Pancreatic cancer still remains one of the most lethal diseases and establishment of new therapy is needed. The purpose of this study is to find novel factors involved in pancreatic cancer progression by proteomic approach. We compared pre- and postoperative serum protein profiling obtained from pancreatic cancer patients who had curative pancreatectomy using surface-enhanced laser desorption ionization time-of-flight mass spectrometry. The peak intensity levels of both 6630 and 6420 Da were significantly higher in the preoperative serum than in the postoperative serum (P<0.002). Sequential amino acid analysis identified these proteins to be apolipoprotein C-1 (ApoC-1). The high level of ApoC-1 in preoperative serum significantly correlated with poor prognosis. Furthermore, ApoC-1 was abundantly expressed in pancreas neoplastic epithelium, and was detected in the culture medium of the pancreatic cancer cell line in vitro, which suggests that cancer cells secrete ApoC-1. Inhibition of ApoC-1 expression by short interfering RNA suppressed cell proliferation and induced apoptosis of pancreatic cancer cells. The specific expression of ApoC-1 and its role in preventing from spontaneous apoptosis in pancreatic cancer cells suggest that ApoC-1 contributes to the aggressiveness of pancreatic cancer and will be useful as a new therapeutic target.
Pancreatic cancer continues to be one of the most lethal malignancies, with a 5-year survival rate of only 4–5% (Jemal et al., 2006). Recent advances in the clinical management of this disease, especially new chemotherapeautic reagents, such as gemcitabine (Burris et al., 1997), have improved patient outcome. In addition, recent progress in molecular cancer biology has led to the development of new molecular targeting therapies for pancreatic cancer; some of these new drugs, such as erlotinib, an epidermal growth factor receptor inhibitor (Moore et al., 2007), have already shown clinical benefits. However, the efficacy of these new therapies has not been sufficient enough, with only a few months' improvement in median survival time, and additional molecular targets are urgently needed.
So far, genetic studies have identified the signature molecular profiles of this malignancy, consisting of mutation in KRAS, CDKN2A, TP53 and SMAD4/DPC4 (Bardeesy and Depinho, 2002). These genetic mutations have been revealed by classical methods of molecular biology, such as genetic analysis of familial cancer syndrome and systematic scan of a loss of heterozygosity in patients with this disease. Recently, development of new technologies has enabled the mass analysis of genetic and proteomic profiles in cancer biology. Among these technologies, proteomic approaches are used to identify new cancer biomarkers. The technique has advantages for detecting differences in protein profiling including post-translational modifications. Although standard methods for protein profiling, such as two-dimensional gel electrophoresis (2DE), have been successfully used to identify new proteins involved in cancer development (Tomonaga et al., 2004), these methods have several limitations. Hydrophobic and low molecular weight proteins resolve poorly, and proteins present in low concentrations often cannot be detected. Surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF MS) combined with the ProteinChip array provides a potentially powerful tool for overcoming these limitations. This procedure results in the identification of protein profiles composed of isolated or clustered peaks that differ according to molecular weight. Thus, different pathological conditions can be identified with high sensitivity and significant reproducibility. This approach has been used to identify specific and sensitive molecular markers (Nomura et al., 2004) in patients with prostatic, pancreatic, liver, colorectal and ovarian malignancies (Xiao et al., 2001; Petricoin et al., 2002; Rosty et al., 2002; Melle et al., 2005; Paradis et al., 2005).
In this study, we sought to identify a molecule that may be involved in pancreatic cancer development or progression using this proteomic approach. Specifically, we used paired pre- and postoperative serum samples obtained from the same patients to exclude individual differences. We found successfully a serum protein, which was upregulated in preoperative serum of pancreatic cancer patients. We also identified an unexpected biological role of this protein in pancreatic cancer cells. Our results indicate that the use of proteomic approach will lead to new insights in research dealing with cancer biology through detection of new biomarkers and elucidation of the molecular mechanisms of cancer.
