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Objective Considerable evidence suggests that neuroinflammation plays an important role in the pathophysiology of major depressive disorder (MDD). However, the relationship between serum C4 binding protein (C4BP) and white matter (WM) tract integrity in MDD has not been investigated.Methods We obtained diffusion tensor images of 44 patients with MDD and 44 healthy controls and performed TRActs Constrained by UnderLying Anatomy (TRACULA) analysis to assess WM tract integrity. Serum C4-binding protein alpha chain (C4BPA) and C4- binding protein beta chain (C4BPB) levels were measured and in-between group comparisons were obtained. The correlation between serum C4BP levels and WM tract integrity was examined.Results In comparison to healthy controls, both serum C4BPA and C4BPB were higher in MDD. Also, fractional anisotropy (FA) was increased in the left cingulum-angular bundle (CAB) in MDD, but not healthy controls (HCs). A significant correlation was found between serum C4BP and FA levels in the right cingulum-cingulate gyrus bundle (CCG) in MDD.Conclusion This study is the first to investigate the correlation between serum C4BP levels and WM tract integrity in MDD. We identified an increase in WM integrity in the left CAB region in MDD. Furthermore, serum C4BP levels were higher in MDD, and this finding correlated with increased WM integrity in the right CCG region.

High-grade serous ovarian cancer (HGSOC) represents the major histological type of ovarian cancer, and the lack of effective screening tools and early detection methods significantly contributes to the poor prognosis of HGSOC. Currently, there are no reliable diagnostic biomarkers for HGSOC. In this study, we performed liquid chromatography data-independent acquisition tandem mass spectrometry (MS) on depleted serum samples from 26 HGSOC cases and 24 healthy controls (HCs) to discover potential HGSOC diagnostic biomarkers. A total of 1,847 proteins were identified across all samples, among which 116 proteins showed differential expressions between HGSOC patients and HCs. Network modeling showed activations of coagulation and complement cascades, platelet activation and aggregation, neutrophil extracellular trap formation, toll-like receptor 4, insulin-like growth factor, and transforming growth factor β signaling, as well as suppression of lipoprotein assembly and Fc gamma receptor activation in HGSOC. Based on the network model, we prioritized 28 biomarker candidates and validated 18 of them using targeted MS assays in an independent cohort. Predictive modeling showed a sensitivity of 1 and a specificity of 0.91 in the validation cohort. Finally, in vitro functional assays on four potential biomarkers (FGA, VWF, ARHGDIB, and SERPINF2) suggested that they may play an important role in cancer cell proliferation and migration in HGSOC. All raw data were deposited in PRIDE (PXD033169).

Purpose Currently, the standard screening tool for breast cancer is screening mammography. There have been many efforts to develop a blood-based diagnostic assay for breast cancer diagnosis; however, none have been approved for clinical use at this time. The purpose of this study was to determine the accuracy of a novel blood-based proteomic test for aiding breast cancer diagnosis in a relatively large cohort of cancer patients. Methods A blood-based test using multiple reaction monitoring (MRM) measured by mass spectrometry to quantify 3 peptides (apolipoprotein C-1, carbonic anhydrase 1, and neural cell adhesion molecule L1-like protein) present in human plasma was investigated. A total of 1,129 blood samples from 575 breast cancer patients, 454 healthy controls, and 100 patients with other malignancies were used to verify and optimize the assay. Results The diagnostic sensitivity, specificity, and accuracy of the MRM-based proteomic assay were 71.6%, 85.3%, and 77%, respectively; the area under the receiver operating characteristic curve was 0.8323. The proteomic assay did not demonstrate diagnostic accuracy in patients with other types of malignancies including thyroid, pancreatic, lung, and colon cancers. The diagnostic performance of the proteomic assay was not associated with the timing of blood sampling before or after anesthesia. Conclusion The data demonstrated that an MRM-based proteomic assay that measures plasma levels of three specific peptides can be a useful tool for breast cancer screening and its accuracy is cancer-type specific.

