Journal of Neuro-Oncology

, Volume 94, Issue 1, pp 1–19

Molecular properties of CD133+ glioblastoma stem cells derived from treatment-refractory recurrent brain tumors

Authors

  • Qinghai Liu
    • Department of Medicine, Division of Hematology-Oncology, David Geffen School of MedicineUniversity of California Los Angeles
  • David H. Nguyen
    • Department of Medicine, Division of Hematology-Oncology, David Geffen School of MedicineUniversity of California Los Angeles
  • Qinghua Dong
    • Department of Medicine, Division of Hematology-Oncology, David Geffen School of MedicineUniversity of California Los Angeles
  • Peter Shitaku
    • Department of Pathology and Laboratory Medicine, David Geffen School of MedicineUniversity of California Los Angeles
  • Kenneth Chung
    • Department of Medicine, Division of Hematology-Oncology, David Geffen School of MedicineUniversity of California Los Angeles
  • On Ying Liu
    • Department of Medicine, Division of Hematology-Oncology, David Geffen School of MedicineUniversity of California Los Angeles
  • Jonathan L. Tso
    • Department of Medicine, Division of Hematology-Oncology, David Geffen School of MedicineUniversity of California Los Angeles
  • Jason Y. Liu
    • Department of Human Genetics, David Geffen School of MedicineUniversity of California Los Angeles
  • Veerauo Konkankit
    • Department of Neurosurgery, David Geffen School of MedicineUniversity of California Los Angeles
  • Timothy F. Cloughesy
    • Department of Neurology, David Geffen School of MedicineUniversity of California Los Angeles
    • Jonsson Comprehensive Cancer CenterUniversity of California Los Angeles
  • Paul S. Mischel
    • Department of Pathology and Laboratory Medicine, David Geffen School of MedicineUniversity of California Los Angeles
    • Jonsson Comprehensive Cancer CenterUniversity of California Los Angeles
  • Timothy F. Lane
    • Department of Ob-Gyn and Biological Chemistry, David Geffen School of MedicineUniversity of California Los Angeles
    • Jonsson Comprehensive Cancer CenterUniversity of California Los Angeles
  • Linda M. Liau
    • Department of Neurosurgery, David Geffen School of MedicineUniversity of California Los Angeles
    • Jonsson Comprehensive Cancer CenterUniversity of California Los Angeles
  • Stanley F. Nelson
    • Department of Human Genetics, David Geffen School of MedicineUniversity of California Los Angeles
    • Jonsson Comprehensive Cancer CenterUniversity of California Los Angeles
    • Department of Medicine, Division of Hematology-Oncology, David Geffen School of MedicineUniversity of California Los Angeles
    • Jonsson Comprehensive Cancer CenterUniversity of California Los Angeles
Open AccessPriority Report

DOI: 10.1007/s11060-009-9919-z

Cite this article as:
Liu, Q., Nguyen, D.H., Dong, Q. et al. J Neurooncol (2009) 94: 1. doi:10.1007/s11060-009-9919-z

Abstract

Glioblastoma multiforme (GBM) remains refractory to conventional therapy. CD133+ GBM cells have been recently isolated and characterized as chemo-/radio-resistant tumor-initiating cells and are hypothesized to be responsible for post-treatment recurrence. In order to explore the molecular properties of tumorigenic CD133+ GBM cells that resist treatment, we isolated CD133+ GBM cells from tumors that are recurrent and have previously received chemo-/radio-therapy. We found that the purified CD133+ GBM cells sorted from the CD133+ GBM spheres express SOX2 and CD44 and are capable of clonal self-renewal and dividing to produce fast-growing CD133− progeny, which form the major cell population within GBM spheres. Intracranial injection of purified CD133+, not CD133− GBM daughter cells, can lead to the development of YKL-40+ infiltrating tumors that display hypervascularity and pseudopalisading necrosis-like features in mouse brain. The molecular profile of purified CD133+ GBM cells revealed characteristics of neuroectoderm-like cells, expressing both radial glial and neural crest cell developmental genes, and portraying a slow-growing, non-differentiated, polarized/migratory, astrogliogenic, and chondrogenic phenotype. These data suggest that at least a subset of treated and recurrent GBM tumors may be seeded by CD133+ GBM cells with neural and mesenchymal properties. The data also imply that CD133+ GBM cells may be clinically indolent/quiescent prior to undergoing proliferative cell division (PCD) to produce CD133− GBM effector progeny. Identifying intrinsic and extrinsic cues, which promote CD133+ GBM cell self-renewal and PCD to support ongoing tumor regeneration may highlight novel therapeutic strategies to greatly diminish the recurrence rate of GBM.

Keywords

GlioblastomaCancer stem cellsSelf-renewalRadial glial cellsNeural crest cellsExpression microarray

Introduction

Glioblastoma multiforme (GBM, World Health Organization/WHO grade IV) remains virtually incurable despite extensive surgical excision and post-operative adjuvant radio/chemotherapy. Currently, most anti-cancer therapies aim to eliminate rapidly proliferating tumor cells; thus, the novel discovery of rare and radioresistant CD133+ GBM stem cells possessing the enhanced ability to repopulate tumors by multiple laboratories [15] provide a potential model to explain the inability to eradicate malignant GBM tumors. Tumor recurrence after treatment may mimic the scenario of post-injury tissue repair and regeneration. Many adult tissues undergo renewal after aging or injury, and hence require a new supply of cells originating from specialized tissue stem cells with the capability to undergo self-renewal, asymmetric cell division, and multipotent differentiation to repair aged cells or damaged tissue [69]. Stem cells often reside in stem cell niches that provide a specialized environment to maintain and regulate their properties and activity [10, 11]. The cellular hierarchy of tissue regeneration by resident stem cells has been described in the hematopoietic system, gut, and skin [1214]. Tissue stem cells are most often slow-cycling and give rise to daughter transient amplifying cells (TAC) that make up the majority of the proliferative cell population in the tissues, and eventually differentiate into non-proliferative cells of a particular tissue type [15, 16]. The studies of airway injury/repair in animal model indicated that airway stem cells will only be induced to self-renewal when an abundant number of TAC are depleted [17, 18], and the elimination of the progenitor and stem cell pools has a consequent failure of tissue regeneration [19]. Thus, at the functional level, CD133+ GBM stem cells behave in ways that are similar to tissue stem cells; CD133+ GBM stem cells can self-renew and reconstitute the original tumor tissue when grafted into mice [15]. Cancer stem cells possess a multi-lineage differentiation capacity support for the hypothesis that cancer hierarchy is a result of developmental diversity among cancer cells in different states of differentiation [2022]. However, it is plausible that multiple genetic and/or epigenetic instability that take place within tumor stem cells might prevent progeny from undergoing non-proliferative terminal differentiation, leading to uncontrolled tumor growth [2325].

To access genes and pathways potentially associated with malignant features of GBM tumors, we recently compared the genome-wide transcription profile of GBM tumors with that of normal brain tissue and lower-grade astrocytoma [2628]. Besides those genes associated with inflammation, coagulation, angiogenesis, and tissue remodeling, a series of genes linked with neural stem cell (NSC), mesenchymal stem cells (MSC) and skeletal/cartilage development, was determined. It thus implicates that a tissue regeneration-like reaction is constitutively activated within GBM tumor situ. The molecular profiles of tumor samples obviously do not reflect those of the CD133+ cancer stem cell population, which only forms a small fraction of the whole tumor tissue samples. In this study, we characterized CD133+ GBM stem cells purified from the passaged CD133+ GBM sphere cultures established from recurrent GBM tumors that had previous treatment. Our results indicated that these CD133+ GBM cells have an unlimited ability to repopulate tumor spheres in cultures and are capable of reconstituting a tumor in mouse brain that displays the key histopathologic features of malignant GBM tumor. Molecular profile analysis revealed CD133+ GBM cells possess neuroectodermal-like cell properties endowed with mesenchymal differentiation and astrogliogenic potentials. Additionally, a list of overexpressed genes characterized a quiescent-like state, implying that CD133+ GBM stem cells may be clinically indolent prior to entering the proliferative phase of the cell cycle to attain their malignant phenotype [29].

