Abstract
Imatinib Mesylate is the drug used for targeted tyrosine kinase inhibition in the beginning of management of all Chronic Myeloid Leukemia (CML) newly diagnosed cases. However, resistance presents a considerable limit to its efficacy. Currently, it is impossible to anticipate IM resistance which makes the recognition of early flags an important treatment goal in CML. In this work we studied the connection between microRNA 30a (miR-30a) and Beclin 1 mediated autophagy and IM resistance in Egyptian CML patients. The study included newly diagnosed (group I, n = 20), imatinib responder (group II, n = 30), imatinib resistant (group III, n = 30) CML patients and a healthy demographically matched control group (group IV, n = 20). miR-30a expression was assayed by quantitative reverse transcription polymerase chain reaction. The variation in expression of miR-30a between CML cases and healthy controls was calculated using relative quantification method (2−ΔΔCT). Beclin 1 was assayed in Peripheral blood mononuclear cells by western blotting. miR-30a was over expressed and Beclin 1 was under expressed in imatinib responders compared to resistant cases median 1.21(0.55–3.02) versus median 0.65 (0.03–1.0) (p = 0.001) and median 950.0 (400.0–2410.0) versus, median 1570.0 (920.0–5430.0) (p < 0.001) respectively. Beclin 1 correlated significantly positively with miR-30a in new cases (p = 0.001) and negatively in imatinib responders (p = 0.021). Receiver Operating Curves demonstrated the performances of miR-30a and Beclin 1 to detect imatinib resistance. They showed sensitivities of 97.14% and 94.29% and specificities of 53.33% and 42.22% at the cut-off values of 1 and 940 respectively. Both miR-30a and Beclin 1 levels showed a relation with imatinib response and can therefore be put forward as valuable markers for detection of resistance and may also have promising future therapeutic implications.
Electronic supplementary material
The online version of this article (10.1007/s12288-019-01241-3) contains supplementary material, which is available to authorized users.
Keywords: MicroRNA 30a, Beclin 1, Imatinib
Introduction
Chronic myeloid leukemia (CML) is a hematopoietic stem cell neoplasm [1] that accounts for 15% of adult leukemia. The highest disease incidence is between ages of 40 and 60 years with slight male predominance [2]. The underlying molecular mechanism is the formation of a short chromosome 22 named Philadelphia chromosome resulting from a translocation between chromosomes 9 and 22 t(9; 22)(q34; q11) reciprocally. This translocation joins the breakpoint cluster region (BCR) gene from chromosome 22 and the Abelson murine leukemia (ABL) gene from chromosome 9 generating BCR-ABL gene encoding a protein tyrosine kinase that imparts the malignant phenotype [3].
By virtue of its targeted competitive inhibition of BCR-ABL tyrosine kinase, imatinib is the gold standard drug for tyrosine kinase inhibition in all new CML cases [4]. However, some cases were found to be intractable limiting the long-term benefits of this drug [5]. It is currently impossible to predict whether a patient will develop resistance to imatinib or not which calls for the identification of new targets involved in this clinical problem [15].
Autophagy, a firmly controlled intracellular catabolic pathway, is concerned with lysosomal degradation and turnover of cytoplasmic organelles and proteins. The coordination of autophagy is the function of a multiplex network of different signaling pathways and autophagy genes (ATGs) encoded proteins. In addition to regulating basal level cellular homeostasis, autophagy also has pro-survival functions during cytotoxic insults such as chemotherapy [6]. The activation of autophagy has demonstrated to be a defense mechanism for tumor cells against chemotherapy by alkylating agents and arsenic trioxide. It was therefore hypothesised that CML cells could be adopting such a mechanism for survival in the face of imatinib chemotherapy [7].
Previous in vitro research on primary CML stem cells demonstrated the interplay between imatinib, miR-30a expression and autophagy [8]. To our knowledge, the current work is the first in vivo research to study this association on a considerable number of CML patient samples.
