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Prognostic Factors in Resected Stage I Non–Small-Cell Lung Cancer: A Multivariate Analysis of Six Molecular Markers

From the Departments of Thoracic/Head and Neck Medical Oncology, Clinical Cancer Prevention, Pathology, and Biostatistics, The University of Texas M.D. Anderson Cancer Center, Houston, TX; Institut Gustave Roussy, Villejuif, France; and Winship Cancer Institute, Emory University, Atlanta, GA

Address reprint requests to Charles Lu, MD, SM, The University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Box 432, Houston, TX 77030-4009; e-mail: clu{at}mdanderson.org

	ABSTRACT

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Authors' Disclosures of... REFERENCES

 
PURPOSE: To analyze the prognostic significance of six molecular biomarkers (death-associated protein kinase [DAPK] promoter methylation, interleukin-10 [IL-10] protein expression, cyclooxygenase-2 [COX-2] mRNA expression, human telomerase reverse transcriptase catalytic subunit [hTERT] mRNA expression, retinoic acid receptor-beta [RAR-ß] mRNA expression, and K-ras mutational status) in stage I non–small-cell lung cancer (NSCLC) patients.

PATIENTS AND METHODS: Biomarker analyses were performed on tumors from 94 patients with stage I NSCLC who underwent surgical resection at our institution. A minimum follow-up period of 5 years was required. DAPK methylation was assessed by methylation-specific polymerase chain reaction (PCR). RAR-ß, COX-2, and hTERT mRNA levels were determined by in situ hybridization with digoxigenin-labeled antisense riboprobes. K-ras mutation status was determined by the PCR–primer introduced restriction with enrichment for mutant alleles method. IL-10 protein expression was analyzed by immunohistochemistry using a polyclonal antihuman IL-10 antibody. Cancer-specific survival was analyzed with a Cox proportional hazards model. To identify independent prognostic factors, a stepwise selection method was used.

RESULTS: DAPK methylation, IL-10 lack of expression, COX-2 expression, hTERT expression, RAR-ß expression, and K-ras mutations were observed in 46.8%, 29.8%, 59.6%, 34.0%, 23.4%, and 34.0% of patients, respectively. In the final model, DAPK methylation and IL-10 lack of expression were significant negative prognostic factors for cancer-specific survival, whereas COX-2 expression was of borderline significance.

CONCLUSION: In this cohort of resected stage I NSCLC patients, molecular markers that independently predict cancer-specific survival have been identified. The prognostic roles of DAPK methylation, IL-10, and other biomarkers in NSCLC merit further investigation.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Authors' Disclosures of... REFERENCES

 
Lung cancer remains a worldwide public health issue of immense proportions. In the year 2003, cancers of the lung and bronchus are expected to continue to account for the most cancer deaths in the United States (157,200 deaths or 28.2%), more than the estimated total number of deaths as a result of cancers of the breast, prostate, colon, and rectum combined.¹ Approximately 80% of lung cancers will have non–small-cell carcinoma histology.²

Approximately 25% of patients present with early-stage disease.³ The standard treatment is surgical resection with appropriate lymph node sampling or dissection. Although early-stage non–small-cell lung cancer (NSCLC) patients have a relatively favorable prognosis, the risk of disease recurrence and death remains substantial. Five-year survival rates for pathologic stages I and II disease are 57% to 67% and 38% to 55%, respectively.⁴ Identification of reliable prognostic factors for disease recurrence and death could have significant clinical import. Patients in a high-risk group, for example, would be appropriate candidates for novel adjuvant or chemoprevention strategies.

Both our group^5-12 and others^13-16 have focused on identifying molecular prognostic factors in early-stage NSCLC. We have established a retrospective cohort of stage I NSCLC patients who underwent surgical resection at our institution. Over the past few years, investigators in our group have analyzed a number of tumor biomarkers within this valuable clinical research database.

Given the roles that retinoids play in the regulation of cell growth, differentiation, and apoptosis, Khuri et al⁸ investigated the prognostic significance of retinoic acid receptor-beta (RAR-ß) mRNA expression in 156 patients. Because RAR-ß expression seems to be suppressed during carcinogenesis, these investigators hypothesized that lower RAR-ß levels would predict a poor clinical outcome. Surprisingly, overall survival was significantly worse in patients with strongly positive RAR-ß expression. Because one RAR-ß isoform, RAR-ß4, may promote hyperplasia and neoplasia,¹⁷ the authors hypothesized that differential expression of RAR-ß isoforms may be a possible explanation for their unexpected findings.

Khuri et al⁹ subsequently evaluated cyclooxygenase-2 (COX-2) mRNA expression and correlated it with the expression of RAR-ß in this cohort of stage I NSCLC patients. COX-2 overexpression had previously been demonstrated in lung, head and neck, and other tumors,^18-20 and cell line data indicated that retinoic acid could suppress COX-2.²¹ These investigators found that COX-2 expression was associated with worse overall and disease-free survival and that COX-2 and RAR-ß mRNA levels were correlated. These findings were in conflict with the prior cell line data, which would have predicted that RAR-ß upregulation should downregulate COX-2.

