Introduction

Colorectal cancer (CRC) is a common malignant tumor worldwide, and over 1.2 million new cases and 608,700 deaths estimated to have occurred in 2008 (Ministry of health 2010). The incidence of CRC in China has increased rapidly since the 1980s (Lei et al. 2009; Li et al. 2009). Distant metastasis after surgery is the cause of treatment failure. At present no objective parameters to identify the risk of distant metastasis have been established in CRC, especially in rectal cancer.

Genomic aberrations are found frequently in cancers and are believed to contribute to initiation and progression of cancer by deletion-induced down-expression of tumor suppressor genes or amplification and activation of oncogenes. In CRC the most frequent chromosomal aberrations were gains at 1q, 7p, 7q, 8q, 13q, and 20q and losses of 1p, 4p, 4q, 5q, 8p, 14p, 14q, 15p, 15q, 17p and 18q (Carvalho et al. 2009; Diep et al. 2006; Douglas et al. 2004; Hoglund et al. 2002; Ishikawa et al. 2016; Mampaey et al. 2015; Nakao et al. 2004; Ried et al. 1996). And orsetti et al. found that losses at 16p13.3 and 19q13.3 were correlated with negative outcome of colon cancer (Orsetti et al. 2014). However, most of published reports are focused on colon cancer. Little information is available concerning the genomic aberrations of rectal carcinoma, especially DNA copy number changes associated with metastasis.

In the present study, we investigated the genomic aberrations of stage II rectal carcinoma by oligonucleotide-based array CGH, and identified the chromosome regions associated with metastasis.

Materials and methods

Study design

First, the genetic aberrations in 32 stage II rectal carcinomas were detected by using Agilent 60 K Human Genome CGH microarray and common genomic changes were identified. Then, the genomic profiling of stage II rectal cancer with or without distant metastasis were compared on basis of follow-up information at 36 months after surgical resection.

Patients and samples

Formalin-fixed, paraffin-embedded tissues from 47 rectal carcinoma patients were got from 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. 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.

Table 1 Clinical characteristics of 32 patients studied by array CGH
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Genomic DNA extraction

The protocol recommended by the ULS labeling system manufacturer (Agilent) was used for DNA extraction from FFPE tissues. Approximately 4 mm3 of tissue (the equivalent of two 20 µm-thick sections measuring 10 × 10 mm) was heat de-paraffined at 90 °C, followed by overnight treatment with 1 M-sodium thiocyanate. This was followed by 48-hour proteinase K treatment. DNA was then purified using the Qiagen DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany), substituting the wash buffer AW2 with 80 % ethanol, and eluting in nuclease–free water.

Array-based CGH

Array CGH experiments were performed using standard Agilent protocols (Agilent Technologies, Santa Clara, CA). FFPE tumour and reference DNA (Commercial human genomic DNA) were labeled using an optimized version of the protocol for ULS labeling of FFPE DNA (Agilent). Prior to labeling, heat fragmentation at 95 °C was required. 250 ng of tumor and reference DNA was then chemically labeled by incubating with ULS-Cy5 and Cy3 respectively in a 30-min reaction. Unreacted dye was then removed using KREApure filters (Agilent). Cy5-labeled tumor DNA was combined with an equivalent amount of Cy3-labeled reference DNA. Repetitive sequences were blocked with human Cot-1 DNA (Invitrogen) and samples were hybridised onto SurePrint G3 Human CGH Microarrays, 8 × 60 K (Agilent) according to manufacturer’s instructions. Following hybridisation for 40 h, microarray slides were washed according to manufacturer’s instructions and scanned immediately on a DNA Microarray Scanner.

Microarray data analysis

Microarray data were analyzed using Agilent Genomic Workbench (Agilent Technologies, Santa Clara, CA), BRB-CGHtools (http://linus.nci.nih.gov/BRB-ArrayTools.html) and SAM (http://www-stat.stanford.edu/~tibs/SAM/). Agilent Genomic Workbench was used to calculate log ratio2 for every probe and to identify genomic aberrations. Mean log ratio2 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.

Real-time PCR

The PCR reactions were performed in a total volume of 20 µl, including 10 µl of 2X Power SYBR ® Green PCR Master Mix (Applied Biosystems, Warrington, UK), 2 µl of cDNA/genomic DNA (5 ng/µl), and 1 µl of primer mix (10 µM each). The PCR amplification and detection were carried out in the ABI 7300 (Applied Biosystems, Warrington, UK) as follows: an initial denaturation at 95 °C for 10 min; 45 cycles of 95 °C for 15 and 60 °C for 1 min. The relative gene expression or relative copy number of the target gene was calculated using the comparative CT Method by normalized to an endogenous GAPDH. The relative to calibrator was given by the formula 2−ΔΔCt. ΔCT was calculated by subtracting the average GAPDH CT from the average CT of the gene of interest. The ratio defines the level of relative expression or relative copy number of the target gene to that of GAPDH. 2−ΔΔCt > 2.0 was set for a target amplification, and 2−ΔΔCt < 0.25 was set for a target homozygous deletion. The primer pairs used for amplification were listed in Table 2.

