A Leukemia-Associated CD34/CD123/CD25/CD99-Positive Immunophenotype Identifies FLT3-Mutated Clones in Acute Myeloid Leukemia

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Author Manuscript Published OnlineFirst on May 8, 2015; DOI: 10.1158/1078-0432.CCR-14-3186 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

A Leukemia-Associated CD34/CD123/CD25/CD99-positive Immunophenotype Identifies FLT3-mutated Clones in Acute Myeloid Leukemia

Daniela F. Angelini1*, Tiziana Ottone,2-3* Gisella Guerrera,1 Serena Lavorgna,2-3 Michela Cittadini,2-3 Francesco Buccisano,2 Marco De Bardi,1 Francesca Gargano,1 Luca Maurillo,2 Mariadomenica Divona,2 Nélida I. Noguera,3-4 Maria Irno Consalvo2, Giovanna Borsellino,1 Giorgio Bernardi,5 Sergio Amadori,2 Adriano Venditti,2 Luca Battistini,1 and Francesco Lo-Coco 2-3

1 Neuroimmunology and Flow Cytometry Units, Fondazione Santa Lucia-I.R.C.C.S., Rome, Italy. 2 Department of Biomedicine and Prevention, University of Tor Vergata, Rome, Italy.

3 Laboratorio di Neuro-Oncoematologia, Fondazione Santa Lucia I.R.C.C.S, Rome, Italy.

4 Department of Chemical Biochemistry (Hematology), National University of Rosario, Argentina. 5 Experimental Neuroscience, Fondazione Santa Lucia, I.R.C.C.S., 00179 Rome,Italy.

*D.F.A. and T.O. Contributed equally to this study

Running title: Immunophenotype of FLT3-ITD mutated cells

Keywords: Acute Myeloid Leukemia, Multiparametric Flow Cytometry, FLT3-ITD, Leukemia Associated Immunophenotype, Minimal Residual Disease,

Financial support: This study was partially supported by the Associazione Italiana per la

Ricerca sul Cancro (IG 11586) to F.L.C. and Associazione Italiana contro le Leucemie (AIL).

Corresponder author: Francesco Lo-Coco, M.D.

Department of Biomedicine and Prevention,

University Tor Vergata, Via Montpellier 1, 00133 Rome, Italy

[email protected]

Conflict of interest: The authors declare no conflict of interest

Word count: 3933 Total number of figure: 6

Downloaded from clincancerres.aacrjournals.org on September 27, 2021. © 2015 American Association for Cancer Research. Author Manuscript Published OnlineFirst on May 8, 2015; DOI: 10.1158/1078-0432.CCR-14-3186 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Statement of Translational Relevance

While it is well established that FLT3 mutations confer poor prognosis in AML, the significance of minor clones harboring this alteration is unclear. Furthermore, such clones are not easily detectable through molecular assays. We show here that minor FLT3-ITD positive subclones are clinically relevant in AML as they may emerge after therapy in patients labelled as FLT3 wild type at presentation. Identification through multiparametric flow cytometry at diagnosis of an immunophenotypic fingerprint associated with these subclones is a novel and simplified tool with improved sensitivity to unravel these clones and allowing patient stratification and risk- adapted treatment with potential impact on outcome of the disease.

Abstract:

Purpose We evaluated leukemia-associated immunophenotypes (LAIP) and their correlation with fms-like tyrosine kinase 3 (FLT3) and nucleophosmin (NPM1) gene mutational status in order to contribute a better identification of patients at highest risk of relapse in AML.

Experimental Design: Bone marrow samples from 132 patients with acute myeloid leukemia (AML) were analyzed by 9-color multiparametric flow cytometry (MPFC). We confirmed the presence of the mutation in diagnostic samples and in sorted cells by conventional

RT-PCR and by patient-specific RQ-PCR.

Results: Within the CD34+ve cell fraction we identified a discrete population expressing high levels of the IL-3 receptor alpha-chain (CD123) and MIC-2 (CD99) in combination with the

IL-2 receptor alpha-chain (CD25). The presence of this population positively correlated with the internal tandem duplications (ITD) mutation in the FLT3 gene (r = 0.71). Receiver operating characteristics (ROC) showed that, within the CD34+ve cell fraction a percentage of

CD123/CD99/CD25+ve cells ≥ 11.7% predicted FLT3–ITD mutations with a specificity and sensitivity of >90%. CD34/CD123/CD99/CD25+ve clones were also detectable at presentation in 3 patients with FLT3 wild-type/NPM1+ve AML who relapsed with FLT3-ITD/NPM1+ve

AML. Quantitative real-time PCR designed at relapse for each FLT3-ITD in these three cases confirmed the presence of low copy numbers of the mutation in diagnostic samples.

Conclusion: Our results suggest that the CD34/25/123/99+ve LAIP is strictly associated with FLT3-ITD positive cells.

Introduction

Immunophenotyping by Multiparametric Flow Cytometry (MPFC) is a valuable and effective tool for diagnostic characterization, classification and minimal residual disease (MRD) monitoring in acute myeloid leukemia (AML). In fact, several studies have defined surface and cytoplasmic markers that are aberrantly expressed on AML blasts at diagnosis (1, 2); these combinations may identify leukemia-associated immunophenotypes (LAIPs) which allow sensitive monitoring of MRD during follow-up (3-5). Compared to molecular evaluation of

MRD through PCR amplification of genetic AML lesions, MPFC offers the advantage of being applicable to the vast majority (i.e. >90%) of cases (6, 7).

In addition to immunophenotype, both karyotypic and molecular genetic characterization are essential parts of the diagnostic work-up in AML. Although in some cases immunophenotypic profiles have been correlated with AML genetic subsets, to date no antigenic signature has been associated with an AML genetic entity with absolute specificity. For instance, expression of CD14, CD4, CD11b and CD64 or CD36 (markers of monocytic and granulocytic differentiation) combined with high levels of CD34 and CD117 and abnormal expression of CD2 characterizes - but is not specific for - AML inv (16) or t(16;16)(8). Similarly, acute promyelocytic leukemia (APL) with t(15;17) is characterized by very low or absent expression of CD34 and HLA-DR, and positivity for CD117/CD33; however, this antigenic profile is not completely specific for APL and some variant LAIPs have been described (9-11).

