Skip to main content
NCBI home page
British Journal of Cancer logoLink to British Journal of Cancer
. 2010 Feb 9;102(5):908–915. doi: 10.1038/sj.bjc.6605558

High expression of Toll-like receptor 4/myeloid differentiation factor 88 signals correlates with poor prognosis in colorectal cancer

E L Wang 1,2,8, Z R Qian 1,8,*, M Nakasono 1,3, T Tanahashi 4, K Yoshimoto 5, Y Bando 6, E Kudo 1, M Shimada 7, T Sano 1
PMCID: PMC2833250  PMID: 20145615

Abstract

Background:

The Toll-like receptor (TLR) 4 signalling pathway has been shown to have oncogenic effects in vitro and in vivo. To demonstrate the role of TLR4 signalling in colon tumourigenesis, we examined the expression of TLR4 and myeloid differentiation factor 88 (MyD88) in colorectal cancer (CRC).

Methods:

The expression of TLR4 and MyD88 in 108 CRC samples, 15 adenomas, and 15 normal mucosae was evaluated by immunohistochemistry, and the correlations between their immunoscores and clinicopathological variables, including disease-free survival (DFS) and overall survival (OS), were analysed.

Results:

Compared with normal mucosae and adenomas, 20% cancers displayed high expression of TLR4, and 23% cancers showed high expression of MyD88. The high expression of TLR4 and MyD88 was significantly correlated with liver metastasis (P=0.0001, P=0.0054). In univariate analysis, the high expression of TLR4 was significantly associated with shorter OS (hazard ratio (HR): 2.17; 95% confidence interval (95% CI): 1.15–4.07; P=0.015). The high expression of MyD88 expression was significantly associated with poor DFS and OS (HR: 2.33; 95% CI: 1.31–4.13; P=0.0038 and HR: 3.03; 95% CI: 1.67–5.48; P=0.0002). The high combined expression of TLR4 and MyD88 was also significantly associated with poor DFS and OS (HR: 2.25; 95% CI: 1.27–3.99; P=0.0053 and HR: 2.97; 95% CI: 1.64–5.38; P=0.0003). Multivariate analysis showed that high expressions of TLR4 (OS: adjusted HR: 1.88; 95% CI: 0.99–3.55; P=0.0298) and MyD88 (DFS: adjusted HR: 1.93; 95% CI: 1.01–3.67; P=0.0441; OS: adjusted HR: 2.25; 95% CI: 1.17–4.33; P=0.0112) were independent prognostic factors of OS. Furthermore, high co-expression of TLR4/MyD88 was strongly associated with both poor DFS and OS.

Conclusion:

Our findings suggest that high expression of TLR4 and MyD88 is associated with liver metastasis and is an independent predictor of poor prognosis in patients with CRC.

Keywords: TLR4, MyD88, colorectal cancer, prognosis

Colorectal cancer (CRC) is the fourth leading cause of cancer-related death in the world and the third leading cause in the United States (Jemal et al, 2009). In Japan, the incidence of CRC has doubled over the past 20 years, and it was the second leading cause of cancer-related death during that period (Tsukuma et al, 2004). Although recent advances in chemotherapy have prolonged the survival of patients with advanced disease, the results are still unsatisfactory, and further research is required to understand the disease and improve its outcome (Wolpin et al, 2007; Wolpin and Mayer, 2008).

Toll-like receptors (TLRs) expressed on immune cells have a critical role in immune responses against invading pathogens (Akira et al, 2006). At least 11 mammalian TLRs have been identified and are involved in recognition by immune and non-immune cells of pathogen-associated molecular patterns, such as lipopolysaccharides (LPSs), viral double-stranded RNA, and unmethylated CpG islands (Akira et al, 2006). The TLRs transmit signals through one or more of four adaptor proteins, namely, myeloid differentiation factor 88 (MyD88), MyD88 adaptor-like, Toll/IL1R domain-containing adaptor molecule inducing interferon-β, and TRIF-related adaptor molecule (Rakoff-Nahoum and Medzhitov, 2009). Stimulation of TLR leads to the activation of nuclear factor-κB (NF-κB) and mitogen-activated protein kinases, which are essential for the classical outcomes of TLR activation: host innate and adaptive immune responses (Rakoff-Nahoum and Medzhitov, 2009). Toll-like receptor-mediated activation of innate or adaptive immunity may be used as an effective immuno-adjuvant in tumour immunotherapy or combined tumour therapy (Huang et al, 2008; Rakoff-Nahoum and Medzhitov, 2009). However, recent evidence has shown that functional TLRs are expressed on a wide variety of tumours (Huang et al, 2008; Rakoff-Nahoum and Medzhitov, 2009). Contemporary experimental evidence suggests that TLRs have important roles in tumourigenesis (Killeen et al, 2008). Lipopolysaccharide, a putative ligand for TLR4, may promote tumour progression by acting directly on cancer cells, resulting in increased tumour cell–endothelial cell adhesion, tumour cell–extracellular matrix adhesion, and tumour cell–extracellular matrix invasion through NF-κB-mediated upregulation of β-1 integrin (Andrews et al, 2001; Wang et al, 2003). Helicobacter pylori acting through TLR2/TLR9 on gastric epithelial cells activated both Src and NF-κB, resulting in an increased expression of cyclooxygenase-2 (Cox-2), which may contribute to gastric cancer progression (Chang et al, 2004). The triggering of TLR4 and TLR9 on prostate cancer cells has also been shown to promote tumour cell proliferation through increased NF-κB activation (Kundu et al, 2008).

Mounting evidence suggests that innate immune responses to luminal microbes participate in the development of gastrointestinal malignancies (Fukata and Abreu, 2008). The large intestine contains the highest density of microorganisms with the potential to have a key function in colorectal carcinogenesis (Fukata and Abreu, 2008). An expanding body of experimental studies has identified the contribution of TLR signalling to intestinal carcinogenesis (Fukata and Abreu, 2008). Blocking TLR4 signalling in colon cancer cells resulted in the reduction of tumour growth in a subcutaneously implanted mouse model (Huang et al, 2005). In addition, the involvement of TLR signalling through MyD88 in tumour growth and progression has been demonstrated in an Apcmin/+ mice model (Rakoff-Nahoum and Medzhitov, 2007). Furthermore, a recent study reported that TLR4 activation seems to promote the development of colitis-associated cancer by enhancing Cox-2 expression and increasing epidermal growth factor receptor (EGFR) signalling (Fukata et al, 2007). These findings have opened a multitude of oncological therapeutic opportunities. However, little is known about the clinical significance of TLR-4/MyD88 signalling expression in sporadic CRC.

