Patients with ulcerative colitis have an increased risk of developing colitis-associated colon cancer (CACC). Changes in glycosylation of the oncoprotein MUC1 commonly occur in chronic inflammation, including ulcerative colitis, and this abnormally glycosylated MUC1 promotes cancer development and progression. It is not known what causes changes in glycosylation of MUC1. Gene expression profiling of myeloid cells in inflamed and malignant colon tissues showed increased expression levels of inflammatory macrophage–associated cytokines compared with normal tissues. We analyzed the involvement of macrophage-associated cytokines in the induction of aberrant MUC1 glycoforms. A coculture system was used to examine the effects of M1 and M2 macrophages on glycosylation-related enzymes in colon cancer cells. M2-like macrophages induced the expression of the glycosyltransferase ST6GALNAC1, an enzyme that adds sialic acid to O-linked GalNAc residues, promoting the formation of tumor-associated sialyl-Tn (sTn) O-glycans. Immunostaining of ulcerative colitis and CACC tissue samples confirmed the elevated number of M2-like macrophages as well as high expression of ST6GALNAC1 and the altered MUC1-sTn glycoform on colon cells. Cytokine arrays and blocking antibody experiments indicated that the macrophage-dependent ST6GALNAC1 activation was mediated by IL13 and CCL17. We demonstrated that IL13 promoted phosphorylation of STAT6 to activate transcription of ST6GALNAC1. A computational model of signaling pathways was assembled and used to test IL13 inhibition as a possible therapy. Our findings revealed a novel cellular cross-talk between colon cells and macrophages within the inflamed and malignant colon that contributes to the pathogenesis of ulcerative colitis and CACC.
See related Spotlight on p. 160
Approximately 1.4 and 2.2 million people are affected with inflammatory bowel diseases (IBD) in the United States and Europe, respectively (1, 2). IBD, including ulcerative colitis and Crohn disease, are chronic intestinal inflammation disorders that affect the gastrointestinal tract; namely the colon in ulcerative colitis and anywhere in the gastrointestinal tract in Crohn disease. Patients with ulcerative colitis often present with bloody diarrhea while those with Crohn disease tend to have weight loss and abdominal pain. Histologically, there is a disruption of crypt architecture and inflammatory cell infiltration (3). Patients with ulcerative colitis and Crohn disease have an increased risk of developing colitis-associated colon cancer (CACC). This risk is proportional to the duration and extent of disease, with a cumulative incidence as high as 30% in individuals with longstanding ulcerative colitis and widespread colonic involvement (4).
During tumor initiation and progression, epithelial cells acquire new capabilities that allow them to become tumorigenic and ultimately malignant. Glycosylation changes are one of the most common posttranslational modifications that occur during malignant transformation (5). Among all glycoproteins, mucin-type O-glycans are frequently altered during ulcerative colitis and progression to colon cancer (6–8). The mucin MUC1 is expressed at low levels on the apical surface of normal epithelial cells and is heavily glycosylated in the tandem repeat region of the extracellular domain rich in proline, serine, and threonine residues (9, 10). During colonic malignant transformation, MUC1 is overexpressed and it loses its apical polarity and displays an altered glycosylation profile, becoming predominantly hypoglycosylated (6–8). Aberrant and tumor-associated mucin glycoforms expose long stretches of naked peptide backbone decorated with sialyl-LewisX (SLeX), prematurely terminated monosaccharides (Tn antigens) or disaccharides (T antigens) and their sialylated forms sTn and sT to the immune system (9). We demonstrated that the presence of human MUC1 exacerbates chronic inflammation and induces tumorigenesis in the azoxymethane/dextran sodium sulfate (AOM/DSS) mouse model of CACC (11). Chronic inflammation promotes the expression of aberrant MUC1 glycosylation in colon epithelial cells whereas no or very low expression of hypoglycosylated MUC1 is detected in colon tissues of healthy mice (11).
Altered O-glycans on mucins can result either from mutations in the cell chaperone COSMC or changes in ST6GALNAC1, enzymes involved in the biosynthesis of Tn/sTn glycans (12). An inflammatory microenvironment can also induce changes in the glycan composition of cells via modulation of glycosyltransferases (13, 14).
Tumor-associated macrophages (TAM), by secreting inflammatory cytokines and chemokines, play a key role in tumor initiation, promotion, invasion, and metastasis. During intestinal inflammation, such as ulcerative colitis, macrophages acquire a typical inflammatory phenotype, present antigens, undergo phagocytic activities, and secrete inflammatory cytokines and chemokines thus contributing to ulcerative colitis pathogenesis and progression to CACC (15–17).
Differentiated macrophages are classified into two subpopulations: the classically activated macrophages (M1 phenotype) and the alternatively activated macrophages (M2 phenotype; ref. 18). In vitro studies have shown that upon stimulation with inflammatory factors, IFNγ and lipopolysaccharides (LPS), macrophages polarize to a M1 state and secrete proinflammatory cytokines IL6, IL1β, and TNFα. In contrast, in response to anti-inflammatory signals IL4 and IL13, macrophages polarize to a M2 state, secrete tumor-promoting cytokines such as arginase (Arg)-1, and express the mannose receptor (MR), IL10, and Fizz1 (18). Within tumors, both pro- and anti-inflammatory signals are simultaneously present, resulting in a more complex spectrum of macrophage polarization states (19).
