CLINICAL STUDY
Clinical Significance of Toll-like Receptor 3, 4, and 9 in Gastric Cancer Belen Fernandez-Garcia,* Noemı´ Eiro´,* Salome´ Gonza´lez-Reyes,* Lucı´a Gonza´lez,* Alina Aguirre,* Luis O. Gonza´lez,*w Jose´ M. del Casar,*z Jose´ L. Garcı´a-Mun˜iz,* and Francisco J. Vizoso*z
Summary: Toll-like receptors (TLRs) have raised an extraordinary interest in cancer research due to their role in tumor progression. By activating the production of several biological factors, TLRs drive an inflammatory response and activate the adaptive immune system. The aim of this study was to investigate the expression and clinical relevance of TLR3, TLR4, and TLR9 in gastric cancer. For this purpose, an immunohistochemical study on cancer specimens from 106 patients with gastric cancer was performed using tissue arrays and specific antibodies against TLR3, TLR4, and TLR9. The results indicate that gastric carcinomas samples show high expression of TLR3, TLR4, and TLR9 by cancer cells. The expression of TLR3 by cancer cells was significantly associated with a poor overall survival in patients with resectable tumors. Moreover, in patients with resectable tumors and lymph node invasion, a high TLR3 expression defines a population with even worse prognosis. Therefore, TLR3 may have clinical interest as indicator of tumor aggressiveness and as a prognostic indicator in gastric cancer. Key Words: Toll-like receptors, gastric carcinoma, tissue arrays, prognosis, tumor invasion
(J Immunother 2014;37:77–83)
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uman Toll-like receptors (TLRs) family consists of currently 11 members, which are structurally characterized by the presence of a leucine-rich repeat domain in their extracellular domain and a Toll/interleukin-1 receptor domain in their intracellular domain.1,2 TLR constitute a kind of link between innate (nonspecific) and adaptive (specific) immunity, and contribute to the capacity of our immune system to efficiently combat pathogens.3 This is done by means of the induction of signaling cascades resulting in the induction of type I interferon (IFNs) and other cytokines, which in turn drive an inflammatory response and activate the adaptive immune system.4 TLRs also enable immune cells to discriminate between self and nonself antigens.5 As molecular sensors, TLRs detect pathogen-derived products and trigger protective responses, including the secretion of cytokines that increase the resistance of infected cells, and the release of chemokines that recruit immune cells to dead cells, thus limiting microbe spreading.6 In this way, TLRs mediate the production of proinflammatory molecules resulting in inflammation. As we know, chronic inflammation plays a Received for publication May 18, 2013; accepted December 4, 2013. From the *Unidad de Investigacio´n; wServicio de Anatomı´ a Patolo´gica; and zServicio de Cirugı´ a General, Fundacio´n Hospital de Jove, Gijo´n, Spain. Reprints: Francisco J. Vizoso, Unidad de Investigacio´n, Fundacio´n Hospital de Jove, Avda. Eduardo Castro s/n, 33920 Gijo´n, Asturias, Spain. E-mail: investigacio´[email protected]. Copyright r 2014 by Lippincott Williams & Wilkins
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crucial role in the development of many human cancers,7 and the process may be mediated in part through various stimuli recognized by TLRs.8–10 The gastrointestinal tract, including stomach, is an organ system with a high incidence of cancer development and cancer-related mortality, accounting for 10% of the total cancer deaths among men and women,11 and it is rather singular due to its development in the presence of diverse enteric microflora. The human gastrointestinal tract contains 10–100 trillion microorganisms, increasing along the gastrointestinal tract from the stomach to the colon. The interaction between the microbiota and the intestinal mucosa through TLRs is required to maintain intestinal homeostasis, and to develop a normal adaptive immune response in the periphery.12 TLRs, as host genetic factors, play an important role in modifying the risk of human disease, such as conditions including Helicobacter pylorigastritis, which is the most important acquired risk factor for gastric cancer.13 Therefore, TLR signaling can play diverse roles with respect to tumorigenesis in stomach. In fact, mice deficient in TLRs were found to be protected from or develop less inducible tumors in experimental models.14,15 In addition, polymorphisms in TLRs have been associated with gastric cancer risk, which suggests that TLR signaling both at a genetic level and genomic level may be involved in the development of this malignancy.13,16,17 Likewise, gastric dysplasia presents a high level of TLRs expression, suggesting that these receptors may play a role in adenocarcinoma development.18,19 In this line, recently it was reported that genetic and therapeutic targeting of TLR2 inhibited gastric tumorigenesis, and that increased TLR2 expression was associated with poor survival in gastric cancer patients.20 However, there are no data about the expression and prognostic significance of the other TLRs in preestablished gastric carcinomas. Recently, we found high expression and prognostic significance of TLR3, TLR4, or TLR9 in tumors from breast, prostate, or colorectal origin, as well as in malignant melanomas.6,21–23 Now, the purpose of the present study was to investigate the expression of several TLRs in gastric cancer, and their relationship with prognosis. To address these questions we used tissue arrays (TA) technology and immunohistochemical techniques.
PATIENTS AND METHODS Patients’ Selection, Patients’ Characteristics, and Tissue Specimen Handling This study included a consecutive series of 106 patients with primary gastric adenocarcinoma, who underwent www.immunotherapy-journal.com |
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surgery from January 1992 to December 2005. Samples of gastric carcinomas were obtained from surgical specimens, being removed from the tumors and avoiding grossly necrotic tissues. Immediately after surgical resection samples were processed for pathologic examination. Patients’ age ranged from 40 to 85 years (average, 66.2 y). Each case was staged according to the TNM classification criteria advocated by the UICC.24 Surgical resectability of these tumors was classified according to these same criteria.24 The histologic tumor type was determined according to Lauren’s criteria.25 None of the patients received radiotherapy or systemic therapy. All patients were evaluated for disease recurrence and survival status by clinical and biochemical examinations (complete blood count, liver function tests, and serum carcinoembryonic antigen), upper gastrointestinal endoscopy, and diagnostic imaging (chest radiograph, ultrasonography, computed tomography, or magnetic resonance imaging) every 3 months during the first year and once every 6 months thereafter. Mean follow-up period was 32.43 months (range, 2–128 mo) for all patients. A total of 77 of the 106 patients died because of tumor recurrence. The patient selection and tissue handling have been used previously.26 The patients’ characteristics included in the study are listed in Table 1. The study adhered to national regulations and was approved by our Hospital’s Ethics and Investigation Committee.
