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. Author manuscript; available in PMC: 2013 Jul 12.
Published in final edited form as: Cancer Res. 2009 Feb 3;69(4):1604–1614. doi: 10.1158/0008-5472.CAN-08-3028

Telomere attrition in cancer cells and telomere length in tumor stroma cells predicts chromosome instability in esophageal squamous cell carcinoma: a genome-wide analysis

Yun-Ling Zheng 1, Nan Hu 2, Qing Sun 1, Chaoyu Wang 2, Philip R Taylor 2
PMCID: PMC3710128  NIHMSID: NIHMS477919  PMID: 19190333

Abstract

Previous studies demonstrated that chromosomal instability was common in esophageal squamous cell carcinoma (ESCC); however, the mechanisms underlying this instability are unknown. Individuals with deficiencies in telomere maintenance are susceptible to enhanced telomere loss during cell proliferation; such deficiencies could result in telomere dysfunction and genomic instability. We investigated the association between genome-wide chromosomal changes in cancer cells and telomere length/attrition in cancer/stroma cells in 47 ESCC patients. Genome-wide detection of loss of heterozygosity (LOH) was performed using the Affymetrix GeneChip SNP arrays. Telomere length was assessed separately for cancer cells, carcinoma-associated fibroblasts (CAFs), infiltrative lymphocytes, and adjacent normal epithelial cells by quantitative fluorescent in situ hybridization using paraffin-embedded sections. Telomere length differed significantly among cell types, such that length in infiltrative lymphocytes > CAFs > cancer cells. Shortened telomeres were observed in cancer cells in 44 out 47 (94%) of the tumors examined. Telomere length in CAFs was significantly associated with chromosomal instability on 4q and 13q, and lymphocytes telomere length was significantly associated with instability on chromosomal arms 15q. While telomere length in cancer cells was not associated with chromosome arm instability, telomere attrition in cancer cells, defined as the telomere length in CAFs minus the telomere length in cancer cells, was significantly associated with chromosomal instability on 13q and 15q. This study provides the evidence that telomere shortening is a common genetic alteration in ESCC, and that chromosome arm instability is related to both telomere attrition in cancer cells and telomere length in tumor stroma cells.

Keywords: Telomere length, chromosomal instability, esophageal squamous cell carcinoma, telomere dysfunction

Introduction

Esophageal squamous cell carcinoma (ESCC) is the sixth most fatal cancer worldwide (1). There is great geographic variation in the occurrence of this cancer, including exceptional high risk areas such as Shanxi province, a region in north central China with some of the highest esophageal cancer rates in the world (2;3). Although epidemiological studies indicate that tobacco and alcohol are the major risk factors for ESCC in the low-risk regions of Europe and North America, the etiology in high-risk regions remains unclear. Several life style factors and environmental exposures, including nutritional deficiencies, extremely hot food intake, nitrosamines and polycyclic aromatic hydrocarbons exposures, have been considered, but none have been convincingly linked to Shanxi’s high rates of esophageal cancer (4;5). Previous studies of this high-risk region have demonstrated a strong tendency toward familial aggregation (6–8), suggesting that genetic susceptibility may play a significant role in the etiology of esophageal cancer.

Using a genome-wide scan approach, our group has demonstrated that genomic instability, i.e., loss of heterozygosity (LOH), was common in ESCC, and particularly high frequencies of LOH were found on chromosome arms 3p, 4p, 4q, 5q, 9p, 9q, 13q, 15q, 17p and 17q (9;10). In patients with a family history of upper gastrointestinal (UGI) cancer, a very high frequency LOH on chromosome 13q was observed (11;12). However, the molecular mechanisms of chromosomal instability in ESCC remain unknown. One mechanism causing chromosomal instability in ESCC may be related to telomere dysfunction. Telomeres are the specialized DNA-protein structures that cap the ends of linear chromosomes. Telomeres protect chromosomes by preventing chromosome end fusions and also by keeping cells from recognizing their own chromosomal ends as double-strand DNA breaks (13). Critically short telomeres can be a major mechanism for the generation of chromosomal abnormalities via repeated breakage-fusion-bridge (BFB) cycles (14;15). Chromosomal instability caused by dysfunctional telomeres could drive the tumorigenic process by increasing genomic instability, thus resulting in increased mutation rates for oncogenes and tumor suppressor genes (16).

Very short telomeres have been reported as common early alterations in many human cancers, including gastric (17;18), colon (19), lung (20), breast (21), pancreatic (22) and prostate (23) cancers. Short telomeres have also been detected in tissue samples taken from patients with Barrett’s esophagus (BE), which is associated with an increased risk of esophageal adenocarcinoma (24). BE patients whose biopsies showed the shortest telomeres also had the highest degree of chromosomal abnormalities (24). Kammori et al examined tumor tissues from 15 ESCC patients and found that the average telomere length in cancer cells was significantly shorter than in adjacent non-cancer esophageal epithelium (25) and telomere length in non-cancer esophageal epithelium was inversely associated with the frequency of chromosome anaphase/telophase bridges in cancer cells (26). Recently, short telomeres in blood leucocytes were reported to predict cancer risk in patients who were diagnosed with Barrett’s esophagus (27). To understand the role of telomeres in the development of ESCC, we investigated the association of telomere length and chromosome arm specific instabilities in 47 ESCC patients. To the best of our knowledge, this is the first study using a genome-wide approach to investigate if telomere dysfunction could contribute to the chromosome arm specific instabilities associated with the development of ESCC.