Materials and methods

Culture of primary GBM cells and tumor spheres

The tumor specimens were obtained from patients who underwent surgery at University of California at Los Angeles (UCLA) Medical Center. All samples were collected under protocols approved by the UCLA Institutional Review Board. The histopathologic typing and tumor grading were done by one neuropathologist according to the WHO criteria. Tumors were enzyme-digested and washed, followed by red blood cell lysis of the pellet. Cells were cultured in a serum-free NSC medium containing DMEM/Ham’s F-12 (Mediatech, Manassas, VA) supplemented with 20 ng/ml human recombinant epidermal growth factor (EGF, Sigma-Aldrich, St. Louis, MO), 20 ng/ml basic fibroblast growth factor (FGF, Chemicon, Billerica, MA), 10 ng/ml leukemia inhibitory factor (LIF, Chemicon), and 1× B27 without vitamin A (Invitrogen, Carlsbad, CA). In some cases, cells were cultured in DMEM/Ham’s F-12 supplemented with 5% fetal bovine serum for 1–2 passage followed by switching into NSC culture condition as previously reported [4]. The D431 spheres were derived from a patient with primary/de novo GBM and S496 spheres were derived from a patient with secondary/progressive GBM [27]. Both tumors received radiation and chemotherapy prior to their recurrence and re-operation. GBM sphere cultures were split with acutase weekly (Sigma-Aldrich, St. Louis, MO) and replaced with fresh media every other day.

Real-time quantitative (qt) and semi-qt reverse transcriptase polymerase chain reaction (RT-PCR) analysis

Real-time qtRT-PCR and semi-qtRT-PCR analysis were performed to verify the expression of selected genes in CD133+ GBM cells and patient tumors. Samples were subjected to total RNA extraction with RNeasy kit (QIAGEN, Valencia, CA) and reverse transcription by using a Taqman RT Reagent Kit (Applied Biosystems, Foster City, CA). Two microgram of purified total RNA was used as template in RT and cDNA synthesis was done for 1 cycle at 50°C for 30 min and 94°C for 2 min. Real-time qtRT-PCR was carried out with MJ Opticon PCR Analyzer (MJ Research, Inc., Waltham, MA) using SYBR Green PCR Core Reagents (Applied Biosystems). The reactions were cycled 30 times [50°C for 2 min and 95°C for 10 min (94°C for 15 s, 58–60°C for 1 min, and 72°C for 1 min) × 30 cycles] and the fluorescence was measured at the end of each cycle to construct amplification curves. A melting curve was done to verify the specificity of PCR products. Quantitation of transcripts was calculated based on a titrated standard curve co-run in the same experiment and calibrated with the expression level of housekeeping gene (β-actin). The semi-quantitative RT-PCR analysis was performed, using 5 μl cDNA equivalents to 100 ng total RNA. The PCR reaction cycles were carried out as described above. After amplification, PCR products (5 μl) were electrophoresed on 2% agarose gel and visualized under ultraviolet light after SYBR Green staining. Primer 3 Input (http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi) was used to selected primers and nonredundant specific primer sequences was verified using National Center for Biotechnology Information BLAST (http://www.ncbi.nlm.nih.gov/blast/Blast.cgi). The primer sequences and expected size of amplified PCR products are listed at supplementary Table 8.

Cell proliferation assay

The proliferative activity of pre-sorted and post-sorted CD133+ and CD133− GBM cells was determined by 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS/PMS) colorimetric assay (Promega, Madison, WI) according to the manufacturer’s instructions. Cells were seeded into 96-well tissue culture plates at a density of 10,000 cells per well in triplicate in NSC selecting media and incubated for 24 h. The optical density was measured at 490 nm after 4-h incubation with MTS/PMS reagent.

Loss of heterozygosity analysis

Genomic DNA from sorted CD133+ GBM cells was amplified, labeled, and hybridized under the manufacturer’s recommended conditions using the GeneChip Human Mapping 10 K Array XbaI 131 (Affymetrix, Santa Clara, CA). Raw allele scores were processed using Affymetrix GeneChip Chromosome Copy Number Tool 1.1 to estimate genome-wide chromosomal gains and losses.

Animal studies and preparation of paraffin slides and frozen sections

Tumorigenicity of GBM cells was determined by injecting the cells orthotopically. Six-week-old female or male Beige/SCID mice were anesthetized and positioned into a stereotactic frame. A burr hole was made using a Dremel drill approximately 3 mm lateral and 1 mm posterior to the intersection of the coronal and sagittal sutures (bregma). Cells were injected using a Hamilton syringe at a depth of 3 mm in a volume of 2 μl. Animals were sacrificed when any sign of neurological symptoms and morbidity/moribundity was observed. Brain tissue were immediately removed and fixed in 10% formalin for 24 h and then transferred to 70% ethanol. Mouse brains were embedded in paraffin in an automatic tissue processor. Brains were sectioned at 5-μm thickness and were mounted on microscope slides. Brain tissue for frozen sections was placed in O.C.T. embedding medium (Tissue-Tekm, Miles Inc.). The sample tray was briefly dipped in liquid nitrogen and was sectioned at 5-μm thickness in a −20°C cryostat and air-dried. Slides were then stored at −70°C until used for hematoxylin and eosin (H–E) stain and immunohistochemical analysis.

Immunocytochemical, histopathological, and immunohistochemical analysis

The immunocytochemical analysis was performed on GBM spheres seeded on an eight-chamber culture slide in the presence of FGF/EGF/LIF for 48 h. Cells were washed, fixed in 4% paraformaldehyde and subjected to immunofluorescent staining. The following primary antibodies were used: CD133 (1:100, Abcam, Cambridge, MA), nestin (1:200, Chemicon, Temecula, CA), SOX2 (1:400; R&D System, Minneapolis, MN), CD105 (3 μg/ml, R&D System), YKL-40 (1:50, Quidel, San Diego, CA) and collagen type I (1:50, Santa Cruz Biotech, Santa Cruz, CA). After washing, cells were incubated with rhodamine red or Alexa Fluor 488-conjugated goat anti-mouse IgG or goat anti rabbit IgG (1:200, Invitrogen) and counterstained with Hoechst 33342 (Invitrogen) to identify all nuclei. Histopathological analyses were performed on frozen section or paraffin slides stained with H–E staining as per standard technique. Immunohistochemical staining was performed on frozen-section slides. Slides were subject to a 1-h blocking step followed by the application of primary antibody or control antibody for 1 h at room temperature. The following primary antibodies were used: CD31 (1:100, Biocare Medical, Concord, CA), CD133, YKL-40 (1:100), and SOX2 (1:100). The immunodetection was performed using Vectastain ABC Standard kit and Vector NovaRED (Vector Laboratories, Burlingame, CA).

Fluorescence-activated cell sorting analyses and purification of CD133+ GBM cells

Fluorescence-activated cell sorting analyses (FACS) analyses were employed to determine the percentage of cells expressing stem cell markers. Dissociated cells were stained with the following antibodies for 30 min at 4°C: anti-CD133-APC (Miltenyi Biotech, Auburn, CA), anti-CD44-FITC (Caltag Laboratories, Burlingame, CA), anti SOX2 (indirect staining, using Alexa Fluor 488-conjugated goat anti-mouse IgG) and fluorescence-conjugated isotype IgG controls. 10,000 events were collected in each analysis. The analyses were performed on a FACSCalibur flow cytometer (Becton Dickinson, San Jose, CA) and ≥10,000 events were collected in each analysis. To purify CD133+ GBM cells, dissociated cells were immunostained with anti-CD133-APC under the sterile condition. The CD133+ and CD133− cells were sorted and collected on a BD FACSAria™ II cell sorter at 70 psi using a 70-μm nozzle. The purity of post-sorted cells was determined.

Microarray procedures and data analysis

Molecular profiling and analysis were performed as described [27]. Briefly, cDNA was generated and converted to cRNA probes using standard Affymetrix protocols and hybridized to Affymetrix GeneChip U133 Plus 2.0 Array. The chips were scanned using the GeneArray scanner (Affymetrix). The CEL files generated by the Affymetrix Microarray Suite version 5.0 were converted into DCP files using the DNA-Chip Analyzer (dChip 1.3; http://biosun1.harvard.edu/complab/dchip/). The DCP files were globally normalized, and gene expression values were generated using the dChip implementation of perfect-match minus mismatch model-based expression index. To avoid inclusion of low-level and unreliable signals, the higher signal needed to exceed 100 and be called present by MAS 5.0 in >30% of the samples. All group comparisons were performed in dChip.