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TA Immunohistochemistry and Analysis All specimens were routinely fixed in 10% neutral buffered formalin and stored after being embedded in paraffin at room temperature from 4 months to 5 years before further testing was performed. Histopathologic representative tumor areas were defined on haematoxylin and eosin–stained sections and marked on the slide. Tumor TA blocks were obtained by punching a tissue cylinder (core) with a diameter of 1.5 mm through a histologic representative area of each “donor” tumor block, which was then inserted into an empty “recipient” TA paraffin block using a manual tissue arrayer (Beecher Instruments, Sun Prairie, WI) as described elsewhere.27 Collection of tissue cores was carried out under highly controlled conditions. Two cores were used for each case. Four composite high-density TA blocks were designed, and serial 5 mm sections were consecutively cut with a microtome (Leica Microsystems GmbH, Wetzlar, Germany) and transferred to adhesive-coated slides. One section from each TA block was stained with hematoxylin and eosin, and these slides were then reviewed to confirm that the sample was representative of the original tumor. Immunohistochemistry was done on these sections of TA fixed in 10% buffered formalin and embedded in paraffin using a TechMate TM50 autostainer (Dako, Glostrup, Denmark). Antibodies for TLRs were obtained from Santa Cruz Biotechnology (CA). The dilution for each antibody
TABLE 1. Relationship Between TLRs Expression and Clinicopathologic Characteristics in Patients With Gastric Carcinomas
TLR3 Characteristics Age (y) < 70 (median) > 70 Sex Female Male Tumor location Upper third Median third Lower third Histologic type Intestinal Diffuse Histologic grade Well differentiated Moderately differentiated Poorly differentiated Tumor stage I II III IV Lymph node invasion No Yes Lymphatic invasion No Yes Surgical resectability R0 R1 R2
n
Median (Range)
TLR4 P
TLR9 P
Median (Range)
0.432 55 51
30.4 (0–132.8) 39.2 (0–147.4)
34 72
23.7 (0–147.4) 40.3 (0–132.8)
20 35 51
49.4 (2.47–125.8) 46.4 (0–147.4) 20.9 (0–132.8)
69 37
37.4 (0–147.4) 38.6 (0–132.8)
19 33 54
45.6 (0–136.8) 40.1 (0–92.6) 34.9 (0–147.4)
17 20 44 25
48.9 36.6 38.6 34.9
35 71
49.3 (0–147.4) 34.6 (0–119.4)
86 20
38.9 (0–147.4) 36.3 (0–82.5)
63 14 29
39.2 (0–147.4) 32.4 (0–93.3) 36.3 (0–132.8)
14.8 (0–74.9) 18.1 (0–67.7) 0.146 28.8 (0–66.7) 10.9 (0–74.9)
0.311 93.5 (25–205.2) 71.8 (0–216.1)
0.667
0.008 23.1 (0–74.9) 24.8 (0–72.7) 12.7 (0–66.6)
0.107 56.7 (12.5–136.3) 104.8 (0–205.2) 67.5 (0–216.1)
0.889
0.857 18.1 (0–74.9) 14.8 (0–72.7)
0.545 75.8 (0–205.2) 71.8 (0–216.1)
0.446
0.622 28.8 (0–74.9) 14.6 (0–64.7) 15.3 (0–72.7)
0.749 93.2 (29.6–148.5) 84.3 (0–216.1) 69.3 (8.4–205.2)
0.949
0.543 10.9 30.9 15.6 19.1
P 0.809
74.9 (0–202.7) 73.1 (0–216.1)
0.269
(0–147.4) (0–88.9) (0–132.8) (0–119.4)
Median (Range)
0.786
(0–67.7) (0–74.9) (0–61.2) (0–70.3)
0.814 71.8 88.3 64.5 93.9
0.111
(13.4–205.2) (25.1–202.7) (0–216.09) (8.4–190.2)
0.360 23.2 (0–74.9) 16.4 (0–70.3)
0.729 71.8 (13.4–205.2) 77.5 (0–216.1)
0.846
0.153 19.1 (0–74.9) 2.0 (0–66.6)
0.710 74.3 (12.5–205.2) 71.7 (0–216.1)
0.998
0.088 15.3 (0–74.9) 36 (0–66.6) 10.0 (0–70.3)
0.904 72.8 (0–216.1) 105.4 (31.9–148.5) 74.2 (0–197.3)
Values in bold are significant at P < 0.05. TLR indicates Toll-like receptor.
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was 1/10 for TLR3, 1/40 for TLR4, and 1/80 for TLR9, and were established based on negative and positive samples as described elsewhere.28 We also used antibodies against cytokeratins (AE1–AE3 ready to use, Dako) and vimentin (1/100, Dako) to distinguish fibroblasts from tumoral cells, as well as several markers to distinguish mononuclear inflammatory cells (MICs): T lymphocytes (CD3, CD45Ro, CD4, and CD8), B lymphocytes (CD20, CD79a), and macrophages (CD68), all from Dako. Tissue sections were deparaffinized in xylene, and then rehydrated. Endogenous peroxidase activity was blocked by incubating the slides in peroxidase-blocking solution (Dako) for 5 minutes. The EnVision Detection Kit (Dako) was used as the staining detection system. Sections were counterstained with hematoxylin, dehydrated with ethanol, and permanently coverslipped. For each antibody preparation studied, the location of immunoreactivity, percentage of stained cells, and intensity were determined. All the cases were semiquantified for each protein-stained area. An image analysis system with the Olympus BX51 microscope and analysis software (AnalySIS; Soft imaging system, Mu¨nster, Germany) was used as follows: tumor sections were stained with antibodies according to the method explained previously and counterstained with hematoxylin. Each core was scanned with a 400 power objective in 2 fields per core, which were selected searching for the protein-stained areas. The computer program selects and traces a line around antibody-stained areas (higher optical threshold: red spots), with the remaining, nonstained areas (hematoxylin-stained tissue with lower optical threshold) standing out as a blue background. The area ratio for a field was obtained by comparing stained (red) areas to nonstained (blue) areas. A final area ratio was obtained after averaging 2 fields. To evaluate immunostaining intensity we used a numeric score ranging from 0 to 3, reflecting the intensity as follows: 0, no staining; 1, weak staining; 2, moderate staining; and 3, intense staining. The mean score was obtained by multiplying the intensity score (I) by the percentage of stained cells (PC) and the results were added together (total score: IPC). This overall score was then averaged with the number of cores that were done for each patient. If there was no tumor in a particular core, then no score was given. In addition, for each tumor, the mean score of 2 core biopsies was calculated. This scoring evaluation was based on a global evaluation of staining areas corresponding to tumor cells and to stromal cells. Nevertheless, in the present work we also evaluated the immunohistochemical staining exclusively in cancerous cells or in stromal cells (MICs and fibroblast-like cells), and every evaluated field contained at least 10 stromal MICs. We distinguished stromal cells from cancer cells because the latter are larger in size and, in addition, fibroblast are spindle shaped, whereas MICs are rounded. Moreover, cancer cells are arranged forming either acinar or trabecular patterns, whereas stromal cells are spread. In addition, we used several markers to distinguish fibroblasts and MICs as described previously.
Data Analysis and Statistical Methods Differences in percentages were calculated with the w2 test. Immunostaining score values for each protein were expressed as median (range). Comparison of immunostaining values between groups was made with the MannWhitney or Kruskal-Wallis tests. The Cox regression model was used to examine interactions of different prognostic factors in a multivariate analysis. For metastasis-free r
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Clinical Significance of TLRs in Gastric Cancer
survival analysis we used the Cox univariate method. The SPSS 18.0 program was used for all calculations. All these methods have been used previously in similar studies from our group.6,21,29
RESULTS In the present study, we investigated the expression of TLR3, TLR4, and TLR9 in 106 patients with gastric cancer. Figure 1 shows examples of immunostaining for these proteins, including negative controls in gastric mucosa (Figs. 1A–C) and positive controls in breast carcinoma samples known to express these TLRs (Figs. 1D–F)6; TLR3, TLR4, and TLR9 have cytoplasmic (the 3 TLRs, Figs. 1G–I) and also membrane location for TLR3 and TLR9 (arrows in Figs. 1G, I) in positive gastric carcinoma cells. In most cases the positive staining was generally found in tumor cells, and less frequently in stromal cells (in fibroblast-like cells and in MICs), even though it is well known that immune cells express TLRs at high level; as shown in Figure 1, gastric carcinoma cells expressed TLR3 and TLR9, but macrophages expressing CD68 (Fig. 1J) showed no expression for those TLRs (Figs. 1K, L). Table 2 shows the number and percentages of tumors positive for each TLR by each cellular type. Tumors showed high expression of TLRs by cancer cells. Nevertheless, a significant percentage of tumors also showed expression of TLR3 and TLR9 by MICs (14.2% and 13.2%, respectively) and by fibroblast-like cells (4.7% and 6.6%, respectively). We also evaluated the possible relationship between TLRs expression and the clinicopathologic factors of gastric carcinomas, including tumor location, histologic type and grade, stage, lymph node involvement, lymphatic invasion, and resectability (Table 1). We found a significant association only between TLR3 score values and tumor location, with tumors located in the lower third showing lower TLR3 values (P = 0.008). The potential association between TLRs score and overall survival was evaluated in the 63 patients with resectable (R0) tumors included in the present study. Patients with R1 and R2 resection were not evaluated, as they are more prone to develop recurrence. First, an optimal cutoff value was defined by statistical analysis of the TLRs score values to predict the overall survival of the study population. This statistical analysis showed a continuous association only between TLR3 score values and overall survival in patients with R0 surgical resection. Figure 2A shows the determination of the optimal cutoff value of the TLR3 scores in R0 gastric tumors for predicting overall survival. P-values obtained for each cutoff value are plotted against the value itself. This analysis led us to define a value of TLR3 of 20 as the optimal cutoff point (w2 = 7.92, P = 0.05). Figure 2B shows overall survival curves in patients with R0 tumors according to the optimal cutoff point for TLR3 score values, indicating that patients with R0 tumors and high TLR3 expression (score value >20) have poor prognosis (P = 0.005). Moreover, in patients with R0 tumors and lymph node invasion, the occurrence of a high TLR3 expression defines a population with even worse overall survival (P = 0.003) (Fig. 2C). However, multivariate analysis according to the Cox model indicated that TLR3 levels showed no significance as independent prognostic factor (data not shown). www.immunotherapy-journal.com |
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FIGURE 1. Examples of TLR immunostaining. Negative controls ( 400) in gastric carcinoma for TLR3 (A), TLR4 (B), and TLR9 (C); positive controls ( 400) in breast carcinoma samples for TLR3 (D), TLR4 (E), and TLR9 (F); positive immunostaining in gastric carcinoma ( 400) for TLR3 (G), TLR4 (H), and TLR9 (I), indicating the membrane-specific staining for TLR3 and TLR9 (arrows). Pictures showing positive immunostaining for TLR3 (K) and TLR9 (L) in tumor cells, but negative for immune cells (macrophages) identified by CD68 immunostaining (J).