In this study, we performed a systematic immunohistochemical analysis of TLR4 and MyD88 expression in normal colon mucosae, adenomas, and CRC. The analysis of the investigation involved two parts: The first was concerned with the correlation between pathological factors and protein expression, and the second tested the correlation between protein expression and disease-free survival (DFS) and overall survival (OS).

Materials and methods

Patients and human tissues

A total of 108 patients with CRC (62 males and 46 females) who underwent surgery from 1990 to 1999 at the Tokushima University Hospital were investigated in this study. Information on patient demographics (sex and age) and tumour features (anatomical site, histology, vascular invasion, lymphatic invasion, lymph node metastasis, liver metastasis, peritoneal metastasis, and TNM stage) was obtained from clinical and pathological records (Table 1). The tumour site was classified as proximal or distal with respect to the splenic flexure. Disease stages were classified according to the criteria proposed by the Standard AJCC (American Joint Committee on Cancer) (Fleming et al, 1997). Disease-free survival was defined as the interval between the day that surgery was performed and the day that recurrence was first detected. If recurrence was not diagnosed, the date of death or of last follow-up was used. Overall survival was defined as the interval between the dates of surgery and death. The follow-up period after the initial operation for the primary lesion was 5 years for DFS and OS. Exclusion criteria were cancers associated with ulcerative colitis, Crohn's disease, or familial adenomatous polyposis. Ethical approval for the project was obtained from the Tokushima University Hospital Research Ethics Committee.

Table 1. Clinicopathological features according to TLR4 and MyD88 expression.

  TLR4
MyD88
TLR4+MyD88
Clinicopathological factors High (n=22) Low (n=86) P-value High (n=25) Low (n=83) P-value High (n=25) Low (n=83) P-value
Age (years)                  
 ⩾65 10 38 0.915 11 37 0.9593 11 37 0.9593
 <65 12 48   14 46   14 46  
                   
Sex                  
 Male 14 48 0.5054 13 49 0.534 13 49 0.534
 Female 8 38   12 34   12 34  
                   
Tumour site                  
 Distal 20 71 0.3113 23 68 0.1972 23 68 0.1972
 Proximal 2 15   2 15   2 15  
                   
Histology                  
 Well 7 33 0.7685 4 36 0.0333 7 33 0.3139
 Moderate 13 48   18 43   15 46  
 Poor/mucinous 2 5   3 4   3 4  
                   
Vascular invasion                  
 Yes 13 34 0.0987 15 32 0.058 16 31 0.0186
 No 9 42   10 51   9 52  
                   
Lymphatic invasion                  
 Yes 18 61 0.3038 20 59 0.3779 18 61 0.8829
 No 4 25   5 24   7 22  
                   
Lymph node metastasis                  
 Yes 13 51 0.9856 18 46 0.1392 16 48 0.5802
 No 9 25   7 37   9 35  
                   
Liver metastasis                  
 Yes 11 11 0.0001 10 12 0.0054 12 10 0.0002
 No 11 75   15 71   13 73  
                   
Peritoneal metastasis                  
 Yes 4 5 0.0611 2 7 0.9452 3 6 0.4666
 No 18 81   23 76   22 77  
                   
Stage                  
 I, II 6 32 0.0197 7 31 0.0745 7 31 0.0036
 III 5 39   7 35   5 37  
 IV 11 17   11 17   13 15  
Open in a new tab

Abbreviations: TLR4=Toll-like receptor 4; MyD88=myeloid differentiation factor 88. Bold values indicate P<0.05.

For the immunohistochemical study, formalin-fixed, paraffin-embedded tissue samples from 15 normal mucosa tissues obtained by colon biopsy, as well as 15 adenomas, 108 CRC, and 14 liver metastases, were used.

Immunohistochemistry for TLR4 and MyD88

To immunostain TLR4 and MyD88 proteins, the streptavidin–biotin labelling method was carried out on 4 μm tissue sections as described previously (Rahman et al, 2009). After deparaffinisation in xylene and rehydration in a series of ethanols, the sections were then treated with 0.3% hydrogen peroxide to block endogenous peroxidase activity for 30 min. Antigen retrieval was performed using an autoclave oven technique. The tissue sections were then incubated with a serum-free protein blocker and incubated at 4°C overnight with mouse monoclonal anti-human TLR4 antibody (1:100; HTA125, eBioscience, San Diego, CA, USA) or rabbit polyclonal anti-MyD88 antibody (1:100; HFL-296, Santa Cruz Biotech, Santa Cruz, CA, USA). The biotinylated secondary antibody and peroxidase-labelled streptavidin (DakoCytomation, Glostrup, Denmark) were applied for 50 min each at room temperature. Antigen–antibody complexes were visualised using the 3, 3′-diaminobenzidine reaction. For confirmation, the 3-amino-9-ethylcarbazole reaction was also used. The slides were counterstained lightly with haematoxylin and mounted for microscopic examination. Human tonsil tissue was used as a positive control for TLR4 and MyD88 immunoreactivity. Phosphate-buffered saline without the primary antibody served as a negative control.

Evaluation of immunohistochemical findings

Each slide was evaluated independently by two pathologists who were blinded to clinical and outcome data. As most samples stained for TLR4 and MyD88 showed similar colour intensity, from moderate to strong, no evaluation of colour intensity was performed in this study. Any intensity of membrane and/or cytoplasmic staining was considered to represent a positive stain for TLR4 and MyD88. Several high-power fields ( × 200) selected from different staining density regions including high, moderate, low, and negative staining areas were captured using a digital camera (Olympus Q-color 3; Olympus Inc., Center Valley, PA, USA). Photographs were printed on plain paper and a grid was drawn over them. We counted a mean of 2000 tumour cells per tumour (range, 1500–2500), and the results were expressed as the percentage of tumour cells with a positive stain. Thereafter, the percentage of TLR4- or MyD88-positive tumour cells was scored on a scale of 0–4 (0: no staining; 1+: ⩽10% 2+: 11–30% 3+: 31–50% 4+: >50%). Furthermore, the expression levels of TLR4 and MyD88 were divided into the following two groups according to score: low (0, 1+, 2+) and high (3+, 4+). In addition, the sum of the score of TLR4/MyD88 staining was divided into the following two groups: <5 and ⩾5.