Gene annotation

Functional annotation of individual gene was obtained from NCBI/Entrez Gene (http://www.ncbi.nlm.nih.gov/sites/entrez), the published literature in PubMed Central (NCBI/PubMed), Online Mendelian Inheritance in Man (NCBI/OMIM), Source database (http://source.stanford.edu/cgi-bin/source/sourceSearch), Protein knowledgebase (UniProtKB) (http://beta.uniprot.org/), and Information Hyperlinked over Proteins (http://www.ihop-net.org/UniPub/iHOP/). Functional categorization of expression-based clusters based on gene ontology (GO) was performed using a web tool dChip v1.3 software (http://www.hsph.harvard.edu/~cli/complab/dchip/). After the hierarchical clustering was performed on genes, dChip searches all branches with at least four functionally annotated genes to assess whether a local cluster is enriched by genes having a particular function with GO term.

Results

GBM spheres contain a minor population of CD133+ cells and express neural and mesenchymal stem cell-associated markers

Five GBM sphere cultures were initiated under NSC-selective culture conditions; two of them (D431 and S496) were expandable, and were used for current study. GBM spheres were dissociated, clonally replated to prevent cells from forming aggregates (4 × 104 cells/7 ml/10 cm dish), and passaged weekly. Most notably, individual cells dissociated from spheres showed distinct proliferative potentials; some form abortive colonies, whereas others form larger colonies varying in size (Fig. 1A), suggesting that cells which formed spheres, are heterogeneous. When compared to autologous GBM cell cultures growing in serum-containing media, a more differentiated state, in which a negligible percent of cells express CD133 (<0.5%), 7–10% CD133+ GBM cells could be detected in GBM sphere cultures, using FACS analysis (Fig. 1B). Moreover, sphere formation analysis by limiting dilution assay revealed 7–15% clonogenic efficiency (Fig. 1C), indicating that the majority of cells within spheres are not sphere-reinitiating cells. We then test whether these bulk CD133+ GBM spheres that contain majority of CD133− GBM cells express GBM tumor-associated genes that are linked with NSC and MSC and their cell lineages as identified in GBM tumors [2628]. Indeed, immunostaining analysis revealed several NSC- and MSC-associated markers, including SRY (sex-determining region Y)-box 2 (SOX2), nestin, YKL-40, collagen Type I, and CD105 (endoglin) were determined (Fig. 1D). RT-PCR analysis was used to confirm the expression of additional GBM markers, including maternal embryonic leucine zipper kinase (MELK), platelet-derived growth factor receptor-alpha (PDGFR-a), SOX4, and musashi homolog 1 (MSI1) (data not shown), demonstrating that cultured CD133+ GBM spheres express molecular markers of stem-like GBM tumors.
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Fig. 1

CD133+ glioblastoma (GBM) sphere culture derived from treated and recurrence GBM tumors express neural and mesenchymal stem cell-associated genes. A Under neural stem cell (NSC)-selective conditions, passaged and dissociated GBM spheres can generate single cells, small spheres, and large spheres (>50 cells), indicating tumor spheres consist of progeny with different proliferative potentials. Scale bar = 50 μm. B Propagated GBM sphere cultures contain ~7% to 10% of the CD133+ GBM cells determined by flow cytometry analysis. C The clonogenic efficiency of dissociated CD133+ GBM spheres assayed by the limiting dilutions relatively correlates to the % of the CD133+ cells determined in the GBM spheres. D CD133+ GBM spheres express neural and mesenchymal/chondrogenic-associated genes as indicated, determined by immunocytochemical analysis. Scale bar = 25 or 50 μm, as indicated

CD133+ GBM spheres were generated and maintained by CD133+ GBM cells through self-renewal and proliferative cell division

To determine whether CD133+ GBM cells are sphere-reinitiating cells, and responsible for generating CD133− GBM progeny within spheres, CD133+ GBM cells were sorted from dissociated CD133+ sphere cultures using specific CD133 antibody and FACS analysis (Fig. 2A). The purity of post sorted CD133+ cells ranged from 92% to 97%. Purified CD133+ cells were seeded in 96-well plates at the clonal density by limiting dilution. Notably, daughter cells divided from a single CD133+ GBM cell grow rapidly and gradually pile up to form GBM spheres. Moreover, populated cells are morphologically heterogeneous revealed by differences in cell size and the formed spheres showed variation in shape (Fig. 2B) [30]. These proliferative dividing cells are mostly CD133− cells as evident by the determination of ~90% CD133− GBM cells in the expanded spheres (Fig. 2C). Meanwhile, ~10% CD133+ GBM cells were determined in single cell-initiated spheres, indicating CD133+ GBM cells could clonally self-renew, but apparently be maintained in a slow-dividing status distinct from CD133− progeny. RT-PCR analysis also provided evidence for the presence of proliferative CD133− daughter cells within the growing spheres, which showed a decreased level of CD133 transcripts compared to that of purified CD133+ GBM cells (Fig. 2D). These data thus demonstrate that CD133+ GBM cells are capable of clonal self-renewal and giving rise to fast-growing CD133− daughter cells.
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Fig. 2

CD133+ GBM cells are sphere-reinitiating cells capable of undergoing clonal self-renewing and proliferative cell division in order to repopulate spheres. A Purification of CD133+ GBM cells from bulk CD133+ sphere cultures using specific anti-CD133 antibody and fluorescence-activated cell sorter. B A single CD133+ GBM cell can undergo proliferative cell division to generate daughter cells that are morphologically heterogeneous as revealed by cell size. Scale bar = 25 μm. C GBM spheres initiated by a single CD133+ GBM cell contain ~10% CD133+ GBM cells as determined by flow cytometry analysis. D RT-PCR analysis showed that purified CD133+ GBM cells overexpress CD133 transcripts compared with GBM spheres. Sorted CD133− GBM cells, serum-cultured GBM cell lines, and fibroblasts do not express CD133 transcripts. Normal neural stem cells served as positive control cells, show a strong signal for CD133. Beta-actin was served as an internal loading control. E The growth expansion assays indicated that GBM sphere cultures initiated by CD133+ GBM daughter cells, not CD133− GBM daughter cells, can be propagated for indefinite passages. (a) Cells were seeded in 6-well plates at a cell density of 104 cells per well in triplicates. Cells were counted approximately every 2 weeks and reseeded at the same cell density. (b) Short-term proliferation assay performed in day 2 cultures indicated that freshly sorted CD133+ GBM cells exhibited less proliferative activity compared to the that of CD133− GBM cells sorted from the same sphere culture, as determined by MTS/PMS colorimetric assay. Bars represent the mean ± standard error of triplicate wells. (c) CD133+ GBM cells, not CD133− GBM cells, sorted from the same CD133+ GBM sphere cultures can repopulate GBM spheres for indefinite passages

To test whether CD133+ cells are responsible for the continuous propagation of GBM sphere in cultures, we compared the growth expansion of purified CD133+ cell-initiated cultures with that of cultures initiated by the purified CD133− progeny (Fig. 2E). In order to ensure that CD133+ cells were completely removed from the CD133− fraction, post-sorted CD133− cells were subjected to a second round of cell sorting. The purified CD133+ and CD133− daughter cells sorted from the same CD133+ GBM sphere cultures initiated by the CD133+ GBM cells were respectively seeded in triplicate in 6-well plates at the cell density of 104 cells/2 ml/well. Cell counting was performed biweekly. Most notably, the growth initiation of cell cultures seeded by purified CD133+ GBM cells (40–50 × 104 cells/ml in first cell counting) was delayed compared to that of purified CD133− GBM cell-seeded culture (70–80 × 104 cells/ml), which showed an enhanced growth rate in the early passages (Fig. 2E, a). This determination was verified by a short-term (24 h) proliferation assay on day 2 after sorting, which also indicated a slower growth rate of freshly purified CD133+ GBM daughter cells compared to CD133− GBM daughter cells sorted from the same sphere cultures (Fig. 2E, b). We however, observed a lesser difference in proliferative activity between CD133+ S496− and CD133− S496 cell-seeded cultures compared to the growth differences between CD133+ and CD133− D431 cell-seed cultures. This may be due to purified CD133+ S496 GBM cell culture being able to drop from ≥95% purity to 5–10% within ~3 to 5 days, whereas it will take ~2 weeks to drop to ~10% to 15% in D431 cells (data not shown). Nevertheless, the pre-sorted GBM cells from the dissociated CD133+ GBM spheres showed a better proliferative activity than sorted CD133+ or CD133− cells in either cases (Fig. 2E, b). The growth of CD133− GBM cell-initiated cultures gradually dropped after repeated passaging in contrast to that of CD133+ cell-initiating cultures, which showed a stable expansion (Fig. 2E, a, c). These results thus indicate that CD133+ GBM cells have the capacity for unlimited self-renewal, which is required for a long-term propagation of D431 and S496 GBM spheres in cultures.

