Originally published as JCO Early Release 10.1200/JCO.2005.12.172 on December 14 2004

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Tumor-Associated Macrophages: The Double-Edged Sword in Cancer Progression

Jeremy J.W. Chen, Yi-Chen Lin, Pei-Li Yao, Ang Yuan, Hsang-Yu Chen, Chia-Tung Shun, Meng-Feng Tsai, Chun-Houh Chen, Pan-Chyr Yang

From the Institutes of Biomedical Sciences and Molecular Biology, National Chung Hsing University, Taichung; Center for Genomic Medicine, National Taiwan University College of Medicine; Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine; Graduate Institute of Epidemiology, National Taiwan University, Taipei; Department of Forensic Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine; Institute of Statistical Science and Institute of Biomedical Sciences, Academia Sinica; and National Health Research Institute, Taipei, Taiwan, Republic of China

Address reprint requests to Pan-Chyr Yang, MD, PhD, Department of Internal Medicine, National Taiwan University Hospital, No. 7, Chung-Shan S Rd, Taipei, Taiwan 100, R.O.C.; e-mail: pcyang{at}ha.mc.ntu.edu.tw.

	ABSTRACT

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PURPOSE: Inflammation plays a critical role in cancer progression. In this study we investigate the pro-tumorigenic activities and gene expression profiles of lung cancer cells after interaction with macrophages.

MATERIALS AND METHODS: We measured intratumoral microvessel counts and macrophage density in 41 lung cancer tumor specimens and correlated these with the patients' clinical outcome. The interaction between macrophages and cancer cell lines was assessed using a transwell coculture system. The invasive potential was evaluated by in vitro invasion assay. The matrix-degrading activity was assayed by gelatin zymography. The microarray was applied to a large-scale analysis of the genes involved in the interaction, as well as to monitor the gene expression profiles of lung cancer cells responding to anti-inflammatory drugs in cocultures.

RESULTS: The macrophage density positively correlated with microvessel counts and negatively correlated with patient relapse-free survival (P < .05). After coculture with macrophages, lung cancer cell lines exhibited higher invasive potentials and matrix-degrading activities. We identified 50 genes by microarray that were upregulated more than two-fold in cancer cells after coculture. Northern blot analyses confirmed some gene expression such as interleukin-6, interleukin-8, and matrix metalloproteinase 9. The two-dimensional hierarchical clustering also demonstrated that the gene expression profiles of lung cancer cells responding to various anti-inflammatory drugs in cocultures are distinct.

CONCLUSION: The interaction of lung cancer cells and macrophages can promote the invasiveness and matrix-degrading activity of cancer cells. Our results also suggest that a great diversity of gene expression occurs in this interaction, which may assist us in understanding the process of cancer metastasis.

	INTRODUCTION

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It is now becoming clear that the inflammatory cells that exist in the tumor microenvironment play an indispensable role in cancer progression. This may explain why many cancers arise from sites of chronic irritation and inflammation.¹ Angiogenesis plays an important role in tumor growth, invasion, and metastasis.^2,3 This process is meticulously regulated by the local increase of the activity of a variety of angiogenic factors, such as interleukin (IL) -8, vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF), and transforming growth factor alpha (TGF-).^3-5

Substantial evidence suggests that stroma cells adjacent to the cancer cells, including fibroblasts, inflammatory cells such as macrophages, neutrophils, and lymphocytes, can interact with cancer cells and express angiogenic factors.^6-8 The interaction of lung cancer cells and stroma fibroblasts can promote the expression of angiogenic factor IL-8 both in cancer cells as well as in stroma fibroblasts.⁹ The macrophage is the pivotal member of inflammatory cells within the tumor stroma. Upon activation, the tumor-associated macrophages can release a vast diversity of growth factors, proteolytic enzymes, cytokines, and inflammatory mediators. Many of these factors are key agents in angiogenesis.

