Overexpression of the Kininogen-1 inhibits proliferation and induces apoptosis of glioma cells

A total of 83 serum specimens were obtained from normal (n = 14) and glioma patients (n = 69) in The Second Affiliated Hospital of Zhejiang University School of Medicine from January, 2016 to December, 2017 were used for quantitative polymerase chain reaction (qPCR) analysis. Glioma was diagnosed according to the 2007 WHO Classification of Tumors of the Central Nervous System. Written informed consent was provided to each patients for surgical procedures. This study was approved by the Specialty Committee on Ethics of The Second Affiliated Hospital of Zhejiang University School of Medicine. Furthermore, detailed clinicopathologic characteristics of the patients were listed in Table 1.

The mRNA expression data for GBM were downloaded from The Cancer Genome Atlas (TCGA) database (https://​cancergenome.​nih.​gov/​), including 169 tumor samples (survival time information was available) and 5 normal samples, which were collected from some of the 169 patients with GBM. As an R package, edgeR was used to identify DEGs between glioma and normal patients with the instruction manual. DEGs were ensured according to the following rule: log₂ fold change (FC) ≥ 2; the P value and false discovery rate (FDR) < 0.05. A heatmap and volcano plot of the DEGs were drawn in the R platform. The top 100 overlapping DEGs based on the |log₂FC| values were subjected for further analysis.

The direct (physical) and indirect (functional) associations of DEGs were evaluated based on STRING database (http://​string.​embl.​de/), providing an important assessment and integration of PPI [30]. Interactive relationships among DEGs were statistically obvious with an interaction score .0.4. Furthermore, we also analyzed the gene ontology [15] terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment for the top 8 core genes, respectively.

To identify the DEGs’ functional annotation, we analyzed GO terms and KEGG pathway enrichment with Database for Annotation, Visualization, and Integrated Discovery (DAVID) v.6.8 (https://​david.​ncifcrf.​gov/​tools.​jsp) [31]. And a P < 0.05 for statistical significance.

The glioma cell lines including SWO-38, U87-MG, SHG-44 and T98G were obtained from the Cell Library of the Chinese Academy of Sciences (Shanghai, China). The glioma cells were maintained in Dulbecco’s modified Eagle’s medium (DMEM; Gibco, Invitrogen, Carlsbad, CA, USA) with 10% fetal bovine serum (FBS, Gibco), 100 U/ml penicillin-streptomycin (Gibco) and 2 mM L-glutamine (Gibco) at 37 °C with 5% CO₂ in an incubator. The media was replaced every 3–4 days and the cultures were split using 0.25% trypsin (Gibco).

Cells (4 × 10⁵) were cultured in 6-well plates. After culture for 24 h, the medium was replaced by Opti-MEM (Invitrogen) and cultured. The pcDNA3.1-KNG1 and control vector were designed and cloned by Takara Biotechnology (Dalian) Co., LTD. In total, plasmids were transfected according to the Lipofectamine 2000 protocol (Invitrogen, Grand Island, NY, USA). After incubation for another 48 h, the treated cells were used for the further study.

Normal and transfected cells at a concentration of 2 × 10⁵ were seeded in 96-well plates and cell viability was detected by a cell counting kit-8 (Beyotime, Beijing, China). The medium was renewed and CCK-8 was added at time points (12, 24 and 48 h) for another 4 h. The absorbance was detected at 450 nm with an iMark microplate reader (Bio-Rad, Hercules, CA, USA).

The glioma cells were divided into 3 groups: normal, untreated cell; NC, cells were transfected with negative control vector; KNG1 group, cells transfected with KNG1 overexpression vector. After incubation as pre-described, the medium in each group was collected. Matrigel (BD Biosciences, SanJose, CA, USA) was placed in a 4 °C refrigerator for 12 h for liquefaction, and then was added to each well of a 96-well plate and solidified in an incubator for 30 min. The endothelial cells at a density of 4 × 104/well were seeded into the plates with matrigel and were respectively maintained in the medium which were collected from the each group. After 20 h culturing, the result was observed under an inverted microscope. The tube formation was according to the formula: 1000 × Total Area of Connected Tubes/Total Image Area.

