| | Comparative genomic hybridization array analysis and real time PCR reveals genomic alterations in squamous cell carcinomas of the lungReceived 1 June 2006; received in revised form 7 September 2006; accepted 20 September 2006. Summary Genomic alterations have been identified in lung cancer tissues and reported in numerous studies. To analyze genomic aberrations in lung cancer patients, we used array comparative genomic hybridization (array CGH) in 14 squamous cell lung carcinoma (SqC) tissues. Copy number gain and loss in chromosomal regions were detected, and the corresponding genes were confirmed by real time PCR. Several frequently altered loci, including gain of 3q (36% of samples), were found. The most frequently identified losses were found at 14q32.33 (21% of samples). The relative degree of chromosomal change was analyzed using log2 ratios. High-level DNA amplifications (>0.8 log2 ratio) were detected at 20 regions in 1p, 2q, 3q, 4q, 6q, 7p, 8q, 9p, 10q, 12q, 14q and 19p. We found that the fold change levels were highest at EVI1 (3q26.2), LPP (3q27-28) and FHF-1 (3q28) gene loci. Our results show that array CGH is a useful tool for identification of gene alteration in lung cancer, and that the above-mentioned genes might represent potential candidate genes for pathogenesis and diagnosis of lung cancer. 1. Introduction  Lung cancer is responsible for the highest number of cancer-related deaths in the world. The two most common histological subtypes are adenocarcinoma (AdC) and squamous cell carcinoma (SqC) of non-small cell lung carcinoma (NSCLC); approximately 80–90% of cancer-related deaths involve NSCLC [1]. Lung tumorigenesis undergoes a process of multiple and sequential morphological and molecular changes [2]; although a significant effort has been directed toward increasing the cure rate for lung cancer, the results for improved diagnosis and treatment have not been satisfactory [3]. Thus, it is of great importance to elucidate the mechanisms involved in human lung cancer carcinogenesis at the cellular and molecular levels so that advances in diagnosis and treatment can lead to improved patient outcomes. Genetic aberrations at the DNA copy number level, such as deletions, amplifications and unbalanced translocations, are important pathogenetic mechanisms that underlie human genetic disorders (http://www.ncbi.nlm.nih.gov/disease/). Analysis of chromosomal aberrations is particularly important in cancer, where amplification of oncogenes and/or deletion of tumor suppressor genes are involved in the multi-step process of cancer development [4]. Efforts to elucidate cytogenetic alterations, involved in lung cancer tumorigenesis, are increased in focusing of charting molecular genetic events; with the goals of improving early detection and providing new therapeutic targets [5]. Consistent chromosomal changes are indicative of critical molecular events involved in tumorigenesis [6]. The array CGH technique provides co-hybridization of a differentially labeled specimen, and reference genomic DNAs, to an array of large insert genomic clones. The inserted genomic clones, spotted on glass slides, allows for the fully reproducible detection of single-copy gains and losses in the analyzed DNA. The application of array CGH analysis, and other molecular cytogenetic techniques, to the study of lung carcinomas has led to the identification of recurring genomic imbalance in SqC [5], [7], [8], [9], [10]. In this study, we analyzed 14 lung SqC specimens using the array CGH method with a BAC clone-based platform for characterization of copy number alterations. DNA copy number fold changes, for a subset of gained or lost gene, were confirmed by real time