Here, we showed that markers associated with both types of macrophages were highly expressed in ulcerative colitis and CACC tissues. The expression of TAM markers, glycosylation-associated enzymes, and tumor-associated MUC1 glycoforms were assessed in human tissues and in a coculture model system. Computational modeling was carried out to evaluate the involvement of macrophage-induced cytokines in aberrant glycosylation, in particular, in the regulation of glycosyltransferase ST6GALNAC1. A novel regulatory mechanism was discovered involving macrophage-derived CCL17 and macrophage-enhanced IL13 in the induction of ST6GALNAC1 expression in colon cancer cells. Chromatin immunoprecipitation assays of human ulcerative colitis and CACC samples indicated that IL13 via STAT6 directly promoted the transcriptional activity of the ST6GALNAC1 gene. Thus, increased expression of ST6GALNAC1 resulted in the production of the MUC1-sTn glycoform, which is associated with colonic inflammation and cancer. A computational model demonstrated the signaling, cross-talk and dynamics involved in regulating gene expression, and identified a potential therapeutic intervention.
Materials and Methods
Cell culture and reagents
SW480 (ATCC CCL-228) and HT-29 (ATCC HTB-38) cell lines were purchased from ATCC in 2016 and frozen upon initial expansion (<5 passages). Cells were cultured for a maximum of 15 passages in RPMI1640 (Cellgro, Mediatech, Inc.) medium supplemented with 10% heat-inactivated FBS, 100 U/mL penicillin, 100 μg/mL streptomycin, and 2 mmol/L l-glutamine. Both cell lines were regularly tested for Mycoplasma contamination. Cells were not reauthenticated. For specific experiments, IL13 and CCL17 (R&D Systems) were used at 20, 50 100 ng/mL for 24 hours. IL13 neutralizing antibody (JES10-5A2, Thermo Scientific) and CCL17 (AF364, R&D Systems) were used at 1:200 dilution.
Patients and tissue samples
Archived paraffin sections of colonic biopsies of patients with ulcerative colitis in remission (noninflamed), with active disease, and those with colitis-associated colon cancer were selected and collected in the Department of Gastroenterology, University of Pittsburgh (Pittsburgh, PA). The study was approved by the institutional review board (IRB) of the University of Pittsburgh (PRO16090194). Chart review to identify patients who had biopsy samples during colonoscopy and/or surgery was performed. To perform IHC staining, a waiver of consent was requested.
Fresh colon tissues were obtained under the approved IRB PRO19070174. Patients had previously provided a signed informed consent at the time their tissue was collected. Tissues were processed and stored in under standard operating procedures of the Pittsburgh Biospecimen Core.
Plasmids and transfection
The cDNA for ST6 N-Acetylgalactosaminide Alpha-2,6-Sialyltransferase 1 (ST6GALNAC1) was subcloned into the pcDNA3 plasmid vector (Invitrogen; ref. 20). Empty vector was used as the negative control. Transfections were performed with Lipofectamine 3000 (catalog no. L3000008, Thermo Fisher Scientific) according to the manufacturer's instructions.
The following primary antibodies were used: anti-p65 (sc-8008), anti-pp65 (sc-166748), anti-IκBα (sc-1643), anti-MUC1 VU-4H5 (sc-7313, Santa Cruz Biotechnology), anti-ST6GALNAC1 (PA5-31200 and 15363-1-AP), anti-IL13 (AHC0132), anti-actin (MA5-11869, Thermo Fisher Scientific), anti-MUC1 5E5 (TAB-418MZ, Creative Biolabs), anti-CD163 (NBP2-36494, Novus Biologicals), anti-CCL17 (ab182793), anti-sialyl Tn, clone sTn 219 (ab115957), anti-CD68 (ab955), anti-CD86 (ab53004, Abcam), anti-AKT (C67E7, #4691), anti-p-AKT (D9E, #4060), p-STAT1 (D4A7, #7649), p-STAT3 (D3A7, #9145), and p-STAT6 (D8S9Y, #56554, Cell Signaling Technology).
Total proteins from human colon tissues and cancer cell lines were extracted using RIPA buffer (150 mmol/L NaCl, 0.5 sodium deoxycholate, 0.1% SDS, 1% NP-40, and 50 mmol/L Tris-HCl) with commercial protease inhibitors (Complete Protease Inhibitor Cocktail, Roche) and phosphatase inhibitors (Phosphatase Inhibitor Cocktail II, Sigma-Aldrich). Proteins were separated by SDS-PAGE and transferred to polyvinylidene difluoride membranes. Blots were incubated with the primary antibodies indicated above. Immunoblots were developed with m-IgGκ BP-HRP (sc-516102) or mouse anti-rabbit IgG-HRP (sc-2357, Santa Cruz Biotechnology) and chemiluminescence reagents (SuperSignal West Pico Substrate, catalog no. #34580, Pierce). Intensity of signals was determined by densitometric scanning (Kodak, Image Station 4000MM). Densitometry of Western immunoblotting results was performed using ImageJ software.