Several studies have reported correlations of aberrantly expressed markers with clinical outcome in AML. For example, CD7 and CD25 expression has been associated with poor prognosis in normal karyotype (NK) AML (12-14). The IL3 receptoralfa (CD123) is overexpressed in 45% of AML patients, and this higher expression has also been associated with poor outcome (15). Finally, overexpression of CD123 has been correlated in this setting with mutations in the fms-like tyrosine kinase receptor (FLT3) gene (16).

A consistent antigenic profile with high CD33 expression has also been associated with

AML with mutated nucleophosmin (NPM1) (17, 18). Patients with NPM1 mutated AML have favourable prognosis except when this gene alteration is accompanied by FLT3 lesions and in particular by internal tandem duplications (FLT3-ITD), which are universally regarded as predictor of a poor outcome (19-22).

Screening by PCR for FLT3-ITD at diagnosis is relevant for risk stratification of AML patients, however this technique is neither sufficiently sensitive nor it may be routinely applied to MRD monitoring due to the instability of this alteration and its inter-patient variability. Recent studies suggest that FLT3-ITD AML relapse may occasionally originate from very small subclones, which are undetectable at diagnosis by routine screening (23). We have previously developed a patient-specific real-time quantitative PCR to implement FLT3-ITD detection at time of relapse (24), but this approach is unfortunately not applicable at diagnosis to unravel minor FLT3-ITD subclones. Through this assay we analysed paired diagnostic and relapse samples in AML patients who had showed FLT3-ITD only at relapse by conventional RT-PCR.

We found that small FLT3-ITD clones which were chemoresistant and eventually gave origin to disease relapse were already present at diagnosis in these patients (24). These findings highlight

the need of improving diagnostic identification in AML of small number of cells harboring

genetic lesions associated with poor prognosis.

In the present study we sought to investigate whether 9-color MPFC could be helpful to

to detect minor subclones potentially associated with resistance and disease recurrence in AML.

We combined typical markers of early myeloid progenitors including CD34, CD117, CD38, with

markers associated with FLT3 mutations, such as CD123, CD25, and CD7. This approach

allowed us to identify a subset of CD34+ve cells whose presence is highly predictive of the

FLT3 mutations in AML.

Materials and Methods

Patients

A total of 132 consecutive patients aged 19-85 years with newly diagnosed AML

observed and treated at the Hematology Unit of the Department of Biomedicine and Prevention

of the University of Tor Vergata during the period 2012-2014 were included in the study. The

vast majority of patients aged <75 received intensive chemotherapy according to European

Organization of Research and Treatment of Cancer (EORTC)/Gruppo Italiano Malattie

EMatologiche dell’Adulto (GIMEMA) protocols, while patients aged >75 years received

supportive care or therapy with hypomethylating agents. According to the declaration of

Helsinki, all patients gave informed consent for the study which was approved by the

Institutional Review Board of the Policlinico Tor Vergata of Rome.

Diagnostic work-up

Routine morphologic, immunophenotypic and genetic analyses were carried out in all cases at presentation. Conventional karyotyping was performed on bone marrow diagnostic aspirates after short-term culture and analyzed after G-banding. The description of the karyotypes was done according to the International System for Human Cytogenetic

Nomenclature. As for molecular analysis, total RNA was extracted from Ficoll-Hypaque isolated bone marrow (BM) mononuclear cells collected at diagnosis and for selected cases, during follow-up using standard procedures (25) and reverse-transcribed with random hexamers as primers. DNA was extracted using a column based Qiagen kit protocol (Qiagen, Hilden,

Germany). RNA samples extracted from sorted cells population were subjected to reverse- transcription using 200 ng of RNA with the SuperScript III One-Step RT-PCR system

(Invitrogen, Carlsbad, CA) according to the manufacturer’s instructions. Most common AML gene fusions, FLT3 status (both ITD and TKD mutations) and NPM1 mutated (mut) or wild-type

(wt) gene status were investigated using the protocols reported elsewhere (19, 26, 27). For selected patients, the FLT3-ITD data is also represented as a ratio of mutant/wild-type cells obtained by a quantitative assay based on Genescan analysis (19). This assay compares the relative abundance of wt versus mutant FLT3 alleles.

MPFC studies and high speed cell sorting

Immunophenotypic studies were performed on bone marrow samples at diagnosis and, for selected cases, in samples obtained during follow-up and at disease relapse. Cells were acquired on a CyAn ADP 9 Color equipped with three lasers (Beckman Coulter, Brea, CA).

Briefly, bone marrow samples were lysed with ammonium chloride (pH 7.2) and stained with pre-defined optimal concentrations of 8 antibodies and a dead cell stain dye (LIVE/DEAD

Fixable Aqua Dead Cell Stain Kit, Life Technologies, Carlsbad, CA). Each sample at diagnosis was stained with 10 distinct antibody combinations (“pre-mixes”); the markers CD45, CD34,

CD117 and HLA-DR represented the “backbone” and were present in all combinations, in addition to a viability stain. The remaining 4 markers were different in each mix. The number of events acquired for each leukemic sample was determined as to have at least 500 events accumulated in the gate of CD34 positive cells. Events analyzed undergo further back gating analysis (CD45 vs side scatter) and exclusion of doublets and dead cells. Following acquisition and analysis of the samples stained with the 10 pre-mixes, new antibody combinations were designed on the spot to include all markers expressed by the leukemic cells, thus each sample was studied specifically using custom-designed panels. Data were analysed using FlowJo software (TreeStar Inc. Ashland, USA).

High-speed cell sorting was performed on a Moflo (Beckman Coulter). Cells were isolated by Ficoll-Hypaque to prevent granulocytic contamination, and then stained as previously described. The antibodies used are listed in the Supplementary Table 1.

FLT3-ITD patient-specific quantitative analysis by RQ-PCR

For FLT3-ITD quantification, we developed patient-specific real time assays (RQ-PCR).

