ARTICLE

p53 Mutations and Survival in Stage I Non-Small-Cell Lung Cancer: Results of a Prospective Study

Steven A. Ahrendt, Yingchuan Hu, Martin Buta, Michael P. McDermott, Nicole Benoit, Stephen C. Yang, Li Wu, David Sidransky

Affiliations of authors: S. A. Ahrendt, Y. Hu, Department of Surgery, University of Rochester, Rochester, NY; M. Buta, N. Benoit, L. Wu, D. Sidransky, Department of Otolaryngology-Head and Neck Surgery, The Johns Hopkins School of Medicine, Baltimore, MD; M. P. McDermott, Department of Biostatistics, University of Rochester; S. C. Yang, Department of Surgery, The Johns Hopkins School of Medicine.

Correspondence to: Steven A. Ahrendt, M.D., Department of Surgery, University of Rochester, 601 Elmwood Ave., Rochester, NY 14642 (e-mail: steven_ahrendt{at}urmc.rochester.edu).


    ABSTRACT
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Background: The p53 gene is frequently mutated in non-small-cell lung cancer (NSCLC); however, the effect of p53 gene mutations on patient prognosis remains unclear. Therefore, we initiated a prospective study to determine the association of p53 gene mutations with survival in patients with stage I NSCLC. Methods: Tumor samples were collected prospectively from 188 patients with operable NSCLC (stages I, II, and IIIA). p53 mutations were detected by direct dideoxynucleotide sequencing and p53 GeneChip analysis. Association of clinical and pathologic variables (e.g., alcohol consumption, sex, age, pathologic stage) with mutation of the p53 gene was determined by logistic regression. Associations between p53 mutation status, clinical and pathologic variables, and survival were assessed using a Cox proportional hazards regression model. All statistical tests were two-sided. Results: p53 mutations were detected in 55% (104/188) of tumors. These mutations were associated with non-bronchoalveolar tumors, a history of alcohol consumption, and younger patient age. The risk of death was statistically significantly higher in patients with p53 mutations in their tumors (hazard ratio [HR] = 1.6, 95% confidence interval [CI] = 1.0 to 2.4; P = .049) than in patients with wild-type p53 in their tumors. Tumor stage, the presence of a p53 mutation, and increasing patient age were statistically significant predictors of patient death in the entire patient group; however, the statistically significant prognostic effect of p53 mutation was limited to patients with stage I NSCLC (stage I HR = 2.8, 95% CI = 1.4 to 5.6; stage II HR = 1.8, 95% CI = 0.74 to 4.4; and stage III HR = 0.70, 95% CI = 0.32 to 1.5). Among patients with stage I NSCLC, actuarial 4-year survival was statistically significantly higher in those with wild-type p53 than in those with mutant p53 (78% versus 52%, respectively; difference in 4-year survival = 26%, 95% CI = 6% to 46%; P = .009, log-rank test). Conclusion: Tumor p53 mutations are a statistically significant predictor of poor outcome in patients with stage I NSCLC.



    INTRODUCTION
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Lung cancer is the leading cause of cancer death among men and women in the United States (1), and the vast majority of lung cancer cases are diagnosed in current and former cigarette smokers (2). Lung cancer mortality among men has recently declined in this country, following a decrease in cigarette smoking prevalence among adult men between 1965 and 1990 (3,4). However, smoking prevalence among adults in the United States has remained stable over the past decade, suggesting that the recent decline in lung cancer mortality might be short-lived (3,4).

Approximately 80% of lung cancer cases are classified histologically as non-small-cell lung cancer (NSCLC). For patients with localized NSCLC (i.e., stage I), surgical resection alone remains the standard of care, and a definitive role for adjuvant therapy has yet to be established (5). Although 5-year survival following surgical resection of stage I NSCLC ranges from 40% to 67%, approximately 40% of these patients will die from recurrent disease (5). At present, no prognostic factors have consistently demonstrated the ability to predict those stage I NSCLC patients who are at increased risk of disease recurrence. Patients with stage I NSCLC already represent the majority of patients with operable lung cancer, and the percentage of resected patients with stage I disease may increase with the introduction of novel lung cancer screening techniques (69). Newer chemotherapeutic agents (e.g., paclitaxel, vinorelbine, and gemcitabine) in combination with cisplatin have led to higher response rates and longer survival than cisplatin alone in patients with advanced NSCLC (i.e., stages III and IV) (5). Therefore, use of these chemotherapeutic regimens could potentially improve survival in stage I NSCLC patients if a high-risk group of such patients could be identified.

The p53 tumor suppressor gene is inactivated by mutations in more than 50% of NSCLC patients (10,11). Many retrospective studies have examined the prognostic role of p53 gene mutations in NSCLC (12). However, most of these studies have been limited by small size, heterogeneous patient samples, potential selection biases, and/or insensitive p53 mutation detection techniques, leading to inconsistent results. p53 mutations have been associated with decreased survival (11,1316), no statistically significant change in survival (1722), or improved survival in NSCLC (23). A recent meta-analysis of 11 retrospective studies (12) that collectively included more than 1000 patients demonstrated a negative prognostic effect of p53 mutations in NSCLC. This decrease in survival was observed in patients with adenocarcinoma but not squamous cell cancer (12). In contrast, the first published prospective trial examining the prognostic role of p53 mutations in NSCLC demonstrated no effect of such mutations on survival in operable patients with stage II or III NSCLC (21). In 1995, we initiated a prospective study that aimed to determine the effect of p53 gene mutations on survival in patients with stage I NSCLC.


    PATIENTS AND METHODS
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Study Cohort

Between July 1995 and November 1999, tumor tissue was prospectively collected from patients (n = 245) undergoing pulmonary resection at The Johns Hopkins Hospital (Baltimore, MD), Johns Hopkins Bayview Medical Center (Baltimore, MD), and Froedtert Memorial Lutheran Hospital (Milwaukee, WI), to determine the prognostic significance of p53 gene mutations in stage I NSCLC. Patients with pathologic stage I NSCLC were the primary focus of this study. p53 mutation status was also determined for resected patients with more advanced disease (i.e., stages II and IIIA) as part of other studies (6,10,24); these patients were also included in this analysis because prior studies have demonstrated an interaction between tumor stage, p53 mutation status, and prognosis (13,14,16).

