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Nishi-Tokyo-shi, Japan

Takada M.,Showa University | Ban Y.,Showa University | Yamamoto G.,Showa University | Ueda T.,Showa University | And 10 more authors.
Biochemical and Biophysical Research Communications

Diabetes can lead to serious microvascular complications including proliferative diabetic retinopathy (PDR), the leading cause of blindness in adults. Recent studies using gene array technology have attempted to apply a hypothesis-generating approach to elucidate the pathogenesis of PDR, but these studies rely on mRNA differences, which may or may not be related to significant biological processes. To better understand the basic mechanisms of PDR and to identify potential new biomarkers, we performed shotgun liquid chromatography (LC)/tandem mass spectrometry (MS/MS) analysis on pooled protein extracts from neovascular membranes obtained from PDR specimens and compared the results with those from non-vascular epiretinal membrane (ERM) specimens. We detected 226 distinct proteins in neovascular membranes and 154 in ERM. Among these proteins, 102 were specific to neovascular membranes and 30 were specific to ERM. We identified a candidate marker, periostin, as well as several known PDR markers such as pigment epithelium-derived factor (PEDF). We then performed RT-PCR using these markers. The expression of periostin was significantly up-regulated in proliferative membrane specimens. Periostin induces cell attachment and spreading and plays a role in cell adhesion. Proteomic analysis by LC/MS/MS, which permits accurate quantitative comparison, was useful in identifying new candidates such as periostin potentially involved in the pathogenesis of PDR. © 2010 Elsevier Inc. Source

Imanishi T.,Japan National Institute of Advanced Industrial Science and Technology | Imanishi T.,Tokai University | Nagai Y.,Japan National Institute of Advanced Industrial Science and Technology | Habara T.,Japan National Institute of Advanced Industrial Science and Technology | And 7 more authors.
Journal of Proteome Research

H-Invitational Database (H-InvDB; http://hinv.jp/) is an integrated database of all human genes and transcripts that started in an international collaborative research project for establishing a functional annotation database of human full-length cDNAs. Because H-InvDB contains an abundance of information for human transcripts, including not only well-characterized proteincoding transcripts but also those without experimental evidence at the protein level, this will be a useful information resource for identifying novel and uncharacterized human proteins (so-called missing proteins). By extending predicted protein data in H-InvDB, we developed the H-Inv Extended Protein Database (H-EPD; http://hinv.jp/hinv/h-epd/). From now on, we plan to carry out a database-driven proteome research that makes full use of H-EPD to promote discoveries in the current and future C-HPP. Furthermore, we will push forward with the integration of genome, transcriptome, and proteome databases using a unique tool for connecting distributed databases and would like to develop a knowledge discovery system by incorporating data mining tools. © 2012 American Chemical Society. Source

Takadate T.,Tohoku University | Onogawa T.,Tohoku University | Fujii K.,Hokkaido University | Motoi F.,Tohoku University | And 15 more authors.
Clinical Proteomics

Background: Pancreatic cancer is among the most lethal malignancies worldwide. This study aimed to identify a novel prognostic biomarker, facilitating treatment selection, using mass spectrometry (MS)-based proteomic analysis with formalin-fixed paraffin-embedded (FFPE) tissue. Results: The two groups with poor prognosis (n = 4) and with better prognosis (n = 4) had been carefully chosen among 96 resected cases of pancreatic cancer during 1998 to 2007 in Tohoku University Hospital. Although those 2 groups had adjusted background (UICC-Stage IIB, Grade2, R0, gemcitabine adjuvant), there was a significant difference in postoperative mean survival time (poor 21.0 months, better 58.1 months, P = 0.0067). Cancerous epithelial cells collected from FFPE tissue sections by laser micro-dissection (LMD) were processed for liquid chromatography-tandem mass spectrometry (LC-MS/MS). In total, 1099 unique proteins were identified and 6 proteins showed different expressions in the 2 groups by semi-quantitative comparison. Among these 6 proteins, we focused on Nm23/Nucleoside Diphosphate Kinase A (NDPK-A) and immunohistochemically confirmed its expression in the cohort of 96 cases. Kaplan-Meier analysis showed high Nm23/NDPK-A expression to correlate with significantly worse overall survival (ρ = 0.0103). Moreover, in the multivariate Cox regression model, Nm23/NDPK-A over-expression remained an independent predictor of poor survival with a hazard ratio of 1.97 (95% CI 1.16-3.56, ρ = 0.0110). Conclusions: We identified 6 candidate prognostic markers for postoperative pancreatic cancer using FFPE tissues and immunohistochemically demonstrated high Nm23/NDPK-A expression to be a useful prognostic marker for pancreatic cancer. © 2012 Takadate et al.; licensee BioMed Central Ltd. Source