Methods

Patient Selection

Patients (N = 47) diagnosed with ESCC between 1998 and 2001 in the Shanxi Cancer Hospital in Taiyuan, Shanxi Province, People’s Republic of China, and considered candidates for curative surgical resection were recruited to participate in this study. None of the patients had prior systemic therapy and Shanxi was the ancestral home for all the participants. After obtaining informed consent, patients were interviewed to obtain information on demographic, clinical, and cancer lifestyle risk factors, including tobacco smoking, alcohol drinking, and family history of cancer etc. Ten milliliters of blood was taken from each consenting patient after the interview. Tumor tissue obtained during surgery was: (i) snap-frozen in liquid nitrogen, along with matching normal tissues, and stored at −130° C; or (ii) fixed in ethanol and embedded in paraffin. This study was approved by the Institutional Review Boards of the Shanxi Cancer Hospital and the US National Cancer Institute.

DNA Extraction

Germ-line DNA was extracted from whole blood using the standard phenol/chloroform method. One 5-micron section was H&E stained and marked by a pathologist as the guide for micro-dissection. Five to ten consecutive 8-micron sections were cut from fresh frozen tumor tissues. Tumor cells were micro-dissected under a light microscope and tumor DNA was extracted followed the protocol from the Puregene DNA Purification Tissue Kit (Gentra Systems, Inc. Minneapolis, MN). 500 – 700 ng of purified DNA were isolated for each tumor samples.

Genome-wide LOH Analysis Using Affymetrix GeneChip SNP Array

The germ-line and tumor DNA samples were analyzed on the Affymetrix 10 K (N=17) or 500 K (N=30) SNP array GeneChips, following the protocol described previously (9) for 10K arrays; the detailed experiment protocol for the 500K array can be found on http://www.affymetrix.com/support/downloads/manuals/500k_assay_manual.pdf. In brief, genomic DNA samples were diluted to approximately 50ng/uL in reduced EDTA TE Buffer (0.1mM EDTA), and assayed according to the GeneChip Mapping Assay manual, supplied by Affymetrix, Inc. A total of 250 ng of germ-line DNA was initially used in the digestion with Nsp I or Sty I for 2 hours in 37°C, and 20 minutes in 65°C. The DNA was then ligated to Nsp I or Sty I adaptors for 3 hours at 16°C, followed by 20 minutes at 70°C prior to PCR amplification. All the steps mentioned above were performed in a pre-PCR clean room. The PCR was started at 94°C for 3 minutes; followed by 30 cycles at 94°C for 30 seconds, 60°C for 30 seconds, and 68°C for 15 seconds. The final extension was done at 68°C for 7 minutes. The PCR product was verified by gel electrophoresis. If the expected product sizes (200 to 2000bp) were observed, then then PCR products were purified using Qiagen MinElute 96 (Qiagen, Valencia, CA) and quantified by spectrophotometer. After successful fragmentation (confirmed by the presence of a smear between 50 to 200bp), the sample was end-labeled with biotin and hybridized onto the array. The chip was hybridized at 49°C for 18 hours, then washed and stained in the GeneChip Fluidics Station 450 following the manufacturer’s instructions. The chip was scanned with the Affymetrix GeneChip Scanner 3000 using GeneChipOperating System version 1.4, and data files were automatically generated. Genotype assignments were generated automatically by GTYPE software (Affymetrix). Genotype calls were defined as AA, AB or BB; “no call” means the SNP did not pass the discrimination filter and was excluded from further evaluation. LOH was defined as a change in the genotyping call from “AB” (heterozygous) in germ-line DNA to “AA” or “BB” (homozygous) in the matched micro-dissected tumor DNA.

Telomere Length Assessment Using Quantitative Fluorescent In Situ Hybridization

Alcohol fixed, paraffin-embedded tissue sections (five micron) were used to measure telomere lengths in four cell types: cancer cells, carcinoma-associated fibroblasts, infiltrative lymphocytes, and normal epithelial cells adjacent to the tumor. The procedure was as follows: The section slides were deparaffinized by incubating in xylene and then hydrated through an ethanol series (100%, 90%, 80% and 70%). The slides were incubated in 10 mM sodium citrate at pH 6.5 and 85°C for 10 minutes and then placed in a RNase solution (40 µg/ml of RNase A) for one hour at 37°C. Slides were then rinsed with deionized water, dipped through an ethanol series (70%, 80%, 90% and 100%), and air dried. Fifteen microliters of hybridization mixture consisting of 0.3 µg/ml Cy3-labeled telomere-specific peptide nucleic acid (PNA) probe (Panagene Inc., Daejeon, Korea), 50% formamide, 10 mM Tris-HCl, pH 7.5, 5% blocking reagent and 1× Denhart’s solution, were applied to each slide and slides were cover-slipped. Slides were then placed in a Hybex microarray hybridization chamber where the DNA was denatured by incubating at 75°C for five minutes, followed by hybridizing at 30°C for three hours. After hybridization, the slides were sequentially washed; once in 1 × SSC, once in 0.5 × SSC and once in 0.1 × SSC; each wash was 10 min at 42°C. The slides were then mounted in anti-fade mounting medium containing 300 ng/ml 4’-6-diamidino-2-phenylindole (DAPI).

The sample slides were analyzed using a Leica DM 4000 epifluorescence microscope equipped with a charge-coupled device (CCD) camera. Fluorescent images were captured with exposure times of 0.1 and 0.05 second for Cy3 and DAPI signals, respectively. An H&E stained adjacent section was used by a senior cancer pathologist (QS) to determine the cell types. Digitized fluorescent telomere signals were quantitated using a semi-automated script, TeloMeter (a kind gift from Dr. Alan Meeker), written with image analysis software (ImageJ). This software permits measurement of telomere signals in individual cells. Image processing was performed as follows: for a given image, the raw Cy3 telomere image was filtered with the background correcting filter. This corrected image was segmented on a gray-value threshold for contouring telomeric spots that were then binarized, creating a mask that was applied to the original telomere fluorescence data. Telomere length was expressed as fluorescent intensity units in thousands (KFIU). Tabulated data were exported to Microsoft Excel for further data analysis. For each patient, thirty cells were analyzed to estimate the mean telomere length for each of the four cell types (cancer cells, normal epithelial cells, infiltrative lymphocytes, and CAFs). Telomere attrition in cancer cells was defined as the telomere length in CAFs minus the telomere length in cancer cells.

