Clinical Cancer Research CTRC-AACR San Antonio Breast Cancer Symposium
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Lin, X.
Right arrow Articles by Wu, X.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Lin, X.
Right arrow Articles by Wu, X.
Clinical Cancer Research Vol. 12, 5720-5725, October 1, 2006
© 2006 American Association for Cancer Research

Imaging, Diagnosis, Prognosis

Expression of Telomere-Associated Genes as Prognostic Markers for Overall Survival in Patients with Non–Small Cell Lung Cancer

Xin Lin1, Jian Gu1, Charles Lu2, Margaret R. Spitz1 and Xifeng Wu1

Authors' Affiliations: Departments of 1 Epidemiology and 2 Thoracic/Head and Neck Medical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas

Requests for reprints: Xifeng Wu, Department of Epidemiology, The University of Texas M.D. Anderson Cancer Center, 1155 Pressler Boulevard, Houston, TX 77030. Phone: 713-745-2485; Fax: 713-792-4657; E-mail: xwu{at}mdanderson.org.


   Abstract
Top
 Abstract
Materials and Methods
 Results
 Discussion
 References
 
Purpose: Human telomeres, which are composed of long, repetitive sequences of TTAGGG and a variety of proteins, function as a protective structure capping the ends of chromosomes. Telomere dysfunction plays important roles in cancer initiation and progression. TRF1, TRF2, POT1, and RAP1 are four major telomere proteins that regulate telomere stability and telomere length. We hypothesized that the expression of these genes would have significant predictive value for cancer development and prognosis.

Experimental Design: We compared the mRNA expression level of TRF1, TRF2, POT1, and RAP1 between tumor and adjacent normal tissues from 148 patients with non–small cell lung cancer using real-time quantitative PCR. We then estimated the prognostic value of the mRNA expression of these genes in tumors.

Results: The expression level of TRF1 was significantly lower in tumor tissues than in adjacent normal tissues (P < 0.0001); no significant difference was found for TRF2, POT1, and RAP1. The expression of RAP1 gene in tumors was highly predictive of overall survival. In the Cox proportional hazards model, patients with higher RAP1 expression were associated with a significantly better survival [hazard ratio (HR), 0.47; 95% confidence interval (95% CI), 0.24-0.91]. This improved survival was more prominent in men (HR, 0.45; 95% CI, 0.22-0.996) and in ever smokers (HR, 0.50; 95% CI, 0.24-1.02). Kaplan-Meier survival curves showed that patients with higher RAP1 expression had significantly longer median survival than patients with lower expression (median = 51.21 versus 15.34 months, P < 0.0009). The expressions of TRF2 in tumor tissues were significantly correlated with tumor grades (P = 0.0114).

Conclusions: RAP1 expression may be a useful biomarker of tumor progression and survival.

Telomeres are specialized nucleic acid-protein complexes that cap the ends of eukaryotic chromosomes and are composed of TTAGGG repetitive sequences bound by a collection of proteins (1). TRF1, TRF2, POT1, and RAP1 are telomere-associated proteins that are part of the telomere structure and have essential roles in controlling telomere length. TRF1 was identified as a suppressor of telomere elongation (2, 3). Long-term overexpression of TRF1 in a telomerase-positive tumor cell line resulted in gradual and progressive telomere shortening, whereas telomere elongation was induced by expression of a dominant-negative form of TRF1 (2). Like TRF1, TRF2 binds specifically to double-stranded TTAGGG repeats at the telomere (3). TRF2 is also a negative regulator of telomere length. Overexpression of TRF2 results in progressive shortening to telomere length, similar to TRF1 (4). More importantly, TRF2 protects human telomeres from end-to-end fusions; thus, TRF2 plays a key role in maintaining telomere integrity (5, 6). POT1 binds to the 3' single-stranded TTAGGG overhang at the end of the chromosome, in agreement with a protective role of chromosome end stability (7, 8). POT1 controls telomerase-dependent telomere elongation by first recruiting telomerase to the single-stranded 3' telomeric overhang, allowing extension of the G strand. Subsequently, POT1 limits further elongation of the telomere by telomerase (9, 10). Human RAP1 is recruited to the telomere by TRF2; it does not bind to DNA directly (11). RAP1 negatively regulates telomere length in vivo (11–13). Depletion of endogenous human RAP1 by small interference RNA leads to longer telomeres; in addition, overexpression of dominant-negative forms of human RAP1 extends telomeres (13).

