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 Table of Contents  
Year : 2022  |  Volume : 13  |  Issue : 4  |  Page : 268-276

Individualized antigen expression in precursor T-cell acute lymphoblastic leukemia: A gate to minimal residual disease analysis by flow cytometry

1 Department of Clinical Pathology, Laboratory Hematology, Faculty of Medicine, Ain Shams University, Cairo, Egypt
2 Department of Internal Medicine, Clinical Hematology, Faculty of Medicine, Ain Shams University, Cairo, Egypt

Date of Submission02-Sep-2021
Date of Acceptance22-Dec-2021
Date of Web Publication18-Oct-2022

Correspondence Address:
Dr. Mervat Abdalhameed Alfeky
Department of Clinical Pathology, Laboratory Hematology, Faculty of Medicine, Ain Shams University, Cairo
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/joah.joah_128_21

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BACKGROUND: In T-acute lymphoblastic leukemia (T-ALL), multi-parametric flow cytometry can serve to detect minimal residual disease (MRD) by using immature or aberrant antigens expression as well as the altered expression of T-cell antigens. The latter approach has been specifically introduced to overcome the absence of leukemia-associated antigens. However, there is no agreed-upon method for the use of T-cell antigens in T-ALL MRD testing.
AIMS AND OBJECTIVES: To compare the expression of classic T-cell antigens on T-lymphoblasts and T-lymphocytes to establish a protocol for their use in MRD analysis.
MATERIALS AND METHODS: Flow cytometric data of PB or BM samples from 63 adults with T-ALL were collected. We assessed the frequency and degree of brightness or dimness of each T-cell marker, in addition to studying the uniformity of the events scatter of a total of 287 follow-up BM samples from 50 patients.
RESULTS: Significant differences in expression intensity of T-cell markers were found between T-lymphoblasts and T-lymphocytes; they were reasonably stable on blasts in follow up samples. This detailed study has nominated the conjoint use sCD3neg/dim and CD5dim/neg in the identification of residual cells, to be supported by other T-cell markers.
CONCLUSION: The suggested gating sequence showed an acceptable level of accuracy in detecting residual leukemia, supporting their use in T-ALL MRD especially when other distinguishing markers might be absent in the diagnosis sample, or susceptible to be lost with induction therapy.

Keywords: Flow cytometry, minimal residual disease, T-acute lymphoblastic leukemia, T-cell antigens

How to cite this article:
El-Gamal RA, Ismail MA, Mohamed IA, Alfeky MA. Individualized antigen expression in precursor T-cell acute lymphoblastic leukemia: A gate to minimal residual disease analysis by flow cytometry. J Appl Hematol 2022;13:268-76

How to cite this URL:
El-Gamal RA, Ismail MA, Mohamed IA, Alfeky MA. Individualized antigen expression in precursor T-cell acute lymphoblastic leukemia: A gate to minimal residual disease analysis by flow cytometry. J Appl Hematol [serial online] 2022 [cited 2023 Oct 2];13:268-76. Available from: https://www.jahjournal.org/text.asp?2022/13/4/268/358701

  Introduction Top

Minimal residual disease (MRD) monitoring is an established independent prognostic indicator in acute lymphoblastic leukemia (ALL) and is commonly used to improve treatment decisions.[1] To be clinically informative, MRD testing should be able to detect residual cells at levels <0.01% of normal cells, as exceeding this threshold has been related to poor outcome. Hence, the highly sensitive multi-parametric flow cytometry (MFC), using leukemia-associated immunophenotypes (LAIP), is an advocated method for MRD testing in ALL.[2],[3] Likewise, the different from normal (DFN) MFC analysis, which is based on defining the immunophenotypic differences that characterize leukemic cells amidst the normal counterpart, is gaining credibility in MRD testing.[3],[4],[5],[6],[7],[8] The effectiveness of the DFN method stems from its ability to assess MRD in the absence of an initial diagnostic phenotype and is not affected by therapy-induced phenotypic changes.[5]

MRD testing in T-acute lymphoblastic leukemia/lymphoma (T-ALL) using MFC commonly depends on the identification of blast cells that express the T-cell precursor phenotype in bone marrow (BM) or peripheral blood (PB), which is normally restricted to the thymic development stages.[9] Aberrant expression of markers of other lineages also has an important role in MRD detection.[10],[11],[12] However, the frequent loss of immature markers after chemotherapy induction[13] increases the dependence on an alternative DFN method, which relies on changes in T-cell antigen expression, like CD2, CD3, CD4, CD5, CD7 and CD8, on T-lymphoblasts.

