Background
Acute lymphoblastic leukemia (ALL) is a common pediatric malignant tumor characterized by the overproduction and accumulation of immature lymphoid cells and accounts for nearly 25% of all cancers among children younger than 15 years old [
1]. Although treatment options for ALL have significantly expanded in the last 10 years, 15–20% of ALL patients cannot achieve long-term remission, and relapse remains a challenge in treating pediatric ALL. Therefore, identifying novel prognostic markers is an urgent issue in ALL [
2,
3].
The Bmi-1 (B cell-specific moloney murine leukemia virus integration site 1) gene is a recognized oncogene of the Polycomb-group (PcG) family and was originally identified via retroviral insertional mutagenesis in
Eμ-c-myc transgenic mice that were infected with the Moloney murine leukemia virus [
4,
5]. The human Bmi-1 gene is located at chr.10p13, which has been shown to undergo rearrangements in malignant T cell lymphomas and chromosomal translocation in infant leukemia [
6‐
8]. Bmi-1 has been implicated to play a critical role in a number of biological pathways, including stem cell self-renewal [
9‐
11], DNA damage response [
12,
13], cell cycle [
14] and senescence [
15,
16].
Recently, Bmi-1 has been the focus of significant clinical interest because studies have demonstrated its upregulation in various malignancies such as non-small cell lung cancer [
17], breast cancer [
18,
19] and colorectal cancer [
20], as well as hematological malignancies including mantle cell lymphoma [
21], B cell non-Hodgkin’s lymphoma [
22] and acute myeloid leukemia (AML) [
23]. Abnormal overexpression of Bmi-1 has also been proposed to be involved in tumor invasion, metastasis, cancer therapy failure, and poor prognosis. For example, elevated Bmi-1 levels were observed in 38.7% (29/ 75) cases in nasopharyngeal carcinoma, and its overexpression is correlated to the patients’ survival rate: the 5-year overall survival rate was higher in the Bmi-1-negative group than that in the Bmi-1-positive group (84.2%
vs.47.6%) [
24]. Similar results were also observed in prostate cancer [
25,
26], chronic myeloid leukemia [
27,
28] and diffuse large B cell lymphomas [
29]. Although a relationship between Bmi-1 expression and the prognosis of patients with pediatric ALL has not been determined, the biological functions of Bmi-1 suggest that this protein could play a crucial role in the pathogenesis of pediatric ALL.
In consideration of the important role of Bmi-1 expression in tumorigenesis, the regulation of Bmi-1 is also thought to be essential. Some studies have revealed that Sall4 directly regulates Bmi-1 in both mouse models and human AML cell lines [
30,
31]. Consistent with this, a positive correlation between the expression of the Bmi-1 and Sall4 genes was also discovered in the placenta and umbilical cord blood groups [
32]. However, to the best of our knowledge, there are no data describing whether Sall4 contributes to the pathogenesis of leukemia.
The current study analyzed the expression and prognostic value of Bmi-1 in pediatric ALL and further elucidated the relationship between Bmi-1 and Sall4. Our results indicated that Bmi-1 was frequently upregulated in patients with ALL compared to healthy subjects, and patients with upregulated Bmi-1 at the time of diagnosis had a lower relapse-free survival (RFS) rate than patients who had lower Bmi-1 expression. In addition, Bmi-1 was observed to be positively correlated to Sall4a. Our data suggest that Bmi-1 could serve as a novel biomarker for the prognostic evaluation of patients with pediatric ALL.
Methods
Patients and samples
Tissue samples from 85 ALL patients before initiation of therapy, 19 ALL patients after therapy completion and 18 healthy subjects were collected between July 2006 and June 2009 at the Guangzhou Women and Children’s Medical Center of Guangzhou Medical University and the First Affiliated Hospital of Sun Yat-sen University. The demographics of the patients and healthy donors are summarized in the supplementary data (Additional file
1: Table S1 and Additional file
2: Table S2). Bone marrow was collected from the patients via bone marrow puncture either at the time of diagnosis or during follow-up after treatment. The research protocols were approved by the Ethics Committee of Guangzhou Women and Children’s Medical Center and the First Affiliated Hospital of Sun Yat-sen University. Written informed consent was obtained from the participants’ parents or guardians.