PCR. 2. Materials and methods 2.1. Tumor samples Fourteen lung SqC samples were collected from patients with histologically confirmed lung SqC at the Department of Internal Medicine at St. Mary's Hospital, Korea, after informed consent was obtained. Samples were collected from 1 woman and 13 men, aged 47–80 years (mean age ±standard deviation, 64.45±7.45 in years); the samples were examined histologically before they were used to ensure that at least 80% of the tumor by area was present and that samples were staged correctly according to the TNM (tumor, nodes, and metastases) classification of malignant tumors. The clinicopathological characteristics of the samples are shown in Table 1, and Subjects were categorized according to smoking status as follows: (a) nonsmokers (n=7) were defined as those patients who had smoked <100 cigarettes during their lifetime; and (b) smokers (n=7) were current or former smokers who had at least a 20-pack/year(s) history of cigarette smoking (pack-year(s)=number of packs of cigarettes smoked per day multiplied by the number of years of smoking). Each tissue sample was incubated at 55°C for over night with cell lysis buffer and 10μl proteinase K (>600mAU/ml) (Qiagen, Hilden, Germany). The genomic DNA was extracted using the Puregene DNA isolation kit (Qiagen, Hilden, Germany). The reference DNA was pooled from 10 gender-matched (male), normal, healthy control subjects. | | |  | Characteristic | No. of patients (n=14 patients) | |
|---|
| Gender | | | Female | 1 | | | Male | 13 | | | | | | Age (years) | | | Range | 47–80 | | | Mean±S.D. | 64.45±7.45 | | | | | | Tumor size (cm) | | | Range | 1.0–7.5 | | | Mean±S.D. | 3.7±1.9 | | | | | | Tumor differentiation | | | Well | 1 | | | Moderate | 11 | | | Poor | 2 | | | | | | TNM classification | | | Tumor status | | | T1 | 5 | | | T2 | 7 | | | T3 | 2 | | | T4 | 0 | | | | | | Lymph node status | | | NX | 0 | | | N0 | 6 | | | N1 | 6 | | | N2 | 2 | | | N3 | 0 | | | | | | Metastatic status | | | MX | 0 | | | M0 | 14 | | | M1 | 0 | | | | | | Tumor stage | | | Stage I | 5 | | | Stage II | 7 | | | Stage III | 2 | | | Stage IV | 0 | | | | |
2.2. Array CGH analysis Array CGH was performed using the MACArray™-Karyo 1.4K BAC-chip (Macrogen, Seoul, Korea) which contains 1440 bacterial artificial chromosome (BAC) clones in triplicate on the whole human genome with a resolution of about 2.3Mbp. Each DNA (tumor and reference DNAs) sample (500–700ng) was denatured in the presence of random primer and reaction buffer (BioPrime® DNA Labeling System, Invitrogen, Carlsbad, CA) at 98–100°C for 5min, and then cooled on ice for 5min. The denatured DNA was differentially labeled with 3μl of 1mM Cy3- and Cy5-conjugated dCTP by random primed labeling (Perkin Elmer, Boston, MA). The mixture was incubated with a Klenow fragment at 37°C overnight. After labeling, unincorporated nucleotides were removed using MicroSpin™ G-50 columns (Amersham Biosciences, Buckinghamshire, UK). Cy3 and Cy5 labeled test DNA and reference DNA were mixed with 50μg of human Cot-1 DNA for blocking of repeat sequences. After purification, this mixture was resolved in hybridization buffer (Macrogen, Seoul, Korea) containing yeast tRNA for blocking of non-specific nucleotides binding. After the MACArray™-Karyo 1.4K BAC-chip was pre-hybridized in hybridization buffer with salmon sperm DNA for 1h, chips were hybridized with the purification mixture. Then it was incubated for 72h in the 37°C hybridization chamber. After hybridization was complete, array chips were washed in 50% formamide-2x SSC at 46°C for 15min, and then 0.1% SDS-2x SSC at 46°C for 30min. In the next step, the chips were washed in 50% sodium phosphate-0.1% NP40 for 15min followed by washing with in 2x SSC for 15min at room temperature. After spin drying, hybridized arrays were scanned with a MAC Viewer™ (Macrogen, Seoul, Korea). 