The hyaluronan-mediated motility receptor (HMMR) is overexpressed in gastric cancer; however, the apparent role of HMMR has not been well defined owing to lack of detailed studies on gastric tumorigenesis. Therefore, we elucidated the functional and regulatory mechanisms of HMMR in gastric cancer. Using publicly available data, we confirmed HMMR overexpression in patients with gastric cancer. HMMR silencing decreased proliferation, migration, and invasion of gastric cancer cells, whereas HMMR overexpression reversed these effects. A gastric cancer xenograft mouse model showed statistically significant inhibition of tumor growth upon HMMR depletion. Previous data from cDNA microarray showed reduced HMMR expression upon inhibition of galectin-3. However, overexpression of galectin-3 increased HMMR expression, cell proliferation, and motility in gastric cancer cells, whereas HMMR silencing blocked these effects. Interestingly, galectin-3 interacted directly with C/EBPβ and bound to HMMR promoter to drive its transcription, and gastric cancer cell proliferation and motility. Altogether, high expression of HMMR promoted gastric cancer cell proliferation and motility and could be a prognostic factor in gastric cancer. In addition, HMMR expression was regulated by the interaction between C/EBPβ and galectin-3. Therefore, targeting HMMR along with galectin-3 and C/EBPβ complex could be a potential treatment strategy for inhibiting gastric cancer progression and metastasis.

Implications:

This study provides evidence that galectin-3 interacts with C/EBPβ in gastric cancer, and galectin-3 and C/EBPβ complex promotes gastric cancer cell progression and motility through upregulating HMMR expression.

Gastric cancer is the fourth most common type of cancer and the second leading cause of cancer-related deaths worldwide (1, 2). Despite current developments in diagnosis, as well as surgical and pharmacologic approaches, metastasized gastric cancer leads to poor prognosis and mortality (3–7). Patients who present with the most favorable characteristics and undergo curative surgical resection often die of recurrent disease due to metastasis (8). Although several recent studies have focused on gastric cancer metastasis (9, 10), the underlying molecular mechanism of this phenomenon has not been completely elucidated (10). Therefore, we aimed to understand the underlying processes involved in gastric cancer metastasis, focusing on specific targets to improve gastric cancer prognosis.

The hyaluronan-mediated motility receptor (HMMR, also known as CD168 or RHAMM), a hyaluronan or hyaluronic acid–binding protein, has several functions and is present on cell surfaces as well as inside the cells (11). For example, when HMMR binds with hyaluronan on the cell surface, it activates a signal transduction cascade causing intracellular protein tyrosine phosphorylation (12, 13). In addition, HMMR interacts with microtubules, actin filaments, and mitotic spindle assembly, necessary for the organization of the cytoskeletal network (12, 14–16). HMMR is not only a modulator of growth factor receptor of hyaluronan, but also has critical roles in the progression and proliferation of various cancers (17–19). HMMR is expressed in different mammalian cells, including smooth muscle cells, endothelial cells, nerve cells, immune cells, and various types of cancer cells (14, 16, 20). In addition, recent reports have shown an association of HMMR with resistance to chemotherapy in gastric cancer (21). Moreover, high expression of HMMR in the lung and breast cancer and gliomas was associated with poor disease outcome (13, 22–24). However, the mechanism(s) responsible for the upregulation of HMMR expression or activation needs to be investigated, because the role of HMMR in gastric cancer progression remains unclear.

Previously, we reported high expression of galectin-3 in gastric cancer (25, 26). To further understand the role of galectin-3 in gastric cancer, we performed cDNA microarray analysis of gastric cancer cells wherein the expression of galectin-3 was knocked down using specific siRNA (27). cDNA microarray results confirmed that silencing of galectin-3 decreased gastric cancer cell motility by downregulating fascin-1, PAR-1, MMP-1, as well as cell motility–related genes (26, 28). Moreover, significant reduction in HMMR levels was detected. Therefore, we hypothesized that both HMMR and galectin-3 might be responsible for increased gastric cancer cell motility and progression. Using gastric cancer cell lines, we performed in vitro and in vivo studies in parallel, to determine the effect of galectin-3 on cancer cell proliferation and motility. We also compared the relative expression levels of HMMR and galectin-3 with survival rates that were obtained from public databases of patients with gastric cancer. Furthermore, we also showed that HMMR expression was regulated by interaction between the transcriptional factor CCAAT/enhancer-binding protein β (C/EBPβ) and galectin-3. C/EBPβ promotes tumor cell invasion and is associated with metastasis in various cancers, including gastric, breast, and colorectal cancers (29–32).

In this study, we hypothesized that high expression of HMMR was responsible for gastric cancer cell proliferation, migration, and invasion. Therefore, HMMR could serve as a potential target to prevent gastric cancer progression and metastasis. Furthermore, we proposed that HMMR expression was regulated by interaction between galectin-3 and C/EBPβ in gastric cancer.