The strategy for FLT3-ITD patient-specific primers designing is reported elsewhere (24). On the basis of clinical outcome, molecular and immunophenotypic results, 4 AML patients (UPN 104,

146, 213 and 241) were selected for further analysis by RQ-PCR for the patient-specific FLT3-

ITD analysis using several follow-up RNA samples. UPN 104 and 146 were characterized by two FLT3-ITDs clones, while UPN 213 and 241 by only one FLT3-ITD clone. The assays were designed to evaluate the copy number variation among different clones carrying FLT3-ITDs. The

RQ-PCR for FLT3-ITD quantification was performed using patient-specific FLT3-ITD forward

primers (FLT3-ITDs genomic coordinates and primer sequences are available on request) a

common reverse primer and probe (FLT3-ITD_reverse 5’-

AGACTCCTGTTTTGCTAATTCCATA-3’, FLT3-ITD_Probe 5’-FAM

AAGGTACTAGGATCAGGTGCTTTTGGAA-3’-BHQ1). The reaction mixture of 25 µl

contained 1×Master Mix (Applied Biosystems, Foster City, CA), 300 nM of each primer, 200

nM of Taqman probe and 5 µl of cDNA (1/10 of RT product). Ampliﬁcation conditions were: 2 min at 50°C, 10 min at 95°C followed by 60 cycles at 95°C for 15 s and at 60°C for 1 min for

UPN 146, 213 and 241 and 62°C for UPN 104. A threshold value of 0.2 was used and baseline was set to 3–15. Patient-specific FLT3-ITDs sensitivity and specificity tests were carried out for each patient with serial water dilutions of RNA and with RNA from healthy donors.

Statistical analysis

Differences between categorical variables were evaluated by Pearson's chi-squared test while differences between continuous variables were analyzed by unpaired t –test with 95% confidence intervals. Positive correlations between categorical and quantitative variables were analysed by Spearman's rank correlation coefficient. Receiver Operating Characteristic (ROC) analysis was performed with MedCalc statistical software (Ostend Belgium). The standard error was calculated using DeLong et al. (1988). The Confidence Interval for the AUC was calculated using Binomial exact confidence interval.

Results

FLT3 and NPM1 mutational status of patients at diagnosis

Out of 132 tested patients, 36 harboured in their leukemic cells the FLT3-ITD mutations

and 48 NPM1 mutations. Considering the status of both genes, 9 patients tested FLT3-

ITD/NPM1-wt, 21 FLT3-ITDneg/NPM1-mut, 27 FLT3-ITD/NPM1-mut, and 75 FLT3-

ITDneg/NPM1-wt. Karyotypic data were available for 70% of patients. The main demographic characteristics and karyotype of patients according to NPM1/FLT3 gene status are reported in

Supplementary Table 2.

MPFC analysis in total bone marrow and in the CD34+ve compartment

As shown in Supplementary Table 3, MPFC studies in the total bone marrow revealed a statistically significant difference in the expression of CD123, CD25, CD99, CD7 and CD11b between FLT3-ITD and FLT3-ITDneg patients (p = 0.02; p = 0.000006; p = 0.03; p = 0.02; p =

0.005 respectively). The fraction of CD34+ve cells was significantly lower in patients with

NPM1-mut, compared to patients who did not carry the mutation (Figure 1A upper panel and

Supplementary table 4); accordingly, the bulk of the leukemic cell population in NPM1-mut patients was CD34-ve/CD117+ve (Figure 1A lower panel). In addition, CD34+ve cells derived from the FLT3 and NPM1 mutated group expressed the lowest levels of CD38 (Figure 1B).

When focusing the analysis on CD34+ve cells, FLT3-ITD patients expressed CD123,

CD25 and CD99 at significantly higher levels compared to patients with FLT3-ITDneg, regardless of NPM1 gene status (Supplementary table 4 and Figure 1B). Expression of CD11b and CD7 was higher in samples with both mutations, but did not discriminate this group from the other genetic subsets. Thus, we investigated whether these three markers (CD123, CD25, CD99)

were co-expressed by the same cells. Figure 1C, shows MPFC analysis of bone marrow samples

from patients with different NPM1/FLT3 gene status. Cumulative data of the percentage of

CD34+ve cells which stained positive for CD25, CD123, and CD99 simultaneously showed that

this antigen combination is very rarely observed or barely detectable in patients with FLT3-

ITDneg (Figure 1C-D). While positivity for each marker measured separately was not sufficient

to unequivocally discriminate between FLT3-ITD and FLT3-ITDneg patients, the combination of all three markers simultaneously reduced the variance within the group of FLT3-ITDneg patients. We then screened all patients for the presence or absence of FLT3-TKD, and we identified 8 cases harboring this mutation in diagnostic bone marrow samples, 5 of which were in the NPM1wt group, while 3 carried also a mutation in NPM1. As shown in figure 1D (red circles), only one case presented with a significant fraction of CD34/CD123/CD25/CD99+ve

cells. It should be noted, however, that this patient also had a mutated karyotype. Interestingly,

also the 2 patients without identifiable FLT3 mutations and with the LAIP had mutated

karyotype and were sent to allogeneic stem cell transplantation (SCT).

Figure 1D also shows that 3 patients with FLT3-ITD and NPM1 wt, presented a low

percentage of CD34/CD123/CD25/CD99+ve cells. All these 3 patients had mutated karyotype at

diagnosis and underwent allogeneic SCT.

Five bone marrow samples from healthy subjects were also analyzed for the presence of

CD34/CD123/CD25/CD99+ve cells. Figure 2 shows a representative MPFC analysis and

cumulative data of CD34+ve cells derived from healthy donors as compared to an FLT3-ITD

positive AML patient. This combination of markers is present in healthy individuals at a rate

ranging from 0.3% to 4% of CD34+ve cells.

Receiver operating characteristic (ROC curve)

We found a strong positive correlation (r = 0.7136; p<0.0001) between the percentage of

CD123/CD99/CD25+ve population within CD34+ve cells and the presence of the FLT3-ITD

mutation, as evaluated in 132 AML bone marrow samples by conventional RT-PCR (Figure 3A).

Receiver operating characteristic (ROC) curve analysis identified the value > 11.7% of

CD34/CD123/CD99/CD25+ve cells within the total CD34+ve fraction as the best determinant

for predicting the presence of FLT3-ITD mutation with a specificity and sensitivity of >90%.

The area under the ROC curve (AUC) was calculated to be 0.96 with 95% confidence interval

ranging from 0.91 to 0.99 and significance level of p < 0.0001 (Figure 3B). The positive and

negative predictive value calculated using 11.7% as threshold were 84.3931% and 96.1488%

respectively (Sensitivity = 90%; Specificity = 93.75; Disease prevalence = 27.3).