We demonstrated that following cancer cell/macrophage coculture, marked IL-8 mRNA expression could be induced in macrophages as well as in lung cancer cells that were controlled via the nuclear factor kappa B (NF-B) pathway.¹⁰ The increased IL-8 expression seen in macrophages after coculture with cancer cells strongly suggests that cancer cells can stimulate inflammatory cells to express angiogenic factors and promote tumor growth.¹¹

Tumor-infiltrating macrophages (TIMs) have recently been shown to correlate with vessel density in ovarian,¹² breast,¹³ and other malignancies,¹⁴ and have been associated with the expression of VEGF and epidermal growth factor receptor (EGFR) in cancer cells.¹⁵ Our previous report also indicated that TIM density was positively correlated with tumoral IL-8 mRNA expression and intratumoral microvessel counts, and negatively correlated with patient survival.¹⁰ However, little is known about the global pro-tumorigenic gene expression profile in the cancer cells interacting with TIMs.

In this study, by using the cDNA microarray,¹⁶ we were able to perform a large-scale analysis of the genes involved in the interaction between cancer cells and the infiltrating macrophages. This information may assist us in exploring complex interactions between cancer cells and stroma that orchestrate the process of tumor progression and metastasis. Furthermore, in our previous study,¹⁰ we found that several anti-inflammatory drugs can effectively inhibit the expression of angiogenic factor IL-8 in a similar fashion. Therefore, to understand whether the suppression of gene expression profiles of cancer cells responding to anti-inflammatory drugs are similar or not, we also applied microarray analysis to monitor the gene expression profiles of lung cancer cells responding to anti-inflammatory drugs in cancer cell/macrophage cocultures, which can help us to interpret the diversity of different functional mechanisms of the various anti-inflammatory drugs.

	MATERIALS AND METHODS

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Cell Lines
Human monocyte cell line THP-1 (ATCC TIB 202; ATCC, Manassas, VA), human non–small-cell lung cancer (NSCLC) cell line A549 (ATCC CCL-185), lung adenocarcinoma cell lines CL1-5, CL1-0,^17,18 and PC14 were grown with RPMI 1640 media (GIBCO BRL, Gaithersburg, MD) supplemented with 1.5g/L Na₂HCO₃, 4.5g/L glucose, and 10% fetal bovine serum (FBS; GIBCO-BRL). All cell lines were incubated at 37°C with 20% O₂ and 5% CO₂. PMA (Sigma Chemical Co, St Louis, MO) 3.2 x 10^–7 M was applied to monocyte cultures. After incubating with PMA for 24 hours, monocytes were differentiated to macrophages. Macrophages were washed three times with RPMI medium containing 10% FBS and incubated for another 24 hours to eliminate the effect of PMA, then were incubated in serum-free media for 24 hours. The culture supernatants were collected as conditioned medium.

Immunohistochemical Staining for Microvessels and Macrophages
To explore the relationships between macrophage density, microvessel counts, and patients' prognosis, tumor specimens from 41 patients who underwent surgical resection of their primary NSCLC at our institute between September 1994 and September 1996 were examined by immunohistochemical staining for TIMs and intratumoral microvessels. This investigation was performed after approval by the institutional review board of National Taiwan University Hospital. Written informed consent was obtained from all patients. The clinicopathologic features of the patients and tissues are shown in Table 1.

In Vitro Invasion Assay
Appropriate Matrigel (Becton Dickinson, Franklin Lakes, NJ) was added into the upper chamber of the transwell apparatus with 8-µm pore size membrane (Costar, Cambridge, MA). After the Matrigel solidified at 37°C, 1 x 10⁵ cancer cells that had been previously cocultured with macrophages were seeded onto the Matrigel and incubated at 37°C overnight. Membranes coated with Matrigel were swabbed with a cotton swab and fixed with 100% methanol for 10 minutes. The membrane with cells were soaked in Giemza stain (Sigma Chemical Co) for 3 hours and then washed with distilled water. The number of cells attached to the lower surface of the polycarbonate filter was counted at 400x magnification under a light microscope. Each type of cell was assayed in triplicate.

