Extracellular Vesicles from High-Grade Glioma Exchange ... · either EV (Supplementary Fig. S2B)....

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Extracellular Vesicles from High-Grade GliomaExchange Diverse Pro-oncogenic Signals ThatMaintain Intratumoral HeterogeneityFranz Ricklefs1,2, Marco Mineo1, Arun K. Rooj1, Ichiro Nakano3, Al Charest4,Ralph Weissleder5, Xandra O. Breakefield6, E. Antonio Chiocca1,Jakub Godlewski1, and Agnieszka Bronisz1

Abstract

A lack of experimental models of tumor heterogeneity limitsour knowledge of the complex subpopulation dynamicswithin thetumor ecosystem. In high-grade gliomas (HGG), distinct hierarchi-cal cell populations arise from different glioma stem-like cell(GSC) subpopulations. Extracellular vesicles (EV) shed by cellsmay serve as conduits of genetic and signaling communications;however, little is known about how HGG heterogeneity mayimpact EV content and activity. In this study, we performed aproteomic analysis of EVs isolated from patient-derived GSC ofeither proneural or mesenchymal subtypes. EV signatures wereheterogeneous, but reflected the molecular make-up of the GSC

and consistently clustered into the two subtypes. EV-borne proteincargos transferred between proneural and mesenchymal GSC in-creased protumorigenic behaviors in vitro and in vivo. Clinically,analyses of HGG patient data from the The Cancer Genome Atlasdatabase revealed that proneural tumors with mesenchymal EVsignatures or mesenchymal tumors with proneural EV signatureswere both associated with worse outcomes, suggesting influencesby the proportion of tumor cells of varying subtypes in tumors.Collectively, our findings illuminate the heterogeneity among tu-mor EVs and the complexity of HGG heterogeneity, which theseEVs help to maintain. Cancer Res; 76(10); 2876–81. �2016 AACR.

IntroductionCharacterization of the genome (1, 2) and RNA transcrip-

tome (3–6) provided an increasingly high-resolution picture ofthe heterogeneity of the HGG landscape. Single-cell RNAsequencing of HGG reveals that tumor cell subpopulationswith different transcriptome subtypes coexist and have devel-opmentally evolved over a period of time from a distantlyrelated precursor, likely a cancer stem-like cell (7, 8). Thisintratumoral heterogeneity with redundant signaling networkaberrancies underlies the ineffectiveness of conventional andtargeted therapies (9–11).

Recently, there is increasing appreciation for the role thatextracellular vesicles (EV) play in cell–cell communication incancers. However, it is not known whether the profound geneticand phenotypic diversity of cells in a HGG is related to theintercellular transfer of functional molecules contained withinEVs (12–14). Here, we show that EVs released by GSCs retainsubtype characteristics and that their transfer between GSC sub-types leads to protumorigenic changes in the target GSC. Exper-imentally, in mouse brains, there is a hierarchical clustering ofdifferent GSC subtypes with visible transfer of EVs. Coupled withthe finding that the EV proteome is predictive of HGG patientoutcome, this study shows that EV communication may be acritical linchpin in HGG GSC subtype diversity.

Materials and MethodsHuman specimens and primary cells

Tumor samples were obtained as approved by Institu-tional Review Board at and The Harvard Medical School(HMS, Boston, MA). Surgery was performed by E.A. Chioccaand I. Nakano. GSCs were obtained by dissociation of tumorsamples and cultivated in stem cell–enriching conditionsusing glutamine, B27, FGF, and EGF-supplemented Neuro-basal medium (14, 15). The unique identity of culturedpatient-derived cells was confirmed by short tandem repeatanalysis (16).

Purification of EVsThe conditioned media were collected and EVs were isolated

by differential centrifugation and analyzed using a NanoSight asdescribed previously (14).

1Department of Neurosurgery, Brigham and Women's Hospital, Har-vard Medical School, Boston, Massachusetts. 2Department of Neuro-surgery, University Medical Center Hamburg-Eppendorf, Hamburg,Germany. 3Department of Neurosurgery and Comprehensive CancerCenter, University of Alabama at Birmingham, Birmingham, Alabama.4Department of Neurosurgery, Molecular Oncology Research Insti-tute,TuftsMedical Center,Tufts University School ofMedicine, Boston,Massachusetts. 5Center for Systems Biology, Massachusetts GeneralHospital, Harvard Medical School, Boston, Massachusetts. 6Depart-ment of Neurology, Neurosurgery andRadiology, Massachusetts Gen-eral Hospital, Boston, Massachusetts.