Telomerase is a ribonucleoprotein that lengthens and maintains the ends of chromosomes that are shortened with successive cell divisions.²² Telomerase is expressed in up to 85% of NSCLC tumors and plays a critical role in sustaining cellular immortality and carcinogenesis.^23,24 Wang et al¹¹ examined mRNA expression of the human telomerase reverse transcriptase catalytic subunit (hTERT) in 153 patients from our database. Positive hTERT expression was significantly associated with worse overall and disease-specific survival.

Tang et al⁷ examined hypermethylation of the death-associated protein kinase (DAPK) promoter in 135 patients from this cohort. Epigenetic inactivation of tumor suppressor genes by promoter hypermethylation frequently occurs in NSCLC.^25,26 DAPK is a putative tumor-suppressor gene that encodes for a calmodulin-dependent kinase that possesses a death domain at its C terminus.²⁷ DAPK is required for interferon-gamma–induced apoptosis and seems to suppress the metastatic ability of lung cancer cells.²⁸ In the study by Tang et al,⁷ DAPK hypermethylation was significantly associated with poorer overall and disease-specific survival.

Soria et al¹² examined the role of interleukin-10 (IL-10) protein expression among 135 patients. The immunomodulatory effects of IL-10 have demonstrated conflicting results in various tumor systems. Some reports support the role of IL-10 in helping tumors evade immunosurveillance because IL-10 can inhibit macrophage, T-cell, and antigen-presenting cell functions.^29,30 Others have demonstrated that IL-10 may function as a potent inhibitor of tumor growth and metastasis.^31,32 In this study, IL-10 lack of expression was significantly associated with poorer overall and disease-specific survival.

The aforementioned hypothesis-driven studies each focused on one or a few biomarkers. To simultaneously examine multiple potential molecular prognostic factors in this clinical research database, we identified 94 patients who had complete information for a panel of six biomarkers (RAR-ß, COX-2, hTERT, DAPK promoter methylation, IL-10, and K-ras). Multivariate Cox regression analysis was used to identify independent predictors of cancer-specific survival in this population of resected stage I NSCLC patients.

	PATIENTS AND METHODS

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Study Population
Five hundred ninety-five consecutive patients with stage I NSCLC underwent definitive surgical resection, defined as a lobectomy or a pneumonectomy, from 1975 to 1990 at The University of Texas M.D. Anderson Cancer Center (Houston, TX). Patients did not receive preoperative or postoperative chemotherapy or radiotherapy. We retrospectively identified 185 patients for whom both tissue samples and a median follow-up period of more than 5 years were available. All available tissue blocks were reviewed by a thoracic pathologist (B.K.), and 163 cases had adequate tumor present in the surgical specimen. The patient population was identified through a search of the Tumor Registry database maintained by the Department of Medical Informatics at The University of M.D. Anderson Cancer Center. Survival status was verified and updated from Tumor Registry records as of December 1, 2000. This study was reviewed and approved by the institutional review board and conducted in accordance with its policies.

Five published studies^7-9,11,12 had previously examined different molecular prognostic factors among the 163 patients with sufficient tumor specimens and more than 5 years of follow-up data. The sample sizes ranged from 135 to 160 patients. A total of 94 patients had complete information for a panel of six biomarkers, and these patients were included in our analysis.

Methylation-Specific Polymerase Chain Reaction (PCR)
These methods have been previously described.⁷ Briefly, 8-µm sections from paraffin-embedded tissue blocks were obtained, and regions with tumor cells were dissected under a stereomicroscope. In the initial chemical modification step, 200 ng of DNA from each tumor was denatured by NaOH and treated with sodium bisulfite (Sigma Chemical Co, St Louis, MO). DNA was recovered in water and was ready to add to a PCR with the use of specific primers for either the methylated or the unmethylated DAPK promoter, as described previously.³³ DNA was amplified for 35 cycles, and PCR products were separated on 2% agarose gels and visualized. For each DNA sample, primer sets for methylated DNA and unmethylated DNA were used for analysis. The hypermethylation status was determined by visualizing a 98-base pair (bp) PCR product with the methylation-specific primer set. All PCRs were repeated twice, and the results were reproducible.