Table 2 Primers used in real-time PCR assay
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Statistical analysis

Student’s t test and Χ 2 test were performed with the statistical software SPSS 15.0. The differences were judged as statistically significant when the corresponding two-sided P value were <0.05.

Results

Recurrent copy number alterations in stage II rectal carcinoma detected by array CGH

In 32 samples of rectal carcinoma analyzed, 16 gains (frequency >50 %) and six losses (frequency >30 %) were frequently detected. The top five most common gains were 1q21.2-q23.1 (96.9 %), 3p21.31 (93.8 %), 11q12.2-q23.3 (90.5 %), 12q24.11-q24.31 (87.1 %) and 12q13.11-q14.1 (81.9 %), and most frequent losses were 18q11.2–q23 (56 %), 17q21.33-q22 (46.9 %), 13q31.1-q31.3 (45.3 %), 21q21.1-q21.3 (39.1 %), 8p23.3-p23.1 (35.2 %) and 4q22.1-q23 (34.4 %, Table 3 and Fig. 1a). Twenty-two high-level amplifications such as 3p21.31, 1q21.2-q21.3, 7q21.3-q22.1, 19p13.11, 19p13.3-p13.12, 6p21.33-p21.31 and 11q23.3, and five homozygous deletions at 18q12.2-q12.3, 4q33-q35.1, 10q22.3-q23.2, 10q26.2-q26.3 and 4q12-q13.3 were also identified in stage II rectal carcinoma (Table 4).

Table 3 Genomic gains and losses in rectal adenocarcinoma
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Fig. 1
figure 1

Genomic aberrations in rectal cancer. a Genome-wide frequency plot of rectal cancer by array CGH analysis. The presentation is per array probe; line on the right of 0 %-axis, gain; line on the left of 0 %-axis, loss. b Numbers of aberrations in rectal cancer. X, number of aberrations; Y, number of cases. c Amplifications and homozygous deletions (HDs) identified by GISTIC. The blue arrows indicate the significant amplifications and homozygous deletions in rectal cancer

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Table 4 High-level amplifications and homozygous deletions in rectal adenocarcinoma
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All of samples in array CGH study had DNA copy number changes. Among them 26 rectal cancers (81 %) had 21–60 genomic alterations in every case (Fig. 1b). However, the total number of genomic changes in each patient with distant metastasis was not significantly different from that in every patient without distant metastasis (Fig. S1).

The literatures showed that S100A1 (1q21.3-q23.1), MCM7 (7q22.1), JUND (19p13.11) and TMEM120B (12q24.31), which were amplified in rectal cancers in our study, played important roles in metastasis of cancer(Bruin et al. 2013; Wang et al. 2000; Zhang et al. 2016), thus we selected these four genes for validation. In 15 independent validation samples, amplification of S100A1, MCM7, JUND and TMEM120B was detected in 8, 7, 7 and 4 cases, respectively (Fig. 2). We further found that S100A1, MCM7 and JUND were significantly overexpressed in stage II rectal cancer compared with morphologically normal margin tissues (Fig. 3). The expression of TMEM120B was not different between rectal tumor tissues and morphologically normal margin tissues (Fig. 3).

Fig. 2
figure 2

Validation of amplified genes in rectal cancer by Real-time PCR. Ratio = (copy number of gene in tumor tissue)/(copy number of gene in commercial human genomic DNA); blue arrows indicate the cases with gene amplification

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Fig. 3
figure 3

mRNA expression of S100A1, MCM7, JUND and TMEM120B in rectal cancer as compared with that in morphologically normal margin tissues detected using Real-time PCR. *, P < 0.05; **, P < 0.01; ns no significance

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Pathways enriched for copy number alterations

Pathway enrichment analysis using KEGG database was applied to the CGH data, and we found two pathways enriched in genes with gain and 12 pathways enriched in genes with loss. VEGF signaling pathway and cyanoamino acid metabolism pathway appear to be up-regulated in the stage II rectal carcinoma tissues based on the gain of several genes in this pathway. We also found the genes in 12 pathways such as pentose and glucuronate interconversions, fatty acid metabolism, bile acid biosynthesis, Androgen and estrogen metabolism, 1- and 2-Methylnaphthalene degradation and Porphyrin and chlorophyll metabolism were down-regulated (Table 5).

