miR-146b-5p within BCR-ABL1 Positive...

Integrated Systems and Technologies

miR-146b-5p within BCR-ABL1–PositiveMicrovesicles Promotes Leukemic Transformationof Hematopoietic CellsHong-Mei Zhang1, Qing Li2, Xiaojian Zhu3,Wei Liu1, Hui Hu1, Teng Liu1, Fanjun Cheng2,Yong You2, Zhaodong Zhong2, Ping Zou2, Qiubai Li2, Zhichao Chen2, and An-Yuan Guo1

Abstract

Evidence is accumulating that extracellular microvesicles(MV) facilitate progression and relapse in cancer. Using amodel in which MVs derived from K562 chronic myelogen-ous leukemia (CML) cells transform normal hematopoietictransplants into leukemia-like cells, we defined the under-lying mechanisms of this process through gene-expressionstudies and network analyses of transcription factors (TF) andmiRNAs. We found that antitumor miRNAs were increasedand several defense pathways were initiated during the earlyphases of oncogenic transformation. Later, oncomiRs andgenes involved in cell cycle, DNA repair, and energy meta-bolism pathways were upregulated. Regulatory networkanalyses revealed that a number of TFs and miRNAs wereresponsible for the pathway dysregulation and the oncogenic

transformation. In particular, we found that miR-146b-5p,which was highly expressed in MVs, coordinated the regu-lation of cancer-related genes to promote cell-transformingprocesses. Notably, treatment of recipient cells with MV deriv-ed from K562 cells expressing mimics of miR-146b-5p reveal-ed that it accelerated the transformation process in largepart by silencing the tumor-suppressor NUMB. High levels ofmiR-146b-5p also enhanced reactive oxygen species levelsand genome instability of recipient cells. Taken together, ourfinding showed how upregulation of oncogenic miRNAs inMVs promote hematopoetic cells to a leukemic state, as wellas a demonstration for TF and miRNA coregulatory analysis inexploring the dysregulation of cancers and discovering keyfactors. Cancer Res; 76(10); 2901–11. �2016 AACR.

IntroductionMicrovesicles (MV) are extracellular vesicles released by most

cells and act asmediators of intercellular communication (1). Thefunctions ofMVs are complex due to their various bioactive cargo,including DNA,mRNA,miRNA, and proteins (2). Tumor-derivedMVs contain specific information of the tumor status, and thusMVs were studied as potential diagnostic markers and targets fortherapeutic intervention (1, 3). Recently, MVs have receivedincreasing attention for their roles in regulating and transferringactive molecules responsible for tumor progression and metas-tasis (4). MVs play dual roles in cancer through transferringtumor-promoting molecules and tumor suppressors in different

conditions (5, 6). Our previous work demonstrated that MVsderived from K562 chronic myelogenous leukemia (CML) cellscan transform mononuclear cells (MNC) from normal hemato-poietic transplants to acute leukemia-like cancer cells throughgenomic instability (7). During the transformation, a new groupof leukemia-like cells could be observed after 14 days of conse-cutive incubation with MVs, and most of them were transformedinto leukemia-like cells after 21 days (7). This transformationmodel provides an opportunity to explore themechanismof blastcrisis (BC) of CML and the occurrence of donor cell leukemia. As acommon type of leukemia, CMLwas considered as a paradigm forunderstanding the molecular evolution of cancer because it wasthe first cancer shown to be initiated at the hematopoietic stemcell level by BCR-ABL1 and may undergo blastic transformationfrom the chronic phase (CP) to BC (8). However, themechanismsof CML BC transformation are still poorly understood. Thus,elucidating the key factors and exploring their regulatorymechan-isms of our model will shed light on the leukemogenesis andtransformation of CML.

Transcription factors (TF) and miRNAs are important regu-lators in the gene expression of hematopoietic system. Duringleukemogenesis, the aberrant regulation and fusion of TFs, suchas RUNX1, SPI1, GATA, AML1-ETO, and CBFB-MYH11, are keyto the disease (9). MiRNAs, such as miR-15/16, miR-17-92, andmiR-155, were reported with essential functions in the com-mitment and differentiation of hematopoietic stem cells, aswell as the occurrence of leukemia (10, 11). The aberrations ofTFs (e.g., AML1 and HOXs) and miRNAs (e.g., miR-150/17/19a/155) have been found to contribute to the disease pro-gression of CML BC (12, 13). Furthermore, TF and miRNA can

1Department of Bioinformatics and Systems Biology, Key Laboratoryof Molecular Biophysics of the Ministry of Education, College of LifeScience and Technology, Huazhong University of Science and Tech-nology,Wuhan,China. 2Institute of Hematology, UnionHospital,TongjiMedical College, Huazhong University of Science and Technology,Wuhan, P.R.China. 3DepartmentofHematology,Tongji Hospital,TongjiMedical College, Huazhong University of Science and Technology,Wuhan, P.R. China.

