|Year : 2019 | Volume
| Issue : 1 | Page : 40-47
Lymphoid enhancer factor 1 gene expression in comparison to other prognostic markers in adult B-acute lymphoblastic leukemia
Manal A ElSourdy1, Mona W Ayad2, Amira I Fayad PhD 2, Sara M Youssef3
1 Haematology Unit, Department of Internal Medicine, Faculty of Medicine, Alexandria University Hospitals, Alexandria, Egypt
2 Department of Clinical Pathology, Faculty of Medicine, Alexandria University Hospitals, Alexandria, Egypt
3 Department of Clinical Pathology, Ministry of Health and Population Hospitals, Alexandria, Egypt
|Date of Submission||14-Nov-2018|
|Date of Acceptance||25-Dec-2018|
|Date of Web Publication||27-Sep-2019|
Amira I Fayad
Imperial college, Postal code 21526, UK
Source of Support: None, Conflict of Interest: None
Background Activation of the canonical Wnt signaling pathway by the key mediator lymphoid enhancer factor 1 (LEF1) plays an important role in the development of several hematological and nonhematological malignancies.
Aims The aim was to study LEF1 gene expression in adult B-acute lymphoblastic leukemia (ALL) and its clinical significance in comparison to other prognostic markers to improve risk-adapted treatment stratification for high-risk patients.
Patients and methods The study was conducted on 50 adult cases with newly diagnosed B-ALL and 50 adult healthy controls with matched age and sex. The cases were divided into three groups according to risk assessment: low risk (have no risk factor), intermediate risk group (have one or more risk factors), and high risk (BCR-ABL positive). LEF1 gene expression was analyzed using quantitative real-time PCR and its correlation with clinical characteristics and treatment outcome at day 28 after induction chemotherapy and in 6 months follow-up period was assessed.
Results LEF1 gene expression showed statistically significant higher expression in ALL cases compared with control (P=0.001). Higher LEF1 gene expression was detected in the high-risk group compared with comparable gene expression in both low- and intermediate- risk groups (P=0.05). Statistically significant positive correlation was detected between LEF1 gene expression and BCR-ABL positive cases. Statistically significant positive correlation was detected between the non-remission group and high LEF1 gene expression (Z=3.026, P=0.002).
Conclusion The high LEF1 gene expression at diagnosis may be used in identifying patients with high risk of treatment failure. The high LEF1 gene expression can be a prognostic marker in adult B-ALL patients.
Keywords: adult B-acute lymphoblastic leukemia, canonical wingless type (Wnt) pathway, lymphoid enhancer factor 1 gene expression, prognostic markers
|How to cite this article:|
ElSourdy MA, Ayad MW, Fayad AI, Youssef SM. Lymphoid enhancer factor 1 gene expression in comparison to other prognostic markers in adult B-acute lymphoblastic leukemia. Egypt J Haematol 2019;44:40-7
|How to cite this URL:|
ElSourdy MA, Ayad MW, Fayad AI, Youssef SM. Lymphoid enhancer factor 1 gene expression in comparison to other prognostic markers in adult B-acute lymphoblastic leukemia. Egypt J Haematol [serial online] 2019 [cited 2022 Jul 3];44:40-7. Available from: http://www.ehj.eg.net/text.asp?2019/44/1/40/268007
| Introduction|| |
Acute lymphoblastic leukemia (ALL) is a malignant neoplasm of lymphocytic precursors (lymphoblasts) . Diagnosis of ALL is based on clinical and microscopic examination of peripheral blood samples, Bone marrow (BM) aspirates/biopsies, immunophenotyping, and molecular genetic analysis . Survival rate of adult lymphoblastic leukemia over the past two decades have not significantly improved where 5-year survival is 30–40% for patients aged 20–60 years, 15% for those older than 60 years, and less than 5% for patients older than 70 years ,. Unlike the cure rate in childhood leukemia, only 20–40% of adults ALL was cured with the current treatment regimens . Identification of new prognostic factors affecting treatment response in ALL is of great interest and can improve treatment strategies . Given the role of Wnt signals in hemopoietic stem-cell self-renewal, survival, and expansion of lymphocyte and myeloid progenitors, it was assumed that Wnt signaling dysregulation could be a mechanism to lymphoid as well as myeloid leukemogenesis ,. Studies in the pathogenesis of malignant hematopoiesis concluded an implicating role of Wnt signaling in normal hematopoiesis and tumorigenesis ,,,,,. Lymphoid enhancer factor 1 (LEF1) has been identified as a key mediator of Wnt signaling pathway activation through the recruitment of β-catenin ,. The Wnt pathway started by the binding of soluble glycoprotein Wnt ligands to surface receptors and coreceptors LRP5/6. Consequently, the β-catenin destruction complex will be blocked, allowing the accumulation of β-catenin with subsequent translocation to the cell nucleus where it regulates transcription through forming a complex with the LEF/T-cell factor (LEF/TCF) DNA binding proteins . LEF1 expression is critical during normal B-cell development in the bone marrow, with expression turned off at later stages of B lineage development. Previous studies have evaluated the Wnt pathway and concluded that deregulation of this pathway has been linked to a large variety of cancers including hematological and nonhematological malignancies ,,. Furthermore, aberrant expression of LEF1 induced B-lymphoblastic leukemia and myeloid leukemia in murine model .
