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Keywords:

  • telomere length;
  • peripheral blood leukocytes;
  • soft tissue sarcoma;
  • cancer risk

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. REFERENCES

BACKGROUND:

Human telomeres consisting of long, tandem repeats of the nucleotide sequence TTAGGG at the chromosome ends are essential for maintaining chromosomal stability. Previous epidemiologic studies have indicated that shorter telomere length in peripheral blood leukocytes (PBLs) is associated with the development of many cancers. However, the relation between PBL telomere length and the risk of soft tissue sarcoma (STS) has not been investigated.

METHODS:

The relative telomere length (RTL) was determined in PBLs using real-time polymerase chain reaction in this case-control study. The study participants included 137 patients with histologically confirmed STS (cases) who had received no prior chemotherapy or radiotherapy and 137 healthy controls who were frequency-matched to cases on age, sex, and ethnicity.

RESULTS:

Patients in the case group had significantly longer RTL than controls (1.46 ± 0.42 for cases vs 1.15 ± 0.39 for controls; P < .001). By using median RTL in the controls as a cutoff level, individuals who had long telomere length were associated with a significantly increased risk of STS compared with those who had short telomere length (adjusted odds ratio, 4.71; 95% confidence interval, 2.63-8.44). When participants were categorized further into 3 or 4 groups according to the tertile or quartile RTL values of healthy controls, a significant dose-response relation was observed between longer RTL and increased risks of STS.

CONCLUSIONS:

The current results provided the first epidemiologic evidence that longer telomere length in PBLs is associated significantly with an increased risk of STS, potentially suggesting an important role for telomere maintenance in STS development. Cancer 2013. © 2013 American Cancer Society.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. REFERENCES

Human telomeres are hexameric tandem repeats of the nucleotide sequence TTAGGG that cap the ends of the eukaryotic chromosome arms.1 Associated with a wide array of specific telomere-binding proteins, including telomeric repeat binding factor 1 (TRF1), TRF2, TRF1-interacting nuclear factor 2 (TIN2), protection of telomere 1 homolog (POT1), tripeptidyl peptidase I (TPP1), and telomeric repeat binding factor 2 interacting protein (RAP1),2 telomeres are folded into loop structures that maintain genomic structural integrity by inhibiting nucleolytic degradation, irregular recombination, and end-to-end fusion of linear chromosomes.3, 4 In somatic cells, telomere DNA is progressively shortened by 30 to 200 base pairs after each cycle of mitotic division because of an “end-replication problem” of DNA polymerase.5, 6 When telomeres become critically short, inappropriately capped chromosomes or telomere-free ends emerge, prompting cell cycle arrest and cellular senescence, eventually leading to apoptosis.7

Previous reports have indicated that the attrition rate of telomeres is accelerated by many exogenous and endogenous risk factors, such as smoking,8-10 oxidative stress,11, 12 unhealthy lifestyles,13-15 obesity,8, 16 and low socioeconomic status.17, 18 Moreover, telomere length shortening is significantly associated with subsequent genomic instability and increased cancer risk. Telomeres are often shorter in tumor cells than in normal tissue. Multiple epidemiologic studies have demonstrated that shorter telomere length in peripheral blood leukocytes (PBLs) is associated with increased risk of various human epithelial malignancies.19-22 A previous study evaluated the association of telomere length in PBLs with the risk of osteosarcoma.23 However, the association of PBLs' telomere length with the risk of soft tissue sarcomas (STS) has not been studied yet.

STS are a heterogeneous group of rare malignancies originating from tissues of mesenchymal differentiation, including muscle, nerve, fat, blood vessels, and other structures that are derived mainly from embryonic mesoderm. These tumors can occur at almost any anatomic site, although they reportedly are more frequent in the extremities.24 In the United States, approximately 11,000 new STS cases are diagnosed annually.25 Although rare, nearly 40% of STS patients have advanced disease (ie, regional or metastatic) at their initial diagnosis, and localized STS progresses to metastatic disease in more than 33% of cases.26-28 Complete surgical resection in combination with radiotherapy is generally the mainstay of localized STS therapy; whereas treatment of metastatic disease continues to be difficult.29 Therefore, novel approaches are urgently needed to identify high-risk subpopulations for targeted prevention and early diagnosis. To date, the usefulness of constitutive telomere length in PBLs as a genetic biomarker of STS risk has not been investigated. In this study, we used a case-control study design to evaluate the association of telomere length in PBLs with susceptibility to STS. To our knowledge, this is the first epidemiologic study to investigate the role of constitutive telomere length in STS etiology.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. REFERENCES