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

Corresponding Authors: Agnieszka Bronisz, Brigham and Women's Hospital/Harvard Medical School, 4 Blackfan Circle, Boston, MA 02115. Phone: 617-525-5684; Fax: 617-713-3050; E-mail: [email protected]; Jakub Godlewski,[email protected]; and E. Antonio Chiocca, [email protected]

doi: 10.1158/0008-5472.CAN-15-3432

�2016 American Association for Cancer Research.

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Mass spectrometry and immunoblottingAll mass spectra were acquired at the Bioproximity LLC and

data were validated by Western blotting (14).

In vitro assaysFor EV transfer, 3�105GSCs/mLweremaintainedovernight in

unsupplemented medium followed by 24-hour treatment withEV derived from mesenchymal (M) GSCs (EVM) or form pro-neural (P) GSCs (EVP; 5 mg protein/mL).

For spheroid formation, GSCs were dissociated to single cellsand plated at 200 (M GSCs) or 1,000 (P GSCs) cells/well and in96-well plate in unsupplemented medium and treated with EVs(5 mg of protein/mL) at 0 and 48 hours and analyzed after 96 hours.

For co-culture assay, single-cell suspensions ofMGSCs, PGSCs,and M/P GSC coculture (at 1:4 ratio) were cultured for 48 hoursin neurosphere medium.

In vivo studiesFemale athymic mice were purchased from Envigo. Mice were

housed in HMS animal facility in accordance with NIH regula-tions. Protocols were approved by the HMS Institutional AnimalCare and Use Committee. Intracranial tumor injection was per-formed as described previously (14). For GSC coimplantationexperiments, either 1 � 103 M GSCs or 5 � 105 P GSCs, or bothcombined were used. For GSC/EV coimplantation, cells were

pretreated with EVs for 24 hours, pelleted, and admixed withEVs (at 5 mg of protein/mL).

MicroscopyEV release was visualized by embedding either PALM-Tomato

MGSC or PALM-GFP PGSC spheroids in collagen. All fluorescentand bright field microscopy assays were observed using a NikonEclipse Ti.

Statistical analysisExperimental and clinical data were analyzed for molecular

profiles of glioblastoma using the GBM-BioDP (17). Data areexpressed asmean� SD. Theunpaired two-tailed t testwas used tocompare between two groups. One-way ANOVA, followed byBonferroni test, was conducted to test for significance amongmultiple groups. P < 0.05 was considered significant.

Results and DiscussionRecent data have shown that gene expression datasets may be

used to classify GSCs from different subtypes (15). To investigatewhether our collection of GSCs (Fig. 1A) display distinct expres-sion profiles, an analysis of gene signature was performed (15)followed by principal component analysis (PCA). This definedtwo distinct subpopulations of GSCs, belonging to the P or the M

Figure 1.Heterogeneity of GSCs is mirrored bythe diversity of EV proteincomposition. A, workflow depictingisolation of GSCs fromprimary tumorsfor GSC culture and proteomicanalysis of EVs (left). Representativemicrographs of GSC spheroids(middle) and GSC EVs (right). B, theGSC EV proteome profiledistinguishes P (green) from M (red)GSC subtypes. Proteins sets that varycoherently between subtypes wereidentified by clustering. C, the GSC EVproteome profile separates P and Mglioblastoma subtypes. Genes codingfor proteins sets that vary coherentlybetween GSC subtypes (classical,C, blue; mesenchymal, M, red;proneural, P, green; neural, N,magenta) from 89 protein signatureswere retrieved from TCGA GBMdataset and identified by clustering:power of prediction of top six genes isshown. D, the GSC EV proteomecontent partially mimics cellularexpression. Selected protein setswere validated by Western blottingusing indicated antibodies, � , specificband on FASN blot.