IL13 concentrations in the conditioned medium of HT-29 or SW480 cancer cells cocultured with M1 or M2 macrophages were measured using a human ELISA kit (DY213, BD Biosciences) following the manufacturer's protocol. Monocultures of HT-29 or SW480, M1, and M2 cells were used as control. IL13 concentrations detected were within the range of the standard curve. All points were done in triplicate, and the experiments were repeated three times. Samples were read in a microplate reader (Infinite 200 Pro, Tekan).
Immunofluorescence confocal microscopy
Cultured cells were fixed in 4% paraformaldehyde for 20 minutes and permeabilized in 0.5% Triton-X100 for 20 minutes. The fixed tissues or cells were incubated with primary antibodies for 1 hour at room temperature followed by secondary anti-mouse Alexa-488 or Cy3 antibody (Invitrogen Life Technologies) for 1 hour at room temperature. Antibodies were diluted in 1% BSA. Nuclei were stained with mounting medium containing DAPI (Vector Laboratories). Confocal images were captured on an Olympus Fluoview 1000 confocal microscope.
Slides were deparaffinized by baking overnight at 59°C. Endogenous peroxidase activity was eliminated by treatment with 30% H2O2 for 15 minutes at room temperature. Antigen retrieval was performed by microwave heating in 0.1% citrate buffer for 10 minutes at 850 V. Nonspecific binding sites were blocked with 2% BSA. Reaction with anti-CD163, anti-CD68, anti-CD86, anti-sTn, anti-ST6GALNAC1 (listed above) was for 16 hours at 4°C. Staining was performed by the avidin–biotin–peroxidase complex method with a commercial kit (PK4000, Vectastain ABC HRP kit; Vector Laboratories) according to the manufacturer's protocol. Positive signals were visualized by a DAB Substrate Kit (catalog no. 550880, BD Pharmingen) according to the manufacturer's protocol. The total inflammation score for each sample was determined as described previously (8). For double staining IHC, ImmPRESS duet staining HRP/AP polymer kits, anti-rabbit IgG-brown, and anti-mouse IgG red was used (MP-7714, Vector Laboratories) according the manufacturer's protocol. Histology sections were observed using an Olympus BX40 microscope. Images were acquired using a Leica DFC420 camera and Leica Application Suite version 2.7.1 R1.
Migration and invasion assay
Migration studies were conducted using 24-well Transwells, 8-μm pore size (Costar Transwell; Corning Inc.). In each well, 4 × 104 HT-29 or SW480 cells were plated into the top chamber in serum-free medium, whereas 700 μL of 5% FBS-containing medium was placed in the bottom chamber. After 16 hours, cells remaining in the top chamber were removed using cotton swabs. Cells adhering to the bottom surface were fixed with 4% paraformaldehyde for 20 minutes and stained with Crystal Violet 1%. Cells were then counted in five different fields using a microscope at 40× magnification.
Peripheral blood monocyte isolation and macrophage differentiation
Peripheral blood mononuclear cells (PBMC) were freshly isolated by density-gradient centrifugation using Ficoll Paque Plus (Sigma-Aldrich) for 50 minutes at 400 × g. At least 20 deidentified human Buffy Coat samples purchased from the Pittsburgh Central Blood Bank (or Vitalant) fulfilling the basic exempt criteria 45 CFR 46.101(b) (4) in accordance with the University of Pittsburgh IRB guidelines. Monocytes were then isolated with CD14+ microbeads (MACS Miltenyi) and incubated for 5 days in RPMI/10%FCS and 1% penicillin/streptomycin solution (Sigma) supplemented with 25 ng/mL human M-CSF (R&D Systems) to stimulate macrophage differentiation. Macrophages were then washed and primed by incubating with RPMI media supplemented with 100 ng/mL IFNγ (R&D Systems) or 50 ng/mL IL4 and IL13 (R&D Systems) for 24 hours to drive M1 or M2 polarization, respectively (21). Unprimed macrophages were incubated with nonsupplemented RPMI media. By adding 20 ng/mL LPS to media containing priming stimuli for another 24 hours, M1 and M2 macrophages were activated. Cells were thoroughly washed in PBS before being transferred to coculture with colon cancer cells.
Indirect coculture assay
CD14+ monocytes were differentiated in Transwell insert dishes (Corning) as described above. After differentiation into M1 and M2, macrophages were washed three times with RPMI and then placed in 6-well plates where HT-29 or SW480 cells (2 X 105 cells/wells) were preplated the day before in RPMI media. Macrophages and colon cancer cells were cocultured for 48 hours in RPMI media.
Cytokine and chemokine expression detection
Bead-based multiplex assay panel.
The supernatants of HT29 and SW480 cells, M1 and M2 macrophages, and the conditioned medium of HT-29 cells cocultured with macrophages were tested for cytokines and chemokines using the Legendplex human inflammation 10-plex panel (BioLegend LEGENDplex catalog no. 740508) for IL1β, IL1RA, TNFα, IP-10, IL6, IL10, IL12p70, IL12p40, CCL17, and IL23. Samples were treated following the manufacturer's instructions, measured with a FACS LSRFortessa (BD Biosciences), and analyzed with FlowJo v.10 software.
Human cytokine array
Supernatants and condition medium were also analyzed using a cytokines array (Raybiotech, AAH-CYT-5-2). The procedure was performed according to the manufacturer's instructions. Membranes were developed, and the dots were quantified using Image J plug-in protein array analyzer according to the developer's instructions (http://image.bio.methods.free.fr/ImageJ/?Protein-Array-Analyzer-for-ImageJ.html).