To note, the fraction of CD123/CD99/CD25+ve cells within CD34+ve cells is significantly higher in the group with mutations in both FLT3 and NPM1, as compared to samples which only have the mutation in FLT3 (Figure 1D).

The ROC analysis generated using only the markers CD123 and CD25 showed similar results, but with a sensitivity and specificity lower than that calculated with also CD99 (Supplementary

Figure 1)

With respect to conventional RT-PCR, MPFC analysis proved to be superior in the ability to detect the FLT3-ITD mutation in subclones. Indeed, blasts from 3 patients (UPN 241, 213 and

104) who underwent FLT3-ITD AML relapse had been labelled as FLT3-wt by conventional RT-

PCR at the time of diagnosis. These patients showed at presentation a significant number of

CD123/CD99/CD25+ve cells within the CD34+ve population: 13%, 11.8% and 20.7% respectively (Supplementary Figure 2A, red circles). Patient-specific RQ-PCR with primers designed at relapse unveiled low copy numbers of FLT3-ITD in all 3 cases using diagnostic samples. Supplementary Figure 2B shows that when the percentage of the

CD34/CD123/CD25/CD99+ve cell subset on total sample was lower than 0.1%, conventional

RT-PCR failed to detect the FLT3-ITD subclone.

Purified CD34/CD123/CD99/CD25+ve cells carry the FLT3-ITD mutation

Based on the availability of samples, we proceeded to investigate the mutational profiles of cell-sorted subfractions within the CD34+ population. We identified two patients harbouring

FLT3-ITD (UPN 118 and 146) in whom MPFC had revealed 64% and 36% of

CD123/CD99/CD25+ve within CD34+ve cells (1.7% and 1.9% of the total sample). Cells from

both patients were purified by cell sorting according to CD34, CD117, CD123, CD99, CD25,

CD7 and CD38 expression (Figure 4), at diagnosis.

The isolated subfractions showed an enrichment of the mutated allele within the cell population

expressing the markers we have identified as LAIP for the FLT3-ITD mutation: in both patients,

the CD34+ve, CD117+/-, CD38low, CD25+ve, CD123+ve, CD99+ve CD7+/- fraction was

highly enriched in cells carrying the mutation, with a FLT3 ratio of 21,67 in one patient and of

8,46 in the other (Figure 4, subset 1). In patient UPN 118 we identified a second subpopulation of cells expressing high levels of CD38 and which contained a heterogeneous cell population with a FLT3 ratio similar to the whole MNC (value = 2.04). The ratio is an indirect quantify of the number of FLT3-ITD positive and negative cells. In particular Thiede et al. (19) found that a high FLT3-ITD allelic burden confers a poor prognosis for AML patients.

Within the CD34+ cells of patient UPN 146 we could identify and isolate to purity another two subpopulations: one containing CD117+CD123+CD99-CD25-CD7+/-CD38+ cells, mostly

harboring FLT3 wt (subset 2), and the other (subset 3) characterized by expression of CD99 and

negativity for CD38 which on the contrary was highly enriched in mutated FLT3 (ratio 7.18).

By patient-specific RQ-PCR, we could define the copy number of FLT3-ITDs clones in the three

phenotypic subsets, which is reported in Supplementary Table 5.

These results confirm that cells carrying the FLT3-ITD mutation are contained within distinct

subfractions of the CD34+ cell population and can be enriched based on the expression of

surface markers.

Sequential immunophenotypic and RQ-PCR monitoring studies through patient-specific

FLT3-ITD

Four patients (UPN 241, 213, 146 and 104) were followed longitudinally through post-

induction, post-consolidation therapy, and at relapse by patient-specific RQ-PCR using RNA

derived from sequential bone marrow samples (Supplementary Table 5). Following serial

dilution experiments with patient-specific RQ-PCR for FLT3-ITD, the assay showed maximum reproducible sensitivity and specificity at 10-6 in UPN 104 and 213; and at 10-4 in UPN 146 and

241. The coefficient of the standard curves for the 4 samples ranged from 0.995 to 0.999 and the

slope ranged from 3.418 to 4.24.

A progressive decrease in FLT3-ITD copy number was detected in UPN 146 after induction therapy but unlike the smaller FLT3-ITD clone (ITD, 30bp), the most representative clone (ITD, 60bp) detected at the diagnosis in this case (Figure 4B upper panel and

Supplementary Table 5) remained unchanged after consolidation therapy. Accordingly, MPFC

analysis after post-consolidation therapy, detected a CD123/CD25/CD99+ve cell subset

comprising 20% of CD34+ve cells and 0.6% of the total blast population (Figure 5A).

UPN 104, 213 and 241 displayed a normal karyotype and had been labelled as FLT3-wt

using the conventional RT-PCR; however, within the small fraction of CD34+ve cells the

CD123/CD99/CD25+ve population was detected by MPFC above the defined threshold (Figure

5B upper panels, Figure 6A, and supplementary Figure 2A-3A). The FLT3-ITD patient-specific

analysis by RQ-PCR performed on all samples at relapse allowed identifying retrospectively

FLT3-ITD in the diagnostic sample (Supplementary Table 5).

In the case of UPN 104 the FLT3-ITD specific RQ-PCR showed a low expression of the

two ITD clones at diagnosis, which were below the detection limit of conventional RT-PCR

assays and which decreased after induction therapy. The FLT3-ITD copy number remained undetectable after the second course of consolidation therapy with Ara-C (Supplementary Table

5 and Figure 6B). This patient relapsed during follow-up and MPFC analysis showed an expansion of the CD34/CD123/CD99/CD25+ve subset, which at this time point represented over

65% of the total blast population (Figure 6C).

The FLT3-ITD patient-specific RQ-PCR of UPN 213 and 241 showed a low expression of the ITD clone at diagnosis, which decreased after induction and post consolidation therapy.