Tumor Heterogeneity Is Enhanced by Extracellular Vesicles

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subtype. As expected, there were also several GSCs that did notcluster into either subtype (Supplementary Fig. S1A). To validatewhether the observed cellular transcriptional subtype diversitywas reflected by the protein composition of EVs released by theseGSCs, EVs were isolated and quantified followed by global massspectrometry (MS)-based analysis of their proteome. Interesting-ly, there was significant physical heterogeneity of EVs released byboth subtypes: larger and homogenously sized EVM, and smallerbut with broader diversity in size EVP. There was no significantdifference in the number of EVs shed by either subtype in culture(Supplementary Fig. S1B). Comprehensive MS analysis revealedover 1,400 proteins within the EV proteome. Over 90% of themwere detected in both subtypes (Supplementary Fig. S1C). Forsubtype signature profiling, a differential expression analysis ofEVP vs. EVM was carried out and 98 proteins were found to besignificantly differentially released in a subtype-dependent man-ner (Fig. 1B, Supplementary Table S1), indicating that the prote-omeofGSCEVs recapitulated subtype clustering. In fact, when theGSC EV proteome data was queried with known molecularsubtypes from TCGA (4), the EV signature clustered into the twosame subgroups (P and M) as those from their respective GSCs(Fig. 1C; Supplementary Table S2). In silico analysis revealedthat proteins identified in EVs from each subtype regulate differ-ent biologic processes and molecular functions. EVP proteinsprimarily control processes related to neurons/nervous systemdevelopment, and EVMproteins function as regulators of receptorbinding, protein synthesis and gene expression (Supplementary

Fig. S1C). To provide validation of the proteome analysis byWestern blots, we selected: (i) specific EV proteins that were mostpredictive of a subtype by TCGA classification (for exampleNCAM1, PLAU for P vs. M GSCs, see Supplementary Fig. S1D),(ii) proteins that were most differentially expressed between thetwo subtypes (for example, IGFPB2 or PNF1 for P vs. M GSCs, seeSupplementary Fig. S1E), and (iii) proteins that are most com-monly present in HGG EVs (ANXA2, FASN; SupplementaryFig. S1E; ref. 14). The analysis showed a cellular and EV sub-type–specific pattern of distribution (Fig. 1D), supporting theglobal analysis (Fig. 1B).

To evaluate whether there were functional consequences afterEVM and EVP exchange, GSCs of each subtype were exposed toEVs isolated from the other subtype, using membrane-taggedGSCs for visualization of EV internalization (18) (Fig. 2A). WhenP GSCs were exposed to EVM, there was a significant increase inGSC sphere frequency, number, viability, and volume (Fig. 2Band Supplementary Fig. S2A–D). Exposure of PGSCs to their ownEVs had no effect. When M GSCs were exposed to EVP, therewas no significant change in M GSC frequency (Fig. 2B) andviability (Supplementary Fig. S2C). However, the frequency oflarger spheroids was moderately increased upon exposure toeither EV (Supplementary Fig. S2B). Next, to model coexistenceof P and M GSCs within tumors (6), single-cell GSCs from eitherM or P subtype were cocultured together to form spheroids(Fig. 2C, left). All of the spheroids ended up growing as mosaicsinstead of growing as homogenous cultures of M or P GSCs only

Figure 2.Differential in vitro effects of GSC coculture and exposure to EVs. A, workflow depicting labeling and cotreatment of GSCs and GSC EVs (top). Representativemicrographs of GSC spheroids releasing labelled EVs (bottom). Arrows indicate EVs shed by P and M GSCs. Scale bar, 50 mm. B, EVM promote growth ofP GSCs. Representative micrographs of GSC spheroids cocultured with EVs (left) and quantification of spheroid frequency (right). � , P < 0.05. Scale bar, 100 mm.C, workflow depicting coculture of labeled GSCs (left). Representative micrographs of GSC spheroids (middle) and transfer of EVs between GSCs in thespheroid (right). Arrows, EV internalization. Scale bars, 100 mm (left) and 25 mm (right). D, M GSCs promote growth of P GSCs. Quantification of cell growth in mono-and coculture. � , P < 0.05.