Cells spontaneously migrate out of GBM spheres and form the surrounding monolayer

It was reported that neural precursor cells migrating out of neurospheres in cultures and outgrowing into a monolayer [31, 32]. We have also observed a similar in vitro characteristic in GBM sphere cultures. GBM cells can spontaneously migrate radially outward from the semi-adherent and flattened GBM sphere bodies, resulting in a rim of monolayer cells surrounding the spheres (Fig. 3A, a–e). Eventually, these migrating cells outgrow into an adherent monolayer that spread out over the surface of the culture dish (Fig. 3A, f). Unexpectedly, these cultures contain a higher percentage of CD133+ GBM cells (15–30% for S496 and 50–70% for D431) than non-adherent sphere cultures (Fig. 3B, a, b). The majority of CD133+ GBM cells co-express SOX2 and CD44 (Fig. 3B, c, d) as those of CD133− progeny in same cultures, indicating that CD133+ GBM cells sharing some of their surface markers with their immediate progeny grew in the same cultures. Since no additional factors were added into the culture to influence the behavior of cells, such a cell migration may be an intrinsic property that reflects inherently migratory properties of the GBM tumor of origin, which may confer a infiltrative nature of GBM tumors in brain that is characterized by the ability to migrate and invade the adjacent healthy brain tissue. When these adherent cells were dissociated and replated at clonal density, they can regrow as sphere cultures (Fig. 3B, e) containing ~10% CD133+ cells (Fig. 3B, f).
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Fig. 3

CD133+ GBM cells can reconstitute an infiltrating GBM tumor in mouse brain that displays hypervascularity and pseudopalisading necrosis-like features. A Passaged CD133+ GBM spheres (>20 passage) can radially migrate out of spheres extensively (af). Magnification, 40× (f), 100× (e), 200× (a, d), 400× (b, c). B The flow cytometry analysis indicated that the adherent GBM sphere cultures contain a higher percentage of CD133+ cells (20–70%) that coexpressed SOX2 and CD44 (ad). Replating adherent CD133+ GBM sphere culture cells at clonal cell density can re-initiate spheres that contain ~10% CD133+ GBM cells (e, f). C Genomic abnormalities that are associated with glioblastoma were detected in CD133+ GBM cells. CD133+ GBM cells were evaluated for allelic imbalances and chromosomal copy number abnormalities by using a high-density single nucleotide polymorphism array analysis. X axis, length of chromosomes 17, 10, and 7; Y axis, score of the evidence of LOH or gain of gene copy. D Intracranial injection of purified CD133+, not CD133− GBM daughter cells, can lead to the development of infiltrating tumors. HE staining shows hypercellular zones surrounding necrotic foci and the formation of a clear space (ai). The hypervascularity was displayed by the strong positivity of CD31/PECAM-1 (platelet endothelial cell adhesion molecule-1) as determined by immunostaining (k, l). CD133 immunoreactive cells were occasionally found in small clusters (m, n). The expression of nestin, SOX2, and YKL-40 in the infiltrating cells validates the origin of human malignant GBM tumor (oq). No immunoreactivity was determined when the control antibody was applied (j). Magnification, 200× (ag; jq), 400× (h, i)

CD133+ GBM cells exhibit genomic abnormalities and are capable of repopulating malignant GBM tumor in mouse brain

Both CD133+ D431 GBM cells and CD133+ S496 GBM cells exhibited loss of heterozygosity (LOH) at various chromosome locations as determined using a high-density single nucleotide polymorphism array analysis. Particularly, LOH at chromosome 10 was found in both CD133+ GBM cells, whereas only CD133+ S496 GBM cells exhibited LOH in chromosome 17 (Fig. 3C). Additionally, chromosome 7 was found to be amplified in CD133+ D431 GBM cells, and to a lesser degree in S496 cells. Similar results were found in the autologous cell line cultures passaging in the serum-containing media [28]. To compare the in vivo fate of CD133+ GBM cells and CD133− GBM cells, cells were stereotactically injected into the brains of SCID mice. Mice that received purified CD133+ GBM cells (5–10 × 103/2 μl) (11/12) sorted from the CD133+ GBM sphere cultures (6 mice per cell type) showed impaired mobility at week 15–28 post-injection, whereas mice that received CD133− GBM cells (5 × 105/2 μl) (0/20) (10 mice per cell type) remained normal at week 30. The injected CD133− GBM cells include CD133− GBM cells sorted from the same CD133+ GBM sphere cultures that were used for sorting CD133+ GBM cells (post two rounds of cell sorting) (0/6), the CD133− cells sorted from autologous GBM cell line cultured in serum (0/6) (note, serum-cultured GBM cells contain 0.2–0.35% CD133+ cells) and serum-cultured GBM cells switched to NSC culture media for 48 h (0/4) and 6 days (0/4). The H–E staining of tumors demonstrated hypercellular zones surrounding necrotic foci that form the histopathologic features of pseudopalisading necrosis as seen in human glioblastoma (Fig. 3D). Notably, S496 tumors (Fig. 3D, a–e) exhibited more enhanced necrosis than that of D431 tumors (Fig. 3D, f–i). Immunohistochemical staining revealed hypervascularity evidenced by the strong expression of CD31/platelet endothelial cell adhesion molecule-1 (PECAM-1) (Fig. 3D, k, l). The CD133 immunoreactive cells were occasionally found (Fig. 3D, m, n), suggesting the CD133− GBM daughter cells play the key role in promoting the malignant features of tumor in mice. The expression of nestin, SOX2, and YKL-40 in infiltrating tumor cells (Fig. 3D, o–q) verified the GBM origin and tumorigenic potential of CD133+ GBM cells.

Shared CD133+ GBM cell-associated genes revealed neuroectodermal properties and a quiescent/antiproliferative phenotype

To explore molecular properties of CD133+ GBM cells, we performed large-scale gene expression analysis using DNA microarrays. Based on the in vitro characterization, it is anticipated that CD133+ and CD133− daughter cells sorted from the same CD133+ sphere cultures initiated by CD133+ GBM cells will share certain properties (e.g. CD44, nestin, SOX2). Therefore, to assess genes that characterized the tumorigenic, stem-like CD133+ GBM cells, we first compared the mean level of normalized expression profiles in each of the two purified CD133+ GBM cell samples (D431 and S496) (n = 3 preparations, passage 20, 29, 40) against the non-tumorigenic, autologous CD133− GBM cells growing in serum (more differentiated condition) with and without switching to a short-term NSC culture condition (24 h, 48 h, and 6 days) (n = 6 preparations). The short-term culture of cells in NSC culture condition diminishes the likelihood of identifying NSC growth factor-responsive genes (background genes) in the comparative analysis. Probe set signals on the expression array that were ≥3-fold higher in each CD133+ GBM cell group versus the autologous CD133− GBM cell group with a pairwise t-test (P < 0.05) were selected. The filtering criteria were described in Materials and Methods. Sixty-four shared genes overexpressed in CD133+ GBM cells were identified in both pairwise comparisons (D431 and S496), and CD133/prominin1 was highly differentially expressed (D431 = 53 folds, S496 = 14 folds) as anticipated, which validates a good purification process (Table 1; Fig. 4A, a). The distinctive gene expression profiles of selected genes were verified by real-time qt-RT-PCR and semi-qt-RT-PCR (supplementary Fig. 1). The gene function enrichment analysis identified 24 significant GO clusters (Fig. 4A), and 38% (find 24 genes), 25% (find 17 genes) and 25% (find 17 genes) genes were found for GO terms related to “development” (P = 0.000001), “system development” (P = 0.000000) and “nervous system development” (P = 0.000000)), respectively (supplementary Table 1). Indeed, a large percentage of genes are neuroectoderm-developmental genes (Table 1). Most notably, Dlx5 and Dlx6 (see gene description in Table 1) are regulators of chondrogenesis of limb [33] and are highly expressed in cranial neural crest. MEOX2, MEST, and FABP4 characterized mesenchymal progenitors, and RARA [34] and Wnt antagonist FRZB [35] are likely to be inducing the signals to suppress the chondrocytic and skeletal progenitor differentiation. Simultaneously, many genes reflective of the normal function of neural crest cells were determined: SEMA6D for cardiac development, CHRNA9 for cochlea hair cell development, PPEF1 for development of cranial ganglion sensory neurons, and SHROOM2 for melanosome biogenesis. Moreover, LGR5, a novel marker gene for adult stem cells was determined [36], indicating CD133+ GBM cells share a property with other tissue stem cells.
Table 1

Shared genes overexpressed in CD133+ D431 and CD133+ S496 GBM cells compared with autologous CD133− GBM cells cultured in serum-containing media

Gene

Symbol

Gene I.D.

