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Journal of Clinical Oncology, Vol 24, No 10 (April 1), 2006: pp. 1627-1632 © 2006 American Society of Clinical Oncology. DOI: 10.1200/JCO.2005.04.0402 Survival Prediction in Patients With Glioblastoma Multiforme by Human Telomerase Genetic Variation
From the Departments of Epidemiology, Pathology, Biostatistics and Applied Mathematics, Radiation Oncology, Neuro-Oncology, and Neurosurgery, The University of Texas M.D. Anderson Cancer Center; and Department of Pediatrics, Baylor College of Medicine, Houston, TX Address reprint requests to Melissa L. Bondy, PhD, Department of Epidemiology, Unit 1340, The University of Texas M.D. Anderson Cancer Center, PO Box 301439, Houston, TX 77230-1439; e-mail: mbondy{at}mdanderson.org
PURPOSE: Glioblastoma multiforme (GBM) is the most common and aggressive glioma with the poorest survival. Use of biomarkers for screening patients with GBM may be used to modify treatments and improve outcomes. The level of human telomerase (hTERT) expression is an independent predictor of outcome of many cancers, and a functional variant of hTERT MNS16A (shorter tandem repeats or short [S] allele) is associated with increased hTERT mRNA expression. We investigated whether hTERT MNS16A variant genotype predicted survival in GBM patients. PATIENTS AND METHODS: We genotyped hTERT MNS16A in 299 GBM patients using polymerase chain reaction and determined hTERT genotype by classifying the DNA band of 243 or 272 base pairs (bp) as S allele and 302 or 333 bp as long (L) allele. We compared overall survival using Kaplan-Meier estimates and equality of survival distributions using the log-rank test, and we computed univariate and multivariate Cox proportional hazards models to estimate the effects of selected variables. RESULTS: Overall survival differed significantly by hTERT MNS16A genotype, with median survivals of 25.1, 14.7, and 14.6 months for the SS, SL, and LL genotypes, respectively. Compared with the SS genotype, the hazard ratios for the SL and LL genotypes were 1.69 and 1.87, respectively, after adjustment for other factors. Multivariate Cox regression analysis showed an independent statistically significant association between the hTERT MNS16A variant genotype and outcome. CONCLUSION: A functional hTERT MNS16A genotype is a potential biomarker for assessment of survival outcome of GBM. Larger studies are needed to verify these findings.
Gliomas account for approximately 78% of the 18,400 estimated new cases of primary malignant brain and CNS tumors diagnosed annually in the United States.1 Half of all gliomas are glioblastoma multiforme (GBM) or grade 4 infiltrating astrocytoma, as classified by WHO. GBM is the most aggressive glioma clinically, with a median survival time of approximately 12 to 15 months, and the standard treatment is typically a combination of surgery and radiotherapy or adjuvant chemotherapy.2 Surgical resection of GBM is required for a definitive histopathologic diagnosis, and gross total resection, with removal of 98% or more of the tumor, may result in substantially increased survival.3 Postsurgical irradiation is the most effective currently available treatment for improving survival in patients with GBM, and recently, the addition of concurrent chemotherapy with radiation followed by adjuvant chemotherapy has been shown to improve survival.2 However, established prognostic factors, such as age at diagnosis, histologic characteristics, extent of surgery, and Karnofsky performance status score, inadequately predict the outcome of GBM.4-8 With the goal of tailored therapy, it is important to identify and evaluate biomarkers for screening patients who may benefit from more aggressive treatments. In particular, recent research efforts have focused on novel molecular alterations. Investigators have found that gene amplification of epidermal growth factor receptor, genetic losses on chromosome 10, and mutations in the tumor suppressors TP53 and PTEN are common events in patients with GBM,9-13 suggesting that genetic instability plays an important role in this disease. Genetic instability is a driving force for transformation of normal cells to a highly malignant phenotype during tumorigenesis, and the events associated with unlimited replicating potential and cell immortalization are major factors essential for carcinogenesis.14 Telomeres are structures that cap the distal ends of chromosomes and function to prevent chromosome degradation, end-to-end fusions, rearrangements, and chromosome loss.15 Telomerase is a holoenzyme that maintains the telomeres; the activity is undetectable in most normal human somatic cells with the exception of peripheral, cord blood, and bone marrow leukocytes.16-18 The existence of detectable telomerase expression in almost all types of human cancers suggests that enhanced telomerase expression is critical for cell growth during tumorigenesis.19,20 The levels of human telomerase (hTERT) mRNA or protein expression have been evaluated in many primary tumors, including neuroblastoma and gastric, breast, colon, cervical, and lung cancers.21-26 The hTERT gene has been recognized as one of the most common tumor markers. The hTERT gene, which is located at chromosome 5p15.33, has 16 exons.27,28 In a previously published study, we identified the MNS16A variable number of tandem repeat polymorphism in the downstream region of the hTERT gene locus.29 Four different alleles of MNS16A were found in a previous population, and we classified them as either short (S) or long (L) alleles on the basis of their functionality. When compared with the MNS16A L allele, we found that the MNS16A S allele was associated with increased expression of hTERT mRNA in all telomerase-positive cell lines and primary lung cancer tissues, suggesting that the hTERT genetic variation defined by MNS16A is an indicator potentially representing hTERT mRNA expression level. Because hTERT has been shown to have potential as a therapeutic target in pharmacogenomic studies30-32 and because the hTERT MNS16A variation affects hTERT mRNA expression, we hypothesized that the hTERT MNS16A variant genotype is associated with survival outcome of GBM and tested the association in 299 patients with GBM.
