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1 Department of Surgery
2 Department of Physiology and Biophysics, University of Alabama at Birmingham, Birmingham, Alabama 35294-0005
3 Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
4 Department of Neurosurgery, Emory University, Atlanta, Georgia 30322
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA)-2 receptors, GABAA receptor subunits 3, 
1, 2, and 3, the glutamate transporter, the glutamate/aspartate transporter II, the potassium channel KV2.1, hKV3, and the sodium/proton exchanger 1 (NHE-1), that are all downregulated in the tumors compared with the normal tissues. In contrast, aquaporin-1, possibly aquaporins-3 and -5, and GLUT-3 message appeared upregulated in the tumors. Our results also confirmed previous work showing that osteopontin, nicotinamide N-methyltransferase, murine double minute 2 (MDM2), and epithelin (granulin) are upregulated in GBMs. We also demonstrate for the first time that the cytokine and p53 binding protein, macrophage migration inhibitory factor (MIF), appears upregulated in GBMs. These results indicate that the modulation of ion and solute transport genes and heretofore unsuspected cytokines (i.e., MIF) may have profound implications for brain tumor cell biology and thus may identify potential useful therapeutic targets in GBMs. glioblastoma; glutamate transporters; amiloride; NMDA receptors; BNaC; potassium channels; gene microarrays; patch clamp; reverse transcription-polymerase chain reaction; immunohistochemistry
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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52 wk from diagnosis (31).
Genetic alterations associated with GBM formation are somewhat different for primary and secondary GBMs (28). Typically, primary GBMs overexpress epidermal growth factor receptor (EGFR) and murine double minute 2 (MDM2) oncogene, occasionally with amplification (6, 22, 58). The tumor suppressor gene PTEN (MMAC1; i.e., "phosphatase and tensin homolog-mutated in multiple advanced cancers") mutations are present in 30%, and p16 tumor suppressor gene deletions are found in another one-third of these primary GBM tumors (7, 15). Secondary GBMs are more likely to exhibit p53 mutations and platelet-derived growth factor-A/platelet-derived growth factor receptor- (PDGF-A/PDGFR-) overexpression, which can also be demonstrated in low-grade tumor specimens (22, 58). Subsequently, these tumors accumulate loss of heterozygosity (LOH) for a segment of chromosomes 17p and 19q and alterations in the retinoblastoma gene, which are associated with progression to anaplastic astrocytoma. Further LOH of chromosome 10, PDGFR- amplification, and DCC (i.e., "deleted in colon cancer") gene mutations are seen in progression to GBM (28). Although some crossover occurs between primary and secondary GBMs that blur the distinction, by and large the division by genetic aberrations appears significant.
With the advent of cDNA/oligonucleotide microarray analysis, a tool has become available for identifying clusters of genes whose expression may be altered in diseased states (20, 34, 47, 57). In this study, we used oligonucleotide microarray technology (Affymetrix) to define differences in gene expression between normal human adult brain (temporal lobe) and primary GBMs. In addition, we applied molecular biological, immunohistochemical, and electrophysiological methods to confirm independently selected findings. Our results show that several ion and solute transport-related genes [e.g., N-methyl-D-aspartate (NMDA) receptors, -amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA)-2 receptors, glutamate transporters] and cytokines [e.g., macrophage inhibitory factor (MIF)] are either downregulated or upregulated in primary GBMs compared with normal neuroglial cells. The findings from this study establish that alterations in expression of genes encoding proteins important for cell cycle control and membrane ion and solute transport exist between normal and glioblastoma tumor cells. This information will be useful for the ultimate identification of patterns of genes that have altered expression in GBMs and thus to define specific disease within a given category of tumor.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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7,000 human genes and expressed sequenced tags (ESTs) (9). Each gene or EST is represented on the array by 20 feature pairs. Each feature pair contains a 25-bp oligonucleotide sequence, which is either a perfect match to the gene or a single central-base homomeric mismatch control. Affymetrix GeneChip analysis was performed using standard procedures (33, 57). Briefly, total RNA was extracted from snap-frozen, freshly resected tissue samples, after dissecting away necrotic and hemorrhagic portions. Three independent samples of whole brain tissue (temporal lobe, white matter) and four independent samples of primary GBM obtained from newly diagnosed patients who had not received chemotherapy or radiation therapy were used in these experiments. Biotinylated mRNA was prepared according to manufacturer’s suggestions (see Refs. 33 and 35 for details) as follows. Poly(A)+ RNA was prepared from 100 µg of total RNA and converted into doubled-stranded cDNA using a cDNA synthesis kit from Life Technologies. Biotinylated cRNA was then generated from the cDNA by an in vitro transcription reaction in which biotin-11-CTP and biotin-16-UTP were included. The labeled cRNA was purified using RNeasy spin columns (Qiagen). The cRNA was fragmented by alkaline treatment and hybridized to a GeneChip probe array. The total intensity of the hybridization was given by the mean filtered perfect match minus mismatch intensities corrected for variations between individual segments on the arrays. The new intensity of each gene sequence on an array was divided by the mean intensity of all the genes represented on that array and multiplied by a nominal average intensity of 50 to compensate for variations between different arrays. The expression level of any particular transcript was calculated by subtracting the difference between the fluorescence intensities of the perfect match and mismatch feature pairs and then averaging over the entire probe set. A negative expression value (i.e., green in Figs. 2–5) indicates that there was more unmatched signal than perfect match signal, whereas a positive expression value (i.e., red in Figs. 2–5) represents the reverse. Data were analyzed by the Cluster and TreeView software programs developed by Michael Eisen and colleagues (16) and available on the world wide web (http://rana.lbl.gov/). The results are presented as normalized intensities.
RNA extraction for RT-PCR.
Freshly excised human brain tissue (GBM or white matter from temporal lobe) was frozen and stored in liquid nitrogen until ready for processing. The frozen tissue was ground into a fine powder using a mortar and pestle, under liquid nitrogen, after which 1 ml of Trizol (Life Technologies) containing 250 µg of glycogen was added. The Trizol/powder mixture was transferred to a chilled glass/Teflon homogenizer and ground for 10 strokes while on ice. The homogenate was sequentially passed through 25- and 26-gauge needles, to shear genomic DNA, and then transferred to a 1.5-ml microcentrifuge tube. A volume of 200 µl of chloroform was added to the homogenate, vortexed for 30 s to mix, and centrifuged at maximum speed (14,000 rpm) for 5 min using a tabletop centrifuge at room temperature. The aqueous phase was transferred to a fresh 1.5-ml tube, 500 µl of ice-cold isopropanol were added, and the RNA was allowed to precipitate overnight at -20°C. The precipitated RNA was pelleted by centrifugation at maximal speed for 15 min at room temperature, washed with 1 ml of 70% ethanol, and centrifuged for 5 min. The pellet was dissolved in 100 µl of RNase-free H2O, re-extracted with phenol:chloroform (1:1), and vortexed, and the aqueous phase was precipitated with 1/10 volume of 7.5 M ammonium acetate and 2.5 vol of 100% ethanol overnight at -20°C. The precipitated RNA was pelleted by centrifugation, washed twice with 70% ethanol, and resuspended in RNase-free H2O. The integrity of the RNA was verified following electrophoresis through 1% agarose-formaldehyde gels. All equipment (e.g., homogenizers, mortar, pestle, etc.) were pretreated with RNase-Zap (Ambion) and rinsed with diethyl pyrocarbonate (DEPC)-treated H2O prior to use.
RT-PCR.
RT-PCR was performed using a OneStep RT-PCR kit (Qiagen) according to manufacturer’s instructions, using 0.2 µg of total RNA as template. Custom primers specific to the genes of interest were synthesized by Life Technologies and used at a final concentration of 0.6 µM. The forward and reverse primers for the human NMDA receptor subtype 2A (GRIN 2A, GenBank accession no. U09002) were 5'-GACTATTCCCCACCTTTTCG-3' and 5'-CTCCATCTCACCATCACCC-3' and corresponded to bases 2023–2042 and 2349–2367 of the coding region, respectively. The forward and reverse primers for the human NMDA receptor subtype 2B (GRIN 2B, GenBank accession no. U28758) were 5'-CCAAAGAGCATCATCACCC-3' and 5'-TGTAGCCATAGCCAGTCAG-3' and corresponded to bases 232–250 and 745–763 of the coding region, respectively. The forward and reverse primers for the human NMDA receptor subtype 2C (GRIN 2C, GenBank accession no. L76224) were: 5'-TCTATGATGCTGCTGTCCTC-3' and 5'-AGATGCCCCTGCTGAAAG-3' and corresponded to bases 2180–2199 and 2573–2590 of the coding region, respectively. The forward and reverse primers for the human brain Na+ channel 1 (BNaC1 or ASIC2, GenBank accession no. U57352) were 5'-GCAACCTAACCCGCTACAAC-3' and 5'-AGCAGGCAATCTCCTCCAAG-3' and corresponded to bases 1091–1110 and 1518–1537 of the coding region, respectively. The forward and reverse primers for the human brain Na+ channel 2 (BNaC2 or ASIC1, GenBank accession no. U78181) were 5'-CCCGCTATGGCAAAGAG-3' and 5'-GGCTCAGCAGGTAAAGTCC-3' and corresponded to bases 1109–1125 and 1572–1587 (plus 3 bases of the 3' untranslated region) of the coding region, respectively.
Reverse transcription was performed using a single cycle of 50°C for 30 min. This was followed by a single cycle of 95°C for 15 min, which inactivates the reverse transcriptases while activating the HotStarTaq DNA polymerase, followed by 30 cycles of 94°C for 1 min, 56°C for 1 min (60°C for BNaC1), and 72°C for 1 min, and finally a single 10-min cycle at 72°C. Aliquots of each reaction mixture were electrophoresed on a 2% NuSieve (FMC) agarose gel using PCR markers (Promega) to determine molecular size. Products of the correct molecular size were isolated from the gel using the QIAquick Gel Extraction kit (Qiagen) and subcloned into the pCR-2.1 vector using the TOPO-TA cloning kit (Invitrogen) following manufacturer’s instructions. Recombinants were selected by blue/white screening and restricted with EcoRI (Promega) to verify incorporation of insert of correct size. Sequences were verified by further restriction enzyme digest analysis and automated DNA sequencing (DNA Sequencing Facility, Iowa State University).
Whole cell patch-clamp studies.
Fresh normal temporal lobe specimens (obtained from patients undergoing surgery for intractable epilepsy) consisting primarily of white matter or GBM tumor specimens were obtained from patients undergoing surgical resection. Samples were immediately transported in sterile culture medium on ice from the operating room to the laboratory. As described above, after dissecting away any visible necrotic and/or hemorrhagic regions, a portion of the remaining tissue was minced, pipetted repeatedly to dissociate cells, and transferred directly to the patch-clamp chamber. Once the cells had adhered to the bottom of the glass perfusion chamber, they were patch clamped. Micropipettes were fashioned using a Narishige PP-83 two-stage micropipette puller (internal tip diameter of 0.3–0.5 mM). The pipettes were filled with a solution containing (in mM) 100 potassium gluconate, 30 KCl, 10 NaCl, 20 HEPES, 0.5 EGTA, and 4 ATP. This solution had less than 1 nM free Ca2+ and had a pH of 7.2. The electrical resistance of the filled pipettes was 1–3 M
. The bath solution was serum-free RPMI 1640 cell culture medium. These solutions approximate the normal ionic gradients across a mammalian cell membrane. Pipettes were mounted in a holder and connected to the head stage of an Axon model 200A patch-clamp amplifier fixed to a three-dimensional micromanipulator system attached to the microscope. The pipette was pressed to the cell and slight suction was applied. Seal resistance was continuously monitored on a Nicolet model 300 oscilloscope, using 0.1-mV electrical pulses from a pulse generator. After formation of seals with greater than 1-G seals, a negative pressure pulse was applied to the pipette to enter the whole cell configuration. Successful completion of this procedure was assessed by the sudden increase in capacitance with no change in seal resistance. Typically, this capacitance was between 5 and 10 pF. Subsequently, any capacitative transients were compensated by the use of the capacitative and resistance circuits of the amplifier.
Once the whole cell configuration was obtained, the pipette solution and the cytoplasmic compartment equilibrated within 30 s. The cells were held at a membrane potential of 0 mV for 1 s between each test voltage. This procedure produced inward sodium (at more hyperpolarized potentials) and outward potassium (at more depolarized potentials) currents to flow across the membrane. The currents were recorded digitally and filed in real time. The entire procedure was controlled using a computer modified for analog-to-digital signals with pCLAMP 6 software (Axon Instruments, Sunnydale, CA). For any given sample, 3–12 individual cells were examined.
Immunostaining of tissues.
Normal temporal lobe specimens were obtained from excess brain tissues surgically removed from patients with intractable epilepsy. GBM specimens were obtained from excess tissues obtained from patients undergoing surgical resection of their tumors. The diagnosis of GBM was confirmed by a neuropathologist. Tissue procurement was approved by the UAB Institutional Review Board for Human Experimentation. Tissues were transported on ice to the lab, debrided of areas of hemorrhage and necrosis, and divided into portions 4–6 mm on a side. Portions of these tissues were snap-frozen in cryovials for later processing for analysis of mRNA expression, and other aliquots of the same tissues were placed in OCT embedding medium and frozen on dry ice. For immunostaining, sections 8–12 µm thick were cut on a Zeiss H505E cryotome, mounted on triethoxy-3-aminopropylsilane (TEPSA)-coated slides and air dried. Representative sections were stained with hematoxylin and eosin and examined to determine the quality and suitability of the tissues for immunostaining. Sections were fixed in acetone at -20°C for 10 min and rehydrated in blocking medium. Antibodies against MIF (R&D Systems, Minneapolis, MN), aquaporin-1 (Alomone Laboratories, Jerusalem, Israel), NMDA receptor 2A/B (Chemicon International, Temecula, CA), GABAA receptor- (Boehringer, Mannheim, Germany), GABAA receptor- (Chemicon), and glutamate receptors 2 and 3 (Chemicon) were used.
Dilutions of commercially obtained polyclonal or monoclonal antibodies were prepared as recommended by the manufacturers, and 100–200 µl of each or nonimmune IgG were applied to adjacent serial sections of the tissues for 30–60 min. Sections were rinsed and incubated with biotinylated secondary antibodies (Vector Laboratories, Burlingame, CA) specific to the primary antibody. Slides were rinsed and incubated with avidin-biotin-peroxidase (ABP) reagent. Binding of the primary antibody was detected by rinsing unbound ABP reagent from the slides and adding diaminobenzidine (0.1 mg/ml) in the presence of 0.03% H2O2. After 5 min, slides were rinsed, counterstained with 1% methyl green, dehydrated, coverslipped with Cytoseal (Stephens Scientific, Riverdale, NJ), and examined microscopically.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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7,000 separate genes are represented on a single Affymetrix GeneChip, we examined our data in one of two ways: 1) by identifying genes either overexpressed or underexpressed in the glioblastomas vs. the normal tissue or 2) by classifying them into specific functional categories, such as neurotransmitters, angiogenesis factors, ion channels, etc. Prior to analysis, all genes identified as "absent" in all six samples (both normal and tumor) were first eliminated. Moreover, an expression sensitivity threshold (at least 2x background) against which average difference values were screened was applied. Figure 1 presents a log-log representation of the differential gene expression of the 7,000 transcripts analyzed in one GBM sample plotted against the expression level of the same genes measured in a single normal sample obtained from the temporal lobe. This pattern of expression was typical for all the other combinations of tumor vs. normal tissues. While the expression levels of most of the transcripts fall within a fivefold range (higher or lower) of the identity line, there are a number of genes whose expression levels are either fivefold greater or fivefold smaller than that seen in so-called normal temporal lobe. Using a color-coded scheme derived from the TreeView program, we created Fig. 2, which shows all of the genes that were significantly (at the <0.05 level) expressed to greater than fivefold in all of the glioblastomas compared with normal tissue samples. While only 34 of the 7,000 transcripts appear in this category, some important genes did emerge, including MDM2 p53-associated protein, -1-antitrypsin, metalloproteinase stromelysin-2 (MMP-10), and caveolin. Moreover, several genes, including 1) certain transcription factors (e.g., FUSE binding protein 2 and HLH IR21/heir1), 2) immune-related genes (e.g., lactoferrin, osteopontin, and PTX3 long pentraxin), 3) genes encoding cytoskeletal proteins [e.g., SNAP25 (synaptosomal-associated protein of 25 kDa), filamin, emerin, and lamin B], and 4) miscellaneous genes [e.g., aquaporin-1 (AQP-1), a nuclear Cl- channel protein, epithelin (granulin), MDM2, MDMX, (a p53-binding protein with homology to MDM2), nicotinamide N-methyltransferase, and the cellular ligand of annexin II], are all expressed in GBMs to a greater extent than in the normal tissue samples (see Supplemental Table 1; please refer to the Supplementary Material1 for this article, published online at the Physiological Genomics web site). The expression of many of these genes or proteins has already been reported to be upregulated in GBM compared with normal brain or cultured human astrocytes (17, 30, 32, 45). However, we found that the message for several secreted peptides, including insulin-like growth factor binding peptides 5 and 6, interferon-
, and macrophage migration inhibitory factor (MIF), appear to be upregulated in the GBMs vs. the normal samples. To our knowledge, none of these genes has been associated previously with brain tumors.
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3 and hKV2.1, glutamate/aspartate transporter II, the glutamate transporters, EAAT1 and 3, GLUT 5, NHE-1, the ionotropic glutamate receptors 2 (HBGR2) and 4 (GluR4), GABAA receptor 1, 2, and 3 subunits, and the NMDA receptors (GRIN 2A and NR1-1) were all underexpressed compared with control samples. Figures 4 and 5 display cluster analyses showing the differential expression profiles of the ion channels and all of the solute and neurotransmitters, respectively, represented on the GeneChip.
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Whole cell patch clamp.
Based on the results of the GeneChip analysis, we wanted to provide some functional verification of the predictors indicated above. We investigated by electrophysiological means two hypotheses generated by microarray analyses, namely, that a voltage-gated K+ channel 3 subunit (hKV3) and NMDA receptor-activated currents are downregulated in GBMs compared with normal brain. Potassium channels are crucial for the proper activity of all excitable cells, including neurons and astrocytes (29). The pore-forming KV channels constitute a large family of proteins with diverse properties. These channels in native cells undergo a variable time course of inactivation presumably because of the presence of different associated -subunits. There are at least three KV subunits that affect KV inactivation (21). KV3 has been isolated and cloned from rat brain (21). This subunit, in heterologous expression studies in oocytes, was shown to associate with hKv1.5 and to convert this channel from one acting as a delayed rectifier (i.e., one with very slow inactivation properties) to a channel with a rapid and well-defined inactivation characteristic (18). We therefore hypothesized that if hKV3 was downregulated in GBM cells, then the relaxation characteristics at hyperpolarizing clamp voltages would be different than those of normal cells. Figure 6 shows typical current traces recorded from freshly isolated, normal human astrocytes, glial GBM tumor cells (from two of the studied specimens, T1 and T3), and SKMG cells (a continuous glial cell line originating from a GBM). Two cells from each group are shown, but these same results were seen in a minimum of 10 cells in each group. A pronounced relaxation of the outward current traces at the two most positive voltage clamp potentials (+80 and +100 mV) could be seen in the normal astrocytes, but this was absent in the tumor cells. These electrophysiological characteristics are consistent with the microarray findings, namely, that the hKV3 gene is downregulated in the tumor cells, thus altering the biophysical characteristics of the K+ conductance.
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, GABAA receptor-, and the glutamate receptor 2 (Fig. 8B). Human GBMs were consistently positive for only AQP-1 and MIF proteins. Sections from normal temporal cortex tissues (i.e., samples N2 and N3) were also probed with these antibodies but showed very little positive staining. One sample showed low levels of positive staining over 50% of the specimen for NMDA receptor 2A/B (Fig. 8E). A summary of the immunohistochemical results is presented in Table 2.
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- and -subunits of the epithelial Na+ channel (-hENaC and -hENaC) were all identified as absent by the microarray analysis software in each of the normal and tumor samples analyzed (Supplemental Table 1). However, -hENaC was positive in each of the samples, with no clear distinction of expression intensity between the normal and GBM samples. The physiological significance of these findings remains to be determined, but variable expression of ENaC subunits has been documented previously (19). Moreover, other subunits belonging to this gene family, such as the acid-sensing ion channel ASIC3 (note: ASIC2a is the same as BNaC1) and 
-hENaC, are not represented on the HuFL GeneChip probe array. Several of these subunits have been shown to co-assemble and form heteromeric cation channels (e.g., Ref. 5). Although GeneChip technology is highly reliable and sensitive, the transcript amount is not necessarily amplified to the same level as obtained with RT-PCR. Therefore, mRNA present within a cell at very low levels may go undetected. To this end, we wanted to verify the presence of BNaC message in normal and GBM by RT-PCR as was done previously (10). Figure 10 shows that BNaC1 and BNaC2 message was present in both normal samples and in most of the tumor samples, at least for BNaC2. Only tumor sample T2 showed the presence of BNaC1. Direct sequencing of the PCR products confirmed their identity. The results are in contrast to the results of the microarray analyses, at least for BNaC1. The RT-PCR results for BNaC2 are not directly comparable to those of the microarray, because the microarray only has the alternatively spliced version of BNaC2 represented. However, the primers utilized to amplify BNaC2 were complementary to both the parental isoform (accession no. U78181) and the alternatively spliced isoform (accession no. U78180) of this gene, which contains a 38-nucleotide insertion between bp 1296 and 1297. Only a single band was detected for the BNaC2 PCR product, at the appropriate weight for the parental BNaC2, indicating absence of the alternatively spliced isoform in these samples.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The heterogeneity of GBMs is undoubtedly a function of their genomic variation and manifests as intertumoral differences with respect to specific markers (e.g., Ref. 7); indeed, there is a high degree of intratumor variability as well (23). Thus, to identify distinct subclasses of any given specific tumor type, the greater the number of samples whose gene expression can be determined, the greater our confidence in predicting outcomes of specific tumor treatment. To that end, we provide new data on gene expression profiling of four unique primary GBM tumors.
Gliomas are primarily derived from astrocytes (>80%), which take a variety of forms and subserve many different functions. Thus, while brain tissue is complex with respect to cell type and specific gene expression, the cells in the tissues used for these studies were primarily astrocytic in origin. It is true that an even more uniform cell population could be obtained from primary astrocytic tumor cell culture. However, cultured cells inevitably alter gene expression as a consequence of the selection pressures of the in vitro environment, thereby adding an artificial complication to attempts to delineate specific tumor-associated genes. To avoid this complication, we chose to restrict our analyses to cells from freshly resected tumors. Since the objective of this study was to identify genes that play a role in tumorigenesis and altered physiology of tumor cells compared with normal cells, we reasoned that the most relevant findings could be obtained from tissues and cells most closely related to the in vivo situation.
Although only the NMDAR1 (NR1-1), NMDAR2A, NMDAR2B, and NMDAR2C genes were represented on the microarray, there are numerous (note: several NMDAR1 variants, including GRIN 1, NR1-1, NR1-2, etc.) NMDAR human subunit cDNAs that have been cloned, with at least four isoforms of the NMDAR2C gene identified (14). There was measurable gene expression of NMDAR2A and NMDAR2C in all of the normal samples, but the expression levels appeared reduced or absent in the tumor samples (see Fig. 9). Based upon our gene expression, RT-PCR, and immunohistochemical results, the functional NMDA receptor activation measured in normal astrocytes (Fig. 7) was probably due to the combination of 1, 2A, 2B, and 2C and to the presence of other receptor subtypes not detected in any of our assays. The NMDA receptor subtype of glutamate-gated ion channels possesses high Ca2+ permeability and can form heteromeric receptors (14, 39, 41). Wang et al. (56) showed that upregulation of NMDA receptors in neurons led to increased NMDA-induced apoptosis. There was no measurable NMDA-activated current in our samples of freshly excised GBM cells. Likewise, the expression levels of the voltage-gated K+ channel 3-subunit (hKV3) and a number of glutamate transporters, including EAAT2, EAAT3, and GLAST, were depressed in the GBMs compared with normal brain. These observations conform to measured changes in relaxation of outward K+ currents in GBM cells (Fig. 6) and the reduced ability of human glioma cells to take up glutamate (60). Thus it is tempting to speculate that an apparent lack of these functional receptors may confer some selective advantage for tumor cell survival by failing to recognize apoptotic-inducing signals. Whether a similar apoptotic mechanism is expressed by normal glial cells remains to be determined.
In most of the four primary GBM, two genes, namely, AQP-1 and MIF, appeared overexpressed compared with normal, although there was wide scatter in the results. This finding was confirmed independently by immunohistochemistry, which demonstrated increased AQP-1 and MIF protein expression. A potential overexpression of AQP-1 by tumor cells is particularly exciting, because this gene encodes a well-characterized plasma membrane protein (1). Any plasma membrane protein expressed exclusively by neoplastic cells in situ is of great interest because extracellular epitopes from such proteins provide specific targets for immunotherapy without necessitating access to the cellular interior or altering nuclear processes.
AQP-1 was the first member of a large family of "water-channel" proteins expressed by mammalian cells (1). Aquaporins are expressed by erythrocytes, choroid plexus epithelium, renal tubular epithelium, and capillary endothelium (4, 43). Expression of aquaporin by neoplasms has not been well characterized, although it has been reported in renal carcinomas, erythroleukemia cell lines, and rodent mammary carcinomas (17, 26, 42). Recently, AQP-1 expression was examined in a single rat glioma and two human glioma cell lines (17). The findings were mixed, with no expression in rat and definite expression in only one of the two human cell lines. These findings illustrate one of the problems encountered when studying gene expression in cell lines, i.e., specific gene expression, or lack thereof, could simply be a function of culture-induced phenotypic alterations.
The finding that AQP-1 was upregulated in all four primary human GBMs appears to be more consistent than the findings from cell cultures. The significance of this apparently abnormal upregulation remains unknown, but others have speculated that such channels are important in allowing glioma cells to extrude water and shrink sufficiently in size to allow invasion of the surrounding brain through the extracellular matrix (17). Another possibility is that glioma cells utilize cGMP-mediated ionic signaling that AQP-1 may facilitate (4).
A second gene found to be upregulated in three of the four GBMs compared with the three normal brain specimens was MIF. MIF is a proinflammatory cytokine that induces the expression of many molecules that are involved in cellular inflammatory and immune responses. Monocytes and macrophages are an important source of MIF and release this substance after exposure to bacterial endo- and exotoxins (11). MIF expression is induced by glucocorticoids and is antagonistic to the immunosuppressive effects of glucocorticoids (40). MIF mRNA and protein overexpression have been reported in septic shock (11) and in various cancers, such as melanoma (51), lymphoma (12), prostatic tumors (36, 37, 54), breast carcinoma (8), and hypophysial and pituitary adenomas (55). It has not been reported previously as being overexpressed in malignant brain tumors. Hudson et al. (24) recently reported that MIF functionally inactivates the p53 tumor suppressor. As indicated earlier, nearly half of all primary GBMs have intact p53 genes; so, in addition to other exogenous suppressors of p53 transcriptional activity, e.g., MDM2 (59), the overexpression of MIF may contribute to the development or proliferation of primary malignant brain tumors via inhibition of p53.