Note: Supplementary data for this article are available at Cancer ResearchOnline (http://cancerres.aacrjournals.org/).

H.M. Zhang, Q. Li, and X. Zhu contributed equally to this article.

Corresponding Author: An-Yuan Guo, Huazhong University of Science andTechnology, 1037 Luoyu Road, Wuhan, Hubei, 430074, PR China. Phone: 86-27-8779-3177; E-mail: [email protected]

doi: 10.1158/0008-5472.CAN-15-2120

�2016 American Association for Cancer Research.

CancerResearch

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Published OnlineFirst March 24, 2016; DOI: 10.1158/0008-5472.CAN-15-2120

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regulate mutually and coregulate the same target to formfeedback loop or feed-forward loop regulatory motifs (14),which are vital and common regulatory motifs in differentbiologic processes and diseases (14–16).

Our previouswork demonstrated thatMVs lost their transform-ing abilities following RNase treatment, indicating that RNAs inMVs were responsible for the transformation (7). To furtherexplore the key regulators and their regulations in the process ofK562-MVs transforming MNCs into leukemia-like cells, wesequenced the mRNAs and small RNAs for samples of the criticaltime points. Then, deep analyses of differentially expressed genes,TFs and miRNAs, as well as the regulatory networks among themwere performed. We identified that miR-146b-5p as a key regu-lator accelerated the transformation by targetingNUMBandothergenes, and also caused genome instability and cell proliferation ofthe recipient cells, which will provide important insights into theleukemogenesis.

Materials and MethodsSequencing and identification of differentially expressed genesand miRNAs

Total RNA was isolated from five samples to perform RNA-seqand small RNA-seq. Details of sequencing and expression anal-ysis were in Supplementary Methods. We used the in-housescripts with Poisson distribution to test the differentiallyexpressed genes andmiRNAs between different samples. P valuesadjusted by the Benjamini and Hochberg procedure lower than0.001 and fold changes higher than two were considered assignificant.We also required RPKM� 20 or RPM� 100 in at leastone sample for the differentially expressed genes (DEG) ormiRNAs (DEM), respectively.

The selection of key TFs, miRNAs, and cancer-related pathwaysWe obtained 161 differentially expressed TFs in the transfor-

mation process, and 42 key TFs were selected on the basis of theirtarget information, importance to the hematopoietic system andcancer progression, and expression change during the transfor-mation (upregulated or downregulated constantly, or highlyexpressed in3Wsample). Thekeydifferentially expressedmiRNAswere chosen according to the RPM higher than 1,000 in at leastone sample or the fold change greater than four times in thecomparison of one stage. Finally, 39 key miRNAs were selectedfrom 143 DEMs.

To analyze the cancer-related genes and pathways, we selected16 cancer-related pathways from KEGG, as well as the chromatinmodification gene list from nanoString PanCancer pathways(http://www.nanostring.com/products/pancancer) and tumor-suppressor genes from the TSGene database (17).

Construction of regulatory network and data visualizationWe applied the same method described in our review article to

construct the miRNA and TF coregulatory network (see Supple-mentary Methods; 14). We used the expression correlationbetween regulatory factors and target genes to filter the false-positive regulatory interactions. We required that the absolutevalue of a TF correlation to its target should be larger than 0.5, andthe correlation of an miRNA to its target should be less than 0.5.The network graphics were shown in Cytoscape (18).

The differentially expressed miRNAs and genes were hierar-chically clustered using an average linkage algorithm and a

Euclidean distance for the distance measure. We used MeV(19) to visualize the clustered data.

Cell culture and MV isolationThe human CML blast crisis cell line K562 was purchased from

the China Center for Type Culture Collection (CCTCC) and wasauthenticated by CCTCC (Wuhan) using the STR genotypingmethod in December 2014. K562 was cultured in RPMI-1640containing 15% FBS at 37�C in 5% CO2. MNCs were extractedfrom the peripheral bloodmobilization of healthy volunteers andwere cultured in StemSpan SFEM (#09600; STEMCELL).

MVs isolation was performed by previous protocol: cells werecentrifuged at 1,000 � g for 10 minutes. The supernatant wascentrifuged at 5,000� g for 20 minutes to remove cellular debris,and the remaining supernatant was centrifuged at 13,000 � g for60 minutes to obtain MVs.

Transformation of MNCs from normal hematopoietictransplants with MVs

Isolated MVs were resuspended with serum-free RPMI-1640and filtered using a Millipore Steriflip polyvinylidene difluoridefilter with a pore size of 1.0 mm (to filter cells). MVs werequantified according to their copies of BCR-ABL1 mRNA. TheMNCswere adjusted to 4� 106 cells perwell in a 6-well plate, andMVswere added to the cells three times a day for 13 to 32days. Themorphology of the transformed cells was observed usingWright'sstain.