Statistical analysis

Analysis was performed using StatView J-4.5 software (Abacus Concepts, Berkeley, CA, USA). The Pearson χ2 test or Fisher's exact test was used to compare qualitative variables. The primary statistical outcomes were DES and OS measured from the day of surgery. Both DFS and OS were estimated by Kaplan–Meier curves, and the curves were compared using the log-rank test. Time to relapse and to death was analysed using the Cox proportional hazards model for univariate and multivariate analyses. In addition, the hazard ratios (HRs) between prognostic groups and their 95% confidence intervals were computed. Probability values (P) <0.05 were considered to be statistically significant.

Results

TLR4 and MyD88 expression in normal colonic mucosae, adenomas, and cancers

Immunolocalisation of TLR4 protein was observed in the membrane and cytoplasm. In general, TLR4 expression was absent or very weak in the normal mucosae collected from biopsy samples and cancer margin samples (Figure 1A). This finding is consistent with those of earlier reports (Cario and Podolsky, 2000; Furrie et al, 2005; Fukata and Abreu, 2008). The expression of TLR4 was also absent or weak in adenomas (Figure 1A). Compared with normal mucosae and adenomas, the expression of TLR4 was detected in a high proportion of cancers (78 of 108, 72%) (Figure 1B). A total of 22 cancers displayed high expression (4+: 6, 3+: 16), and 86 cancers showed low expression (2+: 33, 1+: 23 and 0: 30) (Table 1). Among the 14 liver metastases obtained by hepatectomy, 12 (86%) were TLR4 positive and 6 (43%) showed a high expression.

Figure 1.

Figure 1

Open in a new tab

Detection of TLR4 and MyD88 immunoreactivity in normal colon tissues, adenoma, and CRC. (A) Normal colon mucosa (left) and adenoma (right) showed no or weak immunoreactions for TLR4 (top) and MyD88 (below), which was identified as negative expression in this study. Original magnification, × 200. (B) In contrast to the situation in the normal and adenoma, strong immunostaining of TLR4, which was localized in the membrane (top) or cytoplasm (below), was observed in the cancer cells. Original magnification, right, × 200; left, × 400. (C) Strong immunostaining of MyD88, which was localised in the cytoplasm, was observed in the cancer cells. Original magnification, right, × 200; left, × 400. (D) High expression of TLR4 was correlated with high expression of MyD88 in CRC. CRC with a high expression of TLR4 (n=22) showed significantly high levels of MyD88 expression than did CRC with a low expression of TLR4 (n=86) (P<0.05). CRC with a high expression of MyD88 (n=25) showed significantly high levels of TLR4 expression than did CRC with a low expression of MyD88 (n=83) (P<0.005).

Immunolocalisation of MyD88 protein was observed in the cytoplasm. Similar to that of TLR4, MyD88 expression was absent or very weak in normal mucosae, cancer margin samples, and adenomas (Figure 1A). In CRC, a total of 93 of 108 (86%) cancers showed MyD88 expression (Figure 1C). A high-level expression was detected in 25 cancers (23%) (4+: 10, 3+: 15). In all, 83 cancers showed a low-level expression (2+: 33, 1+: 35, and 0: 15). All of 14 liver metastases were positive for MyD88 expression and 12 (86%) of them displayed high expression.

In the co-expression analysis, MyD88 expression levels were higher in TLR4 high-expression CRC than in TLR4 low-expression CRC (P<0.05, Figure 1D). Similarly, significantly high levels of TLR4 were detected in CRC with high MyD88 expression (P<0.005, Figure 1D). Finally, the correlation between the expression of TLR4 and MyD88 in CRC was confirmed using Pearson's correlation coefficient analysis (r=0.33, P<0.05) and Spearman's correlation coefficient analysis (P=0.003). In addition, 25 (23%) cancers showed a high-level combined expression of TLR4/MyD88 (5+: 12, 6+: 5, 7+: 7, and 8+: 1) (Table 1).

Clinicopathological significance of TLR4 and MyD88 expression

The co-distribution of CRC with a high or low TLR4/MyD88 expression in relation to cancer and patient characteristics is shown in Table 1. The high expression of TLR4 was significantly associated with liver metastasis (P=0.0001) and TNM stage (P=0.0197) and potentially related to peritoneal metastasis (P=0.0611). The high expression of MyD88 was significantly associated with cancer histology (P=0.0333) and liver metastasis (P=0.0054) and potentially related to TNM stage (P=0.0745). Furthermore, a high co-expression of TLR4/MyD88 was significantly associated with vascular invasion (P=0.0186), liver metastasis (P=0.0002), and TNM stage (P=0.0036). In addition, CRC with liver metastasis showed higher levels of TLR4 and MyD88 expression than did CRC without liver metastasis (Figure 2A–C, P=0.0015, P=0.0035, P=0.0001, respectively).

Figure 2.

Figure 2

Open in a new tab

Differences in immunostaining scores of TLR4 and MyD88 in liver metastasis (+) CRC (n=22) and liver metastasis (−) CRC (n=86) were analysed. The TLR4 (A), MyD88 (B), and combined TLR4/MyD88 expression (C) levels were significantly higher in liver metastasis (+) CRC than in liver metastasis (−) CRC (P=0.0015, P=0.0035, P=0.0001, respectively).

