Heparanase, a protein with enzymatic and nonenzymatic properties, contributes toward disease progression and prevention. In the current study, a fortuitous observation in transgenic mice globally overexpressing heparanase (hep-tg) was the discovery of improved glucose homeostasis. We examined the mechanisms that contribute toward this improved glucose metabolism. Heparanase overexpression was associated with enhanced glucose-stimulated insulin secretion and hyperglucagonemia, in addition to changes in islet composition and structure. Strikingly, the pancreatic islet transcriptome was greatly altered in hep-tg mice, with >2,000 genes differentially expressed versus control. The upregulated genes were enriched for diverse functions including cell death regulation, extracellular matrix component synthesis, and pancreatic hormone production. The downregulated genes were tightly linked to regulation of the cell cycle. In response to multiple low-dose streptozotocin (STZ), hep-tg animals developed less severe hyperglycemia compared with wild-type, an effect likely related to their β-cells being more functionally efficient. In animals given a single high dose of STZ causing severe and rapid development of hyperglycemia related to the catastrophic loss of insulin, hep-tg mice continued to have significantly lower blood glucose. In these mice, protective pathways were uncovered for managing hyperglycemia and include augmentation of fibroblast growth factor 21 and glucagon-like peptide 1. This study uncovers the opportunity to use properties of heparanase in management of diabetes.

Heparan sulfate proteoglycans (HSPGs), located mainly on the cell surface and in the extracellular matrix, are composed of a core protein to which one or more heparan sulfate (HS) side chains are attached (1). HSPGs function not only as structural proteins, but also as anchors for bioactive molecules, as HS is negatively charged. Highly expressed in pancreatic islets, HS binds and guides the signaling and distribution of fibroblast growth factor (FGF) family members, which regulate pancreatic endocrine cell differentiation, clustering, and development (2). It has been suggested that the presence of HSPG in the nucleus has a suppressive effect on histone acetyltransferase activity and may therefore modulate gene expression (3).

Heparanase is an endo-β-d-glucuronidase that is ubiquitously expressed in many organs, with blood and endothelial cells having the highest expression. Heparanase is encoded as a 65-kDa latent precursor (HepL) that requires proteolytic cleavage to form an active enzyme (HepA) (4). Functionally, HepA cleaves HS at d-glucuronic acid residues, an action associated with extracellular matrix disruption (5) and release of cell surface–bound molecules such as FGF (2). Aside from the function of HepA in cleaving HS, HepL can also activate numerous signaling elements, including extracellular signal–regulated kinase 1/2, phosphoinositide 3-kinase–AKT, RhoA, and Src (68). These signaling events, in addition to the entry of HepA into the nucleus to regulate histone acetylation by cleaving HS, have been suggested as mechanisms for modulating gene expression (3).

Heparanase has physiological functions in wound healing and hair growth (9). However, intensive research has also hinted toward an additional role of heparanase in both disease progression and prevention. Thus, in cancer, degradation of HS chains by the increased expression of heparanase is associated with extracellular matrix and basement membrane (BM) disruption; loss of this physical barrier facilitates tumor cell invasion (10). In the pancreas, islet-enriched HS blocks immune cell infiltration, reduces T cell–mediated inflammation (11), and supports β-cell survival and function (12). Thus, removal of HS by heparanase is critical for the initiation and progression of autoimmune (type 1) diabetes (T1D) (11). Additionally, heparanase expression is induced in many organs during diabetes. In the heart, such inappropriate expression may amplify fatty acid delivery and use. These events, if sustained, can lead to lipotoxicity and cardiovascular disease (13). In contrast to these observations, heparanase has also been shown to have beneficial effects in some diseases. For instance, overexpression of this protein is protective against adriamycin-induced kidney injury (14). In the brain, fragmentation of HS because of heparanase cleavage reduced amyloid deposition in Alzheimer’s disease (15). Similarly, amyloid formation in the islets, a hallmark of type 2 diabetes, could be ameliorated by heparanase-induced matrix metalloproteinase-9 expression (16,17). Matrix metalloproteinase-9 constitutes an endogenous islet protease that limits islet amyloid deposition and its concomitant toxic effects via degradation of the amyloid polypeptide (18). Thus, precise temporal and spatial control of heparanase may be essential for normal cell physiology.

In the current study, when monitoring the metabolism of transgenic mice that globally overexpress heparanase (hep-tg), we made the fortuitous observation that glucose homeostasis was improved in these animals. Compared with wild-type (WT) controls, these mice had lower plasma insulin and blood glucose levels; however, they exhibited higher glucagon concentrations, suggesting the presence of glucagon resistance. Given that glucagon receptor knockout (GRKO) mice exhibited increased insulin sensitivity and resistance to diabetes (19,20), we followed up these preliminary observations by examining whether heparanase overexpression could contribute toward improving glucose metabolism as well as resistance to chemically induced diabetes. Our data indicate that heparanase overexpression is associated with dramatic shifts in hormones secreted from the pancreas, reorganization of islet composition and structure, significant changes in islet gene expression, and protection from streptozotocin (STZ)–induced diabetes.

Experimental Animals

WT C57BL/6J mice aged 10–12 weeks were purchased from Charles River Laboratories. Hep-tg mice, in which a constitutive β-actin promoter drives the expression of human heparanase gene in a C57BL/6J genetic background, were a gift from I.V. All animals were housed in pathogen-free conditions on a 12-h light/dark cycle. Hep-tg mice were previously crossed for 10 generations with C57BL/6J mice to produce a stable homozygous background. Male homozygous hep-tg mice aged 12–15 weeks were used for all experiments. For confirmation of genotype, genomic DNA was prepared from 21-day-old animal ear-punched tissue and analyzed by PCR (Fig. 1A) as previously detailed (9). All experiments were approved by the University of British Columbia Animal Care Committee and performed in accordance with the Canadian Council on Animal Care Guidelines.

Figure 1

Heparanase overexpression improves glucose homeostasis. A: PCR amplification of DNA extracted from WT and hep-tg (TG) mice ear tissue. L19 is used as an internal control. B and C: Following a 6-h fast, plasma insulin and blood glucose levels were measured in WT and TG mice. n = 9 to 10. *P < 0.05 vs. WT. D: Intraperitoneal administration of insulin (2 μg/kg body weight) to 6-h–fasted mice, followed by skeletal muscle isolation for Western blot. n = 3. *P < 0.05 vs. control; #P < 0.05 vs. WT insulin. E and F: Following an overnight fast (16 h), WT and TG mice were administered an oral glucose (2 g/kg) gavage. At the indicated times, blood glucose and insulin were measured. n = 4 to 5. *P < 0.05 vs. WT. G: Isolated islets (10) from the different groups were used to extract insulin with acid-ethanol, and the insulin content was measured with ELISA (WT, 2.38 ± 0.23 ng/mL; hep-tg, 3.08 ± 1.04 ng/mL; P = 0.218). Different islets from the same animals were exposed to 3 and 16.7 mmol/L glucose, respectively, and insulin secretion determined. n = 3. *P < 0.05.