Statistical Analysis

Spearman correlations were examined between LOH frequency and telomere length by chromosome arm and cell type. Linear regression was used to analyze the relationship between the LOH frequency on chromosome arms and telomere length, while controlling for age, gender, smoking status, family history of cancer and tumor grade. Chromosome arms with ≥25% LOH frequency (75th percentile value of LOH frequencies of all chromosome arms combined) were considered positive (yes) for chromosomal instability. Wilcoxon-Mann-Whitney tests were used to compare median telomere length between chromosomal instability groups (yes/no). In some analyses, telomere length was dichotomized as short/long using the 50th percentile values in the sample sets as a cut point. Multivariate logistic regression was used to analyze the relationship between chromosome arm instability status and telomere length, while controlling for age, gender, smoking status, family history of cancer and tumor grade. All P-values were two-sided and considered statistically significant if P < 0.05. All analyses were performed using SAS software, version 9 (SAS Institute Inc., Cary, NC).

Results

Characteristics of Study Population

Table 1 lists the characteristics of patients in the study and telomere length by host factors. The mean age of the patients was 55.5 years old. Telomeres in CAFs and infiltrative lymphocytes were significantly shorter in non-smokers compared to smokers. Telomeres in tumor cells, CAFs, and infiltrative lymphocytes tended to be longer in cases with a family history of upper gastrointestinal (UGI) cancer than in cases without such family history.

Table 1.

Distribution of Telomere Length (KFIU) by Host Factors

Host factor N TL in Cancer cells TL in CAFs TL in Lymphocytes Telomere attrition
in Cancer cells
Median P Median P Median P Median P
All subjects 47 60.4 <0.001* 171.4 -- 234.6 0.006† 100.9 --
Age in years
  <56 22 108.8 232.0 245.2 123.2
  >=56 25 78.0 0.966 171.6 0.092 236.8 0.670 93.6 0.359
Gender
  Female 22 61.8 162.7 214.1 89.4
  Male 25 58.4 0.881 177.5 0.159 264.6 0.027 103.3 0.495
Smoking Status
  No 21 60.4 152.9 205.8 83.2
  Yes 26 69.1 0.534 201.5 0.010 263.8 0.036 116.8 0.099
FHC UGI
  No 29 48.2 154.1 222.4 108.9
  Yes 18 111.1 0.014 197.0 0.066 259.0 0.076 84.3 0.304
Tumor Stage
  II 8 45.9 148.7 151.0 83.7
  III 39 63.2 0.515 174.8 0.202 253.7 0.022 108.9 0.258
Tumor Grade
  1+2 37 70.8 187.5 240.7 94.6
  3+4 8 59.4 0.744 158.6 0.229 223.1 0.406 119.2 0.952
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KFIU = fluorescence intensity unit in thousand; TL = telomere length; CAFs = carcinoma-associated fibroblasts; FHC UGI = Family history of upper gastrointestinal (UGI) cancers.

*

P-value comparing telomere length between cancer cells and CAFs

†

P-value comparing telomere length between lymphocytes and CAFs

All P values are two-sided by Wilcoxon-Mann-Whitney test

Characteristics of Telomere Length in Cancer and Stoma Cells

Telomere lengths were significantly different among cell types, such that length in infiltrative lymphocytes > CAFs > cancer cells (Figure 1). The mean telomere length in infiltrative lymphocytes (mean + SD = 240.7 + 90.2 KFIU) was significantly longer than CAFs (199.9 + 113.3, P = 0.004), and cancer cells (92.4 + 89.5, P < 0.001). Mean telomere length was also significantly longer in CAFs than in cancer cells (P < 0.001). In three cases, however, we found longer telomeres in cancer cells than in either CAFs or infiltrative lymphocytes. Telomere length was also determined in normal epithelial cells in the subset of samples (N = 14) in which normal tissue adjacent to tumors was available for telomere analysis. The mean telomere length in normal epithelial cells adjacent to tumors (158.2 + 39.2 KFIU) was not significantly different from mean telomere length in CAFs (186.4 + 74.1, P = 0.232).

Figure 1.

Figure 1

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Representative pictures of telomere FISH with a Cy3-labeled telomere specific PNA probe (red). The nuclei were counterstained with DAPI. Various intensity of red telomere signals on cancer cells (A), CAFs (B), and infiltrative lymphocytes (C). Magnification is 1000×

We also examined telomere length correlation between cell types and found that telomere length in CAFs was significantly correlated with telomere length in infiltrative lymphocytes (r = 0.53, P < 0.001). Slightly lower correlations were seen for telomere length between tumor cells and CAFs (r = 0.37, P = 0.010), and between tumor cells and infiltrative lymphocytes (r = 0.33, P = 0.024). No significant correlation (r = 0.23, P = 0.427) in telomere length between CAFs and normal epithelial cells adjacent to tumors was seen.