The aim of the present study is to study the expression of LEF1 in human adult B-ALL and determine its role as a prognostic marker in comparison to other consensual prognostic parameters (risk factors)  such as age, total leukocytic count at the time of disease presentation, percentage of blasts in BM, central nervous system (CNS) infiltration, BCR-ABL analysis, and response to induction chemotherapy at day 28.
| Patients and methods|| |
The present study was conducted on 50 cases recently diagnosed as B-precursor ALL and were admitted to the hematology unit of Alexandria University Hospital and 50 healthy controls with matched age and sex during the period from February to December 2015. Patients under the age of 18 years and those with mature B-ALL (ALL-L3) were not included in this study. The patients were classified according to risk stratification to: low-risk group with no risk factor (six cases, 12%), intermediate-risk group with one or more risk factors (40 cases, 80%), and high-risk group with BCR-ABL positive (four cases, 8%). Bone marrow and peripheral blood samples were collected before the start of treatment and after induction chemotherapy at day 28. All patients received the same treatment protocol as instructed by the hematology team at the Alexandria Hematology Unit. Bone marrow aspiration was done at the time of presentation of the disease and on day 28 after starting induction chemotherapy to evaluate the treatment outcome. Complete remission was identified by the absence of peripheral blood blasts and BM blast cells less than 5% after induction chemotherapy at day 28 and/or 6 months follow-up period. Relapse was defined by the reappearance of greater than 5% BM blasts and/or CNS infiltration by leukemic cells ,,. Informed consents to participate in the study and approval of the Medical Ethics Committee were fulfilled.
Complete blood picture
EDTA-venous blood samples were withdrawn from all studied subjects for complete blood count and the diagnosis of acute leukemia according to the WHO classification of tumors of the hematopoietic and lymphoid tissue classification .
clotted venous blood samples were used for blood chemistry analysis and measured by Chemistry AutoAnalyzer Dimension RxL Max (Siemens Healthcare Diagnostics, CA, USA).
Cerebrospinal fluid aspirate
(For cases only) for cytological examination and immunophenotypic analysis of cells.
Bone marrow aspiration
(For cases only) was stained by Leishman’s stain for morphological examination and diagnosis was made by the presence of greater than or equal to 20% lymphoblasts in bone marrow smears.
For peripheral blood samples, bone marrow aspirates, and cerebrospinal fluid samples. The following panels of monoclonal antibodies were used for the diagnosis of acute leukemia: primary panel B-lymphoid markers: CD19; T-lymphoid markers: CD2 and CD7; myeloid markers: CD13, CD33, and CD14; nonlineage specific markers: CD45, HLA-DR, CD34, and CD10. A second set of monoclonal antibodies was used: Cyt CD22 or Cyt μ. Miltenyi Biotec MACSQuant flowcytometry analyzer (Miltenyi Biotec, CA, USA) was used and equipped with MACSQuantify software version 2.4.
Fluorescence in-situ hybridization
For the detection of Ph chromosome (BCR/ABL).