Study Population and Epidemiologic Data

Patients with histologically confirmed STS and no prior chemotherapy or radiotherapy (cases) were recruited between November 2010 and January 2012 from The University of Texas M. D. Anderson Cancer Center through a daily review of computerized appointment schedules. No age, sex, ethnicity, or disease stage restrictions were applied. Patient blood samples were processed by the institutional Blood Specimen Research Resource within the Center for Translational and Public Health Genomics at The University of Texas M. D. Anderson Cancer Center. Individuals for the control group who had no prior history of cancer were identified from the rosters of Kelsey-Seybold Clinic, the largest multispecialty physician group in the Houston metropolitan area. Controls who were recruited during the same period as the cases were matched to the cases by age (±1 year), sex, and ethnicity. All participants were interviewed by trained staff to collect information regarding demographics, smoking history, alcohol consumption, family history of cancer, medical history, and employment history. Baseline blood samples were collected after the interview. This study was approved by the institutional review boards at M. D. Anderson and Kelsey-Seybold. The response rates for cases and controls were 92% and 77%, respectively.

Overall Telomere Length Assessment by Real-Time Polymerase Chain Reaction

High-quality genomic DNA was isolated from participants' PBLs using the QIAamp Maxi DNA kit (Qiagen, Valencia, Calif) according to the manufacturer's protocol. Relative telomere length (RTL) was measured using a modified version of the real-time quantitative polymerase chain reaction (PCR) method originally described by Cawthon.30, 31 Briefly, 2 main steps were involved in RTL quantification: the ratio of the telomere repeat copy number to a single gene (ie, human globulin [Hgb]) copy number was determined for each sample using standard curves (the derived ratio was proportional to the overall telomere length). Second, the ratio for each sample was normalized to a calibrator DNA sample to standardize different runs. The PCR reaction mixture (14 μL) for the telomere amplification consisted of 1 × SYBR Green Master Mix (Applied Biosystems, Foster City, Calif), 200 nmol/L Tel-1 primer, 200 nmol/L Tel-2 primer, and 5 ng genomic DNA. The PCR reaction mixture (14 μL) for Hgb gene amplification consisted of 1 × SYBR Green Master Mix, 200 nmol/L Hgb-1 primer, 200 nmol/L Hgb-2 primer, and 5 ng genomic DNA. The thermal cycling conditions were 1 cycle at 95°C for 10 minutes followed by 40 cycles at 95°C for 15 seconds and at 56°C (for telomere amplification) or 58°C (for Hgb amplification) for 1 minute. Each sample was run in duplicate in a 384-well plate. Real-time PCR was performed using the HT7900 system (Applied Biosystems). Each sample was run in duplicate in the same 384-well plate. The telomere and Hgb PCRs were done on separate 384-well plates with the same samples in the same well positions. Each plate contained randomly selected samples to have equal representation of cases and controls. The laboratory personnel were blinded to case and control status. During each run, negative controls (water), a calibrator DNA sample, and a standard curve were included. For the standard curve, a reference DNA sample (from a healthy control with established RTL in our previous studies) was serially diluted by using a 2-fold serial dilution to generate a 6-point standard curve between 20 ng and 0.625 ng of DNA in each reaction. The same reference DNA has been used consistently for all plates in this current and our previous studies.31, 32 The R2 correlation for each standard curve was ≥0.99. The acceptable standard deviation (SD) was set at 0.3 for the threshold cycle (Ct) values. If it was determined that the result was out of the acceptable range, then the run was repeated for the same sample. For testing interassay variation, 2 samples with relatively long and short telomere lengths were tested using 3 different runs. The interassay variation was <3% in our studies.31, 32