We propose to use cRFP (common Repository of FBS Proteins) in the MS (mass spectrometry) raw data search of cell secretomes. cRFP is a small supplementary sequence list of highly abundant fetal bovine serum proteins added to the reference database in use. The aim behind using cRFP is to prevent the contaminant FBS proteins from being misidentified as other proteins in the reference database, just as we would use cRAP (common Repository of Adventitious Proteins) to prevent contaminant proteins present either by accident or through unavoidable contacts from being misidentified as other proteins. We expect it to be widely used in experiments where the proteins are obtained from serum-free media after thorough washing of the cells, or from a complex media such as SILAC, or from extracellular vesicles directly.

e17564 Background: Ovarian cancer (OC) is one of the most common causes of cancer-related death among women worldwide. High-grade serous ovarian cancer (HGSOC) represents the major OC histological type, and challenges associated with its early detection and prediction of clinical outcomes significantly contribute to the high prevalence and poor prognosis of OC. Lack of reliable biomarkers further exacerbates the low survival rate of patients with HGSOC. Methods: In this study, we performed liquid chromatography data independent acquisition tandem-mass spectrometry (LC-DIA-MS/MS) experiments on depleted serum samples [26 HGSOC cases, 24 healthy controls (HCs)] to identify potential diagnostic and prognostic biomarkers for HGSOC. Results: A total of 1,148 proteins were identified in all samples combined, representing one of the largest quantifications in the serum proteome of OC to date. Among them, 122 proteins showed differential expressions between the serum proteome of HGSOC patients and HCs, including 109 up- and 14 down-regulated proteins in HGSOC. These potential diagnostic biomarkers were involved in the pathways related to immune response, TGF- β and IGF signaling, and lipid metabolism. Moreover, we performed Kaplan-Meier survival analysis on the HGSOC patients with and without recurrence, and identified several potential prognostic biomarkers highly associated with progression free survival (PFS). Using independent cohort samples, we validated the expression levels of HGSOC serum biomarker candidates using targeted proteomics approaches (MRM and PRM). In vitro functional assays revealed that some of these biomarkers may play an essential role in cancer cell migration and proliferation in HGSOC. Conclusions: In summary, our LC-DIA-MS/MS analysis of the HGSOC serum proteome successfully identified novel diagnostic and prognostic biomarkers for HGSOC, some of which were experimentally shown to have functional relevance to the pathophysiology of OC.

Biomarkers factor into the diagnosis and treatment of almost every patient with cancer. The innovation in proteomics follows improvement of mass spectrometry techniques and data processing strategy. Recently, proteomics and typical biological studies have been the answer for clinical applications. The clinical proteomics techniques are now actively adapted to protein identification in large patient cohort, biomarker development for more sensitive and specific screening based on quantitative data. And, it is important for clinical, translational researchers to be acutely aware of the issues surrounding appropriate biomarker development, in order to facilitate entry of clinically useful biomarkers into the clinic. Here, we discuss in detail include the case research for clinical proteomics. Furthermore, we give an overview on the current developments and novel findings in proteomics-based cancer biomarker research.

Biomarkers factor into the diagnosis and treatment of almost every patient with cancer. The innovation in proteomics follows improvement of mass spectrometry techniques and data processing strategy. Recently, proteomics and typical biological studies have been the answer for clinical applications. The clinical proteomics techniques are now actively adapted to protein identification in large patient cohort, biomarker development for more sensitive and specific screening based on quantitative data. And, it is important for clinical, translational researchers to be acutely aware of the issues surrounding appropriate biomarker development, in order to facilitate entry of clinically useful biomarkers into the clinic. Here, we discuss in detail include the case research for clinical proteomics. Furthermore, we give an overview on the current developments and novel findings in proteomics-based cancer biomarker research.

Among the three isoforms encoded by Rtn4, Nogo-A has been intensely investigated as a central nervous system inhibitor. Although Nogo-A expression is increased in muscles of patients with amyotrophic lateral sclerosis, its role in muscle homeostasis and regeneration is not well elucidated. In this study, we discovered a significant increase in Nogo-A expression in various muscle-related pathological conditions. Nogo−/− mice displayed dystrophic muscle structure, dysregulated muscle regeneration following injury, and altered gene expression involving lipid storage and muscle cell differentiation. We hypothesized that increased Nogo-A levels might regulate muscle regeneration. Differentiating myoblasts exhibited Nogo-A upregulation and silencing Nogo-A abrogated myoblast differentiation. Nogo-A interacted with filamin-C, suggesting a role for Nogo-A in cytoskeletal arrangement during myogenesis. In conclusion, Nogo-A maintains muscle homeostasis and integrity, and pathologically altered Nogo-A expression mediates muscle regeneration, suggesting Nogo-A as a novel target for the treatment of myopathies in clinical settings.