Takadate T.,Tohoku University | Onogawa T.,Tohoku University | Fukuda T.,Biosys Technologies Inc | Motoi F.,Tohoku University | And 14 more authors.
International Journal of Cancer

Pancreatic cancer is among the most lethal malignancies worldwide. We aimed to identify novel prognostic markers by applying mass spectrometry (MS)-based proteomic analysis to formalin-fixed paraffin-embedded (FFPE) tissues. Resectable, node positive pancreatic ductal adenocarcinoma (PDAC) with poor (n = 4) and better (n = 4) outcomes, based on survival duration, with essentially the same clinicopathological backgrounds, and noncancerous pancreatic ducts (n = 5) were analyzed. Cancerous and noncancerous cells collected from FFPE tissue sections by laser microdissection (LMD) were processed for liquid chromatography (LC)-tandem MS (MS/MS). Candidate proteins were identified by semiquantitative comparison and then analyzed quantitatively using selected reaction monitoring (SRM)-based MS. To confirm the associations between candidate proteins and outcomes, we immunohistochemically analyzed a cohort of 87 cases. In result, totally 1,229 proteins were identified and 170 were selected as candidate proteins for SRM-based targeted proteomics. Fourteen proteins overexpressed in cancerous as compared to noncancerous tissue showed different expressions in the poor and better outcome groups. Among these proteins, we found that three novel proteins ECH1, OLFM4 and STML2 were overexpressed in poor group than in better group, and that one known protein GTR1 was expressed reciprocally. Kaplan-Meier analysis showed high expressions of all four proteins to correlate with significantly worse overall survival (p < 0.05). In conclusion, we identified four proteins as candidates of prognostic marker of PDAC. The combination of shotgun proteomics verified by SRM and validated by immunohistochemistry resulted in the prognostic marker discovery that will contribute the understanding of PDAC biology and therapeutic development. What's new? While the search for biomarkers for particular cancers has often focused on mRNA, protein profiles may actually be more accurate. In addition, mRNA levels can't detect the activation of key signaling molecules in protein networks. In this study of pancreatic cancer, the authors used a novel strategy combining "global shotgun proteomics" using mass spectrometry (MS), and targeted "selected reaction monitoring" (SRM). They found that patients whose tumors expressed the proteins ECH1, OLFM4, STML2 and GTR1 had significantly worse outcomes. These proteins may thus have prognostic significance, and may also suggest new therapeutic targets. Copyright © 2012 UICC. Source

Nakayama N.,Biosys Technologies Inc | Bando Y.,Biosys Technologies Inc | Fukuda T.,Biosys Technologies Inc | Kawamura T.,University of Tokyo | And 5 more authors.
Drug Metabolism and Pharmacokinetics

A strong demand in drug discovery and development today is to overcome "Big Gaps" encountered by differences in species and races, to accelerate effective developments in cost and time, and to meet medical needs. Moreover, drugs of various types have emerged which cover middle-size molecules and polymers rather than conventional small molecules. Upon those challenges, mass spectrometry (MS)-based technologies, which will be described in this paper, will play an increasingly important role, among which the liquid chromatography-tandem mass spectrometry (LC/MS/MS) platform will be powerful as rapid and molecule-based analysis more than ever. nanoPore Optical Interferometry (nPOI) newly introduced can detect even weak interactions in protein-protein and protein-compound, and can be connected directly to LC/MS/MS for identification of binding molecular species, which will be quite useful for affinity ranking and high-throughput interaction screening. Imaging MS provides the molecular information and spatial distribution of targeted molecules within a tissue specimen. MS-based clinical proteomics utilizing clinical specimens and empowered by advanced bioinformatics can attain both key protein-protein interaction (PPI) networks with major protein players responsible for functional mechanisms of a disease subtype. An integration of those MS-based technologies will deliver a seamless platform of drug development from molecules identified in human clinical specimens. Copyright © 2015 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved. Source

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