To confirm the effect of miR-146b-5p, K562 cells were trans-fected with miR-146b-5p mimics and inhibitor: K562 cells wereseeded onto 6-well plates (6 � 105 cells/well) the day beforetransfection. Cells were transfectedwith 10 mL 20 mmol/L formiR-146b-5p inhibitor, 5 mL 20 mmol/L miR-146b-5p mimics(RiboBio), and 50ngmiR-X vector using riboFECTTMCPReagent(RiboBio), respectively. Real-time PCRwas performed tomeasurethe level of miR-146b-5p in the cells and their MVs. The super-natant of transfected cells was collected 48 hours after transfectionto isolate MVs.

To investigate whether miR-146b-5p could complete thetransformation without BCR-ABL1, we performed extra workto incubate the MNCs with imatinib at the concentration of0.25 and 0.5 mm/mL. K562-MV with elevated miR-146b-5p wasadded to the MNCs-imatinib mixtures to induce the transfor-mation as described above.

Experiments of DNA breaks in recipient cells and intracellularreactive oxygen species (ROS) were performed as our previousstudy and also in Supplementary Methods. Other detailed exper-imental methods regarding the luciferase assay, RT-PCR, westernblot, etc., were provided in the online Supplementary Files.

Data availabilityThe RNA-seq and small RNA-seq data are available at NCBI

Sequence Read Archive (SRA) with the accession SRP057826.

ResultsGene and miRNA expression in the transformation

To determine the gene-expression change and the mechanismof the process that K562-MVs transform MNCs, we performedRNA-seq and small RNA-seq for five samples of the key timepoints, which were samples of K562-MVs, MNCs, 1 week(1W)/2weeks (2W)/3 weeks (3W) cells after MVs incubation (see project

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Cancer Res; 76(10) May 15, 2016 Cancer Research2902




design in Supplementary Fig. S1). The 1W sample was consideredas reversible of the transformation. Whereas, the 2W sample wasan irreversible status and a group of leukemia-like cells wasobserved at this time. The 3W sample was considered as the finishof the transformation, as the majorities were leukemia-like cells(7). The summary of sequenced data and mapping informationwere listed in Supplementary Table S1. In the five samples, wedetected 18,614 expressed genes (RPKM > 0) and 1,425 expressedmiRNAs (RPM > 0). In each sample, about 20% to 25% of theexpressed genes were with RPKM > 20, and 3.5% to 5.8% of theexpressed genes were at a high level with RPKM > 100 (Supple-mentary Table S2). FormiRNAs, only 169miRNAs (11.78%)were

highly expressed (RPM > 100) in one or more samples, and theyoccupied more than 99% of the mapping reads. It is surprisingthat K562-MVs contained mRNAs of more than 14,000 genes,especially that it had the highest ratio (5.82%) and number (821)of highly expressed genes (RPKM > 100) among the five samples.However, K562-MVs embodied only 535 expressed miRNAs and20 highly expressedmiRNAs, which were less than other samples.When comparing the highly expressed genes in all samples(Fig. 1A), samples ofMVs and 3W contained themost overlappedgenes, which is consistent with their tumor status. There were 235genes highly expressed in all samples, among them 80 genesencoded ribosomal protein and ribonucleoprotein, andothers are

Figure 1.Summary of highly or differentiallyexpressed genes, miRNAs, andpathways. A, Venn graphs of highlyexpressed genes (left) and miRNAs(right) in thefive samples. B, DEGs andDEMs in three stages of thetransformation. Numbers in thesectors are the numbers of DEGsor DEMs upregulated (gray) ordownregulated (white). C, thestatistics of cancer-related DEGsin up- (gray) and down (white)-regulation by pathways. The circlesizes were normalized accordingto the percentage of DEGs in thepathways. Numbers in the sectors arethe percentages of upregulated anddownregulated DEGs. Oxidative is the"oxidative phosphorylation" pathway;repair is the "replicationand repair" pathway; ChrMod is the"chromatin modification" pathway;Carbon is the "central carbonmetabolism in cancer" pathway;Immune is the "immune system"pathway; TSG is the "tumor-suppressor gene" in TSGenedatabase;and JAK is the "Jak-STAT signalingpathway." For others, please seeSupplementary Table S4.

Network Analysis of the Leukemia Transformation

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enriched in terms "energy metabolism" and "glucose catabolicprocess." It is remarkable that there were many highly express-ed miRNAs, especially in the 3W sample. Almost all (18/20) ofthe highly expressed miRNAs in MVs were also highly express-ed in the other four samples (Fig. 1A). The top five highlyexpressed miRNAs (RPM > 1,000) in MVs were hsa-miR-146b-5p, hsa-miR-486-5p, hsa-miR-92a-3p, hsa-miR-182-5p, andhsa-miR-191-5p.