DISCUSSION This study analyzes tumor expression of TLR3, TLR4, and TLR9, and for the first time the prognostic significance of this expression, in patients with preestablished gastric cancer. The results showed high expression of these TLRs by cancer cells compared with stromal cells (fibroblast or MICs). In addition, the expression of TLR3 was significantly associated with a poor overall survival in patients with resectable tumors. It is known that normal intestinal epithelial cells and lamina propia mononuclear cells must respond to breaches in the mucosal barrier by activating TLR-
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dependent pathways that result in increased epithelial proliferation, wound healing, and recruitment of acute inflammatory cells.12 However, it has been shown that cells from several malignant tumors display increased TLR expression,6,21–23 and also mice deficient in such receptors may be protected from, or develop fewer, inducible tumors in experimental models.14,15 Therefore, the expression of these receptors by tumoral cells may display several actions promoting cancer progression. Cancer cells activated by TLRs signals can release cytokines and chemokines which in turn recruit immune cells and stimulate them to release further cytokines and chemokines. This process results in r
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TABLE 2. TLR Expression by Each Cell Type in 106 Cases of Gastric Cancer
Positive Cases [n (%)] Factor
Tumor Cells
Fibroblasts
MICs
TLR3 TLR4 TLR9
64 (60.4) 51 (48.1) 93 (87.7)
5 (4.7) 0 7 (6.6)
15 (14.2) 0 14 (13.2)
Samples on tissue sections were either insufficient or lost for analysis in 24 cases for TLR3, 29 cases for TLR4, and 11 cases for TLR9. MICs indicates mononuclear inflammatory cells; TLR, Toll-like receptor.
an aberrant cytokine profile that is associated with the promotion of angiogenesis and subversion of adaptive immunity with immune tolerance.30,31 TLR-mediated signals transduced through the adapter protein myeloid differentiation factor 88 (MyD88) and through the TIR-domain-
Clinical Significance of TLRs in Gastric Cancer
containing adapter-inducing interferon-b (TRIF) protein. This is relevant because these both MyD88-dependent and the MyD88-independent pathways mediate nuclear factor-k B (NF-kB) activation and subsequent inflammatory cytokine production though different mechanisms and kinetics. It is known that NF-kB activation participate in carcinogenic promotion and progression by different mechanisms, such as cell proliferation, antiapoptosis, angiogenesis, invasion, and metastasis.32 In addition, TLRs also enhances tumor cell invasion and metastasis by regulating metalloproteases and integrins.33–36 In fact, we have described recently that some metalloproteases (MMP-1, MMP-13, and MMP-14) and their inhibitors (TIMP-3) are overexpressed in gastric carcinoma samples, when compared with normal gastric tissue.37 Our data also show a variability of TLR expressions among gastric carcinomas, which may be consequence of the biological heterogeneity of these tumors. Consequently, we also investigate whether these variations in TLR amount by tumors might have a prognostic value. TLR4 and TLR9
FIGURE 2. Analysis of cutoff points and overall survival for TLR3 score in resectable (R0) patients. A, Maximum likelihood determination of the cutoff value of the TLR3 score in R0 gastric tumor for predicting overall survival in patients with gastric cancer. P-values obtained for each cutoff value are plotted against the value itself. Statistical significance is indicated by the horizontal line at the 0.05 level. Analysis led to the definition of a TLR3 score value (marked with an arrow) as the optimal cutoff point (r2 = 7.92, P = 0.05). B, Overall survival curve in R0 patients as a function of the optimal cutoff point for TLR3 score values (P = 0.005). C, Overall survival curve in R0 patients with lymph node invasion, as a function of the optimal cutoff point for TLR3 score values (P = 0.003). r
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are involved in the interaction with H. pylori, resulting in chronic gastritis38 and inducing invasion and angiogenesis at gastric mucosa.19,39 Our results did not show association of these TLRs expression by tumors with clinicopathologic factors in patients with gastric carcinomas. However, our data suggest that the expression of TLR3 in cancer cells is associated with tumor location in patients, and also related with poor survival in patients with resectable tumors. Thus, our results are in agreement with previous observations reporting that regulation of TLR3 is associated with pathogenesis and/or increased tumoral aggressiveness in different tumor types, such as breast, endometrial, prostate, colorectal renal carcinomas, and cutaneous malignant melanomas.6,21–23,40–44 In addition, it was recently shown a positive correlation between mRNA relative expression of TLR3 and chemokine (C-X-C motif) receptor 4 (CXCR4), and also mRNA relative expression of TLR3 was found significantly increased in breast cancer tumor tissue from patients expressing high IFN-g. Thus, it has been proposed that an overexpression of IFN-g mRNA due to the proinflammatory microenvironment can lead to an upregulation of CXCR4 mRNA and consequently to an increased TLR3 mRNA expression.45 Further studies are necessary to explore the possible role and clinical significance of TLR3 expression in a possible molecular inflammatory axis in the microenvironment of gastric carcinomas. Our data suggest that TLR3 expression in combination with other prognostic factors may contribute to a better prognostic evaluation of patients with resectable gastric carcinomas. In addition, our data could open a new line of research to explore the possible contribution of viral infections to the origin and progression of gastric cancer. This is because double-stranded RNA produced by most viruses during replication is capable of activating signaling pathways depending on TLR3 stimulation.46–50 In contrast, there are studies showing a variable antineoplastic effect caused by a blockage of TLR351,52 and therefore TLR3 might represent a good therapeutic target in gastric cancer. CONFLICTS OF INTEREST/ FINANCIAL DISCLOSURES Supported by grants from Fondo de Investigacio´n Sanitaria from Instituto Carlos III (FIS-PI070306) and FICEMU. All authors have declared there are no financial conflicts of interest with regard to this work. REFERENCES 1. Akira S, Takeda K. Toll-like receptor signalling. Nat Rev Immunol. 2004;4:499–511. 2. Moynagh PN. TLR signalling and activation of IRFs: revisiting old friends from the NF-kappa B pathway. Trends Immunol. 2005;26:469–476. 3. Kawai T, Akira S. TLR signaling. Cell Death Differ. 2006;13: 816–825. 4. Pasare C, Medzhitov R. Toll-like receptors: linking innate and adaptive immunity. Microbes Infect. 2004;6:1382–1387. 5. Matzinger P. An innate sense of danger. Ann N Y Acad Sci. 2002;961:341–342. 6. Gonzalez-Reyes S, Marin L, Gonzalez L, et al. Study of TLR3, TLR4 and TLR9 in breast carcinomas and their association with metastasis. BMC Cancer. 2010;10:665–673. 7. Alexopoulou L, Holt AC, Medzhitov R, et al. Recognition of double-stranded RNA and activation of NF-kappa B by Tolllike receptor 3. Nature. 2001;413:732–738. 8. Coussens LM, Werb Z. Inflammation and cancer. Nature. 2002;420:860–867.
