Nitroproteins in Human Astrocytomas Discovered by Gel Electrophoresis and Tandem Mass Spectrometry

Mass spectrometry analysis of phosphotyrosine-containing proteins

Tyrosine phosphorylation is a crucial posttranslational modification that is involved in various aspects of cell biology and often has functions in cancers. It is necessary not only to identify the specific phosphorylation sites but also to quantify their phosphorylation levels under specific pathophysiological conditions. Because of its high sensitivity and accuracy, mass spectrometry (MS) has been widely used to identify endogenous and synthetic phosphotyrosine proteins/peptides across a range of biological systems. However, phosphotyrosine-containing proteins occur in extremely low abundance and they degrade easily, severely challenging the application of MS. This review highlights the advances in both quantitative analysis procedures and enrichment approaches to tyrosine phosphorylation before MS analysis and reviews the differences among phosphorylation, sulfation, and nitration of tyrosine residues in proteins. In-depth insights into tyrosine phosphorylation in a wide variety of biological systems will offer a deep understanding of how signal transduction regulates cellular physiology and the development of tyrosine phosphorylation-related drugs as cancer therapeutics.

Clinical-Molecular characteristics and Post-Translational modifications of colorectal cancer in north China: Implications for future targeted therapies

This study delineated the elucidate molecular changes and their post-translational modifications (PTMs) in heterogenetic colorectal cancer (CRC) for a deeper understanding of the CRC pathophysiology and identifying potential therapeutic targets. In this retrospective study, the profiles of 13 hot spot gene mutations were analyzed and the microsatellite instability (MSI) status was determined.Employing the Circulating Single-Molecule Amplification and Resequencing Technology (cSMART) assay, the clinical-pathological features of CRC were characterized in 249 Chinese patients. PTMs were quantified online.Among the patients with CRC, the mutation frequencies of KRAS, NRAS, BRAF, PIK3CA, TP53, and APC genes were 47.8%, 3.6%, 4.8%, 13.7%, 55.8%, and 36.9%, respectively. The proportion of MSI-high (MSI-H) was 7.8%.Subsequent multiple logistic regression analysis showed significant associations including a link between lung metastasis and KRAS mutation, between liver metastasis and lymph node metastasis, between MSI-H and early-onset CRC (EOCRC) and KRAS mutation, between right-sided colon cancer and peritoneal metastasis, and between PIK3CA mutation and PTEN mutation. Patients with KRAS mutation presented with MSI-H, lung metastasis, and PIK3CA mutation. MSI-H, BRAF mutation, and PTEN mutation were more frequent in EOCRC. Phosphorylation and ubiquitylation were found in KRAS, BRAF, PTEN, and SMAD4; SUMOylation and ubiquitylation were observed in HRAS and NRAS; while phosphorylation was obvious in APC, P53, and MLH1. Notably, Phosphorylation and ubiquitylation were the two most common PTMs. The biological characteristics of CRC in Chinese patients have some unique clinical features, which can be explained by the genetic mutation profile, correlations among gene mutations and clinical characteristics. These distinctions set the Chinese patient population apart from their Western counterparts.

Uncommon posttranslational modifications in proteomics: ADP-ribosylation, tyrosine nitration, and tyrosine sulfation

Posttranslational modifications (PTMs) are covalent modifications of proteins that modulate the structure and functions of proteins and regulate biological processes. The development of various mass spectrometry-based proteomics workflows has facilitated the identification of hundreds of PTMs and aided the understanding of biological significance in a high throughput manner. Improvements in sample preparation and PTM enrichment techniques, instrumentation for liquid chromatography-tandem mass spectrometry (LC-MS/MS), and advanced data analysis tools enhance the specificity and sensitivity of PTM identification. Highly prevalent PTMs like phosphorylation, glycosylation, acetylation, ubiquitinylation, and methylation are extensively studied. However, the functions and impact of less abundant PTMs are not as well understood and underscore the need for analytical methods that aim to characterize these PTMs. This review focuses on the advancement and analytical challenges associated with the characterization of three less common but biologically relevant PTMs, specifically, adenosine diphosphate-ribosylation, tyrosine sulfation, and tyrosine nitration. The advantages and disadvantages of various enrichment, separation, and MS/MS techniques utilized to identify and localize these PTMs are described.

