detection of minimal residual disease (MRD) is still under investigation. The aim of the present retrospective study was to assess the role of Wilms tumor gene 1 (WT1) overexpression in a large monocentric cohort of AML patients. Among 255 enrolled patients, MRD was investigated in those in complete remission (CR) with an available WT1 at baseline (> 250 copies) and at two further time-points: after induction (n = 117) and prior allogeneic hematopoietic cell transplantation (allo-HCT), n = 65. Baseline BM WT1 overexpression was not associated with response to induction (p = 0.244). Median overall survival (OS) and disease-free survival (DFS) were significantly shorter in patients with > 350 WT1 copies after induction compared to those with≤350 (HR for mortality 2.13; 95% CI 1.14–3.97, p = 0.018 and HR for relapse 2.81; 95% CI 1.14–6.93, p = 0.025). Patients with WT1 > 150 copies pre allo-HCT had a significantly higher 2-year cumulative incidence of relapse (CIR) compared to those with WT1≤ 150 (HR 4.61; 95% CI 1.72–12.31, p = 0.002). The prognostic role of WT1 overexpression resulted independent from other well-established risk factors. According to these results, WT1 overexpression might represent an additional MRD tool for risk stra-tification in patients classified nowadays in CR.
1. Introduction
The detection of residual leukemic cells at a submicroscopic level (minimal residual disease− MRD) provides a powerful and precise tool for monitoring the kinetics of disease response after treatments.[1–3] Quantitative real-time polymerase chain reaction (QRT-PCR) has a sensitivity exceeding 10−5leukemic cells with a high reproducibility profile and has become the most popular method to investigate mea-surable residual disease. [4]About 60% of AML carries a leukemia-specific target (a chimeric fusion gene or a gene mutation such as NPM1, CEBPA, FLT3-ITD, MLL) suitable for MRD detection.[5,6]In the remaining 30–40% of AML lacking a specific molecular target, QRT-PCR has been used to detect transcripts commonly overexpressed in AML blasts. Recently, Wilms tumor gene 1 (WT1) overexpression has been proposed, among a large number of candidates,[7]as a promising MRD marker. Indeed, WT1 is highly overexpressed in several
hematopoietic tumors reaching a positivity up to 80–90% in AML[8] without modulation due to post chemotherapy regeneration. Cilloni et al. standardized the QRT-PCR method on behalf of the European LeukemiaNet (ELN)[9]and proposed cut-off levels of 50 WT1 copies in peripheral blood (PB) and 250 in bone marrow (BM) per 104copies of the ABL housekeeping gene, respectively. In our study, patients with less than 2-log reduction in WT1 transcripts after induction treatment had an independent significantly increased relapse risk.[9]Based on these preliminary data, WT1 transcript was suggested as an additional tool for response assessment and relapse prediction. Subsequent studies investigated the role of WT1 overexpression in different time-points (early after induction, post-induction and post intensification) with controversial results.[10–13]The aim of the present study was to assess the role of WT1 overexpression as a MRD marker after intensive in-duction chemotherapy and before allogeneic hematopoietic cell trans-plantation (allo-HCT) in a large monocentric cohort of AML patients
http://dx.doi.org/10.1016/j.leukres.2017.08.008
Received 8 June 2017; Received in revised form 15 August 2017; Accepted 16 August 2017
⁎Corresponding author.
E-mail address:[email protected](C. Frairia).
0145-2126/ © 2017 Elsevier Ltd. All rights reserved.
