Molecular analysis of ex-vivo CD133+ GBM cells revealed a common invasive and angiogenic profile but different proliferative signatures among high grade gliomas

Abstract

Background: Gliomas are the most common type of primary brain tumours, and in this group glioblastomas (GBMs) are the higher-grade gliomas with fast progression and unfortunate prognosis. Two major aspects of glioma biology that contributes to its awful prognosis are the formation of new blood vessels through the process of angiogenesis and the invasion of glioma cells. Despite of advances, two-year survival for GBM patients with optimal therapy is less than 30%. Even in those patients with low-grade gliomas, that imply a moderately good prognosis, treatment is almost never curative. Recent studies have demonstrated the existence of a small fraction of glioma cells with characteristics of neural stem cells which are able to grow in vitro forming neurospheres and that can be isolated in vivo using surface markers such as CD133. The aim of this study was to define the molecular signature of GBM cells expressing CD133 in comparison with non expressing CD133 cells. This molecular classification could lead to the finding of new potential therapeutic targets for the rationale treatment of high grade GBM.

Methods: Eight fresh, primary and non cultured GBMs were used in order to study the gene expression signatures from its CD133 positive and negative populations isolated by FACS-sorting. Dataset was generated with Affymetrix U133 Plus 2 arrays and analysed using the software of the Affymetrix Expression Console. In addition, genomic analysis of these tumours was carried out by CGH arrays, FISH studies and MLPA;

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

Conclusions: Primary glioblastomas could be sub-classified according to the properties of their CD133+ cells. The molecular characterization of these potential stem cell populations could be critical to find new therapeutic targets and to develop an effective therapy for these tumours with very dismal prognosis.

Figure 1

FACS sorting of glioblastoma cells using CD133 and CD34 antibodies. Control samples from human bone marrows incubated with CD133 antibody. 1: Total cellularity; 2: Gate CD34 without CD133-PE; 3: Gate CD34 with CD133-PE.

Figure 2

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

Figure 3

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

Figure 4

Unsupervised clustering of CD133+ cells vs. CD133- cell gene expression signature from each tumour sample show 2 main GBM groups. To molecularly characterize glioblastoma stem cells of GBM tumours, we compared the gene expression profiles of purified CD133+ cells from GBM patients versus CD133-cells from each patient. Each gene (identified at right) is represented by a single row of coloured boxes; each patient is represented by one single column. Data are displayed by a colour code where red indicates over-expression in CD133+ fraction versus CD133-cells. A group of genes over-expressed for almost all samples are grouped in the bottom. SOTArray tool from GEPAS Release v3.1, let us to classify CD133+ vs. CD133- cells from each tumour in 2 mainly groups: G9, G11 and the rest.

Figure 5

Commonly CD133+ cell up-regulated genes participate in angiogenesis, tumour development and neural developmental disorders. Ingenuity representation and classification by functions of those common up-regulated genes in all CD133+ vs. CD133- cell GBM samples. Red colour genes are the most positive deregulated and grey one those with a lower over-expression levels in this group. The first cluster of genes (COL1A1, COL1A2, TGFB1...) has been described largely in angiogenesis and permeability whereas the second cluster (LRRFIP1 and OPHN1) participates in developmental disorders. Changing transcription pattern of all of them favour tumour development.

Figure 6

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

Figure 7

Forty differential genes in G4 and G7 samples discriminate between high or low proliferative potential. Unsupervised clustering and ingenuity pathways representation of 40 differentially expressed genes. A) Unsupervised clustering of this 40 gene list let us to distinguish 2 well defined and opposite groups. Ingenuity principal represented pathways include B) recombination and repair pathways and C) cancer and cell compromise. Those GBMs with a positive pattern CD133+/CD133- for this gene expression signature, could present a higher proliferative potential of their tumour stem cells or, by the opposite, a lower proliferative potential of the mature glioma cells.

Figure 8

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