The use of mass spectrometry in a proteome-centered multiomics study of human pituitary adenomas

A pituitary adenoma (PA) is a common intracranial neoplasm, and is a complex, chronic, and whole-body disease with multicausing factors, multiprocesses, and multiconsequences. It is very difficult to clarify molecular mechanism and treat PAs from the single-factor strategy model. The rapid development of multiomics and systems biology changed the paradigms from a traditional single-factor strategy to a multiparameter systematic strategy for effective management of PAs. A series of molecular alterations at the genome, transcriptome, proteome, peptidome, metabolome, and radiome levels are involved in pituitary tumorigenesis, and mutually associate into a complex molecular network system. Also, the center of multiomics is moving from structural genomics to phenomics, including proteomics and metabolomics in the medical sciences. Mass spectrometry (MS) has been extensively used in phenomics studies of human PAs to clarify molecular mechanisms, and to discover biomarkers and therapeutic targets/drugs. MS-based proteomics and proteoform studies play central roles in the multiomics strategy of PAs. This article reviews the status of multiomics, multiomics-based molecular pathway networks, molecular pathway network-based pattern biomarkers and therapeutic targets/drugs, and future perspectives for personalized, predeictive, and preventive (3P) medicine in PAs.

HSP60 Regulates Lipid Metabolism in Human Ovarian Cancer

Accumulating evidence demonstrates that cancer is an oxidative stress-related disease, and oxidative stress is closely linked with heat shock proteins (HSPs). Lipid oxidative stress is derived from lipid metabolism dysregulation that is closely associated with the development and progression of malignancies. This study sought to investigate regulatory roles of HSPs in fatty acid metabolism abnormality in ovarian cancer. Pathway network analysis of 5115 mitochondrial expressed proteins in ovarian cancer revealed various lipid metabolism pathway alterations, including fatty acid degradation, fatty acid metabolism, butanoate metabolism, and propanoate metabolism. HSP60 regulated the expressions of lipid metabolism proteins in these lipid metabolism pathways, including ADH5, ECHS1, EHHADH, HIBCH, SREBP1, ACC1, and ALDH2. Further, interfering HSP60 expression inhibited migration, proliferation, and cell cycle and induced apoptosis of ovarian cancer cells in vitro. In addition, mitochondrial phosphoproteomics and immunoprecipitation-western blot experiments identified and confirmed that phosphorylation occurred at residue Ser70 in protein HSP60, which might regulate protein folding of ALDH2 and ACADS in ovarian cancers. These findings clearly demonstrated that lipid metabolism abnormality occurred in oxidative stress-related ovarian cancer and that HSP60 and its phosphorylation might regulate this lipid metabolism abnormality in ovarian cancer. It opens a novel vision in the lipid metabolism reprogramming in human ovarian cancer.

PredNTS: Improved and Robust Prediction of Nitrotyrosine Sites by Integrating Multiple Sequence Features

Nitrotyrosine, which is generated by numerous reactive nitrogen species, is a type of protein post-translational modification. Identification of site-specific nitration modification on tyrosine is a prerequisite to understanding the molecular function of nitrated proteins. Thanks to the progress of machine learning, computational prediction can play a vital role before the biological experimentation. Herein, we developed a computational predictor PredNTS by integrating multiple sequence features including K-mer, composition of k-spaced amino acid pairs (CKSAAP), AAindex, and binary encoding schemes. The important features were selected by the recursive feature elimination approach using a random forest classifier. Finally, we linearly combined the successive random forest (RF) probability scores generated by the different, single encoding-employing RF models. The resultant PredNTS predictor achieved an area under a curve (AUC) of 0.910 using five-fold cross validation. It outperformed the existing predictors on a comprehensive and independent dataset. Furthermore, we investigated several machine learning algorithms to demonstrate the superiority of the employed RF algorithm. The PredNTS is a useful computational resource for the prediction of nitrotyrosine sites. The web-application with the curated datasets of the PredNTS is publicly available.