RNA isolation and quantitative reverse transcription polymerase chain reaction (qRT-PCR)
Total RNA was extracted from patient samples by using TRIzol reagent (Life Technologies, Grand Island, NY) according to the manufacturer’s protocol. The purity and integrity of total RNA were tested to assess the RNA quality. First, the OD ratios at A260/A280 and A260/A230 ranged between 1.8-2; second, the ratio of the 28S and 18S rRNA bands, which were assessed by denaturing gel electrophoresis, was approximately 2:1. For qRT-PCR, cDNA was synthesized from 100 ng total RNA using ABI TaqMan® Reverse Transcription Reagents (Thermo Fisher Scientific Inc., Waltham, MA USA). For first-strand cDNA synthesis, 100 ng of total RNA was used with random hexamer primers, 1× TaqMan RT buffer, 50 U of MultiScribe Reverse Transcriptase and 40 U of RNase inhibitor in a final volume of 20 μl. The mixture was incubated for 10 min at 25 °C, 30 min at 48 °C, and 5 min at 95 °C. Then, qPCR was performed using a Platinum® Quantitative PCR SuperMix-UDG kit (Thermo Fisher Scientific Inc.) according to the standard TaqMan® protocol. The qPCR was performed in a 20 μl PCR reaction containing l μl RT product, 1× PCR SuperMix-UDG, and 100 nM probe. The reactions were performed in a 96-well plate with an initial denaturation at 95 °C for 2 min followed by 40 cycles of 95 °C for 15 s and 60 °C for 30 s. All PCR reactions were run in triplicate with GAPDH used as an internal control. All the primers used are listed in Additional file
3: Table S3. The relative expression of each gene was calculated according to the comparative 2
−ΔΔCt method where ΔCt = Ct (target gene) – Ct (GAPDH) and ΔΔCt = ΔCt (sample) − ΔCt (control); the processed data are presented as the fold change of each mRNA.
Statistical analysis
All results were analyzed using proper statistical methods. Beyond the traditional descriptive statistical analyses, inferential analyses were performed using nonparametric methods. Differences in the mRNA expression between two groups (e.g., control vs primary, primary vs complete remission (CR), CR vs relapse) were analyzed using the Mann–Whitney U test for independent unpaired samples and the Wilcoxon test for paired samples. In instances of comparisons among more than two groups (e.g., samples divided into the low-risk group (LR), intermediate risk group (IR) and high-risk group (HR)), the Kruskal-Wallis test was performed first followed by Bonferroni’s correction for multiple comparisons. For categorical variables, the χ
2 or Fisher exact tests were used, and correlations were determined using the Spearman rank correlation coefficient(r). An analysis of RFS—defined as the time from CR to relapse—was performed according to the Kaplan–Meier method, and comparisons of outcomes among subgroups were performed by using the log-rank test. A two-sided P < 0.05 was considered to represent a statistically significant difference. All calculations were performed using GraphPad Prism 6.0 software.
Discussion
New biomarkers could be helpful in predicting treatment outcomes earlier and more precisely, which is of great interest to physicians and researchers in the field. This report describes for the first time that the proto-oncogene Bmi-1 is aberrantly expressed in the majority of primary ALL patients, and this expression is sharply decreased in CR patients after therapy. It has been shown that patients with elevated Bmi-1 expression at the time of diagnosis possessed a significantly higher likelihood of a poor response to prednisone and a higher clinical risk classification. Furthermore, we found that ectopic expression of Bmi-1 was closely associated with a poor prognosis for ALL patient survival, as patients with increased Bmi-1 expression had a significantly lower OS. Thus, this study not only extends our knowledge about the upregulation of this PcG protein but also verifies that Bmi-1 is an important and promising candidate tumor biomarker to predict the prognosis of pediatric patients with ALL.