Statistical Analysis

All statistical analyses were done using the Stata 10.1 statistical software package (Stata Corporation, College Station, Tex). The difference in the distribution of host characteristics between cases and controls was evaluated using the Pearson chi-square test for categorical variables (sex and ethnicity), and the Student t test was used for analyzing age and telomere length as continuous variables. Telomere lengths were also analyzed as categorical variables by setting a cutoff point at the median, tertile, or quartile value in the control group. The association between STS risk and telomere length was estimated using unconditional multivariate logistic regression to determine the adjusted odds ratio (aOR) and 95% confidence interval (CI), adjusting for age, sex, ethnicity, smoking status, and alcohol use. All statistical tests were 2-sided, and associations were considered statistically significant at P < .05.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. REFERENCES

In total, 137 patients with STS and 137 healthy controls were included in this study (Table 1). The cases and controls were matched on age (±1 year), sex, and ethnicity. The mean ± SD ages of STS cases and controls were 58.78 ± 12.90 years and 59.07 ± 12.84 years, respectively. There were no significant differences in the frequency of smoking or alcohol use between cases and controls. The clinical characteristics of the patients are summarized in Table 2. Of these patients, 40.14% had T1 tumors (≤5 cm in greatest dimension), and 56.52% had T2 tumors (>5 cm in greatest dimension) at the time of diagnosis. On the basis of tumor-lymph node-metastasis (TNM) staging (according to the 2012 National Comprehensive Cancer Network Guidelines), the cases were classified as follows: stage I, 53.02%; stage II, 13.13%; stage III, 16.79%; and stage IV, 15.33%. The most common histologic types were leiomyosarcoma (17.52%), liposarcoma (14.60%), and extraskeletal osteosarcoma (11.68%).

Table 1. Host Characteristics of Cases and Controls
 No. (%)
VariableCases, n = 137Controls, n = 137P
  1. Abbreviations: SD, standard deviation.

Age: Mean ± SD, y58.78 ± 12.9059.07 ± 12.84.851
Sex  1.0
 Men85 (62.04)85 (62.04) 
 Women52 (37.96)52 (37.96) 
Ethnicity   
 White117 (85.40)117 (85.40) 
 Hispanic12 (8.76)12 (8.76) 
 Black8 (5.84)8 (5.84) 
Smoking status  .139
 Never70 (51.09)88 (64.23) 
 Former49 (35.77)36 (26.28) 
 Current12 (8.76)12 (8.76) 
 Incomplete6 (4.38)1 (0.73) 
Alcohol consumption  .121
 Never51 (37.23)39 (28.47) 
 Ever83 (60.58)95 (69.34) 
 Incomplete3 (2.19)7 (5.11) 
Table 2. Clinical Characteristics of Patients
CharacteristicFrequency (No.)Percentage (%)
  • a

    Stage and histology classification were assigned according to the American Joint Committee on Cancer (AJCC) Cancer Staging Manual and AJCC Cancer Staging Handbook 7th editions and the National Comprehensive Cancer Network Guideline 2.2012.

  • b

    Others included synovial sarcoma (6.57%), malignant fibrous histiocytoma (5.11%), gastrointestinal stromal tumors (2.92%), fibrosarcoma (2.19%), endometrial stromal sarcoma (2.19%), angiosarcoma (2.19%), rhabdomyosarcoma (1.46%), and other minor types.

Tumor size, cm  
 ≤55540.14
 >57856.52
 Incomplete42.92
Stagea  
 I7453.02
 II1813.13
 III2316.79
 IV2115.33
 Incomplete10.73
Histology  
 Leiomyosarcoma2417.52
 Liposarcoma2014.60
 Extraskeletal osteosarcoma1611.68
Othersb8964.96

We measured RTL using a real-time PCR method in all samples. There was a borderline significant inverse correlation between RTL and age in both controls (r = −0.14; P = .10) and cases (r = −0.15; P = .08). There was no significant relation between RTL and smoking status (P = .46) or alcohol use (P = .44). We also analyzed the correlation of RTL with clinical variables. We observed a trend toward longer RTL in patients with metastasis (P = .081). The lack of statistical significance was probably because of the small number of patients with metastatic disease in our study (n = 21).