Telomeres play key roles in protecting linear chromosomes from end-to-end fusion, recombination, and degradation; thus, telomeres are critical for maintaining genome integrity (14, 15). Changes in telomere-associated proteins can lead to telomere dysfunction, which in turn could cause genomic instability and cancer development. Without telomere protection, fusion of unprotected chromosome ends can generate dicentric chromosomes or chromosome circulation. Expression of a dominant-negative form of TRF2 disrupted telomere function, resulting in chromosomal end-to-end fusions and anaphase bridges, leading to induction of an ATM- or p53-dependent apoptotic response (5, 16). Similarly, POT1 knockdown cells displayed chromatin bridges between interphase cells and improper chromosomal segregation (17). It was shown that RAP1 loss genotype in yeast causes telomere fusions, and that this telomere protection role of RAP1 could be evolutionarily conserved (18). In addition to its primary role as a negative regulator of telomere length, TRF1 was indicated to be important in chromosome end protection, as end-to-end fusions at telomeres were found accumulated in TRF1-deficient mouse embryonic stem cells (19).

Given the importance of these telomere-associated proteins in controlling telomere length, telomere stability, and genomic integrity, we were interested in investigating the association between the expression levels of these telomeric genes in normal and tumor lung tissues and their association with lung cancer prognosis. Gene expression of TRF1, TRF2, POT1, and RAP1 were analyzed by reverse transcription-PCR and quantified by real-time PCR. Three housekeeping genes [glyceraldehyde-3-phosphate dehydrogenase (GAPDH), 18S rRNA, and ß-actin] were used to normalize the expression of each target gene. It has been shown that to measure expression level accurately, normalization by multiple housekeeping genes instead of one is required (20). The geometric mean of three housekeeping genes was validated as an accurate normalization factor by analyzing publicly available microarray data (20). In this study, we used the geometric mean expression of GAPDH, 18S rRNA, and ß-actin, three housekeeping genes, as internal control for normalization of gene expression.


   Materials and Methods
Top
 Abstract
 Materials and Methods
Results
 Discussion
 References
 
Patients and Samples
We analyzed samples from 148 non–small cell lung cancer patients who were enrolled in our ongoing lung cancer case-control study and underwent surgical resection at the M.D. Anderson Cancer Center from 1993 to 1997. These samples were fresh lung tumor tissues, and their paired adjacent normal tissues were collected at thoracotomy. The specimens were stored immediately after excision in a liquid nitrogen freezer (–130°C) until subjected to total RNA extraction. The current study did not restrict patient recruitment on the basis of age, gender, ethnicity, or tumor stage. As of June 2005, 99 (66.9%) of these patients were deceased; 93.9% of our study subjects were Caucasians. No statistically significant differences in sex, ethnicity, smoking status, age, and pack-years were observed when comparing alive patients to deceased patients, although there were more never smokers in alive patients (12.2%) than in deceased patients (6.0%; Table 1 ).


View this table:
[in this window]
[in a new window]
  		Table 1. Demographic characteristics of patients

 
Real-time Reverse Transcription-PCR
RNA extraction. Total RNA samples were isolated from surgically removed tumor or normal tissues from the lung using an E.Z.N.A. total RNA kit (Omega Bio-tek, Doraville, GA). The kit used the reversible binding properties of HiBind matrix, a new silica-based material. Briefly, tissues were first lysed under denaturing conditions that inactivate RNases. Samples were then applied to the HiBind spin columns to which total RNA was bound while debris and contaminants were washed away. Finally, high-quality RNA was eluted in DEPC-treated sterile water. The quality of the RNA samples was determined by electrophoresis through agarose gels and stained with ethidium bromide. The 18S and 28S RNA bands were visualized under UV light.

cDNA synthesis. Reverse transcription of total RNA was done with a Taqman reverse transcription reagents kit (Applied Biosystems, Branchburg, NJ) in a final volume of 20 µL containing 1x RT buffer, 5 mmol/L MgCl2, 250 µmol/L each deoxynucleotide triphosphate, 20 units of RNase inhibitor, 50 units of multiscribe reverse transcriptase, 2.5 µmol/L random hexamers, and 0.5 µg total RNA. The samples were incubated at room temperature for 10 minutes and 42°C for 30 minutes; reverse transcriptase was inactivated by heating the mixture at 99°C for 5 minutes.