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9. Hayashi F, Smith KD, Ozinsky A, et al. The innate immune response to bacterial flagellin is mediated by Toll-like receptor 5. Nature. 2001;410:1099–1103. 10. Zhang YB, He FL, Fang M, et al. Increased expression of Tolllike receptors 4 and 9 in human lung cancer. Mol Biol Rep. 2009;36:1475–1481. 11. Jemal A, Bray F, Center MM, et al. Global cancer statistics. CA Cancer J Clin. 2011;61:69–90. 12. Fukata M, Abreu MT. Role of Toll-like receptors in gastrointestinal malignancies. Oncogene. 2008;27:234–243. 13. Hold GL, Rabkin CS, Chow WH, et al. A functional polymorphism of toll-like receptor 4 gene increases risk of gastric carcinoma and its precursors. Gastroenterology. 2007;132:905–912. 14. Fukata M, Chen A, Vamadevan AS, et al. Toll-like receptor-4 promotes the development of colitis-associated colorectal tumors. Gastroenterology. 2007;133:1869–1881. 15. Swann JB, Vesely MD, Silva A, et al. Demonstration of inflammation-induced cancer and cancer immunoediting during primary tumorigenesis. Proc Natl Acad Sci U S A. 2008; 105:652–656. 16. Ohara T, Morishita T, Suzuki H, et al. Heterozygous Thr 135 Ala polymorphism at leucine-rich repeat (LRR) in genomic DNA of toll-like receptor 4 in patients with poorly-differentiated gastric adenocarcinomas. Int J Mol Med. 2006;18:59–63. 17. Zeng HM, Pan KF, Zhang Y, et al. Genetic variants of toll-like receptor 2 and 5, Helicobacter pylori infection, and risk of gastric cancer and its precursors in a Chinese population. Cancer Epidemiol Biomarkers Prev. 2011;20:2594–2602. 18. Pimentel-Nunes P, Afonso L, Lopes P, et al. Increased expression of toll-like receptors (TLR) 2, 4 and 5 in gastric dysplasia. Pathol Oncol Res. 2011;17:677–683. 19. Pimentel-Nunes P, Goncalves N, Boal-Carvalho I, et al. Helicobacter pylori induces increased expression of Toll-like receptors and decreased Toll-interacting protein in gastric mucosa that persists throughout gastric carcinogenesis. Helicobacter. 2013;18:22–32. 20. Tye H, Kennedy CL, Najdovska M, et al. STAT3-driven upregulation of TLR2 promotes gastric tumorigenesis independent of tumor inflammation. Cancer Cell. 2012;22: 466–478. 21. Gonzalez-Reyes S, Fernandez JM, Gonzalez LO, et al. Study of TLR3, TLR4, and TLR9 in prostate carcinomas and their association with biochemical recurrence. Cancer Immunol Immunother. 2011;60:217–226. 22. Eiro N, Ovies C, Fernandez-Garcia B, et al. Expression of TLR3, 4, 7 and 9 in cutaneous malignant melanoma: relationship with clinicopathological characteristics and prognosis. Arch Dermatol Res. 2013;305:59–67. 23. Eiro N, Gonzalez L, Gonzalez LO, et al. Study of the expression of toll-like receptors in different histological types of colorectal polyps and their relationship with colorectal cancer. J Clin Immunol. 2012;32:848–854. 24. UICC. TNM Classification of Malignant Tumors. 7th ed. Hoboken, NJ: Wiley-Blackwell; 2010. 25. Lauren P. The two histological main types of gastric carcinoma: diffuse and so-called intestinal-type carcinoma. An attempt at a histo-clinical classification. Acta Pathol Microbiol Scand. 1965;64:31–49. 26. Vizoso FJ, del Casar JM, Corte MD, et al. Significance of cytosolic hyaluronan levels in gastric cancer. Eur J Surg Oncol. 2004;30:318–324. 27. Parker RL, Huntsman DG, Lesack DW, et al. Assessment of interlaboratory variation in the immunohistochemical determination of estrogen receptor status using a breast cancer tissue microarray. Am J Clin Pathol. 2002;117:723–728. 28. Gonzalez-Reyes S, Fernandez JM, Gonzalez LO, et al. Study of TLR3, TLR4, and TLR9 in prostate carcinomas and their association with biochemical recurrence. Cancer Immunol Immunother. 2011;60:217–226. 29. Gonzalez LO, Corte MD, Vazquez J, et al. Androgen receptor expression in breast cancer: relationship with clinicopathological characteristics of the tumors, prognosis, and expression of r
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42. Allhorn S, Boing C, Koch AA, et al. TLR3 and TLR4 expression in healthy and diseased human endometrium. Reprod Biol Endocrinol. 2008;6:40–50. 43. Morikawa T, Sugiyama A, Kume H, et al. Identification of Toll-like receptor 3 as a potential therapeutic target in clear cell renal cell carcinoma. Clin Cancer Res. 2007;13:5703–5709. 44. Chin AI, Miyahira AK, Covarrubias A, et al. Toll-like receptor 3-mediated suppression of TRAMP prostate cancer shows the critical role of type I interferons in tumor immune surveillance. Cancer Res. 2010;70:2595–2603. 45. Amarante MK, de Oliveira KB, Guembarovski RL, et al. Toll-like receptor 3: implications for proinflammatory microenvironment in human breast cancer. Mol Biol Rep. 2012;39: 11087–11092. 46. Edelmann KH, Richardson-Burns S, Alexopoulou L, et al. Does Toll-like receptor 3 play a biological role in virus infections? Virology. 2004;322:231–238. 47. Lore K, Betts MR, Brenchley JM, et al. Toll-like receptor ligands modulate dendritic cells to augment cytomegalovirusand HIV-1-specific T cell responses. J Immunol. 2003;171: 4320–4328. 48. Majde JA, Kapas L, Bohnet SG, et al. Attenuation of the influenza virus sickness behavior in mice deficient in Toll-like receptor 3. Brain Behav Immun. 2010;24:306–315. 49. Askar E, Bregadze R, Mertens J, et al. TLR3 gene polymorphisms and liver disease manifestations in chronic hepatitis C. J Med Virol. 2009;81:1204–1211. 50. Sato A, Iizuka M, Nakagomi O, et al. Rotavirus doublestranded RNA induces apoptosis and diminishes wound repair in rat intestinal epithelial cells. J Gastroenterol Hepatol. 2006; 21:521–530. 51. Khan AL, Richardson S, Drew J, et al. Polyadenylicpolyuridylic acid enhances the natural cell-mediated cytotoxicity in patients with breast cancer undergoing mastectomy. Surgery. 1995;118:531–538. 52. Lacour F, Lacour J, Spira A, et al. Adjuvant immunotherapy using polyadenylic acid and polyuridylic acid (Poly A., Poly U.) in operable carcinoma of the breast (author’s transl). Chirurgie. 1980;106:737–743.
