Downregulation of Mir-31, Mir-155, and Mir-564 in Chronic Myeloid Leukemia Cells

Abstract

Background/Aims

MicroRNAs (miRNAs) are short non-coding regulatory RNAs that control gene expression and play an important role in cancer development and progression. However, little is known about the role of miRNAs in chronic myeloid leukemia (CML). Our objective is to decipher a miRNA expression signature associated with CML and to determine potential target genes and signaling pathways affected by these signature miRNAs.

Results

Using miRNA microarrays and miRNA real-time PCR we characterized the miRNAs expression profile of CML cell lines and patients in reference to non-CML cell lines and healthy blood. Of all miRNAs tested, miR-31, miR-155, and miR-564 were down-regulated in CML cells. Down-regulation of these miRNAs was dependent on BCR-ABL activity. We next analyzed predicted targets and affected pathways of the deregulated miRNAs. As expected, in K562 cells, the expression of several of these targets was inverted to that of the miRNA putatively regulating them. Reassuringly, the analysis identified CML as the main disease associated with these miRNAs. MAPK, ErbB, mammalian target of rapamycin (mTOR) and vascular endothelial growth factor (VEGF) were the main molecular pathways related with these expression patterns. Utilizing Venn diagrams we found appreciable overlap between the CML-related miRNAs and the signaling pathways-related miRNAs.

Conclusions

The miRNAs identified in this study might offer a pivotal role in CML. Nevertheless, while these data point to a central disease, the precise molecular pathway/s targeted by these miRNAs is variable implying a high level of complexity of miRNA target selection and regulation. These deregulated miRNAs highlight new candidate gene targets allowing for a better understanding of the molecular mechanism underlying the development of CML, and propose possible new avenues for therapeutic treatment.

About the Authors:

Oshrat Hershkovitz Rokah

Contributed equally to this work with: Oshrat Hershkovitz Rokah, Galit Granot

Affiliation: Felsenstein Medical Research Center, Beilinson Hospital, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel

Galit Granot

Contributed equally to this work with: Oshrat Hershkovitz Rokah, Galit Granot

* E-mail: [email protected]

Affiliation: Felsenstein Medical Research Center, Beilinson Hospital, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel

Adelina Ovcharenko

Affiliation: Felsenstein Medical Research Center, Beilinson Hospital, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel

Shira Modai

Affiliation: Department of Cell and Developmental Biology, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel

Metsada Pasmanik-Chor

Affiliation: Bioinformatics Unit, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel

Amos Toren

Affiliation: Department of Pediatric Hematology-Oncology, Safra Children's Hospital, Tel-Hashomer, Israel

Noam Shomron

Affiliation: Department of Cell and Developmental Biology, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel

Ofer Shpilberg

Affiliations Felsenstein Medical Research Center, Beilinson Hospital, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel, Institute of Hematology, Beilinson Hospital, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel

Introduction

Chronic myeloid leukemia (CML) is one of the most extensively studied and, probably, best understood neoplasms. The cytogenetic hallmark of CML is the Philadelphia chromosome (Ph), created by a reciprocal translocation between chromosomes 9 and 22 (t[9]; [22] [q34;q11]). This translocation results in the formation of a hybrid bcr-abl oncogene on chromosome 22, which codes for a deregulated tyrosine kinase. BCR-ABL activates multiple signal transduction pathways, including mitogen-activated protein kinase (MAPK), phosphatidylinositol 3 kinase, STAT5/Janus kinase, and Myc. BCR-ABL activity leads to uncontrolled cell proliferation and reduced apoptosis, resulting in the malignant expansion of pluripotent stem cells in bone marrow [1]. Since CML is caused by this distinct genetic lesion it was possible to design an effective targeted molecular therapy which selectively inhibits the aberrant BCR-ABL tyrosine kinase. Imatinib mesylate (STI-571 or Gleevec), is the first BCR-ABL tyrosine kinase inhibitor (TKI) to be used for the treatment of CML [2]. Imatinib is a small-molecule drug that competitively binds the ATP-binding site of BCR-ABL thus preventing a conformational switch to the active form of the oncoprotein. This inhibits BCR-ABL autophosphorylation, interferes with its activation and blocks its downstream signal transduction.

MicroRNAs (miRNAs) are a family of 19–24 nucleotide non-coding RNAs, which affect the regulation of gene expression in eukaryotic cells by binding to a 3′-untranslated region (3′ UTR) within target messenger RNAs (mRNAs). MiRNAs are transcribed by RNA polymerase II as long primary transcripts (pri-miRNAs) and undergo sequential processing to produce mature miRNAs [3], [4]. MiRNAs play important roles in many cellular processes such as development [5], stem cell division [6], [7], apoptosis [8], [9] and cancer [10], [11]. MiRNAs regulate gene expression by either inhibiting translation or promoting degradation of specific mRNA transcripts. An estimated 3% of human genes code for miRNAs, yet these miRNAs may regulate around 30% of the protein-coding genes [12]. This suggests not only their importance in various regulatory pathways, but also their potential for manipulation. MiRNAs themselves have been shown to act both as tumor suppressors and as oncogenes, which can promote tumor growth. In addition, aberrant miRNA levels, specifically an overall downregulation, is observed in many cancers, as compared to their normal tissue counterparts [13], [14]. Recently, a growing body of evidence has implicated specific miRNAs in the pathogenesis of a variety of solid tumors (ovarian, breast and colorectal cancers among others) and hematological malignancies (chronic lymphocytic leukemia (CLL), B-cell lymphomas, acute promyelocytic leukemias, acute lymphocytic leukemia (ALL) and CML) [15], [16]. Most publications on miRNA expression in CML explore the expression of specific miRNAs [17], [18], [19], [20], [21]. Agirre et al [17] revealed decreased expression of miR-10a in CML-derived CD34⁺ bone marrow cells compared with healthy controls. Venturini et al [18] found increased expression of miR-17-5p in CML-derived CD34⁺ peripheral blood cells though this was disputed by Hussein et al [21] who found no significant difference in the expression of this miRNA in CML-derived bone marrow cells compared to healthy controls. In this same paper, CML-derived cells had a tendency for higher expression levels of miR-155 and miR-223 in a subfraction of cases which was, however, not significant. Overall, the data regarding CML specific miRNA expression is inadequate and sometimes inconclusive and the role of miRNAs in CML is still poorly understood. To better elucidate the significance of differential miRNA expression in CML, it is crucial to examine miRNAs expression profiles through microarray analysis in normal and CML tissues or cell lines.

Here, we profiled miRNAs expressed in the CML cell line K562, as compared to its healthy counterpart, normal blood. With the aid of unsupervised hierarchical clustering we found that healthy blood samples were clustered separately from K562 cells. Following miRNA real-time PCR validation, we have determined that miR-31, miR-155, and miR-564 are downregulated in CML cell lines and patients in comparison to non-CML cell lines and healthy blood. Downregulation of these miRNAs is presumably mediated by BCR-ABL tyrosine kinase activity. Bioinformatics analysis revealed predicted targets and affected pathways of the deregulated miRNAs. As expected, in K562 cells, the expression of several of these targets was inverted to that of the miRNA putatively regulating them. Reassuringly, the analysis identified CML as possibly associated with major deregulation of these miRNAs and MAPK, ErbB, mammalian target of rapamycin (mTOR) and and vascular endothelial growth factor (VEGF) as the main molecular signaling pathways regulated by these miRNAs. Overall, our data indicate that these deregulated miRNAs and their putative targets may play a pivotal role in the biology of CML. Consequently, these miRNAs may serve as potential diagnostic and prognostic biomarkers and with further investigation may be used as possible therapeutics for patients suffering from CML.