Serum protein profiling associated with pancreatic cancer based on SELDI-TOF MS analysis
To identify new serum protein characteristics in pancreatic cancer patients, we compared the protein profiling of serum collected from the same patients before and after curative resection to exclude individual differences in serum protein expression. Using SELDI-TOF MS analysis and ProteinChip arrays, serum protein profiling of pre- and postoperative sera were compared in 20 pancreatic cancer patients who had curative resection (Table 1). The Biomarker Wizard function of the ProteinChip software identified clusters of 85 peaks, which had different expression levels in pre- and postoperative sera of pancreatic cancer patients. Proteins with 6630 and 6420 Da m/z peaks in the urea buffer at pH 6.5 were candidates for pancreatic cancer-specific serum proteins (Figure 1a). A SELDI profile of 6630 Da showed a higher intensity in the preoperative serum than in the postoperative serum of 15 patients (75%); the average of 6630 Da peak normalized intensities of the preoperative serum of all 20 patients (mean±s.d.; 2.80±1.95) was significantly higher than that of the postoperative serum (1.65±1.61; P<0.002; Student's paired t-test; Figure 1b). Peak intensities at 6420 Da also showed a significantly higher average peak intensity in the preoperative serum of 20 patients (1.46±1.10) than in their postoperative serum (0.92±0.78; P<0.002; Student's paired t-test; data not shown). We selected these two peaks for further analysis.
Identification of 6630 and 6420 Da proteins as apolipoprotein C-1
We next tried to purify and identify these proteins. The optimized purification conditions were directly transferred to fractionations using fast protein liquid chromatography (FPLC). The eluate was applied to reverse phase columns for further separation from other proteins, and the fractionation was carried out with a stepwise gradient, using two-dimensional high performance liquid chromatography (HPLC). Using these procedures, the target 6630 and 6420 Da proteins were successfully purified (Figure 1c).
N-terminal amino-acid sequence analysis of the purified proteins revealed that they were apolipoprotein C-1 (ApoC-1; Lauer et al., 1988). This analysis was carried out with completely identifying the first 15 amino-acid sequences on the N terminus. We obtained two sequences, which were identical except for two additional amino acids on the N terminus. ApoC-1 is known to have molecular sizes of 6630 and 6420 Da (Wroblewski et al., 2006), which may represent these two amino–acids truncation. The immunodepletion assay confirmed that these peaks were ApoC-1; the reaction of serum with control mouse immunoglobulin G (IgG) did not affect the 6630 and 6420 Da peaks of the ProteinChip array, whereas both peaks were clearly decreased when the anti-ApoC-1 antibody was used (Figure 1d). In addition, western blot analysis of the HPLC final fraction also showed that the band reacted with anti-human ApoC-1 antibody (data not shown).
A high serum ApoC-1 level is associated with a poor prognosis in pancreatic cancer patients
To examine the clinical significance of the ApoC-1 serum level, we assessed whether the ApoC-1 peak intensity level in the serum was clinically relevant in pancreatic cancer patients. Twenty patients were divided into two groups of 10 patients each based on the median value of the sum of 6630 and 6420 Da peak intensity levels of their preoperative serum: the low-level group (LL) had levels below the median value, and the high-level group (HL) had levels above the median value. The Kaplan–Meier analysis showed that the LL group patients had a significantly longer overall survival time than the HL group patients (P=0.005, log-rank test; Figure 2a). To confirm this result, we analysed the peak intensity levels of the 6630 and 6420 Da peptide in the preoperative serum samples from an independent group of 69 pancreatic cancer patients who had surgical resection of cancer (Table 1). The 69 patients were also divided into two groups based on the median value of the sum of 6630 and 6420 Da peak intensity preoperative serum levels. In this 69 patients group, the overall survival time was also longer in LL group patients than in HL group patients (P=0.023, log-rank test; Figure 2b).