Any patient who received preoperative therapy (i.e., neoadjuvant chemotherapy and/or radiation therapy) was not eligible to participate in this study. Forty-five patients were excluded from the study because their final pathology report showed more advanced disease (i.e., stage IIIB or IV tumors, n = 16), other non-NSCLC primary lung neoplasms (n = 11), no evidence of tumor (n = 5), pulmonary metastasis from another primary site (n = 10), or multiple primary lung tumors (n = 3). Another twelve patients were excluded because they had insufficient tumor tissue available for DNA extraction. Thus, a total of 188 patients were included in this data analysis, which represents approximately 85% of eligible patients managed at these institutions during this time period.

Demographic data, such as age, race, and sex, were collected from patient interviews, review of hospital and physician charts, and The Johns Hopkins Hospital Tumor Registry. Pathologic stage was determined by using the revised International System for Staging Lung Cancer (7). Histopathologic type was assigned using the World Health Organization lung tumor classification in clinical use (25). Tumors from patients with squamous cell or adenocarcinoma of the lung who also had a history of a second primary squamous cell or adenocarcinoma at a different site underwent careful pathologic review of both cancers to exclude the presence of a pulmonary metastasis from a non-lung primary tumor. Patients in whom the possibility of metastases could not be ruled out were excluded from the study.

A history of alcohol consumption and cigarette smoking was also obtained from patient interviews, hospital and physician charts, and the Tumor Registry. Patients were classified as alcohol drinkers if they consumed one or more drinks per day on average during the 20 years prior to being diagnosed with lung cancer and were classified as nondrinkers if they consumed less than one drink per day (10). Nonsmokers were defined as patients who had smoked fewer than 100 cigarettes in their lifetime (10). All smokers had at least a 10 pack-year history of smoking.

Patient follow-up information was obtained through review of hospital and physician records, direct patient contact, the Tumor Registry, and the Social Security Death Index. Seven patients were lost to follow-up before completion of the study. This research protocol was approved by the Joint Committee on Clinical Investigation of The Johns Hopkins School of Medicine and the Institutional Review Board of the Medical College of Wisconsin with an assurance filed and approved by the U.S. Department of Health and Human Services. Written informed consent was obtained from all patients.

DNA Isolation

Primary tumor tissue was collected at the time of pulmonary resection and frozen at -80 °C after an initial gross pathologic examination. Viable portions of the primary tumor were cut into 7-µm sections, stained with hematoxylin and eosin, and examined by light microscopy to assess neoplastic cellularity. Additional 12-µm sections were cut and placed in a mixture of 1% sodium dodecyl sulfate (SDS) and proteinase K (0.5 mg/mL) to digest at 48 °C overnight. Tumors with a low neoplastic cellularity (i.e., <70% of cells were neoplastic) were further microdissected on a cryostat to remove contaminating normal cells (before proteinase K digestion). The proteinase K-digested mixture was washed twice with buffer-saturated phenol and once with chloroform/isopropanol (49 : 1). DNA was precipitated with 1 mL of cold absolute ethanol at -20 °C overnight. The DNA pellet was washed with 70% ethanol and dried under vacuum for 20 minutes. DNA was then resuspended in 5 nM ethyl EDTA (pH 8.0) at 4 °C.

p53 Sequence Analysis

The first 90 tumor samples collected were analyzed by direct dideoxynucleotide sequencing, the GeneChip p53 assay (Affymetrix, Santa Clara, CA), and automated fluorescent-based sequencing (24). This analysis demonstrated that the p53 GeneChip assay was faster and as accurate as direct sequencing for p53 sequence analysis (24). However, this technique had a sensitivity of only 80% in detecting p53 mutations in human lung cancer samples (24). After completing this study, we began analyzing the remaining tumors (n = 65) using the p53 GeneChip assay. Tumors scored as wild-type by the p53 GeneChip assay were also analyzed by direct dideoxynucleotide sequencing. Tumors with wild-type p53 (n = 84) were analyzed by using both sequencing techniques because of the limited sensitivity of each technique when used alone (Fig. 1Go) (24). All p53 mutations (n = 107) produced an amino acid substitution or truncated transcript (insertion/deletion); two known polymorphisms at codons 47 and 72 were not considered mutations. The total number of tumors analyzed does not add up to 188 because three patients had two p53 mutations in their tumors.



View larger version (25K):
[in this window]
[in a new window]
 
Fig. 1. Flowchart for p53 sequence analysis demonstrating the sensitivity of combining direct dideoxynucleotide sequencing with the p53 GeneChip assay in detecting p53 mutations in non-small-cell lung cancer (NSCLC). * = p53 mutations confirmed using GeneChip or allele-specific hybridization in 36 of 36 tumors analyzed. {dagger} = p53 mutations confirmed using direct sequencing in five of five tumors analyzed. {ddagger} = p53 mutation confirmed using allele-specific hybridization in 10 of 10 tumors analyzed. § = Three of seven tumors contained a frame-shift mutation.

 
GeneChip p53 Assay

The GeneChip p53 assay was performed as previously described (24). Briefly, exons 2–11 of the p53 gene from each tumor and the normal reference DNA (50 ng/µL human placental DNA in 10 mM Tris–HCl [pH 8.0] and 0.1 mM EDTA [pH 8.0]) were amplified as 10 separate amplicons in a single polymerase chain reaction (PCR). Each PCR contained 250 ng of genomic DNA, 5 µL of the p53 primer set (Affymetrix), 10 U of AmpliTaq Gold (PerkinElmer, Boston, MA), PCR buffer II (PerkinElmer), 2.5 mM MgCl2, and 0.2 mM of each dNTP in a final volume of 100 µL. The reaction tubes were then heated to a denaturing temperature of 95 °C for 10 minutes, followed by 35 cycles at 95 °C for 30 seconds, 60 °C for 30 seconds, and 72 °C for 45 seconds, followed by a final extension of 10 minutes at 72 °C. Amplified tumor and reference DNA (both 45 µL) were then fragmented with 0.25 U of fragmentation reagent (Affymetrix) at 25 °C for 18 minutes in 2.5 U of calf intestine alkaline phosphatase, 0.4 mM EDTA, and 0.5 mM Tris–acetate [pH 8.2], followed by heat inactivation at 95 °C for 10 minutes.