Material and Methods

Cell lines

The K562 (obtained from the German Resource Center for Biological Material [DSMZ], DSMZ no. ACC 10), Meg-01 (obtained from the American Type Culture Collection [ATCC], no. CRL-2021) and HL60 cell lines (kindly provided by Prof. Shay Izraeli, Sheba Medical Center, Israel) were cultured in RPMI-1640 medium supplemented with 10% heat-inactivated fetal bovine serum (FBS), 2 mM glutamine, 1% penicillin and streptomycin and cultured at 37°C in a humidified incubator with 5% CO2.

The continuous K562 cell line was originally established from the pleural effusion of a 53-year-old female with BCR-ABL positive CML in terminal blast crises. The cell population has been characterized as highly undifferentiated and of the granulocytic series.

The Meg-01 cell line was originally derived from bone marrow cells taken from a patient in megakaryoblastic crisis of BCR-ABL positive CML.

The HL-60 cell line was originally derived from peripheral blood leukocytes of a 36-year-old female with acute promyelocytic leukemia.

Leukocyte isolation

Peripheral blood samples were drawn, with informed consent, from newly diagnosed CML patients before and on days 5 and 30 of treatment with imatinib at a dose of 100 mg/day on days 1–7, 200 mg/day on days 8–14, 300 mg/day on days 15–21, and 400 mg/day from day 22 and thereafter and from healthy volunteers. The samples were treated with red-blood-cell lysis buffer and the remaining leukocytes were used for further experiments. Only blood samples containing 67–70% granulocytes (according to routine blood counts) were used. Blood samples, meeting these criteria, were mixed with erythrocyte lysis buffer (Qiagen, Germany) and centrifuged at 400 g for 10 min at 4°C. The leukocyte pellet was washed and centrifuged again. The remaining leukocytes were snap-frozen and used for further experiments.

Ethics statement

All healthy volunteers were members of the Experimental Hematology Lab, Felsenstein Medical Research Center, at the Rabin Medical Center. Before the experiment, participants were provided with verbal information outlining the general purpose of the study and they were informed that they could withdraw at any time without penalty. They were also verbally informed that the data obtained from their samples would be confidential and used only for the purpose of this research. Verbal consent was obtained for this study because the risks were minimal and all participants were associates of the Lab, and were therefore familiar with the basic methods employed in the relevant experiments. The head of the ethics committee; Institutional Review Board (Helsinki committee), Rabin Medical Center, Beilinson Hospital, Petah Tikva, Israel granted us with the following approval in this matter: "Blood sampling from healthy volunteers who are also research workers do not require IRB approval in our country. Therefore I grant you exemption from IRB approval in this matter". Verbal consent was documented according to IRB ethics committee procedures. All methods employed in this study were in accordance with the Declaration of Helsinki.

Studies executed on patient blood samples were performed with consent. The protocols used were approved by the ethics committee; Institutional Review Board (Helsinki committee), Rabin Medical Center, Beilinson Hospital, Petah Tikva, Israel.

MiRNA microarray analysis

Microarray analysis was performed on the K562 cell line and on a pool of leukocytes derived from blood of 3 healthy volunteers. MiRNAs were extracted from each sample using the miRNeasy Mini Kit (Qiagen, Germany) according to manufacturer's protocol. RNA quantity and quality was assessed using the Nanodrop and Agilent 2100 bioanalyzer systems, respectively. The amount of RNA taken from each sample was equalized, based on these assessments. The miRNA microarray experiments were performed at the Biological Services Unit at the Weizmann Institute of Science using the Agilent Human miRNA Microarray Kit version 1.0 (Agilent Technology, USA). For each miRNA, multiple probes were spotted on the array and the average intensity of these probes was calculated to represent the expression value of the miRNA. In addition, multiple spots were included as negative controls. For each tissue sample, 100ng total RNA was hybridized with the miRNA array and further processed in accordance with the manufacturer's instructions. Two biological replicates were done for each treatment. The arrays were scanned using an Agilent Technology G2565BA scanner and the scanned images were processed using the Feature Extraction software package version 9.5 (Agilent Technology, USA). Coefficient of variation (CV) within groups of replicate probes was used as a quality control measure to reflect the intra-array reproducibility. Complete raw and normalized microarray data and their MIAME compliant metadata have been deposited at GEO (www.ncbi.nlm.nih.gov/geo) under the accession number GSE28825.

Bioinformatics analysis

Partek® genomics suite software.

MiRNA microarray results were analyzed using Partek® Genomics Suite software V6.5, Copyright© 2009 (Partek Inc., St. Louis, MO, USA; www.partek.com). Data were normalized and summarized with the robust multi-average method (RMA) [22], using quantile normalization approach [23], followed by Analysis of Variance (ANOVA). Differentially expressed miRNAs were obtained with p<0.05 and fold-change cutoff of 4.

MiRNA Target Analysis.

Each relevant CML-associated or treatment-associated miRNA was tested using TargetScan. TargetScan uses a computational algorithm to predict biological targets of miRNAs by searching for the presence of conserved 8 mer and 7 mer sites that match the seed region of each miRNA (http://www.targetscan.org) [24]. All the predicted targets from this analysis were then used as input for Ingenuity Pathway Analysis.

Ingenuity Pathway Analysis.

Ingenuity Pathway Analysis (IPA) identifies lists of genes that satisfy particular biological criteria. IPA scores these genes against pathways in the Ingenuity Knowledge Base which houses a large database of biological and chemical relationships extracted from scientific literature. IPA integrates data from a variety of experimental platforms making it possible to identify signaling and metabolic pathways, molecular networks, and biological/disease processes that are most significantly perturbed in our dataset of interest. For each analysis, IPA ranks each function or pathway using the right-tailed Fisher Exact Test, which measures the likelihood that the lists of genes are associated with a certain pathway/function (www.ingenuity.com).

KEGG Pathway Database.

The predicted targets from our analysis were also used as input for the KEGG pathway database [25]. KEGG is used as a reference knowledge base for biological interpretation of large-scale datasets generated by high-throughput experimental technologies. KEGG is a collection of manually drawn pathway maps representing our knowledge on the molecular interaction and reaction networks for metabolism, genetic information processing, environmental information processing, cellular processes and human diseases. . KEGG uses in-house software called KegSketch (http://www.genome.jp/kegg/pathway.html).

Utilizing both IPA and KEGG technologies provides clues for the function of our miRNA of interest.

Venn diagrams.

Venn diagrams were used to show all hypothetically possible logical relations between the top scoring pathways identified by Partek Genomics Suite software V6.5, Copyright© 2009.

MiRNA-specific real time PCR (miR–qRT-PCR)

MiRNA real-time RT-PCR was performed using the TaqMan® Small RNA primer and probe sets (Applied Biosystems, USA). RNA was isolated from all cell lines and from leukocytes purified from blood of CML patients and of healthy volunteers. RNA was reverse-transcribed with miRNA specific stem-looped RT primers (Applied Biosystems, USA) and incubated for 30 min at 16°C, 30 min at 42°C and 5 min at 85°C. Real-time PCR was performed in duplicates using the following conditions: 95°C for 10 min, followed by 40 cycles of 95°C for 15 s, and 60°C for 1 min. Each value of miRNA expression is represented relative to the expression of U6-snRNA, which was used as an internal control. The fold change was calculated using 2^−ΔΔCt method.

Real-time PCR

RNA was isolated using RNeasy Plus Mini Kit (Qaigen, Germany) and reverse transcribed using the high capacity cDNA RT kit (Ambion, USA). Real-time PCR was then performed using the SDS 7000 machine (Applied Biosystems, USA) in a 20 µl reaction containing 10 ng RNA, 10 µl TaqMan master mix (Ambion, USA), 1 µl of target gene or GUSB RNA control primers and a FAM dye-labeled TaqMan probe (Ambion, USA). Amplification conditions were: 50°C for 2 min, followed by 95°C for 10 min, then 40 cycles of 95°C for 15 sec and 60°C for 1 min. The ΔΔC_t method was used to calculate relative expression levels.

