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Cancer Biomarkers 13 (2013) 281–288 DOI 10.3233/CBM-130351 IOS Press

Genomic changes in rectal adenocarcinoma associated with liver metastasis Hai-Tao Zhoua,1, Zhi-Zhou Shib,1 , Zhi-Xiang Zhoua , Yan-Yi Jiangb , Jia-Jie Haob , Tong-Tong Zhangb , Feng Shib , Xin Xub , Ming-Rong Wangb and Yu Zhangb,∗ a

Department of Abdominal Surgery, Cancer Hospital/Institute, Chinese Academy of Medical Science, Peking Union Medical College, Beijing, China b State Key Laboratory of Molecular Oncology, Cancer Hospital/Institute, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

Abstract. BACKGROUND: At present no objective parameters to identify the risk of liver metastasis after surgery have been established in rectal cancer. OBJECTIVE: To identify the chromosomal aberrations that are correlated with liver metastasis of rectal cancer. METHODS: Primary tumor tissues of rectal carcinoma were analyzed by array-based comparative genomic hybridization (arrayCGH). Genomic aberrations were identified by Genomic Workbench and MD-SeeGH. RESULTS: The most frequent gains in rectal cancer were at 20q11.21-q13.33, 8q11.21-q24.3, 13q12.11-q14.2 and losses in 5q13.2, 8p23.3-p22, 17p13.3-p13.2 and 18q11.2-q23. Seven amplifications at 6p21.1, 8q24.21, 8q24.3, 13q13.2 and 20q13.2q13.32 and nine homozygous deletions at 1q31.3, 4q12-q13.1, 4q32.3-q33, 5q13.2, 8p23.2, 8q11.23, 16p13.2, 19p13.11 and 19q13.41 were identified. Both frequency plot comparison and SAM (Significance analysis of microarray) methods indicated that losses at 1p35.3, 4p14, 14q23.1-q32.11 and 18p11.32-p11.21 were more frequent in patients without liver metastasis. CONCLUSIONS: These liver metastasis associated genomic changes may be useful to reveal the mechanism of metastasis and identify candidate biomarkers. Keywords: Array CGH, rectal cancer, liver metastasis, biomarker

1. Introduction Colorectal cancer (CRC) is a common malignant tumor worldwide. CRC in China has increased rapidly since the 1980s [1,2], and now become the fifth leading cause of cancer-related deaths [3]. Distant metastasis after surgery is the cause of treatment failure, and liver metastasis is the most frequent situation. At present no objective parameters to identify the risk of liver metastasis after surgery have been established in colorectal cancer, especially in rectal cancer. 1 These

two authors contributed equally to this work. author: Yu Zhang, State Key Laboratory of Molecular Oncology, Cancer Hospital/Institute, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. E-mail: [email protected]. ∗ Corresponding

Chromosomal aberrations are common in colorectal cancer and tumor clones are assumed to differ in potential of causing distant metastasis. And the characterization of genetic alterations linked to colorectal cancer may further provide information relevant for early tumor detection, refined prognosis, and development of novel targeted therapeutics. Several previous studies have identified some recurrent chromosome alterations associated with clinical parameters of colorectal cancer, especially with metastasis status. Chen et al. found that the number of chromosomal aberration was closely associated with tumor stage of colorectal cancer [4]. Kim et al. revealed that losses on 1p36 and 21q22 were independent indicators of poor prognosis. Especially, reduced expression of CAMTA1 at 1p36 was observed and associated with poor prognosis [5]. Al-Mulla et al. revealed that loss of chromosome 4p

c 2013 – IOS Press and the authors. All rights reserved ISSN 1574-0153/13/$27.50 

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H.-T. Zhou et al. / Genomic changes in rectal adenocarcinoma associated with liver metastasis Table 1 Clinical characteristics of 16 patients studied by array CGH No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Metastasis status1 Non metastasis Non metastasis Non metastasis Non metastasis Non metastasis Non metastasis Non metastasis Non metastasis Metastasis Metastasis Metastasis Metastasis Metastasis Metastasis Metastasis Metastasis

Sex M F M F M F F M F M F M F M F M

Age 45 47 65 66 56 68 72 50 53 58 48 62 70 57 49 66

pT2 3 3 4 3 3 3 3 3 3 3 3 3 3 4 3 4

pN3 0 1 1 1 1 1 0 0 1 0 2 1 0 2 0 2

pM4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Differentiation Middle Middle high Middle Middle Middle Middle Middle low low high low Middle Middle Middle low