Fold change

Chromosome

Functional involvement

D431

S496

Sema, transmembrane, and cytoplasmic domain, 6D

SEMA6D

80031

117.89

4.16

15q21

Guidance of myocardial patterning in cardiac development

Growth associated protein 43

GAP43

2596

110.32

25.56

3q13.1-q13.2

Nervous system regeneration

Distal-less homeo box 6

DLX6

1750

78.94

40.90

7q22

Craniofacial morphogenesis/chondrogenesis

BH-protocadherin (brain–heart)

PCDH7

5099

62.58

3.76

4p15

Calcium-dependent cell–cell adhesion

Prominin 1/CD133

PROM1

8842

52.87

13.70

4p15.32

Neuroepithelial stem cell marker; cell polarity

Endothelin 3

EDN3

1908

43.96

26.35

20q13.2-q13.3

Promotes neural crest cell and precursor proliferation

ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyltransferase 4

ST8SIA4

7903

43.56

5.39

5q21

Synthesis of polysialic acid in neural stem cells

Transcription factor AP-2 beta

TFAP2B

7021

37.28

23.09

6p12

Neural crest cell growth and differentiation

Distal-less homeo box 5

DLX5

1749

36.64

17.18

7q22

Craniofacial morphogenesis/chondrogenesis

Neurexin 3

NRXN3

9369

27.84

5.79

14q31

Stabilizes synapses

Cholinergic receptor, nicotinic, alpha polypeptide 9

CHRNA9

55584

27.24

3.99

4p14

Cochlea hair cell development

Fatty acid binding protein 4, adipocyte

FABP4

2167

26.43

70.07

8q21

Lipid and glucose metabolism

Peptidase inhibitor 15

PI15

51050

24.09

7.79

8q21.11

Expressed in neuroblastoma/glioblastoma

Cholinergic receptor, nicotinic, alpha polypeptide 1 (muscle)

CHRNA1

1134

23.12

6.33

2q24-q32

Neuromuscular transmission

Glycoprotein M6B

GPM6B

2824

23.12

5.79

Xp22.2

Stabilizes proteolipids in neuron

Sortilin-related VPS10 domain containing receptor 1

SORCS1

114815

19.39

45.42

10q23-q25

Brain neuropeptide receptors

Protein phosphatase, EF-hand calcium binding domain 1

PPEF1

5475

19.18

6.57

Xp22.2-p22.1

Specific sensory neuron function and/or developments

Kinesin family member 5C

KIF5C

3800

19.03

17.36

2q23.1

Neuronal kinesin enriched in motor neurons

Down syndrome critical region gene 1-like 1

RCAN2

10231

18.71

10.06

6p12.3

Suppresses angiogenesis

Leucine-rich repeat-containing G protein-coupled receptor 5

LGR5

8549

18.56

4.59

12q22-q23

Stem cell marker of small intestine, colon, skin, hair

Glutamate receptor, ionotropic, AMPA 1

GRIA1

2890

16.48

14.20

5q31.1

Excitatory neurotransmitter receptors

Mesenchyme homeo box 2

MEOX2

4223

15.64

47.53

7p22.1-p21.3

Somitogenesis; myogenic/sclerotomal differentiation

Monooxygenase, DBH-like 1

MOXD1

26002

15.53

23.19

6q23.1-q23.3

Dopamine-oxygenase; neural crest/ganglia marker

Cholinergic receptor, muscarinic 3

CHRM3

1131

14.44

7.26

1q43

Smooth muscle contraction; secretion of glands

Sulfatase 1

SULF1

23213

13.96

30.43

8q13.2-q13.3

Remove 6-O-sulfate groups of heparan sulfate

Regulator of G-protein signaling 5

RGS5

8490

13.19

15.10

1q23.1

Marker for pericytes; antiangiogenesis

Frizzled-related protein

FRZB

2487

12.98

6.01

2qter

Antagonizes Wnt pathway

Neurocalcin delta

NCALD

83988

11.78

3.54

8q22.2

Neuronal calcium sensors; interact with S100 beta

Gamma-aminobutyric acid (GABA) receptor, rho 1

GABRR1

2569

11.35

5.08

6q13-q16.3

Reduces sensitivity to retinoic acid

Protocadherin 19

PCDH19

57526

11.04

5.16

Xq13.3

Expressed in neuroepithelium

SRY (sex determining region Y)-box 2

SOX2

6657

10.74

7.49

3q26.3-q27

Neural stem cell marker, self-renewal

TRAF2 and NCK interacting kinase

TNIK

23043

9.72

3.41

3q26.2-q26.31

Regulates actin cytoskeleton

Mesoderm specific transcript homolog (mouse)

MEST

4232

8.79

45.13

7q32

Expressed in mesodermal derivatives

Phosphorylase kinase, gamma 2 (testis)

PHKG2

5261

8.79

8.01

16p12.1-p11.2

Activates glycogen phosphorylase

Spondin 1, extracellular matrix protein

SPON1

10418

8.43

33.87

11p15.2

Cementoblastic differentiation; inhibits angiogenesis

Rap guanine nucleotide exchange factor (GEF) 5

RAPGEF5

9771

8.42

19.43

7p15.3See

RAS activator via maintain the GTP-bound state

Trinucleotide repeat containing 9

TOX3

27324

8.36

56.65

16q12.1

Regulation of neurodevelopment or neuroplasticity

Insulin-like growth factor binding protein 2, 36 kDa

IGFBP2

3485

7.83

3.09

2q33-q34

Activation of the Akt and/K-Ras

Death-associated protein kinase 1

DAPK1

1612

7.69

15.44

9q34.1

Tumor suppressor

Formin homology 2 domain containing 3

FHOD3

80206

7.49

3.15

18q12

Present in nestin-expressing neuroepithelial cells

Scrapie responsive protein 1

SCRG1

11341

7.09

80.65

4q31-q32

Mesenchymal chondrogenesis, growth suppression

Potassium large conductance calcium-activated channel

KCNMB4

27345

7.09

6.00

12q

Smooth muscle tone and neuronal excitability

Retinoic acid receptor, alpha

RARA

5914

6.67

12.21

17q21

Marker for prechondrogenic progenitors

Neurofilament, light polypeptide 68 kDa

NEFL

4747

6.6

6.28

8p21

Controls electrical signals travel down the axon

Oxoglutarate (alpha-ketoglutarate) dehydrogenase

OGDH

4967

6.24

4.36

7p14-p13

Krebs cycle

ADAM metallopeptidase domain 23

ADAM23

8745

5.32

4.38

2q33

Tumor suppressor

Cadherin 2, type 1, N-cadherin (neuronal)

CDH2

1000

5.06

11.21

18q11.2

Cell–cell adhesion; left-right asymmetry; cell migration

Immunoglobulin superfamily, member 4C

IGSF4C

199731

4.75

10.07

19q13.31

Tumor suppressor

Ankyrin 3, node of Ranvier (ankyrin G)

ANK3

288

4.71

4.19

10q21

Maintenance of ion channels at nervous systems

Alpha-2-macroglobulin

A2M

2

4.31

11.49

12p13.3-p12.3

Protease inhibitor and cytokine transporter

Inhibin, beta A (activin A, activin AB alpha polypeptide)

INHBA

3624

4.28

7.16

7p15-p13

Tooth development; tumor suppressor

Neuropilin 2

NRP2

8828

4.26

5.98

2q33.3

Axon guidance in the peripheral and central neural system

Very low density lipoprotein receptor

VLDLR

7436

4.18

5.83

9p24

Wnt antagonist; metabolism of apoprotein-E

Sortilin-related VPS10 domain containing receptor 2

SORCS2

57537

3.81

8.95

4p16.1

Brain neuropeptide receptor

GalNAc-T10

GALNT10

55568

3.67

4.30

5q33.2

Predominant expression in CNS

FXYD domain containing ion transport regulator 6

FXYD6

53826

3.49

22.75

11q23.3

Modulator of the Na, K-ATPase

Leucine rich repeat neuronal 3

LRRN3

54674

3.49

3.49

7q31.1

Developing ganglia and motor neurons

Interleukin 17 receptor D

IL17RD

54756

3.44

9.59

3p14.3

Tumor suppressor-like role via FGF signaling

Pleiotrophin

PTN

5764

3.37

4.86

7q33-q34

Heparin binding; neurite growth-promoting factor

Muscleblind-like 2 (Drosophila)