Gene expression profiling
Total RNA from colon tissues of patients with no inflammation (control, n = 3), active, and severe ulcerative colitis (inflamed, n = 3), CACC (n = 3) was isolated using RNeasy Micro Kit (Qiagen) following the manufacturer's instructions. The myeloid innate immune response was examined using the nCounter Human Myeloid Innate Immunity Panel v2 (NanoString Technologies). The protocol was carried out at the University of Pittsburgh NanoString facility using 80 ng of total RNA from each sample following their commercial protocol. Data were analyzed using the NanoStringDiff R-package, following the procedure described in the package's instructions (22). Normalization of mRNA content, for heatmap visualization purposes, was performed by using the NanoString Data Normalization function, which adjusts for positive control size factors, background noise, and housekeeping genes size factors. Differentially expressed genes were detected by using the glm.LRT function. P values were adjusted for multiple comparison using the procedure of Benjamini and Hochberg. A gene was considered significantly overexpressed if associated with an adjusted P < 0.01 and a logFC > 1.
Chromatin immunoprecipitation assay
The chromatin immunoprecipitation assay was performed on frozen human colon tissues, utilizing the commercially available ChromaFlash High Sensitivity ChIP Kit (catalog no. P-2027, Epigentek), according to the manufacturer's instructions. Cells were fixed with 1% formaldehyde for 10 minutes at 37ºC. Chromatin was precipitated with 4 μg of anti-pSTAT6 (Thermo Fisher Scientific) or anti-p-p65 (Santa Cruz Biotechnology) at 4°C overnight. The presence of ST6GALNAC1 gene promoter sequences in immunoprecipitated DNA was identified by RT-PCR using the following primer sequences: F1: AGTTGGATCTGGACCCCAAG, R1: CACGTATGAGGGCTCACTCT; F2: CCCTCATACGTGCTGGTCAT, R2: AACCCATCTGCCGCCATATAA. In control samples, primary antibody was replaced with nonimmune IgG. All experiments were repeated at least three times.
Quantitative real-time PCR
Total RNA was extracted from colon cancer cell lines, murine and human colon tissues using QIAshredder (catalog no. 79654) and RNeasy Mini Kit (catalog no. 74104, Qiagen) according to the manufacturer's instructions. RNA was measured using a Gen5 microplate reader (Biotek). A total of 2 μg of RNA was reverse-transcribed using the RT2 HT First Strand Kit (cat. 330411, Qiagen). A total of 4 μL of RT products was used to amplify ST6GALNAC1 and GAPDH as an internal control. Real-time PCR was performed using a SYBR Green PCR kit (Qiagen) and a StepOnePlus realtime PCR system (Applied Biosystems). Gene expression was determined using the 2−ΔCt. All experiments were repeated three times in triplicate.
Gene expression profiling of glycosylation-associated enzymes
Gene expression profiling of human glycosylation was performed using the RT2 Profiler PCR Array (PAHS-046Z, Qiagen). This PCR array is a 96-well plate containing the RT2 Profiler PCR Primer Assays for a set of 84 related genes, plus five housekeeping genes and three controls. Data analyses were performed using the web-based analysis software found at https://geneglobe.qiagen.com/us/analyze/.
Differences between two conditions were analyzed by the Student t test or one-way ANOVA with Tukey post-tests for multiple pairwise comparisons. In all cases, P < 0.05 was considered statistically significant. Statistics were calculated with Prism software (GraphPad).
Computational modeling and simulation
The protein interactions involved in signaling pathways investigated in this study were collected from the literature and entered using the BioRECIPES tabular format (23), a model representation format that includes the name, type (protein, gene or a chemical), cellular location, number of possible discrete states, and formatted list of regulators for each model element. Three levels were used to represent activation or inhibition of elements. Level 0 was if the element has low activity, level 1 was if the element has moderate activity, and 2 was if the element has high activity. All elements were initialized to 0 except input cytokines that were set to match experimental conditions. From the tabular representation, an executable discrete model was created using the element update functions generated from the formatted regulator lists. Simulations of the model were performed using the publicly available stochastic simulator, DiSH (24). Different experimental conditions, scenarios, were defined by assigning initial values to all model elements, and a set of inputs for scenarios of normal, UC, CACC, and IL13 inhibitor. Many independent runs of the scenario represent multiple cells in an experiment that have the same starting point but traverse through time steps differently. From these individual simulation runs, we computed average trajectories to plot and visualize element behavior over time.
Increased macrophage-associated markers in colonic inflammation and colon cancer
To investigate changes in the innate immune-related genes during progression from ulcerative colitis to CACC, 770 genes involved in the innate immune response were profiled using the NanoString nCounter Human Myeloid Innate Immunity Panel. Tissue samples of noninflamed colon of patients with ulcerative colitis (Control) were compared with severe active ulcerative colitis and CACC (Supplementary Fig. S1A). Increased expression of seven genes was unique to ulcerative colitis and of 221 genes was unique to CACC, with 45 genes upregulated in both ulcerative colitis and CACC (Fig. 1A). Upregulated genes were defined as having a log fold change of expression >1 as compared with those in control tissues.