Differentially expressed genes, miRNAs, and pathwaysUsing the cutoff value described in Materials and Methods, we

identified 3,717 DEGs (including 161 TFs) and 143 DEMs in thetransformation process. Stage 3 (2W-3W) contained the largestnumber of DEGs and DEMs (Fig. 1B), suggesting that the biggestdifference of cell population occurred during 2 to 3 weeks.Enrichment analysis revealed most of the DEGs in three stageswere enriched in "immune response" and "response to stimulus"related terms on Gene Ontology (GO) biologic process (Supple-mentary Table S3). DEGs in stage 3 were also enriched in "cell-cycle" and "cell death" pathways. By mapping the DEGs into 18cancer-related pathways or categories (Supplementary Table S4),we obtained 647 cancer-relatedDEGs, which are likely to play key

roles in the transformation. We summarized the expressionchanges of these cancer-related DEGs through comparing thenormal MNCs and 3W leukemia-like samples (Fig. 1C). DEGsin "cell growth" and "energy production" related pathways weremainly upregulated, whereas most DEGs in "apoptosis" and"immune system" pathways were downregulated. Surprisingly,nine of the 11 downregulated genes in the "cell-cycle" pathwaywere suppressors of the cell cycle. Some signaling pathways, suchas TGFb, Wnt, and PI3K–Akt pathways had equivalent up- anddownregulated genes.

On the basis of the expression change in the three stages of thetransformation, we classified these DEGs and DEMs into eightclasses, respectively, which were DDD, DDU, DUD, DUU, UDD,UDU, UUD, and UUU (D, down and U, up; SupplementaryFig. S2 and Fig. 2). There were 702 genes continuously increased(UUU cluster) in the transformation, and their top enrichedfunctions were "translational initiation" and "cell-cycle process"(Supplementary Table S5). The 406 continuously decreased(DDD) genes were enriched in functional clusters "immuneresponse, response to stimulus" and "cytokine production."According to the expression change (up or down) in stage 3 ofthe transformation, we divided the eight miRNA clusters into two

Figure 2.Clusters of differentially expressed miRNAs. A and B, miRNAs clusters that upregulated or downregulated, respectively, in stage 3. D, downregulation;U, upregulation.

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groups (Fig. 2A and B).ManymiRNAs upregulated in stage 3werereported as oncomiRs. Especially, the highest expressed miRNAsin the UUU cluster were all oncomiRs, including miR-17/18a/20a/92a/378a/130b, which may promote cell proliferationand migration in the transformation. On the contrary, manytumor suppressor miRNAs or apoptosis-related miRNAs, such asmiR-15/16/181a/30d/30e/26a/142-3p (UDD cluster), weredownregulated in the transformation (20). Almost all miRNAsin the DDD cluster, including miR-148a/let-7/199ab/30e, werereported as antitumors or promoted apoptosis, which wasconsistent with the transformation.

miRNA and TF regulation of cancer genes and pathwaysTo explore the perturbed mechanisms of cancer pathways, we

constructed the regulatory network among miRNAs, TFs, andgenes in cancer pathways. Among the 143 and 161 differentiallyexpressed miRNAs and TFs, respectively, we refined 39 miRNAsand 42 TFs for further regulatory analysis based on their targetinformation, expression, and importance to cancer (see Materialsand Methods and Supplementary Fig. S3).

Different cancer-related pathways were activated or repressedin each stage of the transformation regulated by miRNAs andTFs (Fig. 3). In the first stage (MNCs-1W), many miRNAs (e.g.,miR-26/27/181/146b), as well as TFs in IRF and STAT families,were up-regulated; whereas, members in CEBP family and AP1complex were downregulated. These regulators were responsiblefor the downregulation of cell-cycle and mTOR pathways, as wellas the upregulation of immune system and NFkB pathway inresponse to the stimuli of MVs. There were fewer regulators andpathways changed in stage 2 than the other two stages. Stage 3constitutes a key stage of the transformation, with significantdysregulation of most regulators and pathways. Notably, allmiRNAs in the miR-17-92 oncomiR cluster were upregulated,and most of the other miRNAs were downregulated in this stage.TFs, such as TP53, RUNX3, BCL6, and members in the STAT,CEBP, and IRF families were downregulated. Especially, membersin the CEBP family were continuously repressed in all three stagesof transformation. OncoTFs, such as MYC, MAZ, MYB, andMYBL2 were upregulated. For pathways in stage 3, theimmune-related pathways, such as immune system, NFkB sig-naling, and Notch signaling were repressed; whereas, cell prolif-eration and energy-related pathways, including the cell-cycle,oxidative phosphorylation,DNA replication, and repair pathwayswere activated.

TF and miRNA coregulatory networks for specific pathwaysNext, we investigated the detailed regulations among TFs,

miRNAs, and genes in the cell-cycle, DNA replication/repair, andNotch pathways.