considered in complete remission (CR) according to the standard re-sponse criteria.[14]
2. Materials and methods 2.1. Study population
The present retrospective cohort study included adult patients with non-APL untreated AML (n = 281), consecutively diagnosed between March 2004 and March 2014 in the Hematology Unit of the University-Hospital Città della Salute e della Scienza-Torino, Italy. The study was approved by the Ethical Committee and was conducted in accordance with the Declaration of Helsinki. The study was registered at www.clinicaltrials.gov as NCT02714790. Only patients with an avail-able baseline BM WT1 > 250 copies [8](223 out of 281) were in-cluded in the study; confirmatory analysis were conducted simulta-neously in all patients with an available baseline BM WT1 irrespectively of value (255 out of 281). Patients with a sole extramedullary disease at the time of diagnosis were excluded. All patients underwent intensive induction chemotherapy with curative intent with two different regi-mens adjusted for patient’s age, comorbidities and performance status (PS). Young patients (< 70 years) with good PS and without severe comorbidities were treated according to the ICE regimen [15]with Idarubicin (12 mg/m2days 1–3), Cytarabine (100 mg/m2q 12 h days 1–7) and Etoposide (16 mg/m2days 1–5). Response in CR patients were consolidated with a course of IC (Idarubicin 10 mg/m2days 1–3 and Cytarabine 100 mg/m2q 12 h days 1–7) and a subsequent cycle with intermediate dose Cytarabine (1 g/m2 q 12 h days 1–4) followed by stem cell harvest. Based on the AML risk assessment, [16]low risk patients were treated with autologous peripheral stem cell transplan-tation (auto-SCT) whereas intermediate/high risk patients underwent allo-HCT based on donor availability. Auto-SCT was performed fol-lowing one course of myeloablative treatment with BU-CY (Busulfan 0·8 mg/kg 6 h days 1–4, Cyclophosphamide 60 mg/kg days 5–6) or three successive courses with Cytarabine 2 g/m2q 12 h days 1–5. The remaining elderly ( > 70 years) or young patients with comorbidities, but fit for intensive chemotherapy, underwent induction with the FLAG-IDA protocol[17](Fludarabine 25 mg/m2days 1–4, Cytarabine 1000 mg/m2days 1–4 and Idarubicin 8 mg/m2days 1,3,5). In case of CR, two further consolidation courses were performed. The response to treatment was defined by the Cheson criteria.[14]Multiparameterflow cytometry (MFC) was additionally used to verify remission.
2.2. WT1 assessment
WT1 expression was evaluated by QRT-PCR using the standardized European LeukemiaNet (ELN) method9 at baseline, after induction treatment and before allo-HCT. Lymphocytes and monocytes were se-parated based on a density gradient (Ambion, Life Technologies). Total RNA was extracted using Trizol reagent (Invitrogen) or, from 2013, with the Maxwell16 LEV simplyRNA Blood Kit (Promega) on the au-tomated Maxwell16 Instrument (Promega)[18]and retrotranscripted. [19] WT1 expression was measured with a QRT-PCR (WT1 Profile-Quant kit ELN, Qiagen) and WT1 transcripts were normalized to the control gene ABL using the respective plasmid standards to generate normalized copy numbers. All samples were expressed according to the kit handbook formula: (number of WT1 copies/number of ABL copies) x 10.000. Poor quality RNA or problems during the qPCR steps resulted in low ABL copy number. Samples giving ABL copy number < 4246 were discarded according to the manufacturer’s instruction.
2.3. Study endpoints
The study endpoints included: i) proportion of achieved CR after induction; ii) overall survival (OS), calculated both from the date of diagnosis and from the date of CR achievement, until the date of death
for any cause; iii) disease-free survival (DFS), calculated from the date of CR achievement, until the date of relapse or death for any cause. Patients that underwent allo-HCT were censored at the date of trans-plant; iv) cumulative incidence of relapse (CIR), calculated from the date of allo-HCT to the date of relapse, whereas death without relapse was considered as a competing event.