Note: 1: the liver metastasis status when following up at 36 months after surgical resection. 2: the invasive depth. 3: the node metastasis status. 4: the distant metastasis status at surgical resection. M: male. F: female.

was an independent prognostic factor in early-stage colorectal cancer. Losses of both chromosome arms 8p and 18q had a statistically significant negative effect on disease-free survival [6]. Kodeda et al. showed that gain of 4q31.1-q31.22 was associated with local recurrence after primary operation and 22 affected genes of this region had high relevance to tumor biology such as p53 regulation and cell cycle activity [7]. A study comparing the genomic profiling between tumor specimens and the corresponding pulmonary metastases showed that loss at chromosome arm 5q had difference in frequency in two groups [8]. Ghadimi et al. reported that losses of chromosomal regions 1p32-qter and 9q33-qter were present at much higher frequencies in metastatic than in non-metastatic cancers [9]. Gain of 8q and losses of 8p12-pter, 9q33.1 and 20p12.2 were associated with lymph node metastasis, while gain of 8q23-qter and loss of 18q12-qter were associated with distant organ metastasis at diagnosis and recurrence after surgery, and gains of 8q23, 8q24-qter and losses of 8p12-pter and 18q12-qter were associated with prognosis [10–12]. An large cohort study further confirmed that differences of copy number profiles between primary tumors and metastases were the biological reason to colorectal carcinogenesis or treatment-associated effects [13]. Although many copy number changes mentioned above linked to clinical parameters of colorectal cancer have been identified, the genetic alterations in primary tumor tissues associated with liver metastasis in rectal cancer have still been largely unknown. Therefore we conducted the present study to detect frequent DNA copy number changes in Chinese rec-

tal cancer and identify genomic aberrations in primary tumor tissues that could predict liver metastasis after surgery.

2. Materials and methods 2.1. Study design First, the genetic aberrations in 16 rectal carcinomas were detected by using Agilent 44 K Human Genome CGH microarray and common genomic changes were identified. Then, the genomic profiling of rectal cancer with or without distant metastasis (8 cases in each group) was compared on basis of follow-up information at 36 months after surgical resection. 2.2. Patients and samples Freshly resected tissues from 16 rectal carcinoma patients were collected by the Department of Pathology, Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, China. All the rectal cancer patients were treated with radical operation, and none of them received any treatment before surgery. Representative tumor regions were excised by experienced pathologists and immediately stored at −70◦ C until used. All the samples used in this study were residual specimens after diagnosis sampling. Every patient signed separate informed consent forms for sampling and molecular analysis. Clinical characteristics of patients used in the array CGH study are shown in Table 1.

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Table 2 Genomic gains and losses in rectal adenocarcinoma Changes Gain

No. 1 2 3 4 5 6 7 8 9 10

Cytoband 20q11.21-q13.33 8q11.21-q24.3 13q12.11-q14.2 13q21.31-q34 20p12.1-p11.21 20p13 7p14.1-p11.2 7p15.3-p14.1 7p22.1-p21.3 8p11.21

Region 29352138-62363633 49041740-146250824 19558794-47066072 60895878-114029609 13930937-26023841 2437673-2462612 41701354-55242365 20788779-39813968 6837409-7245076 40608362-42866112

Ave frequency1 58% 43% 35% 31% 31% 31% 31% 31% 31% 31%

Loss

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

5q13.2 8p23.3-p22 17p13.3-p13.2 18q11.2-q23 14q23.1-q32.11 17p13.1-p11.2 2p22.3 8p21.2-p12 8p22-p21.2 14q12 18q11.2 18p11.32-p11.21 19q13.12-q13.13 21q21.2-q21.3 4q21.23 4q12 5q21.1-q21.3 8p22-p11.21 17p13.3 18p11.21-q11.2 2p23.1-p22.3 4p14-q28.3 5p13.3-q31.1 17p13.2-q11.2 14q11.2-q32.33 21q11.2-q22.3 10q21.3 15q15.1-q21.3 22q11.1-q13.33 17q22-q25.3 1p35.3-p13.3 12p11.21

68434643-70988467 181530-16934515 202809-6289449 21876699-76083117 60020243-89113369 8133829-18845678 31967230-32891168 26571195-36027465 18648724-25945406 26134544-29386470 16976046-21059845 170229-13752309 41377289-43085470 24950157-26547205 84149489-84616491 58544942-58953266 101176789-106705014 16934515-39990415 84287-202809 13752309-21876699 31816500-33102640 37816340-131439859 31487385-134218751 6289449-27707560 19508845-103376255 13926078-46880878 68951687-70518111 38653893-53738451 15443579-48934359 53997246-78623230 28014742-108526137 31433613-32798193

50% 36% 35% 34% 33% 33% 33% 33% 33% 31% 31% 31% 31% 31% 31% 31% 31% 23% 22% 22% 22% 22% 21% 21% 21% 21% 21% 20% 20% 20% 20% 19%

Note: 1: when two or more adjacent cytobands have copy number increase at a frequency above 30% or copy number decrease at a frequency above 15%, the average frequency of these cytobands was calculated and listed.