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(Fig. 2C, middle). This exclusivity of mosaic growth indicated aselective pressure forGSCs to grow in a heterogenous rather than ahomogenous subtype environment (Supplementary movie).Interestingly, these mosaic spheroids formed a visibly distinctarchitecture with the M GSCs clustered together in the inner coreof the spheroid, while P GSCs localized to the outer layers.Importantly, frequent exchange of EVs between cells from bothsubtypes was observed, suggesting dynamic and ongoing EV-mediated communication between cell types (Fig. 2C, right).To verify whether growth of each subtype benefited from theobserved coexistence, growth of GSCs was assessed in cocultureversus monoculture conditions. Similar to the EV treatmentexperiments, growth of M GSCs was not affected in cocultureversus monoculture, but there was a significant increase in PGSCs growth when cocultured with M GSCs (Fig. 2D). Todetermine which signaling pathways may be involved in GSCsubtype cross-talk, the expression of key pro-oncogenic kinaseswas analyzed: AKT was more phosphorylated in P GSCs, whileERK, SRC, and P65 were more phosphorylated in M GSCs(Supplementary Fig. S2E). Although these kinases were morephosphorylated in EVM-treated P GSCs, suggesting a possiblemechanism for the observed increase in P GSC growth, theinvolvement of other signaling pathways cannot be excluded.The analysis of the GSC/EV proteome showed that EGFRwas M GSC–enriched with little immunopositivity in P GSCs(Fig. 1D), which was further validated by in situ staining andqPCR (Supplementary Fig. S2F). When P GSCs were exposedto EVM, EGFR was detected in P GSCs, demonstrating thatEGFR could be transferred from M GSCs to P GSCs by EVs.Such transfer, coupled with the previously observed kinasephosphorylation, could explain the significant growth enhance-ment observed in P GSCs exposed to EVM.

To determinewhether the in vivomicroenvironment influencedthe EV-mediated cross-talk between GSCs observed in vitro, weperformed set of experiments using an intracranial GSC xenograftmodel. First, P GSCs were coinjected with either EVP or EVM.Second, P GSCs were coinjected with M GSCs (Fig. 3A). For thefirst experiment, animals were sacrificed four days after GSCimplantation: an approximately 3-fold higher percentage of Ki-67–positive P GSCs upon coinjection with EVM was observedwhen compared with P GSCs alone. However, this increase wasnot observed upon coinjection with EVP (Fig. 3B). Because MGSCs growmore aggressively than do PGSCs (15), P GSCs andMGSCswere admixed in a 500:1 ratio in the second coimplantationexperiment. Nine days after implantation, tumors formed bymixed GSCs were significantly larger than those comprised of

Figure 3.Heterogeneous GSCs exchange EVs in vivo and promote tumorigenicity. A,workflow depicting in vivo model. B, EVM promote proliferation of P GSCsin vivo. Representative micrographs of P GSCs 4 days after coimplantationwith EVM with Ki-67 immunostaining (top left), higher magnification insets(bottom), and Ki-67 quantification (top right). �, P < 0.05. Scale bars, 200 mm(top) and 50 mm (bottom). C, EVs are transferred intratumorally in vivo.Representative micrographs of coimplanted tumors (top row). Distinctdistribution of P and M GSCs (second row, arrow, infiltrating P GSCs).Intratumoral EV transfer between P andMGSCs (third and fourth row, arrows,internalized EVs). Scale bars from top to bottom: 1mm, 100 mm, 25 mm, 10 mm.D, heterogenous GSC-originated tumors are associated with worsenedsurvival. Kaplan–Meier curves are shown. N¼ 4; P¼ 0.007. Average survival:G34–, 18.5 days, G146þG34–, 14 days.






M GSCs only (Fig. 3C, top), perhaps unsurprisingly as the latterwere initially formed by much fewer cells. However, volume oftumors originated by M GSCs implanted with P GSCs wasapproximately 4-fold greater than that of M GSCs alone (Sup-plementary Fig. S3A), suggesting that the heterogeneous environ-ment provided a mitotic advantage to M GSCs. This differedsomewhat from the in vitro data where EVPs did not provide agrowth advantage to M GSCs, possibly suggesting additionalinfluences to growth in the in vivo model. Analysis of tumorarchitecture revealed thatMGSCs tended to form the noninvasivetumor core, while P GSCs located preferentially to the peripheralzone with single cells invading into surrounding tissue, similarlyto in vitro observation of spheroids' architecture. Both cell typeswere found with numerous internalized EVs from the other celltype (Fig. 3C, bottom and Supplementary Fig. S3B), suggestingthat EV-mediated communication is in fact frequent betweenthese cell types in vivo. Finally, a cohort of animals from thecoimplantation experiment was studied for survival, showing asignificant survival disadvantage for tumors composed of two cellsubtypes (Fig. 3D),when comparedwith those formedbyMGSCsor by P GSCs alone. Analysis of tumor composition revealed thatdespite the initial dominance of P GSCs, by day 9 most of thetumor was composed of M GSCs and by the terminal phasealmost the entire tumor was composed of M GSCs (Supplemen-tary Fig. S3C–D). Likely, M GSCs benefited from the P GSCscoimplantation at the beginning and overgrew to take over theentire neoplasm, suggesting that heterogeneity coexisting withinone tumor ecosystem drives tumor progression.