Apoptosis and cell cycle assays were measured by the Annexin V-fluorescein isothiocyanate apoptosis kit and cell cycle analysis kit (BD Biosciences, SanJose, CA, USA) according to the protocols. The results were analyzed with a FACSCalibur flow cytometer (BD Biosciences).

Total RNA of renal tissues was isolated using Trizol reagent (Invitrogen, San Diego, CA, USA). Briefly, renal tissues were homogenized in 700 μL Trizol reagent followed by 300 μL chloroform. Then the samples were mixed for 5 min. After centrifugation (12,000 g for 15 min at 4 °C), the supernatant was carefully drew into a new tube. Equal volume of isopropyl alcohol was added and incubated at room temperature for 20 min. Following the centrifugation (12,000 g at 4 °C for 10 min), the supernatants were removed completely and the precipitate was washed twice by 75% ethanol. Finally, nuclease-free DEPC water was added to elute the RNA. The concentration and purity were detected by Shimadzu UV-2550 UV-visible spectrophotometer (Suzhou, China). The cDNA was obtained by 1 μg RNA according to the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA). In brief, the RNA was incubated with 2X RT master mix containing 10 × RT Buffer, 25 × dNTP Mix, 10 × RT Random Primers and MultiScribe™ Reverse Transcriptase at 25 °C for 10 min followed by 37 °C for 2 h and 85 °C for 5 min. Then the PCR products were separated on a 1% agarose gel with ethidium bromide staining. Densitometry was analyzed with the 200TM-Image software (Bio-Rad, USA) and GAPDH served as an internal reference gene. The specific primers were list in Table 2.

The expressions were conducted in the ABI 7500 real-time quantitative PCR system (Life Technologies, Grand Island, NY) with the following conditions: 95 °C for 5 min, 40 cycles of 95 °C for 15 s, 56 °C for 30 s. The specific primers were list in Table 2. GAPDH served as an internal reference gene and the data analysis were conducted with the 2^-ΔΔCt method.

Renal tissues were washed by PBS and lysed in lysis buffer (Beyotime, Shanghai, China). Then the lysates were incubated on ice for 30 min and oscillated for 30 s. After centrifugation at 10,000 g for 30 min at 4 °C, the supernatant was collected to measure the protein concentrations by BCA kit (Solarbio, Beijing, China). The proteins separated by the SDS-PAGE were transferred onto polyvinylidene difluoride membranes (GE Healthcare, Little Chalfont, UK). Then the membranes were incubated overnight at 4 °C 1 h after blocking with primary antibodies as follows: KNG1 (1:500, Abnova, Jhongli, Taiwan), caspase-3 (1:500, Abcam), caspase-9 (1:500, Abcam), CyclinD1 (1:1000, Abcam), ki67 (1:1000, Abcam), X-linked inhibitor of apoptosis (XIAP) (1:1000, Cell Signaling Technology, Beverly, MA), VEGF (1:1000, Cell Signaling Technology), PI3K (1:1000, Cell Signaling Technology), P-PI3K (1:1000, Cell Signaling Technology), Akt (1:1000, Cell Signaling Technology), p-Akt (1:1000, Cell Signaling Technology) and GAPDH (1:10000, Cell Signaling Technology). Then the membranes were probed with the anti-rabbit IgG (1:50000, Cell Signaling Technology). The bands were determined by a Molecular Imager VersaDoc MP 5000 System (Bio-Rad, Hercules, CA). The densitometry was determined with a Quantity One (Bio-Rad).

The study was approved by the Institutional Animal Care and Use Committee of The Second Affiliated Hospital of Zhejiang University School of Medicine. The male nude mice (average weight 30 g; 5-week-old) were obtained from Experimental Animal Laboratories, Shanghai, China). The mice were cultivated in a specific pathogen-free room at 25 °C under a 12-h light/dark cycle with free access to food and water. Then mice werer injected subcutaneously with transfected U87-MG and SHG-44 cells at a density of 1 × 10⁶ and the size and volume (mm³, = length × width × height × 0.5236) of tumor were calculated. All mice were sacrificed after implantation, the tumor tissues were blocked in paraffin for further analysis.