2.3. Data analysis The scanned images were analyzed to determine Cy3:Cy5 ratios for each array element using MAC Viewer v1.6.3. Software (Macrogen, Seoul, Korea). Data are presented as log2 (Cy3 intensity/Cy5 intensity ratios) plotted against the position of clones within a particular chromosome in the region of the genome. Fluorescence ratios of scanned images of the arrays were calculated, and the raw array CGH profiles were processed to identify statistically significant differences in copy number using a segmentation algorithm, which uses permutation to determine the significance of change points in the raw data. Ratios were normalized by using the median of fluorescence ratios computed as log2 values from the housekeeping DNA control fragments linearly distributed across the genome. Thereafter, the ratios of the two color-switch hybridizations were averaged and normalized (data not shown). Based on the ratios of clones mapping to chromosome X in a hybridization of normal male versus normal female DNA, a specific amplicon was determined (Fig. 1). The X and Y chromosomes were excluded from the analysis in the tumor samples since female tumor DNA was hybridized with male control DNA to serve as an internal control, and was used to detect genomic imbalances. A ratio of 1.0 indicated a balanced state of DNA gain or loss between tumor and reference samples. A threshold level of 0.75 (=log2 −0.41) indicated significant DNA loss, while 1.25 (=log2 0.32) represented significant gains [11]. The threshold corresponds to 2 standard deviation (S.D.) values from the mean. In addition, high-level gains (amplification) were defined as a log2 ratio >0.8 and high-magnitude deletions as log2 ratio less than −2 [11], [12], [13], [14]. Centromeric and heterochromatic regions were excluded from the analysis. The information on each individual clone was obtained from the UCSC Genome Bioinformatics database (May 2004, http://genome.ucsc.edu). 2.4. Real time quantitative PCR To validate genomic imbalances identified by array CGH in this study, 14 DNA samples, with obvious genomic changes, were analyzed using real time PCR. For relative quantification, the reactions were performed in a total volume of 25μl, including 12.5μl of 2x IQ™SYBR® green supermix (Bio-Rad, Hercules, CA), 1μl of DNA (10ng/μl), 1μl of each primer (10pmol/μl). The PCR amplification and detection were carried out in a iCycler (Bio-Rad, Hercules, CA) for 30 cycles, each with 30s at 95°C, 60°C, and 72°C, with initial denaturation at 95°C for 3min. Primers for three genes (EVI1, LPP and FHF-1) were selected and the position of each clone was obtained from the UCSC genome database (May 2004). The relative genomic copy number was calculated using the comparative Ct Method [15]. The threshold cycle (Ct) for each gene was determined using thermocycler software and the average of three independent experiments was calculated. The copy number of the target gene normalized to an endogenous reference, and relative to calibrator is given by the formula 2−ΔΔCt. α-Tubulin was used as an endogenous reference [16], [17], and ΔCt was calculated by subtracting the average α-tubulin Ct from the average Ct of the gene of interest. The ratio defines the level of increased copy number of the target to copy number of the reference gene. A calculated N-value>2 was set for a target gain, and an N-value<0.5 was regarded as a copy number loss [12]. 