MBNL2

10150

3.15

3.67

13q32.1

Skeletal muscle development

Microtubule-associated protein 2

MAP2

4133

3.09

4.36

2q34-q35

Microtubule assembly in neurogenesis

Apical protein-like (Xenopus laevis)

SHROOM2

357

3.06

6.24

Xp22.3

Regulates melanosome biogenesis and localization

EPH receptor B3

EPHB3

2049

3.01

8.71

3q21-qter

Precise guidance of axon and neural crest cell migration

FK506 binding protein 1B, 12.6 kDa

FKBP1B

2281

3.00

4.18

2p23.3

Excitation–contraction coupling in cardiac muscle

Analysis was based on a cutoff of 3-fold increase in relative expression compared to autologous CD133− GBM cells (P < 0.05). Individual P value is shown in supplementary Table 7

https://static-content.springer.com/image/art%3A10.1007%2Fs11060-009-9919-z/MediaObjects/11060_2009_9919_Fig4_HTML.gif
Fig. 4

Analyses of gene expression profiles of purified, tumorigenic CD133+ GBM cells sorted from the CD133+ GBM sphere cultures. A All plots show normalized gene expression values converted into a heat map. The log2 of the fold difference is indicated by the heat map scale at the bottom. Each column is an individual sample organized into cell types and culture conditions defined at the top. Each row is a single probe set measurement of transcript abundance for an individual gene. The genes are listed in the same order from top to bottom as the corresponding tables for each of the lists. (a) All genes were filtered to select transcripts with ≥3-fold expression in the tumorigenic CD133+ GBM cells (D431 and S496) sorted from the CD133+ sphere cultures (passage (p) 20, p29, and p40) compared with the non-tumorigenic, autologous CD133− GBM cells cultured in serum-containing media (p5, p10 and p15) with or without switching to a short-term NSC culture condition for 24 h, 48 h and 6 days. Sixty-four shared genes were identified from the intersection of the comparisons between CD133+ D431 GBM cells and CD133− D431 cells, and the comparison between CD133+ S496 GBM cells and CD133− S496 GBM cells. Functional categories of gene clusters upregulated in the CD133+ GBM cells were analyzed using a gene ontology annotation–based gene function enrichment analysis (d-chip software). (b, c) Gene changes in CD133− GBM daughter cells compared to CD133+ GBM daughter cells sorted from same CD133+ GBM sphere cultures. Genes that were upregulated or down-regulated with ≥1.5-fold expression in CD133− GBM daughter cells compared with CD133+ GBM daughter cells were collected. The CD133+ and CD133− GBM cells were sorted from the sphere cultures at p20, p29, and p40. Functional categories of gene clusters in GO terms were shown. B RT-PCR analysis showed that CD133+ GBM stem cell-associated transcripts are expressed in patient-derived GBM tumors

Meanwhile, a series of genes functioning in antimitotic/antigrowth effect was identified. For instance, MEOX2 suppresses cell proliferation in a p21-dependent manner [37], SULF1 suppresses peptide growth factor signaling and angiogenesis [38], IL17RD antagonizes FGF-induced cell proliferation [39], and FRZB and VLDL act as negative regulators of the Wnt signaling pathway and angiogenesis [40]. Simultaneously, EDN3, a potent mitogen for early neural crest-derived glial and melanocytic precursors [41], and GAP-43, a crucial component of an effective neural regenerative response [42] were determined, implicating a role for maintaining the basic growth activity of CD133+ GBM cells. Thus, the overall molecular profile characterizes CD133+ GBM cells as having a slow-growing, non-differentiated, self-renewing, chondrogenic, and antidevelopmental phenotype.

Unique CD133+ GBM cell-associated genes may reflect inherently migratory properties of GBM tumor of origin

The 50 most strongly differentially expressed genes only over-expressed in each purified CD133+ GBM cells sorted from the CD133+ GBM spheres were selected (supplementary Tables 2 and 3). Uniquely, fatty acid binding protein 7 (FABP7), a migratory radial glial cell (RGC) gene, was identified as the top distinct gene in CD133+ S496. The FABP7 expressing RGC have been proposed to be the malignant glioma cell of origin [43] and the increased expression of nuclear FABP7 was found to be associated with the regions of GBM tumor infiltration, reduced survival, and recurrence [44]. On the other hand, MYCN, a migratory neural crest cell gene, and MDM2, a direct transcriptional target of MYCN, were detected in CD133+ D431. The overexpression of MDM2 is implicated in the development of de novo GBM [45]. Additional genes that are associated with cell migration machinery expressed in either CD133+ D431, CD133+ S496 or both, include genes that are associated with cell polarity (e.g. GPC3, FZD1, EPH receptor B1/B3), motor protein (KIF5C), assembly of microtubules and formation of lamellipodia and filopodia (MAP2, RHOJ, RHOU, TNIK) and formation of actin stress fibers and focal adhesions (SORBS1), pointing to an active migration characteristic of CD133+ GBM cells. More importantly, the determination of Notch effector genes (HEY1, NFIA, ID4, FABP7) reflected the prolonged Notch activation and abrogation of neurogenesis, thereby promoting a migratory phenotype and glial-fate specification [4650]. In general, both unique gene lists are consistent with “anti-proliferative phenotype” as those of shared genes in Table 1.

CD133− GBM daughter cells divided from CD133+ GBM cells express molecular profiles associated with malignant GBM phenotype

Since CD133+ GBM cells sorted from CD133+ GBM spheres cultures expressed molecular profiles that characterized a quiescent phenotype, it is reasonable to predict that the malignant tumor-associated genes are mainly expressed in CD133− GBM daughter cells, which make up the major population of CD133+ GBM spheres and tumors. Indeed, comparative analysis of purified CD133+ and CD133− GBM daughter cells sorted from the same CD133+ GBM sphere cultures that were initiated by the purified CD133+ GBM cells revealed a transition from a tumor suppressive-like profile to tumorigenic profile when CD133+ GBM cells divided and produced CD133− GBM daughter cells. The top 15 genes in molecular changes were presented (Table 2; Fig. 4A, b and c), and the CD133 appears to be the top down-regulated gene in both pairwise comparisons. Uniquely, the gene function category analysis of gene changes in D431 cells identified 5 significant clusters all belong to extracellular component-associated GO terms (Fig. 4A, b), and 10 out of 30 genes (33%) under the GO term “extracellular region” (P value = 0.000004) (supplementary Table 4). This data thus suggests most genes that are modulated when CD133+ D431 GBM cells undergo cell division and produce fast-growing CD133− D431 daughter cells primarily include genes associated with mesenchymal/extracellular components. Evidently, two top genes, IBSP and YKL-40, determined in CD133− daughter cells are markers of osteoblast/chondrocyte differentiation and are angiogenic factors. More importantly, YKL-40 is linked to the mesenchymal and recurrent GBM phenotype [51]. Several upregulated genes further point to the early onset of inflammatory and angiogenic response. In contrast, genes that are downregulated in CD133− D431 daughter cells mostly are CD133+ D431 GBM associated genes (anti-proliferative genes) as described (Table 1; supplementary Table 2).
Table 2

Top 15 gene changes in CD133− GBM daughter cells compared to CD133+ GBM daughter cells sorted from the same CD133+ GBM sphere cultures

Gene

Symbol

Gene I.D.