We obtained 441 and 258 pairs of regulatory interactions forthe cell-cycle and DNA replication/repair pathways, respectively(Supplementary Table S6). These two pathways are related to theproliferation of cancer cells and were upregulated during thetransformation (Fig. 3). Interestingly, we observed that most of

Figure 3.The regulation of differentially expressed TFs and miRNAs to cancer-relatedpathways in the three stages of transformation. Green, gene/pathwaydownregulated in the comparison of two samples; red, upregulation; andyellow, about half of theDEGs downregulated and half of themupregulated in

the pathway. The left semicircle, middle column, and right semicircle of eachcircle are lists of TF, pathway, and miRNA, respectively. The size of thepathway represents the percentage of DEGs in each pathway. The thicknessof each regulatory line indicates the ratio of DEGs regulated by the TF ormiRNA in the pathway.






the miRNAs in the cell-cycle and all miRNAs in the DNA repli-cation/repair pathways were downregulated in the 3W sample(Fig. 4A and B). Tumor repressor miRNAs miR-15a/16-5p, miR-155-5p, miR-26a/b-5p, and miR-24-3p regulated many genes ofthese two pathways, and some of the regulations were verified byexperiments. The upregulation of miR-17-92, miR-130b-3p, andmiR-301b repressed the expression of cell-cycle repressors RBL2,CDKN1A, ATM, and GADD45B. The upregulation of TFs (e.g.,MYC, MYB, KLF1, and GATA1/2) and downregulation of otherTFs (e.g., KLF6, RUNX3, TP53, and CEBPB) may lead to theactivation of many DEGs in these two pathways. In addition,the TFs and miRNAs also regulated each other, such as MYCactivated the expression of miR-17-92,miR-150-5p, and miR-15a-5p repressedMYB, and then combined to regulate the same genesto achieve subtle regulations.

Because the Notch signaling pathway plays a critical role incell-fate determination and has a complex function in leuke-

mia, we were especially interested in its regulation (21). Weobtained 67 pairs of regulatory interactions among 15 TFs, 11miRNAs, and six genes in the Notch signaling pathway, andconstructed the TF and miRNA coregulatory network (Fig. 4C).The upregulation of miRNAs, such as miR-146b-5p and miR-125a/b-5p, and the downregulation of TFs, such as KLF6 andCEBPB, may be responsible for the downregulation of theNotch signaling pathway. Interestingly, we noticed that almostall members in the miR-17-92 cluster did not target the genes inthe Notch signaling pathway. In this network, miR-146b-5ptargeted NOTCH2, NUMB, and LFNG, and was targeted by TFsSTAT5A and LEF1. As miR-146b-5p had the highest expressionlevel on average and increased dramatically in the transforma-tion, we highlighted it and constructed an miR-146b-5p–spe-cific regulatory network (Fig. 4D). As a result, we found thatmiR-146b-5p regulated many other cancer-related genes com-bined with several TFs. Especially, genes BRCA1, IRAK1, and

Figure 4.Specific TF and miRNA coregulatory networks. A, network for the cell-cycle pathway. B, network for the DNA replication and repair pathways. C, networkfor the Notch signaling pathway. D, potential network of miR-146b-5p as a center. Diamonds, TFs; triangles, genes; hexagons, miRNAs. To simplify the figure, wemerged themiRNAs from the same family or cluster to one node andmerged the JUN/FOS/FOSL2/JUNB toAP1. Nodes in red indicate upregulation in the 3Wsamplecompared with MNCs, and nodes in green are downregulated. The yellow rectangles in D are pathways referring to Fig. 1. Lines in purple and blue representthe regulation of TFs and miRNAs to their targets, respectively. Bold lines mean that the regulations are experimentally verified.

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NFKB1 were confirmed targets of miR-146b-5p by previousstudies (22, 23).

Apart frommiR-146b-5p, we were also interested in the specialregulatory network of other TFs and miRNAs that were highlyexpressed in MVs (Supplementary Fig. S4A). All of them wereverified to be crucial to the occurrence of leukemia and othercancers. YBX1, as a highly expressed TF in K562-MVs, was upre-gulated constantly in the transformation process. Many studiesverified that YBX1 promotes cell proliferation through activatingthe expression of positive regulatory genes in the cell cycle andrepressing the expression of antiapoptotic genes (24). MYC andSTAT5A could also activate the expression of genes in the cell-cycle, PI3K–Akt, and apoptosis pathways. All miRNAs in themiR-17-92 cluster were increased constantly in the transformation.Their overexpression is critical to the progress ofmultiple kinds ofleukemia (25–27) through reducing the expression of tumor-suppressor genes and genes in apoptosis and cell-cycle pathways.These highly expressed TFs and miRNAs in MVs could alsopromote the transformation of MNCs through activating theonco-miRNAs/TFs and repressing the antitumor regulators in acascading manner (Supplementary Fig. S4B).