Cell culture

The human gastric cancer cell lines AGS, MKN28, SNU-216, -601, -638, and -668 were purchased from the Korea Cell Line Bank (KCLB). YCC-2 cells and human normal gastric epithelial cell lines (GES-1) were obtained from Yonsei Cancer Center and cultured in RPMI1640 medium (Welgene) supplemented with 5% FBS (Corning) and 1% antibiotics (including streptomycin/penicillin, Gibco, Thermo Fisher Scientific) at 37°C in a humidified incubator with 5% CO2. These cell lines were free from contamination by Mycoplasma, as determined using the Mycoplasma Detection Kit (Takara). KCLB uses DNA fingerprinting analysis, species verification testing, Mycoplasma contamination testing, and viral contamination testing. All experiments performed on cells that were passaged less than 30 times from thawed cell stock.

siRNA transfection and plasmid construction

Human HMMR siRNAs and plasmid DNA were transfected using Lipofectamine RNAiMAX Reagent or Lipofectamine 2000 Reagent (Invitrogen) following the manufacturer's protocol. The coding sequences of HMMR siRNAs purchased from Genolution Inc., were #1: 5′-GAACGACAGUGGCUCAGCAUU-3′ and #2: 5′-CCACUUGGAUGCUAUGGACUU-3′. Human HMMR construct was cloned into pCMV-Flag plasmid in the Sal1 and Apa1 restriction enzyme sites, to generate the pCMV_HMMR construct. The full-length HMMR cDNA was PCR-amplified using the primers: 5′-GATCGTCGACGCCACCATGTCCTTTCCTAAGGCGC-3′ (sense) and 5′-GATCGGGCCCCTTCCATGATTCTTGACACTCC-3′ (antisense). Human C/EBPβ was cloned into pCMV-Flag plasmid in the BamH1 and Xho1 restriction enzyme sites, to generate the pCMV_C/EBPβ construct. The full-length C/EBPβ construct was PCR-amplified using the primers: 5′-ATCGGATCCATGCAACGCCTGGTGGCCTGGGACCC-3′ (sense) and 5′-ATCCTCGAGCTAGCAGTGGCCGGAGGAGGCGAGCAG-3′ (antisense). HMMR and C/EBPβ cDNA clones were provided by the Korea Human Gene Bank (KHGB). The generation of galectin-3 siRNA and plasmid vector constructs has been described in previous studies (26, 28).

RNA isolation and reverse transcription-PCR

Total RNA was isolated from human gastric cancer cells using RNAiso Reagent (Takara) following the manufacturer's protocol. cDNA synthesis was carried out using a Reverse Transcription System (Toyobo), and PCR was performed using nTaq DNA Polymerase (Enzynomics). The primer sequences used were: HMMR: 5′-AACAGCTGGAAGATGAAGAA-3′ (sense) and 5′-ATTTAGCTGTTCCTGAGCTG-3′ (antisense); LGALS3: 5′-ATGGCAGACAATTTTTCGCTCC-3′ (sense) and 5′-ATGTCACCAGAAATTCCCAGTT-3′ (antisense); C/EBPα: 5′-GCCGGGAGAACTCTAACTCC-3′ (sense) and 5′-AGGAACTCGTCGTTGAAGGC-3′ (antisense); C/EBPβ: 5′-GGTCAAGAGCAAGGCCAAG-3′ (sense) and 5′-CTAGCAGTGGCCGGAGGAG-3′ (antisense); C/EBPγ: 5′-AGTGACGAGTATCGGCAACG-3′ (sense) and 5′-TACTGTCCTGCATTGTCGCC-3′ (antisense); and GAPDH: 5′-GGCTGCTTTTAACTCTGGTA-3′ (sense) and 5′-ACTTGATTTTGGAGGGATCT-3′ (antisense).

Western blot analysis

Briefly, cells were lysed using RIPA Lysis Buffer (Biosesang Inc.) containing phosphatase and protease inhibitor cocktail (GenDEPOT), followed by sonication on ice. The cell lysate was centrifuged at 16,000 × g for 20 minutes and the supernatant was collected. Proteins (20 μg) were separated by SDS-PAGE and transferred onto a polyvinylidene fluoride membrane (Merck). After blocking with 5% skim milk for 1 hour, the membrane was incubated with primary antibodies in 5% BSA overnight at 4°C. The following antibodies were used: anti-RHAMM (HMMR), anti-galectin-3, anti-C/EBPα, anti-C/EBPβ, anti-C/EBPγ, and anti-lamin A/C purchased from Santa Cruz Biotechnology. Anti-GAPDH (Bioworld) antibody was used as the control. The membranes were incubated with horseradish peroxidase–conjugated secondary antibody (Bethyl Laboratories) for 90 minutes, followed by detection using a Supernova-Q1800 and ECL Kit (Bio-Rad).

Cell proliferation assay

AGS, MKN28, SNU-638-LacZ, and SNU-638-galectin-3 cells were seeded in 96-well plates (4 × 103 cells per well). After overnight incubation, cells were transfected with siRNA (scRNA or HMMR siRNA) and plasmid vector [pCMV_Empty Vector (E.V) or pCMV_HMMR]. WST-1 Solution (Daeil Lab Services Co., Ltd) was added to each well 24, 48, 72, and 96 hours after transfection. The plates were incubated for another 1–2 hours and gently shaken and the absorbance was measured at 450 nm.