Mass spectrometry-based proteomics analyses of post-translational modifications and proteoforms in human pituitary adenomas

Pituitary adenoma (PA) is a common intracranial neoplasm, which affects the hypothalamus-pituitary-target organ axis systems, and is hazardous to human health. Post-translational modifications (PTMs), including phosphorylation, ubiquitination, nitration, and sumoylation, are vitally important in the PA pathogenesis. The large-scale analysis of PTMs could provide a global view of molecular mechanisms for PA. Proteoforms, which are used to define various protein structural and functional forms originated from the same gene, are the future direction of proteomics research. The global studies of different proteoforms and PTMs of hypophyseal hormones such as growth hormone (GH) and prolactin (PRL) and the proportion change of different GH proteoforms or PRL proteoforms in human pituitary tissue could provide new insights into the clinical value of pituitary hormones in PAs. Multiple quantitative proteomics methods, including mass spectrometry (MS)-based label-free and stable isotope-labeled strategies in combination with different PTM-peptide enrichment methods such as TiO₂ enrichment of tryptic phosphopeptides and antibody enrichment of other PTM-peptides increase the feasibility for researchers to study PA proteomes. This article reviews the research status of PTMs and proteoforms in PAs, including the enrichment method, technical limitation, quantitative proteomics strategies, and the future perspectives, to achieve the goals of in-depth understanding its molecular pathogenesis, and discovering effective biomarkers and clinical therapeutic targets for predictive, preventive, and personalized treatment of PA patients.

The challenge of detecting modifications on proteins

Post-translational modifications (PTMs) are integral to the regulation of protein function, characterising their role in this process is vital to understanding how cells work in both healthy and diseased states. Mass spectrometry (MS) facilitates the mass determination and sequencing of peptides, and thereby also the detection of site-specific PTMs. However, numerous challenges in this field continue to persist. The diverse chemical properties, low abundance, labile nature and instability of many PTMs, in combination with the more practical issues of compatibility with MS and bioinformatics challenges, contribute to the arduous nature of their analysis. In this review, we present an overview of the established MS-based approaches for analysing PTMs and the common complications associated with their investigation, including examples of specific challenges focusing on phosphorylation, lysine acetylation and redox modifications.

MASS SPECTROMETRY-BASED MITOCHONDRIAL PROTEOMICS IN HUMAN OVARIAN CANCERS

The prominent characteristics of mitochondria are highly dynamic and regulatory, which have crucial roles in cell metabolism, biosynthetic, senescence, apoptosis, and signaling pathways. Mitochondrial dysfunction might lead to multiple serious diseases, including cancer. Therefore, identification of mitochondrial proteins in cancer could provide a global view of tumorigenesis and progression. Mass spectrometry-based quantitative mitochondrial proteomics fulfils this task by enabling systems-wide, accurate, and quantitative analysis of mitochondrial protein abundance, and mitochondrial protein posttranslational modifications (PTMs). Multiple quantitative proteomics techniques, including isotope-coded affinity tag, stable isotope labeling with amino acids in cell culture, isobaric tags for relative and absolute quantification, tandem mass tags, and label-free quantification, in combination with different PTM-peptide enrichment methods such as TiO₂ enrichment of tryptic phosphopeptides and antibody enrichment of other PTM-peptides, increase flexibility for researchers to study mitochondrial proteomes. This article reviews isolation and purification of mitochondria, quantitative mitochondrial proteomics, quantitative mitochondrial phosphoproteomics, mitochondrial protein-involved signaling pathway networks, mitochondrial phosphoprotein-involved signaling pathway networks, integration of mitochondrial proteomic and phosphoproteomic data with whole tissue proteomic and transcriptomic data and clinical information in ovarian cancers (OC) to in-depth understand its molecular mechanisms, and discover effective mitochondrial biomarkers and therapeutic targets for predictive, preventive, and personalized treatment of OC. This proof-of-principle model about OC mitochondrial proteomics is easily implementable to other cancer types. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

A database for inventory of proteoform profiles: "2DE-pattern"

The human proteome is composed of a diverse and heterogeneous range of gene products/proteoforms/protein species. Because of the growing amount of information about proteoforms generated by different methods, we need a convenient approach to make an inventory of the data. Here, we present a database of proteoforms that is based on information obtained by separation of proteoforms using 2DE followed by shotgun ESI-LC-MS/MS. The database's principles and structure are described. The database is called "2DE-pattern" as it contains multiple isoform-centric patterns of proteoforms separated according to 2DE principles. The database can be freely used at http://2de-pattern.pnpi.nrcki.ru.