Immunohistochemical Staining for IL-10 Protein
Paraffin-embedded, 4-µm–thick tissue sections were stained for IL-10 protein using a primary goat polyclonal antihuman IL-10 antibody (AF-217-NA; R&D Systems, Minneapolis, MN) as previously described.¹² Routinely processed tissue sections of normal lymph nodes and tonsils were used as positive staining controls and were also stained with the primary antibody omitted to confirm staining specificity. Normal bronchial epithelial cells that constitutively produce IL-10 were also used as internal positive controls.³⁴

The IL-10 labeling index was defined as the percentage of tumor cells displaying cytoplasmic immunoreactivity and was calculated by counting IL-10–stained tumor cells among at least 1,000 tumor cells for each section as previously described.¹² On the basis of previous reports, if 10% or more of the tumor cells were positive for IL-10, the case was considered to be IL-10 positive.³⁵ All slides were scored concomitantly by a pathologist (X.T.) and another investigator (J.-C.S.) in a blinded manner.

hTERT In Situ Hybridization (ISH)
These methods have been previously described.¹¹ The riboprobes were a 430-bp EcoRV-BamH1 fragment of the hTERT cDNA that has been used in other studies^36,37 as well as part of exon 1 from the heterogeneous nuclear ribonucleoprotein A1 as a control to verify sample quality. The single-strand–specific, digoxigenin-labeled riboprobes were generated by in vitro transcription. ISH was performed as previously described.³⁷ Slides displaying a diffuse but clear cytoplasmic signal were considered to be positive, as reported by Falchetti et al.³⁸ More specifically, our slides were rated as positive if a definite and clear signal was present in more than two large areas on the slide. Slides with faint signal, the absence of signal, or only focal positivity were considered to be negative. We did not grade the intensity of the hybridization signals.

COX-2 and RAR-ß ISH
COX-2 and RAR-ß mRNA were detected in 4-µm–thick sections from paraffin-embedded tissue using nonradioactive ISH with digoxigenin-labeled antisense riboprobes as previously described.^8,9,39 Retinoid X receptor-alpha (RXR-), which is present in greater than 90% of NSCLCs,⁴⁰ was used as a control to detect RNA degradation. The rationale for using RXR- as a control for intact RNA was the observation that all 70 cases of NSCLC and normal lung tissue expressed RXR- mRNA in a previous study.⁴⁰ Stained sections were reviewed by three independent researchers, including two pathologists, in a blinded fashion. Only cytoplasmic staining was considered positive. Because normal bronchial epithelium expresses RAR-ß, positive and aberrant RAR-ß expression was defined as 10% and less than 10% intratumoral staining, respectively.⁸ The RAR-ß probe that was used identified all RAR-ß isoforms. COX-2 expression was defined as either positive (present) or negative (absent).⁹

K-ras Mutation Analysis With PCR–Primer Introduced Restriction With Enrichment for Mutation Alleles (PCR-PIREMA)
A modified PCR-PIREMA method was used to detect K-ras codon 12 mutations.⁴¹ Briefly, 8-µm sections from paraffin-embedded tissue blocks were obtained, and regions with tumor cells were dissected under a stereomicroscope. Dissected tissues were digested in 200 µL of digestion buffer containing 50 mmol/L Tris-HCl (pH 8.0), 1% sodium dodecyl sulfate, and proteinase K (0.5 mg/mL) at 42°C for 36 hours. The digested products were purified by extracting with phenol-chloroform twice. DNA was then precipitated by the ethanol precipitation method in the presence of glycogen (Roche Biochemicals, Indianapolis, IN), recovered in distilled water, and then stored at –20°C until used for PCR.

Briefly, PCR around K-ras codon 12 was performed using a mismatched primer (forward primer: 5'-TGAATATAAACTTGTGGTAGTTGGACCT-3'; reverse primer: 5'-CTGTATCAAAGAATGGTCC TGCACC-3') that introduced an MvaI restriction site into the PCR products derived from normal alleles. MvaI digestion of the PCR products left only the PCR products derived from mutant alleles intact, after which further PCR selectively amplified the mutant PCR products. The first PCR reaction was performed with mixtures containing 0.5 µL of DNA recovery solution, 10 ng of each nucleotide, and the mismatched primer to introduce an Mva I restriction site flanking the K-ras exon 1, with 15 cycles at an annealing temperature of 55°C. The first PCR products were digested with MvaI and diluted 1:100. One microliter of the diluted product was amplified by 20 cycles of PCR with the same primers at an annealing temperature of 40°C, and the products were digested with MvaI a second time. The second PCR products were diluted 1:100, amplified by 35 cycles with the previous forward primer and a new reverse primer (5'-CTCTATTGTTGGATCATATTCGTCCAC-3') at an annealing temperature of 65°C, and digested with MvaI a third time. The final digested products were then electrophoresed on 2.5% agarose gels and stained with ethidium bromide. A digestion-resistant 106-bp band indicated the presence of a K-ras codon 12 mutation. Extensive measures were taken to prevent cross-contamination of samples. A normal control sample and a known mutation sample were included in all of the experiments.

Statistical Analyses
Overall survival, disease-specific survival, and disease-free survival were analyzed in this study. Survival curves were estimated by the Kaplan-Meier method. The log-rank test was used to compare survival time between groups. Fisher's exact test was used to analyze the association between categoric variables. Using a stepwise selection method, a Cox proportional hazards model was created to identify independent predictors of survival, with adjustment for relevant clinical covariates (tumor stage, histology, smoking status, and sex). All statistical tests were two-sided, and P < .05 was considered statistically significant.

