Novel Diagnostic Biomarkers for High-Grade Serous Ovarian Cancer Uncovered by Data-Independent Acquisition Mass Spectrometry.

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 ß 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).

The Possible Role of Neurobeachin in Extinction of Contextual Fear Memory.

Established fear memory becomes vulnerable to disruption after memory retrieval and extinction; this labile state is critical for inhibiting the return of fear memory. However, the labile state has a very narrow time window after retrieval, and underlying molecular mechanisms are not well known. To that end, we isolated the hippocampus immediately after fear memory retrieval and performed proteomics. We identified Neurobeachin (NBEA), an autism-related regulator of synaptic protein trafficking, to be upregulated after contextual fear memory retrieval. NBEA protein expression was rapid and transient after fear memory retrieval at the synapse. Nbea mRNA was enriched at the synapses, and the rapid induction of NBEA expression was blocked by inhibition of the mammalian target of rapamycin (mTOR)-dependent signaling pathway. Mice with cornu ammonis 1 (CA1)-specific Nbea shRNA knockdown showed normal fear acquisition and contextual fear memory but impaired extinction, suggesting an important role of Nbea in fear memory extinction processes. Consistently, Nbea heterozygotes showed normal fear acquisition and fear memory recall but showed impairment in extinction. Our data suggest that NBEA is necessary either for induction of memory lability or for the physiological process of memory extinction.

Both targeted mass spectrometry and flow sorting analysis methods detected the decreased serum apolipoprotein E level in Alzheimer's disease patients.

Apolipoprotein E (ApoE) polymorphism has been appreciated as a valuable predictor of Alzheimer disease (AD), and the associated ε4 allele has been recognized as an indicator of susceptibility to this disease. However, serum ApoE levels have been a controversial issue in AD, due to the great variability regarding the different target detection methods, ethnicity, and the geographic variations of cohorts. The aim of this study was to validate serum ApoE levels in relation to AD, particularly using two distinct detection methods, liquid chromatography-selected reaction monitoring (SRM) mass spectrometry and microsphere-based fluorescence-activated cell sorting (FACS) analysis, to overcome experimental variations. Also, comparison of serum ApoE levels was performed between the level of protein detection by FACS and peptide level by SRM in both control and AD patients. Results from the two detection methods were cross-confirmed and validated. Both methods produced fairly consistent results, showing a significant decrease of serum ApoE levels in AD patients relative to those of a control cohort (43 control versus 45 AD, p < 0.0001). Significant correlation has been revealed between results from FACS and SRM (p < 0.0001) even though lower serum ApoE concentration values were measured in protein by FACS analysis than in peptide-level detections by SRM. Correlation study suggested that a decrease of the serum ApoE level in AD is related to the mini-mental state exam score in both results from different experimental methods, but it failed to show consistent correlation with age, gender, or clinical dementia rating.

Demonstrating the feasibility of large-scale development of standardized assays to quantify human proteins.

Multiple reaction monitoring (MRM) mass spectrometry has been successfully applied to monitor targeted proteins in biological specimens, raising the possibility that assays could be configured to measure all human proteins. We report the results of a pilot study designed to test the feasibility of a large-scale, international effort for MRM assay generation. We have configured, validated across three laboratories and made publicly available as a resource to the community 645 novel MRM assays representing 319 proteins expressed in human breast cancer. Assays were multiplexed in groups of >150 peptides and deployed to quantify endogenous analytes in a panel of breast cancer-related cell lines. The median assay precision was 5.4%, with high interlaboratory correlation (R(2) > 0.96). Peptide measurements in breast cancer cell lines were able to discriminate among molecular subtypes and identify genome-driven changes in the cancer proteome. These results establish the feasibility of a large-scale effort to develop an MRM assay resource.

Multiple reaction monitoring of multiple low-abundance transcription factors in whole lung cancer cell lysates.