Primers and probes. Primers and probes for TRF1, TRF2, POT1, RAP1, GAPDH, 18S rRNA, and ß-actin genes were designed using the Primer Express software (version 2.0, Applied Biosystems, Branchburg, NJ). We conducted searches in National Center for Biotechnology Information databases to confirm the total gene specificity of the nucleotide sequences chosen for the primers and probes as well as the absence of single nucleotide polymorphisms. In particular, the primer pairs were selected to be unique when compared with the sequences of the closely related family member genes. To avoid amplification of contaminating genomic DNA, one of the two primers or the probe was placed at the junction between two exons. Agarose gel electrophoresis allowed us to verify the specificity of PCR amplicons. The sequences of the primers and probes of these five genes are as followed: TRF1, forward primer 5'- CCACATGATGGAGAAAATTAAGAGTTAT-3', reverse primer 5'-TGCCGCTGCCTTCATTAGA-3', probe 5'-FAM-TTATGTGCTAAGTGAAAAATCATCAACCT-TAMRA-3'; TRF2, forward primer 5'- ACCAGGGCCTGTGGAAAAG-3', reverse primer 5'- GGTGGTTGGAGGATTCCGTA-3', probe 5'- FAM-CACCCAGAGAACCCGCAAGGCAG-TAMRA-3'; POT1, forward primer 5'-TCAGATGTTATCTGTCAATCAGAACCT-3', reverse primer 5'-TGTTGACATCTTTCTACCTCGTATAATGA-3', probe 5'-FAM- ACGACAGCTTTCCAAGCTCTGGA-TAMRA-3'; RAP1, forward primer 5'-GCCACCCGGGAGTTTGA-3', reverse primer 5'-GGGTGGATCATCATCACACATAGT-3', probe 5'-FAM-AGGTTGTGGTGGATGAGAGCCCTCC-TAMRA-3'; GAPDH, forward primer 5'-AAGGCTGAGAACGGGAAGC-3', reverse primer 5'-GAGGGATCTCGCTCCTGGA-3', probe 5'-FAM-TGTCATCAATGGAAATCCCATCACCATC-TAMRA-3'; 18S rRNA, forward primer 5'-AGTCCCTGCCCTTTGTACACA-3', reverse primer 5'-GATCCGAGGGCCTCACTAAAC-3', probe 5'-FAM-CGCCCGTCGCTACTACCGATTGG-TAMRA-3'; ß-actin, forward primer 5'-CGAGCGCGGCTACAGCTT-3', reverse primer 5'-TCCTTAATGTCACGCACGATTT-3', probe 5'-FAM-ACCACCACGGCCGAGCGG-TAMRA-3'.

PCR amplification. Quantitative values were obtained from the cycle number (Ct). At this specific cycle number, the increase in fluorescent signal associated with exponential growth of PCR products started to be detected by the laser detector of the ABI Prism 7900 Sequence Detection System (Applied Biosystems, Foster City, CA). The build in analysis software was used according to manufacturer's manuals. For each tested gene, a standard curve was plotted to quantify the amount of each transcript.

All PCR reactions were done using an ABI Prism 7900 Sequence Detection System (Applied Biosystems, Foster City, CA) with the Taqman 1000 Rxn Gold/Buffer A Pack (Applied Biosystems, Foster City, CA). Each PCR reaction was done in a final volume of 10 µL containing 1x buffer A, 3.4 mmol/L MgCl2, 100 µmol/L each deoxynucleotide triphosphate, 0.2 µmol/L each primer, 0.1 µmol/L probe, 0.02 unit of AmpliTaq Gold DNA polymerase, and 1 µL of each synthesized cDNA sample. The thermal cycling conditions comprised an initial denaturing step at 95°C for 10 minutes and 40 cycles at 95°C for 15 seconds and 60°C for 1 minute.

