Comparative profiling by data-independent acquisition mass spectrometry reveals featured plasma proteins in breast cancer: a pilot study.

Purpose: Breast cancer is known to be influenced by genetic and environmental factors, and several susceptibility genes have been discovered. Still, the majority of genetic contributors remain unknown. We aimed to analyze the plasma proteome of breast cancer patients in comparison to healthy individuals to identify differences in protein expression profiles and discover novel biomarkers. Methods: This pilot study was conducted using bioresources from Seoul National University Bundang Hospital's Human Bioresource Center. Serum samples from 10 breast cancer patients and 10 healthy controls were obtained. Liquid chromatography-mass spectrometry analysis was performed to identify differentially expressed proteins. Results: We identified 891 proteins; 805 were expressed in the breast cancer group and 882 in the control group. Gene set enrichment and differential expression analysis identified 30 upregulated and 100 downregulated proteins in breast cancer. Among these, 10 proteins were selected as potential biomarkers. Three proteins were upregulated in breast cancer patients, including cluster of differentiation 44, eukaryotic translation initiation factor 2-α kinase 3, and fibronectin 1. Seven proteins downregulated in breast cancer patients were also selected: glyceraldehyde-3-phosphate dehydrogenase, α-enolase, heat shock protein member 8, integrin-linked kinase, tissue inhibitor of metalloproteinases-1, vasodilator-stimulated phosphoprotein, and 14-3-3 protein gamma. All proteins had been previously reported to be related to tumor development and progression. Conclusion: The findings suggest that plasma proteome profiling can reveal potential diagnostic biomarkers for breast cancer and may contribute to early detection and personalized treatment strategies. A further validation study with a larger sample cohort of breast cancer patients is planned.

Association Between the C4 Binding Protein Level and White Matter Integrity in Major Depressive Disorder.

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.

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).

Proteomic Interrogation in Cancer Biomarker.

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.

Nogo-A regulates myogenesis via interacting with Filamin-C.

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.

Erratum: A Validation Study of a Multiple Reaction Monitoring-Based Proteomic Assay to Diagnose Breast Cancer.

[This corrects the article on p. 579 in vol. 22, PMID: 31897331.].

Common Repository of FBS Proteins (cRFP) To Be Added to a Search Database for Mass Spectrometric Analysis of Cell Secretome.

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.

A Validation Study of a Multiple Reaction Monitoring-Based Proteomic Assay to Diagnose Breast Cancer.

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.

Interrogating the hidden phosphoproteome.

Postgenomic 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. The use of this approach with multidimensional fractionation in mammalian cells yielded more than 7000 unique cys-phosphopeptide sequences, comprising 15-20% novel phosphorylation sites. The use of our approach in combination with pharmacologic inhibitors of the mechanistic target of rapamycin complex 1 and 2 identified several putatively novel protein substrates for the mechanistic target of rapamycin kinase.

Leucine-rich repeat kinase 2 and Parkinson's disease.

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.

Direct Analysis of Phosphorylation Sites on the Rpb1 C-Terminal Domain of RNA Polymerase II.

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."

Development and Validation of a Novel Plasma Protein Signature for Breast Cancer Diagnosis by Using Multiple Reaction Monitoring-based Mass Spectrometry.

AIM: We aimed to develop a plasma protein signature for breast cancer diagnosis by using multiple reaction monitoring (MRM)-based mass spectrometry. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSION: 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.

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.

Expression profiling of more than 3500 proteins of MSS-type colorectal cancer by stable isotope labeling and mass spectrometry.

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/ß-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.

Comparative profiling of plasma proteome from breast cancer patients reveals thrombospondin-1 and BRWD3 as serological biomarkers.

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.

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.

Analysis of nuclear high mobility group box 1 (HMGB1)-binding proteins in colon cancer cells: clustering with proteins involved in secretion and extranuclear function.

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.

Quantitative analysis of mTRAQ-labeled proteome using full MS scans.

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.

Improved quantitative analysis of mass spectrometry using quadratic equations.

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.

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.