Ovarian cancer causes more deaths than any other malignant tumor of the female reproductive system. This is because the condition usually goes undetected until the late stages. The purpose of the present study is to identify alterations in the serum proteome profile during the development of ovarian cancer and to provide an experimental basis for discovering new and valuable serum biomarkers for the early detection of ovarian carcinoma. Surface-enhanced laser desorption/ionization-time of flight (SELDI-TOF-MS) was used to profile changes in the serum proteome of Fischer 344 rats with ovarian cancer during the progress of tumor development. Sera were collected from the rats on day A (1 week before injection of tumor cells), day B (4 weeks after injection), and day C (6 weeks after injection). Each sample was subjected to SELDI-TOF-MS testing. Peak detection and alignment and selection of peaks with the highest discriminatory power were performed using ProteinChip biomarker software. Decision tree analyses were performed using biomarker pattern software. Finally, 3 peaks were found to be the most valuable ones (3759, 4659 and 9318 Da). The expression frequency of m/z 3759-Da peaks was downregulated and another two frequencies (4659 and 9318 Da) were upregulated, and the levels of expression of these three proteins showed the same tendency as the expression frequency during the development of ovarian cancer. The total accuracy rate of diagnosis at 4 and 6 weeks post-injection was 94.7 and 97.3%, respectively. Profiling the serum proteome changes during the process of the cancer development using SELDI-TOF-MS may provide useful information regarding carcinogenesis and facilitate discovery of novel serum biomarkers for early detection.
Ovarian cancer is the second most common gynecologic cancer and causes more deaths than any other malignant tumor of the female reproductive system (
Cancer cells secrete different kinds of proteins that can enter the blood circulation. Consequently, the serum proteome may reflect the abnormality or pathologic state of the disease (
SELDI-TOF-MS was used to profile changes in the serum proteome changes of Fischer 344 rats with ovarian cancer during tumor development. The differential expression of proteinogram before and after tumor generation in rats offered useful information regarding proteins and genes that may be a key to carcinogenesis. It may also facilitate identification of novel serum biomarkers suitable for detection of ovarian cancer (
The Fischer 344-rat-derived epithelial ovarian carcinoma cell line NuTu-19 was a kind gift provided by Dr Airong Zhang of the Second Hospital of Shandong University. The NuTu-19 cells were maintained in complete media consisting of Dulbecco’s modified Eagle’s medium (DMEM; Gibco-Life Technologies) with 10% heat-inactivated fetal bovine serum (Gibco-Life Technologies) at 37°C, 5% CO2 and 100% humidity.
Female pathogen-free Fischer 344 rats (100–125 g) were obtained from Weitong Lihua, Inc., Beijing, China, and housed in a pathogen-free animal facility. Rats were kept in an environment with a 12-h light 12-h dark cycle and free access to food and water in the animal facility of the Shandong University Medical School. The present study was carried out in strict accordance with the guidelines for the Animal Care and Use of the Shandong University, China. The protocol was approved by the Committee on the Ethics of Animal Experiments in Qilu Hospital of Shandong University, and an informed consent form was provided by them. Surgery was performed under sodium pentobarbital anesthesia, and all efforts were made to minimize suffering.
NuTu-19 cells were harvested with 0.25% trypsin and 0.01% ethylenediaminetetraacetic acid (EDTA) and washed twice with phosphate-buffered saline (PBS) solution. Then a total of 106 cells were injected intraperitoneally into each rat. The animals were observed daily and weighed weekly. All animals grew in parallel and the body weight of each rat was kept uniform throughout the experiment.
Peripheral blood (0.5 ml) was collected from the axillary vein of rats on day A (1 week before tumor cell injection), day B (4 weeks after injection), and day C (6 weeks following injection). Each blood sample was allowed to clot and was centrifuged at 3,000 rpm for 20 min soon after collection to remove all cellular components. Then, serum samples were aliquoted into 10-μl sections and kept at −80°C until use. The serum samples were centrifuged at 10,000 rpm for 20 min at 4°C and then diluted 1:3 into 20 μl U9 buffer solution (9 mol/l urea, 2% CHAPS, 50 mmol/l Tris-HCl, pH 9.0, 1% DTT) before testing. After incubation on ice for 30 min, the samples were diluted again 1:13 into 360 μl of sodium acetate buffer solution (50 mmol/l NaAc, pH 4.0). Then the samples were ready for SELDI testing.