We next compared the usefulness of the serum ApoC-1 peak intensity levels as a prognostic marker for pancreatic cancer with serum level of carbohydrate tumor-associated antigen 19-9 (CA19-9), which is most popular serum marker for pancreatic cancer. Again, these 69 patients were divided into two groups based on the median value of preoperative serum CA19-9 levels (median values: 175 U ml−1; HL group, patients with CA19-9 level higher than 175 U ml−1; LL group, patients with CA19-9 level lower than 175 U ml−1). However, there was no statistically significant difference of the overall survival time between these two groups (P=0.090, log-rank test; Figure 2c). We also carried out the receiver-operator-characteristics (ROC) analysis between patients with survival time more and less than 2 years. The respective area under the ROC curve (AUC) was 0.66 for ApoC-1 peak intensity and 0.60 for CA19-9 level (Figure 2d). These results indicated that serum ApoC-1 peak intensity had the better ability as a prognostic marker than serum CA19-9 level.
On univariate analysis, tumor size (⩾30 mm vs <30 mm), the existence of lymph node metastasis, UICC classification stage (IIB, III vs I, IIA), and serum ApoC-1 peak intensity level (HL vs LL) were correlated with overall survival time. Furthermore, among these factors, only serum ApoC-1 peak intensity level was an independent prognostic factor on multivariate analysis (hazard ratio; 2.160, 95% confidence interval; 1.084–4.302, P=0.0285; Table 2).
Abundant expression of ApoC-1 in pancreatic cancer tissues
The decreased serum ApoC-1 level, which was found after curative surgery, suggested that ApoC-1 was overexpressed in cancerous tissue. To confirm this, we analysed the expression of ApoC-1 in pancreatic cancer tissues. Reverse transcription (RT)–PCR revealed that the expression level of ApoC-1 mRNA was much higher in pancreatic cancer tissues than in adjacent normal pancreatic tissue (Figure 3a). Quantitative RT–PCR using samples of resected pancreatic tissue obtained from 16 patients confirmed this finding; a significantly higher ApoC-1 mRNA level was found in pancreatic cancer tissues than in adjacent normal pancreatic tissue (11.49±15.91- and 0.21±0.18-fold ApoC-1/glyceraldehyde-3-phosphate dehydrogenase mRNA copy number, respectively, P<0.0001; Mann–Whitney U-test; Figure 3b).
Western blot analysis also confirmed that ApoC-1 protein was expressed in pancreatic cancer tissues. The cancerous tissues of the four cases that were examined were positive for ApoC-1 protein with a 6.6 Da band; in contrast, a same size band could not be found in adjacent normal pancreatic tissues (Figure 3c).
ApoC-1 is expressed in neoplastic epithelium of pancreatic cancer
To examine the localization of ApoC-1 in pancreatic cancer tissues, we carried out immunohistochemical staining for ApoC-1 in 66 invasive pancreatic ductal carcinoma tissues and in adjacent normal pancreatic tissues. In Figure 4a, hepatocytes from normal liver tissue, which are known to express ApoC-1 (Schaefer et al., 1978; Lauer et al., 1988), are clearly stained with anti-ApoC-1 antibody. As previously reported (Lauer et al., 1988), ApoC-1 expression was negative in pancreatic ductal cells that were located in adjacent normal pancreatic tissue (Figure 4b). On the other hand, ApoC-1 expression was found in carcinoma cells of 48 of 66 invasive pancreatic ductal carcinoma cases (72.7%; Figures 4c–f). The ApoC-1 expression was localized in the neoplastic epithelial cells and was not found in the stromal cells surrounding the ductal carcinoma cells. Moderately differentiated adenocarcinoma (Figures 4c and d) and poorly differentiated adenocarcinoma (Figures 4e and f) were almost equally stained with ApoC-1 antibody.
Furthermore, we analysed the correlation of ApoC-1 expression in carcinoma cells with serum ApoC-1 peak intensity level of SELDI in 66 pancreatic cancer patients. Interestingly, positive staining of ApoC-1 significantly correlated with high serum ApoC-1 peak intensity level (P=0.036; Mann–Whitney U-test).