LOH Frequency by Chromosome Arm

Prior to the availability of 500 K SNP array chips, 17 tumor samples were analyzed using the 10 K SNP array chips. In five of these samples, the percentage of informative SNPs (SNPs showing heterozygosity) was low (<20%), resulting in sparse data for many chromosome arms (especially for small chromosomes), and prevented the accurate estimation of LOH frequencies. Thus, we excluded these five cases from the statistic analysis, which left a final data set of 42 cases with genome-wide LOH data. The mean frequency of LOH for all the chromosome arms combined (overall) was 18.7% and the mean frequency of LOH for individual chromosome arms varied widely, ranging from 8% to 48%. High average frequencies of LOH (≥ 25%) were observed on chromosomes 3p, 4p, 4q, 5q, 9p, 9q, 11q, 13q, 17p, 17q, 18q, 21q.

Telomere Length and Chromosomal Instability

We initially examined telomere length and LOH frequency as continuous variables using Spearman rank correlations (Table 2). Significant correlations were observed between telomere length and LOH frequency: (i) for cancer-associated fibroblasts on chromosomes arms 1p, 1q, 3q, 4p, 4q, 5q, and 13q; (ii) for infiltrative lymphocytes on 3q, 4p, and 4q; and (iii) for cancer cells on 3q. Telomere attrition in cancer cells (defined as telomere length in CAFs minus the telomere length in cancer cells) was significantly correlated with LOH frequency on chromosome arms 1p, 6q, 13q and 15q. We defined telomere attrition in cancer cells using CAFs as the reference cell type because most previous studies have used tumor stromal cells as the reference cells (23;28–30) and defined telomere attrition as the difference between telomere length in cancer cells and telomere length in stromal cells (28) or as the ratio of telomere length in cancer cells to stromal cells (30). Multiple linear regressions, shown in Table 3, revealed that telomere length was significantly associated with LOH frequency: (i) for CAF cells on chromosome arms 4p, 4q, 5p, 5q, 6q, 10q, 12p, 12q, 13q, 15q, 16p, and 16q; (ii) for infiltrative lymphocytes on 4q, 10q, 12q, 15q, and 16p; and (iii) for cancer cells on 12q. Telomere attrition in cancer cells was significantly associated with LOH frequency on chromosome arms 5p, 5q, 6q, 15q, 16p, and 16q.

Table 2.

Spearman Correlations between Telomere Length or Attrition and LOH Frequency by Chromosome Arm and Cell Type

Chromosome
arm LOH		 TL in Cancer cells TL in CAFs TL in Lymphocytes Telomere attrition in
Cancer cells
r P r P r P r P
1p −0.059 0.711 0.402 0.008 0.096 0.547 0.320 0.039
1q 0.125 0.430 0.315 0.042 0.150 0.344 0.198 0.208
2p 0.142 0.368 0.123 0.436 0.013 0.937 −0.167 0.289
2q 0.025 0.873 0.213 0.176 0.111 0.485 0.061 0.701
3p 0.147 0.353 0.158 0.318 0.131 0.409 0.033 0.837
3q 0.338 0.029 0.320 0.039 0.326 0.035 0.027 0.865
4p 0.144 0.363 0.376 0.014 0.307 0.048 0.192 0.222
4q 0.124 0.433 0.422 0.005 0.357 0.020 0.256 0.102
5p 0.053 0.737 0.291 0.062 −0.131 0.408 0.189 0.230
5q 0.132 0.405 0.316 0.041 0.224 0.146 0.205 0.193
6p −0.014 0.928 0.021 0.892 0.207 0.188 0.056 0.723
6q −0.115 0.469 0.213 0.175 0.076 0.634 0.321 0.038
7p 0.193 0.221 0.174 0.270 0.042 0.791 0.004 0.981
7q 0.183 0.246 0.221 0.159 0.060 0.706 0.030 0.852
8p −0.286 0.067 −0.015 0.922 −0.254 0.105 0.179 0.256
8q −0.007 0.965 −0.013 0.935 −0.188 0.231 0.014 0.931
9p 0.239 0.127 0.069 0.664 −0.037 0.818 −0.113 0.478
9q 0.048 0.765 0.090 0.572 −0.079 0.619 0.000 0.998
10p 0.126 0.427 0.007 0.964 −0.025 0.876 −0.125 0.430
10q 0.099 0.533 0.220 0.162 0.285 0.067 0.005 0.973
11p −0.009 0.953 0.171 0.278 0.020 0.898 0.121 0.444
11q 0.199 0.205 0.077 0.626 0.072 0.651 −0.112 0.479
12p 0.046 0.773 0.165 0.295 −0.137 0.386 −0.028 0.860
12q 0.091 0.568 0.242 0.123 −0.012 0.940 0.095 0.550
13q 0.038 0.811 0.495 <0.001 0.234 0.136 0.318 0.040
14q 0.044 0.780 −0.184 0.244 0.057 0.720 −0.132 0.405
15q 0.122 0.439 0.293 0.050 0.225 0.152 0.325 0.036
16p −0.115 0.469 0.029 0.875 0.035 0.827 0.109 0.493
16q −0.063 0.690 0.131 0.405 0.033 0.833 0.216 0.170
17p 0.049 0.757 0.020 0.900 −0.088 0.577 −0.119 0.454
17q −0.044 0.782 0.144 0.364 0.115 0.469 0.025 0.875
18p 0.131 0.407 −0.065 0.682 0.068 0.668 −0.111 0.484
18q −0.031 0.844 0.208 0.186 0.028 0.862 0.134 0.399
19p 0.156 0.323 0.147 0.352 0.041 0.797 −0.017 0.915
19q 0.231 0.141 0.204 0.195 −0.081 0.607 −0.039 0.804
20p −0.109 0.494 0.109 0.493 −0.196 0.214 0.083 0.600
20q −0.109 0.491 0.200 0.204 −0.044 0.780 0.107 0.280
21q 0.201 0.201 0.229 0.145 −0.017 0.916 −0.064 0.689
22q −0.055 0.730 −0.041 0.795 −0.216 0.170 0.050 0.755
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LOH = loss of heterozygosity; TL = telomere length; CAFs = carcinoma-associated fibroblasts; r is the correlation coefficient; P = p-value

Table 3.