Lung cancer-related transcription factors (TFs) were identified by integrating previously reported genomic, transcriptomic, and proteomic data and were quantified by multiple reaction monitoring (MRM) in various cell lines. All experiments were performed without affinity depletion or subfractionation of cell lysates. Since the target proteins were expected to be present in low abundance, we experimentally optimized MRM transition parameters with chemically synthesized peptides. Quantitation was based on stable isotope-labeled standard peptides (SIS peptides). Out of 288 MRM measurements (36 peptides representing 28 TFs × 8 cell lines), 241 were successfully obtained within a quantitation limit of 15 amol, 221 measurements (91.7%) showed coefficients of variation (CVs) of ≤ 20%, and 149 (61.8%) showed CVs of ≤ 10%, quantifying as low as 19.4 amol/µg protein for STAT2 with a CV of 6.3% in an A549 cell. Comparisons between MRM measurements and levels of the corresponding mRNAs revealed linear, nonlinear, or no relationship between protein and mRNA levels, indicating the need for an MRM assay. An integrative analysis of MRM and gene expression profiles from doxorubicin-resistant H69AR and sensitive H69 cells further showed that 14 differentially expressed TFs, such as STAT1 and SMAD4, regulated genes associated with drug resistance and cell differentiation-related processes. Thus, the analytical performance of MRM for the quantitation of low abundance TFs suggests its usefulness for biological application.

A systems approach for decoding mitochondrial retrograde signaling pathways.

Mitochondrial dysfunctions activate retrograde signaling from mitochondria to the nucleus. To identify transcription factors and their associated pathways that underlie mitochondrial retrograde signaling, we performed gene expression profiling of the cells engineered to have varying amounts of mitochondrial DNA with an A3243G mutation (mt3243) in the leucine transfer RNA (tRNA(Leu)), which reduces the abundance of proteins involved in oxidative phosphorylation that are encoded by the mitochondrial genome. The cells with the mutation exhibited reduced mitochondrial function, including compromised oxidative phosphorylation, which would activate diverse mitochondrial retrograde signaling pathways. By analyzing the gene expression profiles in cells with the mutant tRNA(Leu) and the transcription factors that recognize the differentially regulated genes, we identified 72 transcription factors that were potentially involved in mitochondrial retrograde signaling. We experimentally validated that the mt3243 mutation induced a retrograde signaling pathway involving RXRA (retinoid X receptor α), reactive oxygen species, kinase JNK (c-JUN N-terminal kinase), and transcriptional coactivator PGC1α (peroxisome proliferator-activated receptor γ, coactivator 1 α). This RXR pathway contributed to the decrease in mRNA abundances of oxidative phosphorylation enzymes encoded in the nuclear genome, thereby aggravating the dysfunction in oxidative phosphorylation caused by the reduced abundance of mitochondria-encoded enzymes of oxidative phosphorylation. Thus, matching transcription factors to differentially regulated gene expression profiles was an effective approach to understand mitochondrial retrograde signaling pathways and their roles in mitochondrial dysfunction.

2-nitrobenzoate 2-nitroreductase (NbaA) switches its substrate specificity from 2-nitrobenzoic acid to 2,4-dinitrobenzoic acid under oxidizing conditions.

2-Nitrobenzoate 2-nitroreductase (NbaA) of Pseudomonas fluorescens strain KU-7 is a unique enzyme, transforming 2-nitrobenzoic acid (2-NBA) and 2,4-dinitrobenzoic acid (2,4-DNBA) to the 2-hydroxylamine compounds. Sequence comparison reveals that NbaA contains a conserved cysteine residue at position 141 and two variable regions at amino acids 65 to 74 and 193 to 216. The truncated mutant Δ65-74 exhibited markedly reduced activity toward 2,4-DNBA, but its 2-NBA reduction activity was unaffected; however, both activities were abolished in the Δ193-216 mutant, suggesting that these regions are necessary for the catalysis and specificity of NbaA. NbaA showed different lag times for the reduction of 2-NBA and 2,4-DNBA with NADPH, and the reduction of 2,4-DNBA, but not 2-NBA, failed in the presence of 1 mM dithiothreitol or under anaerobic conditions, indicating oxidative modification of the enzyme for 2,4-DNBA. The enzyme was irreversibly inhibited by 5,5'-dithio-bis-(2-nitrobenzoic acid) and ZnCl(2), which bind to reactive thiol/thiolate groups, and was eventually inactivated during the formation of higher-order oligomers at high pH, high temperature, or in the presence of H(2)O(2). SDS-PAGE and mass spectrometry revealed the formation of intermolecular disulfide bonds by involvement of the two cysteines at positions 141 and 194. Site-directed mutagenesis indicated that the cysteines at positions 39, 103, 141, and 194 played a role in changing the enzyme activity and specificity toward 2-NBA and 2,4-DNBA. This study suggests that oxidative modifications of NbaA are responsible for the differential specificity for the two substrates and further enzyme inactivation through the formation of disulfide bonds under oxidizing conditions.

