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Expression and Prognostic Significance of lncRNA MALAT1 in Pancreatic Cancer Tissues

Expression and Prognostic Significance of lncRNA MALAT1 in Pancreatic Cancer Tissues Background: Long non-coding RNAs (lncRNAs) have been recently observed in various human cancers. However, the role of lncRNAs in pancreatic duct adenocarcinoma (PDAC) remains unclarified. The aim of this study was to detect the expression of lncRNA MALAT1 in PDAC formalin-fixed, paraffin embedded (FFPE) tissues and to investigate the clinical significance of the MALAT1 level. Methods: The expression of MALAT1 was examined in 45 PDAC and 25 adjacent non-cancerous FFPE tissues, as well as in five PDAC cell lines and a normal pancreatic epithelium cell line HPDE6c-7, using qRT-PCR. The relationship between MALAT1 level and clinicopathological parameters of PDAC was analyzed with the Kaplan-Meier method and Cox proportional hazards model. Results: The relative level of MALAT1 was significantly higher in PDAC compared to the adjacent normal pancreatic tissues (p=0.009). When comparing the MALAT1 level in the cultured cell lines, remarkably higher expression of MALAT1 was found in aspc-1 PDAC cells compared with the immortal pancreatic duct epithelial cell line HPDE6c-7 (q=7.573, p<0.05). Furthermore, MALAT1 expression level showed significant correlation with tumor size (r=0.35, p=0.018), tumor stage (r=0.439, p=0.003) and depth of invasion (r=0.334, p=0.025). Kaplan-Meier analysis revealed that patients with higher MALAT1 expression had a poorer disease free survival (p=0.043). Additionally, multivariate analysis indicated that overexpression of MALAT1, as well as the tumor location and nerve invasion, was an independent predictor of disease-specific survival of PDAC. Conclusion: MALAT1 might be considered as a potential prognostic indicator and may be a target for diagnosis and gene therapy for PDAC. Keywords: Pancreatic cancer - long non-coding RNA - MALAT1 - survival - prognosis Asian Pac J Cancer Prev, 15 (7), 2971-2977 prevention and treatment (Prassas et al., 2012). Recently, Introduction there has been growing evidence to indicate that non- Pancreatic cancer (PC) is a highly malignant tumor coding RNAs (ncRNAs) can influence cancer onset, with increasing incidence and mortality in the world progression and outcome, which provides new insights (Canyilmaz et al., 2013; Siegel et al., 2013; Zahir et al., into the biology of PC (Gutschner et al., 2013; Kim et al., 2013), which leads to disproportionately high percentage 2013). In the human genome, the ratio of non-coding DNA (6.58%) of cancer-related deaths (Siegel et al., 2011). to total genomic DNA is nearly 98.5%. Recent studies In USA, it is the fourth leading cause of cancer -related have shown that transcription is not limited to protein- deaths, with deleted estimated 43, 920 new cases and 37, coding regions, but is available in the whole genome 390 deaths in 2012 (Siegel et al., 2012). In China, it is the (>90%), including non-coding regions. This yields large sixth main cause of cancer death with 3.66% incidence numbers of ncRNAs (Consortium, 2007). Based on and 2.55% mortality of all cancer incident cases in 2013 transcript size, regulatory ncRNAs can be further divided (Chen et al., 2013c). Pancreatic duct adenocarcinoma into two subclasses: small ncRNA (20-200nt) and long (PDAC) accounts for approximately 90% of primary PC ncRNAs (lncRNAs, >200nt) ( Tano and Akimitsu, 2012; (Haugk, 2010), with an overall 5-year survival rate of 5% Tzadok et al., 2013;Liu et al., 2014). Some lncRNAs and a median survival time of 6 months (Schneider et al., can execute a wide range of vital functions, for instance, 2005). This poor prognosis is due to the late diagnosis and gene regulation (Yang et al., 2011), splicing control (Zong lack of effective treatments (Shrikhande et al., 2011; Tajiri et al., 2011) or X chromosome dosage compensation et al., 2012). Despite the recent advances in clinical and (Tian et al., 2010) in the cell. The lncRNAs are also experimental oncology, the prognosis of PC still remains associated with human diseases, especially cancer, since poor (Mardin et al., 2013). Thus a thorough understanding lncRNAs can be deregulated and actively contribute to of the mechanism underlying the development and tumorigenesis (Gutschner and Diederichs, 2012; Spizzo progression of PC is essential to improve the diagnosis, et al., 2012). Metastasis Associated Lung adenocarcinoma 1 2 Department of Emergency, Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China Equal contributors *For correspondence: 13878802796@163.com Asian Pacific Journal of Cancer Prevention, Vol 15, 2014 2971 Jiang-Hua Liu et al Transcript1 (MALAT1), also known as nuclear-enriched RNA preparation, reverse transcription and quantitative abundant transcript 2 (NEAT2), has an evolutionarily real-time PCR highly conserved, long noncoding 8.7-kb transcript, which Total RNAs were extracted from FFPE cancer and ANT locates on chromosome 11q13 (Ji et al., 2003). MALAT1 tissues by using RNeasy FFPE Kit (QIAGEN, Germany), presents no protein expression in vitro translation because abiding by the manufacturer protocol. RNA was isolated there are no open reading frames. MALAT1 co-localizes from the cultured cells by using an RNA isolation kit (TRI with SC35 splicing domains, which is known as nuclear Reagent, Invitrogen, USA) according to the manufacture speckles in mouse and human cells, suggesting a role instructed protocol. Reverse transcription (RT) and qPCR in RNA (Hutchinson et al., 2007). MALAT1 regulates kits were applied to evaluate expression of MALAT1 gene expression and post-transcriptionally modifies from tissue and cell samples. The 20μl RT reactions were primary transcripts (Schorderet and Duboule, 2011), performed using a Maxima First Strand cDNA Synthesis which is highly conserved among mammals and widely Kit (Fermentas, K1641, Canada) and were incubated expressed in normal mouse and human tissues, such as for 30min at 37°C, 5s at 