The fragmented amplicons were then 3'-end labeled with 1 µL of fluoresceinated dideoxy AMP, and 50 uL of the fragmented DNA was incubated in 100 µL of reaction buffer containing 25 U of terminal transferase (Boehringer Mannheim, Indianapolis, IN), 20 µL of TdTase buffer (Enzo Diagnostics, Farmingdale, NY), and 10 µM fluorescein-N6-ddATP at 37 °C for 45 minutes, followed by heat inactivation at 95 °C for 5 minutes. The fluorescein-labeled DNA sample was then hybridized in 0.5 mL of reaction buffer containing 6x SSPE (NaCl, NaH2PO4, EDTA), 0.05% Triton X-100, 1 mg of acetylated bovine serum albumin (BSA), and 2 nM control oligonucleotide F1 (Affymetrix) to the p53 probe array at 45 °C for 30 minutes. The probe array was washed four times with wash buffer A (3x SSPE, 0.005% Triton X-100) and then scanned by a laser HP GeneArray Scanner (Hewlett-Packard, Palo Alto, CA).

p53 mutations were detected using a mixture detection algorithm in which a sample with a wild-type p53 DNA sequence as a reference was hybridized and scanned under conditions identical to those used for DNA samples with unknown p53 sequence. The algorithm assigned a score for each site designated as containing a mutation or deletion in proportion to the intensity of binding to the mutant probe set. Missense mutations with a score between 13 and 32 were considered true p53 mutations. Mutations with borderline scores (i.e., 10–12) were confirmed by direct sequencing. These cut points were chosen per the manufacturer’s (Affymetrix) recommendations (which were based on their preliminary work on chip locations with redundant probe sets) and on our earlier work (24).

Direct Dideoxynucleotide Sequencing

A 1.8-kilobase (kb) fragment of the p53 gene (i.e., exons 5–9) was amplified from primary tumor DNA by PCR as previously described (24,26). Briefly, the PCR products were purified and directly sequenced using Amplicycle sequencing kits (Applied Biosystems, Foster City, CA) and appropriate sequencing primers (i.e., 5'-TGAGGAATCAGAGGCCTGG-3' for exon 5, 5'GTCCCCAGGCCTCTGATTCC-3' for exon 6, 5'-GAGGCAA GCAGAGGCTGG-3' for exon 7, 5'-TGAATCTGAGGCATAA CTGC-3' for exon 8, and 5'-TTATGCCTCAGATTCACTTTT-3' for exon 9). The products of the sequencing reactions were then separated by electrophoresis on a 6% denaturing polyacrylamide gel and exposed to film. The film was then exposed overnight (longer if necessary) at -80 °C and then reviewed. All p53 gene mutations were confirmed on a second sequencing gel following reamplification of the 1.8-kb fragment from tumor DNA.

Statistical Analysis

The associations between p53 mutation status and individual clinical and pathologic variables, such as age, sex, race, alcohol consumption, smoking history, tumor cell type, pathologic stage, and pathologic grade, were assessed using logistic regression. A stepwise variable selection procedure was used to build a multiple logistic regression model for p53 mutation status; a statistical significance level of 0.20 was used to determine whether a variable could be entered into, or removed from, the logistic regression model. Associations between p53 mutation status and individuals variables were quantified using odds ratios (ORs) and their 95% confidence intervals (CIs).

Survival time was determined as the time from tumor resection to death from any cause. For survivors, survival times were censored on the last date that patients were known to be alive. The associations between individual clinical and pathologic variables, such as age, sex, race, tumor cell type, pathologic stage, pathologic grade, T stage, N stage, p53 mutation status, and survival, were assessed using the Cox proportional hazards regression model. The data were consistent with the assumptions of the Cox proportional hazards regression model (27). Our primary interest was the association between p53 mutation status and survival and whether this association was dependent on pathologic stage (i.e., stage I, II, or IIIa). The interaction between p53 mutation status and pathologic stage was examined by including the appropriate main effect and interaction terms in the Cox proportional hazards model. The separate associations between p53 mutation status and survival for each of the pathologic stages were also estimated using this model. A stepwise variable selection procedure was used to build a Cox proportional hazards multiple regression model for time to death; a statistical significance level of 0.20 was used as a cutoff to determine whether a variable could be entered into, or removed from, the regression model. Associations were quantified using hazard ratios (HRs) and their 95% CIs.

The effects of different types of p53 gene mutations on survival were also analyzed in a post hoc, exploratory fashion. p53 mutations were initially classified as missense mutations (i.e., single base-pair change) or truncating mutations (i.e., deletion, insertion, splice-site-mutation, or termination codon). Missense mutations were further classified as to whether they affected residues important in DNA binding (i.e., DNA contact mutations at codons 120, 241, 248, 273, 276, 277, 280, 281, and 283) or occurred at sites known to produce marked changes in p53 protein conformation when mutated (i.e., structural mutations at codons 143, 175, 176, 179, 238, 242, 245, 249, and 282) (28,29). Log-rank tests were used to compare survival curves among the various subgroups of patients. Survival probabilities were estimated using the Kaplan–Meier method (30). All statistical tests were two-tailed.


    RESULTS
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
p53 gene mutations were detected in 55% (104/188) of the tumors. Two distinct p53 mutations were detected in each of three tumors, whereas the remaining 101 tumors contained a single mutation. Of the 107 mutations, 28 were truncating mutations and 79 were missense mutations. The strategy for detecting all mutations by direct dideoxynucleotide sequencing and the p53 GeneChip assay and the sensitivity of each technique are outlined in Fig. 1Go. The sensitivity of direct sequencing and the p53 GeneChip assay at detecting p53 mutations were 66% (95% CI = 54% to 76%) and 81% (95% CI = 65% to 91%), respectively.