2.3. Genomic DNA extraction Genomic DNA was isolated from tumor tissues using the Qiagen DNeasy Blood and Tissue Kit as described by the manufacturer (Qiagen, Hilden, Germany). Tumor cell content of all the samples was greater than 50% by HE staining. 2.4. Array-based CGH Array CGH experiments were performed using standard Agilent protocols (Agilent Technologies, Santa

Clara, CA). Commercial human genomic DNA (PROMEGA, Warrington, UK) was used as reference. For each CGH hybridization, 500 ng of reference genomic DNA and the same amount of tumor DNA were digested with Alu I and RSA I restriction enzyme (PROMEGA, Warrington, UK). The digested reference DNA fragments were labeled with cyanine-3 dUTP and the tumor DNA with cyanine-5 dUTP (Agilent Technologies, Santa Clara, CA). After clean-up, reference and tumor DNA probes were mixed and hybridized onto Agilent 44 K human genome CGH microarray (Agilent) for 40 h. Washing, scanning and

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H.-T. Zhou et al. / Genomic changes in rectal adenocarcinoma associated with liver metastasis Table 3 High-level amplifications and homozygous deletions in rectal adenocarcinoma

Changes Cytoband Amp 6p21.1 6p21.1

Region 42669962-42821174 43589125-43846100

No. of probes No. of cases Genes 4 2 UBR2, PRPH2, TBCC 15 2 YIPF3, POLR1C, XPO5, POLH, GTPBP2, MAD2L1BP, RSPH9, MRPS18A, VEGFA 8q24.21 128243288-129216964 9 3 POU5F1P1, POU5F1B, LOC727677, MYC, PVT1 8q24.3 144311163-145534978 41 3 LY6H, GPIHBP1, ZFP41, GLI4, ZNF696, TOP1MT, C8orf51, RHPN1, MAFA, ZC3H3, GSDMD, C8orf73, NAPRT1, EEF1D, TIGD5, PYCRL, TSTA3, ZNF623, ZNF707, BREA2, MAPK15, FAM83H, SCRIB, PUF60, NRBP2, EPPK1, PLEC1, PARP10, GRINA, SPATC1, OPLAH, EXOSC4, GPAA1, CYC1, SHARPIN, MAF1, KIAA1875, C8orf30A, HEATR7A, SCXB, SCXA, BOP1, HSF1, DGAT1, SCRT1 8q24.3 141595348-141738199 5 3 CHRAC1, EIF2C2, PTK2 13q13.2 33226665-33381799 4 2 RFC3 20q13.2-q13.32 51013575-57000469 105 3 TSHZ2, ZNF217, SUMO1P1, BCAS1, CYP24A1, PFDN4, DOK5, CBLN4, MC3R, C20orf108, AURKA, CSTF1, CASS4, C20orf43, GCNT7, C20orf106, C20orf107, TFAP2C, BMP7, SPO11, RAE1, RBM38, HMGB1L1, CTCFL, PCK1, ZBP1, PMEPA1, C20orf85, PPP4R1L, RAB22A, VAPB, APCDD1L, STX16, NPEPL1, GNASAS, GNAS, TH1L

HD

1q31.3 4q32.3-q33 4q12 - q13.1 5q13.2

195054835-195150021 170252666-170428244 57090202-61302109 68434643-70988467

4 6 26 27

1 1 1 1

8q11.23 8p23.3 16p13.2 19q13.41 19p13.11

54309487-55130203 181530-1711072 6367978-7010690 58574652-58646135 16299299-16489753

11 17 6 4 8

1 1 1 1 1

CFHR1, CFHR4 SH3RF1 HOPX, SPINK2, REST, C4orf14, POLR2B, IGFBP7 SLC30A5, CCNB1, CENPH, MRPS36, CDK7, CCDC125, TAF9, RAD17, MARVELD2, OCLN, LOC647859, GTF2H2C, GTF2H2, GTF2H2B, GTF2H2D, LOC100272216, LOC653188, SERF1A, SERF1B, SMN2, SMN1, LOC100170939, NAIP, PMCHL2, BDP1, MCCC2 OPRK1, ATP6V1H, RGS20, TCEA1, LYPLA1 ZNF596, FBXO25, C8orf42, ERICH1, DLGAP2, CLN8 A2BP1 ZNF525, ZNF765, ZNF761, LOC147804 KLF2, EPS15L1, CALR3, C19orf44, CHERP