Clinicopathological parameters and patient survival in CRC

At the 5-year follow-up, 53 patients had tumour recurrence (DFS rate: 49%), and 46 patients had died (OS rate: 43%). In univariate analysis, histology (DFS, P=0.0322; OS, P=0.0084), TNM stage (DFS, P<0.0001; OS, P=0.0001), vascular invasion (DFS, P<0.0001; OS, P=0.0001), lymphatic invasion (DFS, P=0.001; OS, P=0.0121), lymph node metastasis (DFS, P=0.0001; OS, P=0.0017), liver metastasis (DFS, P<0.0001; OS, P<0.0001), and peritoneal metastasis (DFS, P=0.0386; OS, P=0.007) were important factors associated with DFS and OS (Table 2). Patient age, sex, and tumour location were not related to DFS or OS (Table 2). Multivariate analysis was performed to identify independent prognostic factors. In Table 3, models that include all histopathological variables and tumour markers found to have significant prognostic value in univariate analysis (Table 2) are shown. In Table 3 modelsA and B, TNM stage was significantly associated with DFS (A, P=0.0026; B, P=0.0043) and OS (A, P=0.0074; B, P=0.0216), and the presence of liver metastasis was significantly associated with DFS (A, P=0.0373; B, P=0.047) (Table 3). In Table 3 model B, the presence of lymphatic invasion was significantly associated with DFS (P=0.0362), and histology was significantly associated with OS (P=0.0435) (Table 3).

Table 2. Clinicopathological features, tumour markers, and patient survival (univariate analysis).

Variable 5-Year DFS HR (95% CI) P-value 5-Year OS HR (95% CI) P-value
Age (⩾65years vs <65 years) 0.84 (0.48–1.45) 0.5355 1.17 (0.65–2.08) 0.5934
Sex (male vs female) 0.95 (0.55–1.63) 0.8568 0.95 (0.53–1.71) 0.8781
Tumour site (distal vs proximal) 2.89 (1.16–8.97) 0.0656 3.17 (0.98–10.23) 0.0534
Histology (poor/moderate vs well) 1.95 (1.05–3.6) 0.0322 2.57 (1.27–5.19) 0.0084
TNM stage (III/IV vs I/II) 8.07 (3.2–20.33) <0.0001 6.26 (2.46–15.88) 0.0001
Vascular invasion (yes vs no) 3.28 (1.86–5.78) <0.0001 3.35 (1.82–6.16) 0.0001
Lymphatic invasion (yes vs no) 4.68 (1.86–11.79) 0.001 3 (1.27–7.09) 0.0121
Lymph node metastasis (yes vs no) 3.64 (1.87–7.09) 0.0001 3.07 (1.52–6.2) 0.0017
Liver metastasis (yes vs no) 5.04 (2.85–8.9) <0.0001 5.35 (2.94–9.74) <0.0001
Peritoneal metastasis (yes vs no) 2.32 (1.05–5.18) 0.0386 3.06 (1.35–6.91) 0.007
TLR4 (high vs low) 1.62 (0.87–2.99) 0.1213 2.17 (1.15–4.07) 0.015
MyD88 (high vs low) 2.33 (1.31–4.13) 0.0038 3.03 (1.67–5.48) 0.0002
TLR4+MyD88 (⩾5+ vs < 5+) 2.25 (1.27–3.99) 0.0053 2.97 (1.64–5.38) 0.0003
Open in a new tab

Abbreviations: DFS=disease-free survival; HR=hazard ratio; CI=confidence interval; OS=overall survival; TNM=tumour, node, metastasis; TLR4=Toll-like receptor 4; MyD88=myeloid differentiation factor 88. Bold values indicate P<0.05.

Table 3. Clinicopathological features, tumour markers, and patient survival (multivariate analysis).

Variable 5-Year DFS HR (95% CI) P-value 5-Year OS HR (95% CI) P-value
Model A        
 Histology (poor/moderate vs well) 1.31 (0.67–2.55) 0.4342 1.75 (0.8–3.81) 0.1619
 TNM stage (III/IV vs I/II) 8.52 (2.11–24.33) 0.0026 8.17 (1.76–27.28) 0.0074
 Vascular invasion (yes vs no) 1.32 (0.69–2.54) 0.4034 1.55 (0.77–3.11) 0.2169
 Lymphatic invasion (yes vs no) 2.53 (0.96–6.67) 0.061 1.50 (0.69–3.83) 0.4004
 Lymph node metastasis (yes vs no) 0.56 (0.21–1.53) 0.259 0.49 (0.15–1.5) 0.2058
 Liver metastasis (yes vs no) 2.02 (1.04–3.92) 0.0373 1.68 (0.79–3.58) 0.1791
 Peritoneal metastasis (yes vs no) 0.99 (0.43–2.31) 0.9897 1.23 (0.49–3.08) 0.655
 TLR4 (high vs low) — — 1.39 (0.67–2.89) 0.381
 MyD88 (high vs low) 2.01 (1.00–4.03) 0.0494 2.31 (1.09–4.89) 0.0279
Model B        
 Histology (poor/moderate vs well) 1.53 (0.81–2.89) 0.1873 2.11 (1.02–4.37) 0.0435
 TNM stage (III/IV vs I/II) 7.17 (1.86–25.68) 0.0043 5.56 (1.87–21.68) 0.0216
 Vascular invasion (yes vs no) 1.33 (0.69–2.56) 0.3887 1.35 (0.77–3.11) 0.2224
 Lymphatic invasion (yes vs no) 2.85 (1.07–7.61) 0.0362 1.74 (0.67–4.5) 0.2522
 Lymph node metastasis (yes vs no) 0.67 (0.25–1.75) 0.4071 0.67 (0.22–1.96) 0.4602
 Liver metastasis (yes vs no) 1.97 (1.01–3.86) 0.047 1.83 (0.87–3.83) 0.1093
 Peritoneal metastasis (yes vs no) 0.89 (0.38–2.11) 0.8065 1.21 (0.5–2.9) 0.6739
 TLR4+MyD88 (⩾5+ vs <5+) 1.87 (0.97–3.59) 0.0625 2.11 (1.05–4.23) 0.0352
Open in a new tab

Abbreviations: DFS=disease-free survival; HR=hazard ratio; CI=confidence interval; OS=overall survival; TNM=tumour, node, metastasis; TLR4=Toll-like receptor 4; MyD88=myeloid differentiation factor 88. Bold values indicate P<0.05.