Figure 1

Heparanase overexpression improves glucose homeostasis. A: PCR amplification of DNA extracted from WT and hep-tg (TG) mice ear tissue. L19 is used as an internal control. B and C: Following a 6-h fast, plasma insulin and blood glucose levels were measured in WT and TG mice. n = 9 to 10. *P < 0.05 vs. WT. D: Intraperitoneal administration of insulin (2 μg/kg body weight) to 6-h–fasted mice, followed by skeletal muscle isolation for Western blot. n = 3. *P < 0.05 vs. control; #P < 0.05 vs. WT insulin. E and F: Following an overnight fast (16 h), WT and TG mice were administered an oral glucose (2 g/kg) gavage. At the indicated times, blood glucose and insulin were measured. n = 4 to 5. *P < 0.05 vs. WT. G: Isolated islets (10) from the different groups were used to extract insulin with acid-ethanol, and the insulin content was measured with ELISA (WT, 2.38 ± 0.23 ng/mL; hep-tg, 3.08 ± 1.04 ng/mL; P = 0.218). Different islets from the same animals were exposed to 3 and 16.7 mmol/L glucose, respectively, and insulin secretion determined. n = 3. *P < 0.05.

Metabolic Assessments and Treatment of Animals

For measurement of basal blood glucose and plasma hormones, animals were fasted for 6 or 16 h and blood sampled from the tail vein. Blood glucose was measured using an Accu-Chek glucose monitor (Roche, Basel, Switzerland). Blood was also collected using a heparinized microtube (Thermo Fisher Scientific, Waltham, MA) and centrifuged immediately for separation of plasma. Circulating hormones in the plasma were measured using the following kits: mouse insulin (ALPCO, Salem, NH), glucagon and GLP-1 (Meso Scale Discovery, Rockville, MD), and FGF21 (R&D Systems, Minneapolis, MN). For the oral glucose tolerance test (OGTT) or intraperitoneal (i.p.) glucose tolerance test (IPGTT), animals were fasted overnight (16 h), 2 g/kg glucose was administered orally or i.p., and blood glucose was measured at the indicated times. A different cohort of animals was treated in the same manner for the assessment of insulin following the OGTT. To perform the glucagon challenge, glucagon (1 μg/kg body weight) was administered i.p. into 6- or 16-h–fasted mice and blood glucose measured at the indicated times. The insulin (0.75 units/kg body weight) and L-arginine (2 g/kg, i.p.) challenges were performed the same way in 6-h–fasted mice. In addition to glucose measurement following injection of L-arginine, plasma insulin and glucagon were also measured at the indicated times. For evaluation of skeletal muscle sensitivity to insulin, mice were fasted for 6 h prior to an i.p. injection of 2 μg/kg insulin. At 10 min post–insulin injection, skeletal muscle (soleus and gastrocnemius) was isolated for Western blot determination of phospho- and total Akt (Cell Signaling Technology, Danvers, MA), with β-actin (Santa Cruz Biotechnology, Dallas, TX) used as an internal control.

Diabetes Induction

STZ is a β-cell–selective toxin. Using STZ, we used two different strategies to induce diabetes. With the first protocol, we injected multiple low doses of STZ (MLD-STZ; 50 mg/kg i.p.) for 5 consecutive days. This procedure induces gradual β-cell death, followed by an immune system response (21). Body weight and plasma glucose levels were monitored daily after the first STZ injection. Metabolic assessment and organ isolation were performed 1 week after the last STZ injection, following confirmation of hyperglycemia. We also used a single high dose of STZ (SHD-STZ; 200 mg/kg i.p.), which is directly cytotoxic to β-cells, resulting in robust hyperglycemia within 24–48 h (22).

Staining and Quantification

The pancreas from normal or MLD-STZ mice was perfused with PBS, harvested, fixed in 4% paraformaldehyde, and stored in 70% ethanol before paraffin embedding. All paraffin sections (5-μm thickness) were processed by Wax-it Histology laboratories (Vancouver, British Columbia, Canada). Immunofluorescence staining and quantification of insulin (Cell Signaling Technology), glucagon (Sigma-Aldrich, St. Louis, MO), GLUT2 (Chemicon International, Temecula, CA), and synaptophysin (Novus Biologicals, Littleton, CO) were performed as previously described (23). Alcian blue (0.65 mol/L MgCl2 [pH 5.8]; Sigma-Aldrich) staining and imaging was used to visualize HS.

Western Blot

Western blot was done as described previously (24). Heparanase (Abcam, Cambridge, U.K.) and HS (Santa Cruz Biotechnology) expression in the pancreas was determined using the appropriate antibodies.

Islet Isolation

Pancreatic islets were isolated using collagenase as described previously (12,25). Briefly, the pancreas was perfused with collagenase through the pancreatic duct. Additional collagenase digestion was performed in a water bath. Following digestion, the tube containing the tissue sample was shaken vigorously. Individual islets were handpicked under a bright-field microscope. Islets were cultured for 3 h (37°C, 5% CO2) in RPMI 1640 medium (Invitrogen, Carlsbad, CA) with 5 mmol/L glucose (Sigma-Aldrich), 100 units/mL penicillin, 100 μg/mL streptomycin (Invitrogen), and 10% FBS (Invitrogen). For RNA sequencing, 100 islets were selected, rinsed with PBS, and snap frozen for later isolation of RNA. For glucose-induced insulin secretion, 10 islets were rinsed three times with PBS to remove glucose and insulin and then transferred to RPMI 1640 medium with either 3 or 16.7 mmol/L glucose for 15 min, followed by medium collection and insulin determination using ELISA. The total insulin content in islets was determined following acid-ethanol extraction.