Statistics

Experiments were done in triplicates. Differences were statistically evaluated by Student's t-test. Unless otherwise stated, p≤0.05 was considered to be statistically significant.

Results

Differentially expressed miRNAs in K562 cells

MiRNA expression has been shown to dramatically change in CLL, ALL, lymphoma and in other hematological malignancies [14], [15], [16]. With the objective of deciphering a potential miRNA expression signature associated with CML, we analyzed the miRNAs expression profile of the CML cell line, K562 in reference to a pool of 3 healthy blood samples using a miRNA-based microarray chip assay. Of the 470 mature human miRNAs analyzed, 142 miRNAs showed reasonable expression levels in these cells (see Materials and Methods). We used unsupervised hierarchical clustering to differentiate the CML cell line from the normal tissues (Figure 1). It was encouraging to notice that the healthy blood tissues were clustered separately from the K562 cell line indicating a distinct miRNA expression pattern between these groups. Of the 142 miRNAs remaining in the final analyses; 75 were found to be downregulated in K562 cells as compared to healthy blood samples (Table 1), whereas only 35 were upregulated (Table 2), both with a p-value≤0.009. These data are consistent with previous reports stating that overall downregulation of miRNA expression is characteristic of many cancers, as compared to their normal tissue counterparts [13], [14].

[Figure omitted. See PDF.]

Figure 1. Unsupervised clustering analysis of miRNA expression in K562 cells as compared to a pooled sample of healthy blood.

Heat maps illustrating unsupervised clustering of miRNAs that were differentially expressed between blood and K562 samples. The red and blue colors indicate relatively high and low fold-change of expression, respectively. Missing values are indicated in gray. The 8 miRNAs we focused on are indicated with arrows at the bottom of the cluster. Blue arrows represent miRNAs whose expression was downregulated in K562 vs blood, the black arrow represent miRNA whose expression was upregulated in K562 vs blood. Two main miRNAs clusters are shown on top (cluster 1; purple and cluster 2, orange), correlated with the expression patterns described above.

https://doi.org/10.1371/journal.pone.0035501.g001

[Figure omitted. See PDF.]

Table 1. Summary of miRNAs downregulated in K562 cells as compared to healthy blood samples.

https://doi.org/10.1371/journal.pone.0035501.t001

[Figure omitted. See PDF.]

Table 2. Summary of miRNAs upregulated in K562 cells as compared to healthy blood samples.

https://doi.org/10.1371/journal.pone.0035501.t002

In order to validate the microarray data and to ensure that the variations observed were biological and not technical we carried out Taqman miR–qRT-PCR analyses of several miRNAs with altered expression between the K562 cell sample and the normal pooled blood sample. We chose a subset of miRNAs for validation; some of which are known to be altered in cancer while others are potential regulators of cancer/growth pathways in the cell. Each miRNA was quantified in the sample and its expression level was normalized to that of the U6-snRNA, which was used as reference. The miRNA expression patterns from the K562 cells and from the normal pooled blood sample were consistent between the microarray and Taqman measurements. Overall, with the aid of miRNA-based microarray, miR–qRT-PCR and preliminary bioinformatics analysis, we identified 8 miRNAs with statistically significant differential expression between K562 cells and healthy controls: 7 of them were downregulated in K562 cells (miR-31, miR-34a, miR-143, miR-145, miR-155, miR-196b and miR-564) and one was upregulated (miR-128) in K562 cells (Figure 2).

[Figure omitted. See PDF.]

Figure 2. Real-time RT-PCR validation of microarray results, presenting changes in miRNA expression in K562 cells as compared to a pooled sample of healthy blood.

The expression of A. miR-31, B. miR-34a, D. miR-143, E. miR-145, F. miR-155, G. miR-196b and H. miR-564 was downregulated whereas the expression of C. miR-128 was upregulated in K562 cells compared to healthy blood. The histograms show percentage of miRNA expression normalized to U6-snRNA±SEM from at least 3 experiments. Insets show microarray expression results for the specified miRNAs (Blood: red circles; K562: blue circles).

https://doi.org/10.1371/journal.pone.0035501.g002

To further test whether these miRNAs could be implicated specifically in the pathogenesis of CML, we analyzed the expression of the deregulated miRNAs in an additional CML cell line; Meg-01 and in a different hematological, non-CML cell line; HL60. Of the 7 miRNAs found to be downregulated in K562, 6 (miR-31, miR-34a, miR-143, miR-145, miR-155, and miR-564) showed a low expression pattern in Meg-01 cells (Figure 3). The expression of 2 of these 6 miRNAs, miR-143 and miR-145, was low in HL60 cells as well indicating that these miRNA are probably not associated exclusively with CML (data not shown). The expression of the remaining 4 miRNAs (miR-31, miR-34a, miR-155, and miR-564) was high in healthy blood and in HL60 and low in K562 and in Meg-01, indicating a higher likelihood of these miRNAs to be involved in CML pathogenesis.

[Figure omitted. See PDF.]

Figure 3. Expression analysis of miRNAs in CML-derived cell lines as compared to a pooled sample of healthy blood.

Expression analysis of miR-31, miR-34a, miR-143, miR-145, miR-155 and miR-564 in Meg-01 and K562 cell lines and in healthy blood samples was analyzed by miR–qRT-PCR. Shown is the percentage of miRNA expression normalized to U6-snRNA±SEM from at least 3 experiments.

https://doi.org/10.1371/journal.pone.0035501.g003

BCR-ABL kinase activity induces downregulation of miR-31, miR-155, and miR-564 in CML

To support the notion that the above mentioned miRNAs are implicated in CML, we tested the expression of these miRNAs in a CML patient. The analysis confirmed the statistically significant difference in the expression of 3 of the 4 miRNAs (miR-31, miR-155, and miR-564) between leukocytes from a CML patient and those from healthy donors (Figure 4). As CML is characterized by the presence of the BCR-ABL protein, we reasoned that the abnormal expression of these 3 miRNAs observed in the CML patient could be dependent on the kinase activity of BCR-ABL. To test this hypothesis, the expression of these miRNAs was analyzed in leukocytes of a CML patient before and during treatment with imatinib. Whereas these miRNAs showed virtually no change in their expression level on day 5 of imatinib treatment at a dose of 100 mg/day (for the first week of treatment), 30 days of treatment with imatinib at a dose of 400 mg/day (from the fourth week of treatment and thereafter) induced an upregulation of all 3 miRNAs (Figure 4).

[Figure omitted. See PDF.]

Figure 4. Expression analysis of miRNAs in a CML patient before and during treatment with imatinib.

Expression analysis of miR-31, miR-155 and miR-564 in a CML patient at diagnosis an on day 5 of imatinib treatment at a dose of 100 mg/day (for the first week of treatment) and on day 30 of imatinib treatment at a dose of 400 mg/day (from the fourth week of treatment and thereafter). Expression was analyzed by miR–qRT-PCR. Shown is the percentage of miRNA expression normalized to U6-snRNA±SEM from at least 3 experiments.

https://doi.org/10.1371/journal.pone.0035501.g004

Target and pathway analysis of the identified miRNAs

MiRNAs can regulate numerous target genes and therefore have the potential to modulate multiple pathways. Several databases based on various algorithms are available for predicting the targets of selected miRNAs. In order to determine potential target genes and signaling pathways implicated in CML, we analyzed predicted targets of the 3 miRNAs differentially expressed in this study using the TargetScan Human 5.1 database (Table 3).

[Figure omitted. See PDF.]