All survival curves were calculated from the date of surgery. Overall survival took all deaths (cancer related or not) into account. Disease-specific survival time was calculated from the date of surgery to death from cancer-related causes. Disease-free survival time was calculated from the date of surgery to relapse or death from cancer-related causes.

	RESULTS

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Data for a panel of six molecular markers (RAR-ß, COX-2, hTERT, DAPK promoter methylation, IL-10, and K-ras) were available for 94 patients in our retrospective cohort. These patients were the study population for our analysis. Patient characteristics are listed in Table 1. Median follow-up time for alive patients and those lost to follow-up was 10.9 years. Sixty-nine patients have died. Twenty-nine deaths were cancer related.

View larger version (20K): [in this window] [in a new window]   Fig 1. Disease-specific survival stratified by (A) retinoic acid receptor-beta (RAR-ß) mRNA expression, (B) K-ras mutation status, (C) human telomerase reverse transcriptase catalytic subunit (hTERT) mRNA expression, (D) cyclooxygenase-2 (COX-2) mRNA expression, (E) death-associated protein kinase (DAPK) methylation, and (F) interleukin-10 (IL-10) protein expression.

View larger version (17K): [in this window] [in a new window]   Fig 2. Disease-specific survival (A) and overall survival (B) of patients with both death-associated protein kinase methylation and interleukin-10 lack of expression (high risk) versus other patients (low risk).

We also investigated other models by performing all two-variable, three-variable, and four-variable multivariate models. On the basis of these analyses, only DAPK methylation and IL-10 lack of expression were statistically significant (P < .05) for all models. Furthermore, the three-variable model, including DAPK methylation, IL-10 lack of expression, and COX-2 expression, had the lowest Akaike Information Criterion (AIC) value of 224.029 (although the two-variable model that excluded COX-2 expression had an AIC of similar value). We noted that there was some evidence of association between IL-10 lack of expression and hTERT expression (OR, 2.63; P = .056) and IL-10 lack of expression and COX-2 expression (OR, 2.63; P = .066). Moreover, hTERT and COX-2 expression were highly associated (OR, 6.14; P = .0004). We ensured that the effect of these variables was not masked by colinearity by modeling them separately. Specifically, we modeled COX-2 expression with DAPK methylation (AIC = 228.135) and hTERT expression with DAPK methylation (AIC = 228.654). Neither of these models provided better fit than the model chosen.

	DISCUSSION

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Our findings further characterize and extend our group's previous research efforts to identify novel molecular prognostic factors in patients with early-stage NSCLC. We identified 94 patients with complete information for a panel of six molecular markers. Each biomarker had been previously studied as a prognostic factor based on its role in carcinogenesis. When analyzed individually, five of these biomarkers (RAR-ß, COX-2, hTERT, DAPK promoter methylation, and IL-10) were demonstrated in prior studies^7-9,11,12 by our group to be significant predictors of survival. One available marker (K-ras) was included in the current analysis based on published data demonstrating that it had prognostic significance in early-stage NSCLC,^14,42 even though it did not have prognostic significance in univariate analysis in our patients. Our multivariable analysis indicates that two biomarkers (DAPK promoter methylation and IL-10) function as independent predictors of disease-specific survival, and a third biomarker (COX-2) is of borderline significance in this cohort. These findings should be confirmed in other NSCLC patient populations.

Our results further support the importance of epigenetic gene regulation in lung carcinogenesis. Others have demonstrated that aberrant promoter methylation of DAPK and other genes frequently occurs in NSCLC tumors,^25,26 suggesting that methylation may be a common mechanism of inactivation of cancer-related genes. DAPK promoter methylation was the most statistically significant predictor of survival in our study. Kim et al⁴³ investigated the role of DAPK methylation in 185 NSCLC patients who underwent surgical resection, including 102 patients with stage I disease. DAPK methylation was significantly correlated with advanced stage, suggesting that DAPK may be important in the progression of NSCLC. Stage I patients with DAPK methylation had worse overall survival, although this association was not statistically significant. The authors noted that patient follow-up data was limited, and this factor may have contributed to their findings. Harden et al⁴⁴ examined promoter methylation of a panel of five genes in tumors and lymph nodes of 90 stage I NSCLC patients. Interestingly, patients with both DAPK and adenomatous polyposis coli gene methylation had poorer overall survival that did not reach statistical significance, although the methylation of either gene alone was not a predictor of survival. Possible explanations for these results include the relatively low frequency of DAPK methylation (17%) compared with our findings (47%). The smaller number of patients with DAPK methylation (n = 15) would result in the study having less power to detect significant associations with survival.