Cytokines and chemokines involved in macrophage chemotaxis were significantly upregulated in ulcerative colitis and CACC samples. In particular, S100A8, S100A9, and VEGF-A, known to mediate the migration of macrophages to the tumor site (23), were upregulated both in ulcerative colitis and CACC (Fig. 1B). Expression levels of macrophage-attracting cytokines and chemokines CCL2, CCL19, and CCL21 were significantly higher in CACC (Fig. 1B). These data suggest that macrophages were recruited and continued to accumulate during inflammation and tumor progression. Genes associated with the a proinflammatory (M1-like) phenotype, including NOS2, TNFA, IL1A, and IL23 were significantly upregulated in ulcerative colitis samples when compared with control and CACC samples (Fig. 1C). The expression of genes linked with an anti-inflammatory (M2-like) phenotype, such as IL6, IL1R1, IL13, CD163, CCL17, and TGFβ were upregulated in both inflamed tissue and tumor samples (Fig. 1C). Notably, some of the M2-associated markers, including CD163, IL6, and IL13 were higher in CACC samples compared with ulcerative colitis samples suggesting a potential role of M2-like cells in CACC promotion.
To further examine the involvement of inflammatory macrophages in inflammation leading to colon cancer, the abundance of infiltrating macrophages in human ulcerative colitis (n = 10) and CACC (n = 8) tissues was evaluated. Tissues collected from patients with ulcerative colitis in remission with no evidence of disease (n = 10) were used as controls. Biopsies were taken from left colon and rectum regions. IHC was performed using anti-CD68 antibody that recognizes all macrophages, anti-CD86 antibody that recognizes M1-like macrophages, and anti-CD163, a well-known marker of M2-like macrophages (18). The number of CD68+, CD86+, and CD163+ cells increased in ulcerative colitis and CACC samples compared with control (Fig. 1D–G). Importantly, the ratio of CD163+/CD68+ was significantly higher in both ulcerative colitis and CACC than in controls (Fig. 1I; Supplementary Data S1B).
Exposure to M2 macrophages induced epithelial ST6GALNAC1 and sTn-MUC1 expression
Having observed that tissue-infiltrating macrophages in ulcerative colitis and CACC are located adjacent to epithelial cells (Fig. 1D), we postulated that these macrophages and epithelial cells may communicate. Using changes in MUC1 as a potential biomarker of this interaction, we investigated in a transwell coculture system whether macrophage-secreted factors could influence the status of MUC1 glycosylation in human colon tumor cells. Freshly isolated human peripheral blood monocytes cultured in transwell inserts were differentiated and polarized into M1 (IFNγ + LPS) or M2 (IL4 + IL13) macrophages. After 24 hours, the inserts containing macrophages were added to transwells containing HT-29, a colon tumor cell line that has been used to study mature intestinal cells, IBD, CACC, and colon cancer (24–26).
Aberrant glycosylation of MUC1 can result from aberrant glycosyltransferase activity and therefore, we first studied the ability of macrophages to modulate the expression of glycosyltransferases. An RT2 Profiler PCR array of 84 glycosylation-associated genes was performed in HT-29 cells cocultured with macrophages. HT-29 cells cultured alone were used as a control. The gene array revealed a distinct glycosyl/fucosyl/sialyl-transferase expression profile in HT29 cells after coculture with macrophages (Fig. 2A). Exposure to M1 or M2 macrophages induced up- or downregulation of 24 and 17 genes, respectively, when compared with control HT-29 cells (Fig. 2B). M1 macrophages promoted the expression of B3GNT4, B3GNT8, EDEM1, GALNT9, GALNT13, GALNT16, MAN2A2, POMT1, ST8SIA2, and ST8SIA3 whereas M2 induced the expression GCNT1, GALNT1, MAN2B1, ST6GALNAC1, ST6GAL1, MAN2A1, and MGAT4A. Both M1 and M2 modulated GALNT11, NEU1, MGAT2, and ST3GAL1. We focused on genes that encoded enzymes involved in the initial steps of O-glycan chain elongation, whose activity would lead to shorter and more tumor-associated MUC1 forms (9). One of these enzymes is ST6GALNAC1, a glycosyltransferase that catalyzes the transfer of a sialic acid residue in alpha-2,6-linkage to O-linked GalNAc residues on mucins to form the cancer-associated sialyl-Tn (sTn) antigen (Fig. 2C; ref. 9).
ST6GALNAC1 is overexpressed in gastric, colon, breast, ovarian, and pancreatic cancers (27–31). Western blot analysis confirmed that M2-secreted factors induced a significant upregulation of ST6GALNAC1 protein in HT29 and SW480 colon cancer cells (Fig. 2D).
High expression of ST6GALNAC1 have been associated with tumorigenicity, increased cell proliferation, and migration in different types of cancer cells (32, 33). To evaluate the effect of ST6GALNAC1 overexpression on cell migration capacity, HT-29 and SW-480 cells were transfected with a plasmid for high-level constitutive expression of ST6GALNAC1 (Supplementary Fig. S2A) and analyzed after 48 hours. Then a cell migration assay was performed using a Boyden chamber. The migration rate of ST6GALNAC1-overexpressing HT-29 and SW480 cells was significantly increased compared with cells transfected with the empty vector control (Supplementary Fig. S2B and S2C).