Materials and Methods
This study included 100 subjects divided into 4 groups. Group I comprising 20 new chronic phase adult CML patients, group II including 30 imatinib responder CML patients, group III including 30 resistant patients (Resistance was defined as BCR-ABL transcript level > 10% 3 months after initiation of Imatinib therapy according to NCCN, Chronic Myeloid Leukemia, Version 1.2019 [9] and a fourth group (control group) including 20 demographically matched healthy subjects. Diagnosis was based on BCR-ABL transcript % in CML patients obtained from the routine monitoring of patients using Quantitative PCR (QPCR) [10]. Sokal risk stratification of patients [9] was calculated at http://www.icsg.unibo.it/rrcalc.asp before initiation of imatinib therapy. All patient samples were collected at the Hematology Unit of Alexandria Main University Hospital from year 2017 to year 2019. An informed consent was obtained from all participants.
MicroRNA-30a Expression by Quantitative Reverse Transcriptase Polymerase Chain Reaction (qRT-PCR)
Extraction of miRNA was done using Qiagen® Mini Kit miRNeasy (Qiagen, CA). (ID: 217004). Single-stranded cDNA was synthesized using specific primers from TaqMan MicroRNA Assays and reagents from the TaqMan® Reverse Transcription Kit for MicroRNA. Measurement of plasma level of miR-30a using the TaqMan MicroRNA Assays was done employing two-step RT-PCR performed via Applied Biosystems StepOne™ Real-Time PCR System using TaqMan® miR-30a Assay, TaqMan® 2 × Universal PCR Master Mix, No AmpErase® UNG and Syn-cel-miR-39 miScript miRNA mimic as a spike in control to normalize the expression of the target miRNA. Reagents were obtained from Applied Biosystems, USA. miR-30a level calculation was done using the (2−ΔΔCT) method [11].
Beclin 1 Protein Expression by Western Blotting
Beclin 1 protein state in PMNCs was determined by western blotting. Following buffy coat isolation, the tissue lysate was prepared by adding radioimmunoprecipitation cell lysis buffer (RIPA), Tris (PH 8.0) and protease inhibitor to the WBCs harvest. The lysates were assayed for total protein concentration by Lowry method [12] and stored until analyzed. After protein electrophoresis, protein transfer from sodium dodecyl sulfate (SDS) polyacrylamide gel onto nitrocellulose membrane was performed by electroblotting. Following transfer, bands representating Beclin 1 were detected using Polyclonal Anti-Beclin 1 Antibody (Catalog No.PB9076, http://www.bosterbio.com) and Western Blotting rabbit IgG DAB Chromogenic Reagent Kit (Catalog No. SA2020, http://www.bosterbio.com) (Fig. 1). The housekeeping protein Beta Actin was used as a loading control to normalize our results. The kit used was Western Blotting Mouse IgG DAB Chromogenic Kit (Catalog No. SA2024, boster@bosterbio.com Web: http://www.bosterbio.com). BIO RAD Gel Doc™ XR+ with Image Lab™ software version 5.1 was used for band imaging and densitometry (Fig. 1).
Fig. 1.
Beclin 1 by western blotting in the four groups
Statistical Analysis
Data were analyzed using IBM SPSS software version 20.0. (Armonk, NY: IBM Corp) number and percent were used to describe qualitative data. To verify normality of distribution, Kolmogorov–Smirnov test was used. Range, mean, standard deviation and median were used for quantitative data description. Significance was judged at the 5% level. The used tests were; Chi square test, F-test (ANOVA), Post Hoc test (Tukey) for pairwise, Mann–Whitney test, Kruskal–Wallis test, Post Hoc (Dunn’s multiple comparisons test) and Spearman coefficient. The performances of both miR-30a and Beclin 1 to detect imatinib resistant cases were displayed by Receiver Operating Curve (ROC), calculated as Area Under Curve (AUC).
Results
This study included 100 age and sex matched subjects, 55 males and 45 females ranging between 21 and 70 years.
The median value miR-30a was significantly lower in groups I, II, and III than in the control group IV with p values < 0.001, 0.006 and < 0.001 respectively and higher significantly in group II than group III (p = 0.001) (Fig. 2).
Fig. 2.
Comparison between the four studied groups according to miR-30a level
CML cases showed significantly increased median value for Beclin 1 compared to healthy subjects (p values < 0.001, 0.003 and < 0.001) respectively and compared to group III, a significant decrease in group II was also found (p = 0.001) (Fig. 3).
Fig. 3.
