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Selected reaction monitoring mass spectrometry (SRM-MS) -based semi-quantitation was performed to assess the validity of 46 selected candidate proteins for specifically diagnosing large-cell neuroendocrine lung carcinoma (LCNEC) and differentiating it from other lung cancer subtypes. The scaling method was applied in this study using specific SRM peak areas (AUCs) derived from the endogenous reference protein that normalizes all SRM AUCs obtained for the candidate proteins. In a screening verification study, we found that seven out of the 46 candidate proteins were statistically significant for the LCNEC phenotype, including 4F2hc cell surface antigen heavy chain (4F2hc/CD98) (p-ANOVA ≤ 0.0012), retinal dehydrogenase 1 (p-ANOVA ≤ 0.0029), apolipoprotein A-I (p-ANOVA ≤ 0.0004), β-enolase (p-ANOVA ≤ 0.0043), creatine kinase B-type (p-ANOVA ≤ 0.0070), and galectin-3-binding protein (p-ANOVA = 0.0080), and phosphatidylethanolamine-binding protein 1 (p-ANOVA ≤ 0.0012). In addition, we also identified candidate proteins specific to the small-cell lung carcinoma (SCLC) subtype. These candidates include brain acid soluble protein 1 (p-ANOVA < 0.0001) and γ-enolase (p-ANOVA ≤ 0.0013). This new relative quantitation-based approach utilizing the scaling method can be applied to assess hundreds of protein candidates obtained from discovery proteomic studies as a first step of the verification phase in biomarker development processes.

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., (Copyright © 2012 UICC.)

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.

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., (Copyright 2009 Elsevier B.V. All rights reserved.)

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., (Copyright 2009 Elsevier B.V. All rights reserved.)

In clinical and diagnostic proteomics, it is essential to develop a comprehensive and robust system for proteome analysis. Although multidimensional liquid chromatography/tandem mass spectrometry (LC/MS/MS) systems have been recently developed as powerful tools especially for identification of protein complexes, these systems still some drawbacks in their application to clinical research that requires an analysis of a large number of human samples. Therefore, in this study, we have constructed a technically simple and high throughput protein profiling system comprising a two-dimensional (2D)-LC/MS/MS system which integrates both a strong cation exchange (SCX) chromatography and a microLC/MS/MS system with micro-flowing reversed-phase chromatography. Using the microLC/MS/MS system as the second dimensional chromatography, SCX separation has been optimized as an off-line first dimensional peptide fractionation. To evaluate the performance of the constructed 2D-LC/MS/MS system, the results of detection and identification of proteins were compared using digests mixtures of 6 authentic proteins with those obtained using one-dimensional microLC/MS/MS system. The number of peptide fragments detected and the coverage of protein sequence were found to be more than double through the use of our newly built 2D-LC/MS/MS system. Furthermore, this multidimensional protein profiling system has been applied to plasma proteome in order to examine its feasibility for clinical proteomics. The experimental results revealed the identification of 174 proteins from one serum sample depleted HSA and IgG which corresponds to only 1 microL of plasma, and the total analysis run time was less than half a day, indicating a fairly high possibility of practicing clinical proteomics in a high throughput manner.

Invasive assays and lung tumor-bearing mice models using a human lung adenocarcinoma cell line A549 cells transfected with the Klotho (KL) gene, A549/KL cells, have confirmed that KL suppresses invasive/metastatic potential. This study aimed to identify the co-expression protein networks and proteomic profiles associated with A549/KL cells to understand how Klotho protein expression affects molecular networks associated with lung carcinoma malignancy. A two-step application of a weighted network correlation analysis to the cells' quantitative proteome datasets of a total of 6,994 proteins, identified by mass spectrometry-based proteomic analysis with data-independent acquisition (DIA), identified one network module as most significantly associated with the A549/KL trait. Upstream analyses, confirmed by western blot, implicated the pro-apoptotic Bim (Bcl-2-like protein 11) as a master regulator of molecular networks affected by Klotho. GeneMANIA interaction networks and quantitative proteome data implicated that Klotho interacts with two signaling axes: negatively with the Wnt/β-catenin axis, and positively by activating Bim. Our findings might contribute to the development of future therapeutic strategies. [ABSTRACT FROM AUTHOR]

Patients with estrogen receptor-positive/human epidermal growth factor receptor 2-negative/Ki-67-high (ER+HER2–Ki-67high) luminal breast cancer have a worse prognosis and do not respond to hormonal treatment and chemotherapy. This study sought to identify disease-related protein networks significantly associated with this subtype, by assessing in-depth proteomes of 10 lesions of high and low Ki-67 values (HOT, five; COLD, five) microdissected from the five tumors. Weighted correlation network analysis screened by over-representative analysis identified the five modules significantly associated with the HOT lesions. Pathway enrichment analysis, together with causal network analysis, revealed pathways of ribosome-associated quality controls, heat shock response by oxidative stress and hypoxia, angiogenesis, and oxidative phosphorylation. A semi-quantitative correlation of key-protein expressions, protein co-regulation analysis, and multivariate correlation analysis suggested co-regulations via network-network interaction among the four HOT-characteristic modules. Predicted highly activated master and upstream regulators were most characteristic to ER-positive breast cancer and associated with oncogenic transformation, as well as resistance to chemotherapy and endocrine therapy. Interestingly, inhibited intervention causal networks of numerous chemical inhibitors were predicted within the top 10 lists for the WM2 and WM5 modules, suggesting involvement of potential therapeutic targets in those data-driven networks. Our findings may help develop therapeutic strategies to benefit patients. [ABSTRACT FROM AUTHOR]

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 knownmarkers, but the one of two new candidate markers such asMLEC 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. [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

For high throughput proteome analysis of highly complex protein mixtures, we have constructed a fully automated online system for multi-dimensional protein profiling, which utilizes a combination of two-dimensional liquid chromatography and tandem mass spectrometry (2D-LC–MS–MS), based on our well-established offline system described previously [K. Fujii, T. Nakano, T. Kawamura, F. Usui, Y. Bando, R. Wang, T. Nishimura, J. Proteome Res. 3 (2004) 712]. A two-valve switching system on a programmable auto sample injector is utilized for online two-dimensional chromatography with strong cation-exchange (SCX) and reversed-phase (RP) separations. The SCX separation is carried out during the equilibration of RP chromatography and the entire sequence of analysis was performed under fully automated conditions within 4h, based on six SCX fractionations, and 40min running time for the two-dimensional RP chromatography. In order to evaluate its performance in the detection and identification of proteins, digests of six standard proteins and yeast 20S proteasome have been analyzed and their results were compared to those obtained by the one-dimensional reversed-phase chromatography system (1D-LC–MS–MS). The 2D-LC–MS–MS system demonstrated that both the number of peptide fragments detected and the protein coverage had more than doubled. Furthermore, this multi-dimensional protein profiling system was also applied to the human 26S proteasome, which is one of the highly complex protein mixtures. Consequently, 723 peptide fragments were identified as 31 proteasome components, together with other coexisting proteins in the sample. The identification could be comprehensively performed with a 63% sequence coverage on an average, and additionally, with modifications at the N-terminus. These results indicated that the online 2D-LC–MS–MS system being described here is capable of analyzing highly complex protein mixtures in a high throughput manner, and that it would be applicable to dynamic proteomics. [Copyright &y& Elsevier]