The role of IL-10 in carcinogenesis remains controversial. Our findings indicate that loss of IL-10 expression predicts poor disease-specific survival in early-stage NSCLC. Human bronchial epithelial cells constitutively produce IL-10, which may regulate the local immune response in normal lungs.³⁴ IL-10 also seems to have significant inhibitory effects on tumor growth and metastasis in multiple animal models and tumor types, including melanoma, breast cancer, prostate cancer, and Burkitt's lymphoma.^31,32,45-47 Evidence suggests that IL-10 exerts its antitumor and antimetastatic activity by inhibiting angiogenesis, and this activity is, in part, mediated by the downregulation of angiogenic molecules, such as vascular endothelial growth factor, IL-1ß, tumor necrosis factor-, IL-6, and matrix metalloproteinase-9 (MMP-9), in tumor-associated macrophages.³¹ In addition, IL-10 may also directly affect the secretion of angiogenic molecules from the tumor. Stearns et al⁴⁶ demonstrated that IL-10 induces tissue inhibitor of metalloproteinase-1 production and inhibits MMP-2 and MMP-9 secretion by human prostate cancer cell lines orthotopically implanted into mice, resulting in decreased tumor microvessel formation and increased mice survival. In a murine mammary tumor model, the antitumor and antimetastatic effects of IL-10 gene transfection were associated with elevated nitric oxide levels in tumors.⁴⁸ Others have shown that IL-10 can directly inhibit the proliferation of endothelial cells stimulated with vascular endothelial growth factor or fibroblast growth factor-2 in vitro.⁴⁷ An intriguing molecular epidemiologic case-control study demonstrated that IL-10 promoter polymorphisms that resulted in lower IL-10 expression were associated with an increased risk of developing melanoma.⁴⁹ Furthermore, some authors have suggested that lung cancer cells can modulate IL-10 expression by stromal components. In the present study, only nine of 94 samples displayed tumor-infiltrating lymphocytes or tumor-associated macrophages, therefore hindering any relevant analysis of IL-10 production by infiltrating immune cells.

The data supporting the antitumor and antimetastatic activity of IL-10 are compelling, but most preclinical models using IL-10 to mediate such effects do so at concentrations that far exceed the levels demonstrated in lung cancer patients. Other authors have demonstrated that IL-10 is a potent immunosuppressive molecule that may promote lung cancer growth by suppressing T-cell and macrophage function and enabling tumors to escape immune detection.^50-52 Elevated baseline serum IL-10 levels were found to be independent predictors of poorer survival in 60 advanced-stage NSCLC patients receiving platinum-based chemotherapy.⁵³ Hatanaka et al⁵⁴ measured IL-10 mRNA levels by reverse transcriptase PCR in the tumors of 82 NSCLC patients who underwent surgical resection. Their assay demonstrated IL-10 expression in 83% of the surgical specimens. In contrast to our results, IL-10 expression was significantly associated with worse survival. The reasons for these discrepant findings remain unclear. These investigators included patients with stages I to IIIb disease in their study and used a different IL-10 assay (mRNA v protein) than the assay we used in our study. These factors may have contributed to these divergent results.

Our exploratory analyses demonstrate a highly significant association between hTERT expression and COX-2 expression (P = .0004). A precise explanation for this correlation is lacking, although various COX-2 inhibitors have been reported to inhibit both tumor growth and telomerase activity in mice.^55,56 We also observed a significant association between K-ras mutations and DAPK methylation (P = .032). Reports suggesting that DNA methylation may be regulated by the ras signaling pathway^57,58 are consistent with these findings. However, others have not found correlations between ras mutations and promoter hypermethylation in NSCLC tumors.^43,59 Clearly, a better understanding of the significance of these associations will require future studies. Our analyses also demonstrate a borderline significant association between IL-10 lack of expression and COX-2 expression (P = .066).^60,61 This finding is consistent with data suggesting that IL-10 has the capacity to potently downregulate COX-2. Therefore, in the absence of IL-10, COX-2 and its derived products would be more abundant and could further promote tumor progression.

This study is limited by its retrospective nature and the inclusion only of patients with complete information for all six biomarkers. It is difficult to speculate on potential biases affecting our results. It is possible, for example, that small tumors with limited tissue availability were underrepresented in this cohort. These results should be validated in a separate population of NSCLC patients.

In conclusion, our analysis of six molecular markers in patients with resected stage I NSCLC yielded two independent predictors of poorer disease-specific survival: DAPK methylation and IL-10 lack of expression. Future studies are warranted to further define their roles in tumor proliferation and metastasis. However, these and other potential molecular prognostic factors have yet to be validated, and thus, the integration of molecular marker assessments into the routine clinical management of NSCLC has remained an elusive goal. As the number of potential molecular markers increases, it has become more difficult to assess which prognostic factors are likely to be clinically relevant. A comprehensive multivariable analysis is not feasible because the majority of studies analyze only a single or a few biomarkers at a time. In this regard, the development of high-throughput technologies to determine gene-expression profiles and proteomic patterns of tissue specimens represents a significant methodologic advance. Several recent reports have demonstrated that mRNA and protein patterns of NSCLC tumors may be predictive of survival.^62,63 Hopefully, these technologies will eventually provide the clinician with a reliable, validated molecular staging system that will improve therapeutic strategies for NSCLC.

	Authors' Disclosures of Potential Conflicts of Interest

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The authors indicated no potential conflicts of interest.