Comparison between the four studied groups according to Beclin 1 expression
The correlation between miR-30a and Beclin 1 in group I was significantly positive (p = 0.001) (Fig. 4). miR-30a and Beclin 1 correlated negatively Group II, (p = 0.021) (Fig. 5) and in group III a negative statistically insignificant correlation was shown between these two parameters (Fig. 6) (p = 0.611).
Fig. 4.
Correlation between miR-30a and Beclin 1 in Group I
Fig. 5.
Correlation between miR-30a and Beclin 1 in Group II
Fig. 6.
Correlation between miR-30a and Beclin 1 in Group III
Total CML cases, showed significant negative correlations between miR-30a level and both BCR-ABL% after treatment and Sokal score (p < 0.001 for both parameters) (Figs. 7, 8). However, Beclin 1 displayed significant positive correlations with both BCR-ABL% after treatment and Sokal score (p < 0.001 and = 0.017 respectively) (Figs. 9, 10).
Fig. 7.
Correlation between miR-30a level and both BCR-ABL% after treatment in total cases
Fig. 8.
Correlation between Beclin 1 and BCR-ABL% after treatment in total cases
Fig. 9.
Correlation between miR-30a level and Sokal score in total cases
Fig. 10.
Correlation between Beclin 1 and Sokal score in total cases
The performance of miR-30a as a prognostic marker was determined by plotting a ROC curve and AUC was found to be 0.760 (p < 0.001). The sensitivity of miR-30a to detect imatinib resistance in CML was 97.14% while its specificity was 53.33% at the cut-off value of 1. The positive and the negative predictive values (PPV, NPV) were estimated to be (61.82) and (96.0) respectively (Fig. 11, Table 1). ROC curve demonstrating Beclin 1 performance shows the AUC to be 0.733 (p < 0.001). The Beclin 1 sensitivity in detecting imatinib resistance in CML was 94.29% while its specificity was 42.22% at the cut-off value of 940. The PPV and the NPV were estimated as (55.9) and (90.5) respectively (Fig. 12, Table 2).
Fig. 11.
ROC curve for miR-30a showing its performance to detect Imatinib resistance
Table 1.
Agreement (sensitivity, specificity) of miR-30a to detect imatinib resistance
| Cut off | BCRABL % follow up | AUC | p | 95% CI | Sensitivity | Specificity | PPV | NPV | |||
|---|---|---|---|---|---|---|---|---|---|---|---|
| ≤ 10 | > 10 | LL | UL | ||||||||
| miR-30a level | > | 24 | 1 | 0.760 | < 0.001* | 0.657 | 0.864 | 97.14 | 53.33 | 61.82 | 96.0 |
| > | 21 | 34 | |||||||||
AUC area under a curve, p value probability value, CI confidence intervals, NPV negative predictive value PPV Positive predictive value
*Statistically significant at p ≤ 0.05
Fig. 12.
ROC curve for Beclin 1 showing its performance to detect Imatinib resistance
Table 2.
Agreement (sensitivity, specificity) of Beclin 1 to detect imatinib resistance
| Cut off | BCRABL % follow up | AUC | p | 95% CI | Sensitivity | Specificity | PPV | NPV | |||
|---|---|---|---|---|---|---|---|---|---|---|---|
| ≤ 10 | > 10 | LL | UL | ||||||||
| Beclin 1 expression | ≤ 940 | 19 | 2 | 0.733 | < 0.001* | 0.625 | 0.841 | 94.29 | 42.22 | 55.9 | 90.5 |
| 940 | 26 | 33 | |||||||||
AUC area under a curve, p value probability value, CI confidence intervals, NPV, negative predictive value, PPV Positive predictive value
*Statistically significant at p ≤ 0.05
Discussion
Autophagy induction plays a role either contributing to or protecting against cell death due to chemotherapy posed cellular stress. It was postulated that if autophagy was a protective mechanism, drugs blocking autophagy may be incorporated to therapy. In contrast, if autophagy is acting as a cell death mechanism besides cytotoxic drugs, promoting autophagy pathway may facilitate treatment responsiveness [8]. MicroRNAs are capable of changing the levels of several key proteins at various steps of the autophagic pathway [13].