Associations of clinical and pathologic variables with mutation of the p53 gene were then examined using logistic regression. Alcohol consumption, tobacco use, male sex, age, cell type, and pathologic grade were all associated with an increased risk of p53 mutation, as previously reported (Table 1Go) (10). These clinical and pathologic variables were then examined in a stepwise logistic regression model to define independent variables associated with mutation of the p53 gene (Table 2Go). A history of alcohol intake (i.e., >=1 drink per day) was independently associated with p53 mutation. In addition, p53 mutation was inversely associated with patient age. Mutation of p53 was statistically significantly less common in bronchoalveolar cancer than in all other histologic types combined (OR = 0.11, 95% CI = .02 to 0.50; P = .005).


View this table:
[in this window]
[in a new window]
 
Table 1. Association between clinical and pathologic characteristics and p53 mutations in patients (n = 188) with non-small-cell lung cancer*
 

View this table:
[in this window]
[in a new window]
 
Table 2. Logistic regression model defining independent variables associated with mutation of the p53 gene in patients with non-small-cell lung cancer*
 
The prognostic value of p53 and other clinical and pathologic variables was evaluated using single-variable Cox proportional hazards regression analysis (Table 3Go). Median follow-up among all patients was 27 months (range = 1–71 months) and among surviving patients was 41 months (range = 1–71 months). Mutation of the p53 gene was statistically significantly associated with decreased overall survival (HR = 1.56, 95% CI = 1.0 to 2.4; P = .049; Table 3Go) in the entire group of 188 patients. Four-year overall actuarial survival was statistically significantly decreased in patients with p53 mutations in their tumors compared with patients with wild-type p53 in their tumors (47% versus 62%, respectively; difference in 4-year survival = 15%, 95% CI = 0% to 30%; P = .049; Fig. 2, AGo). Patient age and pathologic tumor–node–metastasis (TNM) stage (7) were also predictive of overall patient survival. Overall survival was statistically significantly decreased in patients with lymph node metastases in N2 nodes [HR = 3.0, 95% CI = 1.8 to 5.1; P<.001 versus N0]. Sex, race, surgical procedure, margin status (i.e., positive or negative), tumor size, tumor grade, and history of prior cancer did not affect overall survival in this group of patients.


View this table:
[in this window]
[in a new window]
 
Table 3. Single variable analysis of prognostic factors in patients with non-small-cell lung cancer*
 


View larger version (20K):
[in this window]
[in a new window]
 
Fig. 2. Effect of p53 mutations on overall actuarial survival in non-small-cell lung cancer (NSCLC). A). Overall survival of patients with stage I, II, or IIIA NSCLC was statistically significantly lower in those with p53 mutant tumors than in those with p53 wild-type tumors (P = .049). B). Overall survival of patients with stage I NSCLC was statistically significantly lower in those with p53 mutant tumors than in those with p53 wild-type tumors (P = .009). Kaplan–Meier survival curves for each patient group were compared using the log-rank test; P values are two-sided. The 95% confidence intervals are shown at 2 and 4 years following surgical resection.

 
The association between p53 mutation status and survival was estimated for each of the pathologic stages separately with the Cox proportional hazards model. The association between p53 mutational status and pathologic stage was not statistically significant (P = .06). However, among patients with stage I NSCLC (n = 106), mutation of p53 was statistically significantly associated with worse patient outcome (HR = 2.6, 95% CI = 1.3 to 5.3; P = .008). Four-year overall actuarial survival in stage I NSCLC patients was statistically significantly lower in those with mutant p53 in their tumors than in those with wild-type p53 in their tumors (52% versus 78%, respectively; difference in 4-year overall survival = 26%, 95% CI = 6% to 46%; P = .009, log-rank test; Fig. 2, BGo). However, p53 mutation status was not associated with worse patient outcome in patients with stage II or IIIA NSCLC (P = .26 and P = .42, respectively).

Multiple regression analysis was performed using a Cox proportional hazards model to determine whether p53 gene mutations independently predicted survival in patients with operable NSCLC (Table 4Go). Pathologic stage (i.e., TNM stage) (7), tumor cell type, age, p53 status, and the interaction between pathologic stage and p53 status were included in the stepwise model selection process. Increasing age (HR = 1.04, 95% CI = 1.02 to 1.06; P = .001) and the interaction between p53 status and pathologic stage (P = .04) were each predictive of patient survival. p53 mutations were independently predictive of decreased survival, but only among pathologic stage I patients (stage I HR = 2.8, 95% CI = 1.4 to 5.6; stage II HR = 1.8, 95% CI = 0.74 to 4.5; stage III HR = 0.70, 95% CI = 0.32 to 1.5).


View this table:
[in this window]
[in a new window]
 
Table 4. Multiple regression analysis of prognostic factors in resected non-small-cell lung cancer*
 
The influence of the location and type of p53 mutation on actuarial survival was also analyzed. Among all pathologic stages combined (n = 188), structural mutations (n = 15) in the p53 gene had the greatest association with patient survival (4-year survival = 25% for structural p53 mutations versus 62% for wild-type p53 mutations; difference in 4-year survival = 37%, 95% CI = 8% to 66%; P = .005, log-rank test). The types of p53 mutations in the entire patient population were fairly evenly split between those mutations predicted to have a large effect on p53 structure or function (n = 55) and those predicted to have little or no effect on p53 structure or function (n = 49). Four-year overall actuarial survival was statistically significantly worse in patients whose tumors contained a truncating, structural, or DNA contact mutation than in patients whose tumors contained wild-type p53 (37% versus 62%, respectively; difference in 4-year survival = 25%, 95% CI = 6% to 44%; P = .01, log-rank test; Fig. 3, AGo). Four-year actuarial survival in patients whose tumors contained other p53 missense mutations was not statistically significantly different from that in patients whose tumors contained wild-type p53 (59% versus 62%, respectively; difference in 4-year survival = 3%, 95% CI = -17% to 23%; P = .39, log-rank test).