Note: Amp: amplifications. HD: homozygous deletions.

data extraction procedures were performed following standard protocols. 2.5. Microarray data analysis Microarray data were analyzed using Agilent Genomic Workbench (Agilent Technologies, Santa Clara, CA) and MD-SeeGH (www.flintbox.ca). Agilent Genomic Workbench was used to calculate log2ratio for every probe and to identify genomic aberrations. Mean Log2ratio of all probes in a chromosome region between 0.25 and 0.75 was classified as genomic gain, > 0.75 as high-level DNA amplification, < −0.25 as hemizygous loss, and < −0.75 as homozygous deletion. 2.6. Statistical analysis Statistical analyses were conducted using the Student’s t-test with the statistical software SPSS 15.0.

The differences were judged as statistically significant when the corresponding two-sided P value were < 0.05.

3. Results 3.1. Recurrent copy number alterations in rectal carcinoma detected by array CGH In 16 samples of rectal carcinoma analyzed, 10 gains and 17 losses were frequently detected (frequency > 30%). The most common gains were 20q11.21q13.33 (58%), 8q11.21-q24.3 (43%) and 13q12.11q14.2 (35%), and most frequent losses were 5q13.2 (50%), 8p23.3-p22 (36%), 17p13.3-p13.2 (35%) and 18q11.2-q23 (34%, Table 2 and Fig. 1). Seven highlevel amplifications at 6p21.1, 8q24.21, 8q24.3, 13q

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Table 4 Chromosome regions associated with liver metastasis in SAM analysis No. 1 2 3 4 5 6

Cytoband (Cytoband shared by two methods1 ) 1p36.31-p12 (1p35.3) 14q11.2-q32.33 (14q23.1-q32.11) 4p16.3-p13 (4p14) 18p11.32-p11.21 (18p11.32-p11.21) 17q11.2-q25.1 3q13.31-q29

No. of probes (No. of probes shared by two methods1 ) 52 (10) 31 (16) 22 (8) 21 (21) 19 15

%2 (%3 ) 19 (19) 11 (52) 8 (36) 8 (100) 7 5

Note: 1: SAM and frequency plot comparison. 2: proportion of individual cytoband probes in all probes identified by SAM analysis. 3 = (No. of probes shared by two methods) / (No. Of probes only identified in SAM method).

Fig. 1. Genome-wide frequency plot of rectal adenocarcinoma by array CGH analysis. Line on the right of 0%-axis, gain; line on the left of 0%-axis, loss. (Colours are visible in the online version of the article; http://dx.doi.org/10.3233/CBM-130351)

13.2 and 20q13.2-q13.32 and nine homozygous deletions at 1q31.3, 4q12-q13.1, 4q32.3-q33, 5q13.2, 8p 23.2, 8q11.23, 16p13.2, 19p13.11 and 19q13.41 were also identified in rectal carcinoma (Table 3). All of samples in array CGH study had DNA copy number changes. Among them 11 rectal cancer cases (69%) had less than fifty genetic alterations, and five cases (31%) had fifty to 118 DNA copy number changes (Fig. 2A). However, the number was not different between patients with liver metastasis and patients without liver metastasis (Fig. 2B). 3.2. Genomic changes associated with liver metastasis In order to identify genetic alterations linked with liver metastasis status, we applied frequency plot comparison and significance analysis of microarrays (SAM) methods to analyze the array CGH data. Fre-

quency plot comparison together with detailed genomic analysis revealed that losses at 1p35.3, 4p14, 5q13.2, 14q23.1-q32.11 and 18p11.32-p11.21 were more frequently occurred in patients without metastasis. And gain of 8q21.3, losses of 21q11.2-q21.1 and 21q21.3-q22.11 were more common in patients with metastasis (Fig. 3). SAM analysis showed that 273 probes (excluding probes in chromosome X and Y) had different copy number between patients with or without liver metastasis, predominantly located in six chromosome regions (Table 4). The two leading ones were 1p36.31-p12 (52 probes, 19%) and 14q32.33q11.2 (31 probes, 11%). Importantly, 1p35.3, 4p14, 14q23.1-q32.11 and 18p11.32-p11.21 were both selected by two methods. We also analyzed the correlation between amplifications and liver metastasis status after surgery, and found that amplifications of 8q24.21 and 8q24.3 were detected in three patients with liver metastasis but in none of patients without liver metas-

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A

B

Fig. 2. Numbers of aberrations in rectal adenocarcinoma. A. Number of aberrations per case. X, case; Y, number of aberrations; horizonal line, 50 genomic aberrations. B. Comparison of numbers of aberrations between patients with and without liver metastasis after surgery. X, patients with liver metastasis and patients without liver metastasis; Y, number of aberrations per case.