Testing panels and gating strategies have been proposed to employ the alteration in T-cell markers expression in MRD analysis.[5],[6],[7],[8] However, these MRD panels lack standardization in terms of how to apply DFN analysis, making MRD assessment in T-ALL challenging especially with the hazard of loss of immaturity markers in the treatment journey.[5],[14] Therefore, the objective of this study is to evaluate the expression pattern of classic T-cell antigens in T-ALL and to determine the most appropriate markers to be used in T-ALL MRD analysis.

  Methods Top

Patients and treatment

Flow cytometric data of PB or BM samples from 63 adults with T-ALL were collected from 2018 to 2021. Enrolled patients included 43 males and 20 females; mean age was 25.7 years (range: 17–42). Patients were treated using hyper-cyclophosphamide, vincristine, adriamycin, and dexamethasone (CVAD) regimen (CVAD alternating with high dose of methotrexate and cytarabine) for remission-induction therapy; central nervous system prophylaxis was achieved by intrathecal injection of methotrexate and steroids. Patients who had matched related donors were subjected to allogenic hematopoietic stem cell transplantation following response to induction treatment. The follow-up protocol depended on complete blood count and a series of BM aspirations for MRD testing done every month in the 1st year of treatment, every 3 months in the 2nd year, and then once per year. MRD samples were requested to be the first aspirated BM specimens, with a volume of 1–2 mL. A total of 287 follow-up BM samples from 50 patients were measured by flow cytometry (as 12 patients were lost-to-follow-up). Average follow-up duration was 11.8 months (range: 1.5-40), with an average of 5.74 MRD tests per patient (range: 1-8). The study had been approved by the Ethical Committee of the Clinical Pathology and the Hematology Departments of the Faculty of Medicine, Ain Shams University and was carried out according to the standards of the Declaration of Helsinki.

Flow cytometric analysis

The involvement of BM or PB samples with T-ALL was assessed using Navios flow cytometer (6-color; Beckman Coulter, USA) employing whole blood lysis method using ammonium chloride-based solution; data was analyzed with Navios software version 1.1. The antibody panel comprised T lineage-associated markers (CD2 PE, CD3 PC5.5 (surface and cytoplasmic staining), CD4 FITC, CD5 FITC, CD7 FITC, CD8 FITC, CD56 PE, TCR αβ PE, TCR γδFITC, immaturity markers (CD34 FITC, TdT FITC, CD10 PE, CD99 APC, HLA-DR FITC), other lineages-associated markers (CD13 PE, CD33 PE, CD117 PE, CD19 PE), and CD45 ECD/PC5.5 for blast gating; all reagents were obtained from Beckman Coulter (Hialeah, FL). Proper instrument compensation and quality control were achieved using AutoSetup software, and flow-check and flow-set fluorospheres, respectively (Beckman Coulter, Brea, CA, USA). Previously titrated volumes of antibodies for surface and cytoplasmic staining of antigens were used. Blasts were gated according to dim CD45 and low side scatter (SSC) characteristics. Residual lymphocytes, granulocytes, or monocytes were employed as sample negative and positive controls, where appropriate. Event acquisition was stopped at 20,000 events for each tube.

Minimal residual disease testing

The MRD panel [Table 1] has included T-cell markers, immaturity markers (CD34, CD99 or CD10) and non-T cell markers (myeloid or B-lymphoid lineage), based on the diagnosis phenotype. Events acquisition was continued to a minimum of 500,000 up to 1,000,000 events. To ensure gating viable events, continuously flowing events were selected using time as a gating parameter, doublets were excluded in the forward scatter area/forward scatter peak plot, and dead cells were eliminated by removing low forward scatter events. A dot plot of CD45/SSC was used to exclude granulocytes and restrict the gate to mononuclear cells.
Table 1: Panel of markers in minimal residual disease analysis

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CD7+/low SSC events were used for primary gating; dim CD7-expressing normal nonleukemic myeloblasts in regenerating BM were identified by their characteristic CD34 maturation pattern and were excluded. The first two tubes of MRD panel were used in all cases. If suspected cells were found, we proceeded to test natural killer (NK) cell markers to ensure the leukemic nature of the identified cells (Tube 3). Low incidence-aberrantly expressed markers were added to the MRD panel only if they were expressed at diagnosis. Some T-cell markers were tested more than once to enhance results reproducibility among the tubes. The rationale for detecting residual cells was based on coexpression of immaturity or aberrant markers with any of the classic T-cell markers, based on the original diagnostic phenotype; this was considered the gold standard against which traditional T-cell markers were evaluated.