Table 3. Putative target genes of the deregulated miRNAs as predicted by Target Scan analysis.

https://doi.org/10.1371/journal.pone.0035501.t003

At this point, we sought to correlate the expression of some of the significantly deregulated miRNAs in K562 with some of their putative targets as predicted by our bioinformatics analysis. For this purpose, we performed real-time PCR analysis on CBL, E2F3, cyclin D1, K-ras and Akt2; five of the most promising target proteins to be involved in CML.

CBL which is involved in cancer initiation and progression and is believed to form a multi-protein complex with BCR-ABL [26], [27] is a putative targets of miRs-31 and miR-155. Cyclin D1 and K-ras which have been shown to cooperate with ABL oncogenes to induce full in-vitro and in-vivo transformation [28], [29] are putative targets of miR-155. E2F3 and Akt2 expression is important for BCR-ABL clonogenic activity and are putative targets of miR-564 [30], [31]. Given the downregulated expression of these miRNAs in K562 cells, we hypothesized that the levels of the above mentioned targets would be elevated in this cell line. Indeed, we found that the expression level of CBL, E2F3, cyclin Dl, K-ras and Akt2 to be significantly higher in K562 cells compared to normal blood samples (Figure 5).

[Figure omitted. See PDF.]

Figure 5. Expression of putative targets of the derugulated miRNAs.

Expression of CBL, E2F3, cyclin D1, K-ras and Akt2 was analyzed by real-time PCR in K562 cells and in healthy blood samples. Shown is the percentage of miRNA expression normalized to GUSB RNA±SEM from at least 3 experiments.

https://doi.org/10.1371/journal.pone.0035501.g005

[Figure omitted. See PDF.]

Table 4. Ingenuity analysis of miRNA predictive pathways.

https://doi.org/10.1371/journal.pone.0035501.t004

Based on these results, we explored biological significance, molecular functions and possible diseases affected by the predicted targets of the 3 deregulated miRNAs, by using Ingenuity Systems pathway analysis software (Table 4). Reassuringly, the analysis identified cancer as the main disease associated with expression of these 3 deregulated miRNAs, and specifically CML as one of the major neoplasms linked to these miRNAs. Colorectal cancer was an additional prominent disease found to be related to these deregulated miRNAs. The MAPK, ErbB, mTOR and VEGF signaling pathways were the main molecular pathways related with these expression patterns. In addition to Ingenuity Systems pathway analysis, KEGG pathway analysis also demonstrated CML as one of the main diseases associated with these miRNAs. Figure 6 shows the molecular pathways, as analyzed by the KEGG pathway database, which may be deregulated in CML due to improper expression of the target genes summarized in Table 3, as a result of the deregulated miRNAs. These pathways correlate with cell survival and uncontrolled cell proliferation. Next, we wanted to hypothetically establish possible logical relations between the top scoring pathways identified by our analyses. Interestingly, according to Venn diagram analysis, there is an overlap between the CML-related miRNAs and the MAPK, ErbB, mTOR and VEGF signaling pathways-related miRNAs (Figure 7).

[Figure omitted. See PDF.]

Figure 6. KEGG pathways of deregulated miRNAs predicted targets in CML.

This figure presents cell survival and growth signaling pathways within a CML cell. Red squares represent proteins encoded by genes targeted by the deregulated miRNAs. We have shown that the miRNAs regulating these target genes are downregulated in CML. As a result, these target genes are probably upregulated leading to increased cell survival and induced of uncontrolled cell proliferation.

https://doi.org/10.1371/journal.pone.0035501.g006

[Figure omitted. See PDF.]

Figure 7. Overlap of predicted target genes.

A Venn diagram showing the overlap between predicted targets of CML-related miRNAs and miRNAs related to the different pathways that are predicted to be deregulated in our study.

https://doi.org/10.1371/journal.pone.0035501.g007

Overall, the data derived from our miRNA profiling and bioinformatics analysis support the notion that the miRNAs identified in this study may have a pivotal role in CML. Nevertheless, while these data point to a central disease, the precise molecular pathways targeted by these miRNAs are variable implying a high level of complexity of miRNA target selection and regulation.

Discussion

Distinct miRNA expression signatures are known to participate in regulatory pathways involved in the development and progression of many types of tumors. Accordingly, to date, all tumors tested have shown significantly different miRNA profiles compared with normal cells from the same tissue. These miRNA expression signatures have been reported to be associated with diagnosis, prognosis and response to treatment [32]. Since miRNAs affect a wide range of molecular pathways, studying miRNA expression in human cancer may provide a better understanding of the molecular pathways contributing to cancer pathogenesis and progression.

We utilized miRNA microarray analysis and miRNA real-time PCR to detect miRNAs whose expression is deregulated in CML. To demonstrate whether different sets of miRNAs may properly classify our groups of interest, we performed unsupervised cluster analysis using Partek Genomics Suite software. The unsupervised cluster analysis generated a tree that clearly separated healthy blood samples from K562 cells suggesting that this miRNA profile may serve as a marker differentiating CML patients from healthy individuals. In general, a higher percentage of miRNAs were downregulated rather than upregulated in K562 cells as compared to normal blood samples. This is in agreement with the acknowledged concept that overall downregulation of miRNA expression is characteristic of many cancers, as compared to their normal tissue counterparts [13], [14].

In this study we identified 3 miRNAs (miR-31, miR-155, and miR-564) to be abnormally downregulated in CML cell lines and in patients with CML as compared to non-CML cell lines and to healthy blood samples thus providing support to our hypothesis that miRNAs could be implicated in CML. Moreover, our data suggest that the low expression of these miRNAs is dependent on BCR-ABL tyrosine kinase activity as demonstrated by their increased expression in leukocytes of an imatinib treated patient. Further studies are required to address the molecular mechanism by which BCR-ABL is responsible for the downregulated expression of these miRNAs and whether this downregulation is essential for the transforming role of BCR-ABL in CML.

One miRNA that we found to be downregulated in CML is miR-155. Several lines of evidence suggest that this miRNA may have an important role in normal hematopoiesis [33]. Similar to our quest for defining a signature expression pattern associated with CML, Calin et al. defined a unique miRNA signature linked with prognostic factors and disease progression in CLL. This unique signature was composed of 13 miRNA, among them was miR-155 [34]. However, in contrast to our findings, this miRNA has been reported to accumulate in several lymphoma subtypes, especially in diffuse large B cell lymphoma [35], Hodgkin lymphoma [36] Burkitt lymphoma [37] and in CLL [38]. These discrepancies may be due to differences in the malignancy investigated. They could also be derived from technical differences influenced by the type of technique used for the identification of the relevant miRNA. Also, differences in the normal control used could also have influenced the outcome of the miRNA profiling analysis.

MiR-31, which was also shown to be downregulated in our cell model, is one miRNA out of a cluster of miRNAs that have been assigned to 9 p (miRBase, http://microrna.sanger.ac.uk/) and documented as recurrently deleted when 9 p instability is present, such as witnessed in many CML cases [39]. MiR-31 has recently been shown to concurrently repress the expression of multiple prometastatic target genes thereby inhibiting several distinct aspects of the invasion-metastasis cascade including motility, invasion and resistance to anoikis. As evidence, overexpression of miR-31 in otherwise-aggressive breast tumor cells suppresses metastasis. Whereas inhibiting miR-31 in-vivo allows otherwise-nonaggressive breast cancer cells to metastasize [40]. In contrast to these and to our results, miR-31 was shown to be upregulated in colorectal tumor cells in comparison to non-tumor adjacent mucosa and in plasma of oral squamous cell carcinoma [41], [42]

Expression of miR-564, which we found to be downregulated in our setting, has not been evaluated previously in CML, and the published data regarding this miRNA seems to be inconsistent. It was shown to be downregulated in multiple myeloma, upregulated in CLL and baring no significant change in expression level in hairy cell leukemia compared with normal levels [43].