Quantitative real-time PCR for LEF1 gene expression
RNA isolation from peripheral blood and cDNA preparation followed by quantitative real-time RT-PCR was done to assess the expression of LEF1 in all cases and controls. RNA purification: RNA purification was done using Thermo Scientific Gene JET (Thermo Fisher Scientific, MA, USA) whole blood RNA purification mini kit #K0761. Reverse transcription of RNA to cDNA was done by high-capacity cDNA reverse transcription kit (Applied Biosystem, MA, USA). The purity and concentration of RNA were measured by nanodrop spectrophotometer with a purity A260/A280 ratio of 1.9–2.1. Purified RNA was stored at −80°C and cDNA at −20°C until used.
Quantification of LEF1 and housekeeping gene GAPDH by real-time quantitative PCR
Quantitation of LEF1 gene expression was performed by real-time RT-PCR and was normalized to the endogenous gene glyceraldehyde-3-phosphate dehydrogenase (GAPDH). RT-PCR was done using the ready to use TaqMan Gene Expression Assays protocol (P4333458) and real-time cycler Rotor gene Q (Qiagen, GmbH, Germany). Log changes in fluorescence were plotted automatically versus the cycle number for each sample by rotor gene software analyzer 2.0.2. The results of real-time PCR were represented by the parameter Ct (threshold cycle). The difference in Ct values between LEF1 and GAPDH reactions was given by ΔCt). Relative quantitation was expressed by a comparative Ct method where the amount of target is normalized to an endogenous reference and relative to a calibrator (in this case we used the mean of ΔCt of normal controls). The calculation of ΔΔCt (2−ΔΔCt) involves the subtraction of ΔCt value of the sample from the ΔCt value of control .
Data were analyzed using IBM SPSS software package version 20.0 (SPSS Inc., Chicago, Illinois, USA). All statistical analysis was done using two-tailed tests and α error of 0.05. P less than or equal to 0.05 was statistically significant. For qualitative data median, mean with SD, percentage to describe the scale, and categorical data were used. For numeric data analysis one-sample Kolmogorov–Smirnov test was used as to compare the observed cumulative distribution function for a variable with a specified theoretical distribution which was the normal distribution at the current data (testing for distributional assumption for numerical data), then the following statistical analysis was used. Independent sample t-test: to compare the mean for two independent groups for numeric data and following normal distribution. Mann–Whitney test: to compare ranks (medians) for two independent groups of cases. Kruskal–Wallis test: to compare mean ranks (medians) for two independent samples data that do not follow normal distribution. Wilcoxon test: to compare the mean ranks (median) of related samples (before and after treatment) for quantitative data measured over time periods (repeated measurements). For categorical data analysis, Pearson’s χ2-test was used to test for the association (or relationship) between the categories of two independent samples. Mont Carlo exact test and Fishers exact test: are alternatives for the Pearson’s χ2-test if there were many small expected values.
| Results|| |
Demographic and clinical–laboratory data
ALL cases included 30 men and 20 women, with age range from 20 to 70 years (mean: 33.4±12.9 years). The control group included 26 men and 24 women; their age ranged from 18 to 58 years (mean: 34.6±12.2 years; [Table 1]). Clinical findings and laboratory investigations are shown in [Table 1]. Immunophenotypic analysis showed: CD19 was expressed in all cases (50/50, 100%); CD10 was expressed in 40/50 (80%; CD34 was expressed in 30/50 (60%), cytoplasmic μ was expressed in 6/50 (12%), and aberrant expression of CD33 1/50 (4%) in B-ALL cases. B-ALL subtypes were pro-B-ALL (12 cases), common B-ALL (32 cases), and pre-B-ALL (six cases). BCR-ABL was detected by fluorescence in-situ hybridization at diagnosis in n=4/50 (8%) and was negative in n=46/50 (92%). CNS infiltration was found only in one patient (1/50, 4%) and the rest of the patients was negative for CNS infiltration (49/50, 96%). The cases were subdivided into three risk groups according to the risk stratification based primarily on clinical variables, immunophenotyping, detection of cytogenetic or molecular lesions, and early response to therapy . B-ALL cases were assigned as: low-risk group, n=6/50 (12%) cases (have no risk factor), intermediate-risk group n=40/50 (80%) cases (have one risk factor), and high-risk group n=4/50 (8%) cases (BCR-ABL positivity). After day 28 postinduction chemotherapy, 10/50 (20%) cases relapsed during the follow-up period; 4/50 (8%) cases were refractory, and 36/50 (72%) cases achieved complete remission.