The presence of the residual leukemic cells found in one tube was verified across the other tubes. The sample was considered positive for MRD only if similar percentages of the suspected cells were found in all tubes, present in the form of cluster, and exceeding the limit of 0.01% of mononuclear cells. To validate the accuracy of MRD testing, assay sensitivity was determined by measuring the lower limit of quantitation (LLOQ) through spiking leukemic cells of PB T-ALL sample into another PB sample with reactive lymphocytosis. LLOQ of 0.007% was validated.

Standardization of expression intensity data

We compared T-cell antigen expression on T-lymphoblasts and normal T-lymphocytes using their mean fluorescence intensity (MFI) values. For valid comparability of values, we eliminated the effect of background staining by normalizing MFI values using antigen-negative cells. MFI quotient (MFIQ) was calculated for each T-cell marker in each sample using the formula:

Statistical analysis

Data were analyzed using IBM SPSS Statistics version 26 (IBM Corp., Armonk, NY, USA). The normality of numerical data was tested by the Shapiro–Wilk test. Parametric numerical variables were presented as mean ± standard deviation; comparison of MFI values of T-lymphoblasts and mature T-lymphocytes was done using independent samples t-test. Nonparametric numerical variables were presented as median and interquartile range; comparison of MFI values of T-lymphoblasts and mature T-lymphocytes was done using Mann–Whitney U test. The average MFI values of expression intensity of T-cell markers on residual T-lymphoblasts were compared to the MFI of T-lymphoblasts at diagnosis using Wilcoxon Signed-Ranks test. A two-sided P < 0.05 was considered statistically significant.

  Results Top

Marker expression in the diagnosis samples

Data of 63 patients with newly diagnosed T-ALL were available for evaluation. Leukemic blasts ranged from 30% to 95% (median: 72%). T-lymphocytes were present at various levels (range: 0.2%–16%, median: 2.6%). Complete loss of one or more T-cell antigens on lymphoblasts was seen in 56 samples (88.9%). Double negative state for CD4 and CD8 was found in 35 samples; 14 samples showed coexpression of both antigens; single expression of CD4 and CD8 was found in 4 and 10 samples, respectively.

Each marker tested on lymphoblasts at diagnosis was compared to its expression on mature lymphocytes present in the same sample; lymphocytes were not recognized in 18 samples. The results have revealed significant differences in expression intensity of T-cell antigens between lymphoblasts and lymphocytes [Table 2] and [Figure 1].
Table 2: Comparison of expression of T-cell markers, CD45 and CD99 expression on T lymphoblasts and mature T lymphocytes

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Figure 1: Box-plots of normalized mean fluorescence intensity values of T lineage-associated markers on T-lymphoblasts and mature T-lymphocytes

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Expression of other markers commonly encountered in T-ALL

  • CD56 was expressed in 18/63 patients (28.6%); T cell receptors were expressed on T-lymphoblasts of six patients: 4 TCR αβ and 2 TCR γδ
  • Immaturity markers: 26 patients (41.3%) expressed CD34; TdT was tested in 43 patients and was expressed in 33/43 (76.7%); HLA-DR was detected in 28.6% patients; CD10 was found in 31 patients (49.2%); CD99 was tested in 23 patients in whom the marker showed a noticeable bright expression
  • Aberrant non-T lineage markers: 28/63 of the patients (44.4%) showed positivity for at least one myeloid marker; nine patients (14.3%) expressed more than one myeloid marker. CD33 was the most frequent to be positive (17/63; 27%), followed by CD117 (13/63; 20.6%) and CD13 (6/63; 9.5%). CD19 was detected in three patients (4.8%).