2.4. Statistical analysis
WT1 levels at baseline were summarized as median and inter-quartile range (IQR) and compared according to patient’s character-istics with non-parametric tests. In detail, Mann-Whitney test was used for dichotomous variables, Kruskal-Wallis test for non-ordered rical characteristics, Wilcoxon-type test for trend for ordered catego-rical characteristics and Spearman's rho correlation coefficient for continuous variables. Due to an extremely skewed distribution of va-lues, WT1 was included in the regression models using a natural log-transformation and the linearity of relationship with the study end-points was investigated using restricted cubic spline transformations. The effect of WT1 overexpression on the probability to achieve a CR after induction was investigated through a logistic regression model adjusting for age, gender, clinical risk, leukocytosis at baseline and allo-HCT (for OS analysis only). The effects of post induction WT1 on DFS and OS were investigated. OS and DFS were estimated using the Kaplan-Meier product-limit method and hazard ratios (HR) were esti-mated using multivariable Cox Regression models adjusted for age, gender, percentage of PB blasts after induction, clinical risk and leu-kocytosis at baseline. A cut point of 350 WT1 copies was applied ac-cording to the slope change of mortality hazard. The same cut point was used in the DFS analysis. Additional discrimination ability of WT1 on OS and DFS was evaluated comparing C-Statistics with and without WT1 as covariate. We further calculated the net reclassification index (NRI) to assess the incremental discriminatory ability of WT1 above other risk factors. The NRI estimates were based on the reclassification tables classifying participants in 2-year OS and 1-year DFS risk. According to Cilloni et al,[9]we also investigated the effect of WT1 on OS and DFS on the basis of a 2-log reduction after induction compared with the pretreatment level. The effect of pre allo-HCT WT1 on the CIR of patients that underwent allo-HCT was also analised. CIR was calcu-lated from the date of allo-HCT to the date of relapse or to the date of the last follow-up, considering death without relapse as a competing event. CIR function was estimated by Gooley method[20]and the ef-fect of WT1 was evaluated using a Fine & Gray model.[21]A cut point of 150 was applied according to the slope change of relapse hazard. Statistical analysis was performed using Stata 11·2 (Stata Corp., Tex., USA) and R 3.0.2 (R Foundation for Statistical Computing,http://www. r-project.org/).
3. Results
Patient disposal through the study is shown inFig. 1. Among 281 patients, 223 fulfilled the inclusion criteria, whereas 58 of them were excluded due to lacking baseline WT1 evaluation (N = 26) or baseline WT1≤ 250 copies (N = 32). MRD was investigated with BM WT1 in patients infirst CR with an available WT1 expression level at two time-points: after induction (n = 117) and prior allo-HCT (n = 65). 3.1. Baseline characteristics and treatment response
Baseline demographical, clinical and molecular characteristics of the entire cohort are summarized inTable 1. With a median follow-up of 62 months (range 10–131) the global 3-year OS of the study popu-lation (n = 223) was 41% (95% CI 34–47), with a median survival time of 23 months (95% CI 17–34). No significant difference was observed in OS when eligible patients were compared to non-eligible patients (3-year OS 30%; 95% CI 19–43), p = 0.159 (Fig. 2). Baseline BM WT1
levels were not associated with demographic variables (age and sex), disease features at diagnosis (percentage of PB blasts, leucocytosis and hepatosplenomegaly) and biological AML features (FAB classification, cytogenetic risk and molecular features including FLT3, NPM1, MLL, AML1/ETO and inv16 aberrations). Baseline BM WT1 overexpression lacked even to show an association with induction response: adjusting in a multivariable logistic model for age, gender, global disease risk and leucocytosis, BM WT1 overexpression did not predict CR achievement (OR 1.16 per 1-unit increase on a log-transformed BM WT1; 95% CI 0.90–1.50, p = 0.244). No evidence of a non-linear effect of BM WT1 was found on the probability of CR achievement.