85°C, and then stabilized lung and pancreas, as well as in multiple cancer types, at 4°C. For relative qPCR, 2μl diluted RT products including lung, breast, colon, prostate and liver cancers were mixed with 12.5μl of 2×SYBRPremix Ex TaqⅡ (Lin et al., 2007). However, the relationship between the (Roche, Switzerland), 1μl forward and reverse primers expression of MALAT1 and PDAC development and and 8.5μl nuclease-free water in a final volume of 25μl progression remains unclear. The aim of the current study according to manufacturer instructions. Glyceraldehyde- is to detect the expression of MALAT1 in PDAC tissues 3-phosphate dehydrogenase (GAPDH) was selected as and to explore the relationship between MALAT1 level an internal control. The PCR primers were as follows: and clinicopathological features and patient survival. MALAT1 sense, 5’AGTACAGCACAGTGCAGCTT3’, reverse, 5’CCCACCAATCCCAACCGTAA3’; GAPDH sense 5’GTAAGACCCCTGGACCACCA3’; reverse, Materials and Methods 5’CAAGGGGTCTACATGGCAACT3’. All reactions Patients and tissue samples were operated on the Eppendorf Master cycler EP Forty-five formalin-fixed, paraffin embedded (FFPE) Gradient S (Eppendorf, Germany) with following PADC tissues were obtained from the patients who conditions: 95°C for 30s , followed by 40 cycles at underwent primary surgical resection of PADC between 95°C for 15s and 60°C for 1min. Real-time PCR was January, 2010 and November, 2011 at the First Affiliated performed in triplicate, including no template controls. Hospital of Guangxi Medical University in China. Twenty- Amplification of the appropriate product was confirmed five cases contained adjacent non-tumor (ANT) pancreatic by melting curve analysis and gel electrophoresis. Relative tissues. The diagnosis of PADC was confirmed by two mRNA expression of MALAT1 was calculated with the −ΔΔCT experienced pathologists. Clinicopathological features comparative threshold cycle (CT) (2 ) method ( Livak were collected, including age, gender, clinical stage, grade, and Schmittgen, 2001;Chen et al., 2013a; 2013b). venous invasion, nervous invasion, status of lymphatic metastasis, distant metastasis, tumor node metastasis Statistical analysis (TNM) stage (Qureshi et al., 2011), carbohydrate antigen The Student test, one ANOVA test, Mann-Whitney 19-9 (CA19-9) and carcinomacmbryonic antigen (CEA). test or χ test were performed to study the significance Post-surgery follow-up was performed every 6 months till of differences between groups using SPSS 19.0 software November 30, 2013. All patients had completed follow- (Chicago, USA). Spearman correlation was applied to up information. The disease specific survival (DSS) was study the relationship between MALAT1 expression defined as the length of time between the surgery and and clinicopathological parameters. Receiver operator death. The study was approved by the Research Ethics characteristic curve (ROC) was employed to identify the Committee of the First Affiliated Hospital of Guangxi diagnostic value. DSS rates were calculated by Kaplan- Medical University, China. Informed written consents Meier method with the log-rank test. Variables with a value were obtained from all patients who participated in this of p<0.05 in univariate analysis were used in subsequent study. multivariate analysis on the basis of Cox proportional hazards mode. p values less than 0.05 were considered Cell lines statistically significant. The human pancreatic cancer cell lines including Panc- 1, Bxpc-3, Aspc-1, Capan-1, Miapaca-2 and the human Results immortal pancreatic duct epithelial cell line HPDE6C-7 were purchased from the Institute of Biochemistry and Expression of MALAT1 in PADC tissues Cell Biology of the Chinese Academy of Sciences (Wuhan, The expression of MALAT1 was significantly higher China). Panc-1, Capan-1 and Miapaca-2 cell lines were in PADC compared with ANT tissues (p=0.009; Figure maintained routinely in Dulbecco’s modified Eagle’s 1A). Furthermore, ROC curve was performed to identify medium (wisent, China), while Bxpc-3, Aspc-1 and the diagnostic value of MALAT1 level in PDAC. The HPDE6C-7 were cultured in supplemented 1640 (wisent, area under curve (AUC) of MALAT1 was 0.69 (95%CI China) with 10% fetal bovine serum (FBS), 100U/ml 0.561~0.829, p=0.009). The cut-off value for MALAT1 penicillin and 100mg/ml streptomycin at 37°C in a 10% was 0.1035. The sensitivity and specificity were 77.8% CO atmosphere. and 60%, respectively (Figure 1B). Asian Pacific Journal of Cancer Prevention, Vol 15, 2014 2972 DOI:http://dx.doi.org/10.7314/APJCP.2014.15.7.2971 Expression of MALAT1 in PC cell lines and HPDE6C- 7cells MALAT1 expression in PC cancer cell lines and HPDE6C-7cell line were also quantified. A significant higher expression of MALAT1 was found in aspc- 1 than in HPDE6C-7 (q=7.573, p<0.05). However, lower expression of MALAT1 was detected in Bxpc-3, miapaca-2 and capan-1 same as above (q=7.573, q=7.446, q=9.45 respectively, p<0.05). There was no significant Figure 1. MALAT1 Expression and its Diagnostic difference of MALAT1 expression between panc-1 and value in PDAC. Quantitative real-time RT-PCR was HPDE6C-7 cells (q=2.130, p>0.05, Figure 2). performed to detect the expression of MALAT1 in pancreatic duct adenocarcinoma tissue (PDAC) and adjacent non-tumor Relationship between MALAT1 expression and (ANT) tissue (A). ROC curve of MALAT1 level in PDAC (B) clinicopathological factors in PDAC . The area under curve (AUC) of MALAT1 was 0.69 (95%CI To assess the correlation of MALAT1 expression 0.561~0.829, p=0.009). with clinicopathological data, expression of MALAT1 in tumor tissues were categorized as low or high according to the mean value. The higher expression of MALAT1 Figure 2. Expression of MALAT1 in Five Human Pancreatic Cancer Cell Lines and an Immortal Figure 3. Relationship between MALAT1 Expression Pancreatic Duct Epithelial Cell Line HPDE6C-7. A significant higher expression of MALAT1 was found in aspc-1 and Clinicopathological Factors in PDAC. MALAT1 and Tumor size (A), Depth of invasion (B) and TNM stage (C) than in