	NOTES

 
Supported in part by National Cancer Institute grant No. K12 CA088084 and the Department of Defense, Biology, Education, Screening, Chemoprevention, and Treatment of Lung Cancer grant No. DAMD17-01-1-0689 and Translational Approaches for the Reversal, Genetic, Evaluation and Treatment of Lung Cancer grant No. DAMD17-02-1-0706.

Presented in part at the 93rd Annual Meeting of the American Association for Cancer Research, San Francisco, CA, April 6–10, 2002.

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

	REFERENCES

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Authors' Disclosures of... REFERENCES

 
1. Jemal A, Murray T, Samuels A, et al: Cancer statistics, 2003. CA Cancer J Clin 53:5–26, 2003[Abstract/Free Full Text]

2. Travis W, Travis LB, Devesa SS: Lung cancer incidence and survival by histologic type. Cancer 75:191–202, 1995 (suppl 1)[CrossRef][Medline]

3. Fry W, Phillips JL, Menck HR: Ten-year survey of lung cancer treatment and survival in hospitals in the United States. Cancer 86:1867–1876, 1999[CrossRef][Medline]

4. Mountain CF: Revisions in the International System for Staging Lung Cancer. Chest 111:1710–1717, 1997[Abstract/Free Full Text]

5. Tseng JE, Kemp BL, Khuri FR, et al: Loss of Fhit is frequent in stage I non-small cell lung cancer and in the lungs of chronic smokers. Cancer Res 59:4798–4803, 1999[Abstract/Free Full Text]

6. Herbst RS, Yano S, Kuniyasu H, et al: Differential expression of E-cadherin and type IV collagenase genes predicts outcome in patients with stage I non-small cell lung carcinoma. Clin Cancer Res 6:790–797, 2000[Abstract/Free Full Text]

7. Tang X, Khuri FR, Lee JJ, et al: Hypermethylation of the death-associated protein (DAP) kinase promoter and aggressiveness in stage I non-small-cell lung cancer. J Natl Cancer Inst 92:1511–1516, 2000[Abstract/Free Full Text]

8. Khuri FR, Lotan R, Kemp BL, et al: Retinoic acid receptor-beta as a prognostic indicator in stage I non–small-cell lung cancer. J Clin Oncol 18:2798–2804, 2000[Abstract/Free Full Text]

9. Khuri FR, Wu H, Lee JJ, et al: Cyclooxygenase-2 overexpression is a marker of poor prognosis in stage I non-small cell lung cancer. Clin Cancer Res 7:861–867, 2001[Abstract/Free Full Text]

10. Zhou X, Kemp BL, Khuri FR, et al: Prognostic implication of microsatellite alteration profiles in early-stage non-small cell lung cancer. Clin Cancer Res 6:559–565, 2000[Abstract/Free Full Text]

11. Wang L, Soria JC, Kemp BL, et al: HTERT expression is a prognostic factor of survival in patients with stage I non-small cell lung cancer. Clin Cancer Res 8:2883–2889, 2002[Abstract/Free Full Text]

12. Soria JC, Moon C, Kemp BL, et al: Lack of interleukin-10 expression could predict poor outcome in patients with stage I non-small cell lung cancer. Clin Cancer Res 9:1785–1791, 2003[Abstract/Free Full Text]

13. Pastorino U, Andreola S, Tagliabue E, et al: Immunocytochemical markers in stage I lung cancer: Relevance to prognosis. J Clin Oncol 15:2858–2865, 1997[Abstract]

14. Kwiatkowski DJ, Harpole DH Jr, Godleski J, et al: Molecular pathologic substaging in 244 stage I non-small-cell lung cancer patients: Clinical implications. J Clin Oncol 16:2468–2477, 1998[Abstract]

15. D'Amico TA, Massey M, Herndon JE II, et al: A biologic risk model for stage I lung cancer: Immunohistochemical analysis of 408 patients with the use of ten molecular markers. J Thorac Cardiovasc Surg 117:736–743, 1999[Abstract/Free Full Text]

16. Ahrendt SA, Hu Y, Buta M, et al: p53 mutations and survival in stage I non-small-cell lung cancer: Results of a prospective study. J Natl Cancer Inst 95:961–970, 2003[Abstract/Free Full Text]

17. Berard J, Gaboury L, Landers M, et al: Hyperplasia and tumours in lung, breast and other tissues in mice carrying a RAR beta 4-like transgene. EMBO J 13:5570–5580, 1994[Medline]

18. Taketo MM: Cyclooxygenase-2 inhibitors in tumorigenesis (Part II). J Natl Cancer Inst 90:1609–1620, 1998[Abstract/Free Full Text]

19. Hida T, Yatabe Y, Achiwa H, et al: Increased expression of cyclooxygenase 2 occurs frequently in human lung cancers, specifically in adenocarcinomas. Cancer Res 58:3761–3764, 1998[Abstract/Free Full Text]

20. Wolff H, Saukkonen K, Anttila S, et al: Expression of cyclooxygenase-2 in human lung carcinoma. Cancer Res 58:4997–5001, 1998[Abstract/Free Full Text]