ApoC-1 is secreted from pancreatic cancer cells
Next, we investigated whether ApoC-1 was also expressed in pancreatic cancer cell lines. In all four pancreatic cancer cell lines (MIA PaCa II, PanC-1, CFPAC-1 and AsPC-1), ApoC-1 expression was confirmed by RT–PCR (Figure 5a) and western blot analysis (Figure 5b). Furthermore, we investigated the possibility that ApoC-1 is secreted from pancreatic cancer cells. Western blot analysis showed that ApoC-1 protein with a 6.6 Da band was present in the medium with cultured MIA PaCa II cells, but not in the medium with no cultured cells (Figure 5c). These results indicated that the MIA PaCa II cells secreted ApoC-1.
Inhibition of ApoC-1 expression by siRNA suppresses cell proliferation of pancreatic cancer cells by inducing apoptotic cell death
The strong correlation of ApoC-1 serum level with poor clinical outcome, accompanied by expression in tumor cells, may indicate the involvement of this protein in cancer progression. For this reason, we next examined whether gene knockdown of this protein would affect the proliferation of pancreatic cancer cells. To specifically silence the ApoC-1 gene, two pancreatic cancer cell lines (MIA PaCa II and AsPC-1) were transfected with short interfering RNA (siRNA) targeting ApoC-1 mRNA (ApoC-1 siRNA1 and -2) or GL2siRNA as a negative control. The suppression of ApoC-1 mRNA level by transfection with 20 nM ApoC-1 siRNA1 and -2 were confirmed in both MIA PaCa II and AsPC-1 (Figure 5d). ApoC-1 protein levels were successfully reduced with ApoC-1 siRNA1 at 5–200 nM concentration 48 h after transfection, as confirmed by western blot analysis (Figure 5e). ApoC-1 siRNA2 also showed similar effects in reducing ApoC-1 protein expression level in MIA PaCa II (Figure 5f; 20 nM concentration of each siRNA).
Pancreatic cancer cells proliferation was comparatively determined by cell counting after the transfection with Mock, GL2siRNA, ApoC-1 siRNA1 and -2. MIA PaCa II and AsPC-1 cells were transfected with 20 nM siRNA, and total cell proliferation was counted 1–4 days after transfection. Cell proliferation was significantly suppressed by transfection with ApoC-1 siRNA1 and -2, compared with cells treated with GL2siRNA in both cell lines (Figure 6a). Interestingly, Trypan blue staining showed that the percentage of dead cells was significantly increased from 2 days after transfection with two ApoC-1 siRNA1 and -2, compared with cells transfected with GL2siRNA (Figure 6b). We also investigated the effect of ApoC-1 silencing on the invasion ability of cancer cells. The cell invasion ability was not affected by gene silencing by transfection of ApoC-1 siRNA1 and -2, compared with cells treated with GL2siRNA in both cell lines (see Supplementary data).
These results indicate that inhibition of ApoC-1 expression may induce apoptotic cell death in pancreatic cancer cells. To examine this, we investigated whether the rate of apoptotic cell death was increased by treatment with ApoC-1 siRNA in these pancreatic cancer cells. ApoC-1 siRNA1 treatment obviously increased the number of apoptotic cells, which were stained purple red, compared with cells treated with control GL2siRNA (Figure 7a). The proportion of apoptotic cells was significantly higher in MIA PaCa II cells treated with ApoC-1 siRNA1 than GL2siRNA at 24 h after transfection (P<0.002; Student's paired t-test; Figure 7b). We also investigated whether the inhibition of ApoC-1 led to activate the procaspase-3 in MIA PaCa II cells. As shown in Figure 7c, the western blot analysis showed that procaspase-3 was more cleaved to activate forms by transfection with both ApoC-1 siRNA1 and -2, compared with GL2siRNA, in MIA PaCa II cells. As well, the caspase-3 activity was significantly higher in MIA PaCa II cells treated with ApoC-1 siRNA1 than GL2siRNA at 24 h after transfection (P<0.02; Student's paired t-test; Figure 7d). These results confirmed that the inhibition of ApoC-1 expression induced apoptosis in pancreatic cancer cells.
