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Molecular analysis of ex-vivo GBM cells revealed a common and angiogenic profile but different signatures among high gliomas

* Corresponding author: Sanchez-Martin


1 Instituto de Estudios de Salud de y León (IESCyL), Spain

2 Centro de Investigación del Cáncer Salamanca

3 OncoStem Pharma Spain


Gliomas are the common type of primary tumours, and in this group (GBMs) are the higher-grade gliomas fast progression and unfortunate Two major aspects of glioma that contributes to its awful are the formation of new blood vessels the process of angiogenesis and the invasion of cells. Despite of advances, survival for GBM patients with therapy is less than Even in those patients low-grade gliomas, that a moderately good prognosis, is almost never curative. studies have demonstrated the of a small fraction of glioma with characteristics of neural cells which are able to in vitro forming neurospheres and can be isolated in vivo using markers such as CD133. The aim of study was to define the molecular of GBM cells expressing CD133 in with non expressing CD133 This molecular classification lead to the finding of new potential targets for the rationale treatment of grade GBM.

Eight primary and non cultured GBMs used in order to study the expression signatures from its positive and negative populations by FACS-sorting. Dataset was generated Affymetrix U133 Plus 2 and analysed using the software of the Expression Console. In addition, analysis of these tumours was out by CGH arrays, FISH studies and

Gene expression analysis of vs. CD133- cell population each tumour showed CD133+ cells presented characteristics in all glioblastoma samples of genes involved in angiogenesis, and down-regulation of genes implicated in assembly, neural cell and neurological disorders). Furthermore, clustering of gene expression led us to between two groups of samples: discriminated by tumour location the most importantly, the group by their proliferative potential;

Primary glioblastomas could be according to the properties of their cells. The molecular characterization of potential stem cell could be critical to find new targets and to develop an effective for these tumours with dismal prognosis.


The relapse and mortality rate that current therapies do not all malignant cells. In this there is increasing evidence many types of cancer their own stem cells: stem cells (CSCs), are characterized by their self-renewing and differentiation ability [1 ]. The study of disorders shed light on the between cancer and stem compartments, and the mechanisms by which might appear and change the progression of the disease [2 ,3 ]. However, the for the existence of CSCs in solid has been more difficult to because of the lack of specific surface markers. During the years, different cancer subpopulations from selected of human solid cancers been identified (breast [4 ], [5 -7 ], colon or colo-rectal [8 -10 ], head and [11 ] and pancreatic cancer [12 ]). These through the use of cell culture, and/or MACS methods, been able to identify cell populations within the showing hallmarks of stem This stem cell including self-renewal and lineage was demonstrated by serial transplantation in animal models. Specifically, the of solid tumour stem has gained momentum particularly in the of gliomas, the most common of brain tumours. In this glioblastoma multiforme is the highest-grade [GBM; grade IV] and is manifested by genetic and phenotypic heterogeneity [13 -15 ]. Two aspects of glioma biology contributes to its awful prognosis are the of new blood vessels through the of angiogenesis and the invasion of glioma the hallmarks of GBM [16 ]. In addition, these blood vessels have been shown to create a niche that houses stem cells [17 ].

Despite of the advances, two-year survival for GBM with the most favourable is less than 30%. in those patients with gliomas therapy is almost curative. Recent studies confirmed the existence of a small of glioma cells with of neural stem cells [1 ]. In this fraction is characterized by its ability, its strikingly increased resistance, and finally, by its ability to surface markers that are used for their FACS-based [5 ,6 ]. With the implantation during last decade of the NS forming as a robust method for the isolation of stem cells [18 ], it has become accepted that adult brain harbours a pool of responsible for the persistent neurogenesis, in limited adult brain such as the sub-ventricular zone, bulb and hippocampal dentate [19 ].

However, it should be borne in that the NS assay is not the most source of primary adult cells for transcriptomic analysis cells are selected based on its in proliferation capacity in the presence of and growth factors in their cultures such as EGF and FGF.

At the end of century, two independent laboratories identify and isolate human nervous system stem using antibodies against [20 ,21 ]. This protein, named identifies a subset of human brain cells distinct to haematopoietic stem cells, are also CD133+ but are also [22 ]. This subset of human fetal brain cells is of neurosphere initiation, self-renewal, and differentiation at the single-cell level [20 ]. The cells can differentiate in vitro to and glial cells, and their into the lateral ventricles of NOD-SCID mouse brains in specific engraftment in numerous of the brain [20 ,21 ,23 ].