3.2. Association of post induction BM WT1 with OS and DFS
The association of post induction BM WT1 with OS and DFS was investigated in patients in CR after induction (n = 117). According to the slope change of mortality hazard, there was a trend in increased mortality risk once exceeded the cut- off level of 350 copies (corre-sponding to log-WT1 5.86) (Fig. 3A). Therefore, this cut-off level was chosen to evaluate the prognostic impact of WT1 on OS and DFS. With a median follow up of 52 months (range 3–131), median OS was sig-nificantly longer in 96 CR patients with ≤350 BM WT1 copies com-pared to 21 CR patients with > 350 WT1 copies: 95 (95% CI 35-not reached) vs 17 months (95% CI 10–34), respectively, p < 0.001 (Fig. 3B). A multivariable Cox model adjusted for demographic (age, gender) and disease-related variables (clinical risk, baseline leucocy-tosis, allo-HCT) confirmed a higher risk of mortality for CR patients with WT1 > 350 copies (HR 2.13; 95% CI 1.14–3.97, p = 0.018). Other already established risk factors maintained their independent prognostic role: FLT3mut/NPM1 wt mutational status (HR 4.54; 95% CI 1.79–11.51, p = 0.001), increased age (HR 1.13 per 5-year increase; 95% CI 1.00–1.27, p = 0.044), and MCF > 10−3after induction (HR 2.16; 95% CI 1.25–3.74, p = 0.006) were significantly associated with worse survival. The addition of WT1 in the model increased the C-sta-tistic from 0.6996 to 0.7193 and the net percentage of persons correctly reclassified was 38% (NRI = 0.384). The simultaneous analysis of all
255 patients with an available baseline BM WT1 expression (irrespec-tively of value) confirmed our results: median OS was significantly shorter in patients with post induction WT1 > 350 copies compared to those with≤ 350 copies (OS 17 vs 54 months with HR 1.81; 95% CI 0.99–3.30, p = 0.05). Further, CR patients who failed to achieve a 2-log reduction of WT1 level from baseline to post induction (n = 15) showed a trend of increased mortality risk (median OS 18 vs 60 months; adjusted HR 2.00, 95% CI 0.99–4.00, p = 0.052) (Fig. 4A). CR patients with < 350 WT1 copies after induction chemotherapy had a significant longer DFS compared to those with > 350 WT1 copies (3-year DFS rates 55% vs 15%, p < 0.001) (Fig. 3C). These results were confirmed at a multivariate model (HR for relapse 2.81, 95% CI 1.14–6.93, p = 0.025). Increased age (HR 1.28, 95% CI 1.07–1.52, p = 0.006) and female gender (HR 2.61, 95% CI 1.09–6.21, p = 0.030) were also as-sociated with worse DFS. Including the BM WT1 value in the model along with other factors determined an increase of the C-statistic from 0.7413 to 0.7920 and the net percentage of persons correctly re-classified was 40% (NRI = 0.4037). The simultaneous analysis of all
223 evaluable 50 refractory 14 dead 159 CR MRD POST INDUCTION n=117 MRD PRE ALLO-HCT n=65 281 patients 58 excluded
Fig. 1. Consort diagram of the study population. MRD = minimal residual disease. CR = complete remission. Allo-HCT = allogeneic hematopoietic stem cell transplanta-tion.
Table 1
Baseline characteristics of the entire cohort. Percentages do not always add up to 100, because of rounding, but refer to the total number of scored events. N = number. t-AML = therapy-related t-AML. MDS-related t-AML = myelodysplastic syndrome-related AML. Allo-HCT = allogeneic hematopoietic stem cell transplantation. HLA = human leukocyte antigen. MUD = matched unrelated donor. LAIP = leukemia-associated im-munophenotype. ICE = Idarubicin, Cytarabine, Etoposide. FLAG-IDA = Fludarabine, Cytarabine, Idarubicin, Granulocyte colony-stimulating factor.
Variable N. (% or range)
Patients 223
Median age at diagnosis, years 56 (19–76)
Sex, male 136 (61)
Leucocytosis 46 (21)
Organomegaly 47 (21)
t-AML and MDS related-AML 48 (22)
Genomic aberrations (n = 209) Normal karyotype 107 (51) Complex karyotype 25 (12) Monosomy 6 (3) t (9;22) 2 (1) Molecular markers (n = 212) AML/ETO, CBF, inv16 or t(8;21) 31 (15) FLT3 ITD +/− FLT3 TKD 48 (23) NPM1mut 46 (22) MLLmut 23 (11) Induction regimen (n = 223) ICE 188 (84) FLAG-IDA 35 (16) Induction response (n = 223) Complete remission 159 (71) Refractory 50 (22) Dead 14 (7) Allo-HCT 106 (48)
Status pre allo-HCT (n = 106)
First CR 71 (67) Second CR 21 (20) First relapse 11 (10) Disease persistence 3 (3) Type of donor (n = 106) HLA-identical sibling 38 (36) MUD 52 (49) Haploidentical 15 (14) Cord 1 (1) Baseline LAIP (n = 223) 146 (65) Baseline median WT1 (n = 223) 10411 (270–83200)
patients with an available baseline WT1 (255 out of 281 patients) also confirmed the results we observed for DFS: patients with post induction WT1 > 350 copies had a significantly shorter survival than those with ≤350 copies (3-year DFS 15% vs 55% with HR of 2.7; 95% CI 1.09–6.51, p = 0.03). No significant differences in relapse risk were found dividing patients according to logarithmic WT1 reduction from baseline to post induction WT1 (patients who failed to achieve a 2-log WT1 reduction had an adjusted HR of 1.23; 95% CI 0.46–3.30, p = 0.677) (Fig. 4B).