TLR4 and MyD88 expression and patient survival in CRC

We assessed the influence of high expression of TLR4 and MyD88 in CRC on patient survival. Patients with a high TLR4 expression had a worse DFS than did those with a low TLR4 expression (36 vs 55%, Figure 3A). However, a high expression of TLR4 did not significantly influence DFS (log-rank P=0.1177; Figure 3A). High expression of MyD88 and high co-expression of TLR4/MyD88 were significantly related to poor DFS (log-rank P=0.0029; log-rank P=0.0042, respectively, Figure 3C and E). Furthermore, high expression of TLR4, MyD88, and co-expression TLR4/MyD88 were significantly associated with poor OS (log-rank P=0.013; log-rank P=0.0001; log-rank P=0.0001, respectively, Figures 3B, D, and F).

Figure 3.

Figure 3

Open in a new tab

Kaplan–Meier survival curves of DFS and OS in patients with CRC according to TLR4 and MyD88 expression. (A, B) High expression of TLR4 was potentially associated with poor DFS and significantly associated with poor OS (P=0.013). (C, D) High expression of MyD88 was significantly associated with poor DFS and OS (P=0.0029, P=0.0001, respectively). (E, F) High co-expression of TLR4+MyD88 was significantly associated with poor DFS and OS (P=0.0042, P=0.0001, respectively).

In univariate analysis, high expression of TLR4 was not significantly related to DFS (Table 2). High expression of MyD88 (HR: 2.33; 95% confidence interval (95% CI): 1.31–4.13; P=0.0038) and high co-expression of TLR4/MyD88 (HR: 2.25; 95% CI: 1.27–3.99; P=0.0053; Table 2) were significantly related to poor DFS. In addition, high expression of TLR4 (HR: 2.17; 95% CI: 1.15–4.07; P=0.015), MyD88 (HR: 3.03; 95% CI: 1.67–5.48; P=0.0002), and co-expression of TLR4/MyD88 (HR: 2.97; 95% CI: 1.64–5.38; P=0.0003; Table 2) significantly influenced OS.

In multivariate analysis of Table 3 model A, high expression of MyD88 was significantly associated with poor DFS (adjusted HR: 2.01; 95% CI: 1.00–4.03; P=0.0494) and OS (adjusted HR: 2.31; 95% CI: 1.09–4.89; P=0.0279) (Table 3). High co-expression of TLR4/MyD88 was significantly associated with poor OS (adjusted HR: 2.11; 95% CI: 1.05–4.23; P=0.0352; Table 3 model B) and potentially related to poor DFS (HR: 1.87; 95% CI: 0.97–3.59; P=0.0625; Table 3 model B). As the TNM stage includes metastasis information, we excluded all metastasis factors from Table 4 models and analysed survival significance of TLR4, MyD88, and TLR4/MyD88. In Table 4 model A, multivariate analysis showed that high expression of TLR4 was significantly associated with poor OS (adjusted HR: 1.88; 95% CI: 0.99–3.55; P=0.0298; Table 4). In Table 4 model B, high expression of MyD88 was significantly associated with poor DFS and OS (adjusted HR: 1.93; 95% CI: 1.01–3.67; P=0.0441; adjusted HR: 2.25; 95% CI: 1.17–4.33; P=0.0112, respectively, Table 4). Table 4 model C showed that high co-expression of TLR4/MyD88 was also significantly associated with poor DFS (adjusted HR: 2.06; 95% CI: 1.11–3.82; P=0.0216) and OS (adjusted HR: 2.4; 95% CI: 1.28–4.52; P=0.0041) (Table 4).

Table 4. Clinicopathological features, tumour markers, and patient survival (multivariate analysis).

Variable 5-Year DFS HR (95% CI) P-value 5-Year OS HR (95% CI) P-value
Model A        
 TLR4 (high vs low) 1.31 (0.71–2.43) 0.3816 1.88 (0.99–3.55) 0.0298
 Histology (poor/moderate vs well) 1.82 (0.98–3.37) 0.0572 2.52 (1.24–5.14) 0.0065
 TNM stage (III/IV vs I/II) 5.8 (2.26–15.09) 0.0003 4.6 (1.72–12.01) 0.0013
 Vascular invasion (yes vs no) 1.81 (1.01–3.25) 0.0448 2.23 (1.18–4.2) 0.019
 Lymphatic invasion (yes vs no) 2.35 (0.91–6.07) 0.0752 1.518 (0.62–3.67) 0.4202
Model B        
 MyD88 (high vs low) 1.93 (1.01–3.67) 0.0441 2.25 (1.17–4.33) 0.0112
 Histology (poor/moderate vs well) 1.54 (0.8–2.95) 0.1878 1.89 (0.9–3.99) 0.0679
 TNM stage (III/IV vs I/II) 5.98 (2.28–15.68) 0.0003 4.52 (1.7–11.99) 0.0017
 Vascular invasion (yes vs no) 1.61 (0.87–2.97) 0.122 2.08 (1.09–3.97) 0.0414
 Lymphatic invasion (yes vs no) 2.27 (0.86–5.94) 0.0944 1.38 (0.55–3.45) 0.5922
Model C        
 TLR4+MyD88 (⩾5+ vs < 5+) 2.06 (1.11–3.82) 0.0216 2.4 (1.28–4.52) 0.0041
 Histology (poor/moderate vs well) 1.74 (0.93–3.24) 0.0806 2.3 (1.13–4.69) 0.0155
 TNM stage (III/IV vs I/II) 5.89 (2.24–15.45) 0.0003 4.48 (1.68–11.92) 0.0018
 Vascular invasion (yes vs no) 1.53 (0.82–2.84) 0.173 1.87 (0.96–3.62) 0.0918
 Lymphatic invasion (yes vs no) 2.52 (0.97–6.56) 0.0577 1.58 (0.64–3.92) 0.3742
Open in a new tab

Abbreviations: DFS=disease-free survival; HR=hazard ratio; CI=confidence interval; OS=overall survival; TNM=tumour, node, metastasis; TLR4=Toll-like receptor 4; MyD88=myeloid differentiation factor 88. Bold values indicate P<0.05.

