Role of Matrix Metalloproteinase MMP-2, MMP-9 and Tissue Inhibitor of Metalloproteinase (TIMP-1) in Clinical Progression of Pediatric Acute Lymphoblastic Leukemia

DOI: https://doi.org/10.21203/rs.3.rs-566181/v1

Abstract

Background: Matrix metalloproteinases (MMPs) play a crucial role in cancer progression and metastasis, however their role in pediatric Acute lymphoblastic leukemia (ALL) is still unrevealed.

Methods: The diagnostic, prognostic and predictive value of tissue inhibitor of metalloproteinase (TIMP-1), MMP-2, MMP-9 and CD34+CD38- CSCs were assessed in bone marrow (BM) samples of 76 ALL children using Flow Cytometry analysis.

Results: There was a significant increase in TIMP-1 [1.52 (0.41-10) versus 0.91(0.6-1.12); respectively, P<0.001], and CSCs CD84+CD38- [1 (0.03-18.6) versus 0.3 (0.01-1.1), P<0.001] expression in ALL patients compared to controls. While there were no significant differences regarding MMP-2 and MMP-9 expression between the two groups. The sensitivity, specificity, AUC of MMP-2 were (80.3%, 53.3% and 0.568, P=0.404), and that of MMP-9 were (53.9%, 40% and 0.660, P=0.053). While that of TIMP-1 were (78.9%, 100% and 0.892, P<0.001), and that of CSCs CD34+ CD38- were (78.9%, 73.3% and 0.855, P<0.001). There was a significant association between MMP-2 overexpression and MRD at day-15, increased BM blast cell count at diagnosis and at day-15, (P=0.020, P=0.047 and P=0.001). Increased TIMP-1 expression associated with the high-risk disease (P<0.001), increased BM blast cell count at diagnosis and at day-15 (P=0.033 and P=0.001), as well as MRD at day 15 and day 42 (P<0.001 for both). CD34+CD38- CSCs associated with MRD at day-15, increased BM blast cell count at diagnosis and at day-15 (P=0.015, P=0.005 and P=0.003). TIMP-1 overexpression associated with shorter DFS and OS rates (P=0.009 and P=0.048). Multivariate logistic regression analysis showed that both TIMP-1 [OR: 4.224, P=0.046], and CD34+CD38- CSCs [OR: 6.873, P=0.005] are independent diagnostic factors for pediatric ALL.

Conclusion: TIMP-1 and CD34+CD38- CSCs could be useful independent diagnostic markers for pediatric ALL. Also, TIMP-1 is a promising prognostic marker for poor outcome of the patients.

Introduction

Acute lymphoblastic leukemia (ALL) is the most common hematological malignancy in children, and it is a leading cause of cancer-related death in these age-group patients [1]. The ALL is caused by neoplastic transformation of cells of the lymphoid lineage, which leads to accumulation of abnormal, immature and poorly differentiated lymphocytes or rarely natural killer cells in the peripheral blood, due to bone marrow (BM) abnormality [2]. There are 85% of pediatric ALL originates from B-precursors, and the remaining15% are of T-cell origin [3]. Despite the advancement achieved in the diagnosis and treatment strategy for pediatric ALL in the last few years, that leads to improving the survival as well as the cure rates of ALL patients [4]. However, the relapse rate is 15% for childhood B‑ALL, and still the prognosis is unfavorable especially for high-risk group ALL patients [5]. The increasing relapse rate could be due to treatment failure which results from the development of multiple drug resistance, or abnormal expression of metabolizing enzymes [6].

The detection of minimal residual disease (MRD) after treatment is the main predictor of disease relapse in ALL [7]. It is produced by the development of leukemic cells that can resist chemotherapy and consequently mediate treatment failure. These leukemic cells can proliferate and survive through their interaction with the BM mesenchymal stromal cells (MSCs), which are the main constituent of BM microenvironment (BMM). This interaction is mediated through the different growth cytokines and growth factors which can support the growth and proliferation of the resistant leukemic cells [7, 8]. A Growing body of evidence suggests that leukemia stem cells (LSCs) is a subset of cancer cells that maintain chemo-resistance and relapse [9]. These CSCs were reported in acute myeloid leukemia (AML) and chronic myeloid leukemia (CML), but their role in ALL is still unclear [10, 11]. Many recent studies reported mutational and phenotypic changes that induce LSC-like properties, which were supported by BMM [11, 12]. These phenotypic changes included upregulation of CD34, CD133, P-glycoprotein and BCRP/ABCG2, as well as downregulation of CD38 [11].

The BBM also supports the progression of cancer cells through the BMM-derived proteases such as matrix metalloproteinases (MMPs) [13]. The MMPs is a large family of 24 zinc‑dependent endopeptidases that regulate the composition of extracellular matrix (ECM), and have a role in hematopoietic stem cell (HSC) mobilization and function [14]. They can be produced by tumor [15] or stromal cells [16], where they have a critical role in the degradation of ECM components, allowing progression, invasion and metastasis of tumor cells [17]. A unique example of MMPs is MMP-2 and MMP-9 which have a similar catalytic domain among MMPs. They have the fibronectin repeat domain, which can bind and degrade type IV collagen and gelatin. MMP-9 additionally has a type V collagen-like domain [18].