Resistance to imatinib in new diagnosed patients with CML could be predicted by a group of 19 miRNAs including miR-30 family as identified by Enériz et al. [14] Subsequent works confirmed that autophagy regulation by miR-30a in a BECN1/Beclin 1-dependent manner may interfere with the effectiveness of chemo-therapy mediated apoptosis in CML [13, 15]. In our work, we studied, in vivo, the relationship between miRNA 30a and autophagy protein Beclin 1 in imatinib response aiming to identify their possible value as early predictors for imatinib resistance and to highlight their future therapeutic potential.
Our results showed significantly upregulated median miR-30a level in imatinib responders compared to resistant cases suggesting that enhanced imatinib cytotoxicity is a function of mediators that are induced at higher miR-30a levels. In this regard, Yu et al. reported that miR-30a mimic increased imatinib and other BCR/ABL TKI-induced cytotoxicity which may be attributed to pro-autophagic proteins being miR-30a targets in CML cells [16].
Moreover, we demonstrated significantly lower Beclin 1 expression in imatinib responders compared to imatinib resistant CML patients showing that lower Beclin 1 levels and thereby autophagy favors imatinib mediated cytotoxicity. This finding highlights the possible therapeutic value of combining autophagy inhibitors with imatinib treatment to eradicate imatinib refractory CML stem cells in resistant cases. In this regard, Carew et al. [17] reported the role of Chloroquine in management of imatinib resistant cases by virtue of its autophagy inhibitory effect.
In this work, miR-30a level and Beclin 1 correlated negatively in imatinib responder cases suggesting a possible regulatory role played by both parameters on imatinib treatment outcome where an upregulation of miR-30a level and an inhibition of Beclin 1 expression are in favor of response and vice versa. The regulatory role played by miR-30a on Beclin 1 was studied by Yu et al. [8] whose in vitro work demonstrated that mimic of miR-30a downregulates autophagy by inhibiting both Beclin 1 and ATG5, and conversely that its antagomir increases their expression and thereby autophagy.
In addition the significant positive correlation between Beclin 1 and BCR-ABL% after treatment and the significant negative correlations between miR-30a level and both BCR-ABL% after treatment and Sokal score promote the possible utility of both parameters as prognostic and follow-up markers to assist risk stratification and guide treatment options in CML cases.
In the present work, the performances of miR-30a and Beclin 1 to detect imatinib resistance were plotted on ROC curves. We demonstrated that miR-30a could identify 97.14% of imatinib resistant cases and could correctly report 53.33% of responders at cut off value 1. Beclin 1, at cut off value 940, was shown to detect resistance in 94.29% of imatinib resistant cases and could identify 42.22% of responders.
Conclusions
The correlation of both miR-30a and Beclin 1 with Sokal score and BCR-ABL% after treatment indicates their possible utility as additional prognostic and follow-up markers for CML. Also, their performances suggest their value as sensitive early predictors of imatinib resistance. Therefore, we recommend their assessment 3 months after initiation of imatinib in cases with BCR-ABL > 10% and it could also be beneficial prior to imatinib treatment in those having high Sokal scores.
Moreover, our results expose the possible therapeutic benefit of addressing miR-30a and Beclin 1mediated autophagy to promote the eradication of CML stem cells, an important mechanism underlying imatinib resistance. Furthermore, we suggest that using miR-30a mimic and/or drugs blocking autophagy combined to imatinib can possibly increase its cytotoxicity providing a novel strategy to enhance imatinib sensitivity in responders and decrease imatinib dose in patients who develop side effects. We therefore put forward the verification of our findings in a larger group of new CML cases.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Funding
No funding was received by the authors for conducting this study.
Compliance with Ethical Standards
Conflict of interest
The authors declare they have potential conflicts of interest, neither financial nor non-financial.
Human and Animal Rights
The study was conducted using human blood samples and an approval by the Ethics Review Board of the Alexandria University, Faculty of Medicine was obtained.