HPDE6C-7 (q=7.573, p<0.05). Table 1. Relationship between MALAT1 Expression and Clinicopathological Features of PDAC Characteristics Number MALAT1 expression p value of case High (n=26) % Low (n=19) % Age (years) <58 21 14 53.85% 7 36.84% 0.259 ≥58 24 12 46.15% 12 63.16% Gender Male 26 15 57.69% 11 57.89% 0.989 Female 19 11 42.31% 8 42.11% Tumor size <4 cm 16 5 19.23% 10 52.63% 0.019 ≥4 cm 29 21 80.77% 9 47.37% Location Pancreatic head 31 17 65.38% 15 79.95% 0.321 Pancreatic tail 14 9 34.62% 4 21.05% Histological grade Well 11 5 19.23% 6 31.58% 0.334 Moderately 25 14 53.85% 11 57.89% Poorly/others 9 7 26.92% 2 10.53% Depthof invasion T1,T2 22 9 34.62% 13 64.42% 0.025 T3,T4 23 17 65.38% 6 31.58% Lymphatic metastasis Absent 22 11 42.31% 11 57.89% 0.369 Present 33 15 57.69% 8 42.11% Venousinvasion Absent 30 18 69.23% 13 68.42% 0.954 Present 15 8 30.77% 6 31.58% Nervous invasion Absent 31 17 63.58% 14 73.68% 0.553 Present 14 9 34.62% 5 26.32% Distant metastasis Absent 38 20 76.92% 18 94.74% 0.103 Present 7 6 23.08% 1 5.26% Tumor stage Iv and II 24 9 34.62% 15 78.94% 0.004 III and IV 21 17 65.38% 4 21.05% CA199 <37U/ml 11 7 26.92% 4 21.05% 0.651 ≥37U/ml 34 19 73.10% 15 78.94% CEA <5ng/ml 28 16 61.54% 12 63.15% 0.912 ≥5ng/ml 27 10 38.46% 7 36.84% Asian Pacific Journal of Cancer Prevention, Vol 15, 2014 2973 Jiang-Hua Liu et al Table 3. Multivariate Analysis of Clinicopathological Factors for Disease-specific Survival in PDAC Variable HR 95% CI p value PDAC Location 3.482 1.414-8.547 0.007 Depth of invasion 1.731 6.90-9.312 0.241 Nervous invasion 4.631 1.86-11.553 0.001 MALAT1 1.798 1.177-7.747 0.007 was found in the groups of larger tumor size, later tumor stage and deeper invasion than in the corresponding groups (all p<0.05, Table 1, Figure 3). Moreover, analyzed with Spearman coefficient of correlation, MALAT1 expression level showed closed correlations with tumor size (r=0.35, Figu re 4. Kaplan-Meyer Curves of MALAT1 p=0.018), tumor stage (r=0.439, p=0.003) and depth of expression in PDAC. Patients with high MALAT1 expression invasion (r=0.334, p=0.025). However, no significant had a significantly poorer prognosis than those with low relationship between MALAT1 expression and other expression (p=0.043) clinicopathological features was found, such as age, Table 2. Univariate Analysis of Clinicopathological gender, tumor location, histological grade, lymphatic Factors for Disease-specific Survival in PDAC metastasis, venous invasion, nervous invasion, CA19-9 and CEA (all p>0.05, Table1). Variable PC(N) HR 95%CI p value (Hazard ratio) Correlation between MALAT1 expression and prognosis Age (years) of PDAC patients <58 21 1 0.328-1.488 0.35 As is shown in Figure 4, patients with high MALAT1 ≥58 24 0.696 expression had a significantly poorer prognosis than those Gender with low expression (p=0.043, Figure 4). Univariate Male 26 1 0.333-1.822 0.38 Female 19 0.711 analysis of DSS revealed that the relative level of Tumor size MALAT1 expression (p=0.036), tumor depth (p=0.021), <4 cm 16 1 0.32-1.644 0.444 nervous invasion (p=0.010) and tumor location (p=0.013) ≥4 cm 29 0.721 were prognostic indicators. Other clinicopathological Location features, such as age, gender, tumor size, histological Pancreatic head 31 1 0.98-4.650 0.013 grade lymphatic metastasis, venous invasion, CA199 Pancreatic tail 14 2.103 and ECA were not statistically significant prognosis Histological grade factors (all p>0.05, Table 2). Variables with a value of Well 11 1 0.777-2.614 0.262 p<0.05 were selected for multivariate COX analysis Moderately 25 1.419 Poorly/others 9 (Table 2). Multivariate analysis indicated that MALAT1 Depth of invasion expression level, nervous invasion and tumor location T1,T2 22 1 0.999-4.965 0.021 were independent prognostic indicators for DSS in patients T3,T4 23 2.136 with PDAC (p<0.05, Table3). Lymphatic metastasis Absent 23 1 0.658-3.093 0.368 Discussion Present 22 1.427 Venous invasion With the advance of high resolution microarray and Absent 30 1 0.446-2.359 0.939 genome wide sequencing technology, lncRNAs have Present 15 1.034 Nervous invasion recently caught increasing attention ( Ma et al., 2012; Tang Absent 31 1 0.893-4.847 0.01 et al., 2013; Liu et al., 2014). Some studies suggest that Present 14 2.08 dysexpression of lncRNAs is associated with numerous Distant metastasis diseases including cancer (Wapinski and Chang, 2011; Absent 38 1 0.211-1.800 0.423 Tang et al., 2013). Furthermore, lncRNAs have been Present 7 0.641 identified to play a major role in the development and Tumor stage progression of different cancers. Some well-defined I and II 24 1 0.296-1.456 0.298 lncRNAs, including HOTAIR (Gupta et al., 2010; Kim et III and IV 21 0.654 al., 2013; Nakagawa et al., 2013), MEG3 (Lu et al., 2013) CA199 <37U/ml 11 1 0.471-2.859 0.738 and LOC285194 (Qi et al., 2013) have been reported to ≥37U/ml 34 1.167 be strongly associated to survival of cancer patients, thus CEA they have been determined as prognostic indicators for a <5ng/ml 28 1 0.307-1.636 0.402 delete certain types of cancers. ≥5ng/ml 27 0.709 MALAT1 was first discovered to be three folds higher MALAT1 expressed in metastasizing human non-small-cell lung Low 19 1 1.027-2.205 0.036 carcinomas (NSCLCs) compared to the non-metastasizing High 26 1.505 tumor using RT-PCR by Ji P, et al in 2003 (Ji et al., Asian Pacific Journal of Cancer Prevention, Vol 15, 2014 2974 DOI:http://dx.doi.org/10.7314/APJCP.2014.15.7.2971 2003). Other groups also studied the expression level and expression and other clinicopathological features in the functions of MALAT1 in different types of malignancies. current study, including age, gender, tumor location, However, no report of MALAT1 in PDAC was found. lymphatic metastasis, venous invasion, nervous invasion, MALAT1 has been found to be up-regulated in several distant metastasis, CA199 and CEA levels. Further large- solid tumors, such as NSCLSs (Schmidt et al., 2011) scale studies are needed to confirm our findings. endometrial stromal sarcoma (Yamada et al., 2006), HCC Next, we studied the influence