Next, to assess the clinical relevance of M2-like macrophages and ST6GALNAC1 expression in ulcerative colitis and CACC, we performed double IHC staining with anti-CD163 (magenta) and anti-ST6GALNAC1 (brown) antibodies on tissue sections. Representative images are shown in Fig. 2E. ST6GALNAC1 showed a homogenous cytoplasmic staining mainly in the Golgi of glandular cells, it was overexpressed in both inflamed and tumor tissues and was absent or weakly stained in noninflamed tissues (Fig. 2E and F). Tissues characterized by high accumulation of CD163+ macrophages overexpressed ST6GALNAC1 (Fig. 2E), whereas small areas of inflamed or cancer tissues with low abundance of CD163+ cells presented low expression of ST6GALNAC1 (Fig. 2G).
To determine whether M2 macrophages induced ST6GALNAC1 in HT-29 cells results in the induction of the MUC1-sTn glycoform, confocal immunofluorescence was performed using anti-MUC1 5E5 that recognizes MUC1-Tn/sTn structures, and anti-MUC1 CT2 that recognizes the cytoplasmic tail of MUC1. Our results showed that MUC1-Tn/sTn expression was increased upon coculture with M2 macrophages when compared with M1 or HT-29 alone (Fig. 3A). To detect the amount of M2-induced MUC1-sTn in HT-29 cells, we performed a coimmunoprecipitation (co-IP) assay. Specifically, protein lysates, extracted from HT-29 cells cocultured with M1 and M2 macrophages were immunoprecipitated with anti-MUC1 5E5 and then immunoblotted with anti-sTn (sTn 219), which displayed a strong band around 150 kDa (Fig. 3B). This assay confirmed that M2 macrophage exposure specifically induced higher expression MUC1-sTn in HT-29 cells compared with M1 and no macrophage samples.
The expression of MUC1-sTn was also evaluated in inflamed ulcerative colitis and CACC tissues by performing an IHC staining with anti-MUC1 5E5 and anti-sTn (sTn 219). All samples expressing the sTn antigen also showed positive staining with MUC1 5E5 (Fig. 3C–E). Altogether, our results demonstrate over-expression of MUC1-sTn in human ulcerative colitis and CACC samples.
M2-induced ST6GALNAC1 expression is mediated by IL13 and CCL17
To explore the mechanism by which M2 macrophages increased the expression of glycosylation-associated enzymes, we used a human cytokine array containing antibodies against 80 cytokines. Cytokine profiling was conducted on the conditioned medium (CM) of HT-29 colon cancer cells cocultured with M1 or M2 macrophages and compared with HT-29, M1 and M2 macrophages cultured alone (Fig. 4A). IL13 and CCL17 emerged as the most upregulated cytokines in the CM of HT-29 cocultured with M2 macrophages (Fig. 4A). M1/M2 multiplex cytometric bead and ELISA assays further confirmed the increase of IL13 and CCL17 in the CM from HT-29 colorectal cancer cells cocultured with M2-polarized macrophages (Fig. 4B and C). The CM of M2 and SW480 colon cancer cell line, showed a similar cytokine profile (Supplementary Fig. S3A and S3B). IL13 was higher in the CM of the coculture compared with M2 alone indicating that M2-exposed colon cancer cells secreted IL13 or stimulated increased macrophage secretion of IL13. As previously reported (34, 35), M2 macrophages secreted the chemokine CCL17, whereas colon cancer cells did not (Fig. 4A and 4B). Levels of CCL17 were slightly lower in HT29-M2 coculture compared with monocultures. As HT-29 express CCR4 (36), the receptor of CCL17, this result could suggest that cells might consume this cytokine.
To confirm IL13 and CCL17 mediated the increased expression of ST6GALNAC1, HT-29 and SW480 colon cancer cells were incubated with neutralizing antibodies against IL13 or CCL17 during coculture with M2 macrophages. Inhibition of IL13 or CCL17 significantly decreased ST6GALNAC1 mRNA levels almost to baseline in both cell lines (Fig. 4D and E). This result was confirmed by Western blotting (Fig. 4D and E). To further substantiate the role of these cytokines in the control of ST6GALNAC1 expression, 20, 50, or 100 ng/mL of exogenous recombinant IL13 or CCL17 were added for 16 hours to the culture medium of HT-29 and SW480 cells. Both IL13 and CCL17 increased the expression of sTn form as well as ST6GALNAC1 protein and mRNA expression in HT-29 (Fig. 4F and G) and SW480 cells (Supplementary Fig. S3C–S3E).