To analyse the effects of ApoC-1 gene knockdown in individual cells, immunofluorescence studies were carried out in MIA PaCa II cells treated with GL2siRNA (Figures 7e–g) and ApoC-1 siRNA (Figures 7h–j). Although the abundant expression of ApoC-1 could be found in cells treated with GL2siRNA (Figures 7e–g, red staining), many cells displayed only faint or no fluorostaining with anti-ApoC-1 antibody due to ApoC-1 siRNA treatment. These cells with faint ApoC-1 staining also showed typical apoptotic features, including dense chromatin condensation with 4,6-diamidino-2-phenylindole (DAPI) staining (Figure 7i, arrow; magnified figure is shown in Figure 7l), whereas the GL2siRNA treatment cells that still expressed high amount of ApoC-1 did not show the features (Figure 7f; magnified figure is shown in Figure 7k). These data also revealed that the inhibition of ApoC-1 resulted in apoptotic cell death in pancreatic cancer cells.
To identify molecules related to pancreatic cancer progression, we used a new strategy based on the proteomic approach. We identified serum proteins that were highly expressed in patients with pancreatic cancer using SELDI-TOF MS. The unique strength of SELDI-TOF MS is its ability to analyse proteins from a variety of crude samples with minimal sample consumption; this enables high-throughput analysis (Xiao et al., 2005). In addition, SELDI-TOF MS has an advantage in resolving hydrophobic and low molecular weight proteins, as compared to conventional 2DE analyses. Thus, SELDI-TOF MS has been used extensively in cancer research and has led to the discovery of better serum markers for many cancers. When analysing human samples, it is important to analyse many samples to diminish individual background differences in protein expression. To minimize this, we compared serum samples obtained from the same patient before and after curative surgery. Using this strategy, we successfully identified proteins whose serum expression levels were reduced after curative surgery, based on the analysis of samples from a limited number of patients. Protein purification and amino-acid sequence analysis identified the proteins to be ApoC-1. Surprisingly, the SELDI peak intensity level of ApoC-1 in the preoperative serum was significantly correlated with patients' overall survival. This result was confirmed by a validation study involving 69 serum samples from an independent group of pancreatic cancer patients.
Serum CA19-9 level has been used as marker for the pancreatic cancer (Rhodes, 1999). Recently Ferrone et al. (2006) showed that perioperative CA19-9 levels predicted survival in patients with curative resection of pancreatic cancer. However, in our study, preoperative ApoC-1 peak intensity level of SELDI is better prognostic serum factor than serum CA19-9 levels in both analysis of Kaplan–Meier method and ROC curve. This finding indicates the usefulness of the ApoC-1 serum level as a potentially prognostic marker for pancreatic cancer. In support of this, using serum protein profiling, several groups have recently reported increased serum levels of other apolipoproteins in patients with several types of cancer (Yu et al., 2005; Goncalves et al., 2006). On the other hand, Ehmann et al. (2007) recently found that serum levels of different apolipoproteins (ApoA-1 and -2) were decreased in pancreatic cancer patients compared with healthy volunteers. These facts may indicate that several apolipoproteins have different roles in pancreatic cancer development. Further analysis of the other peaks that were differentially expressed in the pre- and postoperative sera of pancreatic cancer patients will provide new and important information.
This is the first study that has found that ApoC-1 is highly expressed in pancreatic cancer cells but is faintly expressed in normal pancreatic ductal and stromal cells that surround cancerous cells. These findings are supported by studies indicating that ApoC-1 mRNA was highly expressed in pancreatic cancer tissues based on the serial analysis of gene expression analysis (Ryu et al., 2001; Iacobuzio-Donahue et al., 2002). We also found that ApoC-1 was expressed in the supernatant of medium used to culture pancreatic cancer cells. Based on these results, we consider that serum ApoC-1 protein is derived from cancer cells; ApoC-1 is overexpressed in the neoplastic epithelium of pancreatic cancer and is secreted into the blood, which results in elevated serum ApoC-1 levels. This is also supported by the correlation between ApoC-1 expression in cancer cells and high serum peak intensity in preoperative serum.