Analysis of the expression pattern of T-cell antigens

We studied the degree of homogeneity of event scatter for each marker [Table 3]. Events limited to one decade of the logarithmic histogram were considered to have a uniform or homogeneous scatter. sCD3 and CD4, as well as CD45, were homogeneously expressed on T-lymphocytes in all samples, whereas CD5 and CD7 had a characteristic decline of intensity and more heterogeneous distribution.
Table 3: Comparison between markers as regards incidence and pattern of expression, and their ability to distinguish blasts

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To standardize the discriminative power of an antigen, we considered the threshold of 50% of the gated blasts, with a different expression intensity of an antigen than lymphocytes, to be adequate to confer a characteristic expression property and would also account for an acceptable level of separation between both populations. Otherwise, blasts were considered to have similar expression intensity to T-lymphocytes. Of the evaluated markers, sCD3, CD5, CD99 and CD45 were the markers that differed most frequently on lymphoblasts compared to T-lymphocytes [Table 2]. sCD3 expression on T-lymphoblasts was below the dimmest event of lymphocytes in 15/16 samples (93.8%); the same was found with CD5 but at a lower incidence (81%). In contrast, CD99 on blasts was brighter than the brightest events of lymphocytes in all samples (100%) [Table 3].

Marker expression in follow-up samples

The pattern of expression of T-cell markers was monitored in three relapse samples and 15 samples showing definitive positive MRD results (>0.01%) [Table 4]. CD5 in follow-up samples was the only marker that showed significant difference in its MFIQ than that of the diagnosis samples (mean rank = 6.56 vs. 3.5; Z = −2.3; P = 0.021).
Table 4: The change in mean fluorescence intensity quotient of studied markers in follow up samples in comparison to diagnosis samples

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The incidence of change in antigen expression in follow-up samples in relation to diagnosis samples are listed in [Table 5]. Immaturity markers were lost in several samples; minor changes in expression intensity affecting T-cell markers, and stability of aberrant non-T-lineage markers were also noted.
Table 5: Frequency and pattern of change of expression of each marker on recurring or residual T-lymphoblasts in relapse or minimal residual disease samples

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Proposed scheme for minimal residual disease testing using classic T-cell markers

Based on the integrated data of the degree of events uniformity and discriminative power specific to each marker, we decided to evaluate the adequacy of dim or negative events of sCD3 and CD5, with the help of other T-cell markers, as appropriate, in 15 samples that showed definitive positive MRD results. The results revealed that six MRD samples showed success in full application of the proposed protocol (sCD3dim, CD5dim, and CD7bright or unusually CD2dim). Residual leukemic cells in five other samples were sCD3neg, CD5dim and CD7bright; dim CD8 on residual cells showed an added value in two samples. The remaining four samples were not resolved because they were sCD3neg, CD5dim/neg, with no help from other markers (CD7 or CD8); residual cells were identified by the preserved CD99 in two sample, CD10 in another sample, aberrant CD33 in three samples, and presence of mediastinal mass in one patient. Therefore, the results showed 73.3% concordance (11/15 samples) between the proposed method using classic T-cell markers and the use of the definitive indicators of residual leukemia. [Figure 2] shows examples of using the sCD3/CD5 gating protocol in MRD detection.
Figure 2: Dot plots of follow-up samples showing residual or treatment-resistant T lymphoblasts (red) and mature T lymphocytes (navy blue). Sample A (first two rows): residual leukemic cells were mainly identified by their clearly dim CD5 and less-definitely dim CD3 expressions; they had bright CD7 and dim CD45 expressions. The cells showed attenuation or loss of the immaturity markers CD10 and CD34, respectively (both markers were strongly expressed at diagnosis); the affirmation of their leukemic nature was possible by their bright CD99 expression and lack of NK cell markers. Sample B (middle row): residual cells were gated according to their dim expression of both CD3 and CD5; the selected events corresponded to positive CD34, bright CD7 and dim CD45 expressions. Sample C (bottom two rows): the treatment-resistant leukemic cells (analyzed at D28) showed dim expression of CD3, CD5 and CD45 and the leukemic identity was confirmed by constructing an additional combination of markers (CD45 ECD, CD7 APC, CD2 PC7, CD13 PE), in which CD13 was aberrantly expressed with negative CD2 expression (the same phenotype expressed in the diagnosis sample); However, the cells have lost their brighter-than-lymphocytes CD99 expression that was displayed at diagnosis (lower-right plot; blasts are magenta and lymphocytes are cyan)

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  Discussion Top

The selection of markers based on well-defined properties can indeed enhance the standardization of MRD detection. In this study, we evaluated each T cell antigen aiming at recognition of an individualized pattern of expression of the antigens on T-lymphoblasts and, of equal importance, on mature T-lymphocytes.