Discussion

It was recently reported that TLR4/MyD88 signalling drives tumour growth in numerous organs (Rakoff-Nahoum and Medzhitov, 2009). Toll-like receptor 4 and other TLRs have been detected in many murine and human cancer cell lines, including laryngeal, lung, breast, gastric, colon, prostate cancer, and melanoma (Huang et al, 2008). Silencing TLR4 signalling in tumour cells results in reduced tumour formation (Huang et al, 2005), and the inhibition of tumour-cell apoptosis by TLR-signalling was also observed in ovarian, lung cancer, and myeloma cells (Jego et al, 2006; Kelly et al, 2006; He et al, 2007). In addition, it was shown that MyD88 is crucial for the promotion of diethylnitrosamine-induced hepatocellular tumours (Naugler et al, 2007). Recently, MyD88 has also been shown to be crucial for tumour promotion in models of spontaneous (Apcmin/+) and carcinogen-induced (azoxymethane) intestinal tumourigenesis (Rakoff-Nahoum and Medzhitov, 2007). In addition, MyD88 is a positive regulator of chemically induced tumours of both the skin and connective tissue (Swann et al, 2008). In this study, we observed that TLR4/MyD88 signalling was frequently overexpressed in CRC compared with normal mucosae and adenomas. A correlation between TLR4 and MyD88 expression was detected. These findings indicated that TLR4/MyD88 signalling in tumour cells itself has important roles as oncogenic factors in CRC.

It is not yet clear whether TLR4 and MyD88 are involved in tumour initiation (Rakoff-Nahoum and Medzhitov, 2009). In humans, chronic infection and inflammation are considered to be two of the most important factors contributing to tumourigenesis and tumour progression (Balkwill and Coussens, 2004). Toll-like receptor signalling may have an important role in numerous cancers, including gastric, ovarian, lung, pancreatic, liver, and colon cancer, which have been shown to be associated with local chronic inflammation (Kelly et al, 2006; Fukata et al, 2007; He et al, 2007; Naugler et al, 2007; Schwartz et al, 2009). Upregulated stimulation of TLRs could lead to damage and mutation of genomic DNA and aberrant chromosomal translocation (Rakoff-Nahoum and Medzhitov, 2009). Toll-like receptor 4 signalling activation seems to promote the development of colitis-associated cancer by mechanisms including enhanced Cox-2 expression and increased EGFR signalling (Fukata et al, 2007). Excluding colitis-associated cancers, commensal bacteria have also been implicated in the development of sporadic CRC (Hope et al, 2005) and may promote CRC by inducing chromosomal instability (Wang and Huycke, 2007). Our findings suggest that TLR4/MyD88 signalling contributes to CRC tumourigenesis not just in colitis-associated cancer but also in sporadic CRC.

The molecular pathway that links inflammation to the acquisition of metastatic capacity during tumour progression has been investigated (Kim et al, 2009). By activating TLR2:TLR6 complexes and inducing TNF-α secretion in myeloid cells, versican strongly enhances Lewis lung carcinoma metastatic growth (Kim et al, 2009). Activation of tumour cell TLR can enhance the invasion and metastasis of tumour cells by regulating metalloproteinases (MMPs) and integrins (Wang et al, 2003; Huang et al, 2008). The highly invasive MDA-MB-231 breast cancer cell line expresses TLR9, which promotes tumour cell invasion by increasing the activity of MMP-13 (Merrell et al, 2006). Toll-like receptor 4 signalling in colon cancer cells is involved in tumour immune escape, accompanied by apoptosis resistance and the preferential induction of immunosuppressive factors and chemokines, such as TGF-β, NO, IL-8, MCP-1, and MMP-9, resulting in tumourigenesis and the promotion of tumour metastasis (Cianchi et al, 2004; Molteni et al, 2006; Wang et al, 2003, Lee and Lim, 2007). Earl et al (2009) reported that silencing of TLR4 in tumour cells reduces the metastatic tumour burden in steatotic livers. Recently, Killeen et al (2009) suggested that bacterial endotoxins directly promote tumour cell adhesion and invasion through upregulation of urokinase plasminogen activator and the urokinase plasminogen activator receptor through TLR-4-dependent activation of NF-κB. Our study showed that TLR4/MyD88 overexpression was frequently detected in CRC with liver metastasis, and TLR4/MyD88 levels were significantly higher in these CRCs. Our findings suggest that TLR4/MyD88 signalling promotes CRC progression by contributing to liver metastasis.

Silencing TLR4/MyD88 signalling in tumour cells not only results in reduced tumour formation but also leads to prolonged survival after subcutaneous tumour injection in mice (Huang et al, 2005; Rakoff-Nahoum and Medzhitov, 2007). These effects suggest that blocking TLR4/MyD88 signalling would provide a survival benefit. However, the association between TLR signalling and cancer mortality has not been well investigated in clinical samples. Our results clearly demonstrated that overexpression of TLR4/MyD88 was an independent and significant prognostic factor for 5-year DFS and OS. This is the first study to show an association between TLR4/MyD88 expression and CRC patient survival. Previous studies reported that elevation of the downstream signals of the TLR4/MyD88 pathway, such as Cox-2 and NF-κB, was related to CRC patient survival. We see that TLR4/MyD88 regulates the expression of Cox-2, which shows its important role in many aspects of tumour growth (Fukata and Abreu, 2008; Rakoff-Nahoum and Medzhitov, 2009). Cyclooxygenase-2 is also considered to have an important role in colorectal carcinogenesis. Recently, Ogino et al (2008) reported that Cox-2 overexpression is associated with worse survival among colon cancer patients. Nuclear factor-κB is an end point of the TLR4/MyD88 signalling pathway. Numerous lines of evidence that link NF-κB activation to cancer development have been reported. Constitutive NF-κB activation is found in most cancer cell lines and in numerous types of tumour tissues (Shishodia and Aggarwal 2004). Scartozzi et al (2007) reported that NF-κB nuclear expression predicts response and survival in irinotecan-refractory metastatic CRC treated with cetuximab–irinotecan therapy. These findings suggested that the tumour cell TLR4/MyD88 signalling pathway has a crucial role in CRC patient prognosis and that blocking this pathway could provide great benefits for patients with CRC.

Recently, several approaches to the treatment of TLR4-mediated diseases have been investigated. Rapamycin may abrogate TLR-triggered colon cancer cell-immune escape and invasion by downregulating TLR4 expression and inhibiting the TLR4-activated NF-κB pathway (Sun et al, 2008). Interestingly, TAK-242, a small-molecule antisepsis agent, has been demonstrated to be a selective inhibitor of TLR4 signalling (Kawamoto et al, 2008). Our study suggests that it is necessary to investigate the usefulness of TAK-242 in CRC therapy.