High-grade serous ovarian carcinoma (HGSOC) and basal-like breast cancer (BLBC) share many features including TP53 mutations, genomic instability and poor prognosis. We recently reported that Elafin is overexpressed by HGSOC and is associated with poor overall survival. Here, we confirm that Elafin overexpression is associated with shorter survival in 1000 HGSOC patients. Elafin confers a proliferative advantage to tumor cells through the activation of the MAP kinase pathway. This mitogenic effect can be neutralized by RNA interference, specific antibodies and a MEK inhibitor. Elafin expression in patient-derived samples was also associated with chemoresistance and strongly correlates with bcl-xL expression. We extended these findings into the examination of 1100 primary breast tumors and six breast cancer cell lines. We observed that Elafin is overexpressed and secreted specifically by BLBC tumors and cell lines, leading to a similar mitogenic effect through activation of the MAP kinase pathway. Here too, Elafin overexpression is associated with poor overall survival, suggesting that it may serve as a biomarker and therapeutic target in this setting.

3044 Background: Breast cancer is the most frequently diagnosed cancer and the most leading cause of cancer-related deaths among women worldwide. Although screening mammography is available, there is an ongoing interest in improved early detection and prognosis. And also, serum tumor marker levels, such as CA 15-3 and others, may reflect disease progression and recurrence, they have not proven to be sensitive for early disease detection. Research investigating biomarkers for early detection, prognosis and the prediction of treatment responses in breast cancer is rapidly expanding. However, no validated biomarker currently exists for use in routine clinical practice, and breast cancer detection and management remains dependent on invasive procedures We aimed to develop biomarker for diagnosis of breast cancer in the real clinical practice by using proteomics technology. Methods: Based on our previous studies, we performed verification and validation of 124 candidate proteins by using proteomics approach. Among these 124 candidate proteins, the three proteins (neural cell adhesion molecule L1-like protein, apolipoprotein C-1, carbonic anhydrase-1) with highest statistical significance were selected. We created the performance algorithm of the 3-protein diagnostic model to predict of the breast cancer. We performed several experiments for establishment and validation of cut-off value. Furthermore we conducted test for acquisition of sample stability and more experiments to achieve the reproducibility and level of evidence, compared with other cancers (colon, thyroid, ovary, pancreas and lung cancer) and established effect of anesthesia. Results: Total 1226 samples (532 patients of breast cancer, 562 healthy women and 100 sample of other cancers) was analyzed. The sensitivity, specificity and accuracy from confirmation experiment was 71.58%, 85.25% and AUC 0.8323, respectively. The result of comparison with other cancers, there are no statistical significant difference and no relevance with effects of anesthesia. With these results, we recently got permission it to use for in vitro diagnostic use from Korea Food and Drug Administration. Conclusions: In this study, we developed a plasma protein biomarker that may help to diagnosis of breast cancer in the real clinical practice. By using MRM approach, the 3-protein biomarker was validated in an independent cohort with acceptable accuracy for early diagnosis of breast cancer.

Leucine-rich repeat kinase 2 (LRRK2) is a large multidomain protein that is expressed in many tissues and participates in numerous biological pathways. Mutations in LRRK2 are recognized as genetic risk factors for familial Parkinson's disease (PD) and may also represent causal factors in the more common sporadic form of PD. The structure of LRRK2 comprises a combination of GTPase, kinase, and scaffolding domains. This functional diversity, combined with a potentially central role in genetic and idiopathic PD motivates significant effort to further credential LRRK2 as a therapeutic target. Here, we review the current understanding for LRRK2 function in normal physiology and PD, with emphasis on insight gained from proteomic approaches.

Screening patients at high risk of recurrence of cancer would allow for more accurate and personalized treatment. In this study, we tried to identify the prognosis-related protein profile by applying two different quantitative proteomic techniques, difference in-gel electrophoresis and cleavable isotope-coded affinity tag method. Six tumor tissues were obtained from stage IV colorectal cancer (CRC) patients, of which three have survived more than five years (good prognostic group, GPG) and the other three died within 25 months (poor prognostic group, PPG) after palliative surgery and subsequent chemotherapy treatment. From the two independent quantitative analyses, we identified 175 proteins with abundance ratios greater than 2-fold. Gene ontology analysis revealed that proteins related to cellular assembly/organization and movement were generally increased in the PPG. Twenty-two proteins, including caveolin-1, were chosen for confirmatory studies by Western blot and immunohistochemistry. The Western blot data for each individual protein were analyzed with Mann–Whitney tests, and a multi-marker panel was generated by logistic regression analysis. Five proteins, fatty acid binding protein 1, intelectin 1, transitional endoplasmic reticulum ATPase, transgelin and tropomyosin 2, were significantly different between the two prognostic groups within 95% confidence. No single protein could completely distinguish the two groups from each other. However, a combination of the five proteins effectively distinguished PPG from GPG patients (AUC = 1). Our study suggests a multi-marker panel composed of proteome signatures that provide accurate predictive information and potentially assist personalized therapy. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Gcn4p is a well-characterized bZIP transcription factor that activates more than 500 genes encoding amino acids and purine biosynthesis enzymes, and many stress–response genes under various stress conditions. Under these stresses, it had been shown that transcriptions of ribosomal protein (RP) genes were decreased. However, the detailed mechanism of this downregulation has not been elucidated. In this study, we present a novel mechanistic model for a repressive role of Gcn4p on RP transcription, especially under amino-acid starvation. It was found that Gcn4p bound directly to Rap1p, which in turn inhibited Esa1p–Rap1p binding. The inhibition of Esa1p recruitment to RP promoters ultimately reduced the level of histone H4 acetylation and RP transcription. These data revealed that Gcn4p has simultaneous dual roles as a repressor for RP genes as well as an activator for amino-acid biosynthesis genes. Moreover, our results showed evidence of a novel link between general control of amino-acid biosynthesis and ribosome biogenesis mediated by Gcn4p at an early stage of adaptation to amino-acid starvation.