The prevalence of T-ALL in men and young people revealed in our study is consistent with previous reports.[15],[16] In addition, early T-cell precursor ALL accounted for 7/63 (11.1%) of the studied patients, while 8/63 (12.7%) were near early T-cell precursor, which also agrees with the reported incidence of each type.[16] CD99 and TdT showed the highest incidence of expression in the tested cases, consistent with the high efficiency of immature markers in the diagnosis of T-ALL,[16],[17] and conforming with the reported results of the two antigens in similar studies.[13],[18]

According to the WHO immunophenotypic criteria, CD33 and CD13 are the most frequent aberrant markers expressed in T-ALL, while CD117 is rarely detected;[16] the expression of the latter was reported in adult T-ALL, especially if associated with activating FLT3 mutation.[19],[20],[21] The FLT3 mutation was not tested in this study, but the expression of CD117 was not as low as described by the WHO; however, some related studies have reported similar results.[21],[22] The expression of CD33 was similar to that of earlier reports, while CD13 expression was much lower in our study (9.5% vs. 25% to 55%).[16],[21] CD19 is described to be rare in T-ALL, however, the incidence reported in the study of Sharma et al. is similar to our results (6.5% vs. 4.8%).[21]

CD7 is usually ubiquitously expressed in T-ALL, while other T-lineage antigens, whose expression is more related to the blasts maturational state, are sometimes absent.[13],[14],[18] In the current study, CD7 was expressed in all cases, while the expression of other T cell markers was inconsistent, among which sCD3 and CD4 had the lowest incidence.

In 18 diagnostic samples, we were not able to assess the dimness or brightness of T-cell markers on blasts either because of the encroaching blasts on mature lymphocytes, or the relative lymphopenia shown in most samples (lymphocytes formed <1% of the cells in 11 samples). T-lymphoblasts and T-lymphocytes of diagnostic samples exhibited considerable differences in the MFI values of T-cell markers as well as CD99 and CD45. As regards the frequency of altered expression, it was the dimmer expression of sCD3 and CD5 and brighter expression of CD99 on T-lymphoblasts that were most frequently found (93.8%, 81% and 100% of samples, respectively). The number of samples with discriminating sCD3dim/CD5dim expression represented 14/42 (33.3%), while the number of samples with sCD3neg/CD5dim expression represented 20/42 (47.6%); sCD3neg/CD5neg samples formed 11.1%. Similar results were described in earlier studies.[6],[13],[23] Also, Porwit-MacDonald et al. have reported an incidence of 63% for sCD3neg/dim/CD5dim cases.[18] However, in the study of Tembhare et al., only 28.3% of CD5dim/negative cases was reported.[7]

These data would naturally nominate T-cell markers to be used in the detection of residual blasts in follow-up samples. However, because MRD analysis requires a high level of sensitivity (0.01%), we must respect the normally present T-lymphocyte subsets that can share leukemic blasts their described dim or bright antigen expression; even the fewest number of these cells can cause false-positive MRD results. For example, CD5 is known to have varying intensity of expression on T-lymphocytes, and CD7 can be normally absent in some T-cell subsets.[24],[25],[26],[27],[28]

Therefore, the degree of expression uniformity was evaluated for each marker on lymphoblasts and lymphocytes to assess the possibility that normal lymphocytes might interfere with MRD gating. sCD3 showed a bright and homogenous expression on normal lymphocytes versus a reduced intensity and more heterogeneous distribution on T-lymphoblasts. The homogeneous sCD3 expression on mature lymphocytes has allowed leukemic cells to fall into a clean area of event acquisition, enabling sCD3 to adequately differentiate between lymphoblasts and lymphocytes in sCD3-positive samples. Interestingly, the reverse was noted with CD5 expression, where T-lymphoblasts had a homogenous dim expression in the face of the spectrum of fluorescence on mature lymphocytes. However, because of the considerable dimness of the marker on lymphoblasts, CD5 was still able to identify lymphoblasts in 81% of samples.