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Clinical Significance of Toll-like Receptor 3, 4, and 9 in Gastric Cancer Belen Fernandez-Garcia,* Noemı´ Eiro´,* Salome´ Gonza´lez-Reyes,* Lucı´a Gonza´lez,* Alina Aguirre,* Luis O. Gonza´lez,*w Jose´ M. del Casar,*z Jose´ L. Garcı´a-Mun˜iz,* and Francisco J. Vizoso*z
Summary: Toll-like receptors (TLRs) have raised an extraordinary interest in cancer research due to their role in tumor progression. By activating the production of several biological factors, TLRs drive an inflammatory response and activate the adaptive immune system. The aim of this study was to investigate the expression and clinical relevance of TLR3, TLR4, and TLR9 in gastric cancer. For this purpose, an immunohistochemical study on cancer specimens from 106 patients with gastric cancer was performed using tissue arrays and specific antibodies against TLR3, TLR4, and TLR9. The results indicate that gastric carcinomas samples show high expression of TLR3, TLR4, and TLR9 by cancer cells. The expression of TLR3 by cancer cells was significantly associated with a poor overall survival in patients with resectable tumors. Moreover, in patients with resectable tumors and lymph node invasion, a high TLR3 expression defines a population with even worse prognosis. Therefore, TLR3 may have clinical interest as indicator of tumor aggressiveness and as a prognostic indicator in gastric cancer. Key Words: Toll-like receptors, gastric carcinoma, tissue arrays, prognosis, tumor invasion
(J Immunother 2014;37:77–83)
H
uman Toll-like receptors (TLRs) family consists of currently 11 members, which are structurally characterized by the presence of a leucine-rich repeat domain in their extracellular domain and a Toll/interleukin-1 receptor domain in their intracellular domain.1,2 TLR constitute a kind of link between innate (nonspecific) and adaptive (specific) immunity, and contribute to the capacity of our immune system to efficiently combat pathogens.3 This is done by means of the induction of signaling cascades resulting in the induction of type I interferon (IFNs) and other cytokines, which in turn drive an inflammatory response and activate the adaptive immune system.4 TLRs also enable immune cells to discriminate between self and nonself antigens.5 As molecular sensors, TLRs detect pathogen-derived products and trigger protective responses, including the secretion of cytokines that increase the resistance of infected cells, and the release of chemokines that recruit immune cells to dead cells, thus limiting microbe spreading.6 In this way, TLRs mediate the production of proinflammatory molecules resulting in inflammation. As we know, chronic inflammation plays a Received for publication May 18, 2013; accepted December 4, 2013. From the *Unidad de Investigacio´n; wServicio de Anatomı´ a Patolo´gica; and zServicio de Cirugı´ a General, Fundacio´n Hospital de Jove, Gijo´n, Spain. Reprints: Francisco J. Vizoso, Unidad de Investigacio´n, Fundacio´n Hospital de Jove, Avda. Eduardo Castro s/n, 33920 Gijo´n, Asturias, Spain. E-mail: investigacio´[email protected]. Copyright r 2014 by Lippincott Williams & Wilkins
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crucial role in the development of many human cancers,7 and the process may be mediated in part through various stimuli recognized by TLRs.8–10 The gastrointestinal tract, including stomach, is an organ system with a high incidence of cancer development and cancer-related mortality, accounting for 10% of the total cancer deaths among men and women,11 and it is rather singular due to its development in the presence of diverse enteric microflora. The human gastrointestinal tract contains 10–100 trillion microorganisms, increasing along the gastrointestinal tract from the stomach to the colon. The interaction between the microbiota and the intestinal mucosa through TLRs is required to maintain intestinal homeostasis, and to develop a normal adaptive immune response in the periphery.12 TLRs, as host genetic factors, play an important role in modifying the risk of human disease, such as conditions including Helicobacter pylorigastritis, which is the most important acquired risk factor for gastric cancer.13 Therefore, TLR signaling can play diverse roles with respect to tumorigenesis in stomach. In fact, mice deficient in TLRs were found to be protected from or develop less inducible tumors in experimental models.14,15 In addition, polymorphisms in TLRs have been associated with gastric cancer risk, which suggests that TLR signaling both at a genetic level and genomic level may be involved in the development of this malignancy.13,16,17 Likewise, gastric dysplasia presents a high level of TLRs expression, suggesting that these receptors may play a role in adenocarcinoma development.18,19 In this line, recently it was reported that genetic and therapeutic targeting of TLR2 inhibited gastric tumorigenesis, and that increased TLR2 expression was associated with poor survival in gastric cancer patients.20 However, there are no data about the expression and prognostic significance of the other TLRs in preestablished gastric carcinomas. Recently, we found high expression and prognostic significance of TLR3, TLR4, or TLR9 in tumors from breast, prostate, or colorectal origin, as well as in malignant melanomas.6,21–23 Now, the purpose of the present study was to investigate the expression of several TLRs in gastric cancer, and their relationship with prognosis. To address these questions we used tissue arrays (TA) technology and immunohistochemical techniques.
PATIENTS AND METHODS Patients’ Selection, Patients’ Characteristics, and Tissue Specimen Handling This study included a consecutive series of 106 patients with primary gastric adenocarcinoma, who underwent www.immunotherapy-journal.com |
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surgery from January 1992 to December 2005. Samples of gastric carcinomas were obtained from surgical specimens, being removed from the tumors and avoiding grossly necrotic tissues. Immediately after surgical resection samples were processed for pathologic examination. Patients’ age ranged from 40 to 85 years (average, 66.2 y). Each case was staged according to the TNM classification criteria advocated by the UICC.24 Surgical resectability of these tumors was classified according to these same criteria.24 The histologic tumor type was determined according to Lauren’s criteria.25 None of the patients received radiotherapy or systemic therapy. All patients were evaluated for disease recurrence and survival status by clinical and biochemical examinations (complete blood count, liver function tests, and serum carcinoembryonic antigen), upper gastrointestinal endoscopy, and diagnostic imaging (chest radiograph, ultrasonography, computed tomography, or magnetic resonance imaging) every 3 months during the first year and once every 6 months thereafter. Mean follow-up period was 32.43 months (range, 2–128 mo) for all patients. A total of 77 of the 106 patients died because of tumor recurrence. The patient selection and tissue handling have been used previously.26 The patients’ characteristics included in the study are listed in Table 1. The study adhered to national regulations and was approved by our Hospital’s Ethics and Investigation Committee.