MPFC analysis had initially shown a percentage of the aberrant population very close to the threshold defined by the ROC curve (11.8 and 13% of CD34+ve cells respectively). This percentage decreased to 2 % after post consolidation treatment for UPN 213 (Figure 5B lower panels) in parallel with FLT3-ITD copy number fluctuations, but unfortunately there is no

MPFC data from the relapse. On the other hand, however, MPFC analysis for UPN 241 showed a 96% of CD123/CD25/CD99+ve within CD34+ve cells when the patient relapsed, reflecting the very high FLT3-ITD copy number (Supplementary Figure 3B-C).

Figure 6 and supplementary figure 3 also show that, both at diagnosis and relapse, the

CD34/CD123/CD99/CD25+ve subset cells expressed low levels of CD38.

Discussion

Using MPFC in leukemic blasts from AML patients, we identified a CD34+ve cell subset

characterized by CD25/123/99 co-expression that, compared to the total mononuclear cell

fraction, contained an enriched FLT3-ITD positive population. Our established threshold of

11.7% cells staining positive for this antigenic profile allowed to predict FLT3-ITD with

specificity and sensitivity >90% and enabled the identification of FLT3 mutated subclones also

in cases labelled as FLT3 wild-type by conventional RT-PCR during diagnostic routine work-up.

As reported previously by our group and by others (28-30) these minor FLT3 mutated subclones,

which escape diagnostic recognition, may undergo clonal evolution and ultimately result in overt

disease relapse, hence their improved identification at diagnosis through MPFC appears to be

clinically relevant.

Our results suggest that the CD34/25/123/99+ve LAIP is strictly associated with FLT3-

ITD mutations in the context of NK-NPM1 mutated AML. A total of six cases in the present study showed discordant results with respect to the correlation between the established LAIP threshold and FLT3 mutational status (Figure 1D). Of these, three patients with FLT3-ITD had

CD34/25/123/99+ve cells below the ROC-assessed 11.7% threshold, and three patients with

FLT3 wild-type configuration disclosed a CD34/25/123/99 LAIP above the threshold; interestingly, all these six cases showed mutated karyotype and NPM1 wild-type gene configuration. Although our findings require confirmation in other independent and larger studies, we outline the clinical relevance of the precise diagnostic definition of NK-NPM1 mutated AML - a subset commonly associated with a favourable prognostic outcome (31) - for the possible concomitant presence of small subclones harbouring the FLT3-ITD mutation.

Other authors have correlated the expression of CD25 and CD123 with FLT3-ITD

mutation in AML (13). In particular, the study by Gonen et al (13) showed a significant

association of CD25 and CD123 with FLT3 mutation but did not find a correlation of CD25

expression with the putative stem cell markers like CD34. Our data has revealed high copy

number of FLT3-ITD in the CD34CD123CD99+ve CD38neg CD117neg population, suggesting

that CD25 expression may appear at a later stage from CD34CD123CD99+ve subset. However,

a ROC analysis performed on this phenotype (AUC=0.89) indicates that this LAIP is not optimal

for the identification of samples with FLT3-ITD.

Rollins-Raval M et al. (32) described the association of CD123 in AML patients with

both FLT3 and NPM1 mutations, in keeping with our observations. Moreover, we reported a higher CD123 expression in FLT3 mutated AML patients as compared to those with germline

FLT3 (16). In the study by Ehninger et al. (33) the analysis of CD33 and CD123 restricted to the

CD34+ve compartment allowed to detect an association with FLT3 mutations in up to 73.1% of

AML patients.

Our study shows that AML blasts with FLT3 mutations also co-express CD99. The addition of CD99 to CD123 and CD25 and the restriction of the analysis to the CD34 population

allowed to increase the specificity and sensitivity of the association of immunophenotypes with

FLT3-ITD from 73.1%, as detected by Ehninger et al. (33), to over 90%. Notably, in the present study the CD34/CD123/CD25/CD99+ve cell fraction was detectable in healthy marrow samples at levels <4%, i.e. far below the 11.7% ROC-generated threshold for the association with FLT3-

ITD. CD99, also known as MIC2 or single-chain type-1 glycoprotein, is a O-glycosylated transmembrane antigen expressed on all leukocytes and is involved in the regulation of apoptosis and adhesive properties of T cells (34, 35). The expression level of this antigen in normal

hematopoiesis is related to distinct maturational stages: it is high in bone marrow CD34+ve cells,

and then declines during the differentiation process (36). In normal bone marrow we detect

CD99 expression on CD34+ cells, but it does not correlate with CD123 or CD25. Interestingly,

CD99 expression by tumor cells has been described in Ewing Sarcoma, where this antigen is the

potential target of immunotherapy (37).

Bachas et al. (28, 30) have studied in detail the subclones detectable within the leukemic

blasts of AML patients and analysed their role in the development of relapse. By analysing AML

cases with FLT3 mutations collected both at diagnosis and at relapse, these authors found a most

significant enrichment of cells carrying the FLT3 mutation in the CD34+ve/CD38-ve

compartment. Our results further improve the identification of these clones by a more accurate

LAIP which strengthens the association with FLT3 mutations.

As to the potential clinical use of our findings we observe that search of this LAIP at

diagnosis may complement routine genetic characterization. In particular, we recommend that

samples from AML patients with normal karyotype and NPM1 mutated/FLT3 wild-type genotype by routine RT-PCR which show a CD34/CD123/CD25/CD99 population above the indicated threshold be strictly monitored by both molecular and MPFC during follow-up for the possible emergence of FLT3 mutated clones.

Author contributions: D.F.A., T.O., L.B., G.Bo., F.B. and F.L.C. made substantial contributions to conception and design of the study and to analysis and interpretation of the data;

L.B. and F.L.C. supervised the study; S.L., G.G., F.G., M.C., M.D., N.N, M.D.B. M.I.C. contributed to carry out the experiments and to acquisition of the data; F.L.C., A.V., G.Bo., L.M.

L.B., S.A., G.Be., D.F.A, T.O. participated in drafting and revision of the article.