21. Li M, Song S, Lippman SM, et al: Induction of retinoic acid receptor-beta suppresses cyclooxygenase-2 expression in esophageal cancer cells. Oncogene 21:411–418, 2002[CrossRef][Medline]

22. Hahn WC: Role of telomeres and telomerase in the pathogenesis of human cancer. J Clin Oncol 21:2034–2043, 2003[Abstract/Free Full Text]

23. Hiyama K, Hiyama E, Ishioka S, et al: Telomerase activity in small-cell and non-small-cell lung cancers. J Natl Cancer Inst 87:895–902, 1995[Abstract/Free Full Text]

24. Kim NW, Piatyszek MA, Prowse KR, et al: Specific association of human telomerase activity with immortal cells and cancer. Science 266:2011–2015, 1994[Abstract/Free Full Text]

25. Zochbauer-Muller S, Fong KM, Maitra A, et al: 5' CpG island methylation of the FHIT gene is correlated with loss of gene expression in lung and breast cancer. Cancer Res 61:3581–3585, 2001[Abstract/Free Full Text]

26. Esteller M, Corn PG, Baylin SB, et al: A gene hypermethylation profile of human cancer. Cancer Res 61:3225–3229, 2001[Abstract/Free Full Text]

27. Deiss LP, Feinstein E, Berissi H, et al: Identification of a novel serine/threonine kinase and a novel 15-kD protein as potential mediators of the gamma interferon-induced cell death. Genes Dev 9:15–30, 1995[Abstract/Free Full Text]

28. Inbal B, Cohen O, Polak-Charcon S, et al: DAP kinase links the control of apoptosis to metastasis. Nature 390:180–184, 1997[CrossRef][Medline]

29. Beissert S, Hosoi J, Grabbe S, et al: IL-10 inhibits tumor antigen presentation by epidermal antigen-presenting cells. J Immunol 154:1280–1286, 1995[Abstract]

30. Rohrer JW, Coggin JH Jr: CD8 T cell clones inhibit antitumor T cell function by secreting IL-10. J Immunol 155:5719–5727, 1995[Abstract]

31. Huang S, Ullrich SE, Bar-Eli M: Regulation of tumor growth and metastasis by interleukin-10: the melanoma experience. J Interferon Cytokine Res 19:697–703, 1999[CrossRef][Medline]

32. Kundu N, Beaty TL, Jackson MJ, et al: Antimetastatic and antitumor activities of interleukin 10 in a murine model of breast cancer. J Natl Cancer Inst 88:536–541, 1996[Abstract/Free Full Text]

33. Esteller M, Sanchez-Cespedes M, Rosell R, et al: Detection of aberrant promoter hypermethylation of tumor suppressor genes in serum DNA from non-small cell lung cancer patients. Cancer Res 59:67–70, 1999[Abstract/Free Full Text]

34. Bonfield TL, Konstan MW, Burfeind P, et al: Normal bronchial epithelial cells constitutively produce the anti-inflammatory cytokine interleukin-10, which is downregulated in cystic fibrosis. Am J Respir Cell Mol Biol 13:257–261, 1995[Abstract]

35. Fujieda S, Lee K, Sunaga H, et al: Staining of interleukin-10 predicts clinical outcome in patients with nasopharyngeal carcinoma. Cancer 85:1439–1445, 1999[CrossRef][Medline]

36. Kolquist KA, Ellisen LW, Counter CM, et al: Expression of TERT in early premalignant lesions and a subset of cells in normal tissues. Nat Genet 19:182–186, 1998[CrossRef][Medline]

37. Soria JC, Moon C, Wang L, et al: Effects of N-(4-hydroxyphenyl)retinamide on hTERT expression in the bronchial epithelium of cigarette smokers. J Natl Cancer Inst 93:1257–1263, 2001[Abstract/Free Full Text]

38. Falchetti ML, Pallini R, D'Ambrosio E, et al: In situ detection of telomerase catalytic subunit mRNA in glioblastoma multiforme. Int J Cancer 88:895–901, 2000[CrossRef][Medline]

39. Xu XC, Ro JY, Lee JS, et al: Differential expression of nuclear retinoid receptors in normal, premalignant, and malignant head and neck tissues. Cancer Res 54:3580–3587, 1994[Abstract/Free Full Text]

40. Xu XC, Sozzi G, Lee JS, et al: Suppression of retinoic acid receptor beta in non-small-cell lung cancer in vivo: Implications for lung cancer development. J Natl Cancer Inst 89:624–629, 1997[Abstract/Free Full Text]

41. Jacobson DR, Mills NE: A highly sensitive assay for mutant ras genes and its application to the study of presentation and relapse genotypes in acute leukemia. Oncogene 9:553–563, 1994[Medline]

42. Slebos RJ, Kibbelaar RE, Dalesio O, et al: K-ras oncogene activation as a prognostic marker in adenocarcinoma of the lung. N Engl J Med 323:561–565, 1990[Abstract]