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TA Immunohistochemistry and Analysis All specimens were routinely fixed in 10% neutral buffered formalin and stored after being embedded in paraffin at room temperature from 4 months to 5 years before further testing was performed. Histopathologic representative tumor areas were defined on haematoxylin and eosin–stained sections and marked on the slide. Tumor TA blocks were obtained by punching a tissue cylinder (core) with a diameter of 1.5 mm through a histologic representative area of each “donor” tumor block, which was then inserted into an empty “recipient” TA paraffin block using a manual tissue arrayer (Beecher Instruments, Sun Prairie, WI) as described elsewhere.27 Collection of tissue cores was carried out under highly controlled conditions. Two cores were used for each case. Four composite high-density TA blocks were designed, and serial 5 mm sections were consecutively cut with a microtome (Leica Microsystems GmbH, Wetzlar, Germany) and transferred to adhesive-coated slides. One section from each TA block was stained with hematoxylin and eosin, and these slides were then reviewed to confirm that the sample was representative of the original tumor. Immunohistochemistry was done on these sections of TA fixed in 10% buffered formalin and embedded in paraffin using a TechMate TM50 autostainer (Dako, Glostrup, Denmark). Antibodies for TLRs were obtained from Santa Cruz Biotechnology (CA). The dilution for each antibody
TABLE 1. Relationship Between TLRs Expression and Clinicopathologic Characteristics in Patients With Gastric Carcinomas
TLR3 Characteristics Age (y) < 70 (median) > 70 Sex Female Male Tumor location Upper third Median third Lower third Histologic type Intestinal Diffuse Histologic grade Well differentiated Moderately differentiated Poorly differentiated Tumor stage I II III IV Lymph node invasion No Yes Lymphatic invasion No Yes Surgical resectability R0 R1 R2
n
Median (Range)
TLR4 P
TLR9 P
Median (Range)
0.432 55 51
30.4 (0–132.8) 39.2 (0–147.4)
34 72
23.7 (0–147.4) 40.3 (0–132.8)
20 35 51
49.4 (2.47–125.8) 46.4 (0–147.4) 20.9 (0–132.8)
69 37
37.4 (0–147.4) 38.6 (0–132.8)
19 33 54
45.6 (0–136.8) 40.1 (0–92.6) 34.9 (0–147.4)
17 20 44 25
48.9 36.6 38.6 34.9
35 71
49.3 (0–147.4) 34.6 (0–119.4)
86 20
38.9 (0–147.4) 36.3 (0–82.5)
63 14 29
39.2 (0–147.4) 32.4 (0–93.3) 36.3 (0–132.8)
14.8 (0–74.9) 18.1 (0–67.7) 0.146 28.8 (0–66.7) 10.9 (0–74.9)
0.311 93.5 (25–205.2) 71.8 (0–216.1)
0.667
0.008 23.1 (0–74.9) 24.8 (0–72.7) 12.7 (0–66.6)
0.107 56.7 (12.5–136.3) 104.8 (0–205.2) 67.5 (0–216.1)
0.889
0.857 18.1 (0–74.9) 14.8 (0–72.7)
0.545 75.8 (0–205.2) 71.8 (0–216.1)
0.446
0.622 28.8 (0–74.9) 14.6 (0–64.7) 15.3 (0–72.7)
0.749 93.2 (29.6–148.5) 84.3 (0–216.1) 69.3 (8.4–205.2)
0.949
0.543 10.9 30.9 15.6 19.1
P 0.809
74.9 (0–202.7) 73.1 (0–216.1)
0.269
(0–147.4) (0–88.9) (0–132.8) (0–119.4)
Median (Range)
0.786
(0–67.7) (0–74.9) (0–61.2) (0–70.3)
0.814 71.8 88.3 64.5 93.9
0.111
(13.4–205.2) (25.1–202.7) (0–216.09) (8.4–190.2)
0.360 23.2 (0–74.9) 16.4 (0–70.3)
0.729 71.8 (13.4–205.2) 77.5 (0–216.1)
0.846
0.153 19.1 (0–74.9) 2.0 (0–66.6)
0.710 74.3 (12.5–205.2) 71.7 (0–216.1)
0.998
0.088 15.3 (0–74.9) 36 (0–66.6) 10.0 (0–70.3)
0.904 72.8 (0–216.1) 105.4 (31.9–148.5) 74.2 (0–197.3)
Values in bold are significant at P < 0.05. TLR indicates Toll-like receptor.
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was 1/10 for TLR3, 1/40 for TLR4, and 1/80 for TLR9, and were established based on negative and positive samples as described elsewhere.28 We also used antibodies against cytokeratins (AE1–AE3 ready to use, Dako) and vimentin (1/100, Dako) to distinguish fibroblasts from tumoral cells, as well as several markers to distinguish mononuclear inflammatory cells (MICs): T lymphocytes (CD3, CD45Ro, CD4, and CD8), B lymphocytes (CD20, CD79a), and macrophages (CD68), all from Dako. Tissue sections were deparaffinized in xylene, and then rehydrated. Endogenous peroxidase activity was blocked by incubating the slides in peroxidase-blocking solution (Dako) for 5 minutes. The EnVision Detection Kit (Dako) was used as the staining detection system. Sections were counterstained with hematoxylin, dehydrated with ethanol, and permanently coverslipped. For each antibody preparation studied, the location of immunoreactivity, percentage of stained cells, and intensity were determined. All the cases were semiquantified for each protein-stained area. An image analysis system with the Olympus BX51 microscope and analysis software (AnalySIS; Soft imaging system, Mu¨nster, Germany) was used as follows: tumor sections were stained with antibodies according to the method explained previously and counterstained with hematoxylin. Each core was scanned with a 400 power objective in 2 fields per core, which were selected searching for the protein-stained areas. The computer program selects and traces a line around antibody-stained areas (higher optical threshold: red spots), with the remaining, nonstained areas (hematoxylin-stained tissue with lower optical threshold) standing out as a blue background. The area ratio for a field was obtained by comparing stained (red) areas to nonstained (blue) areas. A final area ratio was obtained after averaging 2 fields. To evaluate immunostaining intensity we used a numeric score ranging from 0 to 3, reflecting the intensity as follows: 0, no staining; 1, weak staining; 2, moderate staining; and 3, intense staining. The mean score was obtained by multiplying the intensity score (I) by the percentage of stained cells (PC) and the results were added together (total score: IPC). This overall score was then averaged with the number of cores that were done for each patient. If there was no tumor in a particular core, then no score was given. In addition, for each tumor, the mean score of 2 core biopsies was calculated. This scoring evaluation was based on a global evaluation of staining areas corresponding to tumor cells and to stromal cells. Nevertheless, in the present work we also evaluated the immunohistochemical staining exclusively in cancerous cells or in stromal cells (MICs and fibroblast-like cells), and every evaluated field contained at least 10 stromal MICs. We distinguished stromal cells from cancer cells because the latter are larger in size and, in addition, fibroblast are spindle shaped, whereas MICs are rounded. Moreover, cancer cells are arranged forming either acinar or trabecular patterns, whereas stromal cells are spread. In addition, we used several markers to distinguish fibroblasts and MICs as described previously.
Data Analysis and Statistical Methods Differences in percentages were calculated with the w2 test. Immunostaining score values for each protein were expressed as median (range). Comparison of immunostaining values between groups was made with the MannWhitney or Kruskal-Wallis tests. The Cox regression model was used to examine interactions of different prognostic factors in a multivariate analysis. For metastasis-free r
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survival analysis we used the Cox univariate method. The SPSS 18.0 program was used for all calculations. All these methods have been used previously in similar studies from our group.6,21,29
RESULTS In the present study, we investigated the expression of TLR3, TLR4, and TLR9 in 106 patients with gastric cancer. Figure 1 shows examples of immunostaining for these proteins, including negative controls in gastric mucosa (Figs. 1A–C) and positive controls in breast carcinoma samples known to express these TLRs (Figs. 1D–F)6; TLR3, TLR4, and TLR9 have cytoplasmic (the 3 TLRs, Figs. 1G–I) and also membrane location for TLR3 and TLR9 (arrows in Figs. 1G, I) in positive gastric carcinoma cells. In most cases the positive staining was generally found in tumor cells, and less frequently in stromal cells (in fibroblast-like cells and in MICs), even though it is well known that immune cells express TLRs at high level; as shown in Figure 1, gastric carcinoma cells expressed TLR3 and TLR9, but macrophages expressing CD68 (Fig. 1J) showed no expression for those TLRs (Figs. 1K, L). Table 2 shows the number and percentages of tumors positive for each TLR by each cellular type. Tumors showed high expression of TLRs by cancer cells. Nevertheless, a significant percentage of tumors also showed expression of TLR3 and TLR9 by MICs (14.2% and 13.2%, respectively) and by fibroblast-like cells (4.7% and 6.6%, respectively). We also evaluated the possible relationship between TLRs expression and the clinicopathologic factors of gastric carcinomas, including tumor location, histologic type and grade, stage, lymph node involvement, lymphatic invasion, and resectability (Table 1). We found a significant association only between TLR3 score values and tumor location, with tumors located in the lower third showing lower TLR3 values (P = 0.008). The potential association between TLRs score and overall survival was evaluated in the 63 patients with resectable (R0) tumors included in the present study. Patients with R1 and R2 resection were not evaluated, as they are more prone to develop recurrence. First, an optimal cutoff value was defined by statistical analysis of the TLRs score values to predict the overall survival of the study population. This statistical analysis showed a continuous association only between TLR3 score values and overall survival in patients with R0 surgical resection. Figure 2A shows the determination of the optimal cutoff value of the TLR3 scores in R0 gastric tumors for predicting overall survival. P-values obtained for each cutoff value are plotted against the value itself. This analysis led us to define a value of TLR3 of 20 as the optimal cutoff point (w2 = 7.92, P = 0.05). Figure 2B shows overall survival curves in patients with R0 tumors according to the optimal cutoff point for TLR3 score values, indicating that patients with R0 tumors and high TLR3 expression (score value >20) have poor prognosis (P = 0.005). Moreover, in patients with R0 tumors and lymph node invasion, the occurrence of a high TLR3 expression defines a population with even worse overall survival (P = 0.003) (Fig. 2C). However, multivariate analysis according to the Cox model indicated that TLR3 levels showed no significance as independent prognostic factor (data not shown). www.immunotherapy-journal.com |
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FIGURE 1. Examples of TLR immunostaining. Negative controls ( 400) in gastric carcinoma for TLR3 (A), TLR4 (B), and TLR9 (C); positive controls ( 400) in breast carcinoma samples for TLR3 (D), TLR4 (E), and TLR9 (F); positive immunostaining in gastric carcinoma ( 400) for TLR3 (G), TLR4 (H), and TLR9 (I), indicating the membrane-specific staining for TLR3 and TLR9 (arrows). Pictures showing positive immunostaining for TLR3 (K) and TLR9 (L) in tumor cells, but negative for immune cells (macrophages) identified by CD68 immunostaining (J).