View larger version (27K):
[in this window]
[in a new window]
 
Fig. 3. The effect of p53 mutation type and functional implication on overall actuarial survival in non-small-cell lung cancer (NSCLC). A) Overall survival was statistically significantly lower in patients with stage I, II, or IIIA NSCLC whose tumors contained truncating p53 mutations or missense mutations in p53 residues involved in DNA contact or maintaining the conformation of the p53 protein than in those whose tumors contained wild-type p53 (P = .01). B) Overall survival was statistically significantly lower in patients with stage I NSCLC whose tumors contained truncating p53 mutations or missense mutations in residues involved in DNA contact or maintaining the conformation of the p53 protein than in those whose tumors contained wild-type p53 (P = .001). Kaplan–Meier survival curves were compared using the log-rank test; P values are two-sided. The 95% confidence intervals are shown at 2 and 4 years following surgical resection. Other mutations include all missense mutations at p53 residues not involved in DNA contact or not known to play a major role in maintaining the conformation of the p53 protein.

 
The effect of p53 gene mutation type was also examined in stage I NSCLC patients specifically. Both truncating mutations and structural mutations were associated with statistically significantly lower patient survival than wild-type p53. When mutations in stage I NSCLC patients were subdivided into those with (e.g., truncating, structural, or DNA contact) and without a predicted effect on p53 function or structure, patients with the former type of p53 mutation had statistically significantly worse 4-year overall actuarial survival than patients with wild-type p53 (35% versus 78%, respectively; difference in 4-year survival = 43%, 95% CI = 18% to 66%; P = .001, log-rank test; Fig. 3, BGo). Patients whose tumors had the latter type of p53 mutation did not have a statistically significantly worse 4-year overall actuarial survival than patients with wild-type p53 (66% versus 78%; difference in 4-year survival = 12%, 95% CI = -9% to 39%; P = .16, log-rank test).


    DISCUSSION
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
p53 mutations are present in the tumors of more than 50% of patients with NSCLC and occur with equal frequency among all pathologic stages of the disease. Moreover, p53 mutations are more prevalent in younger lung cancer patients, are common in all histologic types of NSCLC with the exception of bronchoalveolar cancer, and are associated with alcohol and tobacco use. Our findings, from a large prospective study, demonstrate that mutation of the p53 gene is a statistically significant predictor of poor outcome in patients with NSCLC. The increased risk of death associated with p53 mutation appears to be greatest in patients with stage I disease. In addition, the clinical behavior of NSCLC tumors that have a p53 gene mutation appeared to vary with the type and location of the specific mutation.

Mutation of the p53 gene is a common event in most human cancers (31). In NSCLC, p53 mutations have been linked to cigarette smoking and to certain tobacco carcinogens (10,32). In this study, p53 mutations occurred with twofold greater frequency in smokers than in nonsmokers, although this association did not reach statistical significance, possibly because of the small number of nonsmokers in our cohort (10). Benzopyrenediolepoxide (BPDE) and other tobacco carcinogens have been shown to bind preferentially to the p53 mutation hotspots present in lung cancer, resulting in an increased frequency of G to T transversions in this disease (3234). In addition, the p53 mutational spectrum in smokers differs from that in nonsmokers, which is dominated by G to A transitions (34).

p53 mutations have also been shown to be associated with alcohol consumption, younger age, and all non-bronchoalveolar histologic subtypes of NSCLC (10). In addition, alcohol consumption has been linked with p53 mutations in head and neck squamous cell cancer (35). Interestingly, the associations between alcohol consumption and p53 mutations in lung and head and neck cancer have been reported only following joint exposure to cigarette smoke and alcohol. Alcohol and acetaldehyde have been shown to increase BPDE adduct formation, and acetaldehyde has been shown to inhibit the activity of O6-methylguanine DNA methyltransferase (MGMT) (36,37). MGMT is inactivated through promoter hypermethylation in 28% of NSCLCs, and MGMT promoter hypermethylation results in an increase in G to A transition mutations of p53 in NSCLC (38). Other factors have also been linked with p53 mutations in NSCLC. For example, p53 mutations have been found more frequently among men than among women (11), and a similar trend was observed in this study. However, men are heavier smokers than women, and tobacco use has rarely been controlled for when reporting the association between sex and p53 mutations in lung cancer. In the present study, sex was not an independent predictor of p53 mutations in the multiple logistic regression analysis.

More than 60 studies have been published examining the prognostic role of p53 alterations in NSCLC (12). Many of these studies used immunohistochemical staining to detect the p53 protein. However, this technique correlates poorly (with a 67% concordance rate) with mutation analysis (15,19) and, in a recent meta-analysis, p53 protein overexpression was associated with a smaller effect on survival than was mutation of the gene (12,15,19). The identification of p53 gene mutations in clinical samples is generally limited by assay sensitivity. Undetected mutations could result in an underestimation of the effect of p53 mutations on survival. The most commonly used approach for mutation detection in prior studies has been single-strand conformation polymorphism (SSCP) for screening, followed by direct dideoxynucleotide sequencing to specifically identify any mutations (12). SSCP is less sensitive than direct dideoxynucleotide sequencing, failing to identify mutations in 14%–38% of tumors in which p53 mutations were detected by the latter technique (39,40). Fluorescence-based automated sequencing and gel-based direct sequencing are also commonly used, but both are less sensitive than the p53 GeneChip assay at detecting missense mutations (24,41,42). The p53 GeneChip assay is, however, unable to accurately detect insertion or deletion mutations (24). In our experience, 18% of NSCLCs that are scored as wild-type p53 tumors by the p53 GeneChip assay had a p53 mutation detected by direct dideoxynucleotide sequencing (24). Our ongoing experience with this method continues to support the use of a second complementary technique to accurately determine p53 status in clinical samples.