Increased miR-146b-5p in MVs accelerated the transformationprocess via targeting NUMB

According to the bioinformatics analysis, experiments wereperformed to verify the role ofmiR-146b-5p in the transformation.A significantly increased level of miR-146b-5p was observed inK562-MVs after transfecting miR-146b-5p mimics into the K562cells, whereas a decrease could be found when transfected withmiR-146b-5p inhibitor (Supplementary Fig. S5A and S5B). How-ever, no dose-dependent effect was observed, and it was difficult toelevate the level of miR-146b-5p in the MVs by transfecting moremimics into theK562 cells (Supplementary Fig. S5C). TodeterminewhetherMVs-associatedmiR-146b-5pwas functional for the trans-formation capability, we added K562-MVs with different levels ofmiR-146b-5p (normal K562, miR-146b-5p mimics, and miR-146b-5p inhibitors) into the recipient cells, taking K562-MVs asa control. We found that a high level ofmiR-146b-5p in K562-MVscould accelerate the transformation process, with an average of 9days (P< 0.05, Table 1).Whereas, a decreased level ofmiR-146b-5pdid not stop the transformation, but resulted in a 2-day short delay,leading to a transformation spanning 15 days (P > 0.05). Toinvestigate whether BCR-ABL1 or miR-146b-5p is more importantto the transformation, we incubated theMNCswith imatinib (0.25and 0.5 mm/mL) and K562-MV with elevated miR-146b-5p. As aresult, we discovered that no sign of transformation was observedwhen theMNCs were treated at both concentration of imatinib for29 days. This indicates that BCR-ABL1 is an essential molecule forthe transformation and miR-146b-5p might act as an accelerationfactor with BCR-ABL1.

Furthermore, we tried to explore the mechanism of miR-146b-5p through its potential target genes. Among all the predictedtarget genes ofmiR-146b-5p,we considered the tumor-suppressorgene NUMB as a particularly promising candidate because of itsimportance in cell-fate determination and CML progression (28).Lower levels of NUMB in the target cells could be observed whenmiR-146b-5p was elevated in the K562-MVs (Fig. 5A and B). Theluciferase reporter assay verified that miR-146b-5p could directlybind to the 30-UTR of NUMB mRNA (Fig. 5C and D). Thefluorescence intensity of NUMB 30-UTR with miR-146b-5p trans-fection was only 75.89% of the negative control, whereas therepression disappeared when the binding site of miR-146b-5pon NUMB 30-UTR was mutated. To prove that miR-146b-5paccelerated the transformation process via silencing the tumor-suppressor gene NUMB, we transfected the recipient cells withNUMB lentivirus. Elevated levels could be detected in targetcells, although the efficacy of the transfection was approximate-ly 15% (Supplementary Fig. S6A and S6B). Incubating withK562-MVs, a significant decay was observed when the targetcells were transfected with NUMB (with an average of 30 days,P < 0.05, Table 1).

Genomic instability of recipient cellsGenomic instability is an important hallmark of cancer, and it

was increased in the malignant transformation of MNCs inducedbyMVs described in our previous work (7). Here, we also assessedwhether the genomic instability of recipient cells was enhanced bythe high level of miR-146b-5p. We found DNA breakage in thevast majority of recipient cells incubated with K562-MVs duringtransformation. There was a significant increase in DNA breakagewhen K562-MVs transfected with miR-146b-5p mimics wereadded to the recipient cells (Fig. 5E), especially at d6 (day 6),d9, and d14. A decrease in the DNA break was also detected by agray value in the recipient cells when NUMB was elevated.However, it was not significant (Fig. 5F). Our previous workdemonstrated that activation-induced cytidine deaminase(AICDA) and ROS might be associated with genomic instabilityinduced by MVs. During transformation, AICDA mRNA andprotein expression was increased in cells incubated with K562-MVs (Fig. 5G and H). The induction might be associated with thetransfer of miR-146b-5p, as the level of AICDA increased whenK562 were treated with miR-146b-5p mimics. Similar to AICDA,there was a significant increase of the ROS level when K562-MVswere treated with miR-146b-5p mimics (Fig. 5I).

DiscussionRecent studies suggest that MVs within the tumor microenvi-

ronment are emerging as potent mediators for the communica-tion of tumor cells (29, 30). MVs could act as an early warning

Table 1. Role of miR-146b-5p and NUMB protein in the transformation process

Groups Recipient cells Cell number Time (days)

K562-MVs Mobilization 4 � 106 13.16 � 1.52K562-MVs with increased miR-146b-5p Mobilization 4 � 106 9.25 � 0.5K562-MVs with decreased miR-146b-5p Mobilization 4 � 106 15.5 � 1.29Recipient cells transfected with NUMB Mobilization 4 � 106 30.3 � 3.5Recipient cells transfected with virus only Mobilization 4 � 106 18 � 2.8Recipient cells transfected with imatinib Mobilization 4 � 106 Failure

NOTE: Transformation time is the first time abnormal cells were observed on the basis of morphology. The imatinib was used for two concentrations: 0.25 and0.5 mm/mL.