References:

1. Ossenkoppele GJ, van de Loosdrecht AA, Schuurhuis GJ. Review of the relevance of aberrant antigen expression by flow cytometry in myeloid neoplasms. British journal of haematology. 2011;153:421-36. 2. Bene MC, Nebe T, Bettelheim P, Buldini B, Bumbea H, Kern W, et al. Immunophenotyping of acute leukemia and lymphoproliferative disorders: a consensus proposal of the European LeukemiaNet Work Package 10. Leukemia. 2011;25:567-74. 3. Kern W, Bacher U, Haferlach C, Schnittger S, Haferlach T. The role of multiparameter flow cytometry for disease monitoring in AML. Best practice & research Clinical haematology. 2010;23:379-90. 4. Peters JM, Ansari MQ. Multiparameter flow cytometry in the diagnosis and management of acute leukemia. Archives of pathology & laboratory medicine. 2011;135:44-54. 5. Buccisano F, Maurillo L, Del Principe MI, Del Poeta G, Sconocchia G, Lo-Coco F, et al. Prognostic and therapeutic implications of minimal residual disease detection in acute myeloid leukemia. Blood. 2012;119:332-41. 6. Buccisano F, Maurillo L, Spagnoli A, Del Principe MI, Fraboni D, Panetta P, et al. Cytogenetic and molecular diagnostic characterization combined to postconsolidation minimal residual disease assessment by flow cytometry improves risk stratification in adult acute myeloid leukemia. Blood. 2010;116:2295-303. 7. Terwijn M, van Putten WL, Kelder A, van der Velden VH, Brooimans RA, Pabst T, et al. High prognostic impact of flow cytometric minimal residual disease detection in acute myeloid leukemia: data from the HOVON/SAKK AML 42A study. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2013;31:3889-97. 8. Dunphy CH. Comprehensive review of adult acute myelogenous leukemia: cytomorphological, enzyme cytochemical, flow cytometric immunophenotypic, and cytogenetic findings. Journal of clinical laboratory analysis. 1999;13:19-26. 9. Guglielmi C, Martelli MP, Diverio D, Fenu S, Vegna ML, Cantu-Rajnoldi A, et al. Immunophenotype of adult and childhood acute promyelocytic leukaemia: correlation with morphology, type of PML gene breakpoint and clinical outcome. A cooperative Italian study on 196 cases. British journal of haematology. 1998;102:1035-41. 10. Paietta E. Expression of cell-surface antigens in acute promyelocytic leukaemia. Best practice & research Clinical haematology. 2003;16:369-85. 11. Orfao A, Ortuno F, de Santiago M, Lopez A, San Miguel J. Immunophenotyping of acute leukemias and myelodysplastic syndromes. Cytometry Part A : the journal of the International Society for Analytical Cytology. 2004;58:62-71. 12. Chang H, Yeung J, Brandwein J, Yi QL. CD7 expression predicts poor disease free survival and post- remission survival in patients with acute myeloid leukemia and normal karyotype. Leukemia research. 2007;31:157- 62. 13. Gonen M, Sun Z, Figueroa ME, Patel JP, Abdel-Wahab O, Racevskis J, et al. CD25 expression status improves prognostic risk classification in AML independent of established biomarkers: ECOG phase 3 trial, E1900. Blood. 2012;120:2297-306. 14. Cerny J, Yu H, Ramanathan M, Raffel GD, Walsh WV, Fortier N, et al. Expression of CD25 independently predicts early treatment failure of acute myeloid leukaemia (AML). British journal of haematology. 2013;160:262-6. 15. Testa U, Riccioni R, Militi S, Coccia E, Stellacci E, Samoggia P, et al. Elevated expression of IL-3Ralpha in acute myelogenous leukemia is associated with enhanced blast proliferation, increased cellularity, and poor prognosis. Blood. 2002;100:2980-8. 16. Riccioni R, Diverio D, Riti V, Buffolino S, Mariani G, Boe A, et al. Interleukin (IL)-3/granulocyte macrophage-colony stimulating factor/IL-5 receptor alpha and beta chains are preferentially expressed in acute myeloid leukaemias with mutated FMS-related tyrosine kinase 3 receptor. British journal of haematology. 2009;144:376-87. 17. De Propris MS, Raponi S, Diverio D, Milani ML, Meloni G, Falini B, et al. High CD33 expression levels in acute myeloid leukemia cells carrying the nucleophosmin (NPM1) mutation. Haematologica. 2011;96:1548-51. 18. Liu YR, Zhu HH, Ruan GR, Qin YZ, Shi HX, Lai YY, et al. NPM1-mutated acute myeloid leukemia of monocytic or myeloid origin exhibit distinct immunophenotypes. Leukemia research. 2013;37:737-41.