The precise amount of total RNA added to each reaction, RNA quality, and reverse transcription efficiency were difficult to assess. We, therefore, also quantified transcripts of GAPDH, 18S rRNA, and ß-actin as endogenous RNA controls and normalized each sample based on its geometric mean expression of all three housekeeping RNAs. Results were expressed as N-fold differences in target gene expression relative to the geometric mean of three internal control genes. The PCR reaction for each gene was duplicated for each sample, and the mean was used in the analysis.

Statistical Analysis
The smoking status of our studied patients was obtained from personal interview and defined as: ever smoker, ≥100 cigarettes in patient's lifetime; former smoker, smoking cessation for ≥1 year before diagnosis. Pack-years were defined as the number of cigarettes per day divided by 20 and then multiplied by the number of years smoked. Survival data were obtained from patient's chart review. The {chi}2 test and Fisher's exact test were used to test the association between the distribution of characteristics and survival status. Student's t test and Wilcoxon-Mann-Whitney test were used for continuous variables. The difference of protein expression in normal and tumor lung tissues was assessed by Sign rank test. Kaplan-Meier plots and log-rank test were applied by using the time of event-free survival, which was calculated from the date of lung cancer diagnosis to the date of end point event or the date of last patient follow-up. The end point in this study was overall mortality. The Cox proportional hazards model was applied to multivariate analysis to assess the effect of expression of individual protein on the risk of the end point event. Gene expression levels in tumor tissues were dichotomized by CART software for the hazard ratio (HR) analysis. The cutoff point for expression of RAP1/geometric mean expression of GAPDH, 18S rRNA, and ß-actin was 0.0153. Patients' age, gender, ethnicity, smoking status, tumor grade, and clinical stage were added into the model to control for confounding factors. The reference HR of 1 was set for low expression. The Kruskal-Wallis test was used to assess the correlation of expression of individual protein and tumor grade. All tests were two sided with a significant level of 0.05. STATA 8.0 software (STATA Corp., College Station, TX) was used to perform statistical analysis.


   Results
Top
 Abstract
 Materials and Methods
 Results
Discussion
 References
 
Clinical characteristic of study population. A total of 148 confirmed lung cancer patients diagnosed from 1993 to 1997 were included in this analysis. Clinical characteristics of these patients were summarized in Table 2 . According to the tumor-node-metastasis staging system, most of the patients were at stage IA (20.27%), stage IB (27.7%), and stage IIIA (18.92%) when diagnosed. Tumor grades are defined as grade 1, well-differentiated (low grade) tumor; grade 2, moderately differentiated (intermediate grade) tumor; and grade 3, poorly differentiated (high grade) tumor. Most of the patients were at grade 2 (38.51%) and grade 3 (39.19%). The majority of the patients had adenocarcinoma (47.3%) or squamous cell carcinoma (35.81%).


View this table:
[in this window]
[in a new window]
  		Table 2. Clinical characteristics of patients

 
TRF1 expression level is down-regulated in the tumor lung samples. Total RNA from normal and tumor lung tissues of the sample individuals were analyzed by reverse transcription-PCR and quantified by real-time PCR to compare the expression levels of TRF1, TRF2, POT1, and RAP1 in normal and tumor tissues. We observed significantly lower expression of the TRF1 gene in tumor tissues than in adjacent normal tissues (P < 0.0001; Table 3 ). However, no significant differences in expression between tumor and normal tissues were observed for TRF2 (P = 0.8111), POT1 (P = 0.1007), and RAP1 (P = 0.3525).