|Table 1 Demographic and clinical and laboratory data of the studied groups|
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LEF1 gene expression at diagnosis and after 28 days of treatment
LEF1 gene expression was studied by RT-PCR and showed in ALL cases; mean 1.75±3.01, median=0.99 (0.14–14.54); in control group mean 0.38±0.26, median 0.33 (0.05–0.76). Strong statistically significant difference was detected in LEF1 expression between two groups (P=0.001; [Figure 1]).
|Figure 1 Dot blot showing lymphoid enhancer factor 1 gene expression in acute lymphoblastic leukemia cases and control group; median values are represented in the figure.|
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LEF1 gene expression in different ALL patients risk groups showed in the low-risk group: mean 0.60±0.37, median=0.39 (0.37–1.03); in the intermediate risk group: mean 1.03±0.85, median=0.83 (0.14–3.48); and in high risk group: mean 10.71±3.4, median=10.7 (6.88–14.54). Statistically significant positive correlation was detected between LEF1 gene expression and risk stratification (rs=0.43, P=0.031) where an increase in risk factors is associated with a similar increase in LEF1 gene expression [Figure 2]. Studying the association between LEF1 gene expression and clinical or immunophenotypic markers showed no statistically significant correlation between LEF1 and any of these parameters [Table 2].
|Figure 2 Dot blot showing lymphoid enhancer factor 1 gene expression in acute lymphoblastic leukemia cases risk groups; median values are represented in the figure.|
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|Table 2 Relation between lymphoid enhancer factor 1 gene expression and clinical or immunophenotypic markers in B-acute lymphoblastic leukemia cases|
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To study the correlation between LEF1 gene expression with different parameters, we classified ALL patients based on LEF1 median expression level (0.99) into low-expression group n=38 (LEF1 expression level of <0.99) and high-expression group n=12 (LEF1 expression level of >0.99) [Table 3]. We studied the relation between LEF1 gene expression with sex, age, white blood cells (WBC) count (at diagnosis, after 28 days of treatment), BCR-ABL, immunophenotyping, CNS infiltration, and clinical outcomes of treatment (after 28 days and after 6 months (discussed later). None of the parameters showed a statistically significant relation with LEF1 gene expression except for BCR-ABL and clinical outcome after 6 months. For BCR-ABL, all cases which showed low LEF1 expression (n=38) were negative for BCR-ABL n=38/38 (100%) while those with high LEF1 expression (n=12) were distributed as follows. BCR-ABL negative n=8/12 (66.7%) and BCR-ABL positive n=4/12 (33.3%). Statistically significant positive correlation was detected between LEF1 gene expression and BCR-ABL (χ2=6.884, P=0.05; [Table 3]).
|Table 3 Relation between lymphoid enhancer factor 1 gene expression and different parameters in B-acute lymphoblastic leukemia patients|
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High LEF1 gene expression associated with unfavorable treatment outcomes after 6 months treatment
For clinical outcome after 6 months, 36/50 cases achieved clinical remission, 10/50 cases relapsed, and 4/50 cases were refractory to treatment. Low LEF1 expressing groups were detected in 36 cases and were distributed as follows: clinical remission cases n=34/36 (89.5%), relapse cases n=2/36 (5.3%), and refractory cases n=2/36 (5.3%). However, high LEF1 expression groups were detected in 14 cases distributed as follows: clinical remission cases n=2/12 (16.7%), relapsed cases n=8/12 (66.7%), and refractory cases n=2/12 (16.7%). Statistically significant positive correlation was detected between LEF1 gene expression and clinical outcome after 6 months (χ2=12.695, P=0.003; [Table 3]).