Colony formation assay

Gastric cancer cells were transfected with siRNA and plasmid vector. After 24 hours of transfection, 500–1,000 cells were plated in the new 60-mm cell culture dish. We changed the media containing 10% FBS and 1% antibiotics every 3 days. After 14 days of incubation, the medium was removed, and the cells were fixed with 1% glutaraldehyde. The cells were then stained with 0.5% crystal violet for 10 minutes. Following rinsing with DPBS, colonies that had formed in each well were counted. Each experiment was performed in triplicate.

Transwell migration and invasion assays

AGS, MKN28, SNU-638-LacZ, and SNU-638-galectin-3 cells were transfected with siRNA (scRNA or HMMR siRNA) and plasmid vector (pCMV_E.V or pCMV_HMMR). After 24 hours of transfection, 2 × 104 cells in 200 μL FBS-free medium were added to the top chamber of the transwell (Corning Costar), on a filter coated with 0.5 mg/mL collagen type I (BD Biosciences) for the migration assay, and Matrigel (1:15; BD Biosciences) coated filters for the invasion assay. RPMI1640 medium containing 10% FBS and 1% antibiotics was added to the bottom chamber, and the plates were incubated for 20 hours. Cells that had migrated and invaded were visualized and quantified by hematoxylin and eosin staining. For quantification, cells were counted from five randomly selected areas in each well using wide-field microscopy. Data are expressed as mean ± SEM from three independent experiments.

Generation of HMMR-depleted xenograft mice

All animal experiments were approved by the Institutional Review Board of the National Cancer Center (NCC, Korea) and performed in specific pathogen-free facilities and conditions following the Guidelines for the Care and Use of Laboratory Animals of NCC (NCC-11-034D). The protocol for the generation of xenograft mice has been described earlier (33).

Luciferase reporter assay

SNU-638-LacZ- and SNU-638-galectin-3–transfected cells were seeded in 6-well plates (5 × 104 cells per well). After overnight incubation, cells were transfected with 2 μg of C/EBP luciferase reporter vector and 0.25 μg of β-galactosidase expression vector. After incubation for 24 hours, cells were harvested and luciferase assay was performed (Promega) following the manufacturer's instructions. β-Galactosidase Enzyme Assay (Promega) was used as control to evaluate transfection efficiency.

Nuclear fractionation

The cytosol was separated by adding buffer A [10 mmol/L HEPES (pH 7.9), 1.5 mmol/L MgCl2, 10 mmol/L KCl, 1 mmol/L DTT, 0.2 mmol/L PMSF, and 0.1% NP-40] to total cell lysates of SNU-638-LacZ and SNU-638-galectin-3. The cytosol was resuspended using buffer A' (buffer A without NP-40). After centrifugation, the supernatant was the cytoplasmic fraction. Buffer C [20 mmol/L HEPES (pH 7.9), 25% glycerol, 0.42 mol/L NaCl, 0.2 mmol/L EDTA, 1.5 mmol/L MgCl2, 1 mmol/L DTT, and 0.2 mmol/L PMSF] was added to the remaining pellet to dissolve the nuclei. Protein expression levels were analyzed by Western blotting.

Immunoprecipitation

As described for Western blot analysis, cell lysates were prepared with RIPA buffer. The samples were subjected to a preclearing step with protein A/G agarose beads at 4°C for 30 minutes in the rotator. Supernatants were obtained after brief centrifugation (350 × g at 4°C for 5 minutes) and were subjected to immunoprecipitation using anti-galectin-3, anti-C/EBPβ, and anti-rabbit IgG (negative control) antibodies. Immunoprecipitated complexes were washed three times with 20% RIPA buffer. After adding 2× SDS sample buffer, samples were boiled for 5 minutes at 95°C and the supernatants were obtained after brief centrifugation (16,000 × g at 4°C for 2 minutes). The respective protein expression levels were determined by Western blot analysis.

Chromatin immunoprecipitation assay

Galectin-3–overexpressing SNU-638 cells were cultured in a 150-mm dish (2 × 105 cells). After incubation for 48 hours, cells were treated with 1% formaldehyde for cross-linking. Chromatin immunoprecipitation (ChIP) assay was performed using Pierce Agarose ChIP Kit (Thermo Fisher Scientific) following the manufacturer's instructions. Anti-rabbit IgG was used as negative control. Antibodies used for immunoprecipitation were: anti-galectin-3 and anti-C/EBPβ purchased from Santa Cruz Biotechnology. C/EBPβ primers were designed with HMMR promoter binding sites: 5′-AAAGTTCACATGCAACGAACAATGG-3′ (sense) and 5′-GCTGGGTTCTGATTGCGTCC-3′ (antisense) and PCR was performed. The primers with the GAPDH promoter site were obtained from the ChIP kits. Reverse transcription-PCR (RT-PCR) was performed with Ex Taq DNA Polymerase (Takara).