Multiple Linear Regression Analyses Predicting LOH Frequency from Telomere Length or Attrition by Chromosome Arm and Cell Type

% of LOH by
Chromosome
arm		 TL in Cancer cells TL in CAFs TL in Lymphocytes Telomere attrition in
cancer cells
Slope SE P Slope SE P Slope SE P Slope SE P
1p −2.9 6.6 0.668 11.9 6.8 0.089 5.5 5.5 0.328 11.0 5.7 0.069
1q −1.0 5.8 0.864 1.1 6.2 0.864 3.4 4.8 0.487 1.6 5.2 0.767
3q 3.3 5.4 0.546 4.4 5.8 0.453 5.5 4.5 0.230 4.3 4.9 0.931
4p 15.7 9.6 0.112 26.0 9.7 0.011 13.2 8.1 0.112 5.6 8.9 0.531
4q 14.2 9.4 0.138 31.8 8.8 0.001 20.9 7.3 0.007 10.8 8.5 0.209
5p −1.3 5.2 0.807 11.5 5.2 0.036 3.6 4.3 0.412 9.0 4.4 0.048
5q −2.9 8.7 0.738 23.1 8.4 0.010 11.8 7.0 0.101 18.5 7.1 0.014
6q −4.1 7.0 0.556 15.4 7.0 0.035 7.6 5.7 0.195 14.1 5.8 0.020
10q 5.0 7.8 0.531 18.2 7.8 0.027 16.8 6.0 0.008 8.7 6.9 0.214
12p 10.6 5.6 0.066 14.3 5.8 0.019 −1.1 5.0 0.831 1.6 5.3 0.757
12q 11.4 4.4 0.014 19.2 4.0 <0.001 9.8 3.7 0.012 4.3 4.2 0.316
13q 7.7 9.6 0.429 27.1 9.3 0.006 10.2 7.9 0.208 12.8 8.4 0.134
15q 3.7 8.6 0.674 28.4 7.9 0.001 16.8 6.7 0.016 16.9 7.2 0.024
16p −4.9 5.4 0.370 14.4 5.4 0.011 10.0 4.3 0.026 14.0 4.3 0.003
16q −2.2 6.1 0.723 15.9 6.0 0.011 8.9 4.9 0.080 13.0 5.0 0.015
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LOH = loss of heterozygosity; TL = telomere length; CAFs = carcinoma-associated fibroblasts

Adjusted for age, gender, smoking status, tumor grade, family history of UGI cancer

All the values for slope and standard error (SE) are × 10−4.

Table 4 shows telomere length by chromosome instability status (chromosome instability was defined as LOH ≥ 25%) for the various cell types studied. These data indicate that significantly longer median telomere length was observed: (i) in CAFs from patients with chromosome instability on 3q, 4p, 4q, 5q, 6q, 10q, 12p, 12q, 13q, 15q, 16q, and 20q; and (ii) in infiltrative lymphocytes from patients with chromosome instability on 4q, 6p, 10q, 12q, 15q, 16p, and 16q. In addition, patients with chromosome instability on 15q, 16p, and 16q showed significantly higher levels of telomere attrition in their tumor cells than in patients without such chromosome arm instability (Table 4). We used 25% LOH as a cut point to define chromosome arm instability status because 25% LOH is approximately the 75th percentile of overall LOH frequency in this sample set. We understand this cut point is somewhat arbitrary and have explored other cut point, i.e. 40% LOH as cut point. We found only one or two subjects (depending on which specific chromosome arm) were classified differently if 40% LOH was used as cut point and the data support the same conclusion as when 25% LOH was used as a cut point.

Table 4.