3. Results 3.1. Copy number changes in individual samples Chromosomal copy number gains and losses were detected by microarray-based CGH in SqCs. Each lung SqC was labeled and hybridized to BAC microarrays and the resulting array CGH profiles of copy number ratios are shown in Fig. 1. Hybridization of normal male versus normal female DNA, for specific amplicon detection, was determined (control). Copy number changes were presented as individual chromosome plots of log2 ratio of normalized Cy3:Cy5 intensities versus chromosome regions, for each of the individual 14 cases of human lung SqCs. The identified regions of genomic alterations, along with patients’ ages, differentiation, TNM status and stages are listed in Table 2. All cases showed a variety of chromosomal alterations as shown in Table 2. The post-surgical pathological stage distributions were as follows: p-stage IA=Sq-1 (one case); IB=Sq-3, Sq-6, Sq-8 and Sq-11 (four cases); IIA=Sq-4, Sq-9, Sq-10 and Sq-12 (four cases); IIB=Sq-5, Sq-7 and Sq-13 (three cases); IIIA=Sq-2 and Sq-14 (two cases). The reported chromosomal changes, amplification (>0.8 log2 ratios) at 20regions: 3q26, 4q31.1 and 7p14.2 (two cases), 1p35.2, 2q12.2, 2q33.2, 3q13.2, 3q26.1, 3q29, 4q12-13, 6q16.3, 7p14.3, 8q23.1, 9p23, 10q11.23, 10q21.3, 12q12, 12q15, 14q32.33 and 19p13.2 (one case) in lung cancer were reproduced in the current study [1], [6] (Table 2, Fig. 1). We draw a comparison of genetic aberrations between the SqC T1 (five cases), T2 (seven cases) and T3 (two cases) status, and lymph node status N0 (six cases), N1 (six cases) and N2 (two cases). The mean frequency of gained or lost chromosomal regions was significantly higher in the T3 status (51%) than in the T1 (31%), and T2 (18%) status, and in the N2 status (58%) than in the N0 status (17%), and N1 (25%) status. We also compared several clinicopathological and genetic features of the tumors from smokers with the TNM status. There was correlation between the quantity of cigarettes smoked during the lifetime and the different stages (tumor and lymph node status) of the disease. From these observations, we identified cigarette-associated T3, N2 status with a high rate of chromosomal abnormalities than in the cigarette-associated T1, T2, N0, and N1. Each tumor harbored 1–19 aberrations at the chromosomal region and the mean number of chromosomal aberrations per tumor was 19.6 gains and 7.2 losses. The majority of tumors (8 of 14 tumors) harbored more than 10 aberrations. | | | | Patient | Gender/age | Differentiation | TNM staging | Array CGH findings | |
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| | | | | Copy number gains | Copy number losses | |
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| Sq1 | M/66 | Moderate | T1N0M0 (IA) | 1p36.33, 3q27.1, 3q27–28, 3q28, 3q29, 7p15–14, 8q24.3, 9q34, 11p25, 11q13.4–13, 13q34, 14q11.2–22.1, 16p13.3, 17q21, 17q25.3, 19p13.1, 22q11.2, 22q13 | 9p21.2 | | | Sq2 | M/59 | Moderate | T3N2M0 (IIIA) | 1p35.3, 1p21.3, 1p21.1, 1p11.2, 1q21.2–25.2, 1q32.1–44, 2q12.1–12.2, 2q12.2, 2q23.1–24.1, 2q32.2, 2q33.2, 3q13.12, 3q13.2–13.33, 3q21.2, 3q21–25.33, 3q26–26.2, 3q26.33–29, 4q12–13, 4q27, 5p15.2, 5p13.2, 5p13.1–12, 6p23, 6p21.1, 6q11.2, 6q22.2, 6q23.1, 7q36.1, 8p11.23–11.22, 8q21.11–21.3, 8q24.13, 10p12.2, 10q11.21–11.23, 10q11.23, 10q21, 10q21.3, 11p13, 11q21, 12p13.32, 12q12, 12q15, 12q24.13–24.1, 13q12, 13q32.2–34, 14q11.2, 15q13.3, 15q22.31, 15q25.2, 19q13.1, 21q22.3, 22q11.2, 22q12, 22q13.1, 22q13.1–13.2 | 3p25.1, 3p14.2, 4q35.2, 5q13.1, 5q21.3, 5q23.1, 5q34, 6p21.2, 7p13, 7p12, 7q32.3, 8p23.3–21.2, 9p21.1, 9p21.32, 9q34, 10q26.2–26.3, 11q13.5, 13q11–12.11, 13q14.2, 13q14.3–21.2, 13q21.33–22.2, 14q24.3, 14q31.3, 14q32.2, 14q32.33, 15q15.15, 17p11.2, 18p11.31, 18p11.22 | | | Sq3 | M/67 | Moderate | T2N0M0 (IB) | 2p13.2–13.1, 