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Journal of Clinical Oncology, Vol 23, No 36 (December 20), 2005: pp. 9105-9112 © 2005 American Society of Clinical Oncology. DOI: 10.1200/JCO.2005.02.2905
14-3-3
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONPATIENTS AND METHODSRESULTSDISCUSSIONAuthors' Disclosures of...REFERENCES |
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, a major G2-M checkpoint control gene, could be a predictor of longer survival.
PATIENTS AND METHODS: A sensitive methylation-specific polymerase chain reaction assay was used to evaluate 14-3-3 methylation status in pretreatment serum DNA obtained from 115 cisplatin-plus-gemcitabine–treated advanced NSCLC patients.
RESULTS: 14-3-3 methylation was observed in all histologic types of 39 patients (34%). After a median follow-up of 9.8 months, median survival was significantly longer in the methylation-positive group (15.1 v 9.8 months; P = .004). Median time to progression was 8 months in the methylation-positive group and 6.3 months in the methylation-negative group (log-rank test, P = .027). A multivariate Cox regression model identified only 14-3-3 methylation status and Eastern Cooperative Oncology Group performance status as independent prognostic factors for survival. In an exploratory analysis, median survival for 22 methylation-positive responders has not been reached, whereas survival was 11.3 months for 29 methylation-negative responders (P = .001).
CONCLUSION: Methylation of 14-3-3 is a new independent prognostic factor for survival in NSCLC patients receiving platinum-based chemotherapy. It can be reliably and conveniently detected in the serum, thus obviating the need for tumor tissue analysis.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONPATIENTS AND METHODSRESULTSDISCUSSIONAuthors' Disclosures of...REFERENCES |
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A member of the 14-3-3 superfamily, 14-3-3 is responsible for G2 cell cycle checkpoint control in response to DNA damage in human cells.4-56 Its function has been analyzed in the human colorectal cancer cell line HCT116 (expressing 14-3-3 and wild-type p53).4-6 Following ionizing irradiation, 14-3-3 sequestered Cdc2/cyclin B1 complexes in the cytoplasm, thus arresting cells in G2 and preventing them from initiating mitosis before repair to their damaged DNA.4 Colon carcinoma cells lacking 14-3-3 treated with doxorubicin can still initiate—but do not maintain—G2 arrest, leading to mitotic catastrophe and cell death.4 The expression of 14-3-3 is reduced by p53 gene inactivation and by silencing of 14-3-3 gene via methylation of CpG islands.7,8 By proteomic analysis, 14-3-3 was undetectable in breast cancer samples,9 and hypermethylation of normally unmethylated CpG islands in the promoter region of 14-3-3 was involved in gene silencing at the transcriptional level in breast cancers.7,10 Similar effects of 14-3-3 hypermethylation have been reported in many tumors, including lung,11 gastric,12 ovarian,13 prostate,14 and hepatocellular15 carcinomas.
It is well known that double-stranded DNA fragments are frequently and abundantly found in the serum of cancer patients, with significantly higher levels in patients with metastases.16 The same microsatellite alterations detected in the tumor were also found in plasma or serum DNA in head and neck,17 small-cell lung18 and non–small-cell lung19,20 cancers. Furthermore, the detection of hypermethylation in the promoter regions of tumor suppressor genes was first reported in the serum of NSCLC patients.21 Hypermethylation can be analyzed by the sensitive methylation-specific polymerase chain reaction assay, which can identify one methylated allele in 1,000 unmethylated alleles.22
14-3-3 was found to be methylated in 43% of 60 gastric cancers and the 14-3-3 methylation–positive human gastric cell lines MKN74 (with wild-type p53) and MKN28 (with mutated p53) were both highly sensitive to doxorubicin, whereas 14-3-3 methylation–negative cell lines (either with wild-type or mutated p53) were resistant.12 Because defects in the cell cycle checkpoint may contribute to chemosensitivity, we reasoned that patients with 14-3-3 methylation–positive tumors would derive greater benefit from cisplatin-based chemotherapy. In this prospective study, we investigated whether 14-3-3 methylation in pretreatment acellular serum DNA could predict survival in advanced NSCLC patients treated with cisplatin plus gemcitabine.
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PATIENTS AND METHODS |
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TOPABSTRACTINTRODUCTIONPATIENTS AND METHODSRESULTSDISCUSSIONAuthors' Disclosures of...REFERENCES |
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methylation in the sera of advanced NSCLC patients and correlate methylation status with survival. The study was approved by the independent ethics committees of all six participating centers, and all patients gave their signed informed consent.