Finally, we examined whether the subtype-specific heteroge-neity of the GSC EV proteome was relevant to HGG patients'outcome according to TCGA (4, 19). Genes encoding for all GSCEV proteins were associated with poorer outcome in a full cohortof HGG patients (Fig. 4A and Supplementary Fig. S4A). However,when we examined the EV protein profiles separately, the EVMsignature was associated with a significantly worse outcome in Pbut not M tumors (Fig. 4B and Supplementary Fig. S4B). Con-versely, the EVP signaturewas associatedwith a significantlyworseoutcome in M but not P tumor subclasses (Fig. 4C and Supple-mentary Fig. S4C). These datasets indicated that heterogeneitywithin tumors, which may be propagated throughout the tumorvia EV communication, was associated with decreased survival.This is in agreement with the scenario proposed by Patel andcolleagues (6) where the clinical outcome of a glioblastomasubclass is influenced by the proportion of tumor cells of alternatesubtypes and emphasizes the clinical importance of intratumoralheterogeneity.

The combination of tumor EVs and cell-specific secretedmolecules that can be taken up by neighboring or distantrecipient cells, leading to changes in gene expression, suggestsa cell-specialized role in physiologic and pathologic conditions(20). We have leveraged the analysis of GSC EV proteomicsto characterize heterogeneous extracellular programs withinHGG tumors interrelating their release, uptake, and function,which have fundamental implications for biology and thera-peutic strategies of HGG, as EVs provide two-way influencethrough release/uptake between tumors' cells in vivo (Fig. 4D).Analysis of single-cell transcriptome demonstrated transcrip-tional diversity within an individual tumor (6) and our analysisreveals that transfer of EV protein cargo between tumor cellssubpopulations offers a means and opportunity for dynamictransitions.

Figure 4.GSCEV proteomepredicts patients' outcome. A–C, survival analysis based onthe impact of the prognostic index of multiple protein-coding genes from allGSC EVs (A), EVM (B) and EVP (C) based on retrospective data extrapolatedfrom the TCGA. D, summarizing cartoon, the heterogeneity of EV cargocontributes to the diverse complexity and enhanced progression of HGG.

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Ricklefs et al.




Disclosure of Potential Conflicts of InterestE.A. Chiocca is a consultant/advisory board member for Tocagen, Nanotx,

Alcyone, Merck, and Stemgen. No potential conflicts of interest were disclosedby the other authors.

Authors' ContributionsConception and design: F. Ricklefs, X.O. Breakefield, E.A. Chiocca,J. Godlewski, A. BroniszDevelopment of methodology: F. Ricklefs, M. Mineo, I. Nakano, R. Weissleder,X.O. Breakefield, A. BroniszAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): F. Ricklefs, M. Mineo, A.K. RoojAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): F. Ricklefs, M. Mineo, R. Weissleder, E.A. Chiocca,J. Godlewski, A. BroniszWriting, review, and/or revision of the manuscript: F. Ricklefs, A.K. Rooj, A.Charest, R. Weissleder, X.O. Breakefield, E.A. Chiocca, J. Godlewski, A. Bronisz

Administrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): F. Ricklefs, A. Charest, A. BroniszStudy supervision: F. Ricklefs, R. Weissleder, E.A. Chiocca, J. Godlewski,A. Bronisz

AcknowledgmentsThe authors thankHannes Ricklefs for helping in the data analysis by writing

a python program.

Grant SupportThis work was supported by grants NCI P01 CA69246 (E.A. Chiocca,

R. Weissleder, X.O. Breakefield) and by NCI P01 CA163205 (E.A. Chiocca),NCI 1R01 CA176203-01A1 (J. Godlewski), and DFG RI 2616/1-1 (F. Ricklefs).

Received December 18, 2015; revised March 9, 2016; accepted March 14,2016; published OnlineFirst March 24, 2016.

References1. Beroukhim R, Getz G, Nghiemphu L, Barretina J, Hsueh T, Linhart D, et al.

Assessing the significance of chromosomal aberrations in cancer: Meth-odology and application to glioma. Proc Natl Acad Sci U S A2007;104:20007–12.