Our study profiled the status of TLR4 and MyD88 in CRC and indicated that this signalling pathway was associated with an increased risk of liver metastasis and worse survival. This study, for the first time, showed the clinicopathological significance of tumour cell self-TLR4/MyD88 expression in CRC. These findings suggested the novel therapeutic possibility of targeting tumour cell TLR4/Myd88 signals in CRC.

Acknowledgments

This study was supported by grants for Cancer Research from the ‘Research Foundation of Tokushima University’. We express our appreciation to our patients. We also thank Taiho Pharmaceutical Co., Ltd for their excellent technical assistance and helpful discussion.

References

  1. Akira S, Uematsu S, Takeuchi O (2006) Pathogen recognition and innate immunity. Cell 124: 783–801 [DOI] [PubMed] [Google Scholar]
  2. Andrews EJ, Wang JH, Winter DC, Lang WE, Redmond HP (2001) Tumor cell adhesion to endothelial cells is increased by endotoxin via an upregulation of β-1 integrin expression. J Surg Res 97: 14–19 [DOI] [PubMed] [Google Scholar]
  3. Balkwill F, Coussens LM (2004) Cancer: an inflammatory link. Nature 431: 405–406 [DOI] [PubMed] [Google Scholar]
  4. Cario E, Podolsky DK (2000) Differential alteration in intestinal epithelial cell expression of Toll-like receptor 3 (TLR3) and TLR4 in inflammatory bowel disease. Infect Immun 68: 7010–7017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Chang YJ, Wu MS, Lin JT, Sheu BS, Muta T, Inoue H, Chen CC (2004) Induction of cyclooxygenase-2 overexpression in human gastric epithelial cells by Helicobacter pylori involves TLR2/TLR9 and c-Src-dependent nuclear factor-κB activation. Mol Pharmacol 66: 1465–1477 [DOI] [PubMed] [Google Scholar]
  6. Cianchi F, Cortesini C, Fantappiè O, Messerini L, Sardi I, Lasagna N, Perna F, Fabbroni V, Di Felice A, Perigli G, Mazzanti R, Masini E (2004) Cyclooxygenase-2 activation mediates the proangiogenic effect of nitric oxide in colorectal cancer. Clin Cancer Res 10: 2694–2704 [DOI] [PubMed] [Google Scholar]
  7. Earl TM, Nicoud IB, Pierce JM, Wright JP, Majoras NE, Rubin JE, Pierre KP, Gorden DL, Chari RS (2009) Silencing of TLR4 decreases liver tumor burden in a murine model of colorectal metastasis and hepatic steatosis. Ann Surg Oncol 16: 1043–1050 [DOI] [PubMed] [Google Scholar]
  8. Fleming ID, Cooper JS, Henson DE, Hutter RVP, Kennedy BJ, Murphy GP (1997) AJCC Cancer Staging Manual 5th edn, Lippincott-Raven Publishers: Philadelphia, PA, pp 83–90 [Google Scholar]
  9. Fukata M, Chen A, Vamadevan AS, Cohen J, Breglio K, Krishnareddy S, Hsu D, Xu R, Harpaz N, Dannenberg AJ, Subbaramaiah K, Cooper HS, Itzkowitz SH, Abreu MT (2007) Toll-like receptor-4 promotes the development of colitis-associated colorectal tumors. Gastroenterology 133: 1869–1881 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Fukata M, Abreu MT (2008) Role of Toll-like receptors in gastrointestinal malignancies. Oncogene 27: 234–243 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Furrie E, Macfarlane S, Thomson G, Macfarlane GT (2005) Toll-like receptors-2, -3 and -4 expression patterns on human colon and their regulation by mucosal-associated bacteria. Immunology 115: 565–574 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. He W, Liu Q, Wang L, Chen W, Li N, Cao X (2007) TLR4 signaling promotes immune escape of human lung cancer cells by inducing immunosuppressive cytokines and apoptosis resistance. Mol Immunol 44: 2850–2859 [DOI] [PubMed] [Google Scholar]
  13. Hope ME, Hold GL, Kain R, El-Omar EM (2005) Sporadic colorectal cancer—role of the commensal microbiota. FEMS Microbiol Lett 244: 1–7 [DOI] [PubMed] [Google Scholar]
  14. Huang B, Zhao J, Li H, He KL, Chen Y, Chen SH, Mayer L, Unkeless JC, Xiong H (2005) Toll-like receptors on tumor cells facilitate evasion of immune surveillance. Cancer Res 65: 5009–5014 [DOI] [PubMed] [Google Scholar]
  15. Jego G, Bataille R, Geffroy-Luseau A, Descamps G, Pellat-Deceunynck C (2006) Pathogen-associated molecular patterns are growth and survival factors for human myeloma cells through Toll-like receptors. Leukemia 20: 1130–1137 [DOI] [PubMed] [Google Scholar]
  16. Jemal A, Siegel R, Ward E, Hao Y, Xu J, Thun MJ (2009) Cancer statistics. CA Cancer J Clin 59: 225–249 [DOI] [PubMed] [Google Scholar]
  17. Kawamoto T, Ii M, Kitazaki T, Iizawa Y, Kimura H (2008) TAK-242 selectively suppresses Toll-like receptor 4-signaling mediated by the intracellular domain. Eur J Pharmacol 584: 40–48 [DOI] [PubMed] [Google Scholar]
  18. Kelly MG, Alvero AB, Chen R, Silasi DA, Abrahams VM, Chan S, Visintin I, Rutherford T, Mor G (2006) TLR-4 signaling promotes tumor growth and paclitaxel chemoresistance in ovarian cancer. Cancer Res 66: 3859–3868 [DOI] [PubMed] [Google Scholar]