Study Population The population for this study was a subset of patients with GBM from a study of primary malignant glioma patients (n = 2,113) consecutively diagnosed and treated at The University of Texas M.D. Anderson Cancer Center (Houston, TX). The patients participated in an ongoing epidemiologic study of malignant gliomas (R01CA70917) from 1994 to 2003.33 We selected GBM patients who had complete medical records with an available DNA sample isolated from peripheral-blood mononuclear cells and who had provided their written informed consent to participate. The research protocol was approved by the M.D. Anderson Cancer Center Institutional Review Board. To achieve a homogenous population, we reviewed the patients' medical records and abstracted data, including the patient characteristics at diagnosis, treatments (extent of surgery, radiotherapy, and adjuvant chemotherapy), and date of death or last contact. We observed the patients from the earliest date of registration at M.D. Anderson Cancer Center in July 1994 to the date of last contact or death through October 2003. The follow-up periods ranged from 1 month to 5.5 years. We included only non-Hispanic white patients in this analysis to eliminate the potential genetic effect from different ethnic backgrounds. GBM patients who experienced recurrence or progression and patients whose tumor evolved from a lower grade glioma were excluded, and we only included patients with a new pathologic diagnosis at the M.D. Anderson Cancer Center. All patients received surgery and radiotherapy, and some patients were treated with adjuvant chemotherapy. Our final study population consisted of 299 GBM patients whose ages at diagnosis ranged from 20 to 65 years (mean age, 49.9 years).
Extraction of DNA, Genotyping of MNS16A, and Definition of the hTERT MNS16A Genotypes Polymerase chain reaction (PCR) was used to genotype the MNS16A variable number of tandem repeat polymorphism with the primer set as reported.29 The forward primer sequence was 5'-AGGATTCTGATCTCTGAAGGGTG-3', and the reverse primer sequence was 5'-TCTGCCTGAGGAAGGACGTATG-3'. Ten microliters of a PCR reaction mixture were assembled with 40 ng of genomic DNA, 2.5 pmol of each primer, 1x PCR buffer (50 mmol/L KCl, 10 mmol/L Tris-HCl, pH 8.3), 1.5 mmol/L of MgCl2, 0.1 mmol/L of each deoxynucleoside triphosphate, and 1 U of Taq polymerase (Denville Scientific Inc, Metuchen, NJ). PCR reaction was performed with the use of a PTC-200 DNA Engine (Peltier Thermal Cycler; MJ Research, Watertown, MA). The amplification procedure consisted of an initial denaturing step for 5 minutes at 95°C followed by 35 cycles for 30 seconds at 95°C, 45 seconds at 60°C, and 1 minute at 72°C, as well as a final extension step for 10 minutes at 72°C. The PCR products were visualized on a 2% agarose gel containing 0.25 µg/mL of ethidium bromide and were photographed. The resulting genotypes could be easily distinguished as different combinations of 243 base pairs (bp), 272 bp, 302 bp, and 333 bp (Fig 1). The DNA bands with 243 bp or 272 bp were classified as S allele, whereas those with 302 bp or 333 bp were classified as L allele29; the hTERT MNS16A genotypes were defined as SS, SL, and LL. Approximately 10% of the samples were randomly selected to repeat the genotyping, and the results were 100% concordant with previous results.
Statistical Analysis The age at diagnosis, sex, surgery treatment, and chemotherapy were considered as the variables observed in this study. Because survival time was calculated from the date of first visit (registration) at the M.D. Anderson Cancer Center, we also considered the interval between registration date and the date of surgery treatments as a covariate in statistical analysis. Almost half of the patients (52.2%) were missing Karnofsky performance status scores; therefore, we did not include this variable in the analysis because of the large amount of missing data. The major variable to be tested for the association with survival outcome of GBM patients in this study was the hTERT MNS16A variant genotype that is not associated with patients' performance status.