Distribution of Median Telomere Length by Chromosome Arm Instability Status

Chromosome
Instability† 		N TL in Cancer cells TL in CAFs TL in Lymphocytes Telomere attrition in
cancer cells
Median P Median P Median P Median P
1p No 36 58.4 154.1 209.8 93.5
Yes 6 51.6 0.857 232.1 0.057 279.6 0.265 173.3 0.052
1q No 35 58.4 154.1 208.1 94.6
Yes 7 79.8 0.649 228.3 0.076 305.5 0.076 174.4 0.088
2p No 36 54.6 159.3 209.8 104.1
Yes 6 93.9 0.590 270.3 0.172 302.8 0.098 92.6 0.886
2q No 35 58.4 164.5 211.5 104.8
Yes 7 60.4 0.933 228.3 0.555 277.3 0.389 84.3 0.748
3p No 21 48.2 167.3 211.5 103.3
Yes 21 70.8 0.359 154.0 0.521 234.6 0.346 100.9 0.734
3q No 36 54.6 154.1 209.8 98.9
Yes 6 119.0 0.196 246.2 0.037 267.3 0.196 141.2 0.495
4p No 22 49.6 153.5 216.9 93.5
Yes 20 69.1 0.290 205.3 0.039 220.2 0.268 110.4 0.597
4q No 24 54.6 153.5 196.6 89.0
Yes 18 64.0 0.594 222.3 0.007 244.1 0.013 122.7 0.127
5p No 39 58.4 164.5 211.5 100.9
Yes 3 109.1 0.574 312.3 0.097 328.4 0.449 173.4 0.213
5q No 28 48.6 153.5 207.0 88.4
Yes 14 65.6 0.392 218.6 0.045 244.1 0.182 119.2 0.098
6p No 34 54.6 159.3 206.0 98.9
Yes 8 63.9 0.798 222.3 0.224 278.1 0.025 141.2 0.179
6q No 35 58.4 154.1 208.1 94.6
Yes 7 79.8 0.649 224.2 0.035 278.8 0.151 181.5 0.061
7p No 35 50.9 154.1 211.5 94.6
Yes 7 67.5 0.428 234.4 0.095 328.4 0.109 116.0 0.194
7q No 35 58.4 154.1 208.1 94.6
Yes 7 40.8 0.906 312.3 0.045 328.4 0.076 174.4 0.142
8p No 28 61.8 168.0 246.0 89.0
Yes 14 36.6 0.157 158.6 0.979 192.5 0.142 112.5 0.274
8q No 33 58.4 164.5 234.6 94.6
Yes 9 58.4 0.748 167.3 0.915 204.0 0.453 103.3 0.818
9p No 17 45.5 171.4 240.7 103.3
Yes 25 67.5 0.434 154.0 0.949 204.0 0.405 100.9 0.635
9q No 20 54.6 159.3 231.5 98.9
Yes 22 63.0 0.821 172.4 0.801 204.9 0.546 102.9 0.980
10p No 32 49.6 159.3 216.9 98.9
Yes 10 88.3 0.249 195.8 0.249 220.2 0.595 102.9 0.768
10q No 32 54.6 154.1 206.0 98.9
Yes 10 89.1 0.497 226.3 0.048 292.8 0.007 115.2 0.637
11p No 29 58.4 154.1 222.4 94.6
Yes 13 58.4 0.967 220.4 0.321 205.8 0.775 108.9 0.438
11q No 26 47.3 165.9 216.9 106.1
Yes 16 75.3 0.170 170.8 0.407 229.8 0.393 83.4 0.623
12p No 34 49.6 153.6 216.9 98.9
Yes 8 94.5 0.249 232.1 0.012 221.9 0.798 112.8 0.564
12q No 38 58.4 154.1 207.0 97.7
Yes 4 92.4 0.549 318.9 0.004 371.5 0.011 182.4 0.103
13q No 21 58.4 145.8 211.5 84.3
Yes 21 58.4 1.00 190.2 0.019 224.9 0.399 113.0 0.222
14q No 30 49.6 176.1 216.9 106.9
Yes 12 73.7 0.867 147.8 0.278 239.6 0.522 55.5 0.290
15q No 30 48.6 151.4 204.9 84.9
Yes 12 75.3 0.181 226.3 0.002 270.9 0.042 165.0 0.008
16p No 37 58.4 154.1 205.8 94.6
Yes 5 48.2 0.801 220.4 0.055 305.5 0.005 181.5 0.019
16q No 36 59.4 153.5 207.0 93.5
Yes 6 48.5 1.00 227.4 0.024 317.0 0.031 158.8 0.031
17p No 19 50.9 154.1 240.7 103.3
Yes 23 67.5 0.791 167.3 0.553 204.0 0.640 100.9 0.658
17q No 26 59.4 160.7 223.6 97.7
Yes 16 44.5 0.756 176.0 0.660 204.9 0.569 110.4 0.856
18p No 33 50.9 154.0 208.1 94.6
Yes 9 67.5 0.657 177.5 0.238 262.9 0.172 108.9 0.399
18q No 26 54.6 153.5 206.0 97.7
Yes 16 63.0 0.877 1724 0.214 244.1 0.254 119.2 0.407
19p No 36 58.4 154.1 209.8 97.7
Yes 6 88.2 0.640 266.4 0.072 317.0 0.184 177.9 0.172
19q No 31 50.9 154.1 222.4 95.6
Yes 11 70.8 0.764 187.5 0.247 194.9 0.875 108.9 0.415
20p No 38 59.4 159.3 216.9 93.5
Yes 4 40.8 0.466 239.8 0.170 261.6 0.578 155.5 0.054
20q No 36 54.6 154.1 216.9 93.5
Yes 6 92.9 0.615 231.3 0.037 261.6 0.350 119.2 0.184
21q No 29 58.4 154.1 222.4 100.9
Yes 13 58.4 0.924 177.5 0.523 204.0 0.540 108.9 0.881
22q No 35 58.4 164.5 223.3 95.6
Yes 7 67.5 0.774 199.5 0.601 236.7 0.933 113.5 0.578
Open in a new tab

TL = telomere length; CAFs = carcinoma-associated fibroblasts

†

chromosome arm instability was defined as the frequency of loss of heterozygosity ≥ 25% of informative markers tested for the specific chromosome arm.

Finally, Table 5 shows multivariate logistic regression analyses in which both our endpoint (chromosome instability, ≥ 25% vs < 25%) and primary exposure (telomere length, long vs short) were dichotomized. For these analyses, telomere length was dichotomized into long/short groups using the median value as a cutoff point. After adjustment for age, gender, smoking status, and tumor grade, long telomeres were significantly associated with chromosome instability: (i) in CAFs for chromosomes 4q and 13q, with adjusted odds ratios (OR) of 4.4 (P = 0.040) and 11.9 (P = 0.007), respectively; and (ii) in infiltrative lymphocytes for chromosome 15q, adjusted OR of 7.5 (P = 0.048). While multivariate logistic regression found no association between telomere length in cancer cells and chromosomal instability, telomere attrition in cancer cells was found significantly associated with instability for chromosomes 13q and 15q, with adjusted ORs of 6.0 (P = 0.038) and 14.3 (P = 0.025), respectively. Because the LOH data were from two types of Affymetrix chips (10K and 500K), we also tested the logistic models to include chip-type (10K or 500K) and found the adding chip-type into the models did not have any significant affect on the estimated odd ratios (data not shown).