RNA Sequencing and Analysis

RNA from five hep-tg and five WT mice was isolated using an RNeasy purification kit (Qiagen, Hilden, Germany). Sequencing libraries were prepared from 400 ng total RNA using the TruSeq Stranded mRNA Sample Preparation kit according to the manufacturer’s instructions (Illumina, San Diego, CA). Samples were checked for quality using a Bioanalyzer (Agilent Technologies) and quantified using a Qubit fluorometer (Thermo Fisher Scientific). Libraries were then multiplexed and sequenced over one rapid run lane on the HiSeq2500 (Illumina), collecting 89 million 100-bp paired-end reads. Kallisto version 0.42.4 was first used to build an index file for the mouse reference transcriptome GRCm38 as downloaded from the Ensembl web site (http://www.ensembl.org). The sequence reads for each sample were then quantified with the quant function of Kallisto. In-house Perl scripts were used to sum the read counts at the transcript level for each gene and create a matrix comprising the read counts for all of the genes for all of the samples. Differential expression analysis was then performed on the data from that matrix using the R package DESeq2 (26). Each sample was assessed using the quality-control software RSeQC version 2.6.3 (27) and the PtR script from the trinity suite (28). One potential outlier was detected when clustering the samples and therefore removed for the differential expression analysis. RNA sequencing transcriptomic data were analyzed using Panther and Database for Annotation, Visualization and Integrated Discovery (DAVID). Network analysis was conducted using STRING.

Statistical Analysis

Statistics were performed using Sigma Plot (Systat Software Inc., Chicago, IL). For all analyses, the Student t test or one-way ANOVA was used to determine differences among group mean values. Values are presented as means ± SEM with individual data points. A P value <0.05 was considered statistically significant.

Hep-tg Mice Have Improved Glucose Homeostasis

At 3 months of age, hep-tg mice had similar body weights compared with WT (hep-tg, 22.03 ± 1.11 g; WT, 22.11 ± 1.08 g). However, the determination of circulating plasma insulin in hep-tg animals after a 6-h fast revealed lower levels compared with WT (Fig. 1B). Interestingly, the transgenic animals also demonstrated reduced basal blood glucose (Fig. 1C), suggesting higher insulin efficiency in these mice. This was tested by administering a bolus dose of insulin and measuring Akt activation in skeletal muscle. Samples of skeletal muscle from hep-tg mice showed an enhanced insulin response (Fig. 1D). To pursue this observation, we performed an OGTT after an overnight fast. Unlike in the case of an acute fast, prolonged fasting eliminated the difference in blood glucose between the two genotypes (Fig. 1E). In addition, although hep-tg mice tended to clear glucose faster, this improvement was not statistically significant (Fig. 1E), suggesting that the improvement in insulin sensitivity observed under basal conditions is not readily apparent during an OGTT. Following an insulin tolerance test, we were also unable to detect any difference in blood glucose lowering between the two groups up to 30 min after insulin injection. Interestingly, after 30 min of insulin, we start to see a separation (recovery of glucose levels) between the WT and hep-tg mice (Supplementary Fig. 1). Unexpectedly, in response to the glucose challenge, insulin secretion in hep-tg animals was almost twofold higher than in WT (Fig. 1F). In addition, when islets from WT and hep-tg mice were isolated and exposed to high glucose, hep-tg islets were capable of releasing greater amounts of insulin compared with WT (Fig. 1G). Although hep-tg islets appeared to contain slightly more insulin compared with WT, this difference was not statistically significant (Supplementary Fig. 2). Similarly, as neither Ins 1 nor Ins 2 expression demonstrated any significant difference between the two strains (data not shown), our data suggest that heparanase overexpression influences the secretory process of insulin rather than its synthesis.

Heparanase Overexpression Induces Glucagon Resistance and Changes in Pancreatic Islet Structure

Intriguingly, hep-tg mice showed an augmentation in circulating basal glucagon levels (Fig. 2A and Supplementary Fig. 3). However, these mice demonstrated resistance when given a glucagon challenge after 6 (Supplementary Fig. 3) or 16 h (Fig. 2B) of fasting. The glucagon resistance in hep-tg mice was evident in the absence of any change in the glucagon receptor in the liver (Supplementary Fig. 4). In response to L-arginine, which drives islet hormone secretion independent of glucose sensing, hep-tg mice showed higher glucagon and lower insulin secretion, effects that were reflected in a higher glucose excursion in these animals (Fig. 2C). To determine the basis for this observed hyperglucagonemia, we quantified pancreatic α-cells, and their ratio to β-cells, using fluorescent staining. Expressed as glucagon-positive (WT, 0.000465 ± 0.00026; hep-tg, 0.000764 ± 0.000318; P = 0.433) and insulin-positive (WT, 0.004056 ± 0.000991; hep-tg, 0.004608 ± 0.001674; P = 0.056) areas individually (signal-positive area versus total area of the section to represent the α- and β-cell number in the pancreas), there was no statistical difference between WT and hep-tg animals in the number of insulin- or glucagon-positive cells. However, when the data were expressed as a ratio of α/β-cells, the hep-tg islets demonstrated α-cells that were more abundant. Additionally, unlike WT islets, in which α-cells are mostly found in the periphery and β-cells in the core, hep-tg islets contained α-cells that were randomly distributed (Fig. 2D). Islets in hep-tg mice exhibit similar average size and size distribution (Fig. 2E) and no difference in their number compared with WT (Supplementary Fig. 5). Overall, heparanase overexpression was associated with dramatic shifts in hormones secreted from the pancreas, in addition to changes in islet composition and structure.

Figure 2

Glucagon resistance and altered islet cytoarchitecture in heparanase-overexpressing mice. A: Plasma glucagon levels in WT and hep-tg (TG) mice were determined after a 16-h fast. n = 4 to 5. *P < 0.05 vs. WT. B: For the glucagon challenge, 16-h–fasted mice were administered glucagon (1 μg/kg), and blood glucose was measured at the indicated times. n = 5. *P < 0.05 vs. WT. C: In 6-h–fasted mice, 2 g/kg L-arginine was administered i.p. and plasma glucagon, insulin, and blood glucose (fold change in glucose was calculated by normalizing to the corresponding value at t = 0) was measured at the indicated times. n = 5. *P < 0.05 vs. WT. D: Higher magnification of insulin- and glucagon-positive cells in pancreas isolated from the two groups of animals using immunofluorescence staining, together with quantification of the α/β-cell ratio. n = 3. *P < 0.05 vs. WT. E: Whole pancreas sections were stained for insulin (red) and glucagon (green) and scanned, and islets were counted and quantified by size.