The patients' age at diagnosis was categorized into two groups according to the mean age (< 50 and The overall survival time was calculated from the date of registration at the M.D. Anderson Cancer Center to the date of last contact or date of death. Patients who were still alive at last contact were considered as a censored event in analysis. Overall survival among three hTERT genotype groups was analyzed by using the Kaplan-Meier estimates, and the log-rank test was used to test for equality of the survival distributions stratified by the hTERT MNS16A genotype. We conducted univariate analysis, and multivariate Cox proportional hazards models were calculated to estimate the effect of hTERT MNS16A genotype on survival in the presence of other known prognostic factors.33,34 Both age at diagnosis and the time interval between registration and diagnosis date (pathologic confirmation of disease) were treated as the numeric covariates in the Cox model. To examine the assumption of proportional hazards in a Cox regression model, the addition of a time-dependent variable in the model35 was used, and the assumption was met. Hazard ratios (HRs) and their corresponding 95% CIs were calculated with adjustment for selected factors in the same model. P values were determined by using two-sided tests, and P < .05 was considered statistically significant. All statistical analyses were performed using the SAS software program (version 8.2; SAS Institute, Inc, Cary, NC).
The distribution of the hTERT MNS16A genotype and demographic and clinical characteristics in the 299 eligible patients with GBM are listed in Table 1. All of the patients were white, and their mean age (± standard deviation) at diagnosis was 49.9 ± 9.9 years. There were 182 male patients (60.9%) and 117 female patients (39.1%). The frequency distribution of the hTERT MNS16A genotype in this population of GBM patients was as follows: SS, 11.4%; SL, 44.1%; and LL, 44.5%. These distribution rates are similar to what we found in a population of patients with non–small-cell lung cancer (SS, 10.9%; SL, 45.0%; and LL, 44.1%). Overall, there were no statistically significant differences in the distribution of the hTERT MNS16A genotype by age, sex, or treatment, including the extent of surgery and chemotherapy. However, the distribution of this genotype was significant different by vital status at last contact, with more hTERT SS genotype patients who were still alive compared with SL or LL genotype patients. The Kaplan-Meier survival curve for the hTERT MNS16A genotype is shown in Figure 2. As shown in Table 2, the median survival duration differed significantly among patients with different hTERT MNS16A genotypes; specifically, the median duration was 25.1 months (95% CI, 14.9 to 30.9 months) for the SS genotype patients, 14.7 months (95% CI, 13.9 to 18.8 months) for the SL genotype patients, and 14.6 months (95% CI, 12.6 to 17.4 months) for the LL genotype patients (P = .039).
We used the univariate Cox proportional hazards model to calculate the HR for age at diagnosis, sex, treatment, and hTERT MNS16A genotype. We also performed a multivariate analysis with corresponding adjustments for variables with potential confounding effects. The results are listed in Table 3. The adjusted HR of age at diagnosis for a 30-year increase would be 2.16 (95% CI, 1.40 to 3.32). There were no statistically significant differences in the HR between male and female patients. Patients with a shorter time interval between registration and surgical treatment had a better survival than patients with a longer interval. The adjusted HR for a 6-month interval between surgery and registration would be 1.86 (95% CI, 1.03 to 3.36). An increased risk of death was observed for patients who underwent surgical treatment (adjusted HR was 1.36 for subtotal resection and 2.07 for biopsy compared with the reference group, total resection) and for patients who did not receive chemotherapy (adjusted HR = 1.65). Interestingly, when compared with the SS genotype, the SL and LL genotypes were associated with an increased risk of death (adjusted HR = 1.78; 95% CI, 1.11 to 2.85). Further analysis showed a dominant effect of the L allele (SL genotype, adjusted HR = 1.69; 95% CI, 1.03 to 2.76; LL genotype, HR = 1.87; 95% CI, 1.15 to 3.03). The trend test for increased HRs of patients with an increasing number of L alleles was statistically significant (P = .02).