There have been many studies that investigated the prognostic value of Bmi-1 expression in other types of tumors. Consistent with our results, research on ovarian cancer [
35], breast cancer [
36,
37], clear cell renal cancer [
38], laryngeal carcinoma [
39], cervical cancer [
40], and esophageal adenocarcinoma [
41] have reported an association between high Bmi-1 expression and an unfavorable prognosis. It has also been reported that high expression of Bmi-1 in AML cells is associated with an unfavorable prognosis [
42]. In brief, Bmi-1 is at an important lynchpin in more than ten different types of cancer, and a wide spectrum of malignancies implicate Bmi-1 as a suitable candidate for predicting outcomes.
However, Teruyuki et al. [
43] reported that Bmi-1 gene expression was lower in pediatric ALL and that there were no significant correlations between the Bmi-1 gene expression level in leukemic cells and clinical characteristics such as patient prognosis. These results were inconsistent with those of our study, which may be due to the different leukemia subtype and the limited number of samples. In Teruyuki’s study, the bone marrow-derived cells were obtained from 15 patients with pediatric precursor B-ALL that were sorted into different subsets by FACS, and CD19+ cells were treated as normal B cells for the analysis. In our study, we used mononuclear cells from the bone marrow instead of sorted normal B cells.
It has been well established that Bmi-1 is an essential regulator of cellular senescence [
16,
44] and that overexpression of Bmi-1 could prevent the development of senescence in proliferating cells by directly repressing the expression of p16
Ink4a and p19
Arf [
45]. Glucocorticoids then play a major role in apoptosis of hematopoietic cells including lymphocytes [
46], exposure to the glucocorticoid dexamethasone results in changes for the expression of genes associated with cellular senescence, for example, upregulating cell cycle-related genes p16 and p21 [
47]. Therefore, it is conceivable that Bmi-1 expression in ALL might counteract the effects of glucocorticoids on the cellular senescence pathway. Consequently, this could also explain why ALL patients with high Bmi-1 expression exhibited a poor response to prednisone.
Furthermore, our results also demonstrated that Sall4a and Sall4b, the two Sall4 isoforms, were constitutively expressed in pediatric ALL patients as well as in normal control subjects, although there was no statistically significant difference in these values between pediatric ALL samples and normal control samples. Similar to Bmi-1, Sall4 expression has been reported in numerous hematological malignancies, including myelodysplastic syndromes [
48], AML [
49,
50], chronic myelogenous leukemia [
51] and precursor B cell lymphoblastic lymphoma [
52,
53]. In addition, we found that the Bmi-1 gene expression levels showed a significantly positive correlation with Sall4a but not Sall4b. This result further verified the conclusion that a relationship between the Bmi-1 and Sall4 expression level in hematological malignancies, which was coincide with previously reports in AML samples [
30,
31]. In addition, these findings indicate that Sall4a and Sall4b may have different functions in pediatric ALL. However, one would expect that Sall4a expression would be higher in primary ALL cells, but this was not the case in our study. We speculate that this discrepancy could be due to the weak correlation between Bmi-1 and Sall4a expression (r = 0.2707) and additional factors involved in the complex regulation of Bmi-1 expression. In addition, Sall4a expression was slightly higher in primary ALL cells, but this increase was not significant. Sall4a is upstream of Bmi-1, and little difference was observed between individuals because of the amplification of the downstream signaling cascade. To better clarify this effect, more experiments with a larger cohort are needed. However, the precise molecular mechanism of Bmi-1 in pediatric ALL still remains unclear and requires further elucidation.
Conclusion
In summary, we provided evidence that Bmi-1 was significantly upregulated in pediatric ALL and that Bmi-1 overexpression was associated with a poor response to prednisone and a higher clinical risk. In addition, a significantly poorer outcome was observed in patients in the high Bmi-1 expression group. These findings suggest that Bmi-1 is an effective biomarker for predicting the prognosis of patients with pediatric ALL, and future studies should explore whether Bmi-1 could be a potential therapeutic target as well.
Acknowledgements
Not applicable.