The CD133 marker is a protein which is expressed in type of progenitors as human brain cells or human stem cells [20 -22 ]. In brain the proportion of these CD133+ represent a minority of the tumour population and are also capable to tumour formation in vivo . it have also been that a proportion of these could be maintained by CD133- [24 ], there are several evidences how this small fraction of CSC forming NS, can also be isolated CD133 as a selection marker [6 ].

In the study, we have analysed the molecular signature of eight primary GBMs focused on its positive and negative cells. all tumours were studied any treatment of the patient and without tumour cell culturing. In to the expression analysis of the FACS-sorted we have also performed analysis by CGH-arrays, FISH at PTEN and EGFR loci, and at the MGMT promoter. The results concluded that the gene signature of CD133+ discriminate genes to all samples involved in two characteristic pathways deregulated in angiogenesis and invasiveness. However, gene expression profile allowed distinguishing between two GBM subtypes in higher or lowering tumours. The molecular biology and the signature of these CD133+ that drive and support the growth will shed on the development of fresh and specific strategies.


Samples, cytometry and sorting assays

tumours from eight affected of primary GBM without any treatment were collected and pathologic features are summarized in 1 ). Patients’ diagnostic were by the Pathology Facility from the Hospital of Salamanca, Spain. At the extraction moment, a vast of each tumour was processed to the CD133+ and CD133- cells previous cell culture. suspensions were prepared individual tumours by standard We decided to undergo a mechanical of tumour samples due to the softness of samples, avoiding enzymatic that could change the surface and even their expression. Briefly, tumours carefully sliced and forced a 70 μm single-cell filter into the Ca ++ /Mg ++ phosphate-buffered saline by applying pressure using the piston of a plastic syringe, All single-cells used for staining. Cells immunophenotyped using human (293C3) phycoerythrin conjugated (MACS, Miltenyibiotec). Mature red were depleted by hypotonic solution (0.38% ammonium for 15 minutes on ice) before Cells suspended in Ca ++ /Mg ++ free saline supplemented with 1% calf serum were with this antibody 1 μg/10 6 cells) for 30 minutes on Cell fluorescence was analyzed and using the FACS Aria (Becton Dickinson, New Jersey, CD133 antibody was tested in human bone marrow cells in which CD133 cells were described (Figure 1 ). BM cells were with CD133 and CD34 (Pharmingen), sustained in studies demonstrate that antibodies CD133 also identified a of CD34 bright BM hematopoietic cells [22 ]. Cell viability was by propidium iodide exclusion (5 Sigma) using flow

Table 1. Clinical characteristics, promoter methylation and FISH of eight primary GBMs.

1. FACS sorting of glioblastoma using CD133 and CD34 . Control samples from bone marrows incubated CD133 antibody. 1: Total 2: Gate CD34 without 3: Gate CD34 with

Expression arrays

We studied a generated with Affymetrix Plus 2 arrays (Affymetrix, Clara, CA, USA) in 8 gliomas. from this expression have been deposited at GEO [25 ] accession number GSE18015.

cells (CD133+ and CD133- each tumour) using methods were collected in vials containing RNA Later Chatsworth, CA, USA). Total RNA was from CD133+ and CD133- cells using Trizol Carlsbard, CA) making a total of 16 (8 positives and 8 negatives). The integrity of the RNA was with the Agilent Bioanalyzer using the RNA 6000 Pico kit We used the GeneChip ® Expression Amplification Two-Cycle Target kit (Affymetrix, Santa Clara, CA, to label the RNA following the manufacturer The cRNA was hybridized to Affymetrix U133 Plus 2 arrays to the manufacturer protocol. Briefly, cDNA was synthesized routinely less than 1 microgram of RNA primed with a poly-(dT) -T7 The cDNA was used in an in vitro reaction in the presence of T7 RNA polymerase and modified nucleotides during 16 at 37°C. Biotinylated cRNA was and then fragmented (35-200 together with hybridization and hybridized to the microarrays for 16 h at 45°C. the GeneChip Fluidics Station 450 the biotin-labelled cRNA was revealed by reactions with streptavidin conjugate, biotinylated anti-streptavidin and streptavidin R-phycoerythrin conjugate. The were finally scanned in an GeneChip Scanner 7G Plus.