2q11.2, 2q31.3–33.3, 3q23, 3q24–25.32, 3q26.1–26.2, 3q26.33–29, 5p15.33, 5p13.3–13.1, 5p12, 7q33–35, 9p13.1, 17p11.2, 22q11.23–11.2, 22q13.1 | 1p13.3–13.1, 2q22.2, 2q36.1, 4q32.2, 8q21.1, 10q26.2, 13q14.2, 14q32.33, 21q21.2 | | | Sq4 | M/58 | Poor | T1N1M0 (IIA) | 7q33–35, 14q13.3 | 9p11.2 | | | Sq5 | M/67 | Moderate | T2N1M0 (IIB) | 7p14.2 | 2q24.1, 3q28, 11q14.2 | | | Sq6 | F/65 | Moderate | T2N0M0 (IB) | 1p36.33, 1q42.3, 5q35.3, 7p14.2, 7q11.23, 9q34, 11q13, 14q24.3, 15q25.1–25.2, 17p11.2, 21q22.3, 22q11.2 | 2q32.1, 3p21.2, 3q21–23, 3q21–27, 3q26.1, 4q32.3, 5q23.1, 6p12.3, 15q14 | | | Sq7 | M/65 | Moderate | T2N1M0 (IIB) | 3q27.1, 3q27.3, 3q28 | | | | Sq8 | M/74 | Moderate | T2N0M0 (IB) | 1p21.1, 2p22.1, 2q24.3, 3q23, 3q25.1, 3q26, 3q27.1, 3q28–29, 8p23.3 | 18q21.3, 22q11.1 | | | Sq9 | M/68 | Moderate | T1N1M0 (IIA) | 1p36.1, 1p35.2–34.3, 1p32.1, 2p22.1, 2q34, 3p21.31, 3q13.12, 3q13.2, 3q21–23, 3q23, 3q26, 4p15.1, 4q21, 4q26, 4q31.1, 6p21, 6q11.2, 7p21.1, 7p14.3, 7p14.2, 8q12.2, 9q21.2, 10q23.31, 10q26, 10q26.12, 12q15, 12q22–23.3, 14q32.11, 14q32.33, 18q21.3, 20q12–13.1 | 11p13 | | | Sq10 | M/72 | Well | T1N1M0 (IIA) | 1p36.33, 1p36.1–35, 1p32, 1p32.1, 1p31.1, 1p21.3–21.2, 1q21.2–21, 1q23, 1q25.2, 1q42.13, 2p22.2–22.1, 2p13–12, 2p12, 2q12.2–12.3, 2q21.3–23.2, 2q24.3, 2q32.2, 3p12.2–12.1, 3q13.2–13.31, 3q24–25.1, 3q25.32, 3q26.31, 3q28, 5p15.33, 5p13.1–12, 6p25.2, 6p23–22.2, 6q16.3, 6q16.2–23.1, 7p12.1–11.2, 7q32.2, 7q33–35, 8q21.11, 8q24.13, 8q24.22–24.23, 9p24, 9p23, 9p21.2–21.1, 9p13, 9q22.31–22.32, 9q34.11, 10q26.3, 11p13, 11p11.12, 12p13.2–12, 13q21.1, 13q21.31, 13q22.2, 13q32.1, 13q34, 17q21–21.1, 17q22, 17q23–24, 18q21.1, 21.31, 18q21.3, 18q21.33–23, 19p13.2, 19p13.11, 20q13.2, 21q21.3, 21q22.3 | 1p13.3–13.1, 3p24.1, 3p21.3–21.2, 3p21.3, 5q31–32, 5q34, 6p25, 7p13, 7q11.23, 7q35, 7q36.33, 8p23.3, 8p22, 8p21.2, 9q31, 10q21, 10q26–26.12, 11p15.4, 11q13.4–13.3, 11q23.3, 12p13.3–12, 14q24.3, 14q32.33, 15q14, 15q15.2, 15q21.2–21.3, 15q25.3, 16q13, 16q22.1, 17p13.1, 17q21, 17p11.2, 19q13.11, 19q13.1–13.2, 22q11.21, 22q12.3, 22q13.1, 22q13.31 | | | Sq11 | M/71 | Moderate | T2N0M0 (IB) | 1q42.3, 2p13–12, 2p14–13.4, 3q26.1, 3q26, 3q26.2–27.1, 3q27.3, 3q28, 3q29, 5p15.33, 5p15.33–14.3, 5p13, 5p13.3–12, 7q33–35, 7q36.3, 8q24.3, 9q34.12, 9q34.1–34, 9q34.3, 10q26.3, 11p15.5, 11q12.3, 14q32.3–32, 22q12.1 | 4q31.1, 8p23.3, 10p15.3, 10q26.12, 10q26.2, 19q13.11 | | | Sq12 | M/52 | Poor | T1N1M0 (IIA) | 1p36.33, 1p21.1 | | | | Sq13 | M/61 | Moderate | T3N0M0 (IIB) | 19q13.1–13.2, 19q13.1 | | | | Sq14 | M/68 | Moderate | T2N2M0 (IIIA) | 1p36.3, 1p35.2, 1p32.1, 1p31.3, 1q25.1, 1q25, 2p24.1, 2q32.2, 2q33.2, 2q37.1, 3p14.1, 3q13.12–13.2, 4p16.3, 4q12, 4q21, 4q31.1, 6p21. 1, 6q16.2, 6q27, 7p21.2–21.1, 7p14.3, 7q32.3, 8p23.3, 8q23.1, 9q31.1, 10q11.2, 10q25.1, 10q26.11, 10q26.2, 11p15.2, 12q23.3, 12q24.33, 14q24.3, 14q31.3, 16p13.3, 19p13, 20p12.1, 20p11.23, 20q12–13.1, 20q13.2, 22q13.2 | 2p12, 19p13.3 | | | | |
3.2. Pattern of aberration of individual chromosomal region Table 3 shows a wide variation of specific region in the frequency of aberration, ranging from 3 in 14 samples (21% of chromosomal loss at 14q) to 5 in 14 samples (36% of chromosomal gain at 3q). Overall, the individual chromosomal aberration pattern was not random and tended to be consistent, showing main DNA gains are found in: 1p, 2p, 2q, 3q, 5p, 6p, 7p, 7q, 13q, 21q, and 22q, and showing main DNA losses are found in: 1p, 5q, 8p, 10q, 13q, 14q, 15p, 17q and 19q. DNA gains, rather than DNA losses, were more frequently observed. The chromosome arm most often over-represented was 3q, detected in 5 of 14 samples (36%). Frequent DNA gains were also observed at 1p, 5p and 7q in four samples (29%), and at 