IPO-38 Is Identified as a Novel Serum Biomarker of Gastric Cancer Based on Clinical Proteomics Technology

Department of Surgery of Ruijin Hospital, Shanghai Institute of Digestive Surgery, Shanghai Jiaotong University, 197 Ruijin second Road, Shanghai, 200025, P.R. China.
Journal of Proteome Research (Impact Factor: 4.25). 10/2008; 7(9):3668-77. DOI: 10.1021/pr700638k
Source: PubMed


Gastric cancer is one of the most common malignancies in China. So far, there are few reliable serum biomarkers for diagnosis. The available biomarkers of CEA, CA19-9 and CA72-4 are not sufficiently sensitive and specific for gastric cancer. In this study, a high density antibody microarray was used for identifying new biomarkers from serum samples of gastric cancer. Serum samples from colorectal cancer, pancreatic cancer, hepatocellular cancer, and breast cancer were also screened for comparative study. As result, some candidate biomarkers were identified. IPO-38, an up-regulated serum protein in gastric cancer was selected for subsequent validation including serum IPO-38 expression by ELISA and IPO-38 protein expression by immunohistochemistry. The immunoprecipitation by IPO-38 for gastric cancer cell line and MALDI-TOF/TOF mass spectrometer suggested that pull-down of IPO-38 belongs to H2B histone, which was supported by co-localization study of laser scanning confocal microscope. A follow-up study showed that the survival rate of IPO-38 negative group was better than that in IPO-38 positive group. The study first clarified the property of IPO-38 proliferating marker, and proposed that IPO-38 protein is a promising biomarker both for diagnosis and for predicting prognosis of gastric cancer.