Analyzing several prognostic variables in remission and non-remission ALL cases as age, sex, WBCs count (at diagnosis), immunophenotypic subtypes, BCR-ABL, and LEF1 gene expression are shown [Table 4]. Statistically significant positive correlation was detected between non-remission group and high LEF1 gene expression (Z=3.026, P=0.002; [Table 4]).
|Table 4 Prognostic variables in remission and nonremission groups after 6 months of treatment|
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| Discussion|| |
In the present study, we addressed the identification of LEF1 gene expression as a prognostic molecular parameter in adult B-ALL after 28 days and 6 months of treatment. We used quantitative RT-PCR to analyze LEF1 gene expression in 50 B-ALL cases and control group and we demonstrated a statistically significant higher LEF1 expression in cases compared with control (P=0.001). Increased LEF1 gene expression was demonstrated in several hematological and non-hematological malignancies ,,,,. Aberrant LEF1 gene expression contributed to tumorigenesis and invasion in the liver , prostatic , and cervical  cancer. Owing to the LEF1 role in lymphocytes’ development in the bone marrow, the untuned LEF1 gene expression was demonstrated in hematological malignancies as CLL ,, B-ALL , lymphomas ,, and AML ,, with LEF1 gene expression more pronounced in lymphoid malignancies .
We studied the LEF1 gene expression behavior at the time of presentation and after 28 days of treatment in relation to variable parameters. No significant differences were detected in LEF1 expression and age, sex, WBCs count (at diagnosis or after 28 days of treatment), clinical examination, immunophenotypic markers, and subtypes. These findings agreed with the Aly and colleagues study , where no significant correlation was detected between LEF1 gene expression and clinical characteristics. However, our study agreed partially with the Kuhnl et al.  study, where they showed no significant correlation between LEF1 expression and clinical, molecular features, or immunophenotypic subtypes except for positive correlation with CD20 and inverse correlation with myeloid markers. Of note, there were not enough patients’ samples for myeloid markers to allow correlation with LEF1 expression. Similarly, Guo and colleagues showed a correlation between high LEF1 gene expression with splenomegaly, LN enlargement, high WBC counts but not with age, sex, or BM blasts.
Further, we studied LEF1 gene expression in different stratified risk groups and showed a statistically significant association between LEF1 gene expression and risk stratification, where a higher LEF1 gene expression was detected in the high-risk group compared with comparable gene expression in both low-risk and intermediate-risk groups (P=0.05). This data, which agreed with several published studies ,,,, highlighted the importance of considering LEF1 expression as a parameter to risk stratifying B-ALL patients which certainly will be reflected in tailoring treatment protocols.
Studying the correlation between LEF1 gene expression with variable clinical parameters showed that BCR-ABL negative ALL cases were in the low LEF1 gene expression group. Additionally, all cases with BCR-ABL positive were in the high LEF1 expressing group. Our findings agreed with several published data where ALL patients with BCR-ABL positive expressed high LEF1 expression ,,. BCR-ABL was identified as an unfavorable marker of ALL ,,. A study conducted by Tsai et al.  suggested a mechanism in which BCR-ABL regulated internal ribosome entry sites-mediated translation of LEF1 gene in CML. This may help in understanding the BCR-ABL role with LEF1 gene in ALL pathogenesis.In the present study, the influence of LEF1 expression on the prognosis of B-ALL patients at day 28 and after 6 months follow-up period was analyzed. Patients with high LEF1 expression were compared with those with low LEF1 expression and showed no significant differences regarding the achievement of CR or frequency of primary refractory disease at day 28 after induction chemotherapy (P=0.089), while after 6 months of follow-up, patients with high LEF1expression, as compared with patients with low LEF1 expression, showed significantly lower remission rates with P value of 0.003. These data agreed with studies that showed that a high LEF1 gene expression was associated with poor disease-free survival ,,,.
It is worth noting that studying LEF1 in AML and MDS showed interesting findings, as LEF1 gene downregulation was associated with poor prognosis. Cytogenetically normal AML showed higher LEF1 gene expression with longer overall survival and event-free survival . Another study showed downregulation of LEF1 gene in CD34+ cells in MDS patients compared with normal controls . These finding can be explained in the context of LEF1 gene role in lymphopoiesis  along with LEF1 gene downregulation-impaired myeloid progenitors maturation, hence targeting LEF1 showed promising approaches in AML treatment ,.
In conclusion, high LEF1 gene expression at diagnosis may be used in identifying patients with a high risk of treatment failure, hence poor prognosis in B-ALL patients. Identification of prognostic markers in B-precursor ALL is important for the development of new molecular therapies and might also allow to improve risk-adapted treatment stratification for high-risk patients.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]