Overexpression of reactive cysteine-containing 2-nitrobenzoate nitroreductase (NbaA) and its mutants alters the sensitivity of Escherichia coli to reactive oxygen species by reprogramming a regulatory network of disulfide-bonded proteins.

The effects of redox-sensitive proteins on Escherichia coli were investigated by overexpressing Pseudomonas 2-nitrobenzoate nitroreductase (NbaA) and its mutants. Overexpression of wild-type and mutant NbaA proteins significantly altered the sensitivity of E. coli to antibiotics and reactive oxygen species regardless of the enzyme activity for reduction of 2-nitrobenzoic acid. The overexpressed proteins rendered cells 100-10000-fold more sensitive to superoxide anion (O2(•-))-generating paraquat and 10-100-fold more resistant to H2O2. A significant increase in intracellular levels of O2(•-), but not H2O2, was observed during expression of wild-type and truncated (Δ65-74, Δ193-216, and Δ65-74Δ193-216) NbaA. From two-dimensional nonreducing/reducing sodium dodecyl sulfate-polyacrylamide gel electrophoresis and mass spectrometry analyses, 29 abundant proteins in the cytoplasm were identified to form interchain disulfide bonds, when cells were exposed to polymyxin B. Of them, down-regulation and modifications of SodB, KatE, and KatG were strongly associated with elevated cellular O2(•-) levels. Western blotting showed up-regulation of cell death signal sensor, CpxA, and down-regulation of cytoplasmic superoxide dismutase, SodB, with ∼2-fold up-regulation of heterodimeric integration host factor, Ihf. Activity gel assays revealed significant reduction of glyceraldehyde-3-phosphate dehydrogenase with constant levels of 6-phosphogluconate dehydrogenase. These changes would support a high level of NADPH to reduce H2O2-induced disulfide bonds by forced expression of thioredoxin A via thioredoxin reductase. Thus, overexpression of wild-type and truncated NbaA partially compensates for the lack of KatE and KatG to degrade H2O2, thereby enhancing disulfide bond formation in the cytoplasm, and modifies a regulatory network of disulfide-bonded proteins to increase intracellular O2(•-) levels.

Novel ß-structure of YLR301w from Saccharomyces cerevisiae.

When the Z-type variant of human α(1)-antitrypsin was overexpressed in Saccharomyces cerevisiae, proteomics analysis identified YLR301w as one of the up-regulated proteins. YLR301w is a 27.5 kDa protein with no sequence homology to any known protein and has been reported to interact with Sec72 and Hrr25. The crystal structure of S. cerevisiae YLR301w has been determined at 2.3 Å resolution, revealing a novel ß-structure. It consists of an N-terminal ten-stranded ß-barrel with two short α-helices connected by a 23-residue linker to a seven-stranded half-barrel with two short helices at the C-terminus. The N-terminal barrel has a highly conserved hydrophobic channel that can bind hydrophobic molecules such as PEG. It forms a homodimer both in the crystal and in solution. YLR301w binds Sec72 with a K(d) of 6.2 µM, but the biological significance of this binding requires further investigation.

Profiling of differentially expressed proteins in stage IV colorectal cancers with good and poor outcomes.

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.

Proteomic approach reveals FKBP4 and S100A9 as potential prediction markers of therapeutic response to neoadjuvant chemotherapy in patients with breast cancer.

Although doxorubicin (Doxo) and docetaxel (Docet) in combination are widely used in treatment regimens for a broad spectrum of breast cancer patients, a major obstacle has emerged in that some patients are intrinsically resistant to these chemotherapeutics. Our study aimed to discover potential prediction markers of drug resistance in needle-biopsied tissues of breast cancer patients prior to neoadjuvant chemotherapy. Tissues collected before chemotherapy were analyzed by mass spectrometry. A total of 2,331 proteins were identified and comparatively quantified between drug sensitive (DS) and drug resistant (DR) patient groups by spectral count. Of them, 298 proteins were differentially expressed by more than 1.5-fold. Some of the differentially expressed proteins (DEPs) were further confirmed by Western blotting. Bioinformatic analysis revealed that the DEPs were largely associated with drug metabolism, acute phase response signaling, and fatty acid elongation in mitochondria. Clinical validation of two selected proteins by immunohistochemistry found that FKBP4 and S100A9 might be putative prediction markers in discriminating the DR group from the DS group of breast cancer patients. The results demonstrate that a quantitative proteomics/bioinformatics approach is useful for discovering prediction markers of drug resistance, and possibly for the development of a new therapeutic strategy.