We observed that RTL was significantly longer in STS cases than in controls. For cases and controls, respectively, the mean ± SD normalized RTL was 1.46 ± 0.42 versus 1.15 ± 0.39 (P < .001). In stratified analysis according to sex (men and women), age (< 60 years and ≥60 years), ethnicity (white and others), and the top 3 histologic subtypes, the RTL was longer in PBLs from STS cases than in PBLs from controls in all strata (Table 3).

Table 3. Relative Telomere Length by Host Characteristics in All Participants
 CasesControls 
VariableNo.RTL: Mean ± SDNo.RTL: Mean ± SDP
  1. Abbreviations: RTL, relative telomere length; SD. standard deviation.

Overall1371.46 ± 0.421351.15± 0.39< .001
Sex     
 Men851.44 ± 0.41841.15 ± 0.40< .001
 Women521.50 ± 0.43511.15 ± 0.39< .001
Age, y     
 <60731.52 ± 0.45691.22 ± 0.47< .001
 ≥60641.39 ± 0.37661.08 ± 0.29< .001
Ethnicity     
 White1171.45 ± 0.421151.13 ± 0.33< .001
 Other201.50 ± 0.38201.25 ± 0.650.1503
Smoking status     
 Never701.48 ± 0.43881.13 ± 0.35< .001
 Ever611.42 ± 0.39461.19 ± 0.47< .001
Alcohol consumption     
 Never511.47 ± 0.32381.10 ± 0.40< .001
 Ever831.46 ± 0.47941.18 ± 0.40< .001
Histology     
 Leiomyosarcoma241.56 ± 0.431351.15 ± 0.39< .001
 Liposarcoma201.56 ± 0.481351.15 ± 0.39< .001
 Extraskeletal osteosarcoma161.40 ± 0.351351.15 ± 0.39< .001

We then performed an unconditional logistic regression analysis adjusting for age, sex, ethnicity, smoking status, and alcohol use to assess the association between RTL and STS risk (Table 4). When participants were dichotomized according to the median RTL value in controls, we observed that longer RTL was significantly associated with a 4.71-fold increased risk of STS (aOR, 4.71; 95% CI, 2.63-8.44). When participants were categorized into 3 groups according to tertile values of RTL in healthy controls, we observed a significant dose-response relation between longer RTL and increased STS risk. That is, when the first (shortest) tertile was used as the reference group, the aORs for the second and third tertile were 3.19 (95% CI, 1.38-7.39) and 9.12 (95% CI, 4.16-20.00), respectively (Ptrend < .001). Similarly, when participants were categorized into 4 groups according to quartile values of RTL in healthy controls, we also observed a significant dose-response relation. When the first (shortest) quartile was used as the reference group, the aORs for the second, third, and fourth quartiles were 3.84 (95% CI, 1.24-11.90), 6.87 (95% CI, 2.34-20.14), and 16.54 (95% CI, 5.72-47.87), respectively (Ptrend < .001). A similar dose-response relation between RTL and STS risk was observed in stratified analyses by age and sex (Table 5).

Table 4. Risk of Soft Tissue Sarcoma as Estimated by Relative Telomere Length
 No. (%)  
RTLCasesControlsAdjusted OR [95% CI]aP
  • Abbreviations: RTL, relative telomere length; OR, odds ratio; CI, confidence interval.

  • a

    Adjusted by age, sex, ethnicity, smoking status, and alcohol use.

By median    
 Short23 (25.56)67 (74.44)1.00 
 Long114 (62.64)68 (37.36)4.71 [2.63-8.44]< .001
By tertile    
 First11 (19.64)45 (80.36)1.00 
 Second31 (40.79)45 (59.21)3.19 [1.38-7.39]< .001
 Third95 (67.86)45 (32.14)9.12 [4.16-20.00]< .001
 P for trend  < .001 
By quartile    
 First5 (13.16)33 (86.84)1.00 
 Second18 (34.62)34 (65.38)3.85 [1.24-11.91].019
 Third35 (50)35 (50)6.87 [2.34-20.15]< .001
 Fourth79 (70.54)33 (29.46)16.54 [5.72-47.87]< .001
 P for trend  < .001 
Table 5. Association Between Relative Telomere Length in Peripheral Blood Leukocytes and Soft Tissue Sarcoma Risk Stratified by Selected Characteristics
 No. (%)  
RTLCasesControlsAdjusted OR [95% CI]aP
  • Abbreviations: RTL, relative telomere length; OR, odds ratio; CI, confidence interval.