Several large retrospective studies (11,1315) and a recent meta-analysis (12) have reported that p53 mutation is a marker of poor prognosis in NSCLC. However, the conclusions of these studies are limited by the selection biases inherent in retrospective studies, and the effect of p53 mutations on survival remains controversial. Schiller et al. (21) prospectively examined the association between p53 gene mutations and survival in stage II and IIIA NSCLC patients undergoing postoperative adjuvant therapy in the Eastern Cooperative Oncology Group Trial E3590. That study demonstrated no prognostic role for p53 gene mutations in NSCLC, although the study did not include patients with stage I NSCLC tumors. Nevertheless, the results of that trial are consistent with our study, which demonstrates a prognostic role for p53 gene mutation in stage I but not in stage II or IIIA NSCLC. Skaug et al. (11) recently reported that mutation of p53 was associated with a statistically significant reduction in lung cancer-free survival in a cohort of 148 patients. However, the effect of p53 gene mutation on overall survival was not reported, and it is not clear whether p53 mutations predicted survival independent of pathologic stage (11). The present study suggests that p53 mutation is associated with a higher risk of eventual patient death in stage I NSCLC patients.

Cancer progression models describe the accumulation of genetic abnormalities as tumors advance from dysplasia through carcinoma in situ to metastatic cancer (43,44). Advanced malignancies continue to evolve subclones with novel mutations/deletions and varying ploidy, metastatic potential, and sensitivity to treatment. As tumors progress and become increasingly complex, each single genetic abnormality may be less likely to define tumor behavior. In a recent, large, prospective study, Nelson et al. (45) demonstrated that K-ras mutations predicted poor survival in patients with stage I NSCLC but not in patients with more advanced NSCLC. Moreover, abnormal p53 expression occurs early in lung cancer progression, but this and other studies (14,21,46) suggest that p53 mutations affect survival only in stage I NSCLC and not in more advanced NSCLC.

The majority of p53 mutations occur at residues that are at or near the protein–DNA interface. Cho et al. (28) have defined several classes of p53 gene mutations based on the position and function of the amino acid encoded by the mutated codon. One class of missense mutations involves residues that contact DNA. Mutations at these residues inactivate p53 by eliminating critical DNA contacts (28). A second class of mutations involves residues important for the stable folding of the core domain. Mutations at these residues, including those involved in binding of the zinc cofactor, lead to unfolding or denaturing of the p53 protein (28). Quantitative analysis of both DNA-binding affinity and residual protein folding for specific p53 mutants may be useful in predicting in vivo tumor behavior and response to pharmacologic rescue of p53 function (47).

Missense mutations at different codons have different biochemical properties, transform cells with different efficiencies in vitro, and may have different effects on tumor behavior in vivo (48). Mutations that denature or strongly destabilize the p53 protein presumably have a greater effect on critical p53 tumor suppressor functions, such as apoptosis, growth suppression, p21 transactivation, or spindle checkpoint control, and are expected to be more refractory to pharmacologic reactivation than mutations that do not affect those p53 functions (49). In the present study, mutations predicted to affect the p53 protein (i.e., truncating and structural mutations) or abolish p53 protein DNA binding (i.e., DNA contact) were associated with a greater negative effect on patient survival, whereas missense mutations in other regions had little effect on survival. These results are similar to those of Skaug et al. (11), who demonstrated that mutations in the L2 loop and the zinc-binding residues and severe flexible and contact mutants (mutations at codons 172, 173, 175, 176, 179, 181, 238, 245, 248, 267, and 282) were all associated with diminished lung cancer-free survival in patients with NSCLC. These latter two types of mutations are similar to the DNA structural and contact mutations, respectively, observed in our study. Complete sequence analysis with the identification and functional classification of specific p53 mutations may be critical in determining the clinical significance of these types of p53 mutations in NSCLC.

In summary, p53 mutations are an independent predictor of decreased patient survival in operable NSCLC, and a prognostic role for p53 appears to be limited to patients with stage I disease. However, patients with stage I NSCLC represent the largest group of patients with operable lung cancer. At present, no adjuvant therapy has a documented survival benefit over surgical resection alone in this group of patients (5). The presence of p53 gene mutations identifies a large subgroup of stage I NSCLC patients at increased risk of treatment failure and/or death. Although many chemotherapeutic agents produce poor responses in p53 mutant tumors, anti-microtubule agents appear to produce responses independent of p53 status (5052). Moreover, novel biologic approaches can specifically target cells overexpressing mutant p53 (53,54). Therefore, further study of targeted adjuvant therapy in this high-risk population is warranted.


    NOTES
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Supported by Public Health Service grant K08 CA76452-01 from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services (to S. A. Ahrendt) and grant CA-58184 from the National Cancer Institute–Specialized Programs of Research Excellence (SPOREs) for lung research (to D. Sidransky).


    REFERENCES
 Top
 Notes
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 

1 Cancer: basic facts. Cancer facts and figures 2001. American Cancer Society; 2001. p. 2–11.

2 Shopland DR, Eyre HJ, Pechacek TF. Smoking-attributable cancer mortality in 1991: is lung cancer now the leading cause of death among smokers in the United States? J Natl Cancer Inst 1991;83:1142–8.[Abstract]

3 Tobacco use. Cancer facts and figures 2001. American Cancer Society; 2001. p. 29–32.

4 National Center for Health Statistics (NCHS). Health, United States, 2000 with Adolescent Health Chartbook. Hyattsville (MD): NCHS; 2000.

5 Hoffman PC, Mauer AM, Vokes EE. Lung cancer. Lancet 2000;355:479–85.[CrossRef][ISI][Medline]

6 Ahrendt SA, Chow JT, Xu LH, Yang SC, Eisenberger CE, Esteller M, et al. Molecular detection of tumor cells in bronchoalveolar lavage fluid from patients with early-stage lung cancer. J Natl Cancer Inst 1999;91:332–9.[Abstract/Free Full Text]

7 Mountain CF. Revisions in the international system for staging lung cancer. Chest 1997;111:1710–7.[Abstract/Free Full Text]

8 Palmisano WA, Divine KK, Saccomanno G, Gilliland FD, Baylin SB, Herman JG, et al. Predicting lung cancer by detecting aberrant promoter methylation in sputum. Cancer Res 2000;60:5954–8.[Abstract/Free Full Text]

9 Fliss MS, Usadel H, Caballero OL, Wu L, Buta MR, Eleff SM, et al. Facile detection of mitochondrial DNA mutations in tumor and bodily fluids. Science 2000;287:2017–9.[Abstract/Free Full Text]