Gene expression profile data and Kaplan–Meier analysis

The available datasets GSE29630, GSE13861, GSE63089, and GSE27342 were downloaded from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). These three datasets (GSE13861, GSE63089, and GSE27342) were normalized using GEO2R, and a scatter plot was obtained for the expression pattern analysis. The gene ontology of GSE29630 dataset was analyzed using by DAVID software. Kaplan–Meier curves for overall survival of patients with gastric cancer were generated using the online resource, Kaplan–Meier Plotter (http://kmplot.com/analysis; ref. 34).

Statistical analysis

Statistical analyses were performed using GraphPad Prism 5 (GraphPad Software, Inc.). The data were analyzed using Student t test, unless otherwise specified. Data from public databases were used to determine differences in patient survival using the Kaplan–Meier plotter. Results were presented as mean ± SEM. P < 0.05 was considered to indicate statistical significance.

Analysis of HMMR expression from cDNA microarray data and publicly available data on survival rate in patients with gastric cancer

HMMR expression was high in a majority of patients with gastric cancer, which correlated with their poor survival. However, significance of this correlation in gastric cancer is not clear. HMMR expression levels were determined from gastric cancer patient data, available in the GEO database (Fig. 1AC). Kaplan–Meier analysis was performed to generate survival curves for gastric cancer patient data (Fig. 1D). We collected three (GSE13861, GSE63089, and GSE27342) gastric cancer patient datasets and compared HMMR expression levels in tumor and normal stomach tissues (Fig. 1AC). In all three datasets analyzed, HMMR expression was increased in tumor tissues, compared with normal tissues. Furthermore, statistical analysis of data from the public database of tumor tissues from patients with gastric cancer showed that high HMMR expression correlated with a significantly low probability of survival, compared with low HMMR expression (Fig. 1D). These results strongly support that increased expression of HMMR in gastric cancer tissues compared with normal tissues, correlated with reduced survival rate.

Figure 1.

Correlation between HMMR expression and survival rate data of patients with gastric cancer derived from the public database. A–C, HMMR mRNA expression levels in tumor and normal tissues from the GEO database. Datasets are presented as a scatter plot (A-GSE13861, B-GSE63089, and C-GSE27342). The P values are calculated using Student t test (A, **, P < 0.01; B and C, ***, P < 0.001). D, Kaplan–Meier survival curves show a correlation between poor prognosis in HMMR-upregulated patients with a worse overall survival in gastric cancer patient data from public database (probe 1: 209709_s_at, n = 593; probe 2: 207165_s_at, n = 593; http://kmplot.com/analysis).

Figure 1.

Correlation between HMMR expression and survival rate data of patients with gastric cancer derived from the public database. A–C, HMMR mRNA expression levels in tumor and normal tissues from the GEO database. Datasets are presented as a scatter plot (A-GSE13861, B-GSE63089, and C-GSE27342). The P values are calculated using Student t test (A, **, P < 0.01; B and C, ***, P < 0.001). D, Kaplan–Meier survival curves show a correlation between poor prognosis in HMMR-upregulated patients with a worse overall survival in gastric cancer patient data from public database (probe 1: 209709_s_at, n = 593; probe 2: 207165_s_at, n = 593; http://kmplot.com/analysis).

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HMMR silencing reduces cell proliferation, migration, and invasion of gastric cancer cells

RT-PCR analysis confirmed HMMR expression in normal gastric epithelial cell line and seven gastric cancer cell lines (Supplementary Fig. S1). The data showed that most gastric cancer cell lines had high HMMR expression levels compared with the GES-1 normal gastric epithelial cells, except for the SNU-638 cell line. Among these, we selected AGS (with relatively low expression) and MKN28 (relatively high expression) cells for further experiments. HMMR expression was silenced using two specific siRNAs and the interference efficiency was confirmed by RT-PCR and Western blot analyses (Fig. 2A). After HMMR knockdown, cell proliferation was analyzed by WST-1 assay. The results showed that knockdown of HMMR significantly reduced the proliferation of gastric cancer cells (Fig. 2B). In addition, we confirmed that cells transfected with HMMR short hairpin RNA (shRNA) formed fewer colonies than pLKO1 cells, as determined by colony formation assay (Fig. 2C). Moreover, cell migration and invasion assays showed that knockdown of HMMR inhibited the migratory and invasive abilities of gastric cancer cells (Fig. 2D and E). These results further indicate that HMMR was highly expressed in gastric cancer cells and regulates gastric cancer cell proliferation and motility.

Figure 2.

Downregulation of HMMR decreases cell proliferation, migration, and invasion of gastric cancer cells. AGS and MKN28 cells were transfected with scrambled siRNA (scRNA) or two siRNA constructs specific for HMMR (siRNA #1 and #2). A, Detection of HMMR-silencing efficiency was by RT-PCR and Western blot (WB) analyses. GAPDH was used as the loading control. B, WST-1 assay was performed to detect cell proliferation. C, Colony formation assays showing the effect of HMMR shRNA #1 and #2 versus pLKO1 on the growth of AGS and MKN28 cells and data are represented as graphs (top) and as image (bottom). Transwell assays to assess migration (D) and invasion (E) of cells. Data are presented as mean ± SEM (n = 5). The P values are calculated using Student t test and significant differences are indicated ***, P < 0.001.