Glioma tumor proteomics: clinically useful protein biomarkers and future perspectives

Introduction: Despite being rare cancers, gliomas account for a significant number of cancer-related deaths. Identification and treatment of these tumors at an early stage would greatly improve the therapeutic outcomes. There is an urgent need for diagnostic and prognostic markers, which can identify disease early and discriminate the subtypes of these tumors thereby improving the existing treatment modalities.Areas covered: In this article, we have reviewed published literature on proteomics biomarkers for gliomas and their importance in diagnosis or prognosis. Proteomic studies for the discovery of protein, autoantibody biomarkers, and biological pathway alterations in serum, CSF and tumor biopsies have been discussed in this review.Expert opinion: The rapid development in the field of mass spectrometry and increased sensitivity and reproducibility in assays has led to the identification and quantification of large number of proteins very precisely. Though genomic markers are the prime focus in the classification of gliomas, incorporating protein markers would further improve the existing classification. In this regard, data mining and studies on large cohorts of glioma patients would help in the identification of diagnostic and prognostic markers ultimately translating to the clinics.

Innovating the Concept and Practice of Two-Dimensional Gel Electrophoresis in the Analysis of Proteomes at the Proteoform Level

Two-dimensional gel electrophoresis (2DE) is an important and well-established technical platform enabling extensive top-down proteomic analysis. However, the long-held but now largely outdated conventional concepts of 2DE have clearly impacted its application to in-depth investigations of proteomes at the level of protein species/proteoforms. It is time to popularize a new concept of 2DE for proteomics. With the development and enrichment of the proteome concept, any given “protein” is now recognized to consist of a series of proteoforms. Thus, it is the proteoform, rather than the canonical protein, that is the basic unit of a proteome, and each proteoform has a specific isoelectric point (pI) and relative mass (M_r). Accordingly, using 2DE, each proteoform can routinely be resolved and arrayed according to its different pI and M_r. Each detectable spot contains multiple proteoforms derived from the same gene, as well as from different genes. Proteoforms derived from the same gene are distributed into different spots in a 2DE pattern. High-resolution 2DE is thus actually an initial level of separation to address proteome complexity and is effectively a pre-fractionation method prior to analysis using mass spectrometry (MS). Furthermore, stable isotope-labeled 2DE coupled with high-sensitivity liquid chromatography-tandem MS (LC-MS/MS) has tremendous potential for the large-scale detection, identification, and quantification of the proteoforms that constitute proteomes.

Quantitative analysis of the human ovarian carcinoma mitochondrial phosphoproteome

To investigate the existence and their potential biological roles of mitochondrial phosphoproteins (mtPPs) in human ovarian carcinoma (OC), mitochondria purified from OC and control tissues were analyzed with TiO₂ enrichment-based iTRAQ quantitative proteomics. Totally 67 mtPPs with 124 phosphorylation sites were identified, which of them included 48 differential mtPPs (mtDPPs). Eighteen mtPPs were reported previously in OCs, and they were consistent in this study compared to previous literature. GO analysis revealed those mtPPs were involved in multiple cellular processes. PPI network indicated that those mtPPs were correlated mutually, and some mtPPs acted as hub molecules, such as EIF2S2, RPLP0, RPLP2, CFL1, MYH10, HSP90, HSPD1, PSMA3, TMX1, VDAC2, VDAC3, TOMM22, and TOMM20. Totally 32 mtPP-pathway systems (p<0.05) were enriched and clustered into 15 groups, including mitophagy, apoptosis, deubiquitination, signaling by VEGF, RHO-GTPase effectors, mitochondrial protein import, translation initiation, RNA transport, cellular responses to stress, and c-MYC transcriptional activation. Totally 29 mtPPs contained a certain protein domains. Upstream regulation analysis showed that TP53, TGFB1, dexamethasone, and thapsigargin might act as inhibitors, and L-dopa and forskolin might act as activators. This study provided novel insights into mitochondrial protein phosphorylations and their potential roles in OC pathogenesis and offered new biomarker resource for OCs.

Detection and quantