platelet endothelial cell adhesion molecule 1 (PECAM1) correlates with hypoxia inducible factor-1 alpha (HIF-1α) in human glioblastoma multiforme

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Enhanced expression of CD31/platelet endothelial cell adhesion molecule 1 (PECAM1) correlates with hypoxia inducible factor-1 alpha (HIF-1α) in human glioblastoma multiforme Giuseppe Musumeci a,1, Alessandro Castorina a,1, Gaetano Magro b, Vera Cardile c, Sergio Castorina a,d, Domenico Ribatti e,f,n a

Department of Biomedical and Biotechnological Sciences, Section of Human Anatomy and Histology, School of Medicine, University of Catania, 95123 Catania, Italy Department G.F. Ingrassia, Azienda Ospedaliero-Universitaria “Policlinico-Vittorio Emanuele”, Section of Anatomic Pathology, University of Catania, Via S. Sofia 87, 95123 Catania, Italy c Department of Biomedical Sciences and Biotechnologies, Section of Physiology, University of Catania, Via S. Sofia 87, 95125 Catania, Italy d Neurosurgery Unit, Fondazione Mediterranea “G.B. Morgagni”, Catania, Italy e Department of Basic Medical Sciences, Neurosciences and Sensory Organs, University of Bari, Medical School, Policlinico – Piazza G. Cesare, 11, 70124 Bari, Italy f National Cancer Institute “Giovanni Paolo II”, 70124 Bari, Italy b

art ic l e i nf o

a b s t r a c t

Article history: Received 23 August 2015 Received in revised form 9 September 2015 Accepted 11 September 2015

Glioblastoma multiforme (GBM) is characterized by numerous abnormal blood vessels, which rapidly proliferate and invade brain tissue and express different angiogenic factors. In this study we have investigated whether the expression levels of CD31/ PECAM1 are deregulated in human GBM tissue specimens and we have also correlated the expression levels of CD31/PECAM1 with those of HIF-1α. Finally, we have established a correlation between the expression levels of CD31/PECAM1 and HIF-1α, and those of two other biomarkers, namely N-cadherin and ADAM-10, of aggressiveness in the same tumors. Results have shown an increased expression of CD31/PECAM1 correlated to HIF-1α expression, confirming evidence demonstrating that different types of tumor are able to trigger aberrant angiogenesis through HIF-1α. Moreover, we also established a further correlation among CD31/PECAM1 and HIF-1α and N-cadherin and ADAM-10, two other markers of aggressiveness in the same tumors. & 2015 Elsevier Inc. All rights reserved.

Keywords: Angiogenesis CD31 Glioblastoma multiforme HIF-1α PECAM1 Tumor progression

1. Introduction Malignant gliomas are neuroectodermal tumors that commonly arise in the white matter of cerebral hemisphere, contributing to 30–45% of all intracranial human tumors [17]. Astrocytomas progress from grade II to grade III tumors with a time interval of several years, whereas progression of grade III to grade IV (glioblastoma multiforme, GBM) is more rapid, generally 2 years. Malignant gliomas are characterized by numerous abnormal blood vessels, which rapidly proliferate and invade brain tissue [3], showing several alterations, including an increased number of endothelial caveolae and fenestrations, prominent pinocytotic vesicles, and a lack of perivascular glial endfeet, as well as the opening, loss and/or abnormal morphology of tight junctions, leading to an altered vascular permeability and loss of the blood– n Corresponding author at: Department of Basic Medical Sciences, Neurosciences and Sensory Organs, University of Bari, Medical School, Policlinico – Piazza G. Cesare, 11, 70124 Bari, Italy. Fax: þ 39 080 5478310. E-mail address: [email protected] (D. Ribatti). 1 These authors have contributed equally to this work “equal contributions”.

brain barrier properties [12,21,32,37]. Microvascular proliferations with a “glomeruloid appearance” are an important feature of GBM, and have been observed in white matter surrounding the tumor near the areas of necrosis. We have demonstrated that in GBM an alternative mode of vascular growth, namely intussusceptive microvascular growth (IMG), is established [31]. IMG could be a mechanism of compensatory vascular growth occurring inhuman glioma. In this context, blood vessels are generated more rapidly; it is energetically and metabolically more economic; and the capillaries thereby formed are less leaky. Malignant gliomas express different angiogenic factors, including vascular endothelial growth factor (VEGF) and its receptors (VEGFR-1 and VEGFR-2) and angiopoietins, and angiogenesis is crucial for their growth [13,24]. VEGF induces the formation of hyperplastic microvascular proliferations known as “glomeruloid bodies”, which share structural similarities with the glomeruloid proliferation seen in GBM [43]. It is clear that excessive angiogenesis is an aberrantly occurring process that develops in GBM in the effort to increase the blood/ nutrient supply to densely packed neoplastic cells, which otherwise would suffer nutrient/oxygen starvation [18].

http://dx.doi.org/10.1016/j.yexcr.2015.09.007 0014-4827/& 2015 Elsevier Inc. All rights reserved.

Please cite this article as: G. Musumeci, et al., Enhanced expression of CD31/platelet endothelial cell adhesion molecule 1 (PECAM1) correlates with hypoxia inducible factor-1 alpha..., Exp Cell Res (2015), http://dx.doi.org/10.1016/j.yexcr.2015.09.007i

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Considering that the phenomenon represents a negative prognostic factor for the already poor outcome associated to these types of tumors [22], in this study we have investigated whether the expression levels of CD31/ PECAM1 are deregulated in human GBM tissue specimens and we have also correlated the expression levels of CD31/PECAM1 with those of hypoxia-inducible factor-1α (HIF-1α). Finally, we have established a correlation between the expression levels of CD31/PECAM1 and HIF-1α, and those of two recently identified biomarkers, namely N-cadherin and ADAM-10, of aggressiveness in the same tumors [30].

2. Materials and methods 2.1. Patients and tissue samples Twenty five samples of GBM, diagnosed by magnetic resonance imaging (MRI), were collected from patients who had undergone surgery at two clinical centers (Neurosurgery Unit, Fondazione Morgagni, Catania, Italy and Neurosurgery Unit, Cannizzaro Hospital, Catania, Italy). The same specimens have already been used in our recently reported investigations [30]. All the patients underwent surgical resection between June 2012 and May 2014. The median age was 68 (range 51–76 years). They had undergone macroscopic total or near-total resection of tumor, as confirmed on postoperative MRI, and had a postoperative Karnofsky Performance Scale (KPS) scoreZ70. The patients received conventional therapy consisting of maximal surgical resection, followed by radiotherapy and/or chemotherapy. The diagnosis of primary GBM was established on a strict morphological criterion (grade IV), according to the classification of 2007 from the World Health Organization (WHO) [23] with the relative code of the International Classification of Diseases for Oncology (ICD-O 94440/3). The glial nature of the tumors was also confirmed by immunohistochemical analyses, showing a diffuse and strong cytoplasmic staining for glial fibrillary acidic protein (GFAP) in all cases (data not shown). Controls (n ¼8) were represented by small portions of the anterior temporal cortex resected from another group of age-matched patients who had undergone surgery for intractable epilepsy. The reason why we chose brain tissue samples from epileptic patients as controls rather than the peritumoral tissues was based on preliminary evidences obtained in our laboratories showing variability in the levels of stemness cell markers in tissues surrounding glioblastomas (data not shown). Furthermore, different evidences suggest the presence of tumor cells infiltrating the peritumour tissue or to changes in the gene expression profile of cells surrounding the tumor [20,33,41,42] that are compatible with a transition state defined “precancerous state” or “quiescent cancer cells”, with show apparently normal morphology [25]. The investigation was performed following the approval of the institutional review board. Informed consent was obtained from each patient; the research was approved by the Local Medical Ethical Committee and conformed to the ethical guidelines of the Declaration of Helsinki. 2.2. Histology Samples were rinsed in phosphate buffered saline (PBS), fixed in 10% buffered-formalin as previously described [26,5]. After an overnight wash, specimens were dehydrated in graded ethanol, cleared in xylene and paraffin-embedded, preserving their anatomical orientation. Sections (4–5 μm in thickness) were cut from paraffin blocks using a microtome, mounted on sialinate-coated slides and stored at room temperature. The sections were then stained with hematoxylin and eosin (H&E) and examined using a Zeiss Axioplan light microscope (Carl Zeiss, Oberkochen, Germany)

for general morphological characterization and to highlight the presence or absence of structural alterations. Finally, representative photomicrographs were captured using a digital camera (AxioCam MRc5, Carl Zeiss, Oberkochen, Germany). 2.3. Immunohistochemistry (IHC) For immunohistochemical analyses, brain tissues were processed as previously described [36,7]. Briefly, slides were dewaxed in xylene, hydrated using graded ethanols and incubated for 30 min in 0.3% H2O2/methanol to quench endogenous peroxidase activity before being rinsed for 20 min with phosphate-buffered saline (PBS; Bio-Optica, Milan, Italy). The sections were heated (5 min  3) in capped polypropylene slide-holders in citrate buffer (10 mM citric acid, 0.05% Tween 20, pH 6.0; Bio-Optica, Milan, Italy), using a microwave oven (750 W) to unmask antigenic sites as previously described. The blocking step was performed before application of the primary antibody with 5% bovine serum albumin (BSA, Sigma, Milan, Italy) in PBS for 1 hour in a moisted chamber. BSA was used as a blocking agent to prevent non-specific binding of the antibody to the tissue sections. Following blocking, the sections were incubated overnight at 4 °C with a mouse monoclonal anti-PECAM-1 antibody (#89C2, Cell Signaling, UK), diluited 1:200 in PBS (Sigma, Milan, Italy) or a rabbit polyclonal anti-HIF1α antibody (H-206, cat no. sc-10790, Santa Cruz Biotechnologies Inc.), diluted 1:100 in PBS. Immune complexes were then treated with a biotinylated linked HRP-conjugated secondary antibody and then detected with peroxidase-labeled streptavidin, both incubated for 10 min at room temperature (LSABþ SystemHRP, K0690, Dako, Glostrup, Denmark). Immunoreactivity was visualized by incubating both control and GBM sections simultaneously until brown color developed in a 0.1% 3,3′-diaminobenzidine and 0.02% hydrogen peroxide solution (DAB substrate Chromogen System; Dako, Denmark). The sections were faintly counterstained with Mayer’s hematoxylin (Histolab Products AB, Göteborg, Sweden) mounted in GVA (Zymed Laboratories, San Francisco, CA, USA) and observed under an Axioplan Zeiss light microscope (Carl Zeiss, Oberkochen, Germany) and then photographed with a digital camera (AxioCam MRc5, Carl Zeiss, Oberkochen, Germany). 2.4. Software-assisted morphometric measurements and image analyses Fifteen fields, randomly selected from each section, were analyzed and the percentage of area stained with PECAM-1 (CD31) or HIF-1α antibodies was calculated using an image analysis software (AxioVision Release 4.8.2 – SP2 Software, Carl Zeiss Microscopy GmbH, Jena, Germany), which allows to create macros that reliably quantify the levels of staining intensity of immunopositive areas in a fixed field, as described previously [28,29]. Digital photomicrographs were taken using the Zeiss Axioplan light microscope (using objective lens of magnification  20 i.e. final magnification  400) equipped with a digital camera (AxioCam MRc5). Parameters for acquisition, including the threshold levels to detect stained areas were kept constant throughout the experiments to reduce technical biases [14]. The formula employed to calculate the percentage of stained area was the following: Percentage of area with positive staining ¼(mean of above  threshold stained area per field/total ROIs area per field)*100. 2.5. Protein extraction procedure Protein lysates from control and GBM tissue samples were obtained as described previously [14,8]. Briefly, tissues were homogenized in ice-cold RIPA buffer containing 20 mM Tris (pH

Please cite this article as: G. Musumeci, et al., Enhanced expression of CD31/platelet endothelial cell adhesion molecule 1 (PECAM1) correlates with hypoxia inducible factor-1 alpha..., Exp Cell Res (2015), http://dx.doi.org/10.1016/j.yexcr.2015.09.007i

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7.4), 2 mM EDTA, 0.5 mM EGTA; 50 mM mercaptoethanol, 0.32 mM sucrose, a protease inhibitor cocktail (Roche Diagnostics) and a phosphatase inhibitor (PhosSTOP, Roche Diagnostic) using a Teflon-glass homogenizer and then sonicated twice for 20 s using an ultrasonic probe, followed by centrifugation at 10.000 g for 10 min at 4 °C. Protein concentrations were determined using the Quant-iT Protein Assay Kit (Invitrogen, Carlsbad, CA, USA) and then stored at  80 °C until further analyses. 2.6. SDS-PAGE and western blot analyses Western blot analysis was performed according to a well-established procedure in our laboratories [6]. Briefly, solubilized proteins (40 μg) were diluted in 2X Laemmli buffer (Invitrogen), heated at 70 °C for 10 min and then separated on a Biorad Criterion XT 4–15% Bis-tris gel (Invitrogen) by gel electrophoresis. Thereafter, proteins were transferred to a nitrocellulose membrane (Invitrogen). Blots were then blocked using the Odyssey Blocking Buffer (Li-Cor Biosciences). Effective transfer was monitored using a prestained protein molecular weight marker (BioRad Laboratories). Immunoblot analyses for PECAM1 and HIF-1α were carried out using the same antibodies used for immunohistochemical studies, but at different dilution: anti-PECAM1 (1:800), anti-HIF1α (1:500). A rabbit anti-β-tubulin antibody (H-235, cat. n. sc-9104, SantaCruz Biotechnologies Inc., 1:500) was used as loading control. Secondary antibodies were used at a dilution of 1: 20,000 and 1: 30,000: the goat anti-rabbit IRDye 800CW, (cat #926-32211; LiCor Biosciences) and the goat anti-mouse IRDye 680CW, (cat #926-68020D; Li-Cor Biosciences), respectively. Blots were scanned using a Li-Cor Odyssey Infrared Imaging System (Li-Cor Biosciences). Densitometric analyses of bands were performed at nonsaturating exposures using the ImageJ software (NIH, Bethesda, MD; available at http://rsb.info.nih.gov/ij/index.html). Densitometric values of target blots were normalized to β-tubulin, which served as loading control. 2.7. Dissociation and culturing of GBM-derived cells In order to investigate the type and differentiation stage of cells in surgical specimens, four GBM specimens were washed twice in Ca2 þ -free Hank's balanced salt solution and transferred into 3 ml of 1% trypsin in PBS for 10 min at room temperature. The tissues were dissociated by mechanical chopping for 10–20 min and filtered through nylon meshes to obtain a single-cell suspension. Cells were pelleted at 200  g and re-suspended in DMEM/F12 (1:1 v/v) containing 10% fetal bovine serum, 2 mM L-glutamine, penicillin (100 U/mL), and streptomycin (100 μg/ml). Cells were maintained in an atmosphere of 5% CO2 and 95% humidified air at 37 °C. Culture media was refreshed twice a week. After 8–10 days in culture, mixed GBM glial cultures were harvested by tripsin/ EDTA and re-plated in 96-well plates at the density of 8  103 cell/ well for immunocytochemistry analyses. 2.8. Immunocytofluorescence analyses In order to determine the cell type and estimate differentiation stage in dissociated cultures obtained from surgical samples of GBM, immunocytochemical analyses using several cell surface markers were carried out. Cells were first washed with PBS, then fixed with 4% paraformaldehyde (PFA) in PBS for 30 min and incubated for another 30 min with a 5% solution of normal goat serum (NGS; Sigma-Aldrich) to block non-specific antigenic sites. Cells were subsequently incubated overnight at 4 °C with the following primary antibodies: antinestin (1:600; Abcam, Prodotti Gianni, Milan, Italy), -GFAP (1:200; Abcam, Prodotti Gianni), -A2B5 (1:5, Abcam, Prodotti Gianni), -O1 (1:5, Abcam, Prodotti Gianni), and -O4 (1:5, Abcam, Prodotti Gianni). The

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following day, cells were rinsed in PBS and incubated for 1 h at room temperature with secondary antibody conjugated to different fluorophores. These were fluorescein isothiocyanate (FITC)-conjugated goat anti-rabbit or Cyanine (Cy)3-conjugated goat anti-mouse secondary antibodies (Millipore). To assess the specificity of immunostaining, we omitted either the primary or secondary antibody. As a rule, cell nuclei were counterstained with DAPI for 10 min. Digital images were acquired using a Leica DMRB fluorescence microscope (Leica Microsystems Srl, Milan, Italy) equipped with a computer-assisted Nikon digital camera (Nital SpA, Turin, Italy). The excitation wavelength was λ ¼554 nm for Cy3, λ ¼488 nm for FITC and λ ¼ 350 nm for DAPI. Immunostaining was evaluated taking into account the signal-to-noise ratio of immunofluorescence. Each antibody was assessed in triplicate, and a semi quantitative analysis was performed as following. Single cells were scored as positive when fluorescent signal for the specific marker was detected; means of triplicate counts were calculated, and values are expressed as percentage of positive cells respect to total nuclei counted (% mean of positive cells 7SEM with respect to the mean total number of nuclei). 2.9. Quantitative real time polymerase chain reaction Total RNA extracts obtained from controls (n ¼4) and resected GBM tissue samples (n ¼8) were isolated using 1 ml TRIzol reagent (Invitrogen) and 0.2 ml chloroform and precipitated with 0.5 ml isopropanol. Pellets were then washed with 75% ethanol and airdried. cDNAs were synthesized by incubating total RNA (5 mg) with SuperScript III RNase H-reverse transcriptase (200 U/μl) (Invitrogen); Oligo-(dT)20 primer (100 nM) (Invitrogen); 1 mM dNTP mix (Invitrogen), dithiothreitol (DTT, 0.1 M), Recombinant RNase-inhibitor (40 U/μl) at 42 °C for 1 h in a final volume of 20 μl. Reaction was terminated by incubation of samples at 70 °C for 10 min. Aliquots of cDNA (100 ng) from non-tumor and GBM tumor samples and external standards at known amounts (purified PCR products, ranging from 102 to 108 copies) were amplified in parallel reactions, using the following primer pairs: CD31 forward, 5′GTGCTGCAATGTGCTGTGAA -3′, CD31 reverse, 3′- TGCTAGCCTTCTG CTTGGTC -5′; S18 forward, 5′- GAGGATGAGGTGGAACGTGT -3′, S18 reverse, 3′- GGACCTGGCTGTATTTTCCA -5′. mRNA levels of the reference gene, the S18 ribosomal protein subunit, were measured in each amplification and used as internal calibrator values. Each PCR reaction contained 0.5 μM primers, 1.6 mM MgCl2 þ, 1X Light Cycler-FastStart DNA Master SYBR Green I (Roche Diagnostic). Amplifications were performed using the Light Cycler 1.5 instrument (Roche Diagnostic) with the following program setting: (I) cDNA denaturation (1 cycle: 95 °C for 10 min); (II) quantification (45 cycles: 95 °C for 10 s, 60 °C for 30 s, 72 °C for 7 s); (III) melting curve analysis (1 cycle: 95 °C for 0 s, 65 °C for 15 s, 95 °C for 0 s); (IV) cooling (1 cycle: 40 °C for 30 s). To assess the different expression levels we analyzed the mean fold change values of each sample, calculated using the ΔΔCt method as previously described [7]. The Ct represents the number of cycles needed to detect a fluorescence above a specific threshold level and it is inversely correlated to the amount of nucleic acids in the reaction. The ΔCt was calculated by normalizing the mean Ct of each sample to the mean Ct of the reference gene measured in the same experimental condition. For the quantification of each gene we considered the cDNA from non-tumor samples as the positive sample (calibrator sample). The ΔΔCt of each sample was then calculated by subtracting calibrator ΔCt to target sample (GBM) ΔCt. The formula 2-ΔΔCt was used to calculate fold changes. Baseline measurements for each calibrator sample were set to 1. PCR products specificity was evaluated by melting curve analysis.

Please cite this article as: G. Musumeci, et al., Enhanced expression of CD31/platelet endothelial cell adhesion molecule 1 (PECAM1) correlates with hypoxia inducible factor-1 alpha..., Exp Cell Res (2015), http://dx.doi.org/10.1016/j.yexcr.2015.09.007i

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2.10. Statistical analyses Statistical analysis was performed using SPSS software (SPSSs release 16.0, Chicago, IL, USA). The Pearson correlation matrix and linear regression analyses were computed using GraphPad Prism ver. 5.03 for Windows, GraphPad Software, San Diego California USA, www.graphpad.com. Data were tested for normality with the Kolmogorov–Smirnov test. All variables were normally distributed. Pairwise comparisons between two group means were tested with the Student's t-test. P-values of less than 0.05 were considered statistically significant; p-values of less than 0.01 or 0.001 were considered highly statistically significant. Data are presented as the mean 7SEM.

3. Results 3.1. Histological observations Histological evaluations (H&E staining) did not show pathological signatures in brain tissue samples obtained from intractable

epileptic patients (herein used as healthy controls) (Fig. 1A). High-grade gliomas were mainly composed of highly atypical glial cells, with variable in size and shape (ranging from polygonal to spindle-shaped cells), and distributed in a fine fibrillary background (Fig. 1B). Notably, numerous cell undergoing mitoses, including atypical mitoses, were identified in tumor tissues. Characteristically, in some tumor areas neoplastic cells tended to aggregate around necrotic foci, defining the known configuration called “palisading necrosis” (Fig. 1B). Moreover, the occurrence of a notable and diffuse neoangiogenetic process was noted, mainly in the form of glomeruloid microvascular hyperplasia. Based on these typical histopathological features, the diagnosis of GBM, World Health Organization (WHO) grade IV, was established. As indicated in Materials and methods section, the glial nature of each tumor was confirmed by immunostaining of neoplastic cells with GFAP antibodies (data not shown). 3.2. CD31 expression is increased in human GBM Vs control tissue samples Comparative IHC analyses using a monoclonal antibody specific

Fig. 1. Histological findings. (A) Representative hematoxylin & eosin (H&E) stained tissue sections showing normal morphology in brain tissue biopsies obtained from intractable epileptic patients (Control). Scale bar: 200 mm. (B) Representative H&E stained tissue sections showing the characteristic histological features of glioblastoma multiforme (GBM): malignant cells with high nuclear pleomorphism, diffuse necrotic areas (palisading necrosis, N and black arrows) and marked vascular proliferation (blue arrows). Scale bar: 300 mm.

Please cite this article as: G. Musumeci, et al., Enhanced expression of CD31/platelet endothelial cell adhesion molecule 1 (PECAM1) correlates with hypoxia inducible factor-1 alpha..., Exp Cell Res (2015), http://dx.doi.org/10.1016/j.yexcr.2015.09.007i

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Fig. 2. CD31 expression in Control Vs GBM tissue samples. (A) Representative photomicrograph low to moderate CD31 (PECAM1) staining restricted to perivascular regions of control specimens. (B) Representative photomicrograph showing extended CD31-staining in GBM tissue. (A' and B') Insets of A and B depicting details of stained areas in both control and GBM tissues at a higher magnification. Magnification  20; Scale bar: 100 mm. Magnification in insets  63.5; Scale bar: 30 μm. (C) Histogram showing the mean (%) of CD31 þ areas over the mean total ROI area7 SEM in control and GBM tissue samples, measured using an image analysis software (AxioVision Release 4.8.2 – SP2 Software, Carl Zeiss Microscopy GmbH, Jena, Germany) according to the procedures detailed in “Materials and Methods”. Each data point was calculated by analysing the % of stained area in three randomly selected fields from the same tissue section. Afterwards, the same procedure was repeated in other five sections taken from different tumor samples from either controls and GBM (n¼ 5 per group) to produce the reported mean values. ***p o 0.001 Vs Control, unpaired two-tailed Student t-test. (D) Immunoblots and densitometric analyses showing the differential expression of CD31 between non-tumoral and GBM samples. Tissue lysates (40 μg) obtained from three separate controls and three GBM samples (n¼ 3 per group) were separated by SDS-PAGE and transferred to nitrocellulose membranes. Thereafter, membranes were incubated using a CD31 antibody and blots were scanned with an Odyssey Infrared Imaging System. Densitometric analyses were then performed using the ImageJ software and values obtained were normalized to β-tubulin, which was used as loading control. Results are expressed as the average ratios7 S.E.M. from at least three independent determinations. *p o0.05 Vs Control, two-tailed Student t-test.

for the endothelial marker CD31 in control Vs. GBM tissues revealed a remarkable increase in the (%) of stained area in tumor tissues with respect to controls (Fig. 2A and B). Indeed, while a physiological and moderate staining was detected in areas surrounding small blood vessels in healthy tissues (see inset in Fig. 2A'), a strong increase of CD31 þ staining was found mainly at the periphery of the necrotic foci (Fig. 2B and B'). Image analyses confirmed our observations, thus showing that the % of CD31 þ staining in GBM was significantly higher compared to controls (63.17 76.34% Vs 6.77 71.12%; t8 ¼8.76, ***p o0.01 Vs Control, Student t-test; Fig. 2C). Additional immunoblot analyses on representative tumor and normal brain tissues samples (n ¼3 for each group) were consistent with IHC and image analyses, with significantly augmented CD31 expression in GBM Vs Controls

(t4 ¼3.66, *p o0.05 Vs Control; Fig. 2D). 3.3. Enhanced HIF-1α levels in GBM tissues correlate with CD31 overexpression Here, we found that constitutive but moderate HIF-1α þ is thoroughly present in normal brain tissues (Fig. 3A), which shows a clear nuclear localization (inset in Fig. 3A'). In GBM tissues, the % of HIF-1α is markedly increased in the nucleus of tumoral cells, but also accumulates in the cytoplasm and in the perinuclear regions of areas showing ongoing glomeruloid microvascular hyperplasia (see Figs. 1B, 3B and 3B' for reference). Semi-quantification of HIF-1α-stained areas demonstrated that in GBM tissues immunostained % was 45.54 76.05% Vs 24.137 2.19% in controls,

Please cite this article as: G. Musumeci, et al., Enhanced expression of CD31/platelet endothelial cell adhesion molecule 1 (PECAM1) correlates with hypoxia inducible factor-1 alpha..., Exp Cell Res (2015), http://dx.doi.org/10.1016/j.yexcr.2015.09.007i

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Fig. 3. Correlation between CD31 and HIF-1α expression in GBM tissues. (A) Illustrative photomicrograph depicting a moderate HIF-1α nuclear staining in control tissues. (B) GBM tissues show evident increases in staining areas, not limited to the nuclear compartment. (A' and B') Insets of A and B showing details of stained areas in both control and GBM tissues at 2  higher magnifications. Magnification  20; Scale bar: 100 mm. Magnification in insets  40; Scale bar: 50 μm. (C) Bar graph displaying the mean (%) of HIF-1α þ areas over the mean total ROI area7SEM in control and GBM tissue samples, measured as specified in Fig. 2 above. *p o 0.05 Vs Control, unpaired twotailed Student t-test. (D) Western blots and densitometric analyses showing the differential expression of HIF-1α between controls and GBMs. Tissue lysates (40 μg) obtained from three separate controls and three GBM samples (n¼ 3 per group) were processed to generate blots as detailed above. Densitometric analyses were then performed using the NIH ImageJ software and values were normalized to β-tubulin, here used as loading control. Results are expressed as the average ratios7 S.E.M. from at least three independent determinations. **p o 0.01 Vs Control, two-tailed Student t-test. (E) The comparative assessment of CD31 transcripts encoding in non-tumor brain tissue biopsies (Control, n¼4) and in GBM tissue samples (n ¼8) was determined by quantitative real time PCR analyses. Amplifications were performed using selected primers optimized for qPCR analyses (o 150 bp length) and recognizing fragments within the coding sequence of the gene of interest. Results are presented as mean fold changes of Controls7 S.E.M. Fold changes of CD31 were obtained after normalization to the endogenous S18 reference gene and then calculated using the comparative ΔΔCt method. Baseline expression levels of the control groups (Control) were set to 1. Bar graphs depicted show the mean results from at least three independent determinations. **p o 0.01 Vs Control, using the unpaired two-tailed Student t-test. (F) Scattered plot showing the correlation trend between CD31- and HIF-1α-stainings (%) in the sample GBM population used in this study (n ¼25 GBM tissues). Pearson's r values and statistical power of the correlation are also shown. For further details on the procedure please refer to Table S1.

Please cite this article as: G. Musumeci, et al., Enhanced expression of CD31/platelet endothelial cell adhesion molecule 1 (PECAM1) correlates with hypoxia inducible factor-1 alpha..., Exp Cell Res (2015), http://dx.doi.org/10.1016/j.yexcr.2015.09.007i

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thus with statistical significance (t8 ¼3.326, *p o0.05 Vs Control; Fig. 3C). Western blot analyses followed by densitometry confirmed the observed increase in HIF-1α expression in GBM (t4 ¼ 5.669, **p o0.01 Vs Control; Fig. 3D). In addition to the assessments at the protein level, we also appraised whether CD31 was effectively upregulated in a transcriptionally regulated fashion in GBM. As expected, CD31 mRNAs were increased 2.66 70.31-fold in GBM compared to controls, reaching the threshold for high statistical power (t6 ¼ 5.052; **p o0.01 Vs Control; Fig. 3E). Lastly, we performed correlation analyses aimed at demonstrating the potential association (if any) between CD31 and HIF-1α expression in our sample GBM population (n ¼25 samples per type). As depicted in Fig. 3F, a highly significant degree of correlation was identified between these two putative markers of angiogenesis (r ¼ 0.602, **p o0.01), suggesting that overexpression of HIF-1α may be predictive of CD31 upregulation in GBM and vice versa.

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Pairwise correlations between CD31 and N-cadherin and CD31 and ADAM-10 are depicted in Fig. 4A and B. Similarly, scattered plots in Fig. 4C and D show correlation data between HIF-1α and N-cadherin and HIF-1α and ADAM-10, respectively. Our data indicated that CD31 displays a high degree of correlation with ADAM-10 in GBM samples (Fig. 4A, r ¼0.595, po 0.01), suggesting the existence of a potential relationship between the proteolytic activity in these tumors and the aberrant angiogenesis. A further but not significant positive correlation was identified between HIF-1α and ADAM-10

3.4. Correlation among CD31, HIF-1α, N-cadherin and ADAM-10 immunoreactivities in GBM tissues After confirming the incidence of both CD31 and HIF-1α immunopositiveness (% of stained area 425%➜[15/25 for CD31, 60%; 13/25 for HIF-1α, 52%]) and the existence of a positive correlation between CD31 and HIF-1α in our GBM population, we also attempted to appraise the degree of correlation (Pearson's r) among such newly identified markers in our sample GBM population and other recently identified biomarkers of aggressiveness in the same tumors [30]. For the purpose, the percentage of staining for CD31, HIF-1α, N-cadherin and ADAM-10 from each GBM sample population (n ¼25) was analyzed using GraphPad Prism software, to compute a Pearson correlation matrix (see Table S1). We identified a positive and highly significant correlation and a slightly positive correlation, although the latter was not statistically significant.

Fig. 5. Bright light microscopy image of cells dissociated from surgical samples of glioblastoma multiforme. Representative photomicrograph showing the morphological appearance of dissociated GBM cells in culture. After 5 DIV, two major types of adherent cells were observed: a predominant cell population with an evident star-like appearance, with several primary processes originating from the soma, and a second population consisting of few sparse bipolar-shaped cells presenting an ovoid cell body and elongated processes, typical of astrocyte type-1 precursors. Magnification  63.5; scale bar: 50 mm.

Fig. 4. Correlation among CD31, HIF-1α, N-cadherin and ADAM-10 immunoreactivities in GBM tissues. Scatter plots of IHC data for each biomarker were generated using GraphPad Prism ver. 5.03 software to demonstrate the correlation level among the indicated biomarkers of GBM aggressiveness. The (%) of stainings for CD31, HIF-1α, N-cadherin and ADAM-10 from each GBM sample (n¼ 25) were used to compute a Pearson correlation matrix (shown in Table S1), followed by measurement of statistical power of pairwise correlations by Student t-test (A–D).

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staining scores, but the limited sample size, along with the variability of results did not allow to reach the threshold for statistical significance (Fig. 4D, r ¼0.325, p ¼0.113). Correlation attempts between CD31 or HIF-1α Vs N-cadherin failed to recognize further potential associations among the markers (Fig. 4A and C, r ¼0.008, p ¼0.696 and r ¼0.103, p ¼0.624, respectively). 3.5. Cellular characterization of cultures obtained from dissociated GBM tissue samples To finally establish the type and differentiation stage of cells in our GBM tissue specimens, surgical samples were mechanically dissociated and the obtained cultures were grown in vitro for morphological evaluation using bright light microscopy (Fig. 5) and by immunofluorescence through the use of several glial cellspecific markers (Fig. 6) according to procedures previously reported [9]. After 5 days of culture, two major types of adherent cells were observed: a predominant cell population with an evident star-like appearance, with several primary processes originating from the soma, and a second population consisting of few sparse bipolar-shaped cells presenting an ovoid cell body and elongated processes (Fig. 5). Immunocytofluorescence analyses

using appropriate combinations of glial markers revealed that cells were negative for both the glial-restricted precursor and the O2A progenitors (A2B5 þ ), for the oligodendrocytes (both O1þ and O4þ), and for type-2 astrocytes (A2B5 þ and GFAP þ ). However, those cells obtained from surgical specimens which were negative for GFAP (GFAP  ) and positive for nestin (Nestin þ ), were characterized as being astrocyte-restricted precursors (bipolar-shaped cells), and those GFAP þ and A2B5  as astrocytes type-1 (star-like cells) (Fig. 6). The percentage of positive cells was 8.55 70.64% and 92.57 2.5% for nestin and GFAP, respectively (Table 1).

Table 1 Percentage (%) of positive cells for each indicated cell marker. Specific cell markers

% of positive cells (mean 7 SEM)

Nestin A2B5 O1 O4 GFAP

8.55 7 0.64 0.32 7 0.1 0.127 0.01 None detected 92.5 7 2.5

Fig. 6. Expression of glial markers in cells obtained from dissociated samples of human GBM. Representative immunofluorescent photomicrographs obtained using specific combinations of glial specific markers to characterize the predominant cell population in GBM. Briefly, after mechanical dissociation of GBM samples, mixed GBM-derived glial cells were maintained in culture for 8–10 DIV. Thereafter, cell cultures were harvested by tripsin/EDTA and re-plated in 96-well plates at the density of 8  103 cell/well for immunohistochemistry. Staining using the appropriate combinations of glial markers revealed that cells were negative for both the glial-restricted precursor (A2B5), for the oligodendrocytes markers (O1 or O4), and for type-2 astrocytes (A2B5 and GFAP). However, those cells negative for GFAP (GFAP  ) and positive for nestin (Nestin þ ), were characterized as being astrocyte-restricted precursors (bipolar-shaped cells), and those GFAP þ and A2B5  as astrocytes type-1 (star-like cells). The percentage of positive cells was 8.55 7 0.64% and 92.5 7 2.5% for nestin and GFAP, respectively (Table 1). Magnification  63.5; Scale bar: 25 mm.