Informed Consent
Subjects’ informed consent was obtained upon sample withdrawal.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Faderl STM, Estrov Z, O’Brien S, Kurzrock R, Kantarjian HM. The biology of chronic myeloid leukemia. N Engl J Med. 1999;341:164–172. doi: 10.1056/NEJM199907153410306. [DOI] [PubMed] [Google Scholar]
- 2.Siegel RL, Miller KD, Jemal A. Cancer statistics. CA Cancer J Clin. 2017;67(1):7–30. doi: 10.3322/caac.21387. [DOI] [PubMed] [Google Scholar]
- 3.Nowell PC. Discovery of the Philadelphia chromosome: a personal perspective. J Clin Investig. 2007;117(8):2033–2035. doi: 10.1172/JCI31771. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.DeAngelo DJ, Ritz J. Imatinib therapy for patients with chronic myelogenous leukemia: are patients living longer? Clin Cancer Res. 2004;10(1):1–3. doi: 10.1158/1078-0432.CCR-1218-3. [DOI] [PubMed] [Google Scholar]
- 5.Apperley JF. Part I: mechanisms of resistance to imatinib in chronic myeloid leukaemia. Lancet Oncol. 2007;8(11):1018–1029. doi: 10.1016/S1470-2045(07)70342-X. [DOI] [PubMed] [Google Scholar]
- 6.Shintani T, Klionsky DJ. Autophagy in health and disease: a double-edged sword. Science. 2004;306(5698):990–995. doi: 10.1126/science.1099993. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Hamilton A (2010) Investigation into the relevance of BCR-ABL for the survival of cancer stem cells in chronic myeloid leukaemia. University of Glasgow
- 8.Yu Y, Yang L, Zhao M, Zhu S, Kang R, Vernon P, et al. Targeting microRNA-30a-mediated autophagy enhances imatinib activity against human chronic myeloid leukemia cells. Leukemia. 2012;26(8):1752. doi: 10.1038/leu.2012.65. [DOI] [PubMed] [Google Scholar]
- 9.Radich JP, Deininger M, Abboud CN, Altman JK, Berman E, Bhatia R, et al. Chronic myeloid leukemia, version 1.2019, NCCN clinical practice guidelines in oncology. J Natl Compr Cancer Netw. 2018;16(9):1108–1135. doi: 10.6004/jnccn.2018.0071. [DOI] [PubMed] [Google Scholar]
- 10.Beillard E, Pallisgaard N, Van der Velden V, Bi W, Dee R, van der Schoot E, et al. Evaluation of candidate control genes for diagnosis and residual disease detection in leukemic patients using ‘real-time’ quantitative reverse-transcriptase polymerase chain reaction (RQ-PCR): a Europe against cancer program. Leukemia. 2003;17(12):2474. doi: 10.1038/sj.leu.2403136. [DOI] [PubMed] [Google Scholar]
- 11.Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2 − ΔΔCT method. Methods. 2001;25(4):402–408. doi: 10.1006/meth.2001.1262. [DOI] [PubMed] [Google Scholar]
- 12.Waterborg JH. The Lowry method for protein quantitation. The protein protocols handbook: Springer; 2009. pp. 7–10. [Google Scholar]
- 13.Gozuacik D, Akkoc Y, Ozturk DG, Kocak M. Autophagy-regulating microRNAs and cancer. Front Oncol. 2017;7:65. doi: 10.3389/fonc.2017.00065. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.San José-Enériz E, Román-Gómez J, Jiménez-Velasco A, Garate L, Martin V, Cordeu L, et al. MicroRNA expression profiling in imatinib-resistant chronic myeloid leukemia patients without clinically significant ABL1-mutations. Mol Cancer. 2009;8(1):69. doi: 10.1186/1476-4598-8-69. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Yang X, Chen Y, Chen L. The versatile role of microRNA-30a in human cancer. Cell Physiol Biochem. 2017;41(4):1616–1632. doi: 10.1159/000471111. [DOI] [PubMed] [Google Scholar]
- 16.Zou Z, Wu L, Ding H, Wang Y, Zhang Y, Chen X, et al. MicroRNA-30a sensitizes tumor cells to cis-platinum via suppressing beclin 1-mediated autophagy. J Biol Chem. 2012;287(6):4148–4156. doi: 10.1074/jbc.M111.307405. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Carew JS, Nawrocki ST, Giles FJ, Cleveland JL. Targeting autophagy: a novel anticancer strategy with therapeutic implications for imatinib resistance. Biol Targets Therapy. 2008;2(2):201. doi: 10.2147/btt.s1840. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.