The correlation of ApoC-1 levels with overall survival in pancreatic cancer, together with its specific expression in cancer cells, may indicate that this protein is involved in cancer progression. This encouraged us to analyse whether ApoC-1 involves in cancer cell proliferation. Using siRNA, we showed that the inhibition of ApoC-1 expression suppressed cell proliferation of pancreatic cancer cell lines. Moreover, we found that this reduced cell proliferation was due to the increased rate of apoptotic cell death. These facts suggest that expression of ApoC-1 (secreted by autocrine manner) is essential for cancer cell survival by preventing from apoptosis, contributing to the malignant phenotype of pancreatic cancer. Supporting this, silencing expression of the apolipoprotein J gene, another apolipoprotein, in osteosarcoma and prostate cancer cells induced a significant reduction of cellular growth and high rates of spontaneous endogenous apoptosis (Trougakos et al., 2004). Chen et al. (2005) also showed that the inhibition of apolipoprotein E, which is genetically linked closely with ApoC-1 (Lauer et al., 1988), in ovarian cancer cells led to G2 cell-cycle arrest and apoptosis. In addition, RELN pathway through signaling via the VLDL receptor, to which ApoC-1 is known to bind, influences cell motility in pancreatic cancer (Sato et al., 2006). It is very tempting to speculate that the inhibition of ApoC-1 expression in pancreatic cancer suppresses the tumor progression in vivo, and siRNA oligonucleotides against ApoC-1 may prove valuable agents for antipancreatic cancer therapy.
In conclusion, we found that serum levels of ApoC-1, which appears to be secreted by cancer cells, can predict the prognosis of pancreatic cancer patients. We also found an unexpected role of ApoC-1 in regulating cancer cell proliferation by avoiding spontaneous apoptotic cell death. Further research to determine the molecular mechanisms whether ApoC-1 inhibits apoptosis in cancer cells is warranted and will likely lead to the discovery of new therapies for pancreatic cancer using ApoC-1 as a therapeutic target.
Materials and methods
Patient samples and cell lines
To identify novel serum markers, serum samples were collected pre- and postoperatively (3–4 weeks after surgery, when the serum levels of C-reactive protein returned to the normal range) from 20 pancreatic cancer patients who had curative surgery. For the validation study, blood samples were obtained preoperatively from 69 patients diagnosed with primary invasive pancreatic ductal carcinoma who had surgery in the Department of General Surgery, Chiba University Hospital, Chiba, Japan, from June 2001 to April 2006. All blood samples were processed according to a standardized protocol, and serum samples were immediately frozen in aliquots at −80 °C until the proteomic study was done. In all patients, the diagnoses of carcinoma were confirmed histologically. Patient characteristics are summarized in Table 1 (Sobin and Wittekind, 2002). None of the patients received any additional therapies, such as radiation or chemotherapy, pre- or postoperatively, until serum samples were collected. The excised pancreatic tissue samples were placed in liquid nitrogen and stored at −80 °C until use. The ethics committee of our institute approved the protocol. Written informed consent was obtained from all patients. The four human pancreatic cancer cell lines, MIA PaCa II and PanC-1 (American Type Culture Collection, Manassas, VA, USA), CFPAC-1 and AsPC-1 (DS Pharma Biomedical Co., Ltd., Japan) that were used in this study were cultured in the appropriate medium and incubated in a humidified atmosphere containing 5% CO2 at 37 °C.
SELDI-TOF MS analysis
To discover the candidate protein, an aliquot of the stored 20-paired pre- and postoperative serum samples was used for SELDI-TOF MS analysis with a weak cationic exchanger 2 (WCX2; Ciphergen Biosystems, Fremont, CA, USA; see Supplementary methods for detail). Each analysis was carried out in duplicate. Peak detection was carried out using ProteinChip Software 3.1 (Ciphergen).
For the validation study, the peak intensity of 6630 and 6420 Da proteins was measured using the SELDI-TOF MS analysis on CM10 ProteinChip arrays (Ciphergen) in 69 preoperative sera of pancreatic cancer patients; the measurements were done in duplicate under the same urea buffer condition as the WCX2 experiment. To reduce the coefficient of variation for peak intensities, we used a robot, Biomek 3000 Laboratory Automation Workstation (Beckman Coulter Inc., Fullerton, CA, USA) in this validation study. Mass accuracy was calibrated externally with an all-in-one-peptide molecular mass standard (Ciphergen).