Preliminary data analysis was using the software of the Affymetrix Console from AGCC (Affymetrix GeneChip Command version 1.1) following the procedures described in the Affymetrix: Console User Guide, the 3′ Expression Analysis for MAS5 and PLIER algorithms in two steps. MAS5 calculated the call index for each of the probe sets on the chip used were standard for the HG Plus 2 array: alpha1 = alpha2 = 0.06, Tau = 0.015, TGT = This present call was used to select 245 probe having Presence index the 16 analyzed samples. PLIER was used to calculate the normalized values of the probe sets quantile normalization and PM-MM correction methods). Statistical and post-processing were performed TIBCO Spotfire 9.1 (TIBCO Inc. Palo Alto CA, webcite ).

Network was performed mapping the results on the IPA 8 database (Ingenuity Pathway

CGH array

DNA from each sample was extracted with the phenol-chloroform method and normal DNA was from human placenta of donors. DNAs were using the Nanodrop spectrophotometer. DNA was assessed by the 260:280 ratio and its by agarose gel ethidium bromide Genomic-wide analysis of DNA copy in each patient was performed CGH based array. Due to the low proportion of positive cells in each sample, CGH array only was using genomic DNA from the tumour. Slides containing BACs were produced in de Investigación del Cáncer (Salamanca, The particular bacterial artificial (BAC) and P-1 derived artificial set used to produce this is distributed to academic institutions by the Trust Sanger Institute United Kingdom) and contains spaced at ≈ 1 Mb density over genome, a set of subtelomeric sequences for chromosome arm and a few hundred of probes for their involvement in oncogenesis. The content is available in the ) [27 ,28 ]. For unsupervised clustering analysis, we the relative ratio value for BAC clone to a score of 1 (gained/amplified), 0 (no or -1 (lost) based data by the binary segmentation method by Olshen et al. [29 ] and analyzed data Cluster and TreeView of GEPAS Experiment Viewer 4.0) on the average linkage method the Pearson uncentered metric Statistical evaluation was carried out the SPSS 15.0 statistical (Chicago, Illinois, USA). All reported were two-sided and significance was defined as P-values Complementary details on this are summarised in Additional file 1 .

file 1. Complementary details on CGH method . Complementary details of the CGH in GBM tumours.

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Dual-probe in situ analysis were with locus-specific probes for 7/EGFR gene and centromere gene (Vysis, Dowerners IL). FISH studies carried out following well-established [30 ]. Polysomies (chromosomal gains) defined as more than 10% of containing three or more CEP Specimens were considered to an amplification of EFGR when than 10% of CD133 negative cells exhibited an EGFR/CEP7 2 or inestimable tight clusters of of the locus probe.

CD133+ and amplified RNA samples were to cDNA. PCR reactions were using equal amounts of as template. SYBR Green PCR mix (Applied Biosystems, USA) was for template amplification using protocol with specific for each of the transcripts examined file 2. Supplemental Table Incorporation of the SYBR Green dye PCR products was monitored in real with an ABI PRISM 7000 detection system (Applied SDS system software was used to the fluorescent data into cycle ( C t ) at which exponential of products begins. The differences in the C t (d C t ) between the transcript of interest and control (GAPDH) were to determine the relative expression of the in each, adapted from [31 ]. was performed using specific to corroborate expression array for several genes of those 245 probes [Additional file 3. Figure S1].

Additional file 2. qPCR Sets . Set of primers carefully to test mRNA expression in and CD133- cells by SYBR real-time PCR.

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file 3. qPCR validation of candidates differentially expressed in arrays . Relative expression of six candidates differentially expressed CD133+ cells and CD133- from four representative of samples is shown. Names of analyzed are on the x-axis and the CD133+/CD133- fold differential regulation is on the


In order to check the of the CD133 antibody and the FACS, we tested the methodology in a human marrow sample. In normal CD133 antibody also a subset of bone marrow cells, which are also positives. Figure 1 shows how antibody identifies a pool of human CD133+/CD34+ cells. the same procedure, we sorted the positive population from fresh GBM sample without cell culture (Figure 2 ). 1 shows the absolute number and of CD133+ cells obtained each sample as well as parameters of each patient. It is to note that only two patients with higher of CD133+ cells (more 10000 cells) did not response to the Interestingly this correlation, CD133+ cell number and to therapy, has also been in patients and in GBM cultured cells [33 -35 ] further validate our approach.

2. FACS sorting of GBM cells CD133 antibody . Dot plot of CD133+ and CD133- populations in GBM samples are shown. CD133+ is painted in red and CD133- population in Percentage of each population is (green for CD133- and red for CD133+ Tumour sample is illustrated in the side of each plot.