Immunohistochemistry was performed with anti-KNG1 (1:200, Abnova), anti-VEGF (1:200, Cell Signaling Technology) and anti-XIAP (1:200, Cell Signaling Technology) antibodies. In brief, tissue sections were dewaxed and washed with ethanol (Sigma-Aldrich), followed by incubation with 10% normal goat serum (Vector Laboratories, Burlingame, CA, USA). Then the sections were incubated with the primary antibodies overnight at 4 °C and hybridized with secondary antibody (Vector Laboratories) for 1 h at room temperature. After incubation with Vectastain Elite avidin-biotin complex reagent (Vector Laboratories) for 0.5 h, the diaminobenzidine (DAB kit; Vector Laboratories) was added and stained with hematoxylin (Sigma-Aldrich).

The sections were incubated at 60 °C for 20 min and were deparaffinized in xylene twice. Then sections were washed in graded series of alcohol and rinsed with PBS. Apoptotic cells were detected according to the protocol of TUNEL kit (Roche, Mannheim, Germany). Apoptotic (TUNEL-positive) cells were quantified under × 400 magnification.

The sections of mice were prepared for immunostaining using anti CD31 (cat. GB11063, Servicebio) according to the manufacturer’s instructions. Any brown staining endothelial cell cluster, clearly separate from adjacent microvessels and tumor cells was considered a countable microvessel. The membranous and cytoplasmic granular staining with VEGF was evaluated for all the tumor cells.

In our study, the heatmap revealed that 2930 DEGs were identified with TCGA dataset and 1591 DEGs were down-regulated while 1439 DEGs were up-regulated (Fig. 1a). Among them, 150 up-regulated DEGs and 404 down-regulated DEGs showed obviously different between normal and GBM samples (Fig. 1b).

To explore the interaction and core genes of DEGs, we selected 100 up-regulated DEGs and 100 down-regulated DEGs for the PPI, respectively (Fig. 1c, d). In the down-regulated DEGs, the top eight genes were identified as core genes. These core genes were KNG1, CCR9, MTNR1A, NPBWR1, OPRM1, RXFP3, SSTR4 and KRT1, in which KNG1 showed the highest interactions among the core genes with 11.

The KNG1 was evidently enriched in extracellular exosome, plasma membrane and neuropiptide signaling pathway, suggesting that KNG1 was mainly involved in exocrine function and blood disease (Fig. 1e). In KEGG pathway analysis, KNG1 was dramatically enriched in PI3K/AKT signaling pathway, cell circle, damage vessel and pathways in cancer (Fig. 2a).

Overall survival [3] analysis for glioma patients revealed that glioma patients with a high KNG1 expression had a longer survival time than those with a low KNG1 level (high expression vs low expression, log-rank P < 0.05, Fig. 2b).

The qPCR results showed that KNG1 expression was obviously reduced in the serums of glioma patients compared with those of normal patients. Moreover, 81.9% (68/83) of the specimens showed a significant decrease (over 6-fold) in KNG1 level (Fig. 2c). Univariate analyses revealed that KNG1 expression was not associated with age (P = 0.076), gender (P = 0.15), histological grade (P = 0.614), pathological stage (P = 0.586) and TNM stage (Table 1).

To further demonstrate the bioinformatic analysis, the eight hub down-regulated genes were detected in glioma cells (Fig. 2d). The results showed that KNG1 was significantly reduced in both the U87-MG and SHG-44 cells (P < 0.05, Fig. 2e). Besides, the protein level of KNG1 was markedly decreased in the U87-MG and SHG-44 cell lines (P < 0.01, Fig. 2f).

To explore the effect of KNG1 expression on glioma cell proliferation, we constructed over-expressed KNG1 vector to enforce its expression. The level of KNG1 was low in the U87-MG cells and the SHG-44 cells (Fig. 2f). KNG1 was transfected into these two cells to increase KNG1 expression. The U87-MG and SHG-44 cells transfected with KNG1 enhanced the expression of NDRG1, whereas no increased KNG1 expression was found in the NC-vector transfected cells at protein and mRNA levels (P < 0.01, Fig. 3a, b).