Fold change

P value

Functional involvement

A. Genes upregulated in CD133− D431 GBM daughter cells

    Integrin-binding sialoprotein

3381

IBSP

10.13

0.01969

A major structural protein of the bone matrices; angiogenesis

    Chitinase 3-like 1 (cartilage glycoprotein-39)

1116

CHI3L1

6.93

0.039091

Chondrogenesis, glioblastoma progression marker

    Tryptophan 2,3-dioxygenase

6999

TDO2

5.62

0.00191

Enzyme involved in tryptophan catabolism

    Fibronectin 1

2335

FN1

4.61

0.039285

Binds to integrins/extracellular matrix; promote tumor growth

    Carbonic anhydrase XII

771

CA12

3.84

0.048487

Acidification of the extracellular milieu; a biomarker of gliomas

    Hydroxysteroid (11-beta) dehydrogenase 1

3290

HSD11B1

3.75

0.013701

Catalyzes the interconversion of inactive cortisone to active cortisol

    Solute carrier family 7

23428

SLC7A8

3.63

0.005935

Transport of neutral amino acids/essential amino acids

    Stonin 2

85439

STON2

3.55

0.020396

A component of the endocytic machinery; regulates vesicle endocytosis

    Plexin A4, A

57671

PLXNA4

3.48

0.039696

Mediates multiple semaphorin signals and regulates axon guidance

    Calcium/calmodulin-dependent protein kinase II inhibitor 1

55450

CAMK2N1

3.42

0.011008

Inhibit brain CaM-kinase II activity

    Anthrax toxin receptor 1

84168

ANTXR1

3.28

0.031259

Mediates cell spreading by coupling extracellular ligands to the actin

    Growth differentiation factor 15

9518

GDF15

3.06

0.004578

Tissue differentiation and maintenance

    Matrix metallopeptidase 14 (membrane-inserted)

4323

MMP14

3.03

0.01905

Angiogenesis, tumor invasion

    Elastin microfibril interfacer 1

11117

EMILIN1

3.02

0.029463

Extracellular matrix constituent associated with elastic fibers

    Tissue factor pathway inhibitor

3675

TFPI

3.02

0.000305

Regulates the coagulation pathway; dynamic conduction of blood

B. Genes downregulated in CD133− D431 GBM daughter cells

    Prominin 1/CD133

8842

PROM1

−8.19

0.004998

Membrane protuberances and cell polarity

    Glutamate receptor, ionotrophic, AMPA 4

2893

GRIA4

−4.03

0.007852

Excitatory neurotransmitter receptors

    v-Myc myelocytomatosis viral related oncogene

4613

MYCN

−3.91

0.006193

Embryonal tumor initiation factor

    PRKC, apoptosis, WT1, regulator

5074

PAWR

−3.64

0.001191

Tumor suppressor; apoptosis induction

    Ksp37 protein

83888

KSP37

−3.46

0.016226

Protein produced by CD4 and cytotoxic lymphocytes

    Sidekick homolog 2 (chicken)

54549

SDK2

−3.43

0.011413

Cell adhesion protein that guides axonal terminals

    Frizzled-related protein

2487

FRZB

−3.38

0.00987

Antagonizes Wnt pathway

    Cytoplasmic FMR1 interacting protein 2

26999

CYFIP2

−3.37

0.002989

A direct p53 target gene; cellular apoptosis

    Monooxygenase, DBH-like 1

26002

MOXD1

−3.31

0.006728

Predicted to hydroxylate a substrate in the endoplasmic reticulum

    Complement factor H

3075

CFH

−3.13

0.011463

Inhibition of complement activation

    Activated leukocyte cell adhesion molecule

29995

ALCAM

−3.08

0.002511

Marker of mesenchymal/colorectal cancer stem cells; growth control

    LIM and cysteine-rich domains 1

214

LMCD1

−3.08

0.007018

Represses GATA6 in the maintenance of the differentiated phenotype

    Scrapie responsive protein 1

11341

SCRG1

−2.98

0.010901

Mesenchymal chondrogenesis, growth suppression

    v-Myb myeloblastosis viral oncogene homolog (avian)

4602

MYB

−2.97

0.049344

Intrinsic factor for neural progenitor cell proliferation

    Cholinergic receptor, nicotinic, alpha polypeptide 3

1136

CHRNA5

−2.97

0.016751

Ligand-binding subunit of the ganglionic type nicotinic receptor

C. Genes upregulated in CD133− S496 GBM daughter cells

    3-Hydroxy-3-methylglutaryl-Coenzyme A synthase 1

3157

HMGCS1

3.09

0.020826

Cholesterologenesis

    Solute carrier family 7

23428

SLC7A8

2.87

0.035311

Transport of neutral amino acids/essential amino acids

    Mitochondrial ribosomal protein L30

51263

MRPL30

2.60

0.00943

Protein synthesis within the mitochondrion

    mRNA turnover 4 homolog

51154

MRTO4

2.56

0.007082

mRNA turnover and ribosome assembly

    CCAAT/enhancer binding protein zeta

10153

CEBPZ

2.31

0.010864

Maintains differentiated state; enhances osteoblastic differentiation

    v-Rel reticuloendotheliosis viral oncogene homolog A

5970

RELA

2.25

0.007044

Cell survival, antiapoptosis

    Endothelin 3

1908

EDN3

2.01

0.04014

Promotes neural crest cell and precursor proliferation

    Guanine nucleotide binding protein-like 3 (nucleolar)-like

54552

GNL3L

1.89

0.022775

Processing of nucleolar preribosomal RNA

    Adaptor-related protein complex 1, sigma 2 subunit

8905

AP1S2

1.89

0.03494

Protein sorting and assembly of endocytic vesicles

    Protein kinase, cAMP-dependent, catalytic, beta

5567

PRKACB

1.62

0.04107

Proliferation and differentiation; c-myc target gene; tumorigenesis

    SLIT-ROBO Rho GTPase activating protein 3

9901

SRGAP3

1.55

0.038237

Negatively regulates cell migration

    Integrin, beta 8

3696

ITGB8

1.55

0.042396

Brain vascular morphogenesis in the developing CNS

    Monoamine oxidase A

4128

MAOA

1.53

0.034433

Degrades amine neurotransmitters

    Phosphoinositide-3-kinase, class 2, beta polypeptide

5287

PIK3C2B

1.53

0.034433

Proliferation, survival; intracellular vesicle transport

    Baculoviral IAP repeat-containing 4

331

XIAP

1.52

0.022379

Blocks the apoptosis pathway via inhibiting caspase-3, 7, and 9

D. Genes downregulated in CD133− S496 GBM daughter cells

    Prominin 1/CD133

8842

PROM1

−11.00

0.039802

Membrane protuberances and cell polarity

    Phosphorylase kinase, gamma 2 (testis)

5261

PHKG2

−5.95

0.008141

Activates glycogen phosphorylase

    BH-protocadherin (brain–heart)

5099

PCDH7

−2.86

0.013744

Calcium-dependent cell–cell adhesion

    Inhibin, beta A (activin A, activin AB alpha polypeptide)

3624

INHBA

−2.82

0.026005

Tooth development; tumor suppressor

    Melanoma cell adhesion molecule

4162

MCAM

−2.81

0.013207

Putative adhesion molecule in neural crest cells/melanoma

    Low density lipoprotein-related protein 1

4035

LRP1

−2.75

0.018718

Lipid metabolism; antigrowth, tumor suppressor

    Leucine rich repeat neuronal 6C

158038

LINGO2

−2.69

0.014473

Expressed in limbic system and neocortex

    AF4/FMR2 family, member 3

3899

AFF3

−2.68

0.008324

Regulation of lymphoid development

    Nephronectin

255743

NPNT

−2.65

0.013665

Tumor suppressor

    ADAM metallopeptidase with thrombospondin type 1 motif 1

9510

ADAMTS1

−2.60

0.017533

Antiangiogenesis

    Forkhead box C1

2296

FOXC1

−2.59

0.022414

Arrests cells in the G0/G1 phase; tumor suppressor

    AT rich interactive domain 1A (SWI-like)

8289

ARID1A

−2.56

0.029044

Differentiation-associated cell cycle arrest; tumor suppressor

    Solute carrier family 4, anion exchanger, member 2

6522

SLC4A2

−2.52

0.025985

Housekeeping regulator of intracellular pH; tumor suppressor

    La ribonucleoprotein domain family, member 1

23367

LARP1

−2.51

0.01622

Protects the 3′ end of nascent small RNAs from exonuclease digestion

    Collagen, type IV, alpha 2

1284

COL4A2

−2.42

0.008793

Inhibits angiogenesis and tumor growth

Analysis was based on a cutoff of 1.5-fold changes in relative expression compared to CD133+ GBM daughter cells (P < 0.05)