In summary, this work provides new insights into the pathogenesis of human brain tumors, particularly GBMs. We have shown that GBMs overexpress the proinflammatory cytokine, MIF, and AQP-1 and underexpress a variety of ion and solute transport related proteins, including NMDAR2A and 2C, GABAA, and AMPA-2 receptors, as well as the glutamate/aspartate transporter II and NHE-1. The mechanism by which these alterations in RNA and protein expression relate to brain tumor development, proliferation, and invasion remains to be determined.
The ability to identify tumor-specific genes brings up a number of exciting possibilities for improved therapy. First, improvements in classification specificity can be made, which in turn can improve the choice of specific therapeutic regimens. Moreover, as in the case of AQP-1 or BNaC, specific gene products may turn out to be accessible targets for new therapies such as immunotherapy. When precise functions for over- or underexpressed genes are determined, new avenues for intervention strategies may emerge. These studies are in their infancy; however, the improved technology employed here shows reasonable promise as our understanding of these deadly tumors increases.
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ACKNOWLEDGMENTS |
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This work was supported by National Institute of Diabetes and Digestive and Kidney Diseases Grants DK-56095 and DK-52789, National Cancer Institute Award P01-CA-71933, and by the National Institute for Neurologic Disorders and Stroke Mentored Clinical Scientist Development Award 1K08-NS-01942 (J. M. Markert). J. K. Bubien is an Established Investigator of the American Heart Association.
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FOOTNOTES |
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Address for reprint requests and other correspondence: D. J. Benos, Dept. of Physiology and Biophysics, Univ. of Alabama at Birmingham, 1918 Univ. Boulevard, MCLM 704, Birmingham, AL 35294-0005 (benos{at}physiology.uab.edu).
1 Supplementary Material (Table 1) to this article is available online at http://physiolgenomics.physiology.org/cgi/content/full/5/1/21/DC1. 
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 W. E. Kim and G. Serrero PC Cell-Derived Growth Factor Stimulates Proliferation and Confers Trastuzumab Resistance to Her-2-Overexpressing Breast Cancer Cells. Clin. Cancer Res., July 15, 2006; 12(14): 4192 - 4199. [Abstract] [Full Text] [PDF]
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C. E. Pelloski, E Lin, L. Zhang, W.K. A. Yung, H. Colman, J.-L. Liu, S. Y. Woo, A. B. Heimberger, D. Suki, M. Prados, et al. Prognostic Associations of Activated Mitogen-Activated Protein Kinase and Akt Pathways in Glioblastoma. Clin. Cancer Res., July 1, 2006; 12(13): 3935 - 3941. [Abstract] [Full Text] [PDF]
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 R. E. Brown and A. Law Morphoproteomic Demonstration of Constitutive Nuclear Factor-kappaB Activation in Glioblastoma Multiforme with Genomic Correlates and Therapeutic Implications Ann. Clin. Lab. Sci., January 1, 2006; 36(4): 421 - 426. [Abstract] [Full Text] [PDF]
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S. A. Schwartz, R. J. Weil, R. C. Thompson, Y. Shyr, J. H. Moore, S. A. Toms, M. D. Johnson, and R. M. Caprioli Proteomic-Based Prognosis of Brain Tumor Patients Using Direct-Tissue Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Cancer Res., September 1, 2005; 65(17): 7674 - 7681. [Abstract] [Full Text] [PDF]
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J. D. Swant, B. E. Rendon, M. Symons, and R. A. Mitchell Rho GTPase-dependent Signaling Is Required for Macrophage Migration Inhibitory Factor-mediated Expression of Cyclin D1 J. Biol. Chem., June 17, 2005; 280(24): 23066 - 23072. [Abstract] [Full Text] [PDF]
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S. Chevillard, N. Ugolin, P. Vielh, K. Ory, C. Levalois, D. Elliott, G. L. Clayman, and A. K. El-Naggar Gene Expression Profiling of Differentiated Thyroid Neoplasms: Diagnostic and Clinical Implications Clin. Cancer Res., October 1, 2004; 10(19): 6586 - 6597. [Abstract] [Full Text] [PDF]
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P. B. Sinclair, A. Sorour, M. Martineau, C. J. Harrison, W. A. Mitchell, E. O'Neill, and L. Foroni A Fluorescence in Situ Hybridization Map of 6q Deletions in Acute Lymphocytic Leukemia: Identification and Analysis of a Candidate Tumor Suppressor Gene Cancer Res., June 15, 2004; 64(12): 4089 - 4098. [Abstract] [Full Text] [PDF]