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Figure 5.Experimental validation of the functions of miR-146b-5p and NUMB in the transformation. Elevated miR-146b-5p in K562-MVs lead to a significant decrease ofNUMBmRNA (A) and protein (B) observed on d3 (day 3), d6, and d9 (P < 0.05). C, miR-146b-5p targeted the 30-UTR of NUMBmRNA by luciferase reporter assay inHEK293T cells. D, no decrease was observed when the miRNA-binding site on NUMB 30-UTR was mutated. E, there was continuous DNA breakage duringtransformation in recipient cells cultured with K562-MVs; a significant increase in DNA breakage occurred when MVs derived from miR-146b-5p mimic-transfected K562 cells were added (P < 0.05), especially at d9. However, the elevated level of NUMB in the recipient cells has no significant effects on theDNA break (F). Expression of AICDA mRNA (G) and protein (H) both increased in miR-146b-5p mimic–transfected K562-MVs during transformation (P < 0.05).Higher levels of ROS were observed in miR-146b-5p–transfected K562-MVs on different days (I).

Zhang et al.





indicator and a novel tool to detect and prevent the occurrence ofcancers (31). Here, we showed that K562-MVs contained a hugeamount of mRNAs and miRNAs, which are indispensable to thetransformation of MNCs to leukemia-like cells. This transforma-tion showed great implications for the process of CML BC, andprovided further clues to the occurrence of donor cell leukemia(7). In addition, the process of malignant transformation mightalso serve as a rapid, convenient, and operable model for theinvestigation of leukemogenesis (7). In this work, we explored thepotential molecules and mechanisms in the transformation bysequencing and bioinformatics analysis, which are BCR–ABL1combined with other TFs and miRNAs, especially miR-146b-5p,to cause cell proliferation and genome instability.

The expressionof thousands of genes andmiRNAswas changedsignificantly during the transformation of MNCs to leukemia-likecells by MVs (Fig. 1B). At the starting stage (stage 1) of thetransformation, many antitumor miRNAs were upregulated, andthe immune response pathway was initiated (Fig. 3). Thus, thisstage could be investigated for the suppression mechanisms ofantitumor elements involved in the tumorigenesis. At stage 2, theimmune response pathway began to downregulate, and the cell-cycle pathway was activated. At stage 3, all antitumor miRNAswere decreased andoncomiRswere upregulated aswell as genes inthe cell-cycle, DNA replication, and energymetabolismpathways.It has been reported that many miRNAs (miR-15a, miR-16, andmiR-146a etc.) were at low levels in CML-AP patients comparedwith CML-CP (32). Our data also confirmed that these miRNAswere downregulated in stage 3 (Fig. 2). The expression tendency ofthese genes andmiRNAs in the transformation provided evidencethat it is a process of tumorigenesis and is similar to the process ofCML CP to BC. Moreover, these results might serve as a resourcefor the process of transformation from normal cells to leukemia.The differentially expressed TFs and miRNAs coregulated many

genes of the cell cycle, and DNA replication/repair, causing theactivationof thesepathways (Fig. 4AandB). TheNotchpathway isimportant in the development of hematopoietic cells and leuke-mia progress (21). The TF and miRNA coregulatory network forthe Notch pathway highlighted miR-146b-5p because it waspredicted to be regulated by TFs STAT5A and LEF1, and regulategenesNUMB,NOTCH2, etc., which are key genes in leukemia andCMLBC (Fig. 4C; refs. 28, 33).On the other hand,miR-146b-5p isthe most highly expressed miRNA in five samples on averageand the fourth highest in K562-MVs. It is also highly expressedin The Cancer Genome Atlas acute myelogenous leukemia sam-ples (34) and had a higher expression in acute lymphoblasticleukemia than its controls, according to theHMEDdatabase (35).

During the transformation, we detected BCR–ABL1 fusion genein the K562-MVs and 3W samples with dozens of reads mappingto the breakpoint site from RNA-seq data, especially in the 3Wsample. BCR-ABL1 has diverse effects on DNA damage-response/DNA repair, checkpoint activation, proliferation, and apoptosisfor the progression of CML CP to BC (36, 37). AlthoughBCR–ABL1 fusion mRNA was essential to this transformation,other RNAs were also required, such as STAT5 (38). We alsoproved that MVs lost their transformative abilities followingRNase treatment (7). Numerous studies have demonstrated thatmiRNA was one of the most promising and key regulatorymolecules in MVs (39). miRNAs in MVs can be transferred intothe recipient cells and function to reprogram the target celltranscriptome (40). Our expression and regulatory network anal-ysis indicated thatmiR-146b-5pmight play important roles in thetransformation, and be activated by STATs, which were inducedby BCR-ABL1 (Fig. 6; ref. 41). miR-146 contains two copies, miR-146a and miR-146b, located at different chromosomes, which donot seem to be redundant because of their different expressionpatterns (Fig. 2; refs. 42, 43). MiR-146a plays functional roles in

Figure 6.A model showing the functions of key miRNAsand TFs in the transformation. Solid lines, thereported regulatory evidences; dotted lines,predicted regulations. Diamonds, TFs;pentagons, miRNAs; rounded rectangles, genes;rectangles, pathways. ROS, reactive oxygenspecies; DSB, DNA double-strand breaks.






hematopoiesis and innate immune responses, as a tumor sup-pressor in many solid tumors (44, 45). MiR-146b was found tofunction in thyroid cancer and glioma by targeting the TGFbpathway and NFkB, and also targeted by TF STATs (41, 46, 47).Our work demonstrated that increasing miR-146b-5p in K562-MVs could accelerate the transformation (Table 1). However, theMNCs were unable to be transformed to leukemia-like cells whenincubated with both imatinib and miR-146b-5p-elevated MVs.We think that miR-146b-5p might act as an acceleration factorwith the essential molecule BCR-ABL1 in the transformation.