3.3. The role of allogeneic transplant
A total of 106 patients underwent an allo-HCT (Table 1). In order to avoid background inhomogeneity, only patients in first CR with an available BM WT1 expression pre allo-HCT (n = 65) were included in the analysis. A cut point of 150 WT1 copies was applied according to the slope change of relapse hazard and was subsequently used for CIR analysis (Fig. 5A). This cut point showed a significant discriminant value in terms of relapse: patients displaying a pre allo-HCT BM WT1 level > 150 copies (n = 18) had a significantly higher CIR (2-year CIR 51%, 95% CI 26–76) compared to patients with a BM WT1 of ≤150 copies (n = 47), 2-year CIR 22% (95% CI 8–36), p = 0.003 (Fig. 5B). Pre allo-HCT BM WT1 remained a significant independent risk factor for CIR (HR 4.61; 95% CI 1.72–12.31, p = 0.002) in a multivariable model adjusted for patient/donor relationship, presence of GVHD and global disease risk. Considering all 255 evaluable patients irrespectively of baseline WT1 value, those with pre allo-HCT WT1 > 150 copies (n = 76) had a significantly higher CIR compared to those with ≤ 150 copies (HR 3.41 at 2-year; 95% CI 1.33–8.73, p = 0.011).
4. Discussion
The results of our study showed that BM WT1 overexpression is associated with survival in AML patients in CR after induction and before allo-HCT. Conversely, baseline WT1 levels are not associated with induction response. Absolute WT1 cut-offs were used to divide patients in groups with different OS, DFS and CIR; the statistically significant independence of WT1 overexpression demonstrated its role as outcome predictor. The cut-off level of 350 BM WT1 copies after induction treatment and 150 BM WT1 copies pre allo-HCT allowed the
identification of subgroups of patients with more favorable outcome. To further explore the strength of our cut-off, we performed an additional analysis in the entire cohort of CR patients with an available baseline WT1 value (irrespectively from its level) confirming the strong pre-dicting role of both WT1 cut-off identified. Compared to other methods, [9,10]an absolute WT1 cut-off seems to be a simpler and better tool. WT1 overexpression appears an appealing marker for AML monitoring since it is overexpressed in the majority of AML, promoting cells pro-liferation, differentiation and inhibition of apoptosis.[8]Furthermore, the adoption of WT1 for MRD monitoring is encouraged by the tech-nique: QRT-PCR methods are very sensitive, rapid and well standar-dized. The results of our study may suggest the potential use of a MRD-oriented approach to plan post-remission risk-adapted therapy, in-cluding therapy intensification for patients in CR but at high risk of relapse according to the MRD status. Published evidences support these suggestions.[9–13,22]However, especially due to methodological is-sues and small sample size of most studies, the role of WT1 driven MRD in AML is still a matter of debate. In particular, the kinetic of the marker, the cut-off values and the time-points are controversial. Starting from the value of 250 BM WT1 copies/104 ABL copies in-dividuated on the behalf of ELNetwork9, subsequent studies found different clinically relevant thresholds. Nomdedeu et al12individuated three risk groups based on BM WT1 after induction chemotherapy. Ostergaard et al13founded a correlation in the logarithmic reduction of WT1 between baseline and post induction, although Mossallam et al [23]did not confirm these findings. ABL is the most commonly used control gene, however other authors studied different genes, including b-glucuronidase (GUS)[10]and the TATA box binding protein gene transcripts. Due to the absence of a consensus, efforts are necessary to establish the clinically relevant threshold and to determine the optimal time-point for WT1 assessment. Besides post induction, another decisive time-point for treatment planning is the pre allo-HCT evaluation. In our cohort, a discriminating pre transplant level > 150 BM WT1 copies was independently associated with relapse risk and survival. This cut-off is different from that identified after induction, and an explanation may rely on the fact that the patients have undergone more chemotherapy before allo-HCT than after first induction. Based on the prognostic significance of MRD positivity before transplant, a pre allo-HCT therapy intensification, a change of conditioning regimen or a different man-agement of immunosuppressive drugs may have a role in the Fig. 2. Global OS of the entire population. Eligible patients (n = 223) showed a 3-year OS of 41% compared to 30% of non-eligible patients (n = 58), p = 0.159. OS = overall survival.