19. Thiede C, Steudel C, Mohr B, Schaich M, Schakel U, Platzbecker U, et al. Analysis of FLT3-activating mutations in 979 patients with acute myelogenous leukemia: association with FAB subtypes and identification of subgroups with poor prognosis. Blood. 2002;99:4326-35. 20. Schnittger S, Schoch C, Kern W, Mecucci C, Tschulik C, Martelli MF, et al. Nucleophosmin gene mutations are predictors of favorable prognosis in acute myelogenous leukemia with a normal karyotype. Blood. 2005;106:3733-9. 21. Mrozek K, Dohner H, Bloomfield CD. Influence of new molecular prognostic markers in patients with karyotypically normal acute myeloid leukemia: recent advances. Current opinion in hematology. 2007;14:106-14. 22. Gale RE, Green C, Allen C, Mead AJ, Burnett AK, Hills RK, et al. The impact of FLT3 internal tandem duplication mutant level, number, size, and interaction with NPM1 mutations in a large cohort of young adult patients with acute myeloid leukemia. Blood. 2008;111:2776-84. 23. Welch JS, Ley TJ, Link DC, Miller CA, Larson DE, Koboldt DC, et al. The origin and evolution of mutations in acute myeloid leukemia. Cell. 2012;150:264-78. 24. Ottone T, Zaza S, Divona M, Hasan SK, Lavorgna S, Laterza S, et al. Identification of emerging FLT3 ITD-positive clones during clinical remission and kinetics of disease relapse in acute myeloid leukaemia with mutated nucleophosmin. British journal of haematology. 2013;161:533-40. 25. Chomczynski P, Sacchi N. Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol- chloroform extraction. Analytical biochemistry. 1987;162:156-9. 26. Noguera NI, Ammatuna E, Zangrilli D, Lavorgna S, Divona M, Buccisano F, et al. Simultaneous detection of NPM1 and FLT3-ITD mutations by capillary electrophoresis in acute myeloid leukemia. Leukemia. 2005;19:1479-82. 27. van Dongen JJ, Macintyre EA, Gabert JA, Delabesse E, Rossi V, Saglio G, 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. 1999;13:1901-28. 28. Bachas C, Schuurhuis GJ, Hollink IH, Kwidama ZJ, Goemans BF, Zwaan CM, et al. High-frequency type I/II mutational shifts between diagnosis and relapse are associated with outcome in pediatric AML: implications for personalized medicine. Blood. 2010;116:2752-8. 29. Cloos J, Goemans BF, Hess CJ, van Oostveen JW, Waisfisz Q, Corthals S, et al. Stability and prognostic influence of FLT3 mutations in paired initial and relapsed AML samples. Leukemia. 2006;20:1217-20. 30. Bachas C, Schuurhuis GJ, Assaraf YG, Kwidama ZJ, Kelder A, Wouters F, et al. The role of minor subpopulations within the leukemic blast compartment of AML patients at initial diagnosis in the development of relapse. Leukemia. 2012;26:1313-20. 31. Liu Y, He P, Liu F, Shi L, Zhu H, Zhao J, et al. Prognostic significance of NPM1 mutations in acute myeloid leukemia: A meta-analysis. Molecular and clinical oncology. 2014;2:275-81. 32. Rollins-Raval M, Pillai R, Warita K, Mitsuhashi-Warita T, Mehta R, Boyiadzis M, et al. CD123 immunohistochemical expression in acute myeloid leukemia is associated with underlying FLT3-ITD and NPM1 mutations. Applied immunohistochemistry & molecular morphology : AIMM / official publication of the Society for Applied Immunohistochemistry. 2013;21:212-7. 33. Ehninger A, Kramer M, Rollig C, Thiede C, Bornhauser M, von Bonin M, et al. Distribution and levels of cell surface expression of CD33 and CD123 in acute myeloid leukemia. Blood cancer journal. 2014;4:e218. 34. Brottier P, Boumsell L, Gelin C, Bernard A. T cell activation via CD2 [T, gp50] molecules: accessory cells are required to trigger T cell activation via CD2-D66 plus CD2-9.6/T11(1) epitopes. Journal of immunology. 1985;135:1624-31. 35. Pettersen RD, Bernard G, Olafsen MK, Pourtein M, Lie SO. CD99 signals caspase-independent T cell death. Journal of immunology. 2001;166:4931-42. 36. Dworzak MN, Fritsch G, Buchinger P, Fleischer C, Printz D, Zellner A, et al. Flow cytometric assessment of human MIC2 expression in bone marrow, thymus, and peripheral blood. Blood. 1994;83:415-25. 37. Rocchi A, Manara MC, Sciandra M, Zambelli D, Nardi F, Nicoletti G, et al. CD99 inhibits neural differentiation of human Ewing sarcoma cells and thereby contributes to oncogenesis. The Journal of clinical investigation. 2010;120:668-80.

Figure Legends

Figure 1 MPFC analysis of CD34+ve cells in AML bone marrow samples according to the

mutational status of FLT3 and NPM1 genes. (A) Percentage of CD34+ve (upper graph) and

CD34-ve CD117+ve cells (lower graph) within the total sample. (B) Percentage of CD123,

CD25, CD99, CD7, CD11b within the CD34+ve CD117+/- cell fraction according to the FLT3

and NPM1 gene status. CD38 expression was measured as median of the fluorescence within

CD34+cells. (C) MPFC analysis of 4 representative AML samples shows the expression of

CD123 vs CD25 and CD123 vs CD99 within the CD34+CD117+/- population (D) Co-

expression of CD123, CD25 and CD99 within CD34+ve population was calculated with Boolean

logic operator. The graph shows the percentage of CD34 cells that co-express the three markers

along with FLT3-TKD mutation (in red) and karyotype status : normal karyotype (NK) or

mutated karyotype (Mut-K).

Figure 2 MPFC analysis of CD34+ve cells in healthy bone marrow samples. (A) MPFC analysis of a bone marrow sample from a healthy donor. The sequential gating strategy shows the expression of CD123 vs CD25 and CD123 vs CD99 within CD34+ve CD117+/- cell subset. (B)

Cumulative data of the percentage of CD123/CD25/CD99+ve within CD34+ve cells in FLT3-

ITD mutated bone marrow samples and in healthy donors (HD).

Figure 3 ROC curve analysis. (A) Spearman's rank correlation coefficient (r) between the percentage of CD123+CD25+CD99+ cells within the total CD34 compartment and the FLT3-

ITD mutation in 132 AML samples. The coefficient was calculated giving the value 1 to the

presence of FLT3-ITD and -1 to the absence of FLT3-ITD. (B) The ROC curve is generated by

plotting the variables mentioned above. Statistical analysis was performed by “Med Calc”

software.

Figure 4 RT-PCR of FLT3-ITD mutation on whole MNC and sorted cell subsets of AML

samples. (A) Diagnostic leukemic cells from UPN 118 AML were analyzed by RT-PCR for

FLT3-ITD in whole MNC (upper panel) and using two different cell subsets (lower panels)

sorted on the basis of expression of CD45, CD34, CD117, CD123, CD99, CD25, CD7 and

CD38. R represents the ratio between fluorescence intensity of the FLT3-ITD and FLT3-wt

peaks. (B) UPN 146 AML sample at diagnosis (upper panel) and three different cell subsets

(lower panels) sorted based on expression of the same markers described above.

Figure 5 MPFC analysis of CD34+ve cells at diagnosis and post consolidation AML samples.

MPFC analysis of UPN 146 AML bone marrow sample (A) and of UPN 213 (B) at diagnosis

and after post consolidation therapy. Gate and arrows in blue show the expression of CD25,

CD123, CD99 within the CD34+ve CD117+/- population. The last plot shows how the selected

populations (in blue) match with CD45 and side scatter in back gating analysis of the total

sample (in red).

Figure 6. MPFC and molecular analysis of UPN 104 bone marrow cells at diagnosis, during

follow-up and at relapse. (A-C) The sequential gating strategy shows the expression of CD123,

CD25, CD99 and CD38 within the CD34+ CD117+/- cell subset (gate in blue) at diagnosis and

at relapse. Percentage of CD34+CD123+CD25+CD99+ve cells within CD34+ve cells and within

the total sample at diagnosis and at relapse is also shown. The last plot shows how the selected populations (in blue) match with CD45 and side scatter in back gating analysis of the total sample (in red). (B) Patient-specific RQ-PCR assay results of FLT3-ITD copy numbers at diagnosis, post induction, post consolidation, post Arabinofuranosil citidina (ARA-C), and at relapse.