Figure 2.

Downregulation of HMMR decreases cell proliferation, migration, and invasion of gastric cancer cells. AGS and MKN28 cells were transfected with scrambled siRNA (scRNA) or two siRNA constructs specific for HMMR (siRNA #1 and #2). A, Detection of HMMR-silencing efficiency was by RT-PCR and Western blot (WB) analyses. GAPDH was used as the loading control. B, WST-1 assay was performed to detect cell proliferation. C, Colony formation assays showing the effect of HMMR shRNA #1 and #2 versus pLKO1 on the growth of AGS and MKN28 cells and data are represented as graphs (top) and as image (bottom). Transwell assays to assess migration (D) and invasion (E) of cells. Data are presented as mean ± SEM (n = 5). The P values are calculated using Student t test and significant differences are indicated ***, P < 0.001.

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HMMR overexpression induces proliferation, migration, and invasion of gastric cancer cells

The effect of gain-of-function of HMMR in AGS and MKN28 gastric cancer cells was examined. Cells were transiently transfected with the HMMR overexpression vector (pCMV_HMMR) or empty vector (pCMV_E.V) for 48 hours. Overexpression of HMMR was confirmed by RT-PCR and Western blot analyses (Fig. 3A). Enhanced HMMR expression significantly increased cell proliferation (Fig. 3B), colony formation (Fig. 3C), cell migration (Fig. 3D), and cell invasion (Fig. 3E). These findings suggested that HMMR was involved in gastric cancer cell proliferation and motility.

Figure 3.

Overexpression of HMMR promotes cell proliferation, migration, and invasion of gastric cancer cells. Overexpression of HMMR in AGS and MKN28 cells was achieved by transfection with an empty vector (pCMV_E.V) or HMMR overexpression vector (pCMV_HMMR). A, RT-PCR and Western blot (WB) analyses detected the mRNA and protein expression of HMMR, respectively. GAPDH was used as the loading control. B, WST-1 assay was performed to detect cell proliferation. C, Colony formation assay showing the effect of pCMV_E.V or pCMV_HMMR on the growth of AGS and MKN28 cells, and presented as graphs (top) and as image (bottom). Transwell migration assays to assess migration (D) and invasion (E) abilities of the cells. Data are presented as mean ± SEM (n = 5). The P values are calculated using Student t test and significant differences are indicated ***, P < 0.001.

Figure 3.

Overexpression of HMMR promotes cell proliferation, migration, and invasion of gastric cancer cells. Overexpression of HMMR in AGS and MKN28 cells was achieved by transfection with an empty vector (pCMV_E.V) or HMMR overexpression vector (pCMV_HMMR). A, RT-PCR and Western blot (WB) analyses detected the mRNA and protein expression of HMMR, respectively. GAPDH was used as the loading control. B, WST-1 assay was performed to detect cell proliferation. C, Colony formation assay showing the effect of pCMV_E.V or pCMV_HMMR on the growth of AGS and MKN28 cells, and presented as graphs (top) and as image (bottom). Transwell migration assays to assess migration (D) and invasion (E) abilities of the cells. Data are presented as mean ± SEM (n = 5). The P values are calculated using Student t test and significant differences are indicated ***, P < 0.001.

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In vivo effect of HMMR inhibition in a gastric cancer xenograft mouse model

We investigated the effect of HMMR inhibition on tumorigenic ability in a mouse xenograft model. We generated two stable AGS SQ cell lines that were silenced for HMMR shRNA. These clones were injected into nude mice (Fig. 4A). Compared with tumors derived from negative control pLKO 0.1-expressing AGS cells, the HMMR-knockdown group of mice showed reduced tumor growth rate (Fig. 4B) and size in xenograft mice (Fig. 4C and D). These data strongly suggest that HMMR accelerates gastric cancer progression in vivo.

Figure 4.

Effect of HMMR inhibition on tumor growth in xenograft mice. A, Lentiviruses expressing shRNA-targeting HMMR were used to generate stable AGS SQ cell lines. Lentivirus expressing pLKO.1_E.V was used as a control. B–D, The effect of HMMR on tumor growth in xenograft mice. AGS SQ cells (50 μL, 1 × 106) with Matrigel were implanted into Balb/c nude mice to form subcutaneous xenografts. Tumor volumes were measured at different time points and are presented as a graph (B). Images of tumors photographed on day 28 (C and D). Data are presented as the mean and SEM. Unpaired Student t-test was used for comparison between the two groups; ***, P < 0.001. WB, Western blot.

Figure 4.

Effect of HMMR inhibition on tumor growth in xenograft mice. A, Lentiviruses expressing shRNA-targeting HMMR were used to generate stable AGS SQ cell lines. Lentivirus expressing pLKO.1_E.V was used as a control. B–D, The effect of HMMR on tumor growth in xenograft mice. AGS SQ cells (50 μL, 1 × 106) with Matrigel were implanted into Balb/c nude mice to form subcutaneous xenografts. Tumor volumes were measured at different time points and are presented as a graph (B). Images of tumors photographed on day 28 (C and D). Data are presented as the mean and SEM. Unpaired Student t-test was used for comparison between the two groups; ***, P < 0.001. WB, Western blot.