43. Kim DH, Nelson HH, Wiencke JK, et al: Promoter methylation of DAP-kinase: Association with advanced stage in non-small cell lung cancer. Oncogene 20:1765–1770, 2001[CrossRef][Medline]

44. Harden SV, Tokumaru Y, Westra WH, et al: Gene promoter hypermethylation in tumors and lymph nodes of stage I lung cancer patients. Clin Cancer Res 9:1370–1375, 2003[Abstract/Free Full Text]

45. Gerard CM, Bruyns C, Delvaux A, et al: Loss of tumorigenicity and increased immunogenicity induced by interleukin-10 gene transfer in B16 melanoma cells. Hum Gene Ther 7:23–31, 1996[Medline]

46. Stearns ME, Garcia FU, Fudge K, et al: Role of interleukin 10 and transforming growth factor beta1 in the angiogenesis and metastasis of human prostate primary tumor lines from orthotopic implants in severe combined immunodeficiency mice. Clin Cancer Res 5:711–720, 1999[Abstract/Free Full Text]

47. Cervenak L, Morbidelli L, Donati D, et al: Abolished angiogenicity and tumorigenicity of Burkitt lymphoma by interleukin-10. Blood 96:2568–2573, 2000[Abstract/Free Full Text]

48. Kundu N, Dorsey R, Jackson MJ, et al: Interleukin-10 gene transfer inhibits murine mammary tumors and elevates nitric oxide. Int J Cancer 76:713–719, 1998[CrossRef][Medline]

49. Howell WM, Turner SJ, Bateman AC, et al: IL-10 promoter polymorphisms influence tumour development in cutaneous malignant melanoma. Genes Immun 2:25–31, 2001[CrossRef][Medline]

50. Sharma S, Stolina M, Lin Y, et al: T cell-derived IL-10 promotes lung cancer growth by suppressing both T cell and APC function. J Immunol 163:5020–5028, 1999[Abstract/Free Full Text]

51. Spagnoli GC, Juretic A, Schultz-Thater E, et al: On the relative roles of interleukin-2 and interleukin-10 in the generation of lymphokine-activated killer cell activity. Cell Immunol 146:391–405, 1993[CrossRef][Medline]

52. Huang M, Sharma S, Mao JT, et al: Non-small cell lung cancer-derived soluble mediators and prostaglandin E2 enhance peripheral blood lymphocyte IL-10 transcription and protein production. J Immunol 157:5512–5520, 1996[Abstract]

53. De Vita F, Orditura M, Galizia G, et al: Serum interleukin-10 levels as a prognostic factor in advanced non-small cell lung cancer patients. Chest 117:365–373, 2000[Abstract/Free Full Text]

54. Hatanaka H, Abe Y, Kamiya T, et al: Clinical implications of interleukin (IL)-10 induced by non-small-cell lung cancer. Ann Oncol 11:815–819, 2000[Abstract/Free Full Text]

55. Nishimura G, Yanoma S, Mizuno H, et al: A selective cyclooxygenase-2 inhibitor suppresses tumor growth in nude mouse xenografted with human head and neck squamous carcinoma cells. Jpn J Cancer Res 90:1152–1162, 1999[CrossRef][Medline]

56. Lonnroth C, Andersson M, Lundholm K: Indomethacin and telomerase activity in tumor growth retardation. Int J Oncol 18:929–937, 2001[Medline]

57. Rouleau J, MacLeod AR, Szyf M: Regulation of the DNA methyltransferase by the Ras-AP-1 signaling pathway. J Biol Chem 270:1595–1601, 1995[Abstract/Free Full Text]

58. Bigey P, Ramchandani S, Theberge J, et al: Transcriptional regulation of the human DNA methyltransferase (dnmt1) gene. Gene 242:407–418, 2000[CrossRef][Medline]

59. Pulling LC, Divine KK, Klinge DM, et al: Promoter hypermethylation of the O6-methylguanine-DNA methyltransferase gene: More common in lung adenocarcinomas from never-smokers than smokers and associated with tumor progression. Cancer Res 63:4842–4848, 2003[Abstract/Free Full Text]

60. Moore KW, de Waal Malefyt R, Coffman RL, et al: Interleukin-10 and the interleukin-10 receptor. Annu Rev Immunol 19:683–765, 2001[CrossRef][Medline]

61. Molina-Holgado E, Arevalo-Martin A, Ortiz S, et al: Theiler's virus infection induces the expression of cyclooxygenase-2 in murine astrocytes: Inhibition by the anti-inflammatory cytokines interleukin-4 and interleukin-10. Neurosci Lett 324:237–241, 2002[CrossRef][Medline]

62. Beer DG, Kardia SL, Huang CC, et al: Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nat Med 8:816–824, 2002[Medline]

63. Yanagisawa K, Shyr Y, Xu BJ, et al: Proteomic patterns of tumour subsets in non-small-cell lung cancer. Lancet 362:433–439, 2003[CrossRef][Medline]

Submitted January 13, 2004; accepted August 26, 2004.

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