HMGB1 is a nuclear protein that is overexpressed and secreted in cancer cells. However, little is known about the roles of HMGB1 in the cytoplasm and secretory pathway in cancer cells. To clarify this aspect of HMGB1 function, we fractionated the cytoplasm of HCT116 colon cancer cells and used a proteomic approach to analyze cytoplasmic HMGB1-binding proteins. Pull-down experiments using recombinant HMGB1 protein as bait, followed by mass spectrometry analysis identified 162 interacting proteins. Among them were 74 proteins known to be localized exclusively to the extra-nuclear region, and 60 proteins known to be localized to both nuclear and extranuclear regions. The functions of these binding proteins include involvement in cell-cycle progression, cell proliferation, anti-apoptosis, and angiogenesis. In addition, nine of the identified proteins are related to protein translocation and secretion. These include annexin A2, myosin IC isoform a, myosin-9, and Ras-related protein Rab10, which are involved in unconventional protein secretion. Cytoplasmic HMGB1 was primarily associated with the lysosomal cytosol fraction and was colocalized with the lysosomal marker LAMP1. Our findings suggest that cytoplasmic HMGB1 binds to a number of molecules related to cancer progression and the unconventional secretory pathway.

Proteomic techniques are mostly used these days to identify proteins in a biological sample. Quantification of the differences between two or more physiological conditions, such as disease or no disease, has become an increasingly challenging task in proteomics. Mass tags introducing stable isotopes into peptides or proteins provide means for quantification in mass spectrometry. The mass tags are recognized by mass spectrometry and at the same time provide quantitative information. In the current study, we introduce mTRAQ for the purpose of quantification by full MS scans. Although mTRAQ reagent was initially designed for multiple reaction monitoring, we verified the utility of mTRAQ for MS1-based relative quantification using standard protein mixtures and blood plasma samples. mTRAQ-labeled peptides showed better quality MS2 spectra with increased XCorr values in a SEQUEST search output than corresponding unlabeled peptides. The improved spectral quality was due mostly to the enhanced matching of b-type ions. By combining mTRAQ with ICAT and applying them to colon cancer tissues, we identified and quantified a total of 3,320 proteins. mTRAQ covered a wider range of the proteome than did ICAT, and only 1053 proteins were shared by the two independent methods. Our results suggest the usefulness of mTRAQ, alone or in combination with ICAT, as a comparative profiling method in quantitative proteomics.

Protein quantification is one of the principal computational problems in mass spectrometry (MS) based proteomics. For robust and trustworthy protein quantification, accurate peptide quantification must be preceded. In recent years, stable isotope labeling has become the most popular method for relative quantification of peptides. However, some stable isotope labeling methods may carry a critical problem, which is an overlap of isotopic clusters. If the mass difference between the light- and heavy-labeled peptides is very small, the overlap of their isotopic clusters becomes larger as the mass of original peptide increases. Here we propose a new algorithm for peptide quantification that separates overlapping isotopic clusters using quadratic equations. It can be easily applied in Trans-Proteomic Pipeline (TPP) instead of XPRESS. For the mTRAQ-labeled peptides obtained by an Orbitrap mass spectrometer, it showed more accurate ratios and better standard deviations than XPRESS. Especially, for the peptides that do not contain lysine, the ratio difference between XPRESS and our algorithm became larger as the peptide masses increased. We expect that this algorithm can also be applied to other labeling methods such as (18)O labeling and acrylamide labeling.