DISCUSSION This study analyzes tumor expression of TLR3, TLR4, and TLR9, and for the first time the prognostic significance of this expression, in patients with preestablished gastric cancer. The results showed high expression of these TLRs by cancer cells compared with stromal cells (fibroblast or MICs). In addition, the expression of TLR3 was significantly associated with a poor overall survival in patients with resectable tumors. It is known that normal intestinal epithelial cells and lamina propia mononuclear cells must respond to breaches in the mucosal barrier by activating TLR-
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dependent pathways that result in increased epithelial proliferation, wound healing, and recruitment of acute inflammatory cells.12 However, it has been shown that cells from several malignant tumors display increased TLR expression,6,21–23 and also mice deficient in such receptors may be protected from, or develop fewer, inducible tumors in experimental models.14,15 Therefore, the expression of these receptors by tumoral cells may display several actions promoting cancer progression. Cancer cells activated by TLRs signals can release cytokines and chemokines which in turn recruit immune cells and stimulate them to release further cytokines and chemokines. This process results in r
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TABLE 2. TLR Expression by Each Cell Type in 106 Cases of Gastric Cancer
Positive Cases [n (%)] Factor
Tumor Cells
Fibroblasts
MICs
TLR3 TLR4 TLR9
64 (60.4) 51 (48.1) 93 (87.7)
5 (4.7) 0 7 (6.6)
15 (14.2) 0 14 (13.2)
Samples on tissue sections were either insufficient or lost for analysis in 24 cases for TLR3, 29 cases for TLR4, and 11 cases for TLR9. MICs indicates mononuclear inflammatory cells; TLR, Toll-like receptor.
an aberrant cytokine profile that is associated with the promotion of angiogenesis and subversion of adaptive immunity with immune tolerance.30,31 TLR-mediated signals transduced through the adapter protein myeloid differentiation factor 88 (MyD88) and through the TIR-domain-
Clinical Significance of TLRs in Gastric Cancer
containing adapter-inducing interferon-b (TRIF) protein. This is relevant because these both MyD88-dependent and the MyD88-independent pathways mediate nuclear factor-k B (NF-kB) activation and subsequent inflammatory cytokine production though different mechanisms and kinetics. It is known that NF-kB activation participate in carcinogenic promotion and progression by different mechanisms, such as cell proliferation, antiapoptosis, angiogenesis, invasion, and metastasis.32 In addition, TLRs also enhances tumor cell invasion and metastasis by regulating metalloproteases and integrins.33–36 In fact, we have described recently that some metalloproteases (MMP-1, MMP-13, and MMP-14) and their inhibitors (TIMP-3) are overexpressed in gastric carcinoma samples, when compared with normal gastric tissue.37 Our data also show a variability of TLR expressions among gastric carcinomas, which may be consequence of the biological heterogeneity of these tumors. Consequently, we also investigate whether these variations in TLR amount by tumors might have a prognostic value. TLR4 and TLR9
FIGURE 2. Analysis of cutoff points and overall survival for TLR3 score in resectable (R0) patients. A, Maximum likelihood determination of the cutoff value of the TLR3 score in R0 gastric tumor for predicting overall survival in patients with gastric cancer. P-values obtained for each cutoff value are plotted against the value itself. Statistical significance is indicated by the horizontal line at the 0.05 level. Analysis led to the definition of a TLR3 score value (marked with an arrow) as the optimal cutoff point (r2 = 7.92, P = 0.05). B, Overall survival curve in R0 patients as a function of the optimal cutoff point for TLR3 score values (P = 0.005). C, Overall survival curve in R0 patients with lymph node invasion, as a function of the optimal cutoff point for TLR3 score values (P = 0.003). r
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are involved in the interaction with H. pylori, resulting in chronic gastritis38 and inducing invasion and angiogenesis at gastric mucosa.19,39 Our results did not show association of these TLRs expression by tumors with clinicopathologic factors in patients with gastric carcinomas. However, our data suggest that the expression of TLR3 in cancer cells is associated with tumor location in patients, and also related with poor survival in patients with resectable tumors. Thus, our results are in agreement with previous observations reporting that regulation of TLR3 is associated with pathogenesis and/or increased tumoral aggressiveness in different tumor types, such as breast, endometrial, prostate, colorectal renal carcinomas, and cutaneous malignant melanomas.6,21–23,40–44 In addition, it was recently shown a positive correlation between mRNA relative expression of TLR3 and chemokine (C-X-C motif) receptor 4 (CXCR4), and also mRNA relative expression of TLR3 was found significantly increased in breast cancer tumor tissue from patients expressing high IFN-g. Thus, it has been proposed that an overexpression of IFN-g mRNA due to the proinflammatory microenvironment can lead to an upregulation of CXCR4 mRNA and consequently to an increased TLR3 mRNA expression.45 Further studies are necessary to explore the possible role and clinical significance of TLR3 expression in a possible molecular inflammatory axis in the microenvironment of gastric carcinomas. Our data suggest that TLR3 expression in combination with other prognostic factors may contribute to a better prognostic evaluation of patients with resectable gastric carcinomas. In addition, our data could open a new line of research to explore the possible contribution of viral infections to the origin and progression of gastric cancer. This is because double-stranded RNA produced by most viruses during replication is capable of activating signaling pathways depending on TLR3 stimulation.46–50 In contrast, there are studies showing a variable antineoplastic effect caused by a blockage of TLR351,52 and therefore TLR3 might represent a good therapeutic target in gastric cancer. CONFLICTS OF INTEREST/ FINANCIAL DISCLOSURES Supported by grants from Fondo de Investigacio´n Sanitaria from Instituto Carlos III (FIS-PI070306) and FICEMU. All authors have declared there are no financial conflicts of interest with regard to this work. REFERENCES 1. Akira S, Takeda K. Toll-like receptor signalling. Nat Rev Immunol. 2004;4:499–511. 2. Moynagh PN. TLR signalling and activation of IRFs: revisiting old friends from the NF-kappa B pathway. Trends Immunol. 2005;26:469–476. 3. Kawai T, Akira S. TLR signaling. Cell Death Differ. 2006;13: 816–825. 4. Pasare C, Medzhitov R. Toll-like receptors: linking innate and adaptive immunity. Microbes Infect. 2004;6:1382–1387. 5. Matzinger P. An innate sense of danger. Ann N Y Acad Sci. 2002;961:341–342. 6. Gonzalez-Reyes S, Marin L, Gonzalez L, et al. Study of TLR3, TLR4 and TLR9 in breast carcinomas and their association with metastasis. BMC Cancer. 2010;10:665–673. 7. Alexopoulou L, Holt AC, Medzhitov R, et al. Recognition of double-stranded RNA and activation of NF-kappa B by Tolllike receptor 3. Nature. 2001;413:732–738. 8. Coussens LM, Werb Z. Inflammation and cancer. Nature. 2002;420:860–867.