2p, 2q, 6p, 7p, 13q, 21q and 22q in three samples (21%). Changes in other chromosomes, and the most frequently involved sites, are summarized in Table 3. Moderate frequencies of DNA over-representation 29–36% of samples were observed in chromosomes 1p (1p36.33), 3q (3q28), 5p (5p12) and 7q (7q33-q35). Other regions with a 21% frequency of DNA gains included: 2p (2p22.1), 2q (2q33.2), 6p (6p21), 7p (7p14.2), 13q (13q34 qter), 21q (21q22.3) and 22q (22q11.2). The most common genomic losses were observed at 14q32.33 (21%), 1p13.3, 5q34, 8p23.3, 10q26.12, 13q14.2, 15p14, 17q11.2 and 19q13.11 (14%). Seven of the 14 samples showed a whole-arm gain of 3q, with several displaying additional small regional aberrations (Fig. 2). Sq-3 was a sample that showed a regional gain, including the EVI1 (3q26.2), LPP (3q28) and FHF-1 (3q27-q28) genes (Fig. 2B). | | | | Gain/loss | Region | No. of patients (n=14) | Frequency of change (%) | |
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| DNA gains | | | 1p | 1p36.33 | 4 | 4/14 (29) | | | 2p | 2p22.1 | 3 | 3/14 (21) | | | 2q | 2q33.2 | 3 | 3/14 (21) | | | 3q | 3q28 | 5 | 5/14 (36) | | | 5p | 5p12 | 4 | 4/14 (29) | | | 6p | 6p21 | 3 | 3/14 (21) | | | 7p | 7p14.2 | 3 | 3/14 (21) | | | 7q | 7q33–q35 | 4 | 4/14 (29) | | | 13q | 13q34 qter | 3 | 3/14 (21) | | | 21q | 21q22.3 | 3 | 3/14 (21) | | | 22q | 22q11.2 | 3 | 3/14 (21) | | | | | | DNA losses | | | 1p | 1p13.3 | 2 | 2/14 (14) | | | 5q | 5q34 | 2 | 2/14 (14) | | | 8p | 8p23.3 | 2 | 2/14 (14) | | | 10q | 10q26.12 | 2 | 2/14 (14) | | | 13q | 13q14.2 | 2 | 2/14 (14) | | | 14q | 14q32.33 | 3 | 3/14 (21) | | | 15p | 15p14 | 2 | 2/14 (14) | | | 17q | 17q11.2 | 2 | 2/14 (14) | | | 19q | 19q13.11 | 2 | 2/14 (14) | | | | |
3.3. Real time PCR To confirm the array CGH results, differential fold change between tumor and healthy tissues was evaluated by real time PCR in 14 SqC samples. The chromosomal fold change of some of the gained (a subset of three genes) genomic regions in tumor samples were measured in comparison to a reference gene α-tubulin in SqCs. The results from array CGH were replicated with the real time PCR method. Primers for the three genes (EVI1, LPP, FHF-1) are presented in Table 4. The clone positions were retrieved from the UCSC genome database (May 2004). | | | | Gene name | Primer forward | Primer reverse | Chromosomal resion | |
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| Gain | | | EVI1 | CCTGTGACGGCTTTCTCTTC | AAAAGGCTTTCTGCTCCACA | 3q26.2 | | | LPP | GCCGTCTCTCTTCCAGACAC | ACACAGTGAAACCCCGTCTC | 3q27–q28 | | | FHF-1 | GCCGCTGAGTTTTTCTTGTC | CTAAGTGCCCCACTCTCTGC | 3q28 | | | | |
Fig. 3 shows a comparison of the array CGH and real time PCR results. Three genes, in the gained region, EVI1, LPP, FHF-1 (A–C), the relative fold increases by real time PCR were consistent with those from the array CGH results. The value of array CGH was depicted by linear-ratios and N-value was delineated in real time PCR. A parallel examination demonstrated that the gene copy differences between tumor and normal lung genomes were generally larger when evaluated by real time PCR analysis compared to array CGH analysis. EVI1, LPP, FHF-1 were analyzed using real time PCR: EVI1, LPP, FHF-1 genes showed a higher fold change, which was consistent with the array CGH finding of DNA copy gains in 3q. Array CGH and real time PCR data corresponded well with respect to chromosomal copy number changes delineated in each samples. EVI1, LPP, FHF-1 showed more than a 1-fold linear-ratio in most of the 14 samples by real time PCR. 4. Discussion Cytogenetic analyses have revealed numerous somatic genetic changes involved in the pathogenesis of lung adenocarcinomas. Despite the