Lung Cancer CL1-5 Cells/Macrophages Coculture
For microarray experiments, CL1-5 cells were cultured for 24 hours in a medium conditioned with and without macrophages, respectively. Total RNA was extracted with RNAzolB (Tel-Test, Friendswood, TX), and mRNA was purified with Oligotex mRNA Midi Kit (QIAGEN, Valencia, CA). For zymographic experiments, the transwell apparatus with a 0.4-µm pore membrane (six-well plate; Costar) was applied to cancer cell/macrophage cocultures. After incubating overnight, the cocultured mediums were collected and centrifuged to remove cellular debris, and the supernatants were frozen at –80°C until assayed for gelatinolytic activity. The details of conditioned medium preparation and cocultures with the transwell apparatus have been described previously.¹⁰

Human cDNA Microarray Analysis
For the first microarray experiment, 9,600 human expressed sequence tag (EST) clones with putative gene names were obtained from the IMAGE consortium libraries through its distributor (Research Genetics, Huntsville, AL). These gene clones were derived from various tissues and in different library constructs. Of the mRNAs isolated from non-cocultured and cocultured CL1-5 cells, 0.5 µg were labeled with biotin during reverse transcription as described in our previous report.¹⁶ All experiments were performed in triplicate individually. The replicates were used to calculate the mean of gene expression for regression analysis and the coefficient of variation (CV) as the measurement of reproducibility.

For the second microarray experiment, four copies of each differentially expressed gene identified from the procedures above were re-arrayed per microarray membrane. The copies were used to calculate the CV as the measurement of reproducibility. The details of target preparation, hybridization, color development, image analysis, and spot quantification have been described previously.^16,18,21

Northern Blot Analysis
To confirm the results derived from microarray, 12 differentially expressed clones were selected from the microarray analysis for Northern blot analysis. One µg mRNA of non-cocultured and cocultured CL1-5 cells were subjected to 1.2% agarose gel electrophoresis and then transferred to nylon membrane with a positive charge. The amplified cDNA fragments were labeled with digoxigenin-11-dUTP by random primed labeling as in our previous reports.¹⁶ Glyceraldehye-3-phosphate dehydrogenase (GAPDH) was used as a loading control.

Gelatin Zymography
Gelatinolytic activity was assayed by gelatin zymography by the method described previously, but with some modification.¹⁷ Briefly, aliquots of non-cocultured and cocultured medium were mixed with sample buffer and applied directly, without prior heating or reduction, to 10.5% acrylamide gels containing 1 mg/mL gelatin (Sigma Chemical Co). After electrophoresis, the sodium dodecyl sulfate was removed from the gel by incubating in 2.5% (v/v) Triton X-100 (Sigma Chemical Co) for 30 minutes. The gels were then incubated at 37°C overnight in development buffer (50 mmol/L Tris-HCl, pH 7.6, containing 0.2 M NaCl, 5 mmol/L CaCl₂), and stained with 40% methanol/10% glacial EDTA containing 0.5% (w/v) Coomassie Brilliant Blue G-250 (Sigma Chemical Co) for 20 minutes.

Gene Expression Profiles of Cancer Cells Responding to Anti-Inflammatory Drugs
The differentially expressed genes identified from the above microarray carrying 9,600 EST clones were pooled to fabricate quick screening arrays for drug-responding gene expression profiles. Three anti-inflammatory drugs, pyrrolidine dithiocarbamate (PDTC), aspirin, and dexamethasone, were purchased from the Sigma Chemical Company. Another anti-inflammatory drug, celecoxib, was provided by Searle (Caguas, Puerto Rico). Thalidomide was provided by Taiwan Tung Yang (TTY Biopharm Co Ltd, Taiwan). Four designated concentrations of each anti-inflammatory drug were used for this experiment: 0, 0.1, 1, and 10 µmol/L of PDTC; 0, 0.1, 1, and 10 µmol/L of aspirin; 0, 0.01, 0.1, and 10 µmol/L of dexamethasone; 0, 0.01, 0.1, and 10 µmol/L of celecoxib; and 0, 5, 25, and 50 µmol/L of thalidomide.¹⁰ The designated concentrations of anti-inflammatory drugs were added to the macrophage/cancer cell cocultures. After incubation for 24 hours, cells were harvested with RNAzol B and followed by microarray experiments.