The of different genetic alterations in the of primary glioblastoma such as amplification, PTEN deletion or promoter methylation has been described. As EGFR . PTEN and genes are usually altered in GBMs, we decided to corroborate the nature of our samples by checking for the of these alterations in the bulk cell population of GBMs by analysis and MLPA assay. amplifications were detected in 3 of 8 and PTEN deletions in 6 of 8 samples. we also detected MGMT methylation but none of these were significantly related to the features of the patients (see 1 and Figure 3B ). It is important to remark the number of cases studied is too low to find this kind of

Figure 3. CGH array and MGMT methylation assays in GBM samples. A) cluster analysis of CGH data 8 primary GBMs. Each represents one case and each row one BAC clone. We assigned values of 1, 0 and -1 for no change and loss, respectively. are in green and gains in red. 0.05. B) Ideogram showing promoter methylation.

Common imbalances identify patients higher number of CD133+ without treatment response

In to the expression studies, we analyzed the profile by CGH in the bulk tumours. All reported were two-sided and significance was defined as P-values In more than 50% of cases the affected to chromosomal regions at 1q31-q42, 3q25, 4p15, 7p21, 7q21, 9p21, 11q22, 12q21 and 18q12. The were located on regions at 1p13, 2p23, 5p15, 12q13, 13q14, and 17p were affected on more than 50% of [Additional file 4. Supplemental S2]. Two major genetic emerge from the unsupervised of CGH data (Figure 3A ). Significantly, the two cases with higher of CD133+ cells and without response, samples G4 and G11, together. This cluster was with common genomic with gains on 3p21.31, 6q25, 7p14.2, 9q22, 20q13 and 22q13 chromosomes.

file 4. CGH-array data set . gains and losses from bulk cells of GBM patients are in this table. Each shows the median of Cy5/Cy3 intensity of triplicate spots of clone normalized by GEPAS.

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CD133+ vs. CD133- gene analysis divided GBMs in 2 groups

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Although the number of is not very large, the main that distinguishes this from previous studies [36 ,37 ] on the ex-vivo study of GBM cells were analysed. Using sorting of CD133+ cells previous cell culture led us to a bona fide primary of CD133+ cells. Even these cells represent a low in the number of tumour cells, as in a tissue, we were able to and amplify their RNA (by two rounds of in order to study their expression signature in comparison to its population of CD133- from the GBM tumour.

Data normalized from analysis was used to calculate those probe sets were present (as described in the algorithm) in all the samples (16 arrays 8 GBM; hybridization per cell Results from this analysis have been at GEO [25 ] with accession number webcite ) allowed us to the first classification of these Importantly, GBM samples were in two main groups (Figure 4 ). G9 and G11 were grouped together and from the rest. However, only common biological was their tumour location. G9 and G11 a parietal location versus the or local locations presented by the tumours (Table 1 ).

Figure 4. clustering of CD133+ cells vs. cell gene expression from each tumour show 2 main GBM groups . To characterize glioblastoma stem of GBM tumours, we compared the gene profiles of purified CD133+ from GBM patients versus from each patient. gene (identified at right) is by a single row of coloured boxes; patient is represented by one single Data are displayed by a colour where red indicates over-expression in fraction versus CD133-cells. A of genes over-expressed for almost all are grouped in the bottom. SOTArray from GEPAS Release let us to classify CD133+ vs. CD133- from each tumour in 2 groups: G9, G11 and the rest.

Commonly and down-regulated genes in CD133+

Following the initial classification by SOTArray of GEPAS, we were to discriminate a minor group of commonly up (19 genes) and down-regulated (22 in all samples (CD133+/CD133-) (Tables 2 and 3 ). up-regulation of genes such as . COL1A2 . PGF, LRRFIP1, or TGFB1 suggested an important of this pool of cells in vessel formation, angiogenesis, and proliferation pathways, essentials in tumour progression [38 -40 ] (Figure 5 ). On the hand, the group of genes down-regulated in all CD133+ vs. CD133- (that means, over-expressed in the compartment) were strikingly to cell assembly, neural organization and molecular pathways in neurological disorders. That is the of, GNB2L1 . DPYSL2 . TUBA1A or . all of them important players in migration, morphology and actin in brief, motility of neural cells (Figure 6 ).