View this table:
[in this window]
[in a new window]
  		Table 3. TRF1, TRF2, POT1, and RAP1 expression levels in normal and tumor lung tissues

 
RAP1 expression in lung tumor tissue is correlated with overall survival of the lung cancer patients. RAP1 expression levels in tumor samples were significantly correlated with overall survival of the patients (Table 4 , Fig. 1 ). High level of RAP1 expression in tumor tissues was associated with a 53% reduced risk of cancer death (HR, 0.47; 95% confidence interval, 0.24-0.91; Table 4). In Kaplan-Meier survival estimates, the median survival time for patients with low RAP1 expression was 15.34 months, whereas the median survival time for patients with high RAP1 expression was 51.21 months (P < 0.0009; Fig. 1). This protective effect of higher RAP1 expression was especially evident in men and in ever smokers (Table 4). In men, the adjusted HR was 0.45 (95% confidence interval, 0.22-0.996). Ever smokers with higher levels of RAP1 had a 50% reduced risk of death with borderline significance (HR, 0.50; 95% confidence interval, 0.24-1.02). These data suggest that RAP1 expression level could be a useful prognostic marker for lung cancer survival.


View this table:
[in this window]
[in a new window]
  		Table 4. Correlation of RAP1 expression in tumor tissues with patient survival

 

Figure 1
View larger version (9K):
[in this window]
[in a new window]
  		Fig. 1. Kaplan-Meier survival estimates of RAP1 expression in tumor tissues. Overall survival of lung cancer patients analyzed by RAP1 expression level in tumor tissues. Y-axis, proportion of survival; X-axis, survival time in month. Dotted line, low level of expression; solid line, high level of expression. MST, median survival time. P < 0.0009.

 
We also studied the association between TRF1, TRF2, and POT1 expression in tumor tissues and overall survival of these patients, but we did not find statistically significant associations (data not shown).

TRF2 expression in lung tumor tissues is correlated with tumor grade. We next analyzed the association between TRF1, TRF2, POT1, and RAP1 expression levels in the tumor tissue and tumor grade. We observed that TRF2 expression was significantly correlated with tumor grade (P = 0.0114; Table 5 ). Higher level of expression of TRF2 was correlated with lower tumor grade, suggesting that TRF2 has a protective role in lung cancer progression.


View this table:
[in this window]
[in a new window]
  		Table 5. TRF1, TRF2, POT1, and RAP1 expression in tumor tissues and their correlation with tumor grade

 

   Discussion
Top
 Abstract
 Materials and Methods
 Results
 Discussion
References
 
We studied the expression of four telomere-associated proteins (TRF1, TRF2, POT1, and RAP1 genes) in normal and tumor tissues of lung cancer patients and observed significant down-regulation of TRF1 in tumor samples and no significant difference in expression between tumor and normal tissues for TRF2, POT1, and RAP1 (Table 3). The down-regulation of TRF1 in tumor tissue was consistent when we used GAPDH alone, 18S rRNA alone, ß-actin alone (data not shown) or the geometric mean of three genes as internal control. In previous published studies, controversial data were presented for these telomeric genes in cancer. Some studies suggested that TRF1 and TRF2 were down-regulated in tumor tissues (21–26), whereas others showed that TRF1 or TRF2 was up-regulated (27–30). Different tumor type and tumor stage may account for some of these differences. One study showed that tumor stage and telomere length might also influence POT1 expression in cancer (31). Their data indicated that in stage I/II gastric cancer, POT1 is mostly down-regulated; and in stage III/IV gastric cancer, POT1 is frequently up-regulated. In addition, POT1 expression decreased as telomere length shortened (31).

Normal adjacent tissues are widely used as baseline (or comparison) specimen class in gene expression profiling and telomerase activity study between tumor and normal tissues (32–34). However, some studies have raised the question that whether normal adjacent tissues can truly represent normal tissues in these type of studies due to a "field" effect (35, 36). They suggested that, in some cases, tissues adjacent to cancer, although appearing morphologically normal, may contain genetic changes associated with cancer (35, 36), which might even influence gene expression (35). Therefore, difference in baseline or normal tissue collection might also contribute to controversial reports on telomere-associated protein expression in cancer.