Distinctively, most upregulated genes in sorted CD133− S496 GBM daughter cells are associated with progression of cell cycle (Table 2). The top gene, HMGCS1, is an enzyme involved in the biosynthesis of lipid/cholesterol, a critical component of biological membranes, and is thus upregulated with constant cellular proliferation [52]. Several upregulated genes further point to the early onset of proliferative differentiation, including CEBPZ, a transcription factor for maintaining the cell differentiation state, PIK3C2B, a downstream target of growth factor receptors that link to the activation of the AKT pathway, and PRKACB, a target gene of c-myc, which induces cell transformation and tumor growth [53]. As expected, down-regulated genes in sorted CD133− S496 GBM daughter cells are mostly growth regulators and tumor suppressor genes (Table 2). Indeed, 11 GO clusters that are mostly related to membrane-associated components were determined (Fig. 4A, c), and 9 (30%) and 8 (27%) genes were respectively found for GO term related to “protein complex” (P value = 0.013675) and “plasma membrane” (P = 0.020780) (supplementary Table 5). This data thus suggest when CD133+ S496 GBM cells undergo cell division and produce fast-growing CD133− S496 daughter cells primarily through intrinsic cell-cycle-based mechanism. The distinctive properties between D431 and S496 GBM cells also identified through the 2-way unsupervised gene and sample clustering of non-sorted CD133+ D431 and CD133+ S496 GBM sphere cultures, which nicely segregated two groups of samples (supplementary Fig. 2; supplementary Table 6). YKL-40 was identified as the top gene overexpressed in CD133+ D431 GBM spheres (101-fold increase) when compared to CD133+ S496 GBM spheres. By contrast, transmembrane protein 47, a gene that expressed high level transcripts in brain, was identified as the top gene overexpressed in CD133+ S496 GBM sphere cultures (233-fold increase). Correspondingly, gene function enrichment analysis showed distinct molecular pathways in the growth of two different CD133+ GBM sphere lines (mesenchymal developmental pathway versus neural developmental pathway) (supplementary Fig. 2). Uniquely, four gene clusters overexpressed in CD133+ S496 spheres were found for GO terms related to cell migration, cell adhesion, cell motility, and locomotion (supplementary Fig. 2), possibly explaining the enhanced infiltrating nature of S496 tumor in mouse brain compared to that of D431 tumor (Fig. 3D).

Expression of CD133+ GBM-associated transcripts in patients’ GBM tumors

Several CD133+ GBM-associated genes identified from the current two CD133+ GBM stem cell models have never been reported as GBM tumor-associated genes. By using RT-PCR analysis, a subset of selected CD133+ GBM-associated transcripts could be amplified in patient-derived GBM tumors (n = 6 patients) (Fig. 4B), suggesting the current culture strategy can preserve GBM stem cell properties.

Discussion

Cancer stem cell model and hypothesis has greatly changed the biological and clinical views of cancer [15, 54]. The molecular profiles of purified CD133+ GBM stem cells derived from the previously treated recurrent tumors characterized dormant-like cells and therefore support the hypothesis that quiescent nature of CD133+ GBM stem cells may underline the treatment resistant to the conventional therapy. The quiescent nature of cancer stem cells has been described in chronic myeloid leukemia (CML), where CML stem cells remain viable in a quiescent state even in the presence of growth factors and tyrosine kinase inhibitor [55, 56]. Indeed, while the genetic changes and tumorigenic potential were demonstrated in purified CD133+ GBM cells sorted from the CD133+ GBM spheres, the molecular profile characterized an antiproliferative nature of CD133+ GBM stem cells, suggesting the pathologic effects of molecular changes to be manifested primarily in a more differentiated progeny. Indeed, the molecular profiles of CD133+ GBM spheres (contain majority of CD133− daughter cells) initiated by the purified CD133+ GBM cells express “proliferative tumor markers” as that of CD133− GBM daughter cells, which distinctive to the quiescent CD133+ GBM daughter cells. Thus, the more differentiated CD133− GBM progeny should be considered as the true effector cells characterized fast-growing and highly angiogenic GBM tumors. The mechanisms and pathways underlying the spontaneous re-entry into active cell cycle from the quiescent state in cultures and in animal experiments remain to be elucidated [57]. In contrast to that fast-growing CD133− daughter cells, the predicted slow-cycling, non-inflammatory, and non-angiogenic nature of CD133+ GBM cells (based on the molecular profiles) may explain that GBM tumor can not be eradicated by the anti-cell cycle-based radiochemotherapy, anti-inflammatory drugs, or antiangiogenic agents.

A hallmark of all stem cells is the ability to simultaneously make identical copies of themselves (e.g. CD133+ GBM daughter cells) and give rise to a hierarchy of more differentiated progeny (e.g. CD133− GBM daughter cells). Indeed, CD133+ GBM cells fulfill this definition and are capable of undergoing cell division that give rise to a malignant tumor tissue. GBM spheres initiated with one single CD133+ GBM cell contain heterogeneous population that showed differences in cell size and proliferative potential. By RT-PCR analysis, we were able to amplify both Numb and Numb-like signals in CD133+ GBM cells (data not shown), suggesting CD133+ GBM cells may possess normal neuroepithelial-like properties capable of undergoing asymmetric cell divisions, thereby maintaining a tumor-suppressor-like phenotype [58]. Prominin/CD133 is selectively localized in protrusions of the apical membrane in neuroepithelial cells, and it was suggested that CD133 plays an important role in the maintenance of apical-basal polarity [59]. Therefore, loss of CD133 (or with other genes) may restrict CD133− GBM daughter cells to the symmetric mode of cell division and act like proliferative intermediate progenitor cells [60, 61]. Consequently, increasing the number of CD133+ GBM cells within the tumor would reflect a fast generation of proliferative and angiogenic CD133− daughter cells to form the bulk tumor [5, 62]. While our data indicated that GBM tumor growth in these two study cases depends on the CD133+ GBM cells, GBM tumor growth seemed to depend on CD133− GBM tumor-initiating cells for other cases [63, 64]. The isolation of CD133+ GBM cells from CD133− GBM cell-initiating tumor was also reported [65], indicating the CD133 is not an obligated marker for GBM stem cells.

We previously showed that GBM tumor lines established from recurrent tumors possess mesenchymal differentiation potential [29]. A recent study further showed that GBM stem cells formed tumors capable of undergoing mesenchymal differentiation [64]. The expression of mesenchymal developmental genes in CD133+ GBM stem cells may therefore provide a potential explanation for the chondrogenic/mesenchymal differentiation in tumors [66] and the shifting toward the mesenchymal phenotype upon tumor recurrence [49]. Moreover, based on the molecular profiles of purified CD133+ GBM cells, we hypothesize that the cell-of-origin of GBM tumors may be the migratory neural crest-like cell or radial glial-like cell. Overexpression of radial glial cell (RGC) marker, FABP7, in CD133+ GBM cells supports the recent finding that RGC can give rise to adult subventricular zone stem cells [67]. On the other hand, although overexpression of MYCN is associated with a childhood malignant tumor of neural crest origin, it was recently found to be one of the most frequently amplified oncogenes in GBM tumors (42%) [68]. More samples should be analyzed in order to generalize these observations. Moreover, whether these molecular properties also applied in the general properties of CD133+ GBM cells derived from the non-treated tumor remain to be investigated. Gene expression profile analyses of GBM tumors by DNA microarrays support the notion that tumor development may indeed via distinct oncogenic mechanisms among the GBM subtypes [26, 27, 69, 70]. The thought of heterogeneity in the pathway of GBM tumor development is further supported by the recent finding in studies of expression profiles of GBM sphere cultures, which showed distinct molecular properties among the GBM stem cell lines [51, 63, 64]. Likewise, although CD133+ GBM cells sorted from CD133+ D431 and CD133+ S496 spheres express shared molecular properties, unsupervised gene and sample clustering segregated two GBM sphere lines by the genes that are associated with mesenchymal developmental pathway versus neural developmental pathway, thus implying the distinct cellular-origin of these two recurrent tumors.

In summary, we characterized CD133+ GBM stem cells isolated from two tumors that are recurrent and had previous treatment. Our in vitro and in vivo data suggest that the tumorigenic CD133+ GBM stem cells are maintained at dormant-like stage state but are able to spontaneously enter the proliferative cell cycle to generate highly proliferative and angiogenic CD133− GBM daughter cells (animal data). This observation implies that tumorigenesis may be initiated through asymmetric cell division of CD133+ GBM cells [71, 72]. Thus, identifying the genes and pathways that promote the CD133+ GBM cells entering proliferative cell division cycle may facilitate the development and design of more effective therapies that specifically target the tumorigenic potential of CD133+ GBM stem cells.

Acknowledgments

This work was supported by American Cancer Society grant #RSG-07-109-01-CCE, National Brain Tumor Foundation, The Bradley Zankel Foundation, UCLA Jonsson Cancer Center Foundation and UCLA Human Gene Medicine Seed Grant.

Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Supplementary material

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