Table 2. up-regulated genes in CD133+ GBM cells.

Table 3. Common genes in CD133+ vs.CD133- GBM

Figure 5. Commonly CD133+ up-regulated genes participate in tumour development and neural disorders . Ingenuity representation and by functions of those common genes in all CD133+ vs. CD133- GBM samples. Red colour genes are the positive deregulated and grey one with a lower over-expression in this group. The first of genes ( COL1A1, COL1A2, . ) has been described largely in and permeability whereas the second ( LRRFIP1 and OPHN1) participates in disorders. Changing transcription of all of them favour tumour

Figure 6. Common CD133+ down-regulated genes are involved in assembly organization and cancer . representation and classification by functions of commonly down-regulated genes in all vs. CD133- cell GBM samples. colour represents those differentially regulated in CD133+ vs. that participates in cell migration and cancer pathways.

Two GBM groups can be functionally defined to the expression pattern of 40 genes

The group of genes discriminated by the of GEPAS presented a differential expression pattern in two of the eight vs. CD133- GBM samples, G4 and G7, in contrast to the cases. In this group, we out a cluster of genes clearly in some of CD133+ vs. CD133- GBM (G4 and G7) but repressed in the rest. Specifically, a of 40 well-defined genes, classified to their function, were to distinguish between 2 different GBM (Figure 7 ) revealing the possible proliferative potential in high GBM tumours ( VIM . GLUL . PLK1 . RPS4X . ) (Figure 8 and Table 4 ).

7. Forty differential genes in G4 and G7 discriminate between high or low potential . Unsupervised c lustering and pathways representation of 40 differentially genes. A) Unsupervised clustering of 40 gene list let us to distinguish 2 defined and opposite groups. principal represented pathways B) recombination and repair pathways and C) and cell compromise. Those with a positive pattern for this gene expression could present a higher potential of their tumour cells or, by the opposite, a lower potential of the mature glioma

Figure 8. Forty differentially genes in ex-vivo CD133+/CD133- GBM classify these tumours to their functional categories . functional classification of 40 differentially genes in primary GBMs two main groups of GBM according to proliferative potential.


are the higher-grade gliomas with progression and unfortunate prognosis. studies have demonstrated in tumours the existence of a small of cancer cells endowed features of primitive neural Although some observations out towards the involvement of CD133- in tumour maintenance [24 ], several have involved the CD133 + as the brain tumour initiating [6 ,41 ,42 ]. In any case, studies performed in to characterize the glioblastoma stem have been carried out in vitro . cultured tumour While these cultured present the capacity to form NS, pathways in cell/tumour biology likely be altered as a direct of the cell culturing such as adhesion, cell-niche junctions, to mitogen activation, rapid of the cells etc.

To gain into the characterization of these we examined directly for the first CD133+ cells by FACS-based from ex-vivo primary without the intervention of cell or any prior expansion procedure.

that the cohort of tumours was not very large, we could a correlation among clinical response to treatment and genomic in two samples (G4 and G11). Both of tumours showed the highest of CD133+ cells, the lack of to treatment and similar chromosomal (multidimensional scaling analysis relationship among these However, this correlation was not supported by transcription profiling of and CD133- cells. Indeed, analysis of CD133+ vs. CD133- expression (Figure 4 ) showed only G9 and G11 samples were together and apart from the being the tumour location the biological feature able to them (see Table 1 ). of this low number of samples, scaling analysis established a relationship between G9/G11 location and their gene

To understand the biological properties of the compartment, we sought to identify gene signature by the comparison of vs. CD133- cell populations. array-based analysis led us to the identification of profiles with common and down-regulated genes. Up-regulated such as COL1A1 . COL1A2 . PGF [38 ] or [43 ], suggested an important role of compartment in blood vessel angiogenesis, permeability and invasiveness, functions in tumour progression [38 -40 ]. most of these up-regulated encoded secreted proteins in autocrine and paracrine signalling, TGFBI . a pleiotropic cytokine among other functions, can the dissociation of VE-cadherin junctions endothelial cells which favour mature tumour or GBM migration [43 ]. Up-regulation of these in putative CD133+ stem would help to increase the of cancer stem cells the brain, which is consistent the high invasive characteristics of tumours and their high to colonize the adjacent area. It is worthy to mention in this regard, the importance of the microenvironment in the cell/cancer stem cell as has recently been pointed out the identification of the perivascular niche in I-IV astrocytomas [44 ]. Several suggest that normal stem cells, and likely neural cancer stem exist within protective as the vascular niches, into endothelial cells secrete that regulate neural cell function [45 ,46 ]. This the question of whether CSCs be located and regulated by these Calabrese et al. proposed that the microvasculature generates specific microenvironments promoting the maintenance of [47 ]. Recent studies using glioblastoma xenografts suggest CSCs secrete proangiogenic that promote the recruitment and of tumour blood vessels [48 ] significantly facilitates brain growth and invasion. Our gene findings in ex-vivo CD133+ cells clearly support result.