More importantly, we observed significant association between RAP1 expression and overall survival of the lung cancer patients (Table 4; Fig. 1). When we used GAPDH alone, 18S rRNA alone, and ß-actin alone as internal control, we also observed significant association in all three cases (data not shown). This result is consistent with the telomere protection role of RAP1 in yeast (18), indicating that this protective role is evolutionarily conserved. We observed that in men and ever smokers, the influence of RAP1 expression is prominent (Table 4). It is well documented that females live longer than males; the different rate of telomere erosion in males and females may lead to differential requirements of telomeric protein levels. This gender disparity in telomeric protein requirement might explain the differences exhibited between males and females in our research. Looking at different risk factors, smoking produces a state of heightened oxidative stress. Increased smoking is associated with accelerated telomere shortening, which may sensitize the tumor to the protective role of RAP1.

We also found TRF2 expression in tumor tissues was inversely correlated with tumor grade: the higher the gene expression, the lower the tumor grade (Table 5). Tumor grade refers to how much the tumor cells resemble normal cells of the same tissue type. The cells of grade 1 tumors resemble normal cells and tend to grow and multiply slowly, whereas grade 3 tumors grow rapidly. Tumor grade is an indicator of the severity of the cancer. Our data suggested that TRF2 might have a protective role in lung cancer progression.

Studies have shown that shortened, dysfunctional telomere might activate a DNA damage response pathway involving ATM, p53, CHK2, and H2AX proteins and lead to cell cycle arrest and senescent phenotype (37). This phenomenon might be a tumor suppressor mechanism. Disruption of DNA damage response mechanism might result in accelerated telomere shortening and elevated frequencies of end-to-end chromosome fusions. Previously, we studied the association among telomere activity, p53 protein overexpression, and genetic instability in lung cancer using samples overlapping with this study (38). We found that p53 overexpression carried a 6.7-fold (95% confidence interval, 1.7-27.7) increased risk for positive telomerase activity, and it is common in individuals genetically susceptible to exposure (38). However, p53 overexpression and telomerase activity were not associated with telomere-associated protein expression in lung cancer tissues (data not shown). We also measured telomere length of tumor samples of these lung cancer patients using real-time PCR; however, no association between telomere length and overall survival was observed (data not shown). Neither was any association between telomere length and telomere-associated gene expression (data not shown). These data suggested the predictive role of RAP1 expression in lung cancer survival might be independent of telomerase activity and telomere length.

In this study, we used the geometric mean of the expression of three housekeeping gene as internal control to normalize target gene expression. This method can eliminate the variability of expression of a single gene control in response to various factors and present a more accurate measure of reverse transcription-PCR expression profiling (20). When we compared the data using the geometric mean of three genes as internal control and using individual gene as internal control, we found that the relative expression level between tumor and normal tissues varied. However, RAP1 expression in tumor consistently showed significant association with overall survival disregard which internal control was used. Because the expression of telomere maintenance genes from tumor tissues could be affected by tumor heterogeneity and lymphocyte infiltration, studies at the cellular level either by immunohistochemistry or by mRNA hybridization are warranted to confirm real-time PCR results. Nevertheless, our data strongly suggested that expression of RAP1 is a promising prognosis marker for lung cancer.


   Footnotes
 
Grant support: National Cancer Institute grants CA 111646, CA 55769, CA 70907, and DAMD17-02-1-0706 and Flight Attendant Medical Research Institute.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received 12/27/05; revised 5/18/06; accepted 7/28/06.