complexity of the genomic alterations, observed in most lung tumors, the pattern and the biological implications of recurrent chromosome alterations have begun to emerge [6]. Genomic copy number alteration is important in most human cancers. Current research is aimed at determining the phenotypic consequences of specific copy number abnormalities [18]. Many genetic changes associated with tumor development and progression involved region-specific gain or loss of DNA copy number. The genomic location of which identifies the position of key genes involved. Thus, regions of DNA amplification commonly harbor oncogenes and tumor suppressor genes are frequently found in regions of DNA deletion [19]. Several methods including classical cytogenetics, fluorescence in situ hybridization (FISH), Southern blot analysis, quantitative PCR-based assays and CGH, have been used to detect copy number changes in tumors [19]. BAC array CGH is a very powerful technique, allowing the simultaneous quantitative analysis of all regions of large genome [20]. In addition to highly improved resolution compared with conventional CGH, array-based CGH has the advantage of higher throughput [19]. Unlike chromosomal CGH, array CGH can also provide quantitative information at the level of chromosomal gain or loss. Such quantitative data allow the identification of regions in the genome highly likely to harbor critical cancer-related genes, including those regions with a high-level of gain/amplification or loss/high-magnitude deletion [13]; real time PCR can be used for validation and quantification of the identified genomic changes [12], [15]. Although interphase FISH validation has been shown to be a stronger technique for confirmation compared to real time PCR, the analysis of solid tumors by FISH has been limited by the associated technical difficulties; evaluating the full extent of genetic gains or losses in the genome requires obtaining metaphases and interpreting karyotypes that are often complex and require prior knowledge or markers of sites of interest [3]. Therefore, in this study, real time PCR was used for validation and quantification of the identified genomic changes. This approach makes the technique particularly attractive for the identification of acquired aberrations in tumor tissue, and for detecting constitutional rearrangements in lung cancer samples. In this report, DNA copy number alterations frequently identified in 14 lung cancers were analyzed by array-based CGH. A large number of regions, in the entire genome, were altered. We classified the subtype of SqCs according to the clinicopathological features of patients and described several aberrant chromosomal regions in each subtype in the results section. The DNA copy number alterations observed in the lung cancers were not random; they involved particular regions of the genome, most commonly involving, parts or all of, DNA gains were found in: 1p, 2p, 2q, 3q, 5p, 6p, 7p, 7q, 13q, 21q, and 22q, and DNA losses were found in: 1p, 5q, 8p, 10q, 13q, 14q, 15p, 17q and 19q. DNA gains, rather than DNA losses, were more frequently observed. The most frequently altered locus was a gain at the 3q28 (36% of samples) region containing the FHF-1. FHF-1 is fibroblast growth factor (FGF) homologous factor 1, FGF12 [21]. FGFs are involved in a variety of biological processes, including embryonic development, cell growth, morphogenesis, tissue repair, tumor growth and invasion [22]. The specific function of this gene has not yet been determined. Two alternatively spliced transcript variants encoding distinct isoforms have been reported [22], [23]. The chromosome arm most often over-represented was 3q and includes FHF-1 gene. These