Under normal physiological conditions, the proteolytic activity of MMPs is regulated by the inhibiting activity of the tissue inhibitors of metalloproteinases (TIMPs), which are formed of four enzymes (TIMP-1 to TIMP-4) [19, 20]. Though TIMPs seem to have a protective role in cancer metastasis, however recent reports showed that TIMP-1 overexpression is associated with poor survival and early recurrence in multiple solid tumors including breast and prostate carcinoma [21, 22]. On the other hand, TIMP-3 is downregulated in metastatic setting and considered as a tumor suppressor gene [23, 24]. Indeed, the role of MMPs in cancer progression is not yet clear especially in ALL, and their deregulation could be a potential target for cancer prognosis and treatment [25]. Therefore, the aim of the current study was to assess the role of MMP-2, MMP-9 and its inhibitor TIMP-1 in pediatric ALL regarding their diagnostic, prognostic and predictive value. In addition, investigate their relation to CD34+CD38 CSCs expression and its implication on cancer progression and outcome. This was performed through correlating TIMP-1, MMP-2, MMP-9 and CD38+CD34CSCs expression levels with the relevant clinic-pathological features of the patients, survival rates and response to treatment. We hypothesized that this will allow to predict patients’ outcome, and find a potential targeted therapy for those patients, based on the expression levels of MMP-2, MMP-9, TIMP-1 and CD34+CD38 CSCs.

Patients And Methods

This prospective cohort study included 76 children with ALL, who were presented to the pediatric out patients’ clinic, National Cancer Institute (NCI), Cairo University during the period from March 2015 to January 2017. The control group included 16 age and sex matched healthy individuals who were volunteers for bone marrow transplantation. All patients were subjected to full clinical examination, laboratory work-up, molecular testing, immunophenotyping (IPT), and cytogenetic analysis for confirmation of ALL according to the French-American-British (FAB) and World Health Organization (WHO) criteria [26]. Follow-up of the patients was carried out for nearly 3.5 years. Patients’ response to treatment was evaluated through morphologic BM examination and IPT for detection of minimal residual disease (MRD) at day 15 and day 42.

Complete remission was defined as achieving; 1) lower than 5% blasts in the BM, 2) Normal maturation of all BM cells, 3) No extra-medullary disease, 4) absolute neutrophil count (ANS) ≥1,000/μl, 5) Platelets count ≥100,000/μl, 6) Transfusion independent, and 7) MRD < 0.01, for at least four weeks.

Relapse was defined by the presence of either BM lymphoblast ≥5%, reappearance of circulating leukemic blasts in the Peripheral blood (PB), development of extra-medullary leukemia and/or MRD ≥ 0.01 [27].

Sample acquisition

Bone marrow (BM) aspirates were drawn from all patients by iliac or tibial puncture under complete aseptic conditions. The samples (1 ml) were collected on anticoagulant (EDTA) tubes and processed within few hours for morphologic, molecular and cytogenetic assessment. The IPT was performed on BM blast cells using a comprehensive panel including CD45, CD13, CD33, MHC CLASSII, CD34, CD11C, CD64, CD36, CD14, CD4, CD8, CD7, CD2, CD1, CD56, CD3, CytCD3, CD5, CD19, CD10, CD22, CD20, Cytμ, Cyt CD79α, CD34, CD117 (Bechman Coulter, Maiami, USA), kappa and Lambda (Dako USA, Capinteria, CA).

Assessment of Matrix Metalloproteinase (MMP-2, MMP-9), TIMP-1 and CD34+CD38- CSCs

Bone marrow aspiration samples were assessed for MMP-2, MMP-9 and TIMP by Flow Cytometry analysis using anti-human monoclonal antibodies for MMP-9 FITC, MMP-2 PE and TIMP-1 FITC (R&D system, Minneapolis, MN 55413, cat. no. IC9111F, IC9111023P and IC970F; respectively), according to manufactures’ instructions (Figure 1A-F).

Stem cells were evaluated in the context of CD34+CD38- population gated on CD45 low expression and CD19+ cells. The whole blood staining method was performed by permeabilization, fixation and intracellular staining using anti-human monoclonal antibodies for CD34 PE-cy5 and CD38 PC7 according to manufacturer’s instructions (Beckman Coulter, Inc., Figure 1G, H).

Viability was done using the 7 AAD test, of which viability more than 90% was accepted for the analysis. FITC-conjugated anti-mouse IgG2 and PE-conjugated anti-mouse IgG2 isotype-matched control were used as a negative control.

Assessment of the studied markers was performed using Multicolor flow cytometry (Beckman Coulter Navios, USA), with the acquisition of at least 10,000 events. Proper gating of the malignant population was then created for analysis of the expression of the studied parameters. Analysis was done on Winlist version 6. Flow-cytometer analysis software (Verity, Topsham, ME). The specific median fluorescence intensity (MFI) of each monoclonal antibody used for each sample was calculated by subtracting the background MFI value produced by isotype-matched control from the MFI value generated by the specific antibody.

Statistical Analysis

Statistical analysis was performed using IBM© SPSS© Statistics version 22 (IBM© Corp., Armonk, NY, USA). Numerical data were expressed as median and range according to the performed normality tests. Qualitative data were expressed as frequency and percentage. The relation between qualitative variables was assessed using Chi-square or Fisher’s exact test as appropriate. Comparison between groups was done using Mann-Whitney test. The Area under the receiver operating curve (ROC) was calculated to investigate the best cut-off value, sensitivity and specificity for the diagnosis of ALL. Survival analysis was done using Kaplan-Meier test. All tests were two-tailed. A p-value < 0.05 was considered significant.