   References
Top
 Abstract
 Materials and Methods
 Results
 Discussion
 References
 

  1. McEachern MJ, Krauskopf A, Blackburn EH. Telomeres and their control. Annu Rev Genet 2000;34:331–58.[CrossRef][Medline]
  2. van Steensel B, de Lange T. Control of telomere length by the human telomeric protein TRF1. Nature 1997;385:740–3.[CrossRef][Medline]
  3. Broccoli D, Smogorzewska A, Chong L, de Lange T. Human telomeres contain two distinct Myb-related proteins, TRF1 and TRF2. Nat Genet 1997;17:231–5.[CrossRef][Medline]
  4. Smogorzewska A, van Steensel B, Bianchi A, et al. Control of human telomere length by TRF1 and TRF2. Mol Cell Biol 2000;20:1659–68.[Abstract/Free Full Text]
  5. van Steensel B, Smogorzewska A, de Lange T. TRF2 protects human telomeres from end-to-end fusions. Cell 1998;92:401–13.[CrossRef][Medline]
  6. Yang Q, Zheng YL, Harris CC. POT1 and TRF2 cooperate to maintain telomeric integrity. Mol Cell Biol 2005;25:1070–80.[Abstract/Free Full Text]
  7. Baumann P, Cech TR. Pot1, the putative telomere end-binding protein in fission yeast and humans. Science 2001;292:1171–5.[Abstract/Free Full Text]
  8. Lei M, Podell ER, Cech TR. Structure of human POT1 bound to telomeric single-stranded DNA provides a model for chromosome end-protection. Nat Struct Mol Biol 2004;11:1223–9.[CrossRef][Medline]
  9. Chandra A, Hughes TR, Nugent CI, Lundblad V. Cdc13 both positively and negatively regulates telomere replication. Genes Dev 2001;15:404–14.[Abstract/Free Full Text]
  10. Loayza D, de Lange T. POT1 as a terminal transducer of TRF1 telomere length control. Nature 2003;423:1013–8.[CrossRef][Medline]
  11. Li B, Oestreich S, de Lange T. Identification of human Rap1: implication for telomere evolution. Cell 2000;101:471–83.[CrossRef][Medline]
  12. Li B, de Lange T. Rap1 affects the length and heterogeneity of human telomeres. Mol Biol Cell 2003;14:5060–8.[Abstract/Free Full Text]
  13. O'Connor MS, Safari A, Liu D, Qin J, Songyang Z. The human Rap1 protein complex and modulation of telomere length. J Biol Chem 2004;279:28585–91.[Abstract/Free Full Text]
  14. Gasser SM. A sense of the end. Science 2000;288:1377–9.[Abstract/Free Full Text]
  15. Shore D. Telomeric chromatin: replicating and wrapping up chromosome ends. Curr Opin Genet Dev 2001;11:189–98.[CrossRef][Medline]
  16. Karlseder J, Broccoli D, Dai Y, Hardy S, de Lange T. p53- and ATM-dependent apoptosis induced by telomeres lacking TRF2. Science 1999;283:1321–5.[Abstract/Free Full Text]
  17. Veldman T, Etheridge KT, Counter CM. Loss of hPot1 function leads to telomere instability and a cut-like phenotype. Curr Biol 2004;14:2264–70.[CrossRef][Medline]
  18. Pardo B, Marcand S. Rap1 prevents telomere fusions by nonhomologous end joining. EMBO J 2005;24:117–27.
  19. Iwano T, Tachibana M, Reth M, Shinkai Y. Importance of TRF1 for functional telomere structure. J Biol Chem 2004;279:1442–8.[Abstract/Free Full Text]
  20. Vandesompele J, De Preter K, Pattyn F, et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 2002;3:1–11.[Medline]
  21. Yamada M, Tsuji N, Nakamura M, et al. Down-regulation of TRF1, TRF2 and TIN2 genes is important to maintain telomeric DNA for gastric cancers. Anticancer Res 2002;22:3303–7.[Medline]
  22. Yamada K, Yagihashi A, Yamada M, et al. Decreased gene expression for telomeric-repeat binding factors and TIN2 in malignant hematopoietic cells. Anticancer Res 2002;22:1315–20.[Medline]
  23. Saito K, Yagihashi A, Nasu S, et al. Gene expression for suppressors of telomerase activity (telomeric-repeat binding factors) in breast cancer. Jpn J Cancer Res 2002;93:253–8.[CrossRef][Medline]