of MALAT1 expression (Lin et al., 2007), bladder urothelial carcinoma (Han et on patient survival. Kaplan-Meier analysis indicated al., 2013) and prostate cancer (Ren et al., 2013). Thus, that patients with high MALAT1 expression had a we speculated that MALAT1 also had similar impact poorer disease free survival than those of low MALAT1 on the tumorigenesis, development and progression of expression in PDAC. Moreover, Univariate analysis PDAC, which might be linked to prognosis of PDAC of DSS revealed that the relative level of MALAT1 patients. To confirm these hypotheses, we firstly detected expression, tumor location, depth of invasion and nervous the MALAT1 level in 45 pairs of PDAC and 25 adjacent invasion could be prognostic indicators. Multivariate normal tissues by RT-qPCR. The relative expression level analysis further showed that expression of MALAT1, of MALAT1 was significantly higher in tumor compared together with tumor location and nervous invasion, was with adjacent normal tissues. This result was confirmed an independent predictor of disease specific survival for in the in vitro sample. The MALAT1 expression in Aspc- PDAC. This was in agreement with the prognostic role 1 cell lines was also remarkably higher compared with of MALAT1 in colorectal cancer (Ji et al., 2013), HCC immortal pancreatic duct epithelial cell line HDPE6C-7. (Lai et al., 2012) and NSCLC (Schmidt et al., 2011). The overexpression of MALAT1 in PDAC tissues and Thus, high MALAT1 expression in several tumors was PDAC Aspc-1 cells suggested that MALAT1 could act associated with a poor prognosis and MALAT1 could act as an oncogene in PDAC similar to other tumors. We as an independent prognostic factor for predicting tumor also performed the ROC curve to identify the diagnostic prognosis, including PDAC. significance of MALAT1 expression in PDAC and the Over-expression of MALAT1 may influence the AUC area was 0.69, suggesting a possible diagnostic development, progression and prognosis of PDAC. value of MALAT1. However, this was based on a limited However, the molecular mechanism involved is unclear. numbers of patients. More evidence should be provided MALAT1 was associated with epithelial mesenchymal with a larger cohort in the future. Most recently, based on transition (EMT) that allowed cancer cells to obtain small numbers, MALAT1 was shown to be detectable in invasive capacity. Ying et al. (2012) demonstrated that the cellular fraction of peripheral human blood, showing down- regulation of MALAT1 caused a decrease of ZEB1, different expression levels between NSCLC patients and ZEB2 and Slug levels, and an increase of E-cadherin cancer-free controls. For the discrimination of NSCLC levels in EMT of bladder cancer cell. Qing et al. (Ji et patients from cancer-free controls a sensitivity of 56% was al., 2013) reported that in colorectal cancer, MALAT1 calculated conditional on a high specificity of 96%. The might indirectly interact with ß-catenin to affect its signal results of this study by Weber, et al (Weber et al., 2013) cascade. Target genes of MALAT1 may differ between indicated that MALAT1 complied with key characteristics specific tissues and cell types. The specific target genes of diagnostic biomarkers, i.e., minimal invasiveness, and signal-pathway controlled by MALAT1 in PDAC high specificity, and robustness. It remains interesting require detailed investigation in the future. to investigate the plasma MALAT1 level as a biomarker Some studies had proved that down-regulation of in PDAC to improve the entire diagnostic performance. MALAT1 level can regulate apoptosis genes expression Then we went further to investigate the relationship such ascaspase-3, caspase-8, Bax, Bcl-2, and Bclxl, which between MALAT1 expression and different leads to inhibit cervical cancer on cell growth, cell cycle clinicopathological parameters. The significantly higher progression and invasion (Guo et al., 2010). In A549 MALAT1 expression was found in the groups of larger NSCLCs, RNAi-mediated suppression of MALAT1 RNA tumor size, deeper invasion and advanced stage, delete suppressed migration and clonogenic growth (Schmidt compared to their corresponding groups. Spearman et al., 2011). Similarly, cell proliferation inhibition, correlation also showed the positive relationships between increased apoptosis, and decreased motility were observed MALAT1 level and tumor size, depth of invasion and in MALAT1 small interfering RNA-transfected bladder tumor stage. Since the clinicopathological parameters urothelial carcinoma T24 and 5637 cells (Han et al., 2013). of tumor size, depth of invasion and tumor stage These studies indicated that MALAT1 could be a potential represent partially the deterioration and progress of the target for molecular therapy for cancers. However, it tumor, MALAT1 might be a factor related to the tumor remains to be investigated how MALAT1 could contribute progression. Similarly to our finding, MALAT1 expression in the treatment of PDAC. levels were reported to be greater in invasive bladder In conclusion, above all, our results showed that urothelial carcinoma than in noninvasive carcinoma (Han MALAT1 mRNA level was significantly higher in et al., 2013). In the same study, MALAT1 expression levels PADC tissues and some PC cell lines. A high expression were greater in high-grade bladder urothelial carcinomas of MALAT1 was detected in tumors of larger size, than in low-grade carcinoma (Han et al., 2013), which advanced tumor stage and deeper invasion. In addition, was inconsistent with our current study, indicating that the overexpression of MALAT1 was associated with poor the function and contribution of MALAT1 could be tumor prognosis. These findings suggested that MALAT1 might dependent. 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RNA Biol, 8, 968-77. Asian Pacific Journal of Cancer Prevention, Vol 15, 2014 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Asian Pacific Journal of Cancer Prevention Unpaywall

Expression and Prognostic Significance of lncRNA MALAT1 in Pancreatic Cancer Tissues