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G. Ghannam, A. Takeda, T. Camarata, M. A. Moore, A. Viale, and N. R. Yaseen The Oncogene Nup98-HOXA9 Induces Gene Transcription in Myeloid Cells J. Biol. Chem., January 9, 2004; 279(2): 866 - 875. [Abstract] [Full Text] [PDF]
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H. Arima, N. Yamamoto, K. Sobue, F. Umenishi, T. Tada, H. Katsuya, and K. Asai Hyperosmolar Mannitol Stimulates Expression of Aquaporins 4 and 9 through a p38 Mitogen-activated Protein Kinase-dependent Pathway in Rat Astrocytes J. Biol. Chem., November 7, 2003; 278(45): 44525 - 44534. [Abstract] [Full Text] [PDF]
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 K. A. Furger, A. L. Allan, S. M. Wilson, C. Hota, S. A. Vantyghem, C. O. Postenka, W. Al-Katib, A. F. Chambers, and A. B. Tuck {beta}3 Integrin Expression Increases Breast Carcinoma Cell Responsiveness to the Malignancy-Enhancing Effects of Osteopontin Mol. Cancer Res., September 1, 2003; 1(11): 810 - 819. [Abstract] [Full Text] [PDF]
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G. Fingerle-Rowson, O. Petrenko, C. N. Metz, T. G. Forsthuber, R. Mitchell, R. Huss, U. Moll, W. Muller, and R. Bucala The p53-dependent effects of macrophage migration inhibitory factor revealed by gene targeting PNAS, August 5, 2003; 100(16): 9354 - 9359. [Abstract] [Full Text] [PDF]
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 S. Guccione, Y.-S. Yang, G. Shi, D. Y. Lee, K. C. P. Li, and M. D. Bednarski Functional Genomics Guided with MR Imaging: Mouse Tumor Model Study Radiology, August 1, 2003; 228(2): 560 - 568. [Abstract] [Full Text] [PDF]
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B. K. Berdiev, J. Xia, L. A. McLean, J. M. Markert, G. Y. Gillespie, T. B. Mapstone, A. P. Naren, B. Jovov, J. K. Bubien, H.-L. Ji, et al. Acid-sensing Ion Channels in Malignant Gliomas J. Biol. Chem., April 18, 2003; 278(17): 15023 - 15034. [Abstract] [Full Text] [PDF]
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O. Petrenko, G. Fingerle-Rowson, T. Peng, R. A. Mitchell, and C. N. Metz Macrophage Migration Inhibitory Factor Deficiency Is Associated with Altered Cell Growth and Reduced Susceptibility to Ras-mediated Transformation J. Biol. Chem., March 21, 2003; 278(13): 11078 - 11085. [Abstract] [Full Text] [PDF]
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M. B. Jones, C. M. Michener, J. O. Blanchette, V. A. Kuznetsov, M. Raffeld, G. Serrero, M. R. Emmert-Buck, E. F. Petricoin, D. B. Krizman, L. A. Liotta, et al. The Granulin-Epithelin Precursor/PC-Cell-derived Growth Factor Is a Growth Factor for Epithelial Ovarian Cancer Clin. Cancer Res., January 1, 2003; 9(1): 44 - 51. [Abstract] [Full Text] [PDF]
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M. K. Tanwar, M. R. Gilbert, and E. C. Holland Gene Expression Microarray Analysis Reveals YKL-40 to Be a Potential Serum Marker for Malignant Character in Human Glioma Cancer Res., August 1, 2002; 62(15): 4364 - 4368. [Abstract] [Full Text] [PDF]
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 A. M. Isidori, G. A. Kaltsas, M. Korbonits, M. Pyle, M. Gueorguiev, A. Meinhardt, C. Metz, N. Petrovsky, V. Popovic, R. Bucala, et al. Response of Serum Macrophage Migration Inhibitory Factor Levels to Stimulation or Suppression of the Hypothalamo-Pituitary-Adrenal Axis in Normal Subjects and Patients with Cushing's Disease J. Clin. Endocrinol. Metab., April 1, 2002; 87(4): 1834 - 1840. [Abstract] [Full Text] [PDF]
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J. W. Yoon, Y. Kita, D. J. Frank, R. R. Majewski, B. A. Konicek, M. A. Nobrega, H. Jacob, D. Walterhouse, and P. Iannaccone Gene Expression Profiling Leads to Identification of GLI1-binding Elements in Target Genes and a Role for Multiple Downstream Pathways in GLI1-induced Cell Transformation J. Biol. Chem., February 8, 2002; 277(7): 5548 - 5555. [Abstract] [Full Text] [PDF]
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Y. Hippo, H. Taniguchi, S. Tsutsumi, N. Machida, J.-M. Chong, M. Fukayama, T. Kodama, and H. Aburatani Global Gene Expression Analysis of Gastric Cancer by Oligonucleotide Microarrays Cancer Res., January 1, 2002; 62(1): 233 - 240. [Abstract] [Full Text] [PDF]
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