Fig. 3. Frequency plot comparison of rectal cancer patients with and without liver metastasis. middle grey, frequency plot of genomic changes in rectal cancer patients with liver metastasis; dark grey, frequency plot of genomic changes in rectal cancer patients without liver metastasis; light grey, shared by two groups; pM1, liver metastasis when following up at 36 months after surgical resection; pM0, no liver metastasis when following up at 36 months after surgical resection. The presentation is per array probe: gains are represented by the lines on the right, and losses by the left. Vertical line represents 100% of the samples. Arrows highlight the chromosomal areas with different frequency in two groups. (Colours are visible in the online version of the article; http://dx.doi.org/10.3233/CBM-130351)

tasis. 6p21.1 amplification was only observed in two patients with liver metastasis, and 13q13.2 amplification only in two patients without liver metastasis.

4. Discussion By applying array CGH, we screened the genomic aberrations associated with liver metastasis in primary tumor tissues using frequency plot comparison and SAM methods. Losses at 1p35.3, 4p14, 5q13.2, 14q23.1-q32.11 and 18p11.32-p11.21 were more common in patients with liver metastasis, and gain of

8q21.3, losses of 21q11.2-q21.1 and 21q21.3-q22.11 were more frequent in patients without liver metastasis. Especially, copy number decrease of 1p35.3, 4p14, 14q23.1-q32.11 and 18p11.32-p11.21 were both identified by frequency plot comparison and SAM analysis. Many studies have revealed the correlation between genomic alterations and liver metastasis. Gain of 20p11 was reported more often in primary tumor tissues of patients with hepatic metastases than extrahepatic metastases. C20orf3 showed strongest correlation between RNA expression and DNA copy number, and particularly immunohistochemistry showed significantly higher protein expression in patients with hep-

H.-T. Zhou et al. / Genomic changes in rectal adenocarcinoma associated with liver metastasis

atic metastases [14]. Genomic aberrations on chromosome 20q occurred in the tumors of primary colorectal cancer patients who subsequently developed liver metastasis [15]. Stange et al. showed that chromosome aberration patterns and expression profiles of primary colorectal cancer and matched liver metastases were strikingly similar. A median of only 11 aberrations per patient, but only 16 expression-changed genes were found to be different between the two groups. Gain of 11p15.5 was more frequent in liver metastases, and ASCL2 together with IGF2 may be the target driving genes [16]. Genetic losses were more common than gains, and several reports also showed the relationship between loss and liver metastasis [17]. Allelic loss on 5q in metastases was significantly lower than that of nonmetastatic primary tumors, and chromosomes, 4, 7, 8 and 19 were more frequently lost in liver metastases, but only 19q loss was significant in statistical ananlysis [18]. Paredes-Zaglul et al. found that gains at 7q, 19q and 20q were both occurred in primary tumors and metastases, gains at 8q, 13q and losses of 4p, 8p, 15q, 17p, 18q, 21q and 22q were more extensive in liver metastases, and losses of 9q, 11q and 17q were unique to metastatic lesions [17]. Genomic changes of genes were also found to link with metastasis. Nm23 gene is a candidate metastatic suppressor gene and consists of two genes, nm23-H1 and nm23-H2. And mutation in nm23-H1 was associated with metastases [19]. In the patients with resectable colorectal liver metastases, both KRAS mutation and BRAF mutation reflected poorer prognosis than wild-type patients [20]. In summary, our study identified multiple liver metastasis correlated genomic aberrations in rectal cancer. Further studies should be conducted to identify the candidate target genes in these chromosomal regions and to explore their implication in the disease.

Acknowledgements This work was supported by Special Public Health Fund of China (200902002-5) and Chinese Hi-Tech R&D Program Grant (2011AA022706).

Conflict of interest The authors disclose no conflicts.

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Genomic changes in rectal adenocarcinoma associated with liver metastasis.

At present no objective parameters to identify the risk of liver metastasis after surgery have been established in rectal cancer...
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