Figure 2

Glucagon resistance and altered islet cytoarchitecture in heparanase-overexpressing mice. A: Plasma glucagon levels in WT and hep-tg (TG) mice were determined after a 16-h fast. n = 4 to 5. *P < 0.05 vs. WT. B: For the glucagon challenge, 16-h–fasted mice were administered glucagon (1 μg/kg), and blood glucose was measured at the indicated times. n = 5. *P < 0.05 vs. WT. C: In 6-h–fasted mice, 2 g/kg L-arginine was administered i.p. and plasma glucagon, insulin, and blood glucose (fold change in glucose was calculated by normalizing to the corresponding value at t = 0) was measured at the indicated times. n = 5. *P < 0.05 vs. WT. D: Higher magnification of insulin- and glucagon-positive cells in pancreas isolated from the two groups of animals using immunofluorescence staining, together with quantification of the α/β-cell ratio. n = 3. *P < 0.05 vs. WT. E: Whole pancreas sections were stained for insulin (red) and glucagon (green) and scanned, and islets were counted and quantified by size.

Heparanase Overexpression Greatly Alters the Pancreatic Islet Transcriptome

Entry of heparanase into the nucleus to regulate histone acetylation has been put forth as a mechanism to modulate transcription (3). Given the impact of heparanase overexpression on insulin and glucagon, we sought to characterize the hep-tg islet transcriptome using RNA-sequencing (Supplementary Table 1). As expected, heparanase was the most profoundly altered mRNA in the islet transcriptome, exhibiting a >100-fold change (Fig. 3B). This was mirrored by an equally robust increase in heparanase protein expression (Fig. 3B, inset). Strikingly, after correction for multiple testing, >2,000 genes were significantly differentially expressed with P < 0.05. Of these, 1,176 were upregulated, and 985 were downregulated (Fig. 3A, inset). From the mRNAs that increased above a cutoff (more than twofold; P < 0.001), we identified 350 genes enriched in multiple cellular processes, including in development (e.g., Crlf1 and Ifrd1) (29), metabolism (e.g., Acacb and Ppargc1a) (30), and cell death regulation (e.g., Npas4, Igf1, and P2rx1) (Fig. 3A) (31,32). Of note, glucagon (Gcg) expression increased (Fig. 3B) and corresponded to the high plasma glucagon observed in hep-tg mice. Among the 112 genes that decreased (more than twofold; P < 0.001), the most compelling effect was observed for genes related to the cell cycle (e.g., Cdc20 and Ccnb) (Fig. 3A). In addition, glucagon receptor (Gcgr) expression was also decreased (P = 0.0004) (Fig. 3B). Combining these data with a protein–protein interaction network model, we identified two functional networks that were upregulated relevant to the current study (Fig. 4, circles): one associated with hormone secretion (e.g., Ppy and Pyy) and the other with extracellular structure (e.g., Sdc1 [that encodes for syndecan 1] and Hs3st3b1 [that encodes for HS–glucosamine 3-sulfotransferase 3B1]) (Figs. 3B and 4). The amplification of pancreatic HS that was observed in hep-tg mice (Fig. 3C) could be attributed, at least in part, to the increase in Sdc1 and Hs3st3b1. Among the downregulated genes, a highly connected network of genes related to the cell cycle function was recognized (Fig. 4, box). Altogether, these data suggest that its ability to modulate gene expression is consistent with the role of heparanase as a potent regulator of islet structure and function.

Figure 3

Islet transcriptome changes dramatically in hep-tg mice. A: Islet RNA from WT and hep-tg (TG) mice was sequenced, and the (P < 0.001) upregulated (red) and downregulated (green) genes were categorized based on the functions. Bar represents the enrichment of the genes in particular category over the total genes of input. B: Representative genes in extracellular matrix, signaling, and cell cycle are shown. Heparanase gene was used as positive control of the entire RNA sequencing, together with islet protein detection as inset. C: Pancreas staining for HS using Alcian blue (pH 5.8, 0.65 mol/L MgCl2) and its quantification using Western blot. n = 3. *P < 0.05 vs. WT.

Figure 3

Islet transcriptome changes dramatically in hep-tg mice. A: Islet RNA from WT and hep-tg (TG) mice was sequenced, and the (P < 0.001) upregulated (red) and downregulated (green) genes were categorized based on the functions. Bar represents the enrichment of the genes in particular category over the total genes of input. B: Representative genes in extracellular matrix, signaling, and cell cycle are shown. Heparanase gene was used as positive control of the entire RNA sequencing, together with islet protein detection as inset. C: Pancreas staining for HS using Alcian blue (pH 5.8, 0.65 mol/L MgCl2) and its quantification using Western blot. n = 3. *P < 0.05 vs. WT.

Figure 4

Association network of genes that were significantly different between WT and hep-tg mice. Analysis of a protein–protein interaction network assembled from RNA sequencing data. The blue square depicts the entire downregulated network that is related to cell cycle. The red circles encompass both the hormone-associated network and the extracellular elements network. Lines represent associations based on differential expression evidence.

Figure 4

Association network of genes that were significantly different between WT and hep-tg mice. Analysis of a protein–protein interaction network assembled from RNA sequencing data. The blue square depicts the entire downregulated network that is related to cell cycle. The red circles encompass both the hormone-associated network and the extracellular elements network. Lines represent associations based on differential expression evidence.

Hep-tg Mice Exhibit Resistance to MLD-STZ–Induced Hyperglycemia

As hep-tg islets are enriched in HS, which is important for β-cell survival (12), we attempted to chemically induce diabetes in these mice. Interestingly, although WT animals showed robust hyperglycemia within 1 week of STZ injection, hep-tg mice failed to present with plasma glucose levels comparable to WT (Fig. 5A). Measurement of plasma insulin provided one explanation for this observation. STZ caused a precipitous drop of plasma insulin in WT animals, an effect that was absent in hep-tg mice (Fig. 5B). Prolonging the duration of the study did not change the results: hep-tg mice remained resistant to STZ-induced hyperglycemia for up to 8 weeks following injection (Supplementary Fig. 6). This resistance to STZ was likely not a result of any difference in expression of pancreatic GLUT2 (Supplementary Fig. 7), the transporter required for STZ uptake. To establish whether the failure to develop STZ-induced hyperglycemia was a consequence of β-cell preservation, we quantified β-cell mass. Surprisingly, upon injection of STZ, both the WT and hep-tg mice displayed an identical loss of insulin-positive cells (Fig. 5C). This implies that the resistance to experimental diabetes in hep-tg mice is not a consequence of β-cell survival, consistent with observations seen in GRKO mice, which do not develop T1D when injected with STZ (19). Given our observation that hep-tg mice secrete more insulin in response to an OGTT (Fig. 1F), it is possible that the islets, which survived STZ toxicity in hep-tg diabetic mice, have a greater insulin secretory capacity. In this regard, hep-tg mice injected with STZ were still, albeit in limited capacity, able to secrete insulin in response to an IPGTT (Fig. 5D). Taken together, our data suggest that the protective effects of heparanase against STZ-induced diabetes is unlikely to be a consequence of HS-mediated β-cell survival, but could be related to the ability of any residual β-cells in these animals to continue their secretion of insulin.