Results

Clinical Features of the Patients

The current study included 76 patients, of them 47 (61.8%) were males and 29 (38.2%) were females, with a median age of 6.5 (range: 1-18) years. The median BM blast at diagnosis was 87%, with a range of 48% to 98%, while it was 0 (range: 0-77%) at day 15 of treatment. The IPT analysis showed that 49 (64.5%) patients had (Pre-B) phenotype, 21 (27.6%) had common B, and 6 (7.9%) patients had T-ALL phenotype. Patients were classified according to risk stratification of ALL [28] into low risk (LR) patients in 26 (34.2%), standard risk (SR) in 19 (25.0%) patients, and high risk (HR) in 31 (40.8%) patients. Regarding MRD at day 15, there were 22 (30.1%) patients had MRD<0.01, and 51 (69.9%) patients had MRD ≥0.01. While for MRD at day 42, there were 31 (57.4%) patients had MRD<0.01, and 23 (42.6%) patients had MRD ≥0.01. Complete remission was achieved in 67 (88.2%) patients, and DNA index was favorable (>1) in 10/76 (13.2%) patients. There were 53 (69.7%) patients presented with hepatomegaly, 61 (80.3%) had splenomegaly, 37 (48.7%) had lymphadenopathy, 8 (10.5%) patients had testicular affection, and 4 (5.3%) patients had central nervous system (CNS) involvement. (Table 1).

Expression levels of TIMP-1, MMP-2, MMP-9 and CSCs CD38+CD34- in ALL patients

There was a significant increase in TIMP-1 expression in ALL patients compared to control subjects [1.52 (0.41-10) versus 0.91(0.6-1.12); respectively, P<0.001], while there were no significant differences between ALL patients and control group regarding the expression levels of MMP-2 [1.12 (0.21-3.5) versus 1.08 (0.42-2.04); respectively, P= 0.404], and MMP-9 [1.12 (0.38-4.07) versus 0.84 (0.57-1.48); respectively, P=0.053]. on the other hand, there was a significant increase in CSCs CD84+CD38- in ALL patients [1 (0.03-18.6)] compared to control group [0.3 (0.01-1.1), P<0.001, Figure 2].

Identification of ALL patients using TIMP-1, MMP-2, MMP-9 and CSCs CD34+CD38-

ROC curve analysis was performed to evaluate the diagnostic power of the studied markers to detect ALL patients. The sensitivity, specificity, AUC of MMP-2 were (80.3%, 53.3% and 0.568; respectively) at a cutoff value of 0.841 (P=0.404), and that of MMP-9 were (53.9%, 40% and 0.660) at a cutoff value of 1.07 (P=0.053). While the sensitivity, specificity, AUC of TIMP-1 were (78.9%, 100% and 0.892; respectively) at a cutoff value of 1.133 (P<0.001), and that of CSCs CD34+ CD38- were (78.9%, 73.3% and 0.855; respectively) at a cutoff value of 0.55 (P<0.001, Figure 3A, B). Patients were classified into low-expression and overexpression of the assessed markers according to the appropriate cutoff values obtained by the ROC curve (Table 2). 

Association between MMP-2, MMP-9 expression and the clinical features of the patients

Patients with MMP-2 overexpression showed a significant increase in the BM blast cell count at diagnosis and at day-15 of treatment, as well as a significant increase in MRD at day-15, compared to those with MMP-2 low expression (P=0.047, P=0.001 and P=0.020; respectively). There was no significant association between MMP-9 expression levels and the assessed relevant clinic-pathological features of the patients (Table 3).

On the other hand, increased TIMP-1 expression associated significantly with increased BM blast cell count at diagnosis and at day-15 of treatment (P=0.033 and P=0.001; respectively). Also, TIMP-1 associated significantly with the high-risk stratification of the patients, as out of 60 patients who had TIMP-1 overexpression, 30 (50.0%) patients had high-risk disease, 17 (28.3%) had standard risk, and 13 (21.7%) patients had low-risk disease (P<0.001). There was a significant association between increased TIMP-1 expression and increased MRD at day 15 and day 42 (P<0.001 for both). Regarding the MMP-9/TIMP-1 ratio, it was observed that all assessed ALL patients who did not achieve complete remission (CR), showed MMP-9/TIMP-1 lower than 0.96, however this association is of a borderline significance (P=0.05, Figure 3C).

Regarding CD34+CD38- CSCs, it associated significantly with increased BM blast cell count at diagnosis and at day-15 of treatment (P=0.005 and P=0.003; respectively). Also, it associated significantly with increased MRD at day-15 (P=0.015, Table 4).

Correlation among MMP-2, MMP-9, TIMP-1 and CD34+CD38- cells expressions

The present results showed that there was no significant correlation among MMP-2, MMP-9, TIMP-1and CD34+CD38- cells expressions under normal condition in control subjects (Figure 3D). However, in ALL pediatric patients, there was a significant correlation between TIMP-1 expression and MMP-2 (r=0.325, P=0.004), as well as MMP-9 (r=0.326, P=0.004). Similarly, CD34+CD38- cells correlated significantly with MMP-2 (r=0.736, P<0.001), MMP-9 (r=0.379, P=0.001), and TIMP-1 (r=0.567, P<0.001, Figure 3E).

Disease-free survival and overall survival rates of ALL patients

There was a significant association between TIMP-1 overexpression and shorter DFS and OS rates of ALL patients (P=0.009 and P=0.048; respectively). however, no significant association detected between the expression of MMP-2, MMP-9, CD34+CD38- cells and survival (DFS, OS) rates of the patients (P>0.05, Figure 4).