Table 5.

Logistic Regression Analysis Examining the Association of Telomere Length and Chromosome Arm Instability

Chromosome
Instability† 		TL in cancer cells TL in CAFs TL in lymphocytes Telomere attrition in cancer cells
S, L OR (95% CI) P S, L OR (95% CI) P S, L OR (95% CI) P Lo, H OR (95% CI) P
4p No 8, 14 1.00 14, 8 1.00 13, 9 1.00 12, 10 1.00
Yes 12, 8 2.87(0.75, 11.0) 0.124 8, 12 2.67 (0.68, 10.4) 0.157 10, 10 1.33 (0.37, 4.81) 0.666 8, 12 1.95(0.52, 7.34) 0.324
4q No 10, 14 1.00 16, 8 1.00 15, 9 1.00 14, 10 1.00
Yes 10, 8 1.89(0.51, 6.97) 0.342 6, 12 4.39 (1.07, 18.0) 0.040 8, 10 2.19(0.59, 8.19) 0.243 6, 12 2.93(0.76, 11.3) 0.119
5p No 18, 21 1.00 21, 18 1.00 22, 17 1.00 19, 20 1.00
Yes 2, 1 1.58(0.11, 22.0) 0.739 1, 2 1.05(0.05, 20.6) 0.974 1, 2 2.51(0.14, 45.7) 0.534 1, 2 1.47(0.08, 27.4) 0.795
5q No 12, 16 1.00 17, 11 1.00 17, 11 1.00 16, 12 1.00
Yes 8, 6 2.32(0.53, 10.2) 0.266 5, 9 4.39(0.90, 21.3) 0.067 0.067 6, 8 1.82(0.44, 7.56) 0.412 4, 10 3.72(0.81, 17.1) 0.091
6q No 16, 19 1.00 20, 15 1.00 21, 14 1.00 18, 17 1.00
Yes 4.3 2.00(0.34, 11.9) 0.445 2, 5 4.18(0.61, 28.9) 0.147 2, 5 3.64(0.53, 24.9) 0.189 2, 5 2.55(0.40, 16.5) 0.324
10q No 14, 18 1.00 19, 13 1.00 20, 12 1.00 16, 16 1.00
Yes 6, 4 2.59(0.53, 12.5) 0.238 3, 7 4.71(0.87, 25.6) 0.072 3, 7 4.92(0.87, 27.9) 0.072 4, 6 1.33(0.29, 6.19) 0.714
12p No 14, 20 1.00 20, 14 1.00 19, 15 1.00 17, 17 1.00
Yes 6, 2 5.31(0.74, 38.2) 0.097 2, 6 3.66 (0.51, 26.2) 0.196 4, 4 1.60(0.26, 9.78) 0.614 3, 5 1.67(0.29, 9.67) 0.568
12q No 18, 20 1.00 22, 16 23, 15 19, 19 1.00
Yes 2, 2 1.42(0.16, 12.5) 0.755 0, 4 NA 0, 4 NA 1, 3 2.35(0.20, 27.4) 0.495
13q No 10, 11 1.00 15, 6 1.00 12, 9 1.00 13, 8 1.00
Yes 10, 11 1.18(0.29, 4.80) 0.817 7, 14 11.9(1.95, 73.3) 0.007 11, 10 1.08(0.27, 4.33) 0.915 7, 14 5.99(1.1, 32.6) 0.038
15q No 13, 17 1.00 19, 11 1.00 20, 10 1.00 18, 12 1.00
Yes 7, 5 2.00(0.36, 11.1) 0.425 3, 9 6.12(0.86, 43.7) 0.071 3, 9 7.50(1.02, 55.1) 0.048 2, 10 14.3(1.40, 146) 0.025
16p No 18, 19 1.00 21, 16 1.00 23, 14 19, 18 1.00
Yes 2, 3 1.39(0.10, 18.9) 0.803 1, 4 7.88(0.44, 140) 0.160 0, 5 NA 1, 4 3.86(0.17, 86.7) 0.395
16q No 18, 18 1.00 21, 15 1.00 22, 14 1.00 19, 17 1.00
Yes 2, 4 0.51(0.05, 5.2) 0.571 1, 5 55.2(0.81, >999) 0.063 1, 5 34.5(0.44, >999) 0.112 1, 5 3.28(0.27, 39.9) 0.352
Open in a new tab
†

chromosome arm instability was defined as the frequency of loss of heterozygosity ≥ 25% of informative markers tested for the specific chromosome arm.

TL = telomere length; CAFs = carcinoma-associated fibroblasts; S = short; L = long; Lo = low level; and H = high level.

The ORs (odds ratio) were adjusted for age, gender, smoking status and tumor grade

Discussion

Genomic instability has been proposed to play an important role in cancer by accelerating the accumulation of genetic changes responsible for cancer cell evolution (31). Previous studies by our group and others demonstrated that chromosomal abnormalities were frequent in ESCC and commonly involve chromosomes 3p, 4p, 4q, 5q, 9p, 9q, 11q, 13q, 15q, 17p and 17q (9–12). However, the molecular mechanisms underlying this chromosome instability are unclear. In the present study, we demonstrated that high level of telomere attrition in cancer cells was significantly associated with specific chromosome arm instabilities in ESCC. Our findings here are consistent with previous reports that telomere shortening is associated with chromosome instability in ESCC tumors (26), in Barrett’s esophagus (24), and in tissues taken from patients with ulcerative colitis, which is associated with increased risk of colon cancer (30). Kammori et al examined tumors from 15 ESCC patients and found that telomere length in normal epithelial cells adjacent to tumor was inversely associated with the frequency of chromosome anaphase/telophase bridges and aneuploidy in tumor cells (26). Finley et al examined 11 biopsies from Barrett’s esophagus patients and found that high telomere attrition in epithelial cells significantly correlated with chromosome abnormalities for chromosomes 17 and 11, but not for chromosome 9 (24). Using a genome-wide scan approach, we discovered that high level telomere attrition in cancer cells was significantly associated with instability on chromosomes 13q and 15q in ESCC. To the best of our knowledge, this is the first study to report that telomeres are involved in the chromosome arm specific instabilities in ESCC.