Ingenuity Systems pathway analysis and KEGG pathway analysis identified CML as one of the major neoplasms linked to these deregulated miRNAs. This analysis also recognized the MAPK, ErbB, mTOR and VEGF signaling pathways as the main molecular pathways related with these expression patterns. These signaling pathways usually participate in a wide range of cellular processes such as growth, proliferation, differentiation and apoptosis. These pathways have continuously been reported to play an important role in hematological malignancies in general and in CML in particular. For instance, BCR-ABL has been shown to activate mTOR and MAPK signaling cascades. These pathways are important components of the aberrant signaling induced by BCR-ABL and contribute to BCR-ABL leukemogenesis. (reviewed in [44], [45], [46], [47]).

In order to determine potential genes implicated in CML, we analyzed predicted targets of the 3 miRNAs differentially expressed using several different algorithms. Nine predicted targets of the 3 deregulated miRNAs have a p-value≤0.005. Most of these targets have been published as related to CML [30], [48], [49], [50], [51]. We observed a downregulation in the expression of the miRNAs targeting Akt2, CBL, E2F2, E2F3, Cyclin Dl, K-ras, PIK3R1, SOS1 and TGFβR2 in CML cell lines and patients as compared to healthy blood. We can therefore hypothesize that the levels of these targets would be elevated in CML cell lines and patients. To begin to confirm the biological effects of these deregulated miRNAs, the expression of CBL, E2F3, cyclin Dl, K-ras and Akt2 was studied. Interestingly, the expression of these proteins was indeed found to be upregulated in K562 cells compared to healthy cells.

Among the possible targets for these miRNAs we found several to mediate transformation of primary human hematopoietic cells. We found that miRs-31 and -155, which were downregulated in our setting, potentially target CBL, which is involved in cancer initiation and progression and was originally discovered as an oncogene which induces B-cell and myeloid leukemias in mice [52]. The expression of this target protein was found to be elevated in K562 cells as compared to control cells. The emerging view is that BCR-ABL assembles a multi-protein complex whose signaling output leads to cellular transformation. Among other proteins, CBL has been identified as participating in this multi-protein complex and as being phosphorylated by BCR-ABL. As a result of these interactions many intracellular signaling pathways, participating in cellular proliferation and survival, are activated, including the K-ras, Akt2 and STAT pathways [26], [27].

E2F3 is an addition protein known to be important for BCR-ABL leukemogenic potential [30]. E2F3 mRNA level has been reported to be higher in BCR-ABL-expressing cell lines compared with non BCR-ABL-expressing cells, and decreases upon inhibition of BCR-ABL kinase activity. Eiring et al have suggested that E2F3 plays a major role in controlling BCR-ABL oncogenic activity and that its expression is required for in-vivo BCR-ABL leukemogenesis. In addition, they show enhanced proliferation to be a characteristic of CML-blast crisis cells, where E2F3 mRNA levels are high but not of CML-chronic phase cells, where E2F3 mRNA levels are low [30]. Our data reveal that miR-564, a putative regulator of E2F3, is downregulated in CML. It is possible that the reduced expression of miR-564 leads to an enhanced expression of E2F3 which assists in the oncogenic activity of BCR-ABL and the growth advantage seen in CML-blast crisis cells.

An additional protein shown to cooperate with BCR-ABL to induce full cellular transformation is cyclin D1. Afar et al have shown that cells overexpressing cyclin Dl (and not cyclin E) and BCR-ABL formed more numerous and larger colonies in soft agar than cells expressing ABL alone [28]. The upregulated expression of cyclin D1 witnessed in K562 cells has been proposed to be achieved through its highly active promoter in these cells [53]. Alternatively, the enhanced expression of cyclin D1 in these cells could be attributed to the reduced expression of miR-155 putatively regulating it.

Ras signaling pathways are activated by a spectrum of hematopoietic cytokine receptors and therefore play important roles in the proliferation and enhanced survival of hematopoietic progenitors. For instance, genetic and biochemical data argue that Ras activation plays a central role in leukemogenic transformation by BCR-ABL [29]. Nevertheless, activating K-ras mutations are detected more often in solid tumors and are a rare event in hematological malignancies in general and in CML in particular [54], [55]. In the absence of oncogenic Ras mutations, alternative mechanisms activating Ras, such as oncogenic activation of upstream tyrosine kinases as seen in AML cells [56], [57], [58], [59] and loss-of-function mutations in the Ras-GAP protein; neurofibromatosis 1 as seen in juvenile myelomonocytic leukemia (JMML) [60], have been suggested. We found the expression of miR-155, a putative negative regulator of K-ras, to be impressively downregulated in CML cell lines and patients. A decrease in miR-155 may serve as an additional mechanism leading to deregulated expression of oncogenic Ras.

Akt2 and Akt3, are genomically amplified in several ovarian, pancreatic and breast cancers [61], [62]. In addition, in a study performed to elucidate the molecular mechanisms underlying CML disease progression, whole-genome profiling was performed to identify recurrent submicroscopic gains and losses of genetic material. In this study, gains for Akt2 were observed [31]. These data propose that overexpression of Akt2 may contribute to the CML malignant phenotype or to malignant disease progression. We also detected a high expression level of Akt2 in K562 cells. We however suggest that this upregulated expression might be due to decreased expression of miR-564, putatively regulating Akt2, in K562 cells.

In this study we identified 3 miRNAs deregulated in CML cell lines and patients versus non-CML cell lines and healthy cells. The presented data suggest that numerous miRNA genes are implicated in the regulation of multiple pathways in hematopoiesis and when aberrantly expressed may promote CML predisposition, initiation and progression. Our identification of CML-related miRNAs and their putative targets can be used as a basis to explore the functions of these miRNAs. Nevertheless, further large scale studies and comprehensive analyses are imperative to validate the role of these miRNAs in CML and to determine whether selective miRNA targeting might modify disease phenotype and outcome. In addition, studies including introduction of exogenous miRNAs or antisense to miRNAs are needed to confirm the direct relationship between each miRNA and its putative target. Ultimately, such studies will have a guiding significance in research and clinical applications and will hopefully aid in the development of novel therapeutic strategies and in determining if these deregulated miRNAs and their targets could be used as diagnostic or prognostic indicators.

Author Contributions

Conceived and designed the experiments: GG AT NS OS. Performed the experiments: OHR AT SM MPC. Analyzed the data: OHR GG AO SM MPC NS OS. Wrote the paper: GG.

Citation: Hershkovitz Rokah O, Granot G, Ovcharenko A, Modai S, Pasmanik-Chor M, Toren A, et al. (2012) Downregulation of Mir-31, Mir-155, and Mir-564 in Chronic Myeloid Leukemia Cells. PLoS ONE 7(4): e35501. https://doi.org/10.1371/journal.pone.0035501

References

1. Deininger MW, Goldman JM, Melo JV (2000) The molecular biology of chronic myeloid leukemia. Blood 96: 3343–3356.MW DeiningerJM GoldmanJV Melo2000The molecular biology of chronic myeloid leukemia.Blood9633433356

2. Savage DG, Antman KH (2002) Imatinib mesylate–a new oral targeted therapy. N Engl J Med 346: 683–693.DG SavageKH Antman2002Imatinib mesylate–a new oral targeted therapy.N Engl J Med346683693

3. Zimmerman AL, Wu S (2011) MicroRNAs, cancer and cancer stem cells. Cancer Lett 300: 10–19.AL ZimmermanS. Wu2011MicroRNAs, cancer and cancer stem cells.Cancer Lett3001019