Patients
Patients were considered eligible if they had stage IV or stage IIIB (with malignant pleural effusion) histologically confirmed NSCLC. Other eligibility criteria included an Eastern Cooperative Oncology Group performance status (ECOG PS) of 0 (asymptomatic and fully active) or 1 (symptomatic, fully ambulatory, restricted in physically strenuous activity); age of at least 18 years; adequate hematologic function (hemoglobin at least 9 g per deciliter [5.6 mmol/L], neutrophil count at least 1,500 per cubic millimeter, and platelet count at least 100,000 per cubic millimeter); adequate renal function (serum creatinine < 1.5x the upper limit of normal); and adequate liver function (bilirubin not > 1.5x the upper limit of normal, AST and ALT not > 5x the upper limit of normal). Patients with clinically overt brain metastases and those who had received previous chemotherapy were excluded. Patients with an ECOG PS of 2 (symptomatic, ambulatory, capable of self care, more than 50% of waking hours spent out of bed) were also excluded, based on results of previous studies in which these patients had a high rate of serious adverse events and poor survival.1
Patients received cisplatin at a dose of 75 mg/m2 of body-surface area on day 1 plus gemcitabine at a dose of 1,250 mg/m2 on days 1 and 8. The cycle was repeated every 3 weeks for a maximum of six cycles.
All patients underwent staging procedures at baseline, including a physical examination, a two-view chest x-ray, and a computed tomography of the thorax and abdomen. Bone scans or computed tomography scans of the brain were required only if bone or brain metastases were suspected. Before each chemotherapy cycle, patients underwent a physical examination with routine biochemistry work-up and blood counts.
Objective tumor responses were evaluated after the third and sixth treatment cycles by repeating the staging procedures. Computed tomography scans were not required to reconfirm response. A complete response was defined as the disappearance of all known sites of disease; a partial response was defined as a decrease of 50% or more in the sum of the products of the largest perpendicular diameters of measurable lesions, finding no new lesions, and no progression of any lesion; stable disease was defined as a decrease of less than 50% or an increase of less than 25% in the sum of the products of the largest perpendicular diameters of measurable lesions and no new lesions; and progressive disease was defined as an increase of 25% or more in the size of one or more measurable lesions, or finding a new lesion. For the evaluation of response, patients achieving complete or partial response were considered "responders," and all other patients were considered "nonresponders." Time to progression was calculated from the date of enrollment to the date of progression. Survival was calculated from the date of enrollment to the date of death or last clinical follow-up.
Methylation-Specific Polymerase Chain Reaction Analysis of 14-3-3
Ten milliliters of peripheral blood were collected in clot activator tubes, and serum was separated from cells by centrifugation. Samples were subjected to two consecutive centrifugations at 1,500 g x 10 minutes at room temperature to remove the cellular component. All samples were analyzed at the Catalan Institute of Oncology (Barcelona, Spain) for 14-3-3 methylation. DNA was extracted from 800 microliters of serum using QIAmp DNA Mini blood kit (Qiagen, Valencia, CA) and resuspended in a final volume of 50 microliters. Paired tumor and serum DNA samples from an independent group of 28 surgically resected NSCLC patients were used as controls. Tumor genomic DNA was derived from paraffin-embedded resected tumor tissue obtained by laser capture microdissection (Palm, Oberlensheim, Germany). Isolated tumor DNA was incubated with proteinase K, and DNA was extracted with phenol-chloroform and ethanol precipitation. Purified serum or tumor DNA was denatured with sodium hydroxide and modified with sodium bisulfite, which converts unmethylated but not methylated cytosines to uracil. Methylation-specific polymerase chain reaction was performed with primers specific for either methylated or the modified unmethylated DNA spanning the region between CpG dinucleotides 3 and 9 within the 14-3-3 gene (Fig 1). DNA samples were then purified with the Wizard DNA purification resin (Promega, Madison, WI), again treated with sodium hydroxide, precipitated with ethanol, and resuspended in water. Primers specific for methylated DNA [5'-GATATGGTAGTTTTTATGAAAGGCGTCG-3'(sense) and 5'-CCTCTAACCGCCCACCACG-3' (antisense)], and primers specific for unmethylated DNA [5'-GATATGGTAGTTTTTATGAAAGGTGTTGTG-3' (sense) and 5'-CCCTCTAACCACCCACCACA-3' (antisense)] yielded a 109 bp polymerase chain reaction product. The polymerase chain reaction conditions were as follows: one cycle of 95°C for 12 minutes; 45 cycles of 95°C for 30 seconds, 58°C (unmethylated reaction) or 64°C (methylated reaction) for 30 seconds, 72°C for 30 seconds; and one cycle of 72°C for 7 minutes.
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, and DNA from colorectal cell line HT29 (ATCC, Rockville, MD) was used as a negative control. Ten microliters of each 50-microliter methylation-specific amplified product was loaded directly onto nondenaturing 2% agarose gels, stained with ethidium bromide, and examined under ultraviolet illumination. Samples were scored as methylation-positive when methylated alleles were present, visualized as bands in the methylated DNA lane (Fig 2), and as methylation-negative when bands were seen only in the unmethylated DNA lane (Fig 2).