Proteomic analyses of synaptic vesicle fraction from rat brain have been performed for the better understanding of vesicle regulation and signal transmission. Two different approaches were applied to identify proteins in synaptic vesicle fraction. First, the isolated synaptic vesicle proteins were treated with trypsin, and the resulting peptides were analyzed using a high-pressure capillary reversed phase liquid chromatography/tandem mass spectrometry (cRPLC/MS/MS). Alternatively, proteins were separated by two-dimensional gel electrophoresis (2DE) and identified by matrix-assisted laser desorption ionization mass spectrometry (MALDI-TOF/MS). Total 18 and 52 proteins were identified from cRPLC/MS-MS and 2DE-MALDI-TOF-MS analysis, respectively. Among them only 2 proteins were identified by both methods. Of the proteins identified, 70% were soluble proteins and 30% were membrane proteins. They were categorized by their functions in vesicle trafficking and biogenesis, energy metabolism, signal transduction, transport and unknown functions. Among them, 27 proteins were not previously reported as synaptic proteins. The cellular functions of unknown proteins were estimated from the analysis of domain structure, expression profile and predicted interaction partners.

Absence seizure has been of interest because the symptom is related to sensory processing. However, the mechanism that causes the disease is not understood yet. To better understand the molecular mechanism related to the disease progress at protein level, we performed proteomic studies using the thalamus of mice for which absence seizure was induced by gamma-butyrolactone (GBL). Differential proteome expression between GBL-treated mice and control mice was examined by fluorescence 2D difference gel electrophoresis (DIGE) at three different time points (5, 10, and 30 min) after GBL-administration. We identified 16 proteins differentially expressed by >1.4-fold at any of the three time points. All proteins besides the serine protease inhibitor EIA were down-regulated in absence seizure-induced mice. The down-regulated proteins can be classified into five groups by their biological functions: cytoskeleton rearrangement, neuroprotection, neurotransmitter secretion, calcium binding, and metabolism. The maximum level of change was reached by 10 min after GBL-treatment, with the expression level returning back to the original at 30 min when mice were awakened from absence seizure thereby demonstrating the proteomic response is reversible. Our results suggest that absence seizures are associated with restricted functional sets of proteins, whose down-regulation may interfere with general function of neuronal cells.

We aimed to develop a plasma protein signature for breast cancer diagnosis by using multiple reaction monitoring (MRM)-based mass spectrometry.Based on our previous studies, we selected 124 proteins for MRM. Plasma samples from 80 patients with breast cancer and 80 healthy women were used to develop a plasma proteomic signature by an MRM approach. The proteomic signature was then validated in plasma samples from 100 patients with breast cancer and 100 healthy women.A total of 56 proteins were optimized for MRM. In the verification cohort, 11 proteins exhibited significantly differential expression in plasma from patients with breast cancer. Three proteins (neural cell adhesion molecule L1-like protein, apolipoprotein C-1 and carbonic anhydrase-1) with highest statistical significance which gave consistent results for patients of stage I and II breast cancer were selected and a 3-protein signature was developed using binary logistic regression analysis [area under the curve (AUC)=0.851, sensitivity=80.6%]. The 3-protein signature showed similar performance in an independent validation cohort with an AUC of 0.797 and sensitivity of 77.2% for detection of stage I and II breast cancer.We developed a distinct plasma protein signature for breast cancer diagnosis based on an MRM-based approach, and the clinical value of the 3-protein signature was validated in an independent cohort.

Dynamic interactions between RNA polymerase II and various mRNA-processing and chromatin-modifying enzymes are mediated by the changing phosphorylation pattern on the C-terminal domain (CTD) of polymerase subunit Rpb1 during different stages of transcription. Phosphorylations within the repetitive heptamer sequence (YSPTSPS) of CTD have primarily been defined using antibodies, but these do not distinguish different repeats or allow comparative quantitation. Using a CTD modified for mass spectrometry (msCTD), we show that Ser5-P and Ser2-P occur throughout the length of CTD and are far more abundant than other phosphorylation sites. msCTD extracted from cells mutated in several CTD kinases or phosphatases showed the expected changes in phosphorylation. Furthermore, msCTD associated with capping enzyme was enriched for Ser5-P while that bound to the transcription termination factor Rtt103 had higher levels of Ser2-P. These results suggest a relatively sparse and simple "CTD code."

Post-genomic studies continue to highlight the potential clinical importance of protein phosphorylation signaling pathways in drug discovery. Unfortunately the dynamic range and variable stoichiometry of protein phosphorylation continues to stymie efforts to achieve comprehensive characterization of the human phosphoproteome. In this study, we develop a complementary, two-stage method for enrichment of cysteine-containing phosphopeptides combined with TMT multiplex labeling for relative quantification. Use of this approach with multi-dimension fractionation in mammalian cells yielded more than 7,000 unique cys-phosphopeptide sequences, comprising 15%–20% novel phosphorylation sites. Use of our approach in combination with pharmacologic inhibitors of the mammalian target of rapamycin complex 1 and 2 (mTORC1/2) identified several putatively novel protein substrates for the mechanistic target of rapamycin (mTOR) kinase.