  • a

    Adjusted by age, sex, ethnicity, smoking status, and alcohol use.

Men    
 By median    
  Short11 (20.75)42 (79.25)1.00 
  Long74 (63.79)42 (36.21)7.52 [3.36-16.82]< .001
 By tertile    
  First6 (17.65)28 (82.35)1.00 
  Second24 (46.15)28 (53.85)4.78 [1.61-14.19].0049
  Third55 (66.27)28 (33.73)10.86 [3.83-30.85]< .001
  P for trend  < .001 
 By quartile    
  First3 (12.50)21 (87.50)1.00 
  Second8 (27.59)21 (72.41)2.92 [0.66-12.89].15
  Third30 (58.82)21 (41.18)11.27 [2.89-43.93]< .001
  Fourth44 (67.69)21 (32.31)18.50 [4.67-73.24]< .001
  P for trend  < .001 
Women    
 By median    
  Short9(25.71)26 (74.29)1.00 
  Long43(63.24)25 (36.76)4.48 [1.73-11.59]< .001
 By tertile    
  First6(26.09)17 (73.91)1.00 
  Second6(26.09)17 (73.91)0.85 [0.21-3.53].83
  Third40(70.18)17 (29.82)6.22 [1.94-19.92].002
  P for trend  < .001 
 By quartile    
  First2 (13.33)13 (86.67)1.00 
  Second7 (35)13 (65)3.34 [0.54-20.79].2
  Third8 (38.10)13 (61.90)3.07 [0.48-19.76].24
  Fourth35 (74.47)12 (25.53)16.72 [3.04-92.09].0012
  P for trend  < .001 
Age <60 y    
 By median    
  Short9 (21.95)32 (78.05)1.00 
  Long58 (63.74)33 (36.26)6.73 [2.72-16.69]< .001
 By tertile    
  First5 (18.52)22 (81.48)1.00 
  Second22 (5022 (50)4.62 [1.45-14.72].01
  Third40 (65.57)21 (34.43)7.93 [2.53-24.85]< .001
 P for trend  < .001 
 By quartile    
  First3 (15.79)16 (84.21)1.00 
  Second6 (27.27)16 (72.73)2.04 [0.42-9.83].37
  Third23 (58.97)16 (41.03)9.20 [2.19-38.67].002
  Fourth35 (67.31)17 (32.69)11.09 [2.69-45.67]< .001
  P for trend  < .001 
Age ≥60 y    
 By median    
  Short11 (23.91)35 (76.09)1.00 
  Long59 (62.77)35 (37.23)6.98 [2.84-17.17]< .001
  By tertile    
  First5 (17.86)23 (82.14)1.00 
  Second17 (42.50)23 (57.50)4.35 [1.26-14.96]0.02
  Third48 (66.67)24 (33.33)12.15 [3.75-39.36]< .001
  P for trend  < .001 
 By quartile    
  First2 (10)18 (90)1.00 
  Second9 (34.62)17 (65.38)6.36 [1.06-37.94].043
  Third15 (45.45)18 (54.55)11.64 [2.08-65.04].0052
  Fourth44 (72.13)17 (27.87)37.12 [6.87-200.64]< .001
  P for trend  < .001 
Only white    
 By median    
  Short22 (27.85)57 (72.15)1.00 
  Long95 (62.09)58 (37.91)4.12(2.22-7.65]< .001
  By tertile    
  First11 (22)39 (78)1.00 
  Second28 (43.08)37 (56.92)3.03 [1.28-7.16].011
  Third78 (66.67)39 (33.33)7.05 [3.16-15.73]< .001
  P for trend  < .001 
 By quartile    
  First6 (17.65)28 (82.35)1.00 
  Second16 (35.56)29 (64.44)2.80 [0.93-8.43].067
  Third29 (49.15)30 (50.85)4.66 [1.64-13.26].0039
  Fourth66 (70.21)28 (29.79)11.46 [4.10-31.99]< .001
  P for trend   < .001

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. REFERENCES

In the current study, we investigated the association of overall RTL in PBLs with the risk of STS. Our novel findings indicate that RTL was significantly longer in patients with STS than in healthy controls. In unconditional logistic regression analysis, individuals with longer telomeres exhibited a nearly 5-fold increased risk of STS, and there was a significant dose-response effect.