10 Ahrendt SA, Chow JT, Yang SC, Wu L, Zhang MJ, Jen J, et al. Cigarette smoking and alcohol consumption increase the frequency of p53 gene mutations in non-small cell lung cancer. Cancer Res 2000;60:3155–9.[Abstract/Free Full Text]

11 Skaug V, Ryberg D, Kure EH, Arab MO, Stangeland L, Myking AO, et al. p53 mutations in defined structural and functional domains are related to poor clinical outcome in non-small cell lung cancer patients. Clin Cancer Res 2000;6:1031–7.[Abstract/Free Full Text]

12 Mitsudomi T, Hamajima N, Ogawa M, Takahashi T. Prognostic significance of p53 alterations in patients with non-small cell lung cancer: a meta-analysis. Clin Cancer Res 2000;6:4055–63.[Abstract/Free Full Text]

13 Horio Y, Takahashi T, Kuroishi T, Hibi K, Suyama M, Niimi T, et al. Prognostic significance of p53 mutations and 3p deletions in primary resected non-small cell lung cancer. Cancer Res 1993;53:1–4.[Abstract]

14 Fukuyama Y, Mitsudomi T, Sugio K, Ishida T, Akazawa K, Sugimachi K. K-ras and p53 mutations are an independent unfavourable prognostic indicator in patients with non-small-cell lung cancer. Br J Cancer 1997;75:1125–30.[ISI][Medline]

15 Tomizawa Y, Kohno T, Fujita T, Kiyama M, Saito R, Noguchi M, et al. Correlation between the status of the p53 gene and survival in patients with stage I non-small cell lung carcinoma. Oncogene 1999;18:1007–14.[CrossRef][ISI][Medline]

16 Mitsudomi T, Oyama T, Kusano T, Osaki T, Nakanishi R, Shrakusa T. Mutations of the p53 gene as a predictor of poor prognosis in patients with non-small-cell lung cancer. J Natl Cancer Inst 1993;85:2018–23.[Abstract]

17 Mitsudomi T, Oyama T, Nishida K, Ogami A, Osaki T, Nakanishi R, et al. p53 nuclear immunostaining and gene mutations in non-small cell lung cancer and their effects on patient survival. Ann Oncol 1995;6:S9–S13.[Medline]

18 de Anta JM, Jassem E, Rosell R, Martinez-Roca M, Jassem J, Martinez-Lopez E, et al. TP53 mutational pattern in Spanish and Polish non-small cell lung cancer patients: null mutations are associated with poor prognosis. Oncogene 1997;15:2951–8.[CrossRef][ISI][Medline]

19 Carbone DP, Mitsudomi T, Chiba I, Piantadosi S, Rusch V, Nowak JA, et al. p53 immunostaining positivity is associated with reduced survival and is imperfectly correlated with gene mutations in resected non-small cell lung cancer. A preliminary report of LCSG 871. Chest 1994;106;(6 Suppl):377S–81S.[Abstract]

20 Sioris T, Husgafvel-Pursiainen K, Karjalainen A, Anttila S, Kannio A, Salo JA, et al. Survival in operable non-small-cell lung cancer: role of p53 mutations, tobacco smoking and asbestos exposure. Int J Cancer 2000;86:590–4.[CrossRef][ISI][Medline]

21 Schiller JH, Adak S, Feins RH, Keller SM, Fry WA, Livingston RB, et al. Lack of prognostic significance of p53 and K-ras mutations in primary resected non-small-cell lung cancer on E4592: a laboratory ancillary study on an Eastern Cooperative Oncology Group prospective randomized trial of postoperative adjuvant therapy. J Clin Oncol 2001;19:448–57.[Abstract/Free Full Text]

22 Huang C, Taki T, Adachi M, Konishi T, Higashiyama M, Miyake M. Mutations in exon 7 and 8 of p53 as poor prognostic factors in patients with non-small cell lung cancer. Oncogene 1998;16:2469–77.[CrossRef][ISI][Medline]

23 Top B, Mooi W, Klaver S, Boerrigter L, Wisman P, Elbers H, et al. Comparative analysis of p53 gene mutations and protein accumulation in human non-small cell lung cancer. Int J Cancer 1995;64:83–91.[ISI][Medline]

24 Ahrendt SA, Halachmi S, Chow JT, Wu L, Halachmi N, Yang SC, et al. Rapid p53 sequence analysis using an oligonucleotide probe array in primary lung cancer. Proc Natl Acad Sci U S A 1999;96:7382–7.[Abstract/Free Full Text]

25 The World Health Organization histological typing of lung tumours. Second edition. Am J Clin Pathol 1982;77:123–36.[ISI][Medline]

26 Sidransky D, Von Eschenbach A, Tsai Y, Jones P, Summerhayes I, Marshall F, et al. Identification of p53 gene mutations in bladder cancers and urine samples. Science 1991;252:706–9.[ISI][Medline]

27 Kalbfleisch J, Prentice R. The statistical analysis of failure time data. New York (NY): Wiley; 1980.

28 Cho Y, Gorina S, Jeffrey PD, Pavletich NP. Crystal structure of a p53 tumor suppressor-DNA complex: understanding tumorigenic mutations. Science 1994;265:346–55.[ISI][Medline]

29 Borresen AL, Anderson TI, Eyfjord JE, Cornelis RS, Thorlacius S, Borg A, et al. TP53 mutations and breast cancer prognosis: particularly poor survival rates for cases with mutations in the zinc-binding domains. Genes Chromosomes Cancer 1995;14:71–5.[ISI][Medline]

30 Meier P, Kaplan E. Nonparametric estimation from incomplete observations. J Am Stat Assoc 1958;53:457–81.[ISI]

31 Greenblatt MS, Bennett WP, Hollstein M, Harris CC. Mutations in the p53 tumor suppressor gene: clues to cancer etiology defined carcinogens. Cancer Res 1994;54:4855–78.[ISI][Medline]

32 Denissenko MF, Pao A, Tang M, Pfeifer GP. Preferential formation of benzo[a]pyrene adducts at lung cancer mutational hotspots in p53. Science 1996;274:430–2.[Abstract/Free Full Text]