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Galectin-3 regulates HMMR expression in gastric cancer cells

After elucidating the role of HMMR in gastric cancer, we extended the study to identify the gene that regulated HMMR expression. Previously, we reported the involvement of galectin-3 in gastric cancer cell progression and cell motility (27). Through the gene ontology analysis cell signal transduction, apoptotic progress, cell proliferation, and cell cycle were regulated by galectin-3 existence (Supplementary Tables S1–S4). The relationship between galectin-3 and HMMR was confirmed using publicly available gastric cancer patient data (Fig. 5A). Moreover, microarray data revealed a decrease in HMMR expression in galectin-3–silenced AGS cells (Supplementary Tables S2 and S4). Among them, cell motility–related genes were selected and arranged by heatmap (Fig. 5B). The above data showed a high correlation of HMMR with galectin-3 expression in gastric cancer. Furthermore, MKN-28 cells were transfected with either galectin-3 siRNA or HMMR siRNA. Both galectin-3 and HMMR expression levels were decreased by galectin-3 siRNA treatment, whereas HMMR siRNA treatment decreased only HMMR expression without any change in galectin-3 expression (Fig. 5C). We transfected galectin-3 plasmid in AGS cells and detected increased expression of both, HMMR and galectin-3 (Fig. 5D). These data showed a strong correlation between galectin-3 and HMMR expression and also indicated that HMMR expression was regulated by galectin-3 in gastric cancer.

Figure 5.

HMMR expression was upregulated by galectin-3. A, Spearman correlation test showing the relationship between galectin-3 and HMMR in gastric cancer patient data obtained from a public database such as GSE63089. B, Heatmaps of cell proliferation- and motility-related genes after galectin-3 silencing in AGS cells (GSE29630). C, mRNA and protein expression levels after transfection of human gastric cancer MKN-28 cells with 30 nmol/L scRNA or each of galectin-3 or HMMR siRNAs. Total RNA and protein isolated from MKN-28 cells after transfection for 48 hours were analyzed by RT-PCR and Western blotting (WB), respectively. D, mRNA and protein expression levels of galectin-3 and HMMR by RT-PCR and Western blotting, after transfection of AGS cells with pcDNA3.0_galectin-3 and vector control pcDNA3.0_E.V.

Figure 5.

HMMR expression was upregulated by galectin-3. A, Spearman correlation test showing the relationship between galectin-3 and HMMR in gastric cancer patient data obtained from a public database such as GSE63089. B, Heatmaps of cell proliferation- and motility-related genes after galectin-3 silencing in AGS cells (GSE29630). C, mRNA and protein expression levels after transfection of human gastric cancer MKN-28 cells with 30 nmol/L scRNA or each of galectin-3 or HMMR siRNAs. Total RNA and protein isolated from MKN-28 cells after transfection for 48 hours were analyzed by RT-PCR and Western blotting (WB), respectively. D, mRNA and protein expression levels of galectin-3 and HMMR by RT-PCR and Western blotting, after transfection of AGS cells with pcDNA3.0_galectin-3 and vector control pcDNA3.0_E.V.

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Galectin-3 promotes gastric cancer cell motility by upregulating HMMR expression

We examined whether galectin-3 increased cell proliferation, migration, and invasion by modulating HMMR expression. To efficiently examine the roles of galectin-3 and HMMR, we used the SNU-638 cell line (galectin-3 null expression). Moreover, previous data showed that SNU-638 cells exhibited low expression levels of HMMR (Supplementary Fig. S1). SNU-638 cells infected with a lentiviral galectin-3 expression cassette, resulted in overexpression of galectin-3, along with an increase in HMMR mRNA and protein expression, and additional HMMR siRNA treatment diminished this response (Fig. 6A). LacZ-overexpressing SNU-638 cells were used as negative control for galectin-3–overexpressing cells. Galectin-3 induced cell proliferation, and HMMR silencing significantly reduced the increased cell proliferation caused by galectin-3 overexpression (Fig. 6B). In addition, galectin-3 overexpression increased colony formation (Fig. 6C), cell migration (Fig. 6D), and cell invasion (Fig. 6E). The increased migratory, invasive, and colony-forming abilities were reduced upon HMMR silencing, similar to that on decreased cell proliferation. These results suggested that galectin-3 promoted proliferation, migration, and invasion of gastric cancer cells by upregulating HMMR.

Figure 6.

Galectin-3–mediated HMMR expression promotes cell proliferation, migration, and invasion of gastric cancer cells. A, mRNA and protein expression levels of galectin-3 and HMMR detected by RT-PCR and Western blot analyses in SNU-638 cells, infected with lentivirus containing LacZ or galectin-3, and then transfected with HMMR siRNA or scRNA (negative control). B, Cell counting assay was performed to analyze proliferation of SNU-638 cells. C, Colony formation assay showing the effect of HMMR siRNA or scRNA on the growth of LacZ- or galectin-3–overexpressing SNU-638 cells, presented as graphs (top) and as image (bottom). Transwell migration assays to assess migration (D) and invasion (E) abilities of cells. Data are represented as a histogram (**, P <0.01; ***, P <0.001).

