Biosys Technologies Inc

Tokyo, Japan

Biosys Technologies Inc

Tokyo, Japan

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Nomura M.,Tokyo Medical University | Fukuda T.,Biosys Technologies Inc | Fujii K.,Hokkaido University of Science | Kawamura T.,University of Tokyo | And 15 more authors.
Journal of Clinical Bioinformatics | Year: 2011

Background: Large cell neuroendocrine carcinoma (LCNEC) of the lung, a subtype of large cell carcinoma (LCC), is characterized by neuroendocrine differentiation that small cell lung carcinoma (SCLC) shares. Pre-therapeutic histological distinction between LCNEC and SCLC has so far been problematic, leading to adverse clinical outcome. We started a project establishing protein targets characteristic of LCNEC with a proteomic method using formalin fixed paraffin-embedded (FFPE) tissues, which will help make diagnosis convincing.Methods: Cancer cells were collected by laser microdissection from cancer foci in FFPE tissues of LCNEC (n = 4), SCLC (n = 5), and LCC (n = 5) with definite histological diagnosis. Proteins were extracted from the harvested sections, trypsin-digested, and subjected to HPLC/mass spectrometry. Proteins identified by database search were semi-quantified by spectral counting and statistically sorted by pair-wise G-statistics. The results were immunohistochemically verified using a total of 10 cases for each group to confirm proteomic results.Results: A total of 1981 proteins identified from the three cancer groups were subjected to pair-wise G-test under p < 0.05 and specificity of a protein's expression to LCNEC was checked using a 3D plot with the coordinates comprising G-statistic values for every two group comparisons. We identified four protein candidates preferentially expressed in LCNEC compared with SCLC with convincingly low p-values: aldehyde dehydrogenase 1 family member A1 (AL1A1) (p = 6.1 × 10-4), aldo-keto reductase family 1 members C1 (AK1C1) (p = 9.6x10-10) and C3 (AK1C3) (p = 3.9x10-10) and CD44 antigen (p = 0.021). These p-values were confirmed by non-parametric exact inference tests. Interestingly, all these candidates would belong to cancer stem cell markers. Immunohistochmistry supported proteomic results.Conclusions: These results suggest that candidate biomarkers of LCNEC were related to cancer stem cells and this proteomic approach via FFPE samples was effective to detect them. © 2011 Nomura et al; licensee BioMed Central Ltd.


Kawamura T.,University of Tokyo | Nomura M.,Tokyo Medical University | Tojo H.,Osaka University | Fujii K.,Hokkaido University | And 5 more authors.
Journal of Proteomics | Year: 2010

We used formalin-fixed paraffin-embedded (FFPE) materials for biomarker discovery in cases of lung cancer using proteomic analysis. We conducted a retrospective global proteomic study in order to characterize protein expression reflecting clinical stages of individual patients with stage I lung adenocarcinoma without lymph node involvement (n = 7). In addition, we studied more advanced stage IIIA with spread to lymph nodes (n = 6), because the degree of lymph node involvement is the most important factor for staging. FFPE sections of cancerous lesions resected surgically from patients with well-characterized clinical history were subjected to laser microdissection (LMD) followed by Liquid Tissue™ solubilization and digestion trypsin. Spectral counting was used to measure the amounts of proteins identified by shotgun liquid chromatography (LC)/tandem mass spectrometry (MS/MS). More than 500 proteins were identified from IA and IIIA cases, and non-parametric statistics showed that 81 proteins correlated significantly with stage IA or IIIA. A subset of those proteins were verified by multiple-reaction monitoring mass spectrometric quantitation (MRM assay), described in other paper in this issue. These results demonstrated the technical feasibility of a global proteomic study using clinically well documented FFPE sections, and its possible utility for detailed retrospective disease analyses in order to improve therapeutic strategy. © 2009 Elsevier B.V. All rights reserved.


Nishimura T.,Tokyo Medical University | Nomura M.,Tokyo Medical University | Tojo H.,Osaka University | Hamasaki H.,University of Tokyo | And 5 more authors.
Journal of Proteomics | Year: 2010

A preceding paper suggested 81 candidates of stage-specifically expressed proteins for either stage IA or IIIA by global shotgun proteomics and spectral counting. Six proteins, a subset of these proteins, were chosen for a further verification study since they are potentially soluble and/or secretory, which nature is convenient for detecting them in blood in clinical practice. The multiple-reaction monitoring (MRM) quantitative analysis suggested that napsin-A and anterior gradient protein 2 homolog (hAG-2) out of the 6 candidates would be useful for determining stage IA or IIIA and are related to metastasis. In the study we noted that stage IIIA patients with better outcome showed napsin-A profiles similar to that of stage IA patients. We therefore examined 14 additional patients for analysis, which contained the IA-stage patients of poorer outcome and the IIIA-stage patients of better outcome. The MRM analysis of napsin-A for all patients suggests that napsin-A contents correlate with better outcome in stage IA. This and discovery studies demonstrate that direct isolation of tumor cells alone by laser microdissection (LMD) greatly reduces complexity on comprehensive analyses, and that MRM mass spectrometry using the endogenous internal standard is a feasible technology for quantitative verification of target proteins in formalin-fixed paraffin embedded (FFPE) tissues. © 2009 Elsevier B.V. All rights reserved.


Kato H.,Niizashiki Chuo General Hospital | Kato H.,International University of Health and Welfare | Kato H.,Tokyo Medical University | Nishimura T.,Tokyo Medical University | And 14 more authors.
Journal of Proteome Research | Year: 2011

In Japan, rising costs have impacted the framework of maintaining an efficient and effective healthcare system. Today, urgent implementation of programs to address this need have led to a rebuilding of the entire approach of medical evaluation and clinical care. Recent developments in clinical proteomics based on mass spectrometry (MS) for identifying, sequencing, and quantifying disease-relevant protein biomarkers is a promising means for optimal drug prescription using biomarker diagnosis. We illustrate in this report our experience with lung cancer cases with various drug therapies evaluated with proteomics studies. © 2011 American Chemical Society.


Takadate T.,Tohoku University | Onogawa T.,Tohoku University | Fujii K.,Hokkaido University | Motoi F.,Tohoku University | And 15 more authors.
Clinical Proteomics | Year: 2012

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.


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 | Year: 2010

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.


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 | Year: 2013

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.


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 | Year: 2016

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.


Ban Y.,Showa University | Yamamoto G.,Showa University | Takada M.,Showa University | Hayashi S.,Showa University | And 7 more authors.
Journal of Thyroid Research | Year: 2012

Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy. We performed shotgun liquid chromatography (LC)/tandem mass spectrometry (MS/MS) analysis on pooled protein extracts from patients with PTC and compared the results with those from normal thyroid tissue validated by real-time (RT) PCR and immunohistochemistry (IHC). We detected 524 types of protein in PTC and 432 in normal thyroid gland. Among these proteins, 145 were specific to PTC and 53 were specific to normal thyroid gland. We have also identified two important new markers, nephronectin (NPNT) and malectin (MLEC). Reproducibility was confirmed with several known markers, but the one of two new candidate markers such as MLEC did not show large variations in expression levels. Furthermore, IHC confirmed the overexpression of both those markers in PTCs compared with normal surrounding tissues. Our protein data suggest that NPNT and MLEC could be a characteristic marker for PTC. © 2012 Yoshiyuki Ban et al.


PubMed | Mariana University, Lund University, Biosys Technologies Inc., Tokyo Electron and University of Tokyo
Type: Journal Article | Journal: Drug metabolism and pharmacokinetics | Year: 2016

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.

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