33 Smith LE, Denissenko MF, Bennett WP, Li H, Amin S, Tang M, et al. Targeting of lung cancer mutational hotspots by polycyclic aromatic hydrocarbons. J Natl Cancer Inst 2000;92:803–11.[Abstract/Free Full Text]

34 Hainaut P, Pfeifer GP. Patterns of p53 G->T transversions in lung cancers reflect the primary mutagenic signature of DNA-damage by tobacco smoke. Carcinogenesis 2001;22:367–74.[Abstract/Free Full Text]

35 Brennan JA, Boyle JO, Koch WM, Goodman SN, Hruban HR, Eby YJ, et al. Association between cigarette smoking and mutation of the p53 gene in squamous-cell carcinoma of the head and neck. N Engl J Med 1995;332:712–7.[Abstract/Free Full Text]

36 Grafstrom RC, Dybukt JM, Sundqvist K, Atzori L, Nielson I, Curren RD, et al. Pathobiological effects of acetaldehyde in cultured human epithelial cells and fibroblasts. Carcinogenesis 1994;15:985–90.[Abstract]

37 Barnes SL, Singletary KW, Frey R. Ethanol and acetaldehyde enhance benzo[a]pyrene-DNA adduct formation in human mammary epithelial cells. Carcinogenesis 2000;21:2123–8.[Free Full Text]

38 Wolf P, Hu YC, Doffek K, Sidransky D, Ahrendt SA. O(6)-Methylguanine-DNA methyltransferase promoter hypermethylation shifts the p53 mutational spectrum in non-small cell lung cancer. Cancer Res 2001;61:8113–7.[Abstract/Free Full Text]

39 Tolbert DM, Noffsinger AE, Miller MA, DeVoe GW, Stemmermann GN, Macdonald JS, et al. p53 immunoreactivity and single-strand conformational polymorphism analysis often fail to predict p53 mutational status. Mod Pathol 1999;12:54–60.[ISI][Medline]

40 Meinhold-Heerlein I, Ninci E, Ikenberg H, Brandstetter T, Ihling C, Schwenk I, et al. Evaluation of methods to detect p53 mutations in ovarian cancer. Oncology 2001;60:176–88.[CrossRef][ISI][Medline]

41 Wen WH, Bernstein L, Lescallett J, Beazer-Barclay Y, Sullivan-Halley J, White M, et al. Comparison of TP53 mutations identified by oligonucleotide microarray and conventional DNA sequence analysis. Cancer Res 2000;60:2716–22.[Abstract/Free Full Text]

42 Wikman FP, Lu ML, Thykjaer T, Olesen SH, Andersen LD, Cordon-Cardo C, et al. Evaluation of the performance of a p53 sequencing microarray chip using 140 previously sequenced bladder tumor samples. Clin Chem 2000;46:1555–61.[Abstract/Free Full Text]

43 Wistuba II, Lam S, Behrens C, Virmani AK, Fong KM, LeRiche J, et al. Molecular damage in the bronchial epithelium of current and former smokers. J Natl Cancer Inst 1997;89:1366–72.[Abstract/Free Full Text]

44 Fearon E, Vogelstein B. A genetic model for colorectal tumorigenesis. Cell 1990;61:759–67.[ISI][Medline]

45 Nelson HH, Christiani DC, Mark EJ, Wiencke JK, Wain JC, Kelsey KT. Implications and prognostic value of K-ras mutation for early-stage lung cancer in women. J Natl Cancer Inst 1999;91:2032–8.[Abstract/Free Full Text]

46 Rusch V, Klimstra D, Linkov I, Dmitrovsky E. Aberrant expression of p53 or the epidermal growth factor receptor is frequent in early bronchial neoplasia, and coexpression precedes squamous cell carcinoma development. Cancer Res 1995;55:1365–72.[Abstract]

47 Bullock A, Henckel J, Fersht A. Quantitative analysis of residual folding and DNA binding in mutant p53 core domain: definition of mutant states for rescue in cancer therapy. Oncogene 2000;19:1245–56.[CrossRef][ISI][Medline]

48 Hinds PW, Finlay CA, Quartin RS, Baker SJ, Fearon ER, Vogelstein B, et al. Mutant p53 DNA clones from human colon carcinomas cooperate with ras in transforming primary rat cells: a comparison of the "hot spot" mutant phenotypes. Cell Growth Differ 1990;1:571–80.[Abstract]

49 Sigal A, Rotter V. Oncogenic mutations of the p53 tumor suppressor: the demons of the guardian of the genome. Cancer Res 2000;60:6788–93.[Abstract/Free Full Text]

50 King TC, Akerley W, Fan AC, Moore T, Mangray S, Hsiu Chen M, et al. p53 mutations do not predict response to paclitaxel in metastatic nonsmall cell lung carcinoma. Cancer 2000;89:769–73.[CrossRef][ISI][Medline]

51 Natsume T, Kobayashi M, Fujimoto S. Association of p53 gene mutations with sensitivity to TZT-1027 in patients with clinical lung and renal carcinoma. Cancer 2001;92:386–94.[CrossRef][ISI][Medline]

52 Bunz F, Hwang PM, Torrance C, Waldman T, Zhang Y, Dillehay L, et al. Disruption of p53 in human cancer cells alters the responses to therapeutic agents. J Clin Invest 1999;104:263–9.[Abstract/Free Full Text]

53 DaCosta L, Jen J, He TC, Chan TA, Kinzler KW, Vogelstein B. Converting cancer genes into killer genes. Proc Natl Acad Sci U S A 1996;93:4192–6.[Abstract/Free Full Text]

54 Harris CC. Structure and function of the p53 tumor suppressor gene: clues for rational cancer therapeutic strategies. J Natl Cancer Inst 1996;88:1442–55.[Abstract/Free Full Text]

Manuscript received October 21, 2002; revised April 10, 2003; accepted April 28, 2003.


This article has been cited by other articles in HighWire Press-hosted journals:


             
Copyright © 2003 Oxford University Press (unless otherwise stated)
Oxford University Press Privacy Policy and Legal Statement