4. Bartel DP (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116: 281–297.DP Bartel2004MicroRNAs: genomics, biogenesis, mechanism, and function.Cell116281297

5. Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, Bettinger JC, et al. (2000) The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature 403: 901–906.BJ ReinhartFJ SlackM. BassonAE PasquinelliJC Bettinger2000The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans.Nature403901906

6. Hatfield SD, Shcherbata HR, Fischer KA, Nakahara K, Carthew RW, et al. (2005) Stem cell division is regulated by the microRNA pathway. Nature 435: 974–978.SD HatfieldHR ShcherbataKA FischerK. NakaharaRW Carthew2005Stem cell division is regulated by the microRNA pathway.Nature435974978

7. Hatfield S, Ruohola-Baker H (2008) microRNA and stem cell function. Cell Tissue Res 331: 57–66.S. HatfieldH. Ruohola-Baker2008microRNA and stem cell function.Cell Tissue Res3315766

8. Cheng AM, Byrom MW, Shelton J, Ford LP (2005) Antisense inhibition of human miRNAs and indications for an involvement of miRNA in cell growth and apoptosis. Nucleic Acids Res 33: 1290–1297.AM ChengMW ByromJ. SheltonLP Ford2005Antisense inhibition of human miRNAs and indications for an involvement of miRNA in cell growth and apoptosis.Nucleic Acids Res3312901297

9. Calin GA, Ferracin M, Cimmino A, Di Leva G, Shimizu M, et al. (2005) A MicroRNA signature associated with prognosis and progression in chronic lymphocytic leukemia. The New England journal of medicine 353: 1793–1801.GA CalinM. FerracinA. CimminoG. Di LevaM. Shimizu2005A MicroRNA signature associated with prognosis and progression in chronic lymphocytic leukemia.The New England journal of medicine35317931801

10. Meltzer PS (2005) Cancer genomics: small RNAs with big impacts. Nature 435: 745–746.PS Meltzer2005Cancer genomics: small RNAs with big impacts.Nature435745746

11. Volinia S, Calin GA, Liu CG, Ambs S, Cimmino A, et al. (2006) A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci U S A 103: 2257–2261.S. VoliniaGA CalinCG LiuS. AmbsA. Cimmino2006A microRNA expression signature of human solid tumors defines cancer gene targets.Proc Natl Acad Sci U S A10322572261

12. Shomron N, Golan D, Hornstein E (2009) An Evolutionary Perspective of Animal MicroRNAs and Their Targets. Journal of Biomedicine and Biotechnology 2009: pp. 1–10.N. ShomronD. GolanE. Hornstein2009An Evolutionary Perspective of Animal MicroRNAs and Their Targets.Journal of Biomedicine and Biotechnology 2009110

13. Ramkissoon SH, Mainwaring LA, Ogasawara Y, Keyvanfar K, McCoy JP , et al. (2006) Hematopoietic-specific microRNA expression in human cells. Leuk Res 30: 643–647.SH RamkissoonLA MainwaringY. OgasawaraK. KeyvanfarMcCoy JP Jr2006Hematopoietic-specific microRNA expression in human cells.Leuk Res30643647

14. Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, et al. (2005) MicroRNA expression profiles classify human cancers. Nature 435: 834–838.J. LuG. GetzEA MiskaE. Alvarez-SaavedraJ. Lamb2005MicroRNA expression profiles classify human cancers.Nature435834838

15. Farazi TA, Spitzer JI, Morozov P, Tuschl T (2011) miRNAs in human cancer. J Pathol 223: 102–115.TA FaraziJI SpitzerP. MorozovT. Tuschl2011miRNAs in human cancer.J Pathol223102115

16. Zhao H, Wang D, Du W, Gu D, Yang R (2010) MicroRNA and leukemia: tiny molecule, great function. Crit Rev Oncol Hematol 74: 149–155.H. ZhaoD. WangW. DuD. GuR. Yang2010MicroRNA and leukemia: tiny molecule, great function.Crit Rev Oncol Hematol74149155

17. Agirre X, Jimenez-Velasco A, San Jose-Eneriz E, Garate L, Bandres E, et al. (2008) Down-regulation of hsa-miR-10a in chronic myeloid leukemia CD34+cells increases USF2-mediated cell growth. Mol Cancer Res 6: 1830–1840.X. AgirreA. Jimenez-VelascoE. San Jose-EnerizL. GarateE. Bandres2008Down-regulation of hsa-miR-10a in chronic myeloid leukemia CD34+cells increases USF2-mediated cell growth.Mol Cancer Res618301840

18. Venturini L, Battmer K, Castoldi M, Schultheis B, Hochhaus A, et al. (2007) Expression of the miR-17-92 polycistron in chronic myeloid leukemia (CML) CD34+cells. Blood 109: 4399–4405.L. VenturiniK. BattmerM. CastoldiB. SchultheisA. Hochhaus2007Expression of the miR-17-92 polycistron in chronic myeloid leukemia (CML) CD34+cells.Blood10943994405

19. Wang WX, Kyprianou N, Wang X, Nelson PT (2010) Dysregulation of the mitogen granulin in human cancer through the miR-15/107 microRNA gene group. Cancer research 70: 9137–9142.WX WangN. KyprianouX. WangPT Nelson2010Dysregulation of the mitogen granulin in human cancer through the miR-15/107 microRNA gene group.Cancer research7091379142

20. Borze I, Guled M, Musse S, Raunio A, Elonen E, et al. (2011) MicroRNA microarrays on archive bone marrow core biopsies of leukemias–method validation. Leuk Res 35: 188–195.I. BorzeM. GuledS. MusseA. RaunioE. Elonen2011MicroRNA microarrays on archive bone marrow core biopsies of leukemias–method validation.Leuk Res35188195

21. Hussein K, Busche G, Muth M, Gohring G, Kreipe H, et al. (2011) Expression of myelopoiesis-associated microRNA in bone marrow cells of atypical chronic myeloid leukaemia and chronic myelomonocytic leukaemia. Ann Hematol 90: 307–313.K. HusseinG. BuscheM. MuthG. GohringH. Kreipe2011Expression of myelopoiesis-associated microRNA in bone marrow cells of atypical chronic myeloid leukaemia and chronic myelomonocytic leukaemia.Ann Hematol90307313

22. Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, et al. (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4: 249–264.RA IrizarryB. HobbsF. CollinYD Beazer-BarclayKJ Antonellis2003Exploration, normalization, and summaries of high density oligonucleotide array probe level data.Biostatistics4249264

23. Bolstad BM, Irizarry RA, Astrand M, Speed TP (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19: 185–193.BM BolstadRA IrizarryM. AstrandTP Speed2003A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.Bioinformatics19185193

24. Lewis BP, Burge CB, Bartel DP (2005) Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets. Cell 120: 15–20.BP LewisCB BurgeDP Bartel2005Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets.Cell1201520

25. Kanehisa M, Goto S (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28: 27–30.M. KanehisaS. Goto2000KEGG: kyoto encyclopedia of genes and genomes.Nucleic Acids Res282730

26. Johnson KJ, Griswold IJ, O'Hare T, Corbin AS, Loriaux M, et al. (2009) A BCR-ABL mutant lacking direct binding sites for the GRB2, CBL and CRKL adapter proteins fails to induce leukemia in mice. PloS one 4: e7439.KJ JohnsonIJ GriswoldT. O'HareAS CorbinM. Loriaux2009A BCR-ABL mutant lacking direct binding sites for the GRB2, CBL and CRKL adapter proteins fails to induce leukemia in mice.PloS one4e7439