We previously showed that the hTERT MNS16A S allele is correlated with elevated hTERT mRNA expression when compared with the L allele29 and that hTERT mRNA expression level is a biomarker that predicts the outcome in non–small-cell lung cancer patients.26 Therefore, we hypothesized that the hTERT MNS16A genotype might also have potential as a biomarker for assessing clinical outcome in patients with GBM. In the present survival analysis, we demonstrated that the hTERT MNS16A SS genotype is associated with a significantly better survival duration than the LL genotype, as assessed by multivariate Cox regression analysis. This study showed that the hTERT mRNA expression–related genetic variation was independently associated with the outcome of GBM, which is consistent with our previous report that showed that hTERT mRNA overexpression is an independent risk factor in non–small-cell lung cancer.26,36 Although the exact molecular mechanisms underlying the association between this genetic variation and survival outcome from GBM needs to be explored in future research, these findings warrant further work on the role of the hTERT MNS16A genotype and related mRNA expression levels in the development and progression of GBM. Patients with GBM, the most common form of glioma in adults, have poor survival, with a median survival duration of only 11 months for all ages.2 Primary brain and CNS cancers rank first among all cancers in average number of years of life lost (20.1 years v 6.1 years for prostate cancer and 11.8 years for lung cancer).37 Any improvement in survival of patients with GBM will depend on the identification of biomarkers that predict outcome that may help select those patients who potentially have better response to the present treatments. Genetic variation not only contributes to susceptibility to cancer but also plays a role in individual response to exposure to environmental hazards, including therapeutic agents. For instance, genetic variation may modulate individuals' response to chemotherapeutic agents.33,38-39 Molecular biomarkers based on genetic variation could be of practical value in the management of GBM because of difficulties in accessing the targeted tissue. Our research efforts in establishing such genetic biomarkers are directed at not only identifying risk factors that could contribute to susceptibility to GBM, but also developing novel treatments by targeting the correlated genetic variations that could alter therapeutic response. Surgical resection remains a critical form of management of GBM. Some have recommended performing gross total resection of GBM whenever possible.40 In the present study, the patients who underwent gross total resection did have a longer survival duration than patients who underwent subtotal resection or biopsy (21.4 v 13.9 months, respectively). This finding is consistent with prior data indicating that gross total resection is associated with improved prognosis in malignant gliomas.3 The average survival time of patients in this study was longer than typical GBM series. A likely explanation for this is the relatively young average age (50 years) of the patients in this study because younger age is a known favorable prognostic factor in patients with these tumors. Interestingly, use of adjuvant chemotherapy resulted in an average survival of 5 months longer compared with no chemotherapy. This may reflect a selection of patients with GBM for chemotherapy based on factors related, at least in part, to prognosis, such as extent and location of the tumor. Indeed, the patients with the hTERT MNS16A SS genotype had a statistically significantly longer survival duration compared with patients with other hTERT MNS16A genotypes (25.1 v 14.4 months, respectively). Multivariate Cox proportional hazards analysis confirmed that the patients with the hTERT MNS16A SL or LL genotype had an almost two-fold increase in the risk of death when compared with patients with the hTERT MNS16A SS genotype and that this effect of genetic variation was independent of other hazard factors, such as age and treatment. To our knowledge, this study is the first to show that an hTERT genetic variation is associated with outcome in patients with GBM. The finding that the hTERT MNS16A SS genotype was predictive of survival can be explained by our previous finding that the hTERT MNS16A S allele was associated with elevated hTERT mRNA expression. There have been some studies in which N-(4-hydroxyphenyl)retinamide, a retinoid used in cancer therapy and chemoprevention,41-44 has been shown to have apoptotic activity. This result may suggest that the better survival of patients with the hTERT MNS16A SS genotype may be a result of therapeutic regimens that cause apoptosis of GBM cells.45 However, we were not able to investigate this possibility in the present study because of the small number of patients with the hTERT MNS16A SS genotype. This hypothesis should be tested in future prospective studies. In summary, we demonstrated that there is an association between the hTERT MNS16A genotype and the treatment outcome in patients with GBM. Given these observations, we conclude that the functional MNS16A genotype of hTERT is a biomarker for assessment of survival outcome in patients with GBM. Furthermore, the hTERT MNS16A genotype has shown potential as a biomarker for selecting patients with GBM who are more sensitive to certain adjuvant chemotherapy. This needs to be further investigated in the future, and larger studies are needed to verify our findings.
The authors indicated no potential conflicts of interest.
We thank our research team headed by Phyllis Adatto and Georgina Armstrong, our patients who participated in this study, the referring physicians, and Donald R. Norwood (Department of Scientific Publications, The University of Texas M.D. Anderson Cancer Center, Houston, TX) for editing the manuscript.
Supported in part by National Institutes of Health Grants No. CA-70917 (M.L.B.), ES-11740 and CA-100264 (Q.W.), and CA-16672 (M.D. Anderson Cancer Center). Presented in part at the 96th Annual Meeting of the American Association for Cancer Research, Anaheim, CA, April 16-20, 2005. Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.
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Copyright © 2006 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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ABSTRACT
INTRODUCTION
50 years). We grouped the type of surgical resection into the following three categories: gross total resection, subtotal resection, and biopsy. The two-sided 
2 test was performed to determine any statistically significant differences in the distribution of the hTERT MNS16A genotypes by the demographic variables and clinical features. 