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methylation status were estimated with the Kaplan-Meier method24 and compared with the two-sided log-rank test.25 Baseline characteristics and response according to 14-3-3 methylation status were compared with either the two-sided Fisher’s exact test or the 
2 test for categoric variables and with the Student’s t test for age. The normality of age was verified with a Kolmogorov-Smirnov test. Correlation between response and other variables was assessed with a two-sided Fisher’s exact test. Univariate and multivariate logistic regression models were fitted to obtain crude and adjusted odds ratios for methylation status. The Hosmer-Lemeshow likelihood test was used to assess the goodness of fit. A univariate Cox regression analysis was used to assess the association between each potential prognostic factor and survival and time to progression. Factors found to be relatively significant (P < .1) in the univariate analysis were included in a multivariate Cox proportional hazards regression model with a stepwise procedure (both forward and backward) to evaluate the independent significance of different variables on survival. The likelihood ratio test was used to assess the goodness of fit, and the Wald’s test was used to assess the coefficient significance. The relative risk and 95% CI were calculated from the Cox model for all significant predictors of the time to event. Estimates of the time to event, with associated 95% CI were made according to the cumulative incidence method. A multivariate analysis was performed using the Cox regression model stratified by response, with 14-3-3 methylation status adjusted by ECOG PS. For all regression analyses, the assumptions of the Cox model were tested and met. Finally, as an exploratory analysis, the landmark technique, with a landmark time of 4 months, was used to evaluate the association between response and survival.26 Statistical significance was set at .05. Analyses were performed using Statistical Package for the Social Sciences (SPSS) for Windows version 11.1 (SPSS Inc, Chicago, IL) for calculations and S-plus (Version 6.1, Statistical Sciences, Seattle, WA) for plots. |
RESULTS |
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TOPABSTRACTINTRODUCTIONPATIENTS AND METHODSRESULTSDISCUSSIONAuthors' Disclosures of...REFERENCES |
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methylation–positive and 76 (66.1%) were 14-3-3 methylation–negative. Demographic and clinical characteristics were well balanced between these two groups (Table 1). Of 28 surgically resected patients used as controls, seven were methylation-positive in both tumor and serum and the remaining 21 patients were methylation-negative in both tumor and serum.
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methylation status and ECOG PS significantly correlated with survival (hazard ratios, 14-3-3 methylation–negative status, 2.07 [95% CI, 1.24 to 3.45; P = .006]; ECOG PS 1, 2.45 [95% CI, 1.39 to 4.32; P = .002]; Table 2). The stepwise multivariate Cox regression model also identified only 14-3-3 methylation status and ECOG PS as independent prognostic factors for survival.
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methylation status significantly correlated with time to progression (hazard ratio, 14-3-3 methylation–negative status, 1.59 [95% CI, 1.05 to 2.40]; P = .029). A stepwise multivariate Cox proportional hazards regression model identified only 14-3-3 methylation status as an independent prognostic factor for time to progression.
Tumor Response
All 115 patients were assessable for response. Two patients (1.7%) attained complete response; 49 (42.6%) had partial response; 27 (23.5%) had stable disease; and 37 (32.2%) had progressive disease. The logistic regression model showed that only ECOG PS correlated significantly with response (crude odds ratio, ECOG PS 0, 2.33 [95% CI, 1.01 to 5.36]; P = .05). The crude odds ratio for 14-3-3 methylation–positive status was 2.10 (95% CI, 0.96 to 4.59; P = .06).
Survival According to Tumor Response and 14-3-3 Methylation Status
As an exploratory analysis, the landmark technique was used. This analysis excluded 16 patients who had died before the landmark time of 4 months and found that in the remaining 99 patients, response was significant for improved survival (hazard ratio for nonresponders, 2.16 [95% CI, 1.29 to 3.61]; P = .03). The univariate Cox regression model showed that only 14-3-3 methylation status, ECOG PS, and response significantly correlated with survival in these 99 patients (hazard ratios, 14-3-3 methylation–negative status, 1.99 [95% CI, 1.13 to 3.51; P = .017]; ECOG PS 1, 2.17 [95% CI, 1.19 to 3.95; P = .012]; nonresponders, 2.68 [95% CI, 1.65 to 4.37; P < .001]). Moreover, a multivariate Cox proportional-hazards regression model that included response, methylation status, and ECOG PS and also allowed for their second-order interactions identified 14-3-3 methylation status, ECOG PS, and response at the selected landmark of 4 months as independent prognostic factors for survival (Table 3).