High expression in the compartment of genes such as . transcriptional repressor of EGFR [49 ], support the idea of EGFR as a secondary event in the process of GBM by promoting infiltration and mediating to therapy. In this same the positive regulation of the tumour gene TMEFF2 [50 ] in the potential stem cell compartment in GBMs, could also as a late event in the initiation of progression. In fact, low levels of and other genes responsible for or cell assembly in the CD133- would promote the down-regulation of to cell interactions and junctions, a molecular mechanism for the highly nature of the GBM.

The second of genes, commonly down-regulated in all vs. CD133- cell from ex-vivo GBM samples (that over-expressed in the CD133- compartment) found to be associated to cell neural cell organization and disorders. That is the case of such as GNB2L1 . an anchor involved in adhesion and migration of glioma cells [51 ], DPYSL2 . a of microtubule assembly and neuronal [52 ], TUBA1A [53 ] or CFL . which controls migration and cell cycle [54 ,55 ]. This group of genes important roles in cell cell polarity and actin (Figure 6 ). In this same scenario, it would be interesting to the deregulated expression of HIF-1 This gene which is in most of the CD133+ samples is involved in tumour angiogenesis and growth [56 ], and could play role in the later events drive tumour progression. In regard, recent studies demonstrated that HIF-1 stabilization contribute to tumour one of the main characteristics of primary [16 ]. Mutations in metabolic enzymes, in isocitrate dehydrogenase enzymes and IDH2), have been to be involved in glioma development and facilitate HIF-1 protein [57 ,58 ]. The negative deregulation of the HIF-1 that we have observed in ex-vivo CD133+ cells in work, also support idea.

A notable feature of the gene pattern of CD133+ cells was the expression of 40 genes that GBM samples in two opposite molecular The classification of these 40 genes to their function (Figure 8 and 4 ) pointed to their implication in growth, cell death, DNA recombination and, definitively, in proliferative control. Amongst genes we wanted to emphasize the expression of the gene coding for ( VIM) . an intermediate filament of the lineage involved in migration, signalling, cancer and neurological [59 ,60 ]. Some other genes expressed in this pool of CD133+ and also involved in and neurological disease are RPS4X . or TUBA1B (Table 4 ). Another member of the top 40 list of genes was . a pleitropic ubiquitin ligase participates in a wide variety of functions related to cell such as cell growth/death, and DNA and that has been described to be in different carcinomas [61 ] (see 8 and Table 4 ). Interestingly, this gene has also been to be an important control gene for the capacity of embryonic NSC in the mice [62 ]. encodes the glutamine synthetase, a enzyme required for the maintenance of the balance and that when causes severe malformations and death [63 ]. Finally, PLK1 . the kinase par excellence, modulates entry and promotes cell upon upregulation as an oncogene [64 -66 ]. differentially regulated molecules be playing pivotal roles in the tumour cells in a switch-on that enables them to proliferate and invade the surrounding tissue.

Table 4. Functional of 40 differentially expressed genes in vs.CD133- GBM samples

In brief, the obtained in this study the presence in CD133+ cells primary glioblastoma of a common expression signature involved in the promotion of proangiogenic and invasive Additionally, CD133+ gene pattern led us to discriminate between two GBM subtypes in higher or lower tumours. The molecular biology and the signature of these CD133+ that drive and support the growth will shed on the development of new treatments to fight GBMs.


Ex-vivo of CD133+ primary GBM cells has us to the valid detection of a common expression profile among principally characterized by the expression of involved in blood vessel angiogenesis and invasiveness, the main of glioma biology that to its adverse prognosis. Besides, obtained from the analysis of a of 40 genes differentially expressed in GBM suggest that primary GBM can be according to the properties of their cells. Differences between groups were provided by the potential of their CD133+ (potential tumour stem We can conclude that molecular of CD133+ population in primary could be critical in the development of new and treatments for these tumours very dismal prognosis.

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