improvement of disease control and survival. The role of WT1 over-expression in the pre transplant setting has been studied less extensively yielding controversial results. [24,25] Therefore, WT1-driven MRD strategies have not yet been incorporated into standard AML
management, mainly due to the absence of randomized trials sup-porting a clinical benefit MRD-tailored treatments, challenges in tech-niques standardization, in cut-off values, in not defined time-points (early assessment, [26] after induction, [9,12] after intensification, Fig. 3. Association of post induction WT1 with response, OS and DFS. A. Restricted cubic spline transformation to test the association between post induction WT1 and OS in CR patients after induction (n = 117). A trend of increased mortality risk was observed when the cut-off level of 350 WT1 copies was exceeded (corresponding to log_WT1 5.86). Post induction CR patients with a WT1 level≤350 showed a significant better OS (B) and DFS (C) compared to CR patients with > 350 WT1 copies (p < 0.001 for OS and p < 0.001 for DFS), Kaplan-Meier estimate. l_WT1 = logarithmic scale of WT1. OS = overall survival. DFS = disease free survival. CR = complete remission.
[12] or any time after HCT [27,28]) or samples types (BM or PB [24,29,30]). Ongoing researches are focused on addressing these lim-itations and new insights in the molecular network of AML prompt MRD monitoring to the forefront of AML treatment. Based to our re-sults, with the limitation of the retrospective nature of the present study, we can conclude that WT1 overexpression may represent an additional MRD tool for the stratification of the risk of AML patients nowadays classified in complete remission. To the best of our knowl-edge, this is one of the largest study addressing the role of WT1 over-expression in CR patients. Prospective randomized studies are required to identify, among CR patients, those with MRD positivity in which a
risk-adapted approach may have a role.
Authors' contributions
C.F., S.A., F.M. designed the research. C.F., S.A., E.A., L.R., S.A., B.A., A.B., S.D., C.M.D., A.D., P.F., B.N., A.S., F.M. collected data. C.F., S.A., A.E., G.C., F.M, U.V. analyzed data. C.F., S.A., U.V. wrote the paper. All authors have read and approved the manuscript and agree with submission to The Lancet Haematology.
Fig. 4. Association between 2-log WT1 reduction (from baseline to post induction) and survival. A: mortality risk according to 2-log reduction of WT1 (adjusted HR 2.00, 95% CI 0.99–4.00, p = 0.052). B: relapse risk according to 2-log reduction of WT1 (adjusted HR 1.23, 95% CI 0.46–3.30, p = 0.677).
Role of funding source
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Ethics committee approval
The study was approved by the Ethical Committee and was con-ducted in accordance with the Declaration of Helsinki and the guide-lines for Good Clinical Practice. The study was registered at www.cli-nicaltrials.gov as NCT02714790.
Conflict of interest
The authors declare no conflict of interest.
Acknowledgements
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
References
[1] J.M. Goldman, R.P. Gale, What does MRD in leukemia really mean? Leukemia 28 (5) (2014) 1131.
[2] D. Grimwade, P. Vyas, S. Freeman, Assessment of minimal residual disease in acute myeloid leukemia, Curr. Opin. Oncol. 22 (6) (2010) 656–663.