27. Patel H, Marley SB, Gordon MY (2006) Detection in primary chronic myeloid leukaemia cells of p210BCR-ABL1 in complexes with adaptor proteins CBL, CRKL, and GRB2. Genes, chromosomes & cancer 45: 1121–1129.H. PatelSB MarleyMY Gordon2006Detection in primary chronic myeloid leukaemia cells of p210BCR-ABL1 in complexes with adaptor proteins CBL, CRKL, and GRB2.Genes, chromosomes & cancer4511211129

28. Afar DEH, Mclaughlin J, Sherr CJ, Witte ON, Roussel MF (1995) Signaling by Abl Oncogenes through Cyclin D1. Proceedings of the National Academy of Sciences of the United States of America 92: 9540–9544.DEH AfarJ. MclaughlinCJ SherrON WitteMF Roussel1995Signaling by Abl Oncogenes through Cyclin D1.Proceedings of the National Academy of Sciences of the United States of America9295409544

29. Peters DG, Hoover RR, Gerlach MJ, Koh EY, Zhang H, et al. (2001) Activity of the farnesyl protein transferase inhibitor SCH66336 against BCR/ABL-induced murine leukemia and primary cells from patients with chronic myeloid leukemia. Blood 97: 1404–1412.DG PetersRR HooverMJ GerlachEY KohH. Zhang2001Activity of the farnesyl protein transferase inhibitor SCH66336 against BCR/ABL-induced murine leukemia and primary cells from patients with chronic myeloid leukemia.Blood9714041412

30. Eiring AM, Neviani P, Santhanam R, Oaks JJ, Chang JS, et al. (2008) Identification of novel posttranscriptional targets of the BCR/ABL oncoprotein by ribonomics: requirement of E2F3 for BCR/ABL leukemogenesis. Blood 111: 816–828.AM EiringP. NevianiR. SanthanamJJ OaksJS Chang2008Identification of novel posttranscriptional targets of the BCR/ABL oncoprotein by ribonomics: requirement of E2F3 for BCR/ABL leukemogenesis.Blood111816828

31. Grossmann V, Kohlmann A, Zenger M, Schindela S, Eder C, et al. (2011) A deep-sequencing study of chronic myeloid leukemia patients in blast crisis (BC-CML) detects mutations in 76.9% of cases. Leukemia : official journal of the Leukemia Society of America, Leukemia Research Fund, UK 25: 557–560.V. GrossmannA. KohlmannM. ZengerS. SchindelaC. Eder2011A deep-sequencing study of chronic myeloid leukemia patients in blast crisis (BC-CML) detects mutations in 76.9% of cases.Leukemia : official journal of the Leukemia Society of America, Leukemia Research Fund, UK25557560

32. Calin GA, Croce CM (2006) MicroRNA signatures in human cancers. Nat Rev Cancer 6: 857–866.GA CalinCM Croce2006MicroRNA signatures in human cancers.Nat Rev Cancer6857866

33. Costinean S, Zanesi N, Pekarsky Y, Tili E, Volinia S, et al. (2006) Pre-B cell proliferation and lymphoblastic leukemia/high-grade lymphoma in E(mu)-miR155 transgenic mice. Proc Natl Acad Sci U S A 103: 7024–7029.S. CostineanN. ZanesiY. PekarskyE. TiliS. Volinia2006Pre-B cell proliferation and lymphoblastic leukemia/high-grade lymphoma in E(mu)-miR155 transgenic mice.Proc Natl Acad Sci U S A10370247029

34. Calin GA, Ferracin M, Cimmino A, Di Leva G, Shimizu M, et al. (2005) A MicroRNA signature associated with prognosis and progression in chronic lymphocytic leukemia. N Engl J Med 353: 1793–1801.GA CalinM. FerracinA. CimminoG. Di LevaM. Shimizu2005A MicroRNA signature associated with prognosis and progression in chronic lymphocytic leukemia.N Engl J Med35317931801

35. Eis PS, Tam W, Sun L, Chadburn A, Li Z, et al. (2005) Accumulation of miR-155 and BIC RNA in human B cell lymphomas. Proc Natl Acad Sci U S A 102: 3627–3632.PS EisW. TamL. SunA. ChadburnZ. Li2005Accumulation of miR-155 and BIC RNA in human B cell lymphomas.Proc Natl Acad Sci U S A10236273632

36. Kluiver J, Poppema S, de Jong D, Blokzijl T, Harms G, et al. (2005) BIC and miR-155 are highly expressed in Hodgkin, primary mediastinal and diffuse large B cell lymphomas. J Pathol 207: 243–249.J. KluiverS. PoppemaD. de JongT. BlokzijlG. Harms2005BIC and miR-155 are highly expressed in Hodgkin, primary mediastinal and diffuse large B cell lymphomas.J Pathol207243249

37. Kluiver J, Haralambieva E, de Jong D, Blokzijl T, Jacobs S, et al. (2006) Lack of BIC and microRNA miR-155 expression in primary cases of Burkitt lymphoma. Genes Chromosomes Cancer 45: 147–153.J. KluiverE. HaralambievaD. de JongT. BlokzijlS. Jacobs2006Lack of BIC and microRNA miR-155 expression in primary cases of Burkitt lymphoma.Genes Chromosomes Cancer45147153

38. Calin GA, Liu CG, Sevignani C, Ferracin M, Felli N, et al. (2004) MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias. Proc Natl Acad Sci U S A 101: 11755–11760.GA CalinCG LiuC. SevignaniM. FerracinN. Felli2004MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic leukemias.Proc Natl Acad Sci U S A1011175511760

39. Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ (2006) miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 34: D140–144.S. Griffiths-JonesRJ GrocockS. van DongenA. BatemanAJ Enright2006miRBase: microRNA sequences, targets and gene nomenclature.Nucleic Acids Res34D140144

40. Valastyan S, Reinhardt F, Benaich N, Calogrias D, Szasz AM, et al. (2009) A pleiotropically acting microRNA, miR-31, inhibits breast cancer metastasis. Cell 137: 1032–1046.S. ValastyanF. ReinhardtN. BenaichD. CalogriasAM Szasz2009A pleiotropically acting microRNA, miR-31, inhibits breast cancer metastasis.Cell13710321046

41. Slaby O, Svoboda M, Fabian P, Smerdova T, Knoflickova D, et al. (2007) Altered expression of miR-21, miR-31, miR-143 and miR-145 is related to clinicopathologic features of colorectal cancer. Oncology 72: 397–402.O. SlabyM. SvobodaP. FabianT. SmerdovaD. Knoflickova2007Altered expression of miR-21, miR-31, miR-143 and miR-145 is related to clinicopathologic features of colorectal cancer.Oncology72397402

42. Liu CJ, Kao SY, Tu HF, Tsai MM, Chang KW, et al. (2010) Increase of microRNA miR-31 level in plasma could be a potential marker of oral cancer. Oral Diseases 16: 360–364.CJ LiuSY KaoHF TuMM TsaiKW Chang2010Increase of microRNA miR-31 level in plasma could be a potential marker of oral cancer.Oral Diseases16360364

43. Moussay E, Wang K, Cho JH, van Moer K, Pierson S, et al. (2011) MicroRNA as biomarkers and regulators in B-cell chronic lymphocytic leukemia. Proceedings of the National Academy of Sciences of the United States of America 108: 6573–6578.E. MoussayK. WangJH ChoK. van MoerS. Pierson2011MicroRNA as biomarkers and regulators in B-cell chronic lymphocytic leukemia.Proceedings of the National Academy of Sciences of the United States of America10865736578

44. Milella M, Kornblau SM, Andreeff M (2003) The mitogen-activated protein kinase signaling module as a therapeutic target in hematologic malignancies. Reviews in clinical and experimental hematology 7: 160–190.M. MilellaSM KornblauM. Andreeff2003The mitogen-activated protein kinase signaling module as a therapeutic target in hematologic malignancies.Reviews in clinical and experimental hematology7160190