There have been numerous epidemiologic studies evaluating the association of leukocyte telomere length with the risk of different cancers, and the association appears to be cancer type-dependent. The majority of studies demonstrated significant associations between short telomeres in PBLs and increased risks of carcinomas, including bladder, esophageal, gastric, head and neck, ovarian, and renal cancer.19-22 There were no significant associations in prostate, breast, or colorectal cancers in several large prospective studies.20-22, 33-37 Mirabello et al evaluated telomere length in PBLs with the risk of osteosarcoma in 98 patients with osteosarcoma and 69 orthopedic controls and did not observe a significant association.23 In contrast, the current study demonstrated that longer RTL in PBLs was associated with an increased risk of STS. Consistent with our finding, Yan et al previously reported long telomeres in tumor tissues from patients with liposarcoma, leiomyosarcoma, and high-grade STS.38

The opposing effect of telomere length on STS and carcinomas may be attributed to their distinct biology. Carcinomas originate from epithelial cells and are far more common in human tumors. They have an in situ stage and usually present in patients aged >50 years. Sarcomas, conversely, are malignant tumors of mesenchymal origin and present in a wide age range.39 Adult human tumors are predominantly epithelial carcinomas, whereas pediatric human tumors and murine tumors are predominantly sarcomas and lymphomas. Longer telomere length in the pediatric population and mice than in human adults has been suggested as a partial explanation for this differential distribution of carcinoma and sarcoma.40 These observations are consistent with our current epidemiologic data indicating an association of longer telomeres with an increased risk of sarcoma.

Although it remains to further investigate the detailed molecular mechanisms, recent studies have suggested that telomere dysfunction has dual roles in cancer progression and carcinogenesis.41 Cells with both very short and very long telomeres may contribute to cancer development. Optimal telomere length is a balance of cell proliferation, senescence, apoptosis, and control. Excessively shortened telomere length may give rise to greater chromosome end-to-end joining, which attenuates DNA damage response and prompts cells to enter mitosis, thereby increasing the potential for genome instability and malignant transformation. In contrast, significantly long telomeres may result in elevated cancer risk by allowing continued cellular proliferation and delaying cellular senescence and apoptosis, thus providing an environment in which cells can accumulate genetic lesions.41 It is worth noting that a previous prospective study reported that longer telomeres in PBLs were associated with an increased risk of non-Hodgkin lymphoma.42 Apparently, the association of long telomeres in PBLs with an increased risk of cancers is not unique to STS. Future studies are warranted to identify additional specific cancer sites with similar associations.

There are a few limitations to this study. First, the small sample size is relatively small because of the rarity of STS. We cannot rule out the possibility of chance findings because of the small sample size. Large studies are needed to confirm our findings. Second, STS is a heterogeneous group of over 50 different histologic subtypes. We could not perform a detailed stratified analysis for different subtypes because of the limited number of each subtype. Nevertheless, when we did analyses of the top 3 subtypes (leiomyosarcoma, liposarcoma, and extraskeletal osteosarcoma), we observed longer telomeres for each of these subtypes compared with controls. Future large studies are needed to evaluate other specific histologic subtypes. Third, although we only included newly diagnosed patients and collected blood samples before treatment, which reduced the effect of disease state and treatment on telomere length, as observed in previous retrospective case control studies,34 we cannot completely overcome the inherited limitation of “reverse causation” in a retrospective case-control study. Future prospective studies are needed to replicate our findings.

In conclusion, this is the first study to evaluate telomere length in PBLs with the risk of STS. Our data demonstrated a significant association between long telomere length in PBLs and an increased risk of sarcoma with a clear dose-response effect. Further validation in prospective studies and investigation of the biologic mechanisms are warranted.

FUNDING SOURCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. REFERENCES

This study was supported by National Cancer Institute grant CA131335, the MD Anderson Cancer Center Research Trust, and University of Texas MD Anderson Cancer Center institutional support for the Center for Translational and Public Health Genomics.

CONFLICT OF INTEREST DISCLOSURES

The authors made no disclosures.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. REFERENCES