Statistical Analysis
Relationships between microvessel counts and macrophage density were analyzed by linear regression. Relapse-free survival curves were obtained by the Kaplan-Meier method, and the difference in survival in subgroups was analyzed using a log-rank test (SPSS software; SPSS Inc, Chicago, IL). The effect of predictors (TIM, histology, grade, stage, tumor status, and node status) was evaluated by Cox regression mode. All statistical tests were two sided. The P value < .05 was considered statistically significant. In an attempt to reduce the variation arising from the experimental results derived from different microarrays, the intensity values of spots from each microarray were rescaled using a global-scale method²² for the first microarray experiment, and a housekeeping gene, GAPDH, for the second microarray experiment. Only the signal value of spots exceeding a figure of 3,000 was considered meaningful in the membrane format microarray system (ie, the intensity of a spot less than 3,000 was hardly distinguishable from background "noise," such that any occasion where the spot intensity value was below 3,000, the value was replaced by a figure of 3,000). Therefore, if the intensity of a gene is below 3,000 in all three replicates, the CV will be set to zero (standard deviation ÷ mean x 100% = 0 ÷ 3,000 x100% = 0). To analyze the first microarray experiment, we regressed the means of the three replicates of each of the 9,600 genes in the non-cocultured group against those in the cocultured group. Genes were selected if (1) they fell outside the 95% CI for the fitted regression line, and (2) there was at least a two-fold change in the means of the two groups. For the directed microarray analysis, the rescaled and replaced signals of each chip were transformed by a logarithm with base 2 and then normalized by the standard normal distribution. The gene expression profiles were shown by a simple two-dimensional hierarchical clustering analysis using an average linkage method with a Pearson correlation coefficient proximity matrix.²³ To give the readers a better feeling for the significance of the differences among the treatments, the multiple scatter plot of correlation was created. For each treatment of drug dosage, a point for the correlation with the untreated cocultured group, and a second point for the untreated non-cocultured group, was plotted. The correlation was evaluated by Pearson correlation coefficient and 95% CI was included as error bar on each point. Where appropriate, the data are presented as the mean ± standard deviation.

	RESULTS

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TIMs Are Significantly Correlated With Microvessel Counts and Patients' Relapse-Free Survival
The immunohistochemical staining showed that the cytoplasm of TIMs was stained brown by anti-CD68 antibodies (Fig 1A), while the microvessels appeared as brown linear fragments, with or without an internal lumen (Fig 1B). Significant correlations were found between the macrophage density and intratumoral microvessel count (linear regression, r = 0.743; P = 2.68 x 10^–8; Fig 1C).

View larger version (87K): [in this window] [in a new window]   Fig 1. Tumor-infiltrating macrophages and microvessel counts in non–small-cell lung cancer (NSCLC) samples and their inter-relationships and correlation with relapse-free survival. Immunohistochemical staining of (A) macrophages and (B) microvessels. (C) Correlation of macrophage density with microvessel counts. (D) Kaplan-Meier survival plots for NSCLC patients grouped according to tumor-infiltrating macrophage density.

Macrophage/Cancer Cell Coculture Increases Cancer Cell Invasive Ability
Four lung cancer cell lines, CL1-0, CL1-5, A549, and PC14 (in the lower chamber of the transwell), were cocultured with macrophages (in the upper chamber) for 24 hours. After discarding the macrophages, the harvested cancer cells were analyzed for invasive activity in a 24-well transwell. Cells transmigrating through the coated membrane were stained by Geimza staining dye (Sigma Chemical Co) and counted under a microscope. All cell lines, except for CL1-0 cocultured with macrophages, revealed significant enhancement in cell invasiveness (Fig 2). CL1-0 cells cocultured with macrophages showed a 1.87-fold increase in comparison to those non-cocultured (cell number 276 ± 79 v 516 ± 128; P = .169, analysis of variance). CL1-5 cells treated in the same way also had a 2.43-fold increase (cell number 1,237 ± 272 v 3,006 ± 147; P = .000586). Similar results were observed in A549 and PC14 cell/macrophage cocultures (cell number 818 ± 40 v 1,711 ± 175; 507 ± 26 v 2,950 ± 845; P = .000993 and P = .007456, respectively).