Figure 6.

Galectin-3–mediated HMMR expression promotes cell proliferation, migration, and invasion of gastric cancer cells. A, mRNA and protein expression levels of galectin-3 and HMMR detected by RT-PCR and Western blot analyses in SNU-638 cells, infected with lentivirus containing LacZ or galectin-3, and then transfected with HMMR siRNA or scRNA (negative control). B, Cell counting assay was performed to analyze proliferation of SNU-638 cells. C, Colony formation assay showing the effect of HMMR siRNA or scRNA on the growth of LacZ- or galectin-3–overexpressing SNU-638 cells, presented as graphs (top) and as image (bottom). Transwell migration assays to assess migration (D) and invasion (E) abilities of cells. Data are represented as a histogram (**, P <0.01; ***, P <0.001).

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Galectin-3 promotes HMMR transcription by interacting with C/EBPβ transcriptional factor and nuclear translocation

To determine the mechanism by which galectin-3 regulates HMMR expression, we checked for binding motifs on HMMR promoter region using prediction programs. We examined the transcription factor binding motifs, and confirmed that the C/EBP binding motif was highly conserved in the HMMR promoter region (Fig. 7A). The transcriptional activity of C/EBP is regulated by galectin-3 binding protein (galectin-3BP) and promotes tumor progression in various cancers including gastric cancer (29). Therefore, we first investigated the relationship between galectin-3 and C/EBP. LacZ- or galectin-3–overexpressing SNU-638 cells were transfected with a reporter plasmid containing the C/EBP-binding sequence in the luciferase promoter. The transcriptional activity of C/EBP increased significantly in galectin-3–overexpressing cells, compared with LacZ-overexpressing cells (Fig. 7B). In addition, C/EBP luciferase activity was increased with endogenous galectin-3 expression in AGS cells and decreased in galectin-3–knockdown MKN28 cells (Supplementary Fig. S2B). Second, we examined the regulation of C/EBP expression by galectin-3, in galectin-3–regulated MKN28, AGS, and SNU-638 cells (Supplementary Fig. S3). The expression of C/EBP was unaltered in galectin-3–regulated gastric cancer cells. Therefore, we considered the possibility of another mechanism by which galectin-3 regulates C/EBP activity without altering the expression level. Third, using immunoprecipitation studies, we determined a direct interaction of galectin-3 with C/EBPβ transcriptional factor (Fig. 7C). Moreover, we confirmed that C/EBPβ binding motif is present in the (−373 bp to −121 bp) promoter region of HMMR using ChIP assay (Fig. 7D). Finally, the nuclear and cytoplasmic fractions were separated to confirm the intracellular location. C/EBPβ levels were higher in the nuclear fraction in galectin-3–overexpressing cells compared with LacZ-overexpressing cells (Fig. 7E). We observed increased HMMR expression upon C/EBPβ overexpression (Supplementary Fig. S4). These results suggested that galectin-3 interacts with C/EBPβ and facilitates its binding to HMMR promoter, thereby increasing HMMR expression by transcriptional regulation.

Figure 7.

Effect of galectin-3–mediated HMMR expression via interaction with transcription factor C/EBPβ. A, Schematic model of the interaction of HMMR promoter with the transcription factor binding site of C/EBPβ. A prediction program (TRANSFAC Public 6.0) was used to identify transcription factors binding to the HMMR promoter. B, Detection of C/EBPβ transcriptional activity using luciferase assay in SNU-638 cells infected with lentivirus containing LacZ or galectin-3. C, Immunoprecipitation (IP) was performed and galectin-3 and C/EBPβ were detected by Western blot analysis. D, ChIP assay was performed as described in “Material and Methods.” Total genomic DNA in the input lane was used as a control for the PCR. E, Nuclear extraction was performed in SNU-638 cells stably overexpressing LacZ and galectin-3. Localized protein levels of galectin-3 and C/EBPβ were confirmed by Western blot analysis. Whole-cell lysates were used as positive control.

Figure 7.

Effect of galectin-3–mediated HMMR expression via interaction with transcription factor C/EBPβ. A, Schematic model of the interaction of HMMR promoter with the transcription factor binding site of C/EBPβ. A prediction program (TRANSFAC Public 6.0) was used to identify transcription factors binding to the HMMR promoter. B, Detection of C/EBPβ transcriptional activity using luciferase assay in SNU-638 cells infected with lentivirus containing LacZ or galectin-3. C, Immunoprecipitation (IP) was performed and galectin-3 and C/EBPβ were detected by Western blot analysis. D, ChIP assay was performed as described in “Material and Methods.” Total genomic DNA in the input lane was used as a control for the PCR. E, Nuclear extraction was performed in SNU-638 cells stably overexpressing LacZ and galectin-3. Localized protein levels of galectin-3 and C/EBPβ were confirmed by Western blot analysis. Whole-cell lysates were used as positive control.