Breast cancer is the most common cancer in women worldwide. It is necessary to identify biomarkers for early detection, to make accurate prognoses, and to monitor for any recurrence of the cancer. In order to identify potential breast cancer biomarkers, we analyzed the plasma samples of women diagnosed with breast cancer and age-matched normal healthy women by mTRAQ-based stable isotope-labeling mass spectrometry. We identified and quantified 204 proteins including thrombospondin-1 (THBS1) and bromodomain and WD repeat-containing protein 3 (BRWD3) which were increased by more than 5-fold in breast cancer plasma. The plasma levels of the two proteins were evaluated by Western blot assay to confirm for their diagnostic value as serum markers. A 1.8-fold increase in BRWD3 was observed while comparing the plasma levels of breast cancer patients (n = 54) with age-matched normal healthy controls (n = 30), and the area under the receiver operating characteristic curve (AUC) was 0.917. THBS1 was detected in pooled breast cancer plasma at the ratio similar to mTRAQ ratio (> 5-fold). The AUC value for THBS1 was 0.875. The increase of THBS1 was more prominent in estrogen receptor negative and progesterone receptor negative patients than receptor-positive patients. Our results are evidence of the diagnostic value of THBS1 in detecting breast cancer. Based on our findings, we suggest a proteomic method for protein identification and quantification lead to effective biomarker discovery.

An efficient means of identifying protein biomarkers is essential to proper cancer management. A well-characterized proteome resource holds special promise for the discovery of novel biomarkers. However, quantification of the differences between physiological conditions together with deep down profiling has become increasingly challenging in proteomics. Here, we perform expression profiling of the colorectal cancer (CRC) proteome by stable isotope labeling and mass spectrometry. Quantitative analysis included performing mTRAQ and cICAT labeling in a pooled sample of three microsatellite stable (MSS) type CRC tissues and a pooled sample of their matched normal tissues. We identified and quantified a total of 3688 proteins. Among them, 1487 proteins were expressed differentially between normal and cancer tissues by higher than 2-fold; 1009 proteins showed increased expression in cancer tissue, whereas 478 proteins showed decreased expression. Bioinformatic analysis revealed that our data were largely consistent with known CRC relevant signaling pathways, such as the Wnt/β-catenin, caveolar-mediated endocytosis, and RAN signaling pathways. Mitochondrial dysfunction, known as the Waburg hypothesis, was also confirmed. Therefore, our data showing alterations in the proteomic profile of CRC constitutes a useful resource that may provide insights into tumor progression with later goal of identifying biologically and clinically relevant marker proteins. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Gcn4p is a well-characterized bZIP transcription factor that activates more than 500 genes encoding amino acids and purine biosynthesis enzymes, and many stress-response genes under various stress conditions. Under these stresses, it had been shown that transcriptions of ribosomal protein (RP) genes were decreased. However, the detailed mechanism of this downregulation has not been elucidated. In this study, we present a novel mechanistic model for a repressive role of Gcn4p on RP transcription, especially under amino-acid starvation. It was found that Gcn4p bound directly to Rap1p, which in turn inhibited Esa1p-Rap1p binding. The inhibition of Esa1p recruitment to RP promoters ultimately reduced the level of histone H4 acetylation and RP transcription. These data revealed that Gcn4p has simultaneous dual roles as a repressor for RP genes as well as an activator for amino-acid biosynthesis genes. Moreover, our results showed evidence of a novel link between general control of amino-acid biosynthesis and ribosome biogenesis mediated by Gcn4p at an early stage of adaptation to amino-acid starvation.

Glycosylation is the most important and abundant post-translational modification in serum proteome. Several specific types of glycan epitopes have been shown to be associated with various types of disease. Direct analysis of serum glycoproteins is challenging due to its wide dynamic range. Alternatively, glycoproteins can be discovered in the secretome of model cell lines and then confirmed in blood. However, there has been little experi-mental evidence showing cell line secretome as a tractable target for the study of serum glycoproteins. We used a hydrazine-based glycocapture method to selectively enrich glycoproteins from the secretome of the breast cancer cell line Hs578T. A total of 132 glycoproteins were identified by nanoLC-MS/MS analysis. Among the identified proteins, we selected 13 proteins that had one or more N-glycosylation motifs in the matched peptides, which were included in the Secreted Protein Database but not yet in the Plasma Proteome Database (PPD), and whose antibodies were commercially available. Nine out of the 13 selected proteins were detected from human blood plasma by western analysis. Furthermore, eight proteins were also detected from the plasma by targeted LC-MS/MS, which had never been previously identified by data-dependent LC-MS/MS. Our results provide novel proteins that should be enrolled in PPD and suggest that analysis of cell line secretome with subfractionation is an efficient strategy for discovering disease-relevant serum proteins.