  19. Killeen SD, Wang JH, Andrews EJ, Redmond HP (2008) Exploitation of the Toll-like receptor system in cancer: a doubled-edged sword? Br J Cancer 95: 247–252 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Killeen SD, Wang JH, Andrews EJ, Redmond HP (2009) Bacterial endotoxin enhances colorectal cancer cell adhesion and invasion through TLR-4 and NF-κB-dependent activation of the urokinase plasminogen activator system. Br J Cancer 100: 1589–1602 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Kim S, Takahashi H, Lin WW, Descargues P, Grivennikov S, Kim Y, Luo JL, Karin M (2009) Carcinoma-produced factors activate myeloid cells through TLR2 to stimulate metastasis. Nature 457: 102–106 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kundu SD, Lee C, Billips BK, Habermacher GM, Zhang Q, Liu V, Wong LY, Klumpp DJ, Thumbikat P (2008) The Toll-like receptor pathway: a novel mechanism of infection-induced carcinogenesis of prostate epithelial cells. Prostate 68: 223–229 [DOI] [PubMed] [Google Scholar]
  23. Lee SJ, Lim KT (2007) UDN glycoprotein regulates activities of manganese-superoxide dismutase, activator protein-1, and nuclear factor-κB stimulated by reactive oxygen radicals in lipopolysaccharide-stimulated HCT-116 cells. Cancer Lett 254: 274–287 [DOI] [PubMed] [Google Scholar]
  24. Merrell MA, Ilvesaro JM, Lehtonen N, Sorsa T, Gehrs B, Rosenthal E, Chen D, Shackley B, Harris KW, Selander KS (2006) Toll-like receptor 9 agonists promote cellular invasion by increasing matrix metalloproteinase activity. Mol Cancer Res 4: 437–447 [DOI] [PubMed] [Google Scholar]
  25. Molteni M, Marabella D, Orlandi C, Rossetti C (2006) Melanoma cell lines are responsive in vitro to lipopolysaccharide and express TLR-4. Cancer Lett 235: 75–83 [DOI] [PubMed] [Google Scholar]
  26. Naugler WE, Sakurai T, Kim S, Maeda S, Kim K, Elsharkawy AM, Karin M (2007) Gender disparity in liver cancer due to sex differences in MyD88-dependent IL-6 production. Science 317: 121–124 [DOI] [PubMed] [Google Scholar]
  27. Ogino S, Kirkner GJ, Nosho K, Irahara N, Kure S, Shima K, Hazra A, Chan AT, Dehari R, Giovannucci EL, Fuchs CS (2008) Cyclooxygenase-2 expression is an independent predictor of poor prognosis in colon cancer. Clin Cancer Res 14: 8221–8227 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Rahman MM, Qian ZR, Wang EL, Sultana R, Kudo E, Nakasono M, Hayashi T, Kakiuchi S, Sano T (2009) Frequent overexpression of HMGA1 and 2 in gastroenteropancreatic neuroendocrine tumours and its relationship to let-7 downregulation. Br J Cancer 100: 501–510 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Rakoff-Nahoum S, Medzhitov R (2007) Regulation of spontaneous intestinal tumorigenesis through the adaptor protein MyD88. Science 317: 124–127 [DOI] [PubMed] [Google Scholar]
  30. Rakoff-Nahoum S, Medzhitov R (2009) Toll-like receptors and cancer. Nat Rev Cancer 9: 57–63 [DOI] [PubMed] [Google Scholar]
  31. Huang B, Zhao J, Unkeless JC, Feng ZH, Xiong H (2008) TLR signaling by tumor and immune cells: a double-edged sword. Oncogene 27: 218–224 [DOI] [PubMed] [Google Scholar]
  32. Scartozzi M, Bearzi I, Pierantoni C, Mandolesi A, Loupakis F, Zaniboni A, Catalano V, Quadri A, Zorzi F, Berardi R, Biscotti T, Labianca R, Falcone A, Cascinu S (2007) Nuclear factor-κB tumor expression predicts response and survival in irinotecan-refractory metastatic colorectal cancer treated with cetuximab-irinotecan therapy. J Clin Oncol 25: 3930–3935 [DOI] [PubMed] [Google Scholar]
  33. Schwartz AL, Malgor R, Dickerson E, Weeraratna AT, Slominski A, Wortsman J, Harii N, Kohn AD, Moon RT, Schwartz FL, Goetz DJ, Kohn LD, McCall KD (2009) Phenylmethimazole decreases Toll-like receptor 3 and noncanonical Wnt5a expression in pancreatic cancer and melanoma together with tumor cell growth and migration. Clin Cancer Res 15: 4114–4122 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Shishodia S, Aggarwal BB (2004) Nuclear factor-κB: a friend or a foe in cancer? Biochem Pharmacol 68: 1071–1080 [DOI] [PubMed] [Google Scholar]
  35. Sun Q, Liu Q, Zheng Y, Cao X (2008) Rapamycin suppresses TLR4-triggered IL-6 and PGE2 production of colon cancer cells by inhibiting TLR4 expression and NF-κB activation. Mol Immunol 45: 2929–2936 [DOI] [PubMed] [Google Scholar]
  36. Swann JB, Vesely MD, Silva A, Sharkey J, Akira S, Schreiber RD, Smyth MJ (2008) Demonstration of inflammation-induced cancer and cancer immunoediting during primary tumorigenesis. Proc Natl Acad Sci USA 105: 652–656 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Tsukuma H, Ajiki W, Oshima A (2004) Cancer incidence in Japan. Gan To Kagaku Ryoho 31: 840–846 (in Japanese, abstract in English) [PubMed] [Google Scholar]
  38. Wang JH, Manning BJ, Wu QD, Blankson S, Bouchier-Hayes D, Redmond HP (2003) Endotoxin/lipopolysaccharide activates NF-κB and enhances tumor cell adhesion and invasion through a β-1 integrin-dependent mechanism. J Immunol 170: 795–804 [DOI] [PubMed] [Google Scholar]
  39. Wang X, Huycke MM (2007) Extracellular superoxide production by Enterococcus faecalis promotes chromosomal instability in mammalian cells. Gastroenterology 132: 551–561 [DOI] [PubMed] [Google Scholar]
  40. Wolpin BM, Meyerhardt JA, Mamon HJ, Mayer RJ (2007) Adjuvant treatment of colorectal cancer. CA Cancer J Clin 57: 168–185 [DOI] [PubMed] [Google Scholar]
  41. Wolpin BM, Mayer RJ (2008) Systemic treatment of colorectal cancer. Gastroenterology 134: 1296–1310 [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from British Journal of Cancer are provided here courtesy of Cancer Research UK

RESOURCES