Isolation and identification of the target proteins
The candidate proteins were purified, isolated and identified (see Supplementary methods for detail). After purification, the target protein was identified by N-terminal amino-acid sequence analysis. The immunodepletion assay and western blot were carried out for the confirmation of the identified protein.
RT–PCR and quantitative RT–PCR
Total RNA was extracted with the RNeasy Mini Kit (Qiagen Tokyo, Japan) according to the manufacturer's instructions. cDNA was synthesized from 1 μg of total RNA with the T-Primed First-Strand Kit for RT–PCR (Amersham Biosciences, Buckinghamshire, UK). Human brain (cerebellum) total RNA (BD Bioscience Clontech, Takaka Bio company, Shiga, Japan) was used as positive control of ApoC-1 (Lauer et al., 1988). Quantitative RT–PCR was carried out as previously described (Mitsuhashi et al., 2003) using LightCycler with LightCycler-Fast Start DNA Master SYBR Green I kit (Roche Diagnostics, Mannheim, Germany; see Supplementary Methods for detail).
Western blot analysis
The extracted proteins from frozen tissue samples, the cultured cells and the supernatant of the cultured cells were subjected to western blot analysis using mouse anti-human ApoC-1 monoclonal antibody (CHEMICON International, Temecula, CA, USA) and rabbit anti-human procaspase-3 polyclonal antibody (Santa Cruz Biotechnology, Santa Cruz, CA, USA; see Supplementary Methods for detail).
Paraffin-embedded tissues were cut in 4-μm-thick serial sections and were deparaffinized. These slides were placed in citric acid buffer (10 mmol l−1, pH 6.0) with 0.2% Tween 20 and boiled in a microwave oven (2 × 6 min) to retrieve the antigen. The slides were then rinsed and blocked in 10% H2O2 solution with methanol for 10 min. Next, they were incubated with mouse anti-human ApoC-1 monoclonal antibody (CHEMICON International) at 1:200 dilution overnight at 4 °C. They were then rinsed in phosphate-buffered saline (PBS), and incubated for 60 min with secondary antibody labeled with streptoavidin-biotin-peroxidase (DAKO LSAB2 kit, DakoCytomation, Glostrup, Denmark). The bound complex was visualized using diaminobenzidine liquid chromogen and counterstained with hematoxylin. Mouse-monoclonal IgG2a (X0943, DAKO) was used as a negative control at an optimal dilution.
Gene knockdown using siRNA
Short interfering RNA (Hannon and Rossi, 2004) that specifically targeted ApoC-1 mRNA was used to reduce ApoC-1 expression. The target sequences for ApoC-1 RNA interference were as follows; ApoC-1 siRNA1: 5′-IndexTermCTGGAGGACAAGGCTCGGGAA-3′, ApoC-1 siRNA2: 5′-IndexTermCTGAAGGAGTTTGGAAACACA-3′. Double-stranded synthetic siRNA1 and 2, and luciferase (GL2) siRNA as a negative control, were purchased from Qiagen. In vitro transfection was carried out using Lipofectamine 2000 reagent (Invitrogen Life Technologies, Carlsbad, CA, USA) according to the manufacturer's instructions (see Supplementary Methods for detail).
Cell proliferation assay and Trypan blue exclusion test
A total of 20 × 104 MIA PaCa II and AsPC-1 human pancreatic cancer cell lines in six-well plates, were cultured in Dulbecco's modified Eagle medium (DMEM; Sigma Chemical Co., St Louis, MO, USA) supplemented with 10% heat-inactivate fetal bovine serum (FBS), and were cultured in RPMI 1640 (Gibco BRL, Grand Island, NY, USA) with 20% FBS, respectively, incubated in a humidified atmosphere containing 5% CO2 at 37 °C for 24 h. After washing with PBS, these cells were transfected with siRNA (20 nM final concentration). Both attached and floating cells were corrected with trypsinization. After staining with Trypan blue, the total cell number and the number of Trypan blue positive cells were counted on days 1–4 after transfection. All of these experiments were carried out in triplicate for three times, independently. The medium was changed every 2 days.