Diabetes can lead to serious microvascular complications like proliferative diabetic retinopathy (PDR), which is the leading cause of blindness in adults. The proteomic changes that occur during PDR cannot be measured in the human retina for ethical reasons, but could be reflected by proteomic changes in vitreous humor. Thus, we considered that comparisons between the proteome profiles of the vitreous humors of PDR and nondiabetic controls could lead to the discovery of novel pathogenic proteins and clinical biomarkers. In this study, the authors used several proteomic methods to comprehensively examine vitreous humor proteomes of PDR patients and nondiabetic controls. These methods included immunoaffinity subtraction (IS)/2-DE/MALDI-MS, nano-LC-MALDI-MS/MS, and nano-LC-ESI-MS/MS. The identified proteins were subjected to the Trans-Proteomic Pipeline validation process. Resultantly, 531 proteins were identified, i.e., 415 and 346 proteins were identified in PDR and nondiabetic control vitreous humor samples, respectively, and of these 531 proteins, 240 were identified for the first time in this study. The PDR vitreous proteome was also found to contain many proteins possibly involved in the pathogenesis of PDR. The proteins described provide the most comprehensive proteome listing in the vitreous humor samples of PDR and nondiabetic control patients.

The native form of serpins (serine protease inhibitors) is a metastable conformation, which converts into a more stable form upon complex formation with a target protease. It has been suggested that movement of helix-F (hF) and the following loop connecting to strand 3 of beta-sheet A (thFs3A) is critical for such conformational change. Despite many speculations inferred from analysis of the serpin structure itself, direct experimental evidence for the mobilization of hF/thFs3A during the inhibition process is lacking. To probe the mechanistic role of hF and thFs3A during protease inhibition, a disulfide bond was engineered in alpha(1)-antitrypsin, which would lock the displacement of thFs3A from beta-sheet A. We measured the inhibitory activity of each disulfide-locked mutant and its heat stability against loop-sheet polymerization. Presence of a disulfide between thFs3A and s5A but not between thFs3A and s3A caused loss of the inhibitory activity, suggesting that displacement of hF/thFs3A from strand 5A but not from strand 3A is required during the inhibition process. While showing little influence on the inhibitory activity, the disulfide between thFs3A and s3A retarded loop-sheet polymerization significantly. This successful protein engineering of alpha(1)-antitrypsin is expected to be of value in clinical applications. Based on our current studies, we propose that the reactive-site loop of a serpin glides through between s5A and thFs3A for the full insertion into beta-sheet A while a substantial portion of the interactions between hF and s3A is kept intact.

Absence seizure has been of interest because the symptom is related to sensory processing. However, the mechanism that causes the disease is not understood yet. To better understand the molecular mechanism related to the disease progress at protein level, we performed proteomic studies using the thalamus of mice for which absence seizure was induced by gamma-butyrolactone (GBL). Differential proteome expression between GBL-treated mice and control mice was examined by fluorescence 2D difference gel electrophoresis (DIGE) at three different time points (5, 10, and 30 min) after GBL-administration. We identified 16 proteins differentially expressed by1.4-fold at any of the three time points. All proteins besides the serine protease inhibitor EIA were down-regulated in absence seizure-induced mice. The down-regulated proteins can be classified into five groups by their biological functions: cytoskeleton rearrangement, neuroprotection, neurotransmitter secretion, calcium binding, and metabolism. The maximum level of change was reached by 10 min after GBL-treatment, with the expression level returning back to the original at 30 min when mice were awakened from absence seizure thereby demonstrating the proteomic response is reversible. Our results suggest that absence seizures are associated with restricted functional sets of proteins, whose down-regulation may interfere with general function of neuronal cells.