Please cite this article as: G. Musumeci, et al., Enhanced expression of CD31/platelet endothelial cell adhesion molecule 1 (PECAM1) correlates with hypoxia inducible factor-1 alpha..., Exp Cell Res (2015), http://dx.doi.org/10.1016/j.yexcr.2015.09.007i

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4. Discussion There is a complex interrelationship between tumor hypoxia and tumor angiogenesis. The deprivation of oxygen and nutrients lead to a reduction of the growth and viability of cells. HIF-1α helps to restore oxygen homeostasis by inducing glycolysis, erythropoiesis and angiogenesis [4]. Hypoxia in tumors develops as chronic hypoxia, resulting from long diffusion distances between tumor vessels, and/or acute hypoxia, resulting from a transient collapse of tumor vessels. Many tumors contain hypoxic microenvironment, a condition that is associated with increased patient mortality in several cancer types and resistance to treatment. Production of several angiogenic cytokines, such as fibroblast growth factor-2 (FGF-2), VEGF, transforming growth factor beta (TGF-β), tumor necrosis factor alpha (TNF-α) and interleukin-8 (IL8), is regulated by hypoxia. VEGF-mRNA expression is rapidly and reversibly induced by exposure of cultured endothelial cells to low PO2. In particular, evidences have shown that HIF-1α is a key transcriptional regulator of these molecules and is involved in tumorigenesis, activating the transcription of genes stimulating angiogenesis and invasion ability. The activity of HIF-1 is regulated by the HIF hydoxylases, a family of dioxygenases, in accordance with oxygen availability and by the interaction with various proteins, such as pVHL, p53, and p300/CBP as well as by post-translational modifications [35]. HIF-1 binds Jab-1, which inhibits the p53-dependent degradation of HIF-1 and enhances the transcriptional activity of HIF-1 and the subsequent VEGF expression under hypoxic conditions [11]. The overexpression HIF-1α caused by intratumoral hypoxia has been associated with poor prognosis [40]. Indeed HIF-1α contributes to tumor aggressiveness, invasiveness and resistance to radiotherapy and chemotherapy [15]. In vitro studies showed that in tumors that overexpress HIF-1α the growth is accelerated, owing to decreased hypoxiainduced apoptosis and increased stress-induced proliferation. Instead loss of HIF-1α reduces hypoxia-induced expression of VEGF, preventing the formation of large vessels in tumors, and impairs vascular function, resulting in hypoxic microenvironments [4]. Thus HIF-1 could be a target for new antitumoral therapies, since in preclinical studies, inhibition of HIF-1α activity has crucial effects on tumor growth [40]. HIF-1α may act as an upstream regulator of CD31 and other vascular markers in uveal melanoma [27], clear-cell renal cell carcinoma [2], gastric carcinoma [38] and neuroblastoma [34]. To our knowledge, this is the first evidence showing this correlation in GBM. In this study, we have demonstrated that an increased expression of CD31/PECAM1 is correlated to HIF-1α expression in human GBM specimens. There is now considerable evidence demonstrating that different types of tumor are able to trigger aberrant angiogenesis through the oxygen-sensing transcription factor HIF-1α. Moreover, we also established a further correlation among CD31/PECAM1 and HIF-1α and two recently identified biomarkers, namely N-cadherin and ADAM-10, of aggressiveness in the same tumors [30]. We have demonstrated that CD31 displays a high degree of correlation with ADAM, suggesting the existence of a potential relationship between the proteolytic activity in these tumors and the aberrant angiogenesis. A further but not significant positive correlation was identified between HIF-1α and ADAM-10 expression. Unfortunately, median survival of GBM from the time of diagnosis is less than a year, with less than 5% of patients surviving 5 years [19]. Standard treatment includes resection of 495% of the tumor followed by chemotherapy and radiotherapy [16]. However, despite advances in the treatment of glioma, no effective therapeutic approach is yet available. Understanding mechanisms of glioma angiogenesis provides a basis for a rational approach to the development of an anti-

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angiogenic therapy in patients with glioma. Sustained inhibition of glioma growth, reduced tumor vascular density, and/or prolonged survival has been observed over extended periods of anti-angiogenesis therapy utilizing monoclonal antibodies anti-VEGF, such as bevacizumab, and receptor-based antagonist therapy with tyrosine kinase inhibitors with anti-VEGF antibodies [1,10,39]. However, anti-angiogenic therapies in high-grade glioma present major limitations, such as invasive recurrence and little survival benefit [10].

Conflict of interest The authors declare that there are no conflict of interest.

Acknowledgments This study was partly supported by a MIUR national grant (PON 01_00110) and by funds provided by the Faculty of Medicine and Surgery to the Department of Bio-Medical Sciences, School of Medicine, University of Catania, Catania, Italy (2009BM7LJC_005). This study was supported also by a grant-in-aid from FIR 2014– 2016 (cod. 314509), University of Catania, Italy. The authors would like to thank Prof. Iain Halliday for commenting and making corrections to the paper and Mr. Pietro Asero for his technical support. The decision to submit this paper for publication was not influenced by any the funding bodies. Furthermore, the funders had no role in the design of the study, the collection and analysis of the data, the decision to publish, or the preparation of the manuscript.

Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.yexcr.2015.09.007.

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