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    • "But there has no effective method to predict metastasis of GC on the current, elucidate the molecular mechanism of invasion and metastasis is crucial for the prognosis of GC [7]. Thereby, numbers of studies on GC metastasis prediction have been carried out and some biomarkers have been used for screening GC [8] [9] [10] [11]. "
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    ABSTRACT: Phosphatase of regenerating liver-3 (PRL-3) is believed to be associated with cell motility, invasion, and metastasis. Our previous work found that PRL-3 is highly overexpressed in gastric cancer (GC) tissue with peritoneal metastasis and directly involved in the pathogenesis of GC peritoneal metastasis. Moreover, we further found that the down-regulation of endogenous miR-495 expression plays a causative role in over expression of PRL-3 in GC peritoneal metastasis. However, the molecular regulation mechanisms by which endogenous miR-495 expression is down-regulated and PRL-3 promotes GC peritoneal metastasis remain to be clearly elucidated. Some studies have shown that the promoter methylation is closely related to the miRNA gene expression. Therefore, in present study, based on our previous findings, we will analysis whether DNA methylation is a major cause of the down-expression of endogenous miR-495, which results in PRL-3 overexpression in GC peritoneal metastasis. Methylation specific PCR (MSP) and sodium bisulfite sequencing method (BSP) detected miR-495 gene promoter methylation status. We treated GC cell lines with 5-Aza-2'-deoxycytidine (5-Aza-dC) to make the gene promoter methylation inactivation. By treating with 5-Aza-dC the migration and invasion of GC cells were significantly inhibited. And the miR-495 was overexpressing, corresponds to the mRNA and protein levels of PRL-3 were reduced, the ability of invasion and metastasis was inhibited. This study suggest that miR-495 have tumor suppressor properties and are partially silenced by DNA hypermethylation in GC, will provide new strategies for prevention and treatment of GC peritoneal metastasis. Copyright © 2014. Published by Elsevier Inc.
    Biochemical and Biophysical Research Communications 12/2014; 456(1). DOI:10.1016/j.bbrc.2014.11.083 · 2.30 Impact Factor
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    • "2-D DIGE coupled with MALDI-TOF/ TOF MS Epidermal fatty acid-binding protein 5, methylcrotonoyl- CoA carboxylase 2, palmitated protein A2, ezrin, stomatin-like protein 2 and smooth muscle 22 [21] 2. Colorectal cancer 2-D DIGE S100A8 and S100A9 (Calgranulin A and B) [22] 2-D DIGE Transaldolase 1 and thyroid receptor interactor [23] LC-MS/MS Growth/differentiation factor 15, trefoil factor 3 [24] 3. Liver cancer Capillary-HPLC analysis, stable isotope dilution-multiple reaction monitoring-MS Clusterin and vitronectin [31] 2-DE coupled with MALDI-TOF/TOF Vimentin [32] 2-DE coupled with MALDI-TOF/TOF Heat shock protein 90 [33] 4. Pancreatic cancer 2-DE-MS Cyclin I, Rab GDP dissociation inhibitor b [34] Protein microarray Phosphoglycerate kinase-1, histone H4 [35] 5. Brain tumor SELDI-TOF-MS, protein chips Gliomas amplified sequence 64 and brain my035 protein [25] SELDI-TOF-MS a2-Heremans-Schmid glycoprotein [26] 6. Breast cancer Nucleic acid programmable protein microarray (NAPPA) p53-specific antibodies [27] MALDI-TOF-MS CEA, CA15-3, cytokeratin fragment 21.1, Leptin, Osteopontin [28] Antibody microarray Epidermal growth factor, soluble CD40 ligand and proapolipoprotein A1, kininogen, soluble vascular cell adhesion molecule1, plasminogen activator inhibitor-1, vitamin D-binding protein and vitronectin [30] 7. Ovarian cancer Protein arrays Upstream stimulatory factor, cathepsin G, HLA- B-associated transcript 4 and zinc finger and BTB domain-containing protein 22 [36] ESI MS/MS, reverse phase protein microarray S100A6 (Calcyclin) [39] 2-DE, MS/MS, reverse phase protein arrays FK506 binding protein, Rho G-protein dissociation inhibitor and glyoxalase I [130] MALDI orthogonal TOF MS Complement component 3 and inter-a (globulin) inhibitor H4, and single peptides from complement component 4A, transthyretin, and fibrinogen [181] 8. Lung cancer 2-DE coupled with MALDI-TOF/TOF Haptoglobin, transthyretin, and TNF superfamily member 8 [38] 9.Gastric Cancer SELDI-TOF-MS, antibody microarray IPO-38 (H2B histone) [182] "
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    ABSTRACT: Serum is an ideal biological sample that contains an archive of information due to the presence of a variety of proteins released by diseased tissue, and serum proteomics has gained considerable interest for the disease biomarker discovery. Easy accessibility and rapid protein changes in response to disease pathogenesis makes serum an attractive sample for clinical research. Despite these advantages, the analysis of serum proteome is very challenging due to the wide dynamic range of proteins, difficulty in finding low-abundance target analytes due to the presence of high-abundance serum proteins, high levels of salts and other interfering compounds, variations among individuals and paucity of reproducibility. Sample preparation introduces pre-analytical variations and poses major challenges to analyze the serum proteome. The label-free detection techniques such as surface plasmon resonance, microcantilever, few nanotechniques and different resonators are rapidly emerging for the analysis of serum proteome and they have exhibited potential to overcome few limitations of the conventional techniques. In this article, we will discuss the current status of serum proteome analysis for the biomarker discovery and address key technological advancements, with a focus on challenges and amenable solutions.
    Proteomics 06/2011; 11(11):2139-61. DOI:10.1002/pmic.201000460 · 3.81 Impact Factor
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    • "Identification of patients with potential poor-prognosis would help us to optimize the clinical treatment for GC patients. Histological grade, anatomically based TNM staging system, serum biomarkers, genes and other factors have been used to predict prognosis so far [5,15,30,31]. Currently, TNM staging system remains the most widely used prognostic model, while newly emerging biomarkers such as CEA, CA72-4 or its combination may provide additional prognostic information. "
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    ABSTRACT: Although gastric cancer (GC) remains the second cause of cancer-related death, useful biomarkers for prognosis are still unavailable. We present here the attempt of mining novel biomarkers for GC prognosis by using serum proteomics. Sera from 43 GC patients and 41 controls with gastritis as Group 1 and 11 GC patients as Group 2 was successively detected by Surface Enhanced Laser Desorption/ionization Time of Flight Mass Spectrometry (SELDI-TOF-MS) with Q10 chip. Peaks were acquired by Ciphergen ProteinChip Software 3.2.0 and analyzed by Zhejiang University-ProteinChip Data Analysis System (ZJU-PDAS). CEA level were evaluated by chemiluminescence immunoassay. After median follow-up periods of 33 months, Group 1 with 4 GC patients lost was divided into 20 good-prognosis GC patients (overall survival more than 24 months) and 19 poor-prognosis GC patients (no more than 24 months). The established prognosis pattern consisted of 5 novel prognosis biomarkers with 84.2% sensitivity and 85.0% specificity, which were significantly higher than those of carcinoembryonic antigen (CEA) and TNM stage. We also tested prognosis pattern blindly in Group 2 with 66.7% sensitivity and 80.0% specificity. Moreover, we found that 4474-Da peak elevated significantly in GC and was associated with advanced stage (III+IV) and short survival (p < 0.03). We have identified a number of novel biomarkers for prognosis prediction of GC by using SELDI-TOF-MS combined with sophisticated bioinformatics. Particularly, elevated expression of 4474-Da peak showed very promising to be developed into a novel biomarker associated with biologically aggressive features of GC.
    Journal of Experimental & Clinical Cancer Research 09/2009; 28(1):126. DOI:10.1186/1756-9966-28-126 · 4.43 Impact Factor
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