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9. Hayashi F, Smith KD, Ozinsky A, et al. The innate immune response to bacterial flagellin is mediated by Toll-like receptor 5. Nature. 2001;410:1099–1103. 10. Zhang YB, He FL, Fang M, et al. Increased expression of Tolllike receptors 4 and 9 in human lung cancer. Mol Biol Rep. 2009;36:1475–1481. 11. Jemal A, Bray F, Center MM, et al. Global cancer statistics. CA Cancer J Clin. 2011;61:69–90. 12. Fukata M, Abreu MT. Role of Toll-like receptors in gastrointestinal malignancies. Oncogene. 2008;27:234–243. 13. Hold GL, Rabkin CS, Chow WH, et al. A functional polymorphism of toll-like receptor 4 gene increases risk of gastric carcinoma and its precursors. Gastroenterology. 2007;132:905–912. 14. Fukata M, Chen A, Vamadevan AS, et al. Toll-like receptor-4 promotes the development of colitis-associated colorectal tumors. Gastroenterology. 2007;133:1869–1881. 15. Swann JB, Vesely MD, Silva A, et al. Demonstration of inflammation-induced cancer and cancer immunoediting during primary tumorigenesis. Proc Natl Acad Sci U S A. 2008; 105:652–656. 16. Ohara T, Morishita T, Suzuki H, et al. Heterozygous Thr 135 Ala polymorphism at leucine-rich repeat (LRR) in genomic DNA of toll-like receptor 4 in patients with poorly-differentiated gastric adenocarcinomas. Int J Mol Med. 2006;18:59–63. 17. Zeng HM, Pan KF, Zhang Y, et al. Genetic variants of toll-like receptor 2 and 5, Helicobacter pylori infection, and risk of gastric cancer and its precursors in a Chinese population. Cancer Epidemiol Biomarkers Prev. 2011;20:2594–2602. 18. Pimentel-Nunes P, Afonso L, Lopes P, et al. Increased expression of toll-like receptors (TLR) 2, 4 and 5 in gastric dysplasia. Pathol Oncol Res. 2011;17:677–683. 19. Pimentel-Nunes P, Goncalves N, Boal-Carvalho I, et al. Helicobacter pylori induces increased expression of Toll-like receptors and decreased Toll-interacting protein in gastric mucosa that persists throughout gastric carcinogenesis. Helicobacter. 2013;18:22–32. 20. Tye H, Kennedy CL, Najdovska M, et al. STAT3-driven upregulation of TLR2 promotes gastric tumorigenesis independent of tumor inflammation. Cancer Cell. 2012;22: 466–478. 21. Gonzalez-Reyes S, Fernandez JM, Gonzalez LO, et al. Study of TLR3, TLR4, and TLR9 in prostate carcinomas and their association with biochemical recurrence. Cancer Immunol Immunother. 2011;60:217–226. 22. Eiro N, Ovies C, Fernandez-Garcia B, et al. Expression of TLR3, 4, 7 and 9 in cutaneous malignant melanoma: relationship with clinicopathological characteristics and prognosis. Arch Dermatol Res. 2013;305:59–67. 23. Eiro N, Gonzalez L, Gonzalez LO, et al. Study of the expression of toll-like receptors in different histological types of colorectal polyps and their relationship with colorectal cancer. J Clin Immunol. 2012;32:848–854. 24. UICC. TNM Classification of Malignant Tumors. 7th ed. Hoboken, NJ: Wiley-Blackwell; 2010. 25. Lauren P. The two histological main types of gastric carcinoma: diffuse and so-called intestinal-type carcinoma. An attempt at a histo-clinical classification. Acta Pathol Microbiol Scand. 1965;64:31–49. 26. Vizoso FJ, del Casar JM, Corte MD, et al. Significance of cytosolic hyaluronan levels in gastric cancer. Eur J Surg Oncol. 2004;30:318–324. 27. Parker RL, Huntsman DG, Lesack DW, et al. Assessment of interlaboratory variation in the immunohistochemical determination of estrogen receptor status using a breast cancer tissue microarray. Am J Clin Pathol. 2002;117:723–728. 28. Gonzalez-Reyes S, Fernandez JM, Gonzalez LO, et al. Study of TLR3, TLR4, and TLR9 in prostate carcinomas and their association with biochemical recurrence. Cancer Immunol Immunother. 2011;60:217–226. 29. Gonzalez LO, Corte MD, Vazquez J, et al. Androgen receptor expression in breast cancer: relationship with clinicopathological characteristics of the tumors, prognosis, and expression of r
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metalloproteases and their inhibitors. BMC Cancer. 2008;8: 149–158. Costantini S, Capone F, Guerriero E, et al. An approach for understanding the inflammation and cancer relationship. Immunol Lett. 2009;126:91–92. Sato Y, Goto Y, Narita N, et al. Cancer cells expressing tolllike receptors and the tumor microenvironment. Cancer Microenviron. 2009;2(suppl 1):205–214. Hanahan D, Weinberg. RA. The hallmarks of cancer. Cell. 2000;100:57–70. Huang B, Zhao J, Unkeless JC, et al. TLR signaling by tumor and immune cells: a double-edged sword. Oncogene. 2008;27:218–224. Rakoff-Nahoum S, Medzhitov R. Role of toll-like receptors in tissue repair and tumorigenesis. Biochemistry (Mosc). 2008;73: 555–561. Voelcker V, Gebhardt C, Averbeck M, et al. Hyaluronan fragments induce cytokine and metalloprotease upregulation in human melanoma cells in part by signalling via TLR4. Exp Dermatol. 2008;17:100–107. Inoue J, Aramaki Y. Toll-like receptor-9 expression induced by tape-stripping triggers on effective immune response with CpG-oligodeoxynucleotides. Vaccine. 2007;25:1007–1013. Gonza´lez L, Aguirre A, Eiro´ N, et al. Expression and clinical significance of metalloproteases and their inhibitors in gastric cancer. Hepatogastroenterology. 2013. [In press]. Schmausser B, Andrulis M, Endrich S, et al. Toll-like receptors TLR4, TLR5 and TLR9 on gastric carcinoma cells: an implication for interaction with Helicobacter pylori. Int J Med Microbiol. 2005;295:179–185. Chang YJ, Wu MS, Lin JT, et al. Helicobacter pylori-Induced invasion and angiogenesis of gastric cells is mediated by cyclooxygenase-2 induction through TLR2/TLR9 and promoter regulation. J Immunol. 2005;175:8242–8252. Salaun B, Coste I, Rissoan MC, et al. TLR3 can directly trigger apoptosis in human cancer cells. J Immunol. 2006;176: 4894–4901. Shojaei H, Oberg HH, Juricke M, et al. Toll-like receptors 3 and 7 agonists enhance tumor cell lysis by human gammadelta T cells. Cancer Res. 2009;69:8710–8717.
2014 Lippincott Williams & Wilkins
Clinical Significance of TLRs in Gastric Cancer
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