Comparative proteome analysis was performed on the cultured media of human nontumor and malignant breast cell lines, Hs578Bst and Hs578T, respectively, in search of a serological biomarker(s) for breast cancer. Proteins in the conditioned media were separated by 2-D PAGE and then visualized by silver-staining. Eight proteins changed differentially by more than two-fold were identified by MALDI-TOF/TOF MS. Among the proteins identified, the terminal laminin-like globular (LG3) domain of endorepellin, which was recently reported as an antiangiogenesis factor, was decreased in the cancer cell line. We confirmed the bone morphogenic protein-1 (BMP-1) mediated cleavage site on the N-terminus of endorepellin LG3 fragment. This finding suggests that the LG3 fragment is specifically released by a BMP-1 driven limited proteolytic process. The protein was also detected in plasma by Western blot analysis and selected reaction monitoring (SRM). The plasma level of the endorepellin LG3 fragment was significantly lower in breast cancer patients compared to healthy donors (p = 0.017; n = 12). The LG3 protein concentration in the control plasma was measured at approximately 3.7 pmol/mL compared to 1.8 pmol/mL in plasma from the cancer patients. We suggest that these results support the potential use of the endorepellin LG3 fragment as a new serological biomarker for breast cancer.

Mycobacterium sp. strain THO100 and Rhodococcus sp. strain TM1 were isolated from a morpholine-containing enrichment culture of activated sewage sludge. Strain THO100, but not strain TM1, was able to degrade alicyclic amines such as morpholine, piperidine, and pyrrolidine. The mixed strains THO100 and TM1 showed a better growth on piperidine as the substrate than the pure strain THO100 because strain TM1 was able to reduce the level of glutaraldehyde (GA) produced during piperidine degradation. GA was toxic to strain THO100 (IC(50) = 28.3 microM) but less toxic to strain TM1 (IC(50) = 215 microM). Strain THO100 possessed constitutive semialdehyde dehydrogenases, namely Sad1 and Sad2, whose activities toward succinic semialdehyde (SSA) were strongly inhibited by GA. The two isozymes were identified as catalase-peroxidase (KatG = Sad1) and semialdehyde dehydrogenase (Sad2) based on mass spectrometric analyses of tryptic peptides and database searches of the partial DNA sequences of their genes. In contrast, strain TM1 containing another constitutive enzyme Gad1 could oxidize both SSA and GA. This study suggested that strain TM1 possessing Gad1 played a synergistic role in reducing the toxic and inhibitory effects of GA produced in the degradation of piperidine by strain THO100.

The native form of serine protease inhibitor (serpin) is kinetically trapped in a metastable state. Metastability in these proteins is critical to inhibit target protease by forming a stable covalent complex. Despite recent determination of the crystal structures of a Michaelis protease-serpin complex as well as a stable covalent complex, details on the kinetic mechanism remain unsolved. In this report, we examined the reaction mechanism of alpha1-antitrypsin toward elastase by a combination of stopped-flow experiments via fluorescence resonance energy transfer and rapid-quench studies. The results suggest a non-covalent complex intermediate other than Michaelis complex as an intermediate before the cleavage of P1-P1' scissile bond, whose formation is the rate-determining step of the overall reaction. This rate-limiting step represents rearrangement of the reactive site loop, and is regulated by a salt bridge between E354 and R196. The ionic interaction is unique to alpha1-antitrypsin, which suggests that protease inhibition mechanisms are varied among serpins.

10621 Background: Multiple reaction monitoring-based mass spectrometry (MRM-MS) has the ability to perform a wide range of proteome analysis in a single experiment using a small volume of specimen. We aimed to develop a plasma protein signature for breast cancer diagnosis using the MRM-MS technology. Methods: Previously, we have identified lists of breast cancer-related proteins from various models of proteomic discovery including cancer plasma vs healthy plasma, cancer cell line secretome vs non-tumorigenic cell line secretome, cancer tissue vs normal tissue, and literature search. Based on these protein panels, total of 29 proteins were selected for further experiments. We verified and validated the protein signature in two independent cohorts of breast cancer patients and healthy women. Results: In the verification cohort of 80 breast cancer patients and 80 healthy women, MRM-MS showed significant differences in plasma concentration for 11 proteins. Among them, the difference was not significant for 4 proteins when the cases were limited to stage I and II patients. Based on p values and consistent expression level along the AJCC stages, we have created a plasma protein signature comprised of 3 plasma proteins. The 3 plasma protein signature effectively discriminated cancer and healthy cases with the AUC of 0.831 (sensitivity 78.7%, specificity 78.7%). The performance of the 3 plasma protein signature was validated in the cohort of 100 cancer patients and 100 healthy women. The accuracy of the 3 protein signature was still meaningful with the AUC of 0.746 and 0.797 for all stages and stage I or II patients, respectively. Conclusions: The 3 plasma protein signature for breast cancer diagnosis, developed by the MRM-MS technology, showed promising results in the present study.