Figure 5

Hep-tg mice are resistant to MLD-STZ–induced diabetes. A and B: To induce T1D, WT and hep-tg (TG) mice were administered 50 mg/kg STZ for 5 consecutive days. Seven days after the last STZ injection and following a 6-h fast, tail vein blood was used for glucose and plasma insulin determination. n = 5–10. *P < 0.05. C: Pancreas from STZ-injected mice was isolated and immune stained for insulin (red) and glucagon (green), and insulin-positive cells were quantified in the different groups. n = 3. *P < 0.05. vs. control (Con). D: Following an IPGTT, plasma insulin in STZ-injected WT and hep-tg mice was measured over the indicated times. The data are expressed as a fold change normalized to the corresponding values at t = 0 min for each animal within the two groups. n = 3–5. *P < 0.05 vs. WT.

Figure 5

Hep-tg mice are resistant to MLD-STZ–induced diabetes. A and B: To induce T1D, WT and hep-tg (TG) mice were administered 50 mg/kg STZ for 5 consecutive days. Seven days after the last STZ injection and following a 6-h fast, tail vein blood was used for glucose and plasma insulin determination. n = 5–10. *P < 0.05. C: Pancreas from STZ-injected mice was isolated and immune stained for insulin (red) and glucagon (green), and insulin-positive cells were quantified in the different groups. n = 3. *P < 0.05. vs. control (Con). D: Following an IPGTT, plasma insulin in STZ-injected WT and hep-tg mice was measured over the indicated times. The data are expressed as a fold change normalized to the corresponding values at t = 0 min for each animal within the two groups. n = 3–5. *P < 0.05 vs. WT.

Severity of Diabetes Remains Disparate Between WT and Hep-tg Mice Injected With SHD-STZ

MLD-STZ induces β-cell death by activating immune mechanisms (21). Hence, we also tested the response of hep-tg mice to SHD-STZ, which produces severe diabetes by direct β-cell toxicity via DNA alkylation (22). In contrast to our observation with MLD-STZ, both WT and hep-tg mice injected with 200 mg/kg STZ (SHD) exhibited a significant reduction in plasma insulin levels (Fig. 6B). In agreement with the loss of insulin, WT diabetic mice demonstrated sustained hyperglycemia (Fig. 6A). Significantly, the values from day 3 onwards for these mice were beyond the upper limit of detection (33.3 mmol/L) of the glucometer, suggesting that the actual blood glucose concentrations were likely higher. Although high-dose STZ was competent to lower insulin and induce diabetes in hep-tg mice, the magnitude of hyperglycemia was lower than that seen in WT animals (Fig. 6A), suggesting the contribution of an insulin mimetic factor. FGF21 has significant beneficial effects on glucose homeostasis (33). Measurement of FGF21 plasma concentration indicated that hep-tg mice had higher concentrations compared with WT (Fig. 6C). Moreover, although STZ-induced diabetes caused a significant drop in FGF21 levels in WT mice, its levels in hep-tg mice were strikingly amplified by threefold (Fig. 6C) and likely related to its increased hepatic production (Supplementary Fig. 8). Another hormone that has glucose-lowering effects independent of insulin is GLP-1 (34). In response to high-dose STZ, GLP-1 trended in the opposite direction between these two strains (Fig. 6D). Thus, in hep-tg mice, driving circulating insulin concentrations down to very low levels uncovers novel protective pathways for the management of hyperglycemia.

Figure 6

SHD-STZ in hep-tg mice uncovers protective responses to manage hyperglycemia. A: SHD-STZ (200 mg/kg) was administered i.p. and glucose levels monitored daily over 5 days. n = 4–8. *P < 0.05. BD: One week after injection of SHD-STZ, insulin, FGF21, and GLP-1 levels from WT and hep-tg (TG) mice were determined. n = 4–8. *P < 0.05.

Figure 6

SHD-STZ in hep-tg mice uncovers protective responses to manage hyperglycemia. A: SHD-STZ (200 mg/kg) was administered i.p. and glucose levels monitored daily over 5 days. n = 4–8. *P < 0.05. BD: One week after injection of SHD-STZ, insulin, FGF21, and GLP-1 levels from WT and hep-tg (TG) mice were determined. n = 4–8. *P < 0.05.

Homozygous transgenic mice overexpressing human heparanase globally are fertile and have a normal life span (9). In addition, physiological functions associated with heparanase in these mice include roles in embryonic implantation, food consumption, tissue remodeling, and vascularization (9). In the current study, an unexpected feature of these animals was our discovery of improved glucose homeostasis, but resistance to glucagon. Strikingly, compared with controls, hep-tg mice manifested significant changes in islet gene expression of >2,000 genes. These mice also demonstrated resistance to chemically induced diabetes. Our data suggest a novel role for heparanase in mechanisms that serve to correct hyperglycemia.

In hep-tg mice, both basal insulin and glucose levels were lower than in WT following a 6-h fast, suggesting superior insulin sensitivity in these animals. This idea was reinforced by an enhanced insulin response to activation of skeletal muscle Akt in this study. Supporting these observations is that, in myeloma cells, insulin receptor is the predominant receptor tyrosine kinase activated by heparanase (6). The lower glucose concentration was evident in the presence of high glucagon levels, suggesting a deficit in glucagon action. Interestingly, an insulin tolerance test used to evaluate insulin efficiency was unable to detect any difference in blood glucose lowering between the two groups. Moreover, the traditional OGTT was also unable to confirm a higher rate of glucose disposal in hep-tg mice. We reasoned that the overnight fast prior to performing the OGTT could explain this inconsistency. Following fasting, hypersensitivity of the liver to glucagon accounts for a multifold increase in hepatic glucose production (34). Should this happen, even marginally, in hep-tg mice that have higher basal glucagon levels, the advantage of augmented insulin sensitivity in these animals would be dampened, resulting in a similar glucose clearance compared with WT. Remarkably, in hep-tg mice, the OGTT elicited higher insulin release, whereas isolated islets from these animals had a more robust secretion of insulin in response to glucose, even with islet insulin content and gene expression remaining unchanged. Our data suggest that although heparanase appears to enhance insulin signaling, whole-body tests to determine insulin sensitivity were unable to confirm this, likely because of the overriding influence of an insulin counterregulatory hormone such as glucagon in the hep-tg mice.