Four different types of chip (Ciphergen Biosystems, Inc., Fremont, CA, USA) with surface chemistry of hydrophobic (H50), ionic (CM10), cationic (WCX2), and metal binding (IMAC3) were tested to determine which produced the best serum profiles. The CM10 ProteinChip, which is a weak cationic exchanger, was selected for the present study (
Chips loaded with samples were placed on the Protein Biological System II mass spectrometer reader (Ciphergen Biosystems). Time-of-flight spectra were generated by averaging 60 laser shots and collected in the positive mode at laser intensity 185 and detector sensitivity 8 with molecular weight optimized from 2,000 to 10,000 Da (
The reproducibility of SELDI spectra from array to array on a single chip (intra-assay) and between chips (inter-assay) was determined using the pooled normal serum quality control (QC) sample (
Data analysis involved peak detection, alignment and selection of peaks with the highest discriminatory power. All spectra were collected using ProteinChip Biomarker software version 3.2 (Ciphergen Biosystems). Spectra range from 2,000 to 20,000 m/z was selected for analysis. The study focused on this region to eliminate low-mass (m/z <1,000) and low-intensity peaks (m/z >20,000). Peak detection involved baseline subtraction, mass accuracy calibration and automatic peak detection (
Decision tree analyses were performed using Biomarker Patterns Software (BPS; Bio-Rad Laboratories). For each sample, the intensity values for each protein peak were entered in BPS and classified according to the tree analysis described. The BPS program can combine multiple biomarkers to distinguish between independent groups, thereby increasing sensitivity and specificity compared with single biomarker predictors. BPS was also used to perform a 10-fold cross-validation because the size of the data set was too small for an independent validation set. This process allows the sensitivity and specificity to be predicted for future data and provides an accurate estimate of the predictive accuracy of the selected decision tree (
NuTu-19 cells grew progressively in the abdominal cavity in a manner typical of human ovarian epithelial carcinomas. At the fourth week after injection of 106 cells, the rats showed no obvious features of cancer. However, during the sixth week, all animals developed cancer in the peritoneal cavity, represented by numerous serosal nodules (peritoneum, omentum, diaphragm and bowel), omentum contraction and malignant bloody ascites. Characteristics of cachexia such as pallor (anemia), marasmus and abundance of bloody ascites appeared gradually. At the end of the study, all animals were sacrificed and tumor tissues were removed for section and H&E staining. Pathohistological results confirmed the existence of adenocarcinoma tissue (
Accurate and reproducible feature selection is essential for SELDI application. The reproducibility of the current SELDI spectra was confirmed successfully, using a QC sample. The intra and inter-assay coefficients of variance for peak location were both 0.05%, and the intra- and inter-assay coefficients of variance for normalized intensity were 12 and 18%, respectively. Little variation was shown across day-to-day sampling and differences in instrumentation and chips (
SELDI spectra of rat serum samples showed a total of 126 raw peaks in the m/z region of 1,000–20,000 Da. Using biomarker pattern software, the spectrum generated from pre-injection rats (1 week before injection) was compared to the spectrum generated from post-injection rats (4 and 6 weeks after injection, respectively). This comparison yielded a model consisting of 10 peaks that discriminated between pre-injection and post-injection rats during the development of ovarian cancer (P<0.05) (
The expression frequency of m/z 3759 peaks was downregulated and that of the other two peaks (4659 and 9318) was upregulated during the development of ovarian cancer. The protein with molecular weight 3759 Da was expressed in 86.8% of the rats before injection of ovarian cancer cells. However, 4 weeks after injection, the frequency dropped to only 35.2%. At 6 weeks after injection, it had dropped to 8.4%. None of the proteins of 4659 Da were detected before injection but levels increased to 2.7 and 39.0% at 4 and 6 weeks, respectively. Similarly, the expression rates of the 9318-Da protein were 31.6% before injection and 67.6 and 75.0% at 4 and 6 weeks (