2. Parsons DW, Jones S, Zhang X, Lin JC-H, Leary RJ, Angenendt P, et al. Anintegrated genomic analysis of human glioblastoma multiforme. Science2008;321:1807–12.

3. Phillips HS, Kharbanda S, Chen R, Forrest WF, Soriano RH, Wu TD, et al.Molecular subclasses of high-grade glioma predict prognosis, delineate apattern of disease progression, and resemble stages in neurogenesis. CancerCell 2008;9:157–73.

4. Verhaak RGW, Hoadley KA, Purdom E, Wang V, Qi Y, WilkersonMD, et al.Integrated genomic analysis identifies clinically relevant subtypes of glio-blastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, andNF1. Cancer Cell 2010;17:98–110.

5. Brennan Cameron W, Verhaak Roel GW, McKenna A, Campos B, Noush-mehr H, Salama Sofie R, et al. The somatic genomic landscape of glioblas-toma. Cell 2014;155:462–77.

6. Patel AP, Tirosh I, Trombetta JJ, ShalekAK,Gillespie SM,WakimotoH, et al.Single-cell RNA-seq highlights intratumoral heterogeneity in primaryglioblastoma. Science 2014;344:1396–401.

7. Hale JS, Sinyuk M, Rich JN, Lathia JD. Decoding the cancer stem cellhypothesis in glioblastoma. CNS Oncol 2013;2:319–30.

8. Lathia JD, Mack SC, Mulkearns-Hubert EE, Valentim CLL, Rich JN. Cancerstem cells in glioblastoma. Gene Dev 2015;29:1203–17.

9. Schonberg DL, Lubelski D, Miller TE, Rich JN. Brain tumor stem cells:Molecular characteristics and their impact on therapy. Mol Aspects Med2014;39:82–101.

10. Stommel JM, Kimmelman AC, Ying H, Nabioullin R, Ponugoti AH,Wiedemeyer R, et al. Coactivation of receptor tyrosine kinases affects theresponse of tumor cells to targeted therapies. Science 2007;318:287–90.

11. Nathanson DA, Gini B, Mottahedeh J, Visnyei K, Koga T, GomezG, et al. Targeted therapy resistance mediated by dynamic regu-

lation of extrachromosomal mutant EGFR DNA. Science 2014;343:72–6.

12. Skog J, Wurdinger T, van Rijn S, Meijer DH, Gainche L, Curry WT, et al.Glioblastoma microvesicles transport RNA and proteins that promotetumour growth and provide diagnostic biomarkers. Nat Cell Biol2008;10:1470–6.

13. Godlewski J, Krichevsky AM, JohnsonMD, Chiocca EA, Bronisz A. Belong-ing to a network—microRNAs, extracellular vesicles, and the glioblastomamicroenvironment. Neuro Oncol 2015;17:652–62.

14. Bronisz A, Wang Y, Nowicki MO, Peruzzi P, Ansari KI, Ogawa D, et al.Extracellular vesicles modulate the glioblastoma microenvironment via atumor suppression signaling network directed by miR-1. Cancer Res2014;74:738–50.

15. Mao P, Joshi K, Li J, Kim SH, Li P, Santana-Santos L, et al. Mesenchymalglioma stem cells are maintained by activated glycolytic metabolisminvolving aldehyde dehydrogenase 1A3. Proc Natl Acad Sci U S A2013;110:8644–9.

16. KimSH, EzhilarasanR, Phillips E,Gallego-PerezD, Sparks A, TaylorD, et al.Serine/Threonine kinase MLK4 determines mesenchymal identity in gli-oma stem cells in an NF-kappaB-dependent manner. Cancer cell2016;29:201–13.

17. Celiku O, Johnson S, Zhao S, Camphausen K, ShankavaramU. Visualizingmolecular profiles of glioblastoma with GBM-BioDP. PLoS One 2014;9:e101239.

18. Lai CP, Kim EY, Badr CE, Weissleder R, Mempel TR, Tannous BA, et al.Visualization and tracking of tumour extracellular vesicle delivery andRNA translation using multiplexed reporters. Nat Commun 2015;6:7029.

19. Consortium GT. The Genotype-Tissue expression (GTEx) project. NatGenet 2013;45:580–5.

20. Hoshino A, Costa-Silva B, Shen TL, Rodrigues G, Hashimoto A, Tesic MarkM, et al. Tumour exosome integrins determine organotropic metastasis.Nature 2015;527:329–35.






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