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methylation status by ECOG PS. A significant difference in risk of death was observed only in the responder group, in which the risk of death for 14-3-3 methylation–negative responders was almost five times that of methylation-positive responders (hazard ratio, 4.87 [95% CI, 1.88 to 12.61]; P = .001 by the Cox model; Table 4).
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methylation status showed that median survival for 22 14-3-3 methylation–positive responders has not been reached, whereas for 29 14-3-3 methylation–negative responders, median survival was 11.3 months (95% CI, 9.0 to 13.5; two-sided log-rank P = .001; Fig 3B). The estimated survival rate at 18 months was 64% (95% CI, 44% to 94%) for methylation-positive responders and 21% (95% CI, 9% to 47%) for methylation-negative responders (two-sided log-rank P = .017). Methylation-negative responders had a four times greater risk of death than methylation-positive responders (hazard ratio = 3.95 [95% CI, 1.57 to 9.94]; Cox P = .004). |
DISCUSSION |
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TOPABSTRACTINTRODUCTIONPATIENTS AND METHODSRESULTSDISCUSSIONAuthors' Disclosures of...REFERENCES |
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expression by methylation-dependent gene silencing has been observed in a wide variety of human cancers.7,10-15 Lack of 14-3-3 in colorectal cancer cells was shown to sensitize them to chemotherapy-induced apoptosis,5 and 14-3-3 expression was upregulated in chemoresistant pancreatic adenocarcinoma cells.33
Besides its G2-M checkpoint function, 14-3-3 has an antiapoptotic role through its inhibitory interactions with the proapoptotic protein bad. Phosphorylated bad induces apoptosis by binding to and inhibiting the antiapoptotic effects of Bcl-2. 14-3-3 sequesters phosphorylated bad in the cytosol, and then the 14-3-3/bad complex is sequestered from mitochondrial localized Bcl-xL, thus inhibiting bad-induced apoptosis.34 A specific inhibitor of 14-3-3/ligand interactions, difopein, enhances cisplatin cytotoxicity.35 In addition, BRCA1, which functions as a differential regulator of chemotherapy-induced apoptosis, has also been implicated in the induction of 14-3-3 by DNA damage, and BRCA1 seems to act synergistically with p53 to activate 14-3-3 expression.36 Decreased BRCA1 mRNA expression in a human breast cancer cell line led to greater sensitivity to cisplatin but to greater resistance to the microtubule-interfering agents paclitaxel and vincristine.37 We have observed that locally advanced NSCLC patients with the lowest BRCA1 mRNA expression obtain the maximum benefit from neoadjuvant gemcitabine-plus-cisplatin chemotherapy, whereas those with the highest levels had the poorest survival.38
Since soluble DNA in the form of chromatin fragments is released in the blood serum of cancer patients16 and DNA methylation of serum is a biomarker,21,39 we investigated 14-3-3 methylation in the serum DNA of advanced NSCLC patients treated with first-line cisplatin plus gemcitabine.
One limitation of this type of study might lie in the possible contamination of serum by DNA from mononuclear cells40; however, by performing two consecutive centrifugations, this risk was minimized in this study. We have shown for the first time that 14-3-3 is methylated in the sera of one third of NSCLC patients and is related to significantly better median survival for these patients overall. Furthermore, 14-3-3 methylation had an even greater influence on survival in responders. The risk of death for 14-3-3 methylation–negative responders was almost five times that of methylation-positive responders. Beyond recognized survival prognostic factors, such as ECOG PS, the present study sheds light on the influence of methylated 14-3-3 in serum, which can identify a subgroup of patients with a significantly better survival and help to explain the striking differences in survival among NSCLC patients.2 Translational research studies in advanced NSCLC are limited by the scarcity of available tumor biopsy tissue. The 14-3-3 serum assay circumvents the need for tumor tissue and merits further validation in prospective studies. In three ongoing Spanish Lung Cancer Group clinical trials, which include a total of more than 1,000 patients, 14-3-3 methylation status and other molecular markers are being analyzed in serum.
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Authors' Disclosures of Potential Conflicts of Interest |
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TOPABSTRACTINTRODUCTIONPATIENTS AND METHODSRESULTSDISCUSSIONAuthors' Disclosures of...REFERENCES |
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Acknowledgment |
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NOTES |
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The study reported in this article is original and was not reported or presented elsewhere at the time of submission.
Authors' disclosures of potential conflicts of interest are found at the end of this article.
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TOPABSTRACTINTRODUCTIONPATIENTS AND METHODSRESULTSDISCUSSIONAuthors' Disclosures of...REFERENCES |
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Submitted April 11, 2005; accepted September 19, 2005.
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Copyright © 2005 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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Methylation in Pretreatment Serum Circulating DNA of Cisplatin-Plus-Gemcitabine-Treated Advanced Non–Small-Cell Lung Cancer Patients Predicts Survival: The Spanish Lung Cancer Group