[3] F. Buccisano, L. Maurillo, M.I. Del Principe, et al., Prognostic and therapeutic im-plications of minimal residual disease detection in acute myeloid leukemia, Blood 119 (2) (2012) 332–341.
[4] V.H. van der Velden, A. Hochhaus, G. Cazzaniga, T. Szczepanski, J. Gabert, J.J. van Dongen, Detection of minimal residual disease in hematologic malignancies by real-time quantitative PCR: principles, approaches, and laboratory aspects, Leukemia 17 (6) (2003) 1013–1034.
[5] A. Corbacioglu, C. Scholl, R.F. Schlenk, et al., Prognostic impact of minimal residual Fig. 5. Association between pre allo-HCT WT1 and outcome. A: Restricted cubic spline in patients infirst CR with an available pre allo-HCT BM WT1 (n = 65). A trend of increased CIR was observed when the cut-off level of 150 WT1 copies was ex-ceeded (corresponding to log_WT1 5.01). B: Patients with a pre allo-HCT WT1 > 150 copies had a higher CIR than patients with ≤150, p = 0.003. CIR = cumulative incidence of relapse.
disease in CBFB-MYH11-positive acute myeloid leukemia, J. Clin. Oncol. 28 (23) (2010) 3724–3729.
[6] P. Gorello, G. Cazzaniga, F. Alberti, et al., Quantitative assessment of minimal re-sidual disease in acute myeloid leukemia carrying nucleophosmin (NPM1) gene mutations, Leukemia 20 (6) (2006) 1103–1108.
[7] D. Steinbach, A. Schramm, A. Eggert, et al., Identification of a set of seven genes for the monitoring of minimal residual disease in pediatric acute myeloid leukemia, Clin. Cancer Res. 12 (8) (2006) 2434–2441.
[8] D. Cilloni, E. Gottardi, D. De Micheli, et al., Quantitative assessment of WT1 ex-pression by real time quantitative PCR may be a useful tool for monitoring minimal residual disease in acute leukemia patients, Leukemia 16 (10) (2002) 2115–2121. [9] D. Cilloni, A. Renneville, F. Hermitte, et al., Real-time quantitative polymerase
chain reaction detection of minimal residual disease by standardized WT1 assay to enhance risk stratification in acute myeloid leukemia: a European LeukemiaNet study, J. Clin. Oncol. 27 (31) (2009) 5195–5201.
[10] E. Barragan, J. Cervera, P. Bolufer, et al., Prognostic implications of Wilms' tumor gene (WT1) expression in patients with de novo acute myeloid leukemia, Haematologica 89 (8) (2004) 926–933.
[11] M.M. Hamalainen, V. Kairisto, V. Juvonen, et al., Wilms tumour gene 1 over-expression in bone marrow as a marker for minimal residual disease in acute myeloid leukaemia, Eur. J. Haematol. 80 (3) (2008) 201–207.
[12] J.F. Nomdedeu, M. Hoyos, M. Carricondo, et al., Bone marrow WT1 levels at di-agnosis: post-induction and post-intensification in adult de novo AML, Leukemia 27 (11) (2013) 2157–2164.
[13] M. Ostergaard, L.H. Olesen, H. Hasle, E. Kjeldsen, P. Hokland, WT1 gene expres-sion: an excellent tool for monitoring minimal residual disease in 70% of acute myeloid leukaemia patients— results from a single-centre study, Br. J. Haematol. 125 (5) (2004) 590–600.
[14] B.D. Cheson, J.M. Bennett, K.J. Kopecky, et al., Revised recommendations of the international working group for diagnosis: standardization of response criteria, treatment outcomes, and reporting standards for therapeutic trials in acute myeloid leukemia, J. Clin. Oncol. 21 (24) (2003) 4642–4649.