Furthermore, how did miR-146b-5p accelerate the trans-formation? We predicted that NUMB was a target of miR-146b-5p and also confirmed this by luciferase assay (Fig. 5C and D). Itoand colleagues (28) found that keeping NUMB at low levels maybe essential for maintaining cells at an immature state and triggerCMLBC transformation. Similar to theCMLBC, decreased level ofNUMB gene was critical to our transformation system induced byMVs. Increased NUMB in recipient cells by lentivirus delayed thetransformation significantly, although transfecting with lentivirusonly can also delay the transformation for the toxicity of the virus(Table 1). This indicates that NUMB might serve as a brakemechanism of the transformation. Thus, we could further authen-ticate the idea that increased miR-146b-5p in K562-MVs promot-ed the transformation via silencing the NUMB gene in the recip-ient cells. NUMB's effects on leukemia cell growth partiallydepend on p53 by preventing ubiquitination and degradationof p53 (28). NUMB is also an inhibitor of the Notch signalingpathway to control cell-fate and inhibit tumor cell proliferation(48). Thus, the increased miR-146b-5p promotes the transfor-mation significantly through repressing the function of NUMB.However, decreased miR-146b-5p showed limited impact on thetransformation. Themismatchmight be explained by the fact thatMVs are packages of a large number of bioactive molecules thatcontain not only contributing factors but also detractors. Thisprovides a novel insight that the occurrence of leukemia inducedby MV could be regulated by content intervention. On the otherhand, overexpression of miR-146b-5p could elevate the level ofAICDA and ROS, consistent with DNA break in the target cells(Fig. 5E andG-I).BRCA1 is a tumor-repressor gene involved in thecell-cycle and DNA damage repair pathways, and its deficiencywill cause genome instability (49). It was reported thatmiR-146b-5p could target and inhibit BRCA1 accompanied by increasedproliferation (22). Consequently, BRCA1 may be another waythat miR-146b-5p leads to genomic instability in the transforma-

tion. We also predicted that miR-146b-5p targeted NOTCH2, atumor-suppressor inmyeloid leukemia (33), to inhibit the Notchpathway. As a result, we inferred that miR-146b-5p served as anoncomiR to promote proliferation and increase genome insta-bility through its targets and downstream pathways in the trans-formation (Fig. 6).

In summary, using expression and regulatory network analysis,we explored the potential transformation mechanism for ourprevious model that K562-MVs transforming MNCs to leuke-mia-like cells. We identified that miR-146b-5p, as a downstreamregulator of BCR–ABL1, promoted the transformation by target-ing several important genes (NUMB, NOTCH2, BRCA1 etc.) toaffect cell proliferation and genome instability. Our study pro-vided an insight into the CML BC transformation and donor cellleukemia, as well as an opportunity for studying the changes ofnormal cells to cancer-like cells.

Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.

Authors' ContributionsConception and design: H.-M. Zhang, Z. Chen, A.-Y. GuoDevelopment of methodology: Q. Li, H. Hu, T. Liu, Q. LiAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): Q. Li, X. ZhuAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): H.-M. Zhang, Q. Li, X. Zhu, W. Liu, A.-Y. GuoWriting, review, and/or revision of the manuscript: H.-M. Zhang, X. Zhu,A.-Y. GuoAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases):H.-M. Zhang, Q. Li, F. Cheng, Y. You, Z. Zhong,Z. ChenStudy supervision: P. Zou, Z. Chen, A.-Y. Guo

Grant SupportThe work was supported by grants from the National Natural Science

Foundation of China (NSFC; 31270885 and 31471247 to A.Y. Guo,81470330 to Z. Chen, 81470348 to P. Zou, and 81470333 to Y. You), NationalBasic Research Program of China (973 Program, 2012CB932501, and theProgram for New Century Excellent Talents in University (NCET;A.Y. Guo).

The costs of publication of this articlewere defrayed inpart by the payment ofpage charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

ReceivedAugust 3, 2015; revised February 29, 2016; acceptedMarch 13, 2016;published OnlineFirst March 24, 2016.

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2016;76:2901-2911. Published OnlineFirst March 24, 2016.Cancer Res Hong-Mei Zhang, Qing Li, Xiaojian Zhu, et al. Leukemic Transformation of Hematopoietic Cells

Positive Microvesicles Promotes−miR-146b-5p within BCR-ABL1

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