To determine the relationship between KNG1 and glioma cell viability, the cell viability was measured. The proliferation of transfected U87-MG and SHG-44 cells were evidently decreased, compared with that in cells transfected with the NC-vector or control (P < 0.05; Fig. 3c, d).

Moreover, in control and NC-vector group, cells gradually stretched, and connected each other into cords and network structure, forming luminal structures of various sizes and shapes. However, tubes formed in overexpressed KNG1 group was rare (Fig. 3e). Furthermore, overexpression of KNG1 notably reduced the number of generated blood vessels (P < 0.05; Fig. 3f).

The apoptosis rate of U87-MG cells with overexpressed KNG1 was remarkably induced, compared with that in the cells with the NC-vector and control (P < 0.05; Fig. 4a, b). Similarly, a relatively high apoptosis rate of transfected SHG-44 cells with KNG1 was observed (P < 0.05; Fig. 4a, b). Additionally, an evident decrease in the number of U87-MG and SHG-44 cells transfected with KNG1 was observed in G1 phase, compared with that in cells with NC-vector (P < 0.05; Fig. 4c, d).

We further investigated the molecular mechanism of KNG1 on the inhibition of glioma cancer angiogenesis and apoptosis in U87-MG cells (Fig. 5a). The protein levels of VEGF, cyclinD1 and ki67 were obviously reduced in the U87-MG cells overexpressing KNG1 (P < 0.05, Fig. 5b), which was consistent with the mRNA expressions (P < 0.05, Fig. 5c). Furthermore, the caspase-3 level was enhanced while the XIAP expression was inhibited. Interestingly, the protein level of caspase-9 was not significantly increased while its mRNA level was markedly increased (P < 0.05, Fig. 5d, e). Besides, the protein and mRNA levels of these genes in SHG-44 cells were similar to those in U87-MG cells (P < 0.05, Fig. 5f-j).

The levels of p-PI3K and p-Akt were reduced in U87-MG cells overexpressing KNG1, whereas the expressions of total PI3K and Akt were unchanged (Fig. 6a). Besides, the ratios of p-PI3K/PI3K and p-Akt/Akt were prominently reduced in the transfected U87-MG cells (P < 0.05, Fig. 6b, c). In addition, the expressions of p-PI3K, PI3K, p-Akt and Akt were similar in the transfected SHG-44 cells (P < 0.05, Fig. 6d-f).

To explore the effects of KNG1 on glioma growth, we established a xenograft nude mouse model. Mice injected with U87-MG cells overexpressing KNG1 showed significantly smaller tumors than those in the control group (P < 0.05, Fig. 7a). Moreover, the tumor weight and tumor volume were obviously decreased in the mice injected with U87-MG cells overexpressing KNG1 (P < 0.05, Fig. 7b, c). Furthermore, the changes of tumors size, weight and volume in the mice injected with SHG-44 cells overexpressing KNG1 were in accordance with those in mice injected with U87-MG cells (P < 0.05, Fig. 7d-e).

The expressions of KNG1, XIAP and VEGF were detected in the tumor tissues of mice injected with U87-MG cells (Fig. 8a). Besides, the KNG1 expression was significantly increased while the levels of XIAP and VEGF were obviously reduced (P < 0.05, Fig. 8b). Moreover, the level of KNG1 was also enhanced in the tumor tissues of mice injected with SHG-44 cells and the expressions of XIAP and VEGF were inhibited (P < 0.05, Fig. 8c, d).

To understand the effect of KNG1 overexpression on apoptosis in glioma, the apoptotic cells of the brain tissues were detected in mice. The apoptotic cells were expressed as the brown nucleus and more apoptotic cells were found in mice injected by U87-MG overexpressing KNG1 than those in control (Fig. 9a). Additionally, the apoptosis rate of mice injected with SHG-44 overexpressing KNG1 were increased (Fig. 9b).

Moreover, the microvessels of the brain tissues from the mice injected with U87-MG cells were markedly induced and were obviously inhibited by the overexpressed KNG1 (P < 0.05, Fig. 9c). Furthermore, the microvessels of brain tissues was obviously observed in mice injected with SHG-44 cells, and overexpressed KNG1 reduced the microvessels (P < 0.05, Fig. 9d).