Table 5 Pathways enriched in array CGH data
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Genomic changes associated with distant metastasis after surgery in stage ii rectal cancer

In order to identify genetic alterations linked with distant metastasis status, we applied significance analysis of microarrays (SAM) method to analyze the array CGH data. SAM analysis showed that 585 probes had different copy number between stage II rectal cancer patients with or without metastasis after 36 months after surgery, predominantly located in six chromosome regions including 13q12.11-q34, 3q11.2-q29, 1q21.1-q42.2, 2q11.2-q37.3, 5q11.2-q35.3 and 15q11.2-q26.3 (Table 6). We also analyzed these candidate genomic regions with distant metastasis status by Χ 2 test, and found that loss of 13q31.1-q34 and gain of 1q44 were associated with distant metastasis (Table 7).

Table 6 Chromosome regions associated with distant metastasis in SAM analysis
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Table 7 Metastasis associated genomic aberrations in stage II rectal cancer
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Discussion

The biological properties of cancers were different in patients with different distant metastasis status. Thus, the optimal treatment should be based on an individual cancer. Biomarkers can improve the accuracy of determination of the distant metastasis status that were predictors of prognosis and indicators of a response to treatment.

To identify the genomic changes associated with distant metastasis, we selected the samples from patients in stage II rectal cancer without lymph node metastasis at diagnosis, and divided them into two groups according to the distant metastasis status 36 months after surgery. By applying array CGH, we screened the genomic aberrations associated with distant metastasis in primary tumor tissues using SAM methods. Loss of 13q31.1-q34 and gain of 1q44 were significantly associated with distant metastasis after surgery. Gain of 15q15.1-q15.3 was more frequent in patients with distant metastasis but without significance. Up to now, many studies have revealed the correlation between genomic alterations and distant metastasis. Bruin et al. identified an extrahepatic recurrence classifier including 12p13 as predictive biomarker for subsequent extrahepatic-recurrence(Bruin et al. 2013). Mekenkamp et al. reported that 20p11 gain was associated with liver-specific metastasis in patients with CRC, especially twelve genes including C20orf3 mapping at 20p11 were significantly overexpressed as a consequence of copy number gain(Mekenkamp et al. 2013). Jasmine et al. found that amplifications of 5p15.2, 5p13.1, 13q31.1 and 20q13.2 were more frequently detected in lymph node negative cases than lymph node positive cases(Jasmine et al. 2012). Nakao et al. revealed that a gain of 8q24.3 and losses of 9q33.1 and 20p12.2 were associated with lymph node metastasis, gain of 8q22.1 and loss of 10q21.3 with lymphovascular invasion and losses of 3p25.1, 10p15.3, 12q15 and 17p13.1 for venous invasion(Nakao et al. 2011). Li et al. compared chromosomal abnormalities between primary and metastatic CRC and identified five potential metastatic pathways: (−18q, −18p) (−8p12-q23, −4p15, −4q33-q34), (+20q, +20p), (+20q, +7p, +7q11-q32), and +8q. Among them, −8p12-p23 and +20q were the two marker events of CRC metastasis(Li et al. 2011). Genomic aberrations on chromosome 20q occurred in the tumors of primary CRC patients who subsequently developed liver metastasis (Bruin et al. 2010). Stange et al. showed that chromosome aberration patterns and expression profiles of primary CRC 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 (Stange et al. 2010). However, there is still no report about the correlations between loss of 13q31.1-q34, gain of 1q44 and distant metastasis, so our results provide new candidate metastasis associated biomarkers.

In this project, we further validated that S100A1, MCM7 and JUND were amplified and overexpressed in rectal cancer by Real-time PCR. S100A1 was reported to overexpressed in ovarian cancers compared with normal tissues in mRNA and protein levels, and its overexpression was associated with relapse-free survival in the endometrioid subtype of ovarian cancers(DeRycke et al. 2009). Barraclough et al. revealed that S100A1 played important role in metastasis of cancer(Wang et al. 2000). MCM7 positive expression was significantly associated with worse overall survival and recurrence-free survival in the patients with Duck C(Ishibashi et al. 2014). Its overexpression was also associated with poor prognosis of esophageal squamous cell carcinoma(Zhong et al. 2015). And inhibition of MCM7 significantly reduced the metastasis of prostate cancer in vivo study(Shi et al. 2010). JUND was a member of AP-1 components, and regulated the proliferation and invasion of lung cancer(Chen et al. 2008; Zhang et al. 2016). Although many literatures have reported the roles of S100A1, MCM7 and JUND in some types of cancers, its roles in rectal cancer were limited. And our findings suggested that S100A1, MCM7 and JUND may play important roles in carcinogenesis of rectal cancer.

By pathway enrichment analysis, we found that 14 pathways enriched in genes with copy number changes. Most importantly, VEGF signaling pathway was identified. Many anti-tumor agents target the members of the VEGF signaling pathway, for example bevacizumab targets the VEGF-A which is a key player in the angiogenesis pathway(Fakih 2013; Saif 2013). Therefore, our results may provide the biomarkers for drug selection and efficacy assessment.

In summary, our study identified multiple distant 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.