results have been observed frequently in SqC of NSCLC [5] and are similar to those found by others, using chromosomal CGH [1], [3], [6]. The similarity of our findings with those of others using above-referenced methods, serves to validate the usefulness of array CGH. Three regions in 3q, 3q26.2, 3q28, and 3q27-q28 showed highest frequency of genomic alteration were confirmed by real time PCR. These findings suggest that array CGH is a reliable method to detect chromosomal aberrations consistent with prior reports [5]. NSCLCs revealed frequent high-level gains of chromosomal DNA at 3q23-q29 when examined by CGH. Within this amplicon, a minimal common region of amplification in lung tumors contains EVI1 gene and had been mapped to 3q26 by earlier studies. Yokoi et al. [24] determined amplification and expression levels of the EVI1 gene in primary NSCLC tumors, in cell lines, by using CGH and FISH. The most noticeable differences between SqCs and AdCs were the gain of chromosome 3q22–26 and the loss of chromosome 3p. The region of recurrent increase is approximately 30Mb in extent, ranging from EVI1 to TFRC [25]. The high frequency of the t(3;12) (q27 approximately 28; q14 approximately 15) in lipomas and pulmonary chondroid hamartomas (PCHs) makes the high mobility group at-hook 2 (HMGA2) - lim domain-containing preferred translocation partner in lipoma (LPP) fusion gene the most frequently identified fusion gene in human tumors [26]. The HMGA2-LPP fusion transcript was amplified in PCH with a normal karyotype; however, FISH revealed a hidden chromosomal aberration [27]. We also found amplified oncogenes such as MYC (8q24), CCND1 (11q13), Her2 (17q21.1) that have been described in previous report [9]. In summary, the array-based CGH analysis in 14 lung cancers showed that DNA copy number alterations are common. Real time PCR confirmed array CGH detected cancer-related genes that were gained. We were able to delineate discrete regions of DNA copy number alteration at the chromosomes 3q region, which are likely to harbor important relevant genes. These data support the utility of array CGH for the identification of genomic alterations in lung cancer. Although our results suggest new aspect of genomic alterations in lung SqC, the limitations of this study are small number of samples and the characteristics of samples are not satisfactory. So the further studies to validate our results and CGH techniques are needed to confirm our data. These findings can be used as a starting point for more focused investigation of the pathophysiology of lung cancer. 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a Department of Anesthesiology, St. Mary's Hospital, The Catholic University, Seoul, South Korea b Catholic Neuroscience Center, The Catholic University, Seoul, South Korea c Department of Pharmacology College of Medicine, Kyung Hee University, Seoul, South Korea d Department of Internal Medicine, Dongguk University International Hospital, Dongguk University College of Medicine, Goyang, South Korea e Division of Pulmonary and Critical Care, Department of Medicine, College of Medicine, Catholic University, Seoul, South Korea f Department of Internal Medicine, Korea University Medical Center, Anam Hospital, Seoul, South Korea g Department of Thoracic Surgery, The Catholic University, Seoul, South Korea h Department of Occupational and Environmental Medicine, St. Mary's Hospital, The Catholic University, Seoul, South Korea  Corresponding author. Tel.: +82 2 3779 1401; fax: +82 2 3481 7602.
PII: S0169-5002(06)00515-0 doi:10.1016/j.lungcan.2006.09.018 © 2006 Elsevier Ireland Ltd. All rights reserved. | |
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