In GRKO mice, a prolonged deficiency in glucagon receptor signaling activates α-cell proliferation and leads to a compensatory elevation in glucagon production (35). We were surprised to observe that these characteristics in GRKO mice were strikingly similar to features seen in hep-tg animals, which did not respond to a glucagon challenge as well as WT mice. More importantly, hep-tg islets presented an architecture that is conducive to hypersecretion of glucagon, under basal conditions, and also subsequent to injection of arginine. In these mice, α-cells lost their peripheral mantle-like localization and were distributed randomly throughout the islets. In addition, the α/β-cell ratio was higher in hep-tg mice. These changes in α-cells were evident even though islet size and size distribution remained unaffected. Currently, it is unclear whether these alterations in α-cell morphology are consequences of glucagon resistance or of disrupted pancreatic islet development through the action of heparanase on HS.

Measurement of HS in the pancreas produced an unanticipated result; rather than depleting HS, the hep-tg pancreas displayed the opposing phenotype, with increased expression of HS, and the gene (Hs3st3b1) that encodes for its biosynthetic enzyme, 3-O-sulfotransferase, being dominant features. A similar observation has also been made in the hep-tg liver, in which the authors described the accumulation of “heparin-like” HS degradation products, both within and between cells, resulting in an accelerated biosynthesis of HS (36). It follows that as in the liver, pancreatic heparanase processes HS into smaller heparin-like oligosaccharides. Regardless of whether a result of its enzymatic activities or its nontraditional signaling activities, overexpression of heparanase produced a dramatic alteration in the islet transcriptome. Among the clusters of genes that were increased, of particular interest were genes that regulate cell death, synthesize extracellular matrix components, and produce pancreatic hormones. Related to cell death, this was not unusual, as cancer cells use the properties of heparanase to induce gene expression and cell survival (37). The impact on the extracellular matrix is especially meaningful, as components like collagen and laminin have roles in islet cell differentiation, proliferation, and hormone secretion (38). Finally, peptide hormones like somatostatin and pancreatic polypeptide hormone are known to influence pancreatic islet function in a paracrine manner (39,40). Unlike the upregulated genes that were enriched for diverse functions, the downregulated genes formed a coherent functional group, including those tightly linked to the cell cycle. Whether these changes in expression create an energy-sparing environment that would be conducive to a higher level of hormone production, as recently reported (41), is certainly consistent with our observations and deserving of further investigation. Collectively, our data provide support for the notion that heparanase in the pancreas is particularly beneficial, reinforcing it against the effects of exogenous stress.

MLD-STZ mimics T1D by stimulating β-cell apoptosis through the recruitment of immune cells (21). Given the role that HS plays in modulating the innate immune response by effecting immune cell adhesion and cytokine and chemokine binding and providing a physical barrier against leukocyte infiltration (42), an increase in HS as seen in hep-tg mice could be potentially beneficial. This, when added to the genomic signature in these mice that is protective against cell death, would anticipate a resistance to MLD-STZ β-cell cytotoxicity. Indeed, our results, for the first time, demonstrate that hep-tg animals developed less severe hyperglycemia compared with WT and that this was associated with an almost unchanged circulating insulin concentration. Inexplicably, the preserved plasma insulin in these animals was not a consequence of higher β-cell mass, as quantification of these cells using immunostaining indicated that hep-tg β-cells were destroyed to an equal extent compared with WT. It is possible that, of the β-cells that survived STZ toxicity in both groups, an enhanced insulin secretory capacity in hep-tg animals could explain this anomaly. In support, hep-tg diabetic animals can still increase insulin secretion in response to a glucose challenge, an effect that is lost in WT diabetic mice. Our data suggest that heparanase produces β-cells that are more functionally efficient, an effect likely related to an elevation of 3-O-sulfotransferases and accumulation of HS in these islets.

STZ in high doses induces diabetes by a mechanism different from MLD-STZ; it directly destroys β-cells by alkylating DNA (22). Additionally, as there is a comparatively more severe and rapid development of hyperglycemia related to a catastrophic loss of insulin, we tested whether heparanase would continue to correct hyperglycemia in this model. Despite the identical low levels of residual circulating insulin in both diabetic groups, hep-tg mice continued to have significantly lower blood glucose. In GRKO mice, FGF21 and GLP-1 have been suggested to be the hormones responsible for glucose clearance in the absence of insulin (43). This was also true in the hep-tg diabetic mouse. In these animals, regardless of their basal concentrations, SHD-STZ caused an augmentation of both FGF21 and GLP-1, effects that can contribute to their lower glucose levels. Altogether, the results indicate that, with the onset of hyperglycemia, additional glucose-lowering mechanisms are triggered in hep-tg mice.

It has been proposed that HS in pancreatic islet BM functions as an obstruction against leukocyte infiltration, in addition to protecting the β-cell against reactive oxygen species–induced cell death (44). Thus, in the NOD mouse, augmented production of active heparanase by immune cells permits destruction of islet BM HS, entry of leukocytes, and degradation of intracellular HS. As the heparanase inhibitor PI-88 preserved intraislet HS and protected NOD mice from T1D, the authors concluded that heparanase inhibition is useful against T1D progression (12). Contrasting results were observed in NOD mice injected with exogenous heparanase, which ameliorated the occurrence of diabetes (45). Unlike the NOD mice or metastatic cancer cells (46), in which the overproduction of active heparanase is responsible for disease development, our model is one in which, in a disease-free background, latent heparanase is overexpressed, with an associated amplification of islet HS. Thus, although active heparanase has been considered a pathogenic marker, our study has discovered multiple novel properties of latent heparanase related to the control of glycaemia. Overexpression of this protein caused glucose lowering, potentiation of insulin secretion, HS induction, prodigious changes in islet gene expression, and protection against chemically induced diabetes. This study unlocks the possibility of using these properties of heparanase in the management of diabetes.