Network clustering revealed the systemic alterations of mitochondrial protein expression.

The mitochondrial protein repertoire varies depending on the cellular state. Protein component modifications caused by mitochondrial DNA (mtDNA) depletion are related to a wide range of human diseases; however, little is known about how nuclear-encoded mitochondrial proteins (mt proteome) changes under such dysfunctional states. In this study, we investigated the systemic alterations of mtDNA-depleted (ρ(0)) mitochondria by using network analysis of gene expression data. By modularizing the quantified proteomics data into protein functional networks, systemic properties of mitochondrial dysfunction were analyzed. We discovered that up-regulated and down-regulated proteins were organized into two predominant subnetworks that exhibited distinct biological processes. The down-regulated network modules are involved in typical mitochondrial functions, while up-regulated proteins are responsible for mtDNA repair and regulation of mt protein expression and transport. Furthermore, comparisons of proteome and transcriptome data revealed that ρ(0) cells attempted to compensate for mtDNA depletion by modulating the coordinated expression/transport of mt proteins. Our results demonstrate that mt protein composition changed to remodel the functional organization of mitochondrial protein networks in response to dysfunctional cellular states. Human mt protein functional networks provide a framework for understanding how cells respond to mitochondrial dysfunctions.

A serum protein profile predictive of the resistance to neoadjuvant chemotherapy in advanced breast cancers.

Prediction of the responses to neoadjuvant chemotherapy (NACT) can improve the treatment of patients with advanced breast cancer. Genes and proteins predictive of chemoresistance have been extensively studied in breast cancer tissues. However, noninvasive serum biomarkers capable of such prediction have been rarely exploited. Here, we performed profiling of N-glycosylated proteins in serum from fifteen advanced breast cancer patients (ten patients sensitive to and five patients resistant to NACT) to discover serum biomarkers of chemoresistance using a label-free liquid chromatography-tandem MS method. By performing a series of statistical analyses of the proteomic data, we selected thirteen biomarker candidates and tested their differential serum levels by Western blotting in 13 independent samples (eight patients sensitive to and five patients resistant to NACT). Among the candidates, we then selected the final set of six potential serum biomarkers (AHSG, APOB, C3, C9, CP, and ORM1) whose differential expression was confirmed in the independent samples. Finally, we demonstrated that a multivariate classification model using the six proteins could predict responses to NACT and further predict relapse-free survival of patients. In summary, global N-glycoproteome profile in serum revealed a protein pattern predictive of the responses to NACT, which can be further validated in large clinical studies.

Gcn4p-mediated transcriptional repression of ribosomal protein genes under amino-acid starvation.

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.

Integrated post-experiment monoisotopic mass refinement: an integrated approach to accurately assign monoisotopic precursor masses to tandem mass spectrometric data.

Accurate assignment of monoisotopic precursor masses to tandem mass spectrometric (MS/MS) data is a fundamental and critically important step for successful peptide identifications in mass spectrometry based proteomics. Here we describe an integrated approach that combines three previously reported methods of treating MS/MS data for precursor mass refinement. This combined method, "integrated post-experiment monoisotopic mass refinement" (iPE-MMR), integrates steps (1) generation of refined MS/MS data by DeconMSn; (2) additional refinement of the resultant MS/MS data by a modified version of PE-MMR; and (3) elimination of systematic errors of precursor masses using DtaRefinery. iPE-MMR is the first method that utilizes all MS information from multiple MS scans of a precursor ion including multiple charge states, in an MS scan, to determine precursor mass. With the combination of these methods, iPE-MMR increases sensitivity in peptide identification and provides increased accuracy when applied to complex high-throughput proteomics data.

A proteomic approach based on multiple parallel separation for the unambiguous identification of an antibody cognate antigen.