  24. Yamada K, Yajima T, Yagihashi A, et al. Role of human telomerase reverse transcriptase and telomeric-repeat binding factor proteins 1 and 2 in human hematopoietic cells. Jpn J Cancer Res 2000;91:1278–84.[CrossRef][Medline]
  25. La Torre D, de Divitiis O, Conti A, et al. Expression of telomeric repeat binding factor-1 in astroglial brain tumors. Neurosurgery 2005;56:802–10.[CrossRef][Medline]
  26. Kishi S, Wulf G, Nakamura M, Lu KP. Telomeric protein Pin2/TRF1 induces mitotic entry and apoptosis in cells with short telomeres and is down-regulated in human breast tumors. Oncogene 2001;20:1497–508.[CrossRef][Medline]
  27. Oh BK, Kim YJ, Park C, Park YN. Up-regulation of telomere-binding proteins, TRF1, TRF2, and TIN2 is related to telomere shortening during human multistep hepatocarcinogenesis. Am J Pathol 2005;166:73–80.[Abstract/Free Full Text]
  28. Klapper W, Qian W, Schulte C, Parwaresch R. DNA damage transiently increases TRF2 mRNA expression and telomerase activity. Leukemia 2003;17:2007–15.[CrossRef][Medline]
  29. Klapper W, Krams M, Qian W, Janssen D, Parwaresch R. Telomerase activity in B-cell non-Hodgkin lymphomas is regulated by hTERT transcription and correlated with telomere-binding protein expression but uncoupled from proliferation. Br J Cancer 2003;89:713–9.[CrossRef][Medline]
  30. Nakanishi K, Kawai T, Kumaki F, et al. Expression of mRNAs for telomeric repeat binding factor (TRF)-1 and TRF2 in atypical adenomatous hyperplasia and adenocarcinoma of the lung. Clin Cancer Res 2003;9:1105–11.[Abstract/Free Full Text]
  31. Kondo T, Oue N, Yoshida K, et al. Expression of POT1 is associated with tumor stage and telomere length in gastric carcinoma. Cancer Res 2004;64:523–9.[Abstract/Free Full Text]
  32. Yoshimatsu K, Altorki NK, Golijanin D, et al. Inducible prostaglandin E synthase is overexpressed in non-small cell lung cancer. Clin Cancer Res 2001;7:2669–74.[Abstract/Free Full Text]
  33. O-Wang J, Kawamura K, Tada Y, et al. DNA polymerase {kappa}, implicated in spontaneous and DNA damage-induced mutagenesis, is overexpressed in lung cancer. Cancer Res 2001;61:5366–9.[Abstract/Free Full Text]
  34. Hiyama K, Hiyama E, Ishioka S, et al. Telomerase activity in small-cell and non-small-cell lung cancers. J Natl Cancer Inst 1995;87:895–902.[Abstract/Free Full Text]
  35. Chandran UR, Dhir R, Ma C, Michalopoulos G, Becich M, Gilbertson J. Differences in gene expression in prostate cancer, normal appearing prostate tissue adjacent to cancer and prostate tissue from cancer free organ donors. BMC Cancer 2005;5:45.[CrossRef][Medline]
  36. Woenckhaus M, Grepmeier U, Wild PJ, et al. Multitarget FISH and LOH analyses at chromosome 3p in non-small cell lung cancer and adjacent bronchial epithelium. Am J Clin Pathol 2005;123:752–61.[CrossRef][Medline]
  37. d'Adda di Fagagna F, Reaper PM, Clay-Farrace L, et al. A DNA damage checkpoint response in telomere-initiated senescence. Nature 2003;426:194–8.[CrossRef][Medline]
  38. Wu X, Kemp B, Amos CI, et al. Associations among telomerase activity, p53 protein overexpression, and genetic instability in lung cancer. Br J Cancer 1999;80:453–7.[CrossRef][Medline]



This article has been cited by other articles:


Home page
 BloodHome page
D. Poncet, A. Belleville, C. t'Kint de Roodenbeke, A. Roborel de Climens, E. Ben Simon, H. Merle-Beral, E. Callet-Bauchu, G. Salles, L. Sabatier, J. Delic, et al.
Changes in the expression of telomere maintenance genes suggest global telomere dysfunction in B-chronic lymphocytic leukemia
Blood, February 15, 2008; 111(4): 2388 - 2391.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Lin, X.
Right arrow Articles by Wu, X.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Lin, X.
Right arrow Articles by Wu, X.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online