Figure 1 A B CD34+CD117+/- CD123 p<0.0001 CD25 p<0.0001 CD99 p=0.0001 p<0.0001 p<0.0001 p=0.001 p<0.0001 p<0.0001 p=0.0007 100 100 100 100 p<0.0001 80 80 80 80

60 60 60 60

40 40 40 40

% of total total of % 20 20 20 20 % within CD34+ CD34+ within %

0 0 0 p<0.0001 0 p=0.01 p<0.0001 p=0.002 p<0.0001 p=0.02 -20 -20 -20 -20 FLT3-ITD + + - - + + - - + + - - + + - - NPM1-muts - + + - - + + - - + + - - + + - CD34-CD117+ CD7 p=0.004 CD11b CD38 p=0.002 p<0.0001 p=0.0004 p=0.002 p=0.002 100 p=0.02 p<0.0001 100 p=0.001 100 200 p=0.03 p=0.04 p=0.0002 80 p=0.0002 80 80 150

60 60 60 100 40 40 40 50 % of total total of % 20 20

% within CD34+ CD34+ within % 20 0

0 0 0 CD34+ within Median

-20 -20 -20 -50 FLT3-ITD + + - - + + - - + + - - + + - - NPM1-muts - + + - - + + - - + + - - + + - C D

FLT3-ITD 103 41 CD123+CD25+CD99+ NPM1-wt 102 100 p=0.02 101 p<0.0001

0 80

0 101 102 103 60 FLT3-ITD 3 10 2.88 NPM1-muts 40 102

101 20

0 CD34+ within % 0 0 101 102 103 p<0.0001

3 -20 FLT3-wt 10 2.44

NPM1-muts 2 FLT3-ITD + + - - 10 NPM1-muts - + + - 101 NK 0

0 101 102 103 Mut-K

3 FLT3-wt 10 79.3 n.d.

NPM1-wt 2 10 NK+FLT3-TKD

101 Mut-K+FLT3-TKD 0 CD117 CD123 CD123 0 101 102 103 n.d.+FLT3-TKD CD34 CD25 CD99

Figure 2

A B

%CD123+CD25+CD99+ 60K 94.7

103 103 100 100 40K 65.7 2 2 10 10 80

1 1 20K 10 10 60

SS 0 0

0 CD25 CD45 0 20K 40K 60K 0 101 102 103 0 20K 40K 60K 40 FS Dead cells SS 20 % within CD34+ CD34+ within % 0 103 3.51

102 -20

101 AML HD

0 FLT3 -ITD CD117 0 101 102 103 CD34 CD25 CD123

CD99

Figure 3

A B %CD123+CD25+CD99+/CD34+

1.5 ITD ITD 1.0

FLT3- 0.5 %CD123+CD25+CD99+/CD34+ 0.0 20 40 60 80 100 -0.5

p < 0.0001 Sensitivity ITDneg ITDneg -1.0 r = 0.7136 -1.5 FLT3-

Specificity

Figure 4

A 357 bp Fluorescence intensity (arbitrary units

Whole MNC R = 4,75 330bp

Subset 1 357 bp CD45+CD34+CD117- R = 21,67 CD123+CD99+CD25+ 330bp CD7+/- CD38low

Subset 2 357 bp CD45+CD34+CD117+ 330bp R = 2.04 CD123+CD99+CD25+

CD7+ CD38+ ) Fragment length

B 425 bp 365bp Whole MNC 395 bp R = 2,66 Fluorescence intensity (arbitrary units

Subset 1 425 bp CD45+CD34+CD117+ 365bp CD123+CD99+CD25+ R = CD7+/- CD38low/- 8,46

Subset 2 425 bp CD45+CD34+CD117+ 365bp R = 0,44 CD123+CD99-CD25- 395 bp CD7+/- CD38+ Subset 3 425 bp

CD45+CD34+CD117- ) CD123+CD99+CD25- 365 bp R = 7,18 CD7+/- CD38- Fragment length

Figure 5

100

3 103 10 6.72 80

Diagnosis 70.7 2 102 60 10

40 1 101 10

20 0 0

0 0 101 102 103 0 101 102 103 0 20K 40K 60K 100

3 3 10 14.3 80 10 Post 2 60 87.9 2 Consolidation 10 10 40 1 101 10

20 0 0

CD117 0 CD123 0 101 102 103 0 101 102 103 CD45 0 20K 40K 60K B CD34 CD25 CD99 SS 100

3 10 0.677 80 103 100 Diagnosis 2 60 10 102

40 1 10 101 20 0 0 0 1 2 3 1 2 3 0 10 10 10 0 10 10 10 0 20K 40K 60K

100

3 10 5.61 80 103 Post 71.4 102 60 Consolidation 102 40 101 101 20 0 0

CD117 0 CD123

1 2 3 CD45 0 10 10 10 0 101 102 103 0 20K 40K 60K CD34 CD25 CD99 SS

Figure 6

%CD123+CD25+CD99+/CD34+ = 20.7 A %CD123+CD25+CD99+CD34+/tot = 0.07

3 103 0.555 10

2 Diagnosis 102 10

1 101 10

0 0

C 0 101 102 103 0 20K 40K 60K

3 103 69 10

2 Relapse 102 10

101 101

0 0 CD38 CD45 CD117 CD123 0 101 102 103 0 20K 40K 60K CD34 CD25 CD99 SS %CD123+CD25+CD99+/CD34+ = 90 %CD123+CD25+CD99+CD34+/tot = 65

B 100000 Relapse 10000

1000 FLT3-ITD_33bp Diagnosis FLT3-ITD_66bp 100

10 Post Consolidation 1 Post Induction Post ARA-C

A Leukemia-Associated CD34/CD123/CD25/CD99-positive Immunophenotype Identifies FLT3-mutated Clones in Acute Myeloid Leukemia

Daniela F Angelini, Tiziana Ottone, Gisella Guerrera, et al.

Clin Cancer Res Published OnlineFirst May 8, 2015.

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