View larger version (17K): [in this window] [in a new window]   Fig 2. The invasion activity of non–small-cell lung cancer cell lines (CL1-0, CL1-5, A549, and PC14) cocultured with macrophages. The yellow bars represent invasive cell number of non-cocultured cancer cells, and the blue bars represent those for cocultured cancer cells. = .05; (*), P < .01; (**), P < .001.

View larger version (69K): [in this window] [in a new window]   Fig 3. Profiling of differentially expressed gene pattern in CL1-5 cells before and after coculturing with macrophages. (A) The digital images of non-cocultured and cocultured CL1-5 cells are illustrated. (B) Close-up views of the microarray images showing different gene expression patterns of non-cocultured and cocultured CL1-5 cells. (C) Distribution of gene expression intensities between non-coculture and coculture. The solid curves were the 95% predicted regression lines.

NF-B

View larger version (44K): [in this window] [in a new window]   Fig 4. Northern blot analyses of genes identified by microarray study. Twelve genes selected from Table 2 were used to demonstrate the validity of the microarray results. Those mRNAs were collected from lung cancer cell line CL1-5 cocultured without (N) and with (C) macrophages.

View larger version (28K): [in this window] [in a new window]   Fig 5. Gelatinase activity in non–small-cell lung cancer cell/macrophage cocultured media. The media were collected from lung cancer cell lines (CL1-0, CL1-5, A549, and PC14) cocultured without (N) and with (C) macrophages. The white bands were decomposed gelatin by gelatinase.

View larger version (47K): [in this window] [in a new window]   Fig 6. The two-dimensional hierarchical clustering analysis of gene expression profiles of CL1-5 cells responding to anti-inflammatory drugs. The five drugs were as follows: celecoxib (cele); dexamethasone (dexa); pyrrolidine dithiocarbamate (PDTC); aspirin; and thalidomide (thali). The three different concentrations are designated on the top of the figures. The scale value of normalization, from –3.0 to 3.0 (arbitrary unit), represented the levels of gene expression from green (low) to red (high).

View larger version (22K): [in this window] [in a new window]   Fig 7. The multiple scatter plots of correlation among drug treatments. There were two points for each treatment of drug dosage that was described below the figure, a point for the correlation with the untreated cocultured group (solid rectangle) and a second point for the untreated non-cocultured group (solid circle). The correlation was evaluated by Pearson correlation coefficient and 95% CI was included as error bar on each point. PDTC, pyrrolidine dithiocarbamate; Dexa, dexamethasone; Cele, celecoxib; Thali, thalidomide.

	DISCUSSION

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Previous reports indicate that angiogenic factors, such as IL-8 and VEGF, correlate with tumor angiogenesis and metastasis,^20,25,26 and cancer cell-macrophage coculture can promote the expressions of these factors in NSCLC.^10,11 The IL-8 expressed by human melanoma cells can also upregulate MMP-2 activity and enhance tumor growth and metastasis.²⁷ In this study, the gelatinolytic activity of MMP-9 is significantly increased in the media of lung cancer cells after coculture with macrophages. It is worth noting that the lung cancer cell lines CL1-0 and CL1-5, derived from the same parental cells, possessed different invasive/metastatic potential in vitro and in vivo, CL1-5 having a greater potential than CL1-0.¹⁸ Our results therefore showed that invasive capabilities and matrix-degrading activities increased to a lesser degree in cancer cells with low invasive capacity (CL1-0) than in cancer cells with a higher invasive capacity (CL1-5; Fig 5).