45. Yarden Y, Sliwkowski MX (2001) Untangling the ErbB signalling network. Nature reviews Molecular cell biology 2: 127–137.Y. YardenMX Sliwkowski2001Untangling the ErbB signalling network.Nature reviews Molecular cell biology2127137

46. Redig AJ, Vakana E, Platanias LC (2011) Regulation of mammalian target of rapamycin and mitogen activated protein kinase pathways by BCR-ABL. Leukemia & lymphoma 52: Suppl 145–53.AJ RedigE. VakanaLC Platanias2011Regulation of mammalian target of rapamycin and mitogen activated protein kinase pathways by BCR-ABL.Leukemia & lymphoma52Suppl 14553

47. Sillaber C, Mayerhofer M, Aichberger KJ, Krauth MT, Valent P (2004) Expression of angiogenic factors in chronic myeloid leukaemia: role of the bcr/abl oncogene, biochemical mechanisms, and potential clinical implications. European journal of clinical investigation 34: Suppl 22–11.C. SillaberM. MayerhoferKJ AichbergerMT KrauthP. Valent2004Expression of angiogenic factors in chronic myeloid leukaemia: role of the bcr/abl oncogene, biochemical mechanisms, and potential clinical implications.European journal of clinical investigation34Suppl 2211

48. Brehme M, Hantschel O, Colinge J, Kaupe I, Planyavsky M, et al. (2009) Charting the molecular network of the drug target Bcr-Abl. Proceedings of the National Academy of Sciences of the United States of America 106: 7414–7419.M. BrehmeO. HantschelJ. ColingeI. KaupeM. Planyavsky2009Charting the molecular network of the drug target Bcr-Abl.Proceedings of the National Academy of Sciences of the United States of America10674147419

49. Liu JH, Yen CC, Lin YC, Gau JP, Yang MH, et al. (2004) Overexpression of cyclin D1 in accelerated-phase chronic myeloid leukemia. Leukemia & lymphoma 45: 2419–2425.JH LiuCC YenYC LinJP GauMH Yang2004Overexpression of cyclin D1 in accelerated-phase chronic myeloid leukemia.Leukemia & lymphoma4524192425

50. Kawauchi K, Ogasawara T, Yasuyama M, Ohkawa S (2003) Involvement of Akt kinase in the action of STI571 on chronic myelogenous leukemia cells. Blood cells, molecules & diseases 31: 11–17.K. KawauchiT. OgasawaraM. YasuyamaS. Ohkawa2003Involvement of Akt kinase in the action of STI571 on chronic myelogenous leukemia cells.Blood cells, molecules & diseases311117

51. Ozaki K, Kosugi M, Baba N, Fujio K, Sakamoto T, et al. (2010) Blockade of the ERK or PI3K-Akt signaling pathway enhances the cytotoxicity of histone deacetylase inhibitors in tumor cells resistant to gefitinib or imatinib. Biochemical and biophysical research communications 391: 1610–1615.K. OzakiM. KosugiN. BabaK. FujioT. Sakamoto2010Blockade of the ERK or PI3K-Akt signaling pathway enhances the cytotoxicity of histone deacetylase inhibitors in tumor cells resistant to gefitinib or imatinib.Biochemical and biophysical research communications39116101615

52. Langdon WY, Hartley JW, Klinken SP, Ruscetti SK, Morse HC (1989) v-cbl, an oncogene from a dual-recombinant murine retrovirus that induces early B-lineage lymphomas. Proceedings of the National Academy of Sciences of the United States of America 86: 1168–1172.WY LangdonJW HartleySP KlinkenSK RuscettiMorse HC 3rd1989v-cbl, an oncogene from a dual-recombinant murine retrovirus that induces early B-lineage lymphomas.Proceedings of the National Academy of Sciences of the United States of America8611681172

53. de Groot RP, Raaijmakers JA, Lammers JW, Koenderman L (2000) STAT5-Dependent CyclinD1 and Bcl-xL expression in Bcr-Abl-transformed cells. Molecular cell biology research communications : MCBRC 3: 299–305.RP de GrootJA RaaijmakersJW LammersL. Koenderman2000STAT5-Dependent CyclinD1 and Bcl-xL expression in Bcr-Abl-transformed cells.Molecular cell biology research communications : MCBRC3299305

54. Collins SJ, Howard M, Andrews DF, Agura E, Radich J (1989) Rare occurrence of N-ras point mutations in Philadelphia chromosome positive chronic myeloid leukemia. Blood 73: 1028–1032.SJ CollinsM. HowardDF AndrewsE. AguraJ. Radich1989Rare occurrence of N-ras point mutations in Philadelphia chromosome positive chronic myeloid leukemia.Blood7310281032

55. Gougopoulou DM, Kiaris H, Ergazaki M, Anagnostopoulos NI, Grigoraki V, et al. (1996) Mutations and expression of the ras family genes in leukemias. Stem cells 14: 725–729.DM GougopoulouH. KiarisM. ErgazakiNI AnagnostopoulosV. Grigoraki1996Mutations and expression of the ras family genes in leukemias.Stem cells14725729

56. Reuter CW, Morgan MA, Bergmann L (2000) Targeting the Ras signaling pathway: a rational, mechanism-based treatment for hematologic malignancies? Blood 96: 1655–1669.CW ReuterMA MorganL. Bergmann2000Targeting the Ras signaling pathway: a rational, mechanism-based treatment for hematologic malignancies?Blood9616551669

57. Gilliland DG, Griffin JD (2002) The roles of FLT3 in hematopoiesis and leukemia. Blood 100: 1532–1542.DG GillilandJD Griffin2002The roles of FLT3 in hematopoiesis and leukemia.Blood10015321542

58. Beghini A, Peterlongo P, Ripamonti CB, Larizza L, Cairoli R, et al. (2000) C-kit mutations in core binding factor leukemias. Blood 95: 726–727.A. BeghiniP. PeterlongoCB RipamontiL. LarizzaR. Cairoli2000C-kit mutations in core binding factor leukemias.Blood95726727

59. Eguchi M, Eguchi-Ishimae M, Tojo A, Morishita K, Suzuki K, et al. (1999) Fusion of ETV6 to neurotrophin-3 receptor TRKC in acute myeloid leukemia with t(12;15)(p13;q25). Blood 93: 1355–1363.M. EguchiM. Eguchi-IshimaeA. TojoK. MorishitaK. Suzuki1999Fusion of ETV6 to neurotrophin-3 receptor TRKC in acute myeloid leukemia with t(12;15)(p13;q25).Blood9313551363

60. Cichowski K, Jacks T (2001) NF1 tumor suppressor gene function: narrowing the GAP. Cell 104: 593–604.K. CichowskiT. Jacks2001NF1 tumor suppressor gene function: narrowing the GAP.Cell104593604

61. Barlund M, Forozan F, Kononen J, Bubendorf L, Chen Y, et al. (2000) Detecting activation of ribosomal protein S6 kinase by complementary DNA and tissue microarray analysis. Journal of the National Cancer Institute 92: 1252–1259.M. BarlundF. ForozanJ. KononenL. BubendorfY. Chen2000Detecting activation of ribosomal protein S6 kinase by complementary DNA and tissue microarray analysis.Journal of the National Cancer Institute9212521259

62. Nakatani K, Thompson DA, Barthel A, Sakaue H, Liu W, et al. (1999) Up-regulation of Akt3 in estrogen receptor-deficient breast cancers and androgen-independent prostate cancer lines. The Journal of biological chemistry 274: 21528–21532.K. NakataniDA ThompsonA. BarthelH. SakaueW. Liu1999Up-regulation of Akt3 in estrogen receptor-deficient breast cancers and androgen-independent prostate cancer lines.The Journal of biological chemistry2742152821532