On the other hand, the previously described discriminating bright CD7[14],[18] was less clear in this study. CD7 showed a uniform expression on lymphoblasts in most samples. However, the explicit heterogeneous expression of CD7 on mature T-cells (95% of samples) is largely responsible for its limited ability to discern between lymphoblasts and mature lymphocytes (28.9% of samples). Similarly, CD8 could not distinguish T-lymphoblasts in most samples since the incidence of heterogeneous expression on lymphocytes was 35% of samples, and both populations showed similar CD8 expression in 60% of samples. As for CD4, although having a homogeneous pattern of scattering on T-lymphocytes, it had a weak discriminative power mostly because of the trespassing leukemic cells into the T-lymphocyte zone of events. CD45 helped distinguish leukemic blasts in about 73.3% of cases, mainly because of its uniform expression on T-lymphocytes in addition to its dim expression on leukemic blasts, coinciding with the reported pattern of expression in other studies.[23] However, one should consider the possible increase in its expression with treatment.[13] Here, we should emphasize the paramount significance of proper antibody titration to achieve acceptable separation between different cell populations.

Despite the limited number of follow-up samples with definitive leukemic cells, some changes in antigen expression were still noted, such as loss or weakening of immaturity markers during therapy, which was reported in earlier studies.[13],[14],[17],[29] Regarding T-cell markers, the degree of events uniformity of each marker found at diagnosis was maintained in all studied follow-up samples. However, changes that involved the expression intensity of classic T-cell markers have occurred, thereby offsetting the putative stability of these markers.[13],[14] Surface CD3 was lost in one relapse sample. We attributed this loss to weak expression of sCD3 on lymphoblasts in the corresponding diagnosis sample (21%), so the cells that lacked the antigen were the ones that resisted the effect of chemotherapy; still, we do not recommend discounting weakly expressed markers, as the reverse can also occur. In two MRD samples, lymphoblasts expressed dimmer CD5 and brighter CD7 compared to their diagnostic samples where both antigens showed less demarcated expression than lymphocytes. When investigating the two related diagnostic samples, lymphocytes represented only 0.5% and 0.2% of cells, compared to 8% and 11.5% in the MRD samples. Therefore, this change in expression might have been caused by a reasonably discrete population of mature lymphocytes that has emerged with the decline in leukemic load in the MRD sample. Furthermore, another MRD sample showed a decrease in the relative CD7 expression intensity on blast cells, and two other samples exhibited changes in CD2 intensity. We have no interpretable causes to justify these latter changes.

We used these follow-up samples to decide whether the concluded expression intensity variations are sufficient for MRD detection. The uniformity of event distribution of each antigen expression on mature lymphocytes, and the maximum difference in expression intensity between the two cell populations for each marker, in addition to the stability of markers with treatment, has all contributed to the solid criteria we have set for selecting the gating markers in MRD detection. Thus, in 15 samples that have been confirmed to be MRD positive, a 73.3% concordance has been revealed between the proposed sCD3/CD5 gating method and the use of the definitive indicators of residual cells. This level of concordance was achieved by the combined high discriminative ability of sCD3 and CD5, together with the uniform sCD3 expression on T-lymphocytes, with the help of the other appropriate T-cell markers. Nevertheless, we need to emphasize the importance of excluding T-lymphocyte subsets that might share the described phenotypic aberrancies with leukemic cells, e.g., NK cells (CD3-CD16/CD56+) or CD3+CD5-γδ TCR+T-lymphocytes.

  Conclusion Top

In conclusion, our results have indicated sCD3, owing to its extremely low noise background, as the most encouraging marker to detect T-lymphoblasts in MRD samples. Thus, blasts expressing all T-lymphocyte markers, which was previously thought of as an inconvenient finding because of the unreal impression of absent DFN pattern, should be considered helpful due to the proved diagnostic role offered by dim sCD3. However, because of its low incidence of expression, adding CD5dim/neg events can enhance the chance of detecting residual cells. The sCD3/CD5-based selected cells can be also related to CD45dim and CD8dim/neg areas of expression, and possibly CD7bright events, depending on their expression status at diagnosis. Although our proposed gating sequence could not resolve all tested MRD cases, it can be of help in samples that lack specific testing LAIP or have lost their immaturity markers, where the identification of residual cells becomes jeopardized. Also, because it is based on the uniformity of events as well as the difference in expression, it offers an alternative method with a relatively limited hazard of reporting false-positive MRD results. A higher number of cases is certainly needed to validate this study findings, though might necessitate long-term studies to achieve, since T-ALL is the least common acute leukemia encountered in clinical settings.


We acknowledge the Flow cytometry Unit and Clinical Hematology Department, Ain Shams University, for allowing us to access patients' results and data, and carrying out the work.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

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  [Figure 1], [Figure 2]

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


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