We previously demonstrated that TIMs can upregulate tumor-associated IL-8 mRNA expression through NF-B pathway.¹⁰ However, how many other genes involved in these regulatory processes are still unknown. By using cDNA microarray, 50 genes with a more than two-fold change, as well as beyond a 95% CI of predicted regression line, were identified and grouped into seven categories. Six categories were based on reported cellular functions, and one was based on anonymous genes that correlated positively (Table 2). Most of the genes identified by microarray were previously unknown or unpublished in cancer cell/macrophage cocultures.

However, many genes have been previously reported to be associated with angiogenesis and metastasis, including the association of IL-6 with a poor prognosis in patients with metastatic breast cancer. Also, many genes have been correlated with the extent of disease²⁸: IL-8 expression was highly associated with distant lymph node metastasis of NSCLC¹⁷; urokinase-type plasminogen activator receptor expressed more in tumor tissues of NSCLC patients, as compared with adjacent normal tissues²⁹; STC-1 mRNA level significantly correlated with primary tumor size, number of lymph nodes, and TNM stages in early-stage breast cancer patients³⁰; plasma ICAM-1 was higher in metastatic patients with renal cell carcinoma compared with nonmetastatic patients³¹; and MMP-1 immunoreactivity of colorectal adenocarcinomas significantly correlated with the presence of lymph node and hepatic metastasis.³² Many genes identified in this study have been confirmed to play a role in metastasis throughout the literature. Further characterization of genes identified in this study is currently in progress.

We previously demonstrated that the interaction between macrophages and cancer cells can upregulate IL-8 expression. This process is mediated, in part, through the NF-B pathway.¹⁰ In this study, the results of microarray analysis further augmented the idea that, for example, IL-6, IL-8, macrophage colony-stimulating factor, MMPs, and ICAM-1 are also involved in NF-B pathway,^33,34 The finding that TIM density is correlated with tumoral IL-8 mRNA expression and intratumoral microvessel counts initiated the idea that inflammatory cells may be involved in regulating the production of angiogenic factors by cancer cells. The anti-inflammatory agents should have the potential to impede the pathway of IL-8 induction, as well as the possible suppression of angiogenesis initiated by inflammatory cells. Previous reports in the literature have also revealed that some nonsteroidal anti-inflammatory drugs, such as aspirin, can reduce the risk of developing colorectal and breast cancers.^35,36 On the other hand, the inflammation in the tumorigenic site plays an important role in cancer progression.¹ Therefore, three drugs, celecoxib, dexamethasone, and aspirin, that are commonly used clinically to suppress inflammation were selected. We also included PDTC, an NF-B specific inhibitor, to assess the role of NF-B pathway involved in cancer cell/macrophage interaction. Thalidomide is an effective anticancer drug and also has a potent antiangiogenic property.³⁷ These drugs cover nonsteroidal anti-inflammatory drugs (celecoxib, PDTC, aspirin, and thalidomide), steroidal anti-inflammatory drugs (dexamethasone) and inflammatory pathway NF-B. Thus, these five drugs were used to evaluate the suppression of gene expression profiles of cancer cells that were activated by macrophage coculture.

Previous studies have also shown that the tested anti-inflammatory agents significantly inhibit IL-8 mRNA expression in CL1-5 cells cocultured with macrophages in a dose-dependent manner.¹⁰ To understand whether the gene expression profiles of cancer cells responding to anti-inflammatory drugs are also dose-dependent, the designated concentrations of drugs were applied to microarray experiments. The concentrations of each anti-inflammatory drug are based on the least effect on cell viability analyses described previously.¹⁰ The averages of the cell viability at all of the designated concentrations are as follows: 94.5% for celecoxib (0.01 to 10 µM), 98% for dexamethasone (0.01 to 10 µM), 96.5% for PDTC (0.1 to 10 µM), 93% for aspirin (0.1 to 10 µM), and 98.4% for thalidomide (5 to 50 µM, unpublished data). The concentrations of thalidomide used in microarray experiments were higher than for other drugs, which is due to the lesser effect on suppressing IL-8 induction.^38,39 Although the suppressive effects of these drugs on IL-8 mRNA induction were very similar, their possible mechanisms of action are quite different.^39-44 Nevertheless, the inhibitory effect of these anti-inflammatory drugs is, for the most part, finally mediated through the NF-B pathway.