[15] R. Bassan, T. Barbui, Remission induction therapy for adults with acute myelo-genous leukemia: towards the ICE age? Haematologica 80 (1) (1995) 82–90. [16] H. Dohner, E.H. Estey, S. Amadori, et al., Diagnosis and management of acute
myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet, Blood 115 (3) (2010) 453–474. [17] J.E. Parker, A. Pagliuca, A. Mijovic, et al., Fludarabine: cytarabine, G-CSF and
idarubicin (FLAG-IDA) for the treatment of poor-risk myelodysplastic syndromes and acute myeloid leukaemia, Br. J. Haematol. 99 (4) (1997) 939–944. [18] L. Riera, F. Sismondi, B. Nuschak, et al., High-Quality RNA from Peripheral Blood
and Bone Marrow Samples After Automated Extraction on a Maxwell®16 Instrument Article, (2013) (accessed), http://ita.promega.com/resources/pubhub/high-
quality-rna-from-blood-and-bone-marrow-after-automated-extraction-on-maxwell16-instrument/.
19] J.J. van Dongen, E.A. Macintyre, J.A. Gabert, et al., Standardized RT-PCR analysis of fusion gene transcripts from chromosome aberrations in acute leukemia for detection of minimal residual disease. Report of the BIOMED-1 concerted action: investigation of minimal residual disease in acute leukemia, Leukemia 13 (12) (1999) 1901–1928. [20] T.A. Gooley, W. Leisenring, J. Crowley, B.E. Storer, Estimation of failure
prob-abilities in the presence of competing risks: new representations of old estimators, Stat. Med. 18 (6) (1999) 695–706.
[21] J. Fine, R. Gray, A proportional hazards model for the subdistribution of a com-peting risk, J. Am. Stat. Assoc. 94 (446) (1999) 496–497.
[22] A. Nowakowska-Kopera, T. Sacha, I. Florek, M. Zawada, S. Czekalska, A.B. Skotnicki, Wilms' tumor gene 1 expression analysis by real-time quantitative polymerase chain reaction for monitoring of minimal residual disease in acute leukemia, Leuk. Lymphoma 50 (8) (2009) 1326–1332.
[23] G.I. Mossallam, T.M. Abdel Hamid, H.K. Mahmoud, Prognostic significance of WT1 expression at diagnosis and end of induction in Egyptian adult acute myeloid leu-kemia patients, Hematology 18 (2) (2013) 69–73.
[24] V. Valkova, J. Polak, M. Markova, et al., Minimal residual disease detectable by quantitative assessment of WT1 gene before allogeneic stem cell transplantation in patients infirst remission of acute myeloid leukemia has an impact on their future prognosis, Clin. Transplant. 27 (1) (2013) E21–E29.
[25] G. Rossi, A.M. Carella, M.M. Minervini, et al., Optimal time-points for minimal residual disease monitoring change on the basis of the method used in patients with acute myeloid leukemia who underwent allogeneic stem cell transplantation: a comparison between multiparameterflow cytometry and Wilms' tumor 1 expres-sion, Leuk. Res. 39 (2) (2015) 138–143.
[26] G. Gianfaldoni, F. Mannelli, V. Ponziani, et al., Early reduction of WT1 transcripts during induction chemotherapy predicts for longer disease free and overall survival in acute myeloid leukemia, Haematologica 95 (5) (2010) 833–836.
[27] S. Pozzi, S. Geroldi, E. Tedone, et al., Leukaemia relapse after allogeneic transplants for acute myeloid leukaemia: predictive role of WT1 expression, Br. J. Haematol. 160 (4) (2013) 503–509.
[28] A. Candoni, E. Toffoletti, R. Gallina, et al., Monitoring of minimal residual disease by quantitative WT1 gene expression following reduced intensity conditioning al-logeneic stem cell transplantation in acute myeloid leukemia, Clin. Transplant. 25 (2) (2011) 308–316.
[29] M. Malagola, C. Skert, G. Ruggeri, et al., Peripheral blood WT1 expression predicts relapse in AML patients undergoing allogeneic stem cell transplantation, BioMed Res. Int. 2014 (2014) 123079.
[30] J. Polak, H. Hajkova, C. Haskovec, et al., Quantitative monitoring of WT1 expres-sion in peripheral blood before and after allogeneic stem cell transplantation for acute myeloid leukemia— a useful tool for early detection of minimal residual disease, Neoplasma 60 (1) (2013) 74–82.