Asian Pacific Journal of Cancer PreventionApr 1, 2014

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10.7314/apjcp.2014.15.7.2971
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Abstract

Background: Long non-coding RNAs (lncRNAs) have been recently observed in various human cancers. However, the role of lncRNAs in pancreatic duct adenocarcinoma (PDAC) remains unclarified. The aim of this study was to detect the expression of lncRNA MALAT1 in PDAC formalin-fixed, paraffin embedded (FFPE) tissues and to investigate the clinical significance of the MALAT1 level. Methods: The expression of MALAT1 was examined in 45 PDAC and 25 adjacent non-cancerous FFPE tissues, as well as in five PDAC cell lines and a normal pancreatic epithelium cell line HPDE6c-7, using qRT-PCR. The relationship between MALAT1 level and clinicopathological parameters of PDAC was analyzed with the Kaplan-Meier method and Cox proportional hazards model. Results: The relative level of MALAT1 was significantly higher in PDAC compared to the adjacent normal pancreatic tissues (p=0.009). When comparing the MALAT1 level in the cultured cell lines, remarkably higher expression of MALAT1 was found in aspc-1 PDAC cells compared with the immortal pancreatic duct epithelial cell line HPDE6c-7 (q=7.573, p<0.05). Furthermore, MALAT1 expression level showed significant correlation with tumor size (r=0.35, p=0.018), tumor stage (r=0.439, p=0.003) and depth of invasion (r=0.334, p=0.025). Kaplan-Meier analysis revealed that patients with higher MALAT1 expression had a poorer disease free survival (p=0.043). Additionally, multivariate analysis indicated that overexpression of MALAT1, as well as the tumor location and nerve invasion, was an independent predictor of disease-specific survival of PDAC. Conclusion: MALAT1 might be considered as a potential prognostic indicator and may be a target for diagnosis and gene therapy for PDAC. Keywords: Pancreatic cancer - long non-coding RNA - MALAT1 - survival - prognosis Asian Pac J Cancer Prev, 15 (7), 2971-2977 prevention and treatment (Prassas et al., 2012). Recently, Introduction there has been growing evidence to indicate that non- Pancreatic cancer (PC) is a highly malignant tumor coding RNAs (ncRNAs) can influence cancer onset, with increasing incidence and mortality in the world progression and outcome, which provides new insights (Canyilmaz et al., 2013; Siegel et al., 2013; Zahir et al., into the biology of PC (Gutschner et al., 2013; Kim et al., 2013), which leads to disproportionately high percentage 2013). In the human genome, the ratio of non-coding DNA (6.58%) of cancer-related deaths (Siegel et al., 2011). to total genomic DNA is nearly 98.5%. Recent studies In USA, it is the fourth leading cause of cancer -related have shown that transcription is not limited to protein- deaths, with deleted estimated 43, 920 new cases and 37, coding regions, but is available in the whole genome 390 deaths in 2012 (Siegel et al., 2012). In China, it is the (>90%), including non-coding regions. This yields large sixth main cause of cancer death with 3.66% incidence numbers of ncRNAs (Consortium, 2007). Based on and 2.55% mortality of all cancer incident cases in 2013 transcript size, regulatory ncRNAs can be further divided (Chen et al., 2013c). Pancreatic duct adenocarcinoma into two subclasses: small ncRNA (20-200nt) and long (PDAC) accounts for approximately 90% of primary PC ncRNAs (lncRNAs, >200nt) ( Tano and Akimitsu, 2012; (Haugk, 2010), with an overall 5-year survival rate of 5% Tzadok et al., 2013;Liu et al., 2014). Some lncRNAs and a median survival time of 6 months (Schneider et al., can execute a wide range of vital functions, for instance, 2005). This poor prognosis is due to the late diagnosis and gene regulation (Yang et al., 2011), splicing control (Zong lack of effective treatments (Shrikhande et al., 2011; Tajiri et al., 2011) or X chromosome dosage compensation et al., 2012). Despite the recent advances in clinical and (Tian et al., 2010) in the cell. The lncRNAs are also experimental oncology, the prognosis of PC still remains associated with human diseases, especially cancer, since poor (Mardin et al., 2013). Thus a thorough understanding lncRNAs can be deregulated and actively contribute to of the mechanism underlying the development and tumorigenesis (Gutschner and Diederichs, 2012; Spizzo progression of PC is essential to improve the diagnosis, et al., 2012). Metastasis Associated Lung adenocarcinoma 1 2 Department of Emergency, Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China Equal contributors *For correspondence: 13878802796@163.com Asian Pacific Journal of Cancer Prevention, Vol 15, 2014 2971 Jiang-Hua Liu et al Transcript1 (MALAT1), also known as nuclear-enriched RNA preparation, reverse transcription and quantitative abundant transcript 2 (NEAT2), has an evolutionarily real-time PCR highly conserved, long noncoding 8.7-kb transcript, which Total RNAs were extracted from FFPE cancer and ANT locates on chromosome 11q13 (Ji et al., 2003). MALAT1 tissues by using RNeasy FFPE Kit (QIAGEN, Germany), presents no protein expression in vitro translation because abiding by the manufacturer protocol. RNA was isolated there are no open reading frames. MALAT1 co-localizes from the cultured cells by using an RNA isolation kit (TRI with SC35 splicing domains, which is known as nuclear Reagent, Invitrogen, USA) according to the manufacture speckles in mouse and human cells, suggesting a role instructed protocol. Reverse transcription (RT) and qPCR in RNA (Hutchinson et al., 2007). MALAT1 regulates kits were applied to evaluate expression of MALAT1 gene expression and post-transcriptionally modifies from tissue and cell samples. The 20μl RT reactions were primary transcripts (Schorderet and Duboule, 2011), performed using a Maxima First Strand cDNA Synthesis which is highly conserved among mammals and widely Kit (Fermentas, K1641, Canada) and were incubated expressed in normal mouse and human tissues, such as for 30min at 37°C, 5s at 85°C, and