IL13 increased ST6GALNAC1 expression in colon cancer cells through p-STAT6
Given our observation that IL13 and CCL17 were both involved in the increased expression of ST6GALNAC1 in response to M2-like macrophages, we investigated the intracellular signaling that could mediate this effect. First, using real-time PCR, we analyzed IL13 expression in colon tissues of patients with ulcerative colitis and CACC. IL13 gene expression was significantly increased in highly inflamed and tumor tissues (Fig. 5A). IL13 is known to activate transcriptional activity of target genes via phosphorylation of STAT6 (37, 38). P-STAT6 was highly expressed in HT-29 cells cocultured with M2 macrophages, whereas it was not detected in HT-29 cocultured with M1 macrophages or HT-29 cells cultured alone (Fig. 5B, top). Furthermore, IL13 addition to HT-29 cells significantly increased p-STAT6 (Fig. 5B, bottom). Next, we assessed whether IL13-pSTAT6 mediated ST6GALNAC1 transcriptional activity in ulcerative colitis and CACC. The Motif Map system was used to identify consensus-binding motifs for p-STAT6 (39). Two consensus elements were detected: NNYTTCYH (AC(T)TTCT(C)) and NDDTTCNN (TA(T)T(A)TTCC) (Fig. 5C). These regulatory elements were found in the ST6GALNAC1 promoter at –444 (TATTCC) and –17 (CCTTCCT) of the transcription start site. To confirm the association of p-STAT6 with the ST6GALNAC1 promoter, we performed a chromatin immunoprecipitation (ChIP) assay. Briefly, chromatin was isolated from colon tissues from ulcerative colitis (n = 4) and CACC (n = 4) patients and immunoprecipitated with an anti-p-STAT6 Ab. The immunoprecipitated chromatin was then amplified using two sets of primers spanning from −175 to +3 and from −540 to −352. Our results showed that p-STAT6 associated with ST6GALNAC1 promoter with highest affinity toward the CCTTCCT element (Fig. 5D).
CCL17 activated ST6GALNAC1 expression in a p65-dependent manner
Real-time PCR indicated upregulation of CCL17 in ulcerative colitis and CACC samples compared with the control tissues (Fig. 5A). To test whether CCL17 signaling pathway and IL13 signaling pathway both mediate their effects via p-STAT6, we checked the state of STAT6 activation in CCL17-treated HT-29 cells. Unlike in IL13-treated HT-29, we saw no activation of pSTAT6 (Fig. 5E). As AKT and STAT3 were abundantly phosphorylated in HT-29 cocultured with M2 macrophages (Fig. 5F), we analyzed the expression of p-STAT3 and p-AKT in CCL17-treated cells and found that CCL17 induced only p-AKT (Fig 5G). The PI3K–AKT signaling pathway can activate NF-κB, p65 through activation of IKK and p-IκB-α (40). We investigated whether CCL17 stimulation induced the expression of p-IκB-α and p-p65 in HT-29 cancer cells. Our results revealed that CCL17 induced phosphorylation and activation of IκB and p65 (Fig. 5G). One κb consensus motif (GGRNKTYCCCHN; Fig. 5H) was found on the ST6GALNAC1 promoter from −33 to −21 (GGAGTTTCCCTT). ChIP assay confirmed the association of p-p65 with the ST6GALNAC1 promoter in human ulcerative colitis and CACC samples (Fig. 5I).
Computational model of activated signaling pathways and ST6GALNAC1 in urolithelial colitis and CACC
We assembled a computational model that incorporated our experimental data and what has been reported in the literature to simulate signaling pathways potentially involved in the development of urothelial colitis and CACC (Supplementary Table S1). The granular modeling framework utilized a standardized tabular framework (41) and the DiSH simulator (42). In this modeling approach, discrete elements change state depending on the influences of positive or negative regulators. The inputs were ligands present in the tumor microenvironment (Fig. 1C) that stimulated signaling cascades to influence the ST6GALNAC1 gene and MUC1 protein of colon cells (Fig. 6A). The stochastic simulation results reflected the experimental results for the normal, ulcerative colitis, and CACC scenarios, when microenvironment signaling ligands were used as inputs (Fig. 6B and C). Higher IL13 and CCL17 observed in M2 coculture with HT-29 cells and CACC resulted in increased transcription of ST6GALNAC1 and MUC1 sTn mediated by p-STAT6 and p65. Introduction of an IL13 inhibitor resulted in decreased sTn only when introduced to ulcerative colitis and not CACC, suggesting early intervention as a therapeutic strategy (Fig. 6D). The model had IL6 and IL13 activating STAT6; however, IL6 was present in CACC and therefore the IL13 inhibitor alone did not prevent ST6GALNAC1 transcription as the model still predicted its expression would occur downstream of IL6. The computational model also indicated the IKK/IKB/P65 pathway was active in the presence of IL13 and CCL17 regulating the PI3K/AKT pathway through inhibition of PTEN. Further development of this model will allow for a more detailed investigation of the regulation of the signaling pathways.
In this study, we have uncovered novel regulatory axes between macrophages and colon cells involved in ulcerative colitis and CACC. Our results indicated that CCL17 and IL13, present in ulcerative colitis and CACC and produced by M2 macrophages cocultured with colon cells, induced activation of multiple oncogenic pathways including AKT and STAT6. CCL17 and IL13 also induced aberrant overexpression of the ST6GALNAC1 glycosyltransferase that lead to an increase in expression of the tumor glycoform MUC1-sTn.
An abundance of infiltrating anti-inflammatory (M2-like) macrophages in the tumor microenvironment is generally associated with poor prognosis and lymph node metastasis of laryngeal squamous cell carcinoma, breast, gastric, ovarian, and colon cancer (43–46) suggesting involvement in tumor progression. Macrophages are highly plastic and able to change their phenotype and function according to the surrounding environment. In normal epithelium, macrophages are located just beneath the intestinal epithelial layer to perform surveillance activities (47). Tissue-infiltrating macrophages are also involved in the pathogenesis and the chronicity of ulcerative colitis and progression to CACC (47–49). However, many open questions remain regarding the specific mechanisms that are involved with aggravating inflammation and promoting tumorigenesis.