Funding. This work was supported by an operating grant from the Canadian Institutes of Health Research (CIHR-MOP-133547 to B.R.). D.Z. and A.P.-L.C. are the recipients of Doctoral Student Research Awards from the Canadian Diabetes Association.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. D.Z. performed most of the experiments and with B.R. generated the hypothesis, designed the study, performed the data analysis, and wrote the manuscript. F.W., N.L., A.P.-L.C., A.W., J.J., D.B., A.A., X.H., F.T., and B.H. contributed in part to some of the experiments performed. S.F., S.S., and C.N. performed RNA sequencing and its analysis. T.P., I.V., J.D.J., and T.J.K. contributed to the discussion and manuscript editing. B.R. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

1.
Sarrazin
S
,
Lamanna
WC
,
Esko
JD
.
Heparan sulfate proteoglycans
.
Cold Spring Harb Perspect Biol
2011
;
3
:
a004952
[PubMed]
2.
Gittes
GK
.
Developmental biology of the pancreas: a comprehensive review
.
Dev Biol
2009
;
326
:
4
35
[PubMed]
3.
Purushothaman
A
,
Hurst
DR
,
Pisano
C
,
Mizumoto
S
,
Sugahara
K
,
Sanderson
RD
.
Heparanase-mediated loss of nuclear syndecan-1 enhances histone acetyltransferase (HAT) activity to promote expression of genes that drive an aggressive tumor phenotype
.
J Biol Chem
2011
;
286
:
30377
30383
[PubMed]
4.
Wu
L
,
Viola
CM
,
Brzozowski
AM
,
Davies
GJ
.
Structural characterization of human heparanase reveals insights into substrate recognition
.
Nat Struct Mol Biol
2015
;
22
:
1016
1022
[PubMed]
5.
Vlodavsky
I
,
Ilan
N
,
Naggi
A
,
Casu
B
.
Heparanase: structure, biological functions, and inhibition by heparin-derived mimetics of heparan sulfate
.
Curr Pharm Des
2007
;
13
:
2057
2073
[PubMed]
6.
Purushothaman
A
,
Babitz
SK
,
Sanderson
RD
.
Heparanase enhances the insulin receptor signaling pathway to activate extracellular signal-regulated kinase in multiple myeloma
.
J Biol Chem
2012
;
287
:
41288
41296
[PubMed]
7.
Riaz
A
,
Ilan
N
,
Vlodavsky
I
,
Li
JP
,
Johansson
S
.
Characterization of heparanase-induced phosphatidylinositol 3-kinase-AKT activation and its integrin dependence
.
J Biol Chem
2013
;
288
:
12366
12375
[PubMed]
8.
Zetser
A
,
Bashenko
Y
,
Edovitsky
E
,
Levy-Adam
F
,
Vlodavsky
I
,
Ilan
N
.
Heparanase induces vascular endothelial growth factor expression: correlation with p38 phosphorylation levels and Src activation
.
Cancer Res
2006
;
66
:
1455
1463
[PubMed]
9.
Zcharia
E
,
Metzger
S
,
Chajek-Shaul
T
, et al
.
Transgenic expression of mammalian heparanase uncovers physiological functions of heparan sulfate in tissue morphogenesis, vascularization, and feeding behavior
.
FASEB J
2004
;
18
:
252
263
[PubMed]
10.
Arvatz
G
,
Weissmann
M
,
Ilan
N
,
Vlodavsky
I
.
Heparanase and cancer progression: new directions, new promises
.
Hum Vaccin Immunother
2016
;
12
:
2253
2256
[PubMed]
11.
Bogdani
M
,
Korpos
E
,
Simeonovic
CJ
,
Parish
CR
,
Sorokin
L
,
Wight
TN
.
Extracellular matrix components in the pathogenesis of type 1 diabetes
.
Curr Diab Rep
2014
;
14
:
552
[PubMed]
12.
Ziolkowski
AF
,
Popp
SK
,
Freeman
C
,
Parish
CR
,
Simeonovic
CJ
.
Heparan sulfate and heparanase play key roles in mouse β cell survival and autoimmune diabetes
.
J Clin Invest
2012
;
122
:
132
141
[PubMed]
13.
Wan
A
,
Rodrigues
B
.
Endothelial cell-cardiomyocyte crosstalk in diabetic cardiomyopathy
.
Cardiovasc Res
2016
;
111
:
172
183
[PubMed]
14.
Assady
S
,
Alter
J
,
Axelman
E
, et al
.
Nephroprotective effect of heparanase in experimental nephrotic syndrome
.
PLoS One
2015
;
10
:
e0119610
[PubMed]
15.
Jendresen
CB
,
Cui
H
,
Zhang
X
,
Vlodavsky
I
,
Nilsson
LN
,
Li
JP
.
Overexpression of heparanase lowers the amyloid burden in amyloid-β precursor protein transgenic mice
.
J Biol Chem
2015
;
290
:
5053
5064
[PubMed]
16.
Purushothaman
A
,
Chen
L
,
Yang
Y
,
Sanderson
RD
.
Heparanase stimulation of protease expression implicates it as a master regulator of the aggressive tumor phenotype in myeloma
.
J Biol Chem
2008
;
283
:
32628
32636
[PubMed]
17.
Aston-Mourney
K
,
Zraika
S
,
Udayasankar
J
, et al
.
Matrix metalloproteinase-9 reduces islet amyloid formation by degrading islet amyloid polypeptide
.
J Biol Chem
2013
;
288
:
3553
3559
[PubMed]
18.
Meier
DT
,
Tu
LH
,
Zraika
S
, et al
.
Matrix Metalloproteinase-9 Protects Islets from Amyloid-induced Toxicity
.
J Biol Chem
2015
;
290
:
30475
30485
[PubMed]
19.
Sørensen
H
,
Winzell
MS
,
Brand
CL
, et al
.
Glucagon receptor knockout mice display increased insulin sensitivity and impaired beta-cell function
.
Diabetes
2006
;
55
:
3463
3469
[PubMed]
20.
Conarello
SL
,
Jiang
G
,
Mu
J
, et al
.
Glucagon receptor knockout mice are resistant to diet-induced obesity and streptozotocin-mediated beta cell loss and hyperglycaemia
.
Diabetologia
2007
;
50
:
142
150
[PubMed]
21.
McEvoy
RC
,
Andersson
J
,
Sandler
S
,
Hellerström
C
.
Multiple low-dose streptozotocin-induced diabetes in the mouse. Evidence for stimulation of a cytotoxic cellular immune response against an insulin-producing beta cell line