then stabilized lung and pancreas, as well as in multiple cancer types, at 4°C. For relative qPCR, 2μl diluted RT products including lung, breast, colon, prostate and liver cancers were mixed with 12.5μl of 2×SYBRPremix Ex TaqⅡ (Lin et al., 2007). However, the relationship between the (Roche, Switzerland), 1μl forward and reverse primers expression of MALAT1 and PDAC development and and 8.5μl nuclease-free water in a final volume of 25μl progression remains unclear. The aim of the current study according to manufacturer instructions. Glyceraldehyde- is to detect the expression of MALAT1 in PDAC tissues 3-phosphate dehydrogenase (GAPDH) was selected as and to explore the relationship between MALAT1 level an internal control. The PCR primers were as follows: and clinicopathological features and patient survival. MALAT1 sense, 5’AGTACAGCACAGTGCAGCTT3’, reverse, 5’CCCACCAATCCCAACCGTAA3’; GAPDH sense 5’GTAAGACCCCTGGACCACCA3’; reverse, Materials and Methods 5’CAAGGGGTCTACATGGCAACT3’. All reactions Patients and tissue samples were operated on the Eppendorf Master cycler EP Forty-five formalin-fixed, paraffin embedded (FFPE) Gradient S (Eppendorf, Germany) with following PADC tissues were obtained from the patients who conditions: 95°C for 30s , followed by 40 cycles at underwent primary surgical resection of PADC between 95°C for 15s and 60°C for 1min. Real-time PCR was January, 2010 and November, 2011 at the First Affiliated performed in triplicate, including no template controls. Hospital of Guangxi Medical University in China. Twenty- Amplification of the appropriate product was confirmed five cases contained adjacent non-tumor (ANT) pancreatic by melting curve analysis and gel electrophoresis. Relative tissues. The diagnosis of PADC was confirmed by two mRNA expression of MALAT1 was calculated with the −ΔΔCT experienced pathologists. Clinicopathological features comparative threshold cycle (CT) (2 ) method ( Livak were collected, including age, gender, clinical stage, grade, and Schmittgen, 2001;Chen et al., 2013a; 2013b). venous invasion, nervous invasion, status of lymphatic metastasis, distant metastasis, tumor node metastasis Statistical analysis (TNM) stage (Qureshi et al., 2011), carbohydrate antigen The Student test, one ANOVA test, Mann-Whitney 19-9 (CA19-9) and carcinomacmbryonic antigen (CEA). test or χ test were performed to study the significance Post-surgery follow-up was performed every 6 months till of differences between groups using SPSS 19.0 software November 30, 2013. All patients had completed follow- (Chicago, USA). Spearman correlation was applied to up information. The disease specific survival (DSS) was study the relationship between MALAT1 expression defined as the length of time between the surgery and and clinicopathological parameters. Receiver operator death. The study was approved by the Research Ethics characteristic curve (ROC) was employed to identify the Committee of the First Affiliated Hospital of Guangxi diagnostic value. DSS rates were calculated by Kaplan- Medical University, China. Informed written consents Meier method with the log-rank test. Variables with a value were obtained from all patients who participated in this of p<0.05 in univariate analysis were used in subsequent study. multivariate analysis on the basis of Cox proportional hazards mode. p values less than 0.05 were considered Cell lines statistically significant. The human pancreatic cancer cell lines including Panc- 1, Bxpc-3, Aspc-1, Capan-1, Miapaca-2 and the human Results immortal pancreatic duct epithelial cell line HPDE6C-7 were purchased from the Institute of Biochemistry and Expression of MALAT1 in PADC tissues Cell Biology of the Chinese Academy of Sciences (Wuhan, The expression of MALAT1 was significantly higher China). Panc-1, Capan-1 and Miapaca-2 cell lines were in PADC compared with ANT tissues (p=0.009; Figure maintained routinely in Dulbecco’s modified Eagle’s 1A). Furthermore, ROC curve was performed to identify medium (wisent, China), while Bxpc-3, Aspc-1 and the diagnostic value of MALAT1 level in PDAC. The HPDE6C-7 were cultured in supplemented 1640 (wisent, area under curve (AUC) of MALAT1 was 0.69 (95%CI China) with 10% fetal bovine serum (FBS), 100U/ml 0.561~0.829, p=0.009). The cut-off value for MALAT1 penicillin and 100mg/ml streptomycin at 37°C in a 10% was 0.1035. The sensitivity and specificity were 77.8% CO atmosphere. and 60%, respectively (Figure 1B). Asian Pacific Journal of Cancer Prevention, Vol 15, 2014 2972 DOI:http://dx.doi.org/10.7314/APJCP.2014.15.7.2971 Expression of MALAT1 in PC cell lines and HPDE6C- 7cells MALAT1 expression in PC cancer cell lines and HPDE6C-7cell line were also quantified. A significant higher expression of MALAT1 was found in aspc- 1 than in HPDE6C-7 (q=7.573, p<0.05). However, lower expression of MALAT1 was detected in Bxpc-3, miapaca-2 and capan-1 same as above (q=7.573, q=7.446, q=9.45 respectively, p<0.05). There was no significant Figure 1. MALAT1 Expression and its Diagnostic difference of MALAT1 expression between panc-1 and value in PDAC. Quantitative real-time RT-PCR was HPDE6C-7 cells (q=2.130, p>0.05, Figure 2). performed to detect the expression of MALAT1 in pancreatic duct adenocarcinoma tissue (PDAC) and adjacent non-tumor Relationship between MALAT1 expression and (ANT) tissue (A). ROC curve of MALAT1 level in PDAC (B) clinicopathological factors in PDAC . The area under curve (AUC) of MALAT1 was 0.69 (95%CI To assess the correlation of MALAT1 expression 0.561~0.829, p=0.009). with clinicopathological data, expression of MALAT1 in tumor tissues were categorized as low or high according to the mean value. The higher expression of MALAT1 Figure 2. Expression of MALAT1 in Five Human Pancreatic Cancer Cell Lines and an Immortal Figure 3. Relationship between MALAT1 Expression Pancreatic Duct Epithelial Cell Line HPDE6C-7. A significant higher expression of MALAT1 was found in aspc-1 and Clinicopathological Factors in PDAC. MALAT1 and Tumor size (A), Depth of invasion (B) and TNM stage (C) than in HPDE6C-7 (q=7.573, p<0.05). Table 1. Relationship between MALAT1 Expression and Clinicopathological Features of PDAC Characteristics Number MALAT1 expression p value of case High (n=26) % Low (n=19) % Age (years) <58 21 14 53.85% 7 36.84% 0.259 ≥58 24 12 46.15% 12 63.16% Gender Male 26 15 57.69% 11 57.89% 0.989 Female 19 11 42.31% 8 42.11% Tumor size <4 cm 16 5 19.23% 10 52.63% 0.019 ≥4 cm 29 21 80.77% 9 47.37% Location Pancreatic head 31 17 65.38% 15 79.95% 0.321 Pancreatic tail 14 9 34.62% 4 21.05% Histological grade Well 11 5 19.23% 6 31.58% 0.334 Moderately 25 14 53.85% 11 57.89% Poorly/others 9 7 26.92% 2 10.53% Depthof invasion T1,T2 22 9 34.62% 13 64.42% 0.025 T3,T4 23 17 65.38% 6 31.58% Lymphatic metastasis Absent 22 11 42.31% 11 57.89% 0.369 Present 33 15 57.69% 8 42.11% Venousinvasion Absent 30 18 69.23% 13 68.42% 0.954 Present 15 8 30.77% 6 31.58% Nervous invasion Absent 31 17 63.58% 14 73.68% 0.553 Present 14 9 34.62% 5 26.32% Distant metastasis Absent 38 20 76.92% 18 94.74% 0.103 Present 7 6 23.08% 1 5.26% Tumor stage Iv and II 24 9 34.62% 15 78.94% 0.004 III and IV 21 17 65.38% 4 21.05% CA199 <37U/ml 11 7 26.92% 4 21.05% 0.651 ≥37U/ml 34 19 73.10% 15 78.94% CEA <5ng/ml 28 16 61.54% 12 63.15% 0.912 ≥5ng/ml 27 10 38.46% 7 36.84% Asian Pacific Journal of Cancer Prevention, Vol 15, 2014 2973 Jiang-Hua Liu et al Table 3. Multivariate Analysis of Clinicopathological Factors for Disease-specific Survival in PDAC Variable HR 95% CI p value PDAC Location 3.482 1.414-8.547 0.007 Depth of invasion 1.731 6.90-9.312 0.241 Nervous invasion 4.631 1.86-11.553 0.001 MALAT1 1.798 1.177-7.747 0.007 was found in the groups of larger tumor size, later tumor stage and deeper invasion than in the corresponding groups (all p<0.05, Table 1, Figure 3). Moreover, analyzed with Spearman coefficient of correlation, MALAT1 expression level showed closed correlations with tumor size (r=0.35, Figu re 4. Kaplan-Meyer Curves of MALAT1 p=0.018), tumor stage (r=0.439, p=0.003) and depth of expression in PDAC. Patients with high MALAT1 expression invasion (r=0.334, p=0.025). However, no significant had a significantly poorer prognosis than those with low relationship between MALAT1 expression and other expression (p=0.043) clinicopathological features was found, such as age, Table 2. Univariate Analysis of Clinicopathological gender, tumor location, histological grade, lymphatic Factors for Disease-specific Survival in PDAC metastasis, venous invasion, nervous invasion, CA19-9 and CEA (all p>0.05, Table1). Variable PC(N) HR 95%CI p value (Hazard ratio) Correlation between MALAT1 expression and prognosis Age (years) of PDAC patients <58 21 1 0.328-1.488 0.35 As is shown in Figure 4, patients with high MALAT1 ≥58 24 0.696 expression had a significantly poorer prognosis than those Gender with low expression (p=0.043, Figure 4). Univariate Male 26 1 0.333-1.822 0.38 Female 19 0.711 analysis of DSS revealed that the relative level of Tumor size MALAT1 expression (p=0.036), tumor depth (p=0.021), <4 cm 16 1 0.32-1.644 0.444 nervous invasion (p=0.010) and tumor location (p=0.013) ≥4 cm 29 0.721 were prognostic indicators. Other clinicopathological Location features, such as age, gender, tumor size, histological Pancreatic head 31 1 0.98-4.650 0.013 grade lymphatic metastasis, venous invasion, CA199 Pancreatic tail 14 2.103 and ECA were not statistically significant prognosis Histological grade factors (all p>0.05, Table 2). Variables with a value of Well 11 1 0.777-2.614 0.262 p<0.05 were selected for multivariate COX analysis Moderately 25 1.419 Poorly/others 9 (Table 2). Multivariate analysis indicated that MALAT1 Depth of invasion expression level, nervous invasion and tumor location T1,T2 22 1 0.999-4.965 0.021 were independent prognostic indicators for DSS in patients T3,T4 23 2.136 with PDAC (p<0.05, Table3). Lymphatic metastasis Absent 23 1 0.658-3.093 0.368 Discussion Present 22 1.427 Venous invasion With the advance of high resolution microarray and Absent 30 1 0.446-2.359 0.939 genome wide sequencing technology, lncRNAs have Present 15 1.034 Nervous invasion recently caught increasing attention ( Ma et al., 2012; Tang Absent 31 1 0.893-4.847 0.01 et al., 2013; Liu et al., 2014). Some studies suggest that Present 14 2.08 dysexpression of lncRNAs is associated with numerous Distant metastasis diseases including cancer (Wapinski and Chang, 2011; Absent 38 1 0.211-1.800 0.423 Tang et al., 2013). Furthermore, lncRNAs have been Present 7 0.641 identified to play a major role in the development and Tumor stage progression of different cancers. Some well-defined I and II 24 1 0.296-1.456 0.298 lncRNAs, including HOTAIR (Gupta et al., 2010; Kim et III and IV 21 0.654 al., 2013; Nakagawa et al., 2013), MEG3 (Lu et al., 2013) CA199 <37U/ml 11 1 0.471-2.859 0.738 and LOC285194 (Qi et al., 2013) have been reported to ≥37U/ml 34 1.167 be strongly associated to survival of cancer patients, thus CEA they have been determined as prognostic indicators for a <5ng/ml 28 1 0.307-1.636 0.402 delete certain types of cancers. ≥5ng/ml 27 0.709 MALAT1 was first discovered to be three folds higher MALAT1 expressed in metastasizing human non-small-cell lung Low 19 1 1.027-2.205 0.036 carcinomas (NSCLCs) compared to the non-metastasizing High 26 1.505 tumor using RT-PCR by Ji P, et al in 2003 (Ji et al., Asian Pacific Journal of Cancer Prevention, Vol 15, 2014 2974 DOI:http://dx.doi.org/10.7314/APJCP.2014.15.7.2971 2003). Other groups also studied the expression level and expression and other clinicopathological features in the functions of MALAT1 in different types of malignancies. current study, including age, gender, tumor location, However, no report of MALAT1 in PDAC was found. lymphatic metastasis, venous invasion, nervous invasion, MALAT1 has been found to be up-regulated in several distant metastasis, CA199 and CEA levels. Further large- solid tumors, such as NSCLSs (Schmidt et al., 2011) scale studies are needed to confirm our findings. endometrial stromal sarcoma (Yamada et al., 2006), HCC Next, we studied the influence of MALAT1 