Close modal

Various biomarkers for gastric cancer have been discovered; however, gastric cancer has high incidence, metastasis rate, and mortality, with low 5-year survival rate (7, 34, 35). This could be due to lack of efforts to identify potential targets, as well as studies to delineate the underlying mechanisms of metastasis and tumor progression (8–10). In this study, we identified HMMR, a regulator of gastric cancer cell proliferation, colony formation, migration, and invasion, as one of the targets for motility and progression. Although previous studies showed high HMMR expression in various cancers, including gastric cancer, the focus of these reports was on the activation of HMMR. Therefore, we studied the role of HMMR and its mechanisms of regulation in gastric cancer, using carefully designed experiments, conducted and verified in three parts.

In the first part, we confirmed HMMR upregulation in patients with gastric cancer by analyzing publicly available cDNA microarray data, which indicated that high HMMR expression in patients correlated with poor survival prognosis from the database. As expected, HMMR knockdown significantly repressed cell proliferation, migration, and invasion in AGS and MKN28 cells, whereas HMMR upregulation enhanced the cell proliferation, migration, and invasion abilities of AGS and MKN28 cells. The results from the first part verified the role of HMMR in gastric cancer cell progression and motility.

In the second part, we examined the relationship between galectin-3 and HMMR in gastric cancer. To understand the upregulated expression of HMMR in gastric cancer, we probed for cell motility–related genes in gastric cancer. Previously, we reported fascin-1 and PAR-1 as cell motility–related genes that were regulated by galectin-3 (26, 28). In addition, galectin-3 was highly expressed and had multiple functions in gastric cancer (25). Therefore, the relative expression of galectin-3 and HMMR in gastric cancer was examined, and the results showed a correlation between galectin-3 and HMMR. cDNA microarray analysis showed significant downregulation in HMMR expression levels in galectin-3–knockdown cells. These results suggest that HMMR is regulated by galectin-3 in gastric cancer cells.

For the third part, we examined the regulation of HMMR by the association between galectin-3 and C/EBPβ. Galectin-3 regulates the expression of various genes via transcription factors involved in the progression of various cancers, including gastric cancer (36–38). Therefore, we checked for transcription factor–binding sites in the HMMR promoter region using TRANSFAC Public 6.0, a transcription factor–binding site prediction program. Among many transcriptional factors, we chose the AP-1 complex and C/EBPβ. An earlier study has reported the relationship between galectin-3 and AP-1 complex in gastric cancer progression (28). In 3T3L-1 cells, C/EBPβ was regulated upon galectin-3 silencing, mediated by PPARγ (39). Furthermore, the transcription factor C/EBP, regulated by galectin-3BP, promotes tumor progression in various cancers (29, 40, 41). The luciferase assay showed that C/EBP had higher transcriptional activity than AP-1 complex in galectin-3–overexpressing cell lines (Supplementary Fig. S2A). Therefore, we focused on the function of C/EBPβ in gastric cancer.

In this study, we examined the mechanism by which galectin-3 regulates C/EBPβ in gastric cancer cell lines. We performed loss-of- and gain-of-function experiments using galectin-3 siRNA and overexpression vector, and showed that there was no change in the expression of C/EBPβ, and the results were different in adipocyte cells (39). However, using immunoprecipitation analysis, we confirmed the interaction of galectin-3 with C/EBPβ. As expected, the transcriptional activity of C/EBPβ was induced in the presence of galectin-3. Furthermore, overexpression of galectin-3 induced the nuclear localization of C/EBPβ and binding to the HMMR promoter. Moreover, we showed that C/EBPβ induced HMMR mRNA and protein expression levels. These results strongly support that C/EBPβ promotes gastric cancer cell motility by regulating HMMR expression. In addition, galectin-3 controlled HMMR expression levels and its role in gastric cancer cell progression and motility by activating C/EBPβ.

In conclusion, our results suggest that HMMR increases gastric cancer cell proliferation and motility. HMMR expression is highly regulated in gastric cancer by interaction with galectin-3 and C/EBPβ. Our results also showed the essential role of HMMR in gastric cancer progression and suggested that HMMR was a potential therapeutic target to control gastric cancer metastasis and progression.

No potential conflicts of interest were disclosed.

Conception and design: K.-H. Chun, S.-J. Kim

Development of methodology: H.-G. Kang, S.-J. Kim

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): H.-G. Kang, W.-J. Kim, S.-J. Kim

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): H.-G. Kang, K.-H. Chun, S.-J. Kim

Writing, review, and/or revision of the manuscript: H.-G. Kang, W.-J. Kim, H.-G. Kang, K.-H. Chun, S.-J. Kim

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): S.-J. Kim

Study supervision: S.-J. Kim

This work was supported by the National Research Foundation (NRF) of Korea grants, funded by the Korean government (NRF-2017R1C1B2005265 and NRF-2014M3C7A1046041), The International Research & Development Program of the NRF, funded by the Ministry of Education, Science and Technology of Korea (NRF-2016K1A3A1A47921595). Additional support for this research was from the KBRI basic research program through the Korea Brain Research Institute funded by the Ministry of Science and ICT (19-BR-03-04).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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