.
J Clin Invest
1984
;
74
:
715
722
[PubMed]
22.
Deeds
MC
,
Anderson
JM
,
Armstrong
AS
, et al
.
Single dose streptozotocin-induced diabetes: considerations for study design in islet transplantation models
.
Lab Anim
2011
;
45
:
131
140
[PubMed]
23.
Asadi
A
,
Bruin
JE
,
Kieffer
TJ
.
Characterization of antibodies to products of proinsulin processing using immunofluorescence staining of pancreas in multiple species
.
J Histochem Cytochem
2015
;
63
:
646
662
[PubMed]
24.
An
D
,
Pulinilkunnil
T
,
Qi
D
,
Ghosh
S
,
Abrahani
A
,
Rodrigues
B
.
The metabolic “switch” AMPK regulates cardiac heparin-releasable lipoprotein lipase
.
Am J Physiol Endocrinol Metab
2005
;
288
:
E246
E253
[PubMed]
25.
Alejandro
EU
,
Kalynyak
TB
,
Taghizadeh
F
, et al
.
Acute insulin signaling in pancreatic beta-cells is mediated by multiple Raf-1 dependent pathways
.
Endocrinology
2010
;
151
:
502
512
[PubMed]
26.
Love
MI
,
Huber
W
,
Anders
S
.
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
.
Genome Biol
2014
;
15
:
550
[PubMed]
27.
Wang
L
,
Wang
S
,
Li
W
.
RSeQC: quality control of RNA-seq experiments
.
Bioinformatics
2012
;
28
:
2184
2185
[PubMed]
28.
Grabherr
MG
,
Haas
BJ
,
Yassour
M
, et al
.
Full-length transcriptome assembly from RNA-Seq data without a reference genome
.
Nat Biotechnol
2011
;
29
:
644
652
[PubMed]
29.
Zimmer
Y
,
Milo-Landesman
D
,
Svetlanov
A
,
Efrat
S
.
Genes induced by growth arrest in a pancreatic beta cell line: identification by analysis of cDNA arrays
.
FEBS Lett
1999
;
457
:
65
70
[PubMed]
30.
Oropeza
D
,
Jouvet
N
,
Bouyakdan
K
, et al
.
PGC-1 coactivators in β-cells regulate lipid metabolism and are essential for insulin secretion coupled to fatty acids
.
Mol Metab
2015
;
4
:
811
822
[PubMed]
31.
Sabatini
PV
,
Krentz
NAJ
,
Zarrouki
B
, et al
.
Npas4 is a novel activity-regulated cytoprotective factor in pancreatic β-cells
.
Diabetes
2013
;
62
:
2808
2820
[PubMed]
32.
Lingohr
MK
,
Buettner
R
,
Rhodes
CJ
.
Pancreatic beta-cell growth and survival--a role in obesity-linked type 2 diabetes?
Trends Mol Med
2002
;
8
:
375
384
[PubMed]
33.
Kwon
MM
,
O’Dwyer
SM
,
Baker
RK
,
Covey
SD
,
Kieffer
TJ
.
FGF21-Mediated Improvements in Glucose Clearance Require Uncoupling Protein 1
.
Cell Reports
2015
;
13
:
1521
1527
[PubMed]
34.
Dardevet
D
,
Moore
MC
,
Neal
D
,
DiCostanzo
CA
,
Snead
W
,
Cherrington
AD
.
Insulin-independent effects of GLP-1 on canine liver glucose metabolism: duration of infusion and involvement of hepatoportal region
.
Am J Physiol Endocrinol Metab
2004
;
287
:
E75
E81
[PubMed]
35.
Gelling
RW
,
Du
XQ
,
Dichmann
DS
, et al
.
Lower blood glucose, hyperglucagonemia, and pancreatic alpha cell hyperplasia in glucagon receptor knockout mice
.
Proc Natl Acad Sci U S A
2003
;
100
:
1438
1443
[PubMed]
36.
Escobar Galvis
ML
,
Jia
J
,
Zhang
X
, et al
.
Transgenic or tumor-induced expression of heparanase upregulates sulfation of heparan sulfate
.
Nat Chem Biol
2007
;
3
:
773
778
[PubMed]
37.
Nadir
Y
,
Brenner
B
.
Heparanase procoagulant activity in cancer progression
.
Thromb Res
2016
;
140
(
Suppl. 1
):
S44
S48
[PubMed]
38.
Meda
P
.
Protein-mediated interactions of pancreatic islet cells
.
Scientifica (Cairo)
2013
;
2013
:
621249
39.
Hauge-Evans
AC
,
King
AJ
,
Carmignac
D
, et al
.
Somatostatin secreted by islet delta-cells fulfills multiple roles as a paracrine regulator of islet function
.
Diabetes
2009
;
58
:
403
411
[PubMed]
40.
Kahleova
H
,
Mari
A
,
Nofrate
V
, et al
.
Improvement in β-cell function after diet-induced weight loss is associated with decrease in pancreatic polypeptide in subjects with type 2 diabetes
.
J Diabetes Complications
2012
;
26
:
442
449
[PubMed]
41.
Szabat
M
,
Page
MM
,
Panzhinskiy
E
, et al
.
Reduced insulin production relieves endoplasmic reticulum stress and induces β cell proliferation
.
Cell Metab
2016
;
23
:
179
193
[PubMed]
42.
Simon Davis
DA
,
Parish
CR
.
Heparan sulfate: a ubiquitous glycosaminoglycan with multiple roles in immunity
.
Front Immunol
2013
;
4
:
470
[PubMed]
43.
Omar
BA
,
Andersen
B
,
Hald
J
,
Raun
K
,
Nishimura
E
,
Ahrén
B
.
Fibroblast growth factor 21 (FGF21) and glucagon-like peptide 1 contribute to diabetes resistance in glucagon receptor-deficient mice
.
Diabetes
2014
;
63
:
101
110
[PubMed]
44.
Simeonovic
CJ
,
Ziolkowski
AF
,
Wu
Z
,
Choong
FJ
,
Freeman
C
,
Parish
CR
.
Heparanase and autoimmune diabetes
.
Front Immunol
2013
;
4
:
471
[PubMed]
45.
Bitan
M
,
Weiss
L
,
Zeira
M
, et al
.
Heparanase prevents the development of type 1 diabetes in non-obese diabetic mice by regulating T-cell activation and cytokines production
.
Diabetes Metab Res Rev
2008
;
24
:
413
421
[PubMed]
46.
Vlodavsky
I
,
Friedmann
Y
.
Molecular properties and involvement of heparanase in cancer metastasis and angiogenesis
.
J Clin Invest
2001
;
108
:
341
347
[PubMed]
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