The expression levels of the 3759-, 4659- and 9318-Da proteins, here indicated by the peak intensity of each protein, showed the same tendency as the expression frequency before and after injection. The peak intensity of the 3759-Da protein dropped from 19.19±5.2 before injection to 11.14±4.62 (P=0.0177) and 7.01±3.65 (P=0.0008) at 4 and 6 weeks after. The peak intensity of the 4659-Da protein was 7.73±4.52 before injection and increased gradually after tumor injection to 8.78±4.21 (P>0.05) at 4 weeks and 21.37±6.19 (P=0.0014) at 6 weeks. Similarly, the peak intensity of protein 9318 Da before injection was 1.5±1.03, which was rather low, and subsequently increased to 3.01±4.07 (P>0.05) at 4 weeks and 7.67±4.99 (P=0.0141) at 6 weeks after tumor injection (
The decision classification tree was used as a predictive tool to distinguish the pre-injection rats from post-injection groups (
For most types of cancers, survival rates depend on early diagnosis of the disease. For example, the 5-year survival rate of patients diagnosed at an advanced stage is ~35%, compared with 90% for cancers at stage I (
Mass spectrometry based on proteomics has been widely used in many related studies to identify and map proteins in bodily fluids, and proteomics profiling is one commonly used approach in proteomics (
The present study evaluated the alterations in the proteomic profiling of the serum of tumor-bearing rats using SELDITOF-MS. These protein markers may be novel oncogenes or tumor suppressing proteins and may provide useful information on tumor cell growth and metastasis, genes related to the tumor cell microenvironment and specific molecular targets (
This study was funded by research grants from the National Natural Science Foundation of China (nos. 81100403) and Foundation for Outstanding Young Scientist in Shandong Province of China (BS2013YY035).
Tumor model. (A–C) At the 6th week after NuTu-19 cell injection, animals developed cancer in the peritoneal cavity, here represented by numerous serosal nodules (peritoneum, omentum, diaphragm and bowel), omentum contraction and malignant bloody ascites. (D) Pathohistological results: adenocarcinoma tissue with H&E staining.
SELDI spectra of rat serum. Using biomarker pattern software, the spectrum generated from (A) rats 1 week before injection, (B) rats 4 weeks after injection and (C) rats 6 weeks after injection. These comparisons and comprehensive selection showed 3 peaks to be the most valuable. All had peak intensity above 5. These 3 peaks corresponded to m/z ratios of 3759, 4659 and 9318.
(A) Expression frequency/rate of key protein detection (3759, 4659 and 9318 Da). The 3759-Da protein was expressed in 86.8% of the rats before ovarian cancer cell injection, and the expression frequency dropped to only 35.2% at 4 weeks after injection and to 8.4% at 6 weeks. No 4659-Da proteins were detected before injection but it was found in 2.7 and 39.0% of rats at 4 and 6 weeks after injection, respectively. The expression rate of the 9318-Da protein was 31.6% before injection and 67.6 and 75.0% at 4 and 6 weeks after injection, respectively. (B) Peak intensity of key proteins (3759, 4659 and 9318 Da). The peak intensity of 3759-Da protein dropped from 19.19±5.2 before injection to 11.14±4.62 (*P<0.05) and 7.01±3.65 (**P<0.001) at 4 and 6 weeks after injection. The peak intensity of 4659-Da protein was 7.73±4.52 before injection and it increased gradually after injection to 8.78±4.21 (P>0.05) at 4 weeks and 21.37±6.19 (*P<0.05) at 6 weeks. The peak intensity of the 9318-Da protein before injection was 1.5±1.03, and it increased to 3.01±4.07 (P>0.05) at 4 weeks and 7.67±4.99 (*P<0.05) at 6 weeks after tumor cells injection. N=6 for all experiments. Data are expressed as mean ± SD. P vs. 1 week pre-injection.
Diagnostic decision tree. Diagnostic decision tree used 6 splitters with distinct masses of 4427.86, 9309.30, 5883.54, 4390.31, 5645.01 and 8219.00 Da, respectively, and cases were classified into 7 terminal nodes.
Diagnostic accuracy of tumor-bearing rats using diagnostic decision tree.
Diagnosis accuracy rate (%) | ||||
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N | Pre-injection | 4 weeks post-injection | 6 weeks post-injection | |
Pre-injection | 38 | 86.84 | 5.26 | 7.89 |
4 weeks post-injection | 38 | 5.26 | 76.30 | 18.42 |
6 weeks post-injection | 37 | 2.70 | 16.22 | 81.08 |