A total of 1 × 105 MIA PaCa II or AsPC-1 cells in Opti-MEM I Reduced Serum Medium were plated onto BD BioCoat Matrigel Invasion Chamber (8 μm pore size; BD Biosciences) and incubated in a humidified atmosphere containing 5% CO2 at 37 °C for 4 h. After transfected with each siRNA (20 nM final concentration; see Supplementary Methods for detail), cells were incubated for 32 h in appropriated medium (DMEM or RPMI 1640 with FBS), noninvading cells on the upper chamber were scraped with a cotton swab. The relative number of invading cells that penetrated the Matrigel-coated membrane were quantified by colorimetric cell proliferation assay using the Cell Counting Kit-8 (DOJINDO, Kumamoto, Japan) according to the manufacturer's instructions (Chen et al., 2006; Shida et al., 2006). All of these experiments were carried out in quadruplicate for three times, independently.
A total of 2 × 104 MIA PaCa II and AsPC-1 cells were plated in 96-well plates, incubated for 24 h and transfected with siRNA (20 nM final concentration). After 24 h, apoptotic cells were stained using the APOPercentage Kit (Biocolor Ltd, Newtownabbey, Northern Ireland, UK) according to the manufacturer's instructions (Fadok et al., 1992; Mutaguchi et al., 2003). Purple-red stained cells were identified as apoptotic cells, and counted manually in each four different random positions in blinded fashion. All experiments were carried out for three times.
The caspase-3 activity assay was carried out according to the manufacturer's protocol (BD ApoAlert Caspase-3 Colorimetric Assay Kit, BD Biosciences Clontech, Mountain View, CA, USA). In brief, a total of 2 × 106 MIA PaCa II cells were plated in six-well plate, transfected with siRNA (20 nM final concentration) and harvested at 24 h after transfection. After counting cell number, cells were centrifuged and resuspended in 50 μl of chilled Cell Lysis Buffer following incubation for 10 min on ice. Cell lysates were mixed with equal amount of with Reaction Buffer/DTT Mix containing 50 μM DEVD-pNA (p-nitroaniline) substrate and incubated at 37 °C for 2 h. Enzyme-catalysed release of pNA was monitored using a Bio-Rad Microplate Reader at 405 nm wavelength. These experiments were carried out for three times.
The cultured cells transfected with siRNA were fixed on slide glasses with acetone for 10 min at 4 °C. After three washes with PBS, the nonspecific binding of antibodies was blocked with blocking buffer (10% FBS/PBS) for 1 h. Samples were incubated for 1 h with mouse anti-human ApoC-1 monoclonal antibody (CHEMICON International) diluted 1:500. After a wash with PBS, samples were incubated with 1:3000 diluted Alexa Fluor 568-conjugated goat anti-mouse IgG secondary antibody (Molecular Probes, Eugene, OR, USA) for 1 h. DNA was counterstained with DAPI III Counterstain (Vysis, Abbott Park, IL, USA). Samples were observed with a fluorescence microscope (Leica QFISH; Leica Microsystems, Tokyo, Japan).
Statistical analyses were carried out using the appropriate tests as indicated. P-values <0.05 were considered statistically significant.
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This study was supported by the Ministry of Education, Culture, Science, Sports and Technology of Japan and Japanese Society of Laboratory Medicine Fund for Promotion of Scientific Research (2006–2007). We thank Mamoru Satoh, PhD and Masumi Ishibashi for technical support and Kosuke Suda, MD, PhD and Kazuki Kobayashi, MD, PhD for special advice.
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Takano, S., Yoshitomi, H., Togawa, A. et al. Apolipoprotein C-1 maintains cell survival by preventing from apoptosis in pancreatic cancer cells. Oncogene 27, 2810–2822 (2008). https://doi.org/10.1038/sj.onc.1210951
- apolipoprotein C-1
- pancreatic cancer
- SELDI-TOF MS
- serum marker
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