Autoantibodies obtained from cancer patients have been identified as useful tools for cancer diagnostics, prognostics, and as potential targets for immunotherapy. Serological proteome analysis in combination with 2-DE is a classic strategy for identification of tumor-associated antigens in the serum of cancer patients. However, serological proteome analysis cannot always indicate the true antigen out of a complex proteome identified from a single protein spot because the most abundant protein is not always the most antigenic. To address this problem, we utilized multiple parallel separation (MPS) for proteome separation. The common identities present in the fractions obtained using different separation methods were regarded as the true antigens. The merit of our MPS technique was validated using anti-ARPC2 and anti-PTEN antibodies. Next, we applied the MPS technique for the identification of glycyl-tRNA synthetase as the cognate antigen for an autoantibody that was overexpressed in the plasma of breast cancer patients. These results reveal that MPS can unambiguously identify an antibody cognate antigen by reducing false-positives. Therefore, MPS could be used for the characterization of diagnostic antibodies raised in laboratory animals as well as autoantibodies isolated from diseased patients.

Differential profiling of breast cancer plasma proteome by isotope-coded affinity tagging method reveals biotinidase as a breast cancer biomarker.

BACKGROUND: Breast cancer is one of the leading causes of women's death worldwide. It is important to discover a reliable biomarker for the detection of breast cancer. Plasma is the most ideal source for cancer biomarker discovery since many cells cross-communicate through the secretion of soluble proteins into blood. METHODS: Plasma proteomes obtained from 6 breast cancer patients and 6 normal healthy women were analyzed by using the isotope-coded affinity tag (ICAT) labeling approach and tandem mass spectrometry. All the plasma samples used were depleted of highly abundant 6 plasma proteins by immune-affinity column chromatography before ICAT labeling. Several proteins showing differential abundance level were selected based on literature searches and their specificity to the commercially available antibodies, and then verified by immunoblot assays. RESULTS: A total of 155 proteins were identified and quantified by ICAT method. Among them, 33 proteins showed abundance changes by more than 1.5-fold between the plasmas of breast cancer patients and healthy women. We chose 5 proteins for the follow-up confirmation in the individual plasma samples using immunoblot assay. Four proteins, alpha1-acid glycoprotein 2, monocyte differentiation antigen CD14, biotinidase (BTD), and glutathione peroxidase 3, showed similar abundance ratio to ICAT result. Using a blind set of plasmas obtained from 21 breast cancer patients and 21 normal healthy controls, we confirmed that BTD was significantly down-regulated in breast cancer plasma (Wilcoxon rank-sum test, p = 0.002). BTD levels were lowered in all cancer grades (I-IV) except cancer grade zero. The area under the receiver operating characteristic curve of BTD was 0.78. Estrogen receptor status (p = 0.940) and progesterone receptor status (p = 0.440) were not associated with the plasma BTD levels. CONCLUSIONS: Our study suggests that BTD is a potential serological biomarker for the detection of breast cancer.

Decolorization of malachite green by cytochrome c in the mitochondria of the fungus Cunninghamella elegans.

We studied the decolorization of malachite green (MG) by the fungus Cunninghamella elegans. The mitochondrial activity for MG reduction was increased with a simultaneous increase of a 9-kDa protein, called CeCyt. The presence of cytochrome c in CeCyt protein was determined by optical absorbance spectroscopy with an extinction coefficient (E(550-535)) of 19.7+/-6.3 mM(-1) cm(-1) and reduction potential of + 261 mV. When purified CeCyt was added into the mitochondria, the specific activity of CeCyt reached 440 +/- 122 micromol min(-1) mg(-1) protein. The inhibition of MG reduction by stigmatellin, but not by antimycin A, indicated a possible linkage of CeCyt activity to the Qo site of the bc1 complex. The RT-PCR results showed tight regulation of the cecyt gene expression by reactive oxygen species. We suggest that CeCyt acts as a protein reductant for MG under oxidative stress in a stationary or secondary growth stage of this fungus.

Multiple products monitoring as a robust approach for peptide quantification.

Quantification of target peptides and proteins is crucial for biomarker discovery. Approaches such as selected reaction monitoring (SRM) and multiple reaction monitoring (MRM) rely on liquid chromatography and mass spectrometric analysis of defined peptide product ions. These methods are not very widespread because the determination of quantifiable product ion using either SRM or MRM is a very time-consuming process. We developed a novel approach for quantifying target peptides without such an arduous process of ion selection. This method is based on monitoring multiple product ions (multiple products monitoring: MpM) from full-range MS2 spectra of a target precursor. The MpM method uses a scoring system that considers both the absolute intensities of product ions and the similarities between the query MS2 spectrum and the reference MS2 spectrum of the target peptide. Compared with conventional approaches, MpM greatly improves sensitivity and selectivity of peptide quantification using an ion-trap mass spectrometer.