To explore and interpret the differentially functional mechanisms of these five anti-inflammatory drugs, we applied microarray analysis to monitor the gene expression profiles of lung cancer cells responding to drugs in macrophage/cancer cell cocultures. It was evident that the gene expression profile of non-cocultured cells was switched to a novel one after macrophage stimulation. Interestingly, the anti-inflammatory agents tested in this study, except for thalidomide, revealed the capacity to recover, at least in part, the switched stage (Fig 6). Some of the differentially expressed genes in treatment with thalidomide as compared with the other anti-inflammatory drugs are well known to be involved in cancer progression. For example, spermidine/spermine N1-acetyltransferase (SSAT) is induced by hepatotoxins and liver tumor promoters⁴⁵ and is found specifically in the tumor tissue, not in normal lung tissue.⁴⁶ Furthermore, SSAT induced by cytokines, IL-1ß, and hepatocyte growth factor controls tumor metabolism and growth, as well as tumor-host interaction.⁴⁵ Human platelet-derived growth factor beta (PDGF-ß) chain is closely involved in cell growth, oncogenicity, and blood vessel maturation.^47,48 Interestingly, the transcription factor NF-B also plays an important role in PDGF-ß chain transformation of mouse fibroblast cells and is sensitive to treatment with aspirin.⁴⁹ STC-1 mRNA is enhanced in hepatocellular carcinoma and colorectal cancer compared to cancer-free tissues, and might be a useful molecular marker.⁵⁰ All these three gene expressions were dramatically suppressed by celecoxib, dexamethasone, and PDTC, which were probably related to the inhibition of the NF-B signaling pathway. Interestingly, thalidomide had little effect on these gene expressions, which was distinctly different from the other four anti-inflammatory drugs. In addition, urokinase-type plasminogen activator receptor and C/EBPB also revealed the similar results.

In dose-dependent experiments, the results indicated that there is no dose-dependent effect of gene expression patterns on cancer cells responding to anti-inflammatory drugs. Although some drugs, such as celecoxib, dexamethasone, and PDTC, showed a dose-dependent effect in inhibiting IL-8 expression in lung cancer cell/macrophage cocultures in a previous study,¹⁰ it was just the result derived from one gene and a different approach. The gene expression profile consisted of many genes, therefore it might not have been suitable to perform a dose-dependent experiment.

Taken together, the interaction of lung cancer cells/macrophages can promote the invasiveness and matrix-degrading activity of lung cancer cells. By using microarray technology, we have identified several genes involved in the interaction between cancer cells and macrophages, which may assist us in exploring complex interactions between cancer cells and stroma that orchestrate the process of cancer metastasis. Our results also confirmed the bipolar roles of tumor-associated macrophages more clearly in cancer progression. Furthermore, the gene expression profiles of lung cancer cells responding to anti-inflammatory drugs in cancer cell/macrophage cocultures provide hints in interpreting the differentially functional mechanisms of drugs, as well as for evaluating the potential for new drug discovery in pharmacogenomics by microarray.

	Authors' Disclosures of Potential Conflicts of Interest

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The authors indicated no potential conflicts of interest.

	NOTES

 
Supported by the National Science Council (NSC 91-3112-P-005-008–Y; NSC91-3112-P-002-017-Y) and National Health Research Institutes of the Republic of China through the National Research Program for Genomic Medicine Grant (NHRI92A1-NSCLC09-5).

Presented in part at the 94th Meeting of the American Association for Cancer Research, Washington, DC, July 11-14, 2003.

Drs Chen, Lin, Yao, and Yuan contributed equally to this work.

Terms in blue are defined in the glossary, found at the end of this issue and online at www.jco.org.

Authors' disclosures of potential conflicts of interest are found at the end of this article.

	REFERENCES

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