Surprisingly, we also found that long telomeres in tumor stroma cells (carcinoma-associated fibroblasts and infiltrative lymphocytes) were significantly associated with instability on chromosomes 4q, 13q and 15q. This finding is not entirely consistent with previous reports that short telomeres in epithelial cells/cancer cells are associated with chromosome abnormalities in human cancers (32–34). However, these previous studies only examined the telomere length in cancer cells or epithelial cells of preneoplastic lesions. No previous study has examined telomere lengths in CAFs and infiltrative lymphocytes and their relationship to chromosome instability in cancer cells. Telomere lengths measured in tumor stroma cells may not be directly comparable to telomere length in cancer cells or epithelial cells of preneoplastic lesions. Shorter telomeres may either have been inherited as a constitutional trait or may have been acquired somatically because of attrition induction by tissuespecific environmental factors, i.e., excessive proliferation. The reduction in telomere length in epithelial cells of preneoplastic lesions may simply reflect a greater number of times that the preneoplastic epithelium has replicated, compared to the surrounding stroma. In the present study, we found that telomeres in stroma cells are significantly longer than in neighboring cancer cells and that there is no significant telomere length correlation between stroma cells and normal epithelial cells adjacent to tumor, and only a weak telomere length correlation between stroma cells and cancer cells in ESCC. These data suggested that cancer cells and stroma cells in ESCC may have experienced different tissue-specific micro-environment of telomere loss/maintenance. We speculate that telomere maintenance in the tumor stroma may be altered to facilitate the development of tumors with high chromosome instability. Previous studies have demonstrated that tumor stroma play a significant role in the initiation and progression of carcinomas (35;36). Reactive tumor stroma differs from normal stroma; it has a reactive phenotype that is associated with an increased number of fibroblasts, enhanced capillary density, and increased type-I-collagen and fibrin deposition. Reactive tumor stroma cells have been shown to provide oncogenic signals that facilitate tumorigenesis (37;38). Extensive gene expression changes and neoplastic-specific changes were observed in the CAFs of breast cancer (39;40). However, the role of telomeres in the reactive tumor stroma in the initiation/progression of ESCC is completely unknown and is an area that warrants further investigation.

Our data suggest that telomere length is associated with chromosome instability only on specific chromosome arms (4q, 13q and 15q). This observation raises the question as to whether these chromosome arms possess generally shorter telomeres than other chromosome arms in ESCC patients. It has been reported that average telomere length may be less important than short telomeres on specific chromosome arms since telomere dysfunction occurs preferentially on chromosomes with critically short telomeres (41). In humans, chromosome specific telomere lengths are highly polymorphic between chromosome arms (42–44) and the telomere length patterns on chromosome arms appear to be heritable (45;46). Several reports have suggested that telomere shortening does not occur at the same rate for all telomeres (47). This view is supported by several studies which demonstrated that those chromosome arms with the shortest telomeres were more often found in the telomere fusions leading to chromosome instability (41;48;49). A recent study compared telomere length between normal breast epithelium, ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC) from 18 patients and found that the shortening of telomeres on chromosome 17q is greater than the average shortening of all telomeres (50). Future studies that examine specific chromosome arm telomere lengths may provide new insights into the molecular mechanisms controlling the chromosome instability commonly observed in epithelial cancers.

We also observed that telomere length differed significantly among cell types, such that length in infiltrative lymphocytes > CAFs > cancer cells. Short telomeres were observed in cancer cells in 44 of 47 (94%) tumors examined, suggesting that telomere shortening is a common genetic alteration in ESCC. This observation is consistent with most previous reports of telomere length in various cancer types. In cancer cells, telomere length varies widely and its equilibrium depends on the balance between telomere shortening from cell division and telomere elongation from telomerase activity (51). Telomerase is a reverse transcriptase that synthesizes and adds the telomeric repeats onto the end of chromosome. Very short telomeres have been reported as common early alterations in many human cancers, including gastric (17;18), colon (19), esophageal (25;26), lung (20;52), breast (21), pancreatic (22), and prostate (23) cancers. In contrast, some tumor types have longer telomeres in cancer cells than in normal cells; for example, intracranial tumors, basal cell carcinomas of the skin, and renal cell carcinoma (54). Our results indicate that shortened telomeres are a common genetic alteration in ESCC, which is consistent with previous reports (25;26).

In conclusion, our data provide further evidence that telomere shortening is a common genetic alteration in ESCC, and that chromosome instability is related to both telomere attrition in cancer cells and telomere length in tumor stroma cells. The data provide new clues for understanding the molecular mechanisms of chromosome arm specific instabilities in ESCC and suggest that genetic defects in telomeres may be involved in the development of ESCC.

Acknowledgements

We thank Dr. Alan Meeker of Johns Hopkins University for providing Telometer software, Dr. Stephen Hewitt of NCI for reviewing the slides used for microdissection, and Shanxi Cancer Hospital of China for providing the tumor tissues. This study is partly supported by a Lombardi Comprehensive Cancer Center Support grant (2P30 CA051008-13) and intramural research funds of the US National Cancer Institute.

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