Univariate and Multivariate logistic regression analysis for diagnosis of ALL

Univariate analysis revealed that the incidence of pediatric ALL associated significantly with increased expression of TIMP-1 [OR: 8.625, P=0.001], and CD34+CD38- CSCs [OR: 10.312, P<0.001], while there was no significant association with MMP-2 and MMP-9 expression levels. Multivariate logistic regression analysis showed that both TIMP-1 [OR: 4.224, P=0.046], and CD34+CD38- CSCs [OR: 6.873, P=0.005] are independent diagnostic factors for pediatric ALL (Table 5).

Discussion

Matrix metalloproteinases (MMPs) and their endogenous inhibitors play a crucial role in the invasion and metastasis of solid tumors, however their role in hematological malignancies especially in ALL is still unrevealed. Moreover, according to the extensive study performed by Kuittinen et al [29], they concluded that the biological characteristics of MMPs varies between adult and pediatric ALL.

The current study demonstrated a significant increase in TIMP-1 and CD84+CD38- CSCs expression levels in ALL pediatric patients compared to the control group, while there were no significant differences between ALL patients and the control group regarding the expression levels of MMP-2 and MMP-9. However, our data regarding MMP-9 expression are not in agreement with Lin et al [30], who demonstrated in their study that the expression levels of MMP-9 in the BM of AML and ALL patients were lower than those in the control group, in addition, MMP-9 has no significant influence on patients’ response to treatment. On the other hand, Verma et al [31], proposed that leukemia cells in B-ALL, may remodel the BMM via the secretion of certain factors inducing the expression of MMP-9, and therefore, increasing tumor’s invasiveness. Indeed, the certain role of MMPs and TIMPs in ALL is not yet clear, especially in the pediatric population who have an extremely a heterogeneous nature of cancer [32]. In an attempt to investigate their diagnostic roles for childhood ALL, the present results demonstrated that TIMP-1 achieved the highest specificity (100%), and AUC (0.892) with a sensitivity of 78.9% for diagnosing pediatric patients with ALL. The TIMP-1 was followed by CD84+CD38- CSCs expression which achieved the same sensitivity as TIMP-1 (78.9%), with a specificity of 73.3% and AUC (0.855). However, MMP-9 and MMP-2 did not show a significant diagnostic power for ALL. Furthermore, these data were confirmed by the multivariate analysis which showed that both TIMP-1 and CD34+CD38- CSCs expression levels are independent diagnostic factors for pediatric ALL.

The current study revealed that patients with MMP-2 overexpression showed a significant increase in the BM blast cell count at diagnosis and at day-15 of treatment, as well as a significant increase in MRD at day-15 compared to those with MMP-2 low-expression. While there was no significant association between MMP-9 expression levels and the assessed relevant clinic-pathological features of the patients including the extramedullary infiltration, risk stratification of the patients, response to treatment, and immunophenotyping of ALL. These data are comparable to that observed by Scrideli et al [33], who reported a higher expression level of MMP-9 associated significantly with low-risk group patients, and absence of extramedullary infiltration. In contrast to these results, Schneider et al [34], demonstrated that MMP-9 was significantly increased in patients with peripheral infiltration than in patients who had no sign of infiltration. This discrepancy in results may be ought to different clinical features, stages, genetic backgrounds and treatment strategies that varied between patients, however further studies are required to validated these data. In line with our results, Schneider et al [34], found no significant difference between MMP-2, MMP-9 and TIMP-1 expression in T-lineage ALL or B-lineage ALL. however, many studies reported a significant association between MMP-2 and T-ALL phenotype [29, 33]. This difference might be due to the small number of patients with T-ALL phenotype included in the current study.

In concordance with our results regarding the MMP-9/TIMP-1 ratio, Scrideli et al [32], observed no significant association between the MMP-9/TIMP-1 ratio and survival rate or the clinico-pathological features of the patients. However, the present results demonstrated that all assessed ALL patients who did not achieve complete remission (CR), showed a decreased MMP-9/TIMP-1 lower than 0.96, though this association is of a borderline significance (P<0.05).

It had been reported that relapsed ALL is the main health problem affecting children with leukemias, and it is indicated by the presence of MRD during therapy [35]. In this context, the present data showed that higher expression levels of MMP-2, TIMP-1 and CD34+CD38- CSCs associated significantly with increased MRD at day-15. Also, they were associated with increased BM leukemia blast cells at diagnosis and at day-15 of treatment. Additionally, increased TIMP-1 expression associated significantly with MRD at day-42, and with high-risk stratification of the patients, which could be a potential prognostic factor for relapse. Moreover, it had been proved by many recent studies the important role of CD34+CD38- CSCs in ALL relapse and chemo-resistance [36-38].

Furthermore, the current study showed that there was no significant correlation among MMP-2, MMP-9, TIMP-1and CD34+CD38- cells expressions under normal conditions in control subjects. However, in ALL pediatric patients, there was a significant correlation between TIMP-1 expression and MMP-2, as well as MMP-9. Similarly, CD34+CD38- CSCs correlated significantly with MMP-2, MMP-9, and TIMP-1 expression. This observation indicates that there is a disruption occurred in the physiological balance between MMPs and TIMPs, which lead to matrix proteolysis that associated with different pathological diseases including cancer progression and metastasis [32]. Also, the finding of the significant correlation between CD34+CD38- CSCs and the assessed markers could be explained by the data observed by Verma et al [31], who reported that B-ALL cells can cause remodelling in the BMM by stimulating MMP-9 expression in the MSCs through the release of TNFα.