expression (Lin et al., 2007), bladder urothelial carcinoma (Han et on patient survival. Kaplan-Meier analysis indicated al., 2013) and prostate cancer (Ren et al., 2013). Thus, that patients with high MALAT1 expression had a we speculated that MALAT1 also had similar impact poorer disease free survival than those of low MALAT1 on the tumorigenesis, development and progression of expression in PDAC. Moreover, Univariate analysis PDAC, which might be linked to prognosis of PDAC of DSS revealed that the relative level of MALAT1 patients. To confirm these hypotheses, we firstly detected expression, tumor location, depth of invasion and nervous the MALAT1 level in 45 pairs of PDAC and 25 adjacent invasion could be prognostic indicators. Multivariate normal tissues by RT-qPCR. The relative expression level analysis further showed that expression of MALAT1, of MALAT1 was significantly higher in tumor compared together with tumor location and nervous invasion, was with adjacent normal tissues. This result was confirmed an independent predictor of disease specific survival for in the in vitro sample. The MALAT1 expression in Aspc- PDAC. This was in agreement with the prognostic role 1 cell lines was also remarkably higher compared with of MALAT1 in colorectal cancer (Ji et al., 2013), HCC immortal pancreatic duct epithelial cell line HDPE6C-7. (Lai et al., 2012) and NSCLC (Schmidt et al., 2011). The overexpression of MALAT1 in PDAC tissues and Thus, high MALAT1 expression in several tumors was PDAC Aspc-1 cells suggested that MALAT1 could act associated with a poor prognosis and MALAT1 could act as an oncogene in PDAC similar to other tumors. We as an independent prognostic factor for predicting tumor also performed the ROC curve to identify the diagnostic prognosis, including PDAC. significance of MALAT1 expression in PDAC and the Over-expression of MALAT1 may influence the AUC area was 0.69, suggesting a possible diagnostic development, progression and prognosis of PDAC. value of MALAT1. However, this was based on a limited However, the molecular mechanism involved is unclear. numbers of patients. More evidence should be provided MALAT1 was associated with epithelial mesenchymal with a larger cohort in the future. Most recently, based on transition (EMT) that allowed cancer cells to obtain small numbers, MALAT1 was shown to be detectable in invasive capacity. Ying et al. (2012) demonstrated that the cellular fraction of peripheral human blood, showing down- regulation of MALAT1 caused a decrease of ZEB1, different expression levels between NSCLC patients and ZEB2 and Slug levels, and an increase of E-cadherin cancer-free controls. For the discrimination of NSCLC levels in EMT of bladder cancer cell. Qing et al. (Ji et patients from cancer-free controls a sensitivity of 56% was al., 2013) reported that in colorectal cancer, MALAT1 calculated conditional on a high specificity of 96%. The might indirectly interact with ß-catenin to affect its signal results of this study by Weber, et al (Weber et al., 2013) cascade. Target genes of MALAT1 may differ between indicated that MALAT1 complied with key characteristics specific tissues and cell types. The specific target genes of diagnostic biomarkers, i.e., minimal invasiveness, and signal-pathway controlled by MALAT1 in PDAC high specificity, and robustness. It remains interesting require detailed investigation in the future. to investigate the plasma MALAT1 level as a biomarker Some studies had proved that down-regulation of in PDAC to improve the entire diagnostic performance. MALAT1 level can regulate apoptosis genes expression Then we went further to investigate the relationship such ascaspase-3, caspase-8, Bax, Bcl-2, and Bclxl, which between MALAT1 expression and different leads to inhibit cervical cancer on cell growth, cell cycle clinicopathological parameters. The significantly higher progression and invasion (Guo et al., 2010). In A549 MALAT1 expression was found in the groups of larger NSCLCs, RNAi-mediated suppression of MALAT1 RNA tumor size, deeper invasion and advanced stage, delete suppressed migration and clonogenic growth (Schmidt compared to their corresponding groups. Spearman et al., 2011). Similarly, cell proliferation inhibition, correlation also showed the positive relationships between increased apoptosis, and decreased motility were observed MALAT1 level and tumor size, depth of invasion and in MALAT1 small interfering RNA-transfected bladder tumor stage. Since the clinicopathological parameters urothelial carcinoma T24 and 5637 cells (Han et al., 2013). of tumor size, depth of invasion and tumor stage These studies indicated that MALAT1 could be a potential represent partially the deterioration and progress of the target for molecular therapy for cancers. However, it tumor, MALAT1 might be a factor related to the tumor remains to be investigated how MALAT1 could contribute progression. Similarly to our finding, MALAT1 expression in the treatment of PDAC. levels were reported to be greater in invasive bladder In conclusion, above all, our results showed that urothelial carcinoma than in noninvasive carcinoma (Han MALAT1 mRNA level was significantly higher in et al., 2013). In the same study, MALAT1 expression levels PADC tissues and some PC cell lines. A high expression were greater in high-grade bladder urothelial carcinomas of MALAT1 was detected in tumors of larger size, than in low-grade carcinoma (Han et al., 2013), which advanced tumor stage and deeper invasion. In addition, was inconsistent with our current study, indicating that the overexpression of MALAT1 was associated with poor the function and contribution of MALAT1 could be tumor prognosis. These findings suggested that MALAT1 might dependent. 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RNA Biol, 8, 968-77. Asian Pacific Journal of Cancer Prevention, Vol 15, 2014

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Asian Pacific Journal of Cancer PreventionUnpaywall

Published: Apr 1, 2014

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