As healthy tissues evolve progressively to a neoplastic state, they acquire new tumorigenic and ultimately malignant potential. A noticeable event during the malignant transformation of epithelial cells is the alteration in glycosylation state of cell surface and secreted glycoproteins (7, 9, 12). We have previously reported that MUC1′s glycosylation pattern is markedly changed during chronic inflammation and CACC (6, 9, 11). In this study we have investigated the role of microenvironment factors in regulating the glycosylation state of MUC1 on inflamed and tumor colon cells.
Our gene expression profiling of myeloid-associated immune response indicated that chemokines and cytokines involved in the recruitment and migratory activities of macrophages are elevated in inflamed and malignant colon tissues. Moreover, analyses of infiltrating macrophages showed that CD163+ cells are significantly increased in both ulcerative colitis and CACC. These data suggest that M2-like macrophages might be involved in ulcerative colitis inflammation and CACC tumor progression.
IL13 is a cytokine markedly elevated in patients with ulcerative colitis produced by natural killer T (NKT) cells, Th 2 cells, and macrophages (50). A previous study reported that, in a murine model of ulcerative colitis, blockade of IL13 prevented development of colitis (51). IL13 modulates epithelial barrier permeability via binding IL13Rα1 and activation of the expression of Claudin-2, a pore-forming tight junction. Here, we expanded the knowledge of the mechanistic role of IL13 in colitis and described its potential role in CACC as well. We showed that IL13 was capable of inducing ST6GALNAC1 expression via phosphorylation of STAT6 in colonic cells. This agrees with other studies showing that the activity of IL13 in colon cancer cells is STAT6 dependent (37, 52) and these findings together with proteins involved in other signaling pathways were incorporated into the computational model.
Considering the role of IL13 in the pathogenesis of ulcerative colitis, various clinical trials have been implemented to target IL13 as a treatment strategy. We can speculate that inhibition of IL13 would result not only in the reduction of colitis but could also prevent tumor progression as shown by the modeling if the inhibitor is implemented during ulcerative colitis.
We also demonstrated that another cytokine is involved in the control of the ST6GALNAC1 of colonic epithelial cells, CCL17, a chemokine produced by macrophages and dendritic cells (34, 35, 53). The receptor for CCL17 in colon cancer cells is CCR4 (36). Our data and computational model also indicated that CCL17 stimulation involved the activation of IκBα and p65 via the AKT pathway. The computational model provided indications for the involvement of NF-κB and also suggested future studies involving VEGF-A signaling. The computational model will allow for rapid, inexpensive testing of multiple scenarios to replace difficult and expensive experiments. Scenarios involving therapeutic interventions, such as inhibiting IL13, and their timing can be performed using our computational model to advance knowledge of complex signaling networks involved in the transition from ulcerative colitis and CACC.
In this report, we also demonstrated that upregulation of ST6GALNAC1 correlated with MUC1-sTn form expression on colon cells of ulcerative colitis and CACC. This is in agreement with previous studies showing that ST6GALNAC1 promotes the synthesis of the tumor-associated MUC1-sTn glycoform in breast and gastrointestinal cancer (54). MUC1-sTn has been associated with tumor progression and cancer (55). In addition, MUC1-sTn glycans might influence immune suppression through inhibition of dendritic cell maturation (56), activity of NK cells (57), and via interaction with macrophage galactose C-type lectin (MGL; ref. 54), which is expressed on immature monocytes and M2-like macrophages. All these events would establish a positive feedback between MUC1-sTn and immune cells that could result in the perpetuation of chronic inflammation of ulcerative colitis and CACC.
Disclosure of Potential Conflicts of Interest
J.G. Hashash reports receiving royalties for chapter writing from UpToDate. D.J. Hartman reports receiving speakers bureau honoraria from Philips and UptoDate (Lippincott Williams & Wilkins). No potential conflicts of interest were disclosed by the other authors.
Conception and design: Y. Ahmed, J.G. Hashash, D.J. Hartman, C.A. Telmer, S. Cascio
Development of methodology: Y. Ahmed, D.J. Hartman, C.A. Telmer, N. Miskov-Zivanov, S. Cascio
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): M. Kvorjak, M.L. Miller, R. Sriram, J.G. Hashash, S. Cascio
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): Y. Ahmed, M.L. Miller, C. Coronnello, D.J. Hartman, C.A. Telmer, N. Miskov-Zivanov, O.J. Finn, S. Cascio
Writing, review, and/or revision of the manuscript: Y. Ahmed, M.L. Miller, C. Coronnello, J.G. Hashash, D.J. Hartman, C.A. Telmer, N. Miskov-Zivanov, O.J. Finn, S. Cascio
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): Y. Ahmed, J.G. Hashash, S. Cascio
Study supervision: S. Cascio
This study was supported by the grants Fondazione Ri.MED (to S. Cascio), NCI 1R35CA210039 (to O.J. Finn), and DARPA W911NF-17-1-0135 (to N. Miskov-Zivanov). The authors thank the Center for Biological Imaging (CBI) of the University of Pittsburgh (NIH grant number 1S10OD019973-01).
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