Regarding the survival analysis of the patients, there was a significant association between TIMP-1 overexpression and shorter DFS and OS rates of ALL patients. however, no significant association detected between the expression of MMP-2, MMP-9, CD34+CD38- cells and DFS or overall survival rates. These results are in agreement with Scrideli et al [33], who demonstrated that higher expression level of TIMP-1 gene in leukemia cells associated significantly with lower 5-year event free-survival by univariable and multivariable analysis, while there was no significant effect of MMP-9 and MMP-2 on survival rates of the assessed ALL children. Also, Schneider et al [34], reported no significant impact of surface MMP-9 expression on the overall survival rate of the patients, while its secreted form associated with a lower overall survival rate. On the other hand, many recent published studies reported that MMP-9- positive blast cells associated significantly with the invasive potential of ALL cells, and the poor survival rates of the patients [35, 20].

According to the previous discussion, we can conclude that the exact prognostic and predictive role of MMP-2, MMP-9 and TIMP-1 is not well understood, and it is still a debatable issue in the literature. However, our results demonstrated a significant association of MMP-2, TIMP-1 and CD34+CD38- CSCs with MRD, which could be considered potential markers for relapse. Regarding their diagnostic role, the current study provides evidence that TIMP-1 and CD34+CD38- CSCs could be considered as useful independent diagnostic markers for pediatric ALL. In addition, TIMP-1 is a promising prognostic marker for high-risk disease, short overall and disease-free survival rates and consequently, poor outcome of the patients.

Declarations

Compliance with ethical standards

The study protocol was approved by the ethical committee of NCI, Cairo university, which was in accordance to Helsinki guidelines. A written informed consents were obtained from parents or legal guardians of all participated patients and control subjects before enrolment in the study.

Conflict of interest

All authors declare that there was no conflict of interest.

References

  1. Hunger SP, Mullighan CG (2015) Redefining ALL classification: toward detecting high-risk ALL and implementing precision medicine. Blood 125:3977–3987
  2. Shafat MS, Gnaneswaran B, Bowles KM, Rushworth SA (2017) The bone marrow microenvironment–Home of the leukemic blasts. Blood Rev 31:277–286
  3. Pui CH, BehmFG SinghB et al (1990) Heterogeneity of presenting features and their relation to treatment outcome in120children with T cell acute lymphoblastic leukemia. Blood 75(1):174–179
  4. Somers K, Evans K, Cheung L, Karsa M, Pritchard T et al (2020 Jun) Effective targeting of NAMPT in patient-derived xenograft models of high-risk pediatric acute lymphoblastic leukemia. Leukemia 34(6):1524–1539
  5. Tran TH, Harris MH, Nguyen JV, Blonquist TM, Stevenson KE, Stonerock E, Asselin BL, Athale UH, Clavell LA, Cole PD et al (2018) Prognostic impact of kinase–activating fusions and IKZF1 deletions in pediatric high–risk B–lineage acute lymphoblastic leukemia. Blood Adv 2:529–533
  6. Huang FL, Liao EC, Li CL, Yen CY, Yu SJ. Pathogenesis of pediatric B-cell acute lymphoblastic leukemia: Molecular pathways and disease treatments. Oncol Lett. 2020 Jul;20(1):448–454. doi: 10.3892/ol.2020.11583
  7. Paganin M, Fabbri G, Conter V, Barisone E, Polato K, Cazzaniga G et al (2014) Postinduction minimal residual disease monitoring by polymerase chain reaction in children with acute lymphoblastic leukemia. J Clin Oncol 32:3553–3558
  8. Lane SW, Scadden DT, Gilliland DG (2009) The leukemic stem cell niche: current concepts and therapeutic opportunities. Blood 114:1150–1157
  9. Yu Y, Ramena G, Elble RC (2012) The role of cancer stem cells in relapse of solid tumors. Front Biosci 4:1528–1541
  10. Chu S, McDonald T, Lin A, Chakraborty S, Huang Q, Snyder DS et al (2011) Persistence of leukemia stem cells in chronic myelogenous leukemia patients in prolonged remission with imatinib treatment. Blood 118:5565–5572
  11. Kihira K, Chelakkot VS, Kainuma H, Okumura Y, Tsuboya N et al (2020 Dec) Close interaction with bone marrow mesenchymal stromal cells induces the development of cancer stem cell-like immunophenotype in B cell precursor acute lymphoblastic leukemia cells. Int J Hematol 112(6):795–806. doi:10.1007/s12185-020-02981-z. Epub 2020 Aug 30. PMID: 32862292
  12. Brennan L, Narendran A. Cancer Stem Cells in the Development of Novel Therapeutics for Refractory Pediatric Leukemia. Stem Cells Dev. 2019 Oct 1;28(19):1277–1287. doi: 10.1089/scd.2019.0035
  13. Christopherson KW, Cooper S, Hangoc G, Broxmeyer HE (2003) CD26 is essential for normal G-CSF-induced progenitor cell mobilization as determined by CD26–/– mice. Exp Hematol 31:1126–1134
  14. Klein G, Schmal O, Aicher WK (2015) Matrix metalloproteinases in stem cell mobilization. Matrix Biol 44–46:175–183
  15. Mehner C, Hockla A, Miller E, Ran S, Radisky DC, Radisky ES (2014) Tumor cell-produced matrix metalloproteinase 9 (MMP-9) drives malignant progression and metastasis of basal-like triple negative breast cancer. Oncotarget 5:2736–2749
  16. Reggiani F, Labanca V, Mancuso P, Rabascio C, Talarico G, Orecchioni S et al (2017) Adipose progenitor cell secretion of GM-CSF and MMP-9 promotes a stromal and immunological microenvironment that supports breast cancer progression. Cancer Res 77:5169–5182
  17. Rydlova M, Holubec L Jr, Ludvikova M Jr, Kalfert D, Franekova J, Povysil C et al (2008) Biological activity and clinical implications of the matrix metalloproteinases. Anticancer Res 28:1389–1397
  18. Hsiao YH, Su SC, Lin CW, Chao YH, Yang WE, Yang SF (2019 Dec) Pathological and therapeutic aspects of matrix metalloproteinases: implications in childhood leukemia. Cancer Metastasis Rev 38(4):829–837
  19. Kapoor C, Vaidya S, Wadhwan V, Hitesh, Kaur G, Pathak A (2016) Seesaw of matrix metalloproteinases (MMPs). J Cancer Res Ther 12(1):28
  20. Egeblad M, Werb Z (2002) New functions for the matrix metalloproteinases in cancer progression. Nat Rev Cancer 2:161–174
  21. Dos Reis ST, Viana NI, Iscaife A, Pontes-Junior J, Dip N, Antunes AA et al (2015) Loss of TIMP-1 immune expression and tumor recurrence in localized prostate cancer. Int Braz J Urol 41(6):1088–1095
  22. Dechaphunkul A, Phukaoloun M, Kanjanapradit K, Graham K, Ghosh S, Santos C et al. Prognostic significance of tissue inhibitor of metalloproteinase-1 in breast cancer. Int J Breast Cancer. 2012; 2012:290854
  23. Rettori MM, De carvalho AC, Bomfim longo AL, De oliveira CZ, Kowalski LP, Carvalho AL et al (2013) Prognostic significance of TIMP3 hypermethylation in post-treatment salivary rinse from head and neck squamous cell carcinoma patients. Carcinogenesis 34(1):20–27
  24. Jackson HW, Defamie V, Waterhouse P, Khokha R (2017 Jan) TIMPs: versatile extracellular regulators in cancer. Nat Rev Cancer 17(1):38
  25. Winer A, Adams S, Mignatti P. Matrix metalloproteinase inhibitors in cancer therapy: turning past failures into future successes. Molecular cancer therapeutics. 2018 Jun 1;17(6):1147-55
  26. Daniel AA, Attilio O, Robert H, J¨urgen T, Michael J. Borowitz M, Michelle M, Le Beau, Clara DB, Mario C, James WV (2016) Revision to the World Health Organization classification of myeloid neoplasms and acute Leukemia:Blood 127(20):2391–2405
  27. Campana D (2009) Minimal Residual Disease in Acute Lymphoblastic Leukemia. Semin Hematol 46(1):100–106
  28. Pui CH, Campana D, Pei D et al (2009) Treating childhood acute lymphoblastic leukemia without cranial irradiation. The New England Journal of Medicine 360(26):2730–2741
  29. Kuittinen O, Savolainen ER, Koistinen P, Möttönen M, Turpeenniemi-Hujanen T (2001 Feb) MMP-2 and MMP-9 expression in adult and childhood acute lymphatic leukemia (ALL). Leuk Res 25(2):125–131
  30. Lin LI, Lin DT, Chang CJ, Lee CY, Tang JL, Tien HF (2002 Jun) Marrow matrix metalloproteinases (MMPs) and tissue inhibitors of MMP in acute leukaemia: potential role of MMP-9 as a surrogate marker to monitor leukaemic status in patients with acute myelogenous leukaemia. Br J Haematol 117(4):835–841
  31. Verma D, Zanetti C, Godavarthy PS, Kumar R, Minciacchi VR et al (2020 Jun) Bone marrow niche-derived extracellular matrix-degrading enzymes influence the progression of B-cell acute lymphoblastic leukemia. Leukemia 34(6):1540–1552
  32. Kaczorowska A, Miękus N, Stefanowicz J, Adamkiewicz-Drożyńska E (2020) Selected Matrix Metalloproteinases (MMP-2, MMP-7) and Their Inhibitor (TIMP-2) in Adult and Pediatric Cancer. Diagnostics (Basel). Jul 31;10(8):547
  33. Scrideli CA, Cortez MA, Yunes JA, Queiróz RG, Valera ET et al (2010 Jan) mRNA expression of matrix metalloproteinases (MMPs) 2 and 9 and tissue inhibitor of matrix metalloproteinases (TIMPs) 1 and 2 in childhood acute lymphoblastic leukemia: potential role of TIMP-1 as an adverse prognostic factor. Leuk Res 34(1):32–37
  34. Schneider P, Costa O, Legrand E, Bigot D, Lecleire S, Grassi V, Vannier JP, Vasse M (2010 Jan) In vitro secretion of matrix metalloprotease 9 is a prognostic marker in childhood acute lymphoblastic leukemia. Leuk Res 34(1):24–31
  35. Madhusoodhan PP, Carroll WL, Bhatla T (2016 Jul) Progress and Prospects in Pediatric Leukemia. Curr Probl Pediatr Adolesc Health Care 46(7):229–241
  36. Kihira K, Chelakkot VS, Kainuma H, Okumura Y, Tsuboya N, Okamura S, Kurihara K, Iwamoto S, Komada Y, Hori H (2020 Dec) Close interaction with bone marrow mesenchymal stromal cells induces the development of cancer stem cell-like immunophenotype in B cell precursor acute lymphoblastic leukemia cells. Int J Hematol 112(6):795–806
  37. Brennan L, Narendran A. Cancer Stem Cells in the Development of Novel Therapeutics for Refractory Pediatric Leukemia. Stem Cells Dev. 2019 Oct 1;28(19):1277–1287. Mudry
  38. Fortney RE, York JE, Hall T, Gibson BM (2000) LF. Stromal cells regulate survival of B-lineage leukemic cells during chemotherapy. Blood 96:1926–1932

Tables

Table 1: Clinical characteristics of ALL patients

 Patients’ characteristics

Frequency (%)

TLC (median & range)×109/L

22.5 (0.8- 325)

BM blast at diagnosis (median & range)

87 (48 -98)%

BMA- day 15 (median & range)

0 (0-77%)%

Age

  mean± SD

8.68 ±5.4 years

 

  median (range)

6.5 (1-18) years

gender

male

 

female

29 (38.2%)

Imunophenotype

T ALL

6 (7.9%)

preB ALL

49 (64.5%)

Common B

21 (27.6%)

Risk stratification

LR

26 (34.2%)

SR

19 (25.0%)

HR

31 (40.8%)

MRD-day 15

<0.01

22 (30.1%)

≥0.01

51 (69.9%)

MRD-day 42

<0.01

31 (57.4%)

≥0.01

23 (42.6%)

CR

no

9 (11.8%)

yes

67 (88.2%)

DNA index

standard

66 (86.8%)

favorable

10 (13.2%)

CD34

negative

40 (52.6)

positive

36 (47.4%)

lymphadenopathy

negative

39 (51.3%)

positive

37 (48.7%)

Testicular

negative

68 (89.5%)

positive

8 (10.5%)

CNS

negative

72 (94.7%)

positive

4 (5.3%)

Hepatomegaly

negative

23 (30.3%)

positive

53 (69.7%)

Splenomegaly

negative

15 (19.7%)

positive

61 (80.3%)


Table 2:
ROC curve analysis of TIMP1, MMP2, MMP9 and CD34+CD38- stem cells for identification of ALL patients                                                                  

Variable(s)

Area

cutoff

sensitivity

specificity

P value

95% Confidence Interval

Lower

Upper

MMP9

0.660

1.07

53.9%

40%

0.053

0.511

0.808

MMP2

0.568

0.841

80.3%

53.3%

0.404

0.414

0.723

TIMP1

0.892

1.133

78.9%

100%

P<0.001

0.827

0.957

CD34+ CD38- CSCs

0.855

0.55

78.9%

73.3%

P<0.001

0.759

0.951


Table 3:
Association between MMP9, MMP2 and clinical features of the patients

 

MMP9

P value

MMP2

P value

 

lowexpression

overexpression

Lowexpression

Overexpression

Age (years)

6.5 (1-18)

6 (1-17)

0.584

8 (1-14)

6 (1-18)

0.911

TLC (×109/L)

15.5 (2.8-325)

27 (0.8-283)

0.125

18 (3-114)

25 (0.8-325)

0.928

BM blast at diagnosis

85 (63-93)%

87 (60-98)%

0.156

82.5 (63-98)%

87 (60-96)%

0.047

BM blast-day-15

0 (0-40)%

0 (0-77)%

0.739

0 (0-4)%

1 (0-77)%

0.001

gender

           

male

21 (61.8%)

34 (59.6%)

0.842

13 (52.0%)

42 (63.6%)

0.344

female

13 (38.2%)

23 (40.4%)

 

12 (48.0%)

24 (36.4%)

 

Phenotype

           

T-ALL

4 (15.4%)

2 (4.0%)

0.091

3 (15.8%)

3 (5.3%)

0.188

Pre B-ALL

13 (50.0%)

36 (72.0%)

13 (68.4%)

36 (63.2%)

Common B

9 (34.6%)

12 (24.0%)

3 (15.8%)

18 (31.6%)

Risk stratfication

           

LR

11 (42.3%)

15 (30.0%)

0.326

7 (36.8%)

19 (33.3%)

0.921

SR

4 (15.4%)

15 (30.0%)

5 (26.3%)

14 (24.6%)

HR

11 (42.3%)

20 (40.0%)

7 (36.8%)

24 (42.1%)

MRD-day 15

           

<0.01

8 (30.8%)

14 (29.8%)

0.930

10 (52.6%)

12 (22.2%)

0.020

≥0.01

18 (69.2%)

33 (70.2%)

9 (47.4%)

42 (77.8%)

MRD-day 42

           

<0.01

12 (66.7%)

19 (52.8%)

0.392

9 (50.0%)

22 (61.1%)

0.561

≥0.01

6 (33.3%)

17 (47.2%)

9 (50.0%)

14 (38.9%)

CR

           

no

3 (11.5%)

6 (12.0%)

0.953

0 (0.0%)

9 (15.8%)

 

yes

23 (88.5%)

44 (88.0%)

 

19 (100.0%)

48 (84.2%)

0.102

CD34

           

negative

12 (46.2%)

28 (56.0%)

0.473

11 (57.9%)

29 (50.9%)

0.791

positive

14 (53.8%)

22 (44.0%)

8 (42.1%)

28 (49.1%)

Testicular

           

negative

24 (92.3%)

44 (88.0%)

0.708

19 (100.0%)

49 (86.0%)

0.189

positive

2 (7.7%)

6 (12.0%)

0 (0.0%)

8 (14.0%)

CNS

           

negative

23 (88.5%)

49 (98.0%)

0.113

18 (94.7%)

54 (94.7%)

1.000

positive

3 (11.5%)

1 (2.0%)

1 (5.3%)

3 (5.3%)

Hepatomegaly

           

negative

9 (34.6%)

14 (28.0%)

0.604

8 (42.1%)

15 (26.3%)

0.251

positive

17 (65.4%)

36 (72.0%)

11 (57.9%)

42 (73.7%)

Splenomegaly

           

negative

4 (15.4%)

11 (22.0%)

0.559

2 (10.5%)

13 (22.8%)

0.330

positive

22 (84.6%)

39 (78.0%)

17 (89.5%)

44 (77.2%)

lymphadenopathy

           

negative

11 (42.3%)

28 (56.0%)

0.335

10 (52.6%)

29 (50.9%)

0.895

positive

15 (57.7%)

22 (44.0%)

9 (47.4%)

28 (49.1%)

DNA index

           

standard

23 (88.5%)

43 (86.0%)

1.000

18 (94.7%)

48 (84.2%)

0.436

favorable

3 (11.5%)

7 (14.0%)

1 (5.3%)

9 (15.8%)


Table 4:
Association between TIMP1, CD34+ CD38- and clinical features of the patients

 

TIMP-1

P value

CD34+CD38- CSCs

P value

Low-expression

overexpression

Low-expression

overexpression

Age (years)

4 (1-18)

7(1-17)

0.217

6 (1-18)

6 (1-17)

0.243

TLC (×109/L)

13.1 (4-93.7)

26.4 (0.8-325)

0.076

16.7 (3-93.7)

25.7 (0.8-325)

0.579

BM blast at diagnosis

81 (72-98)%

87 (60-96)%

0.033

78 (63-98)%

87 (60-96)%

0.005

BM blast-day15

0 (0-2)%

1 (0-77)%

0.001

0 (0-9)%

1 (0-77)%

0.003

gender

 

 

 

 

 

 

male

10 (62.5%)

37 (61.7%)

0.951

11 (40.7%)

44 (68.8%)

0.01

 

female

6 (37.5%)

23 (38.3%)

16 (59.3%)

20 (31.3%)

Phenotype

 

 

 

 

 

 

T_ALL

1 (6.3%)

5 (8.3%)

0.915

1 (6.3%)

5 (8.3%)

0.268

preB_ALL

11 (68.8%)

38 (63.3%)

 

13 (81.3%)

36 (60.0%)

commonB

4 (25.0%)

17 (28.3%)

 

2 (12.5%)

19 (31.7%)

Risk stratification

 

 

 

 

 

 

LR

13 (81.3%)

13 (21.7%)

<0.001

9 (56.3%)

17 (28.3%)

0.109

 

 

SR

2 (12.5%)

17 (28.3%)

3 (18.8%)

16 (26.7%)

HR

1 (6.3%)

30 (50.0%)

4 (25.0%)

27 (45.0%)

MRD day 15

 

 

 

 

 

 

<0.01

12 (75.0%)

10 (17.5%)

<0.001

9 (56.3%)

13 (22.8%)

0.015

 

≥0.01

4 (25.0%)

47 (82.5%)

7 (43.8%)

44 (77.2%)

MRD day 42

 

 

 

 

 

 

<0.01

13 (100%)

18 (43.9%)

<0.001

7 (58.3%)

24 (57.1%)

0.941

 

≥0.01

0 (0.0%)

23 (56.1%)

5 (41.7%)

18 (42.9%)

CR

 

 

 

 

 

 

no

0 (0.0%)

9 (15.0%)

0.191

1 (6.3%)

8 (13.3%)

0.675

 

yes

16 (100%)

51 (85.0%)

15 (93.8%)

52 (86.7%)

Testicular

 

 

 

 

 

 

negative

16 (100%)

52 (86.7%)

0.191

16 (100%)

52 (86.7%)

0.191

 

positive

0 (0.0%)

8 (13.3%)

 

0 (0.0%)

8 (13.3%)

CNS

 

 

 

 

 

 

negative

15 (93.8%)

57 (95.0%)

0.842

15 (93.8%)

57 (95.0%)

0.842

 

positive

1 (6.3%)

3 (5.0%)

 

1 (6.3%)

3 (5.0%)

Hepatomegaly

 

 

 

 

 

 

negative

7 (43.8%)

16 (26.7%)

0.226

5 (31.3%)

18 (30.0%)

0.923

 

positive

9 (56.3%)

44 (73.3%)

 

11 (68.8%)

42 (70.0%)

Splenomegaly

 

 

 

 

 

 

negative

5 (31.3%)

10 (16.7%)

0.286

3 (18.8%)

12 (20.0%)

 

0.911

positive

11 (68.8%)

50 (83.3%)

 

13 (81.3%)

48 (80.0%)

lymphadenopathy

 

 

 

 

 

 

negative

5 (31.3%)

34 (56.7%)

0.094

6 (37.5%)

33 (55.0%)

0.266

 

positive

11 (68.8%)

26 (43.3%)

 

10 (62.5%)

27 (45.0%)

DNA index

 

 

 

 

 

 

standard

14 (87.5%)

52 (86.7%)

0.930

15 (93.8%)

51 (85.0%)

 

0.678

favorable

2 (12.5%)

8 (13.3%)

 

1 (6.3%)

9 (15.0%)


Table 5:
Multivariate logistic regression analysis for the incidence of ALL

 

Univariate logistic regression

Multivariate logistic regression

 

OR

95% CI

Sig.

OR

95% CI

Sig.

MMP2

2.000

.629

6.355

0.240

 

 

 

 

MMP9

2.198

.717

6.733

0.168

 

 

 

 

TIMP-1

8.625

2.403

30.961

0.001

4.224

1.024

17.422

0.046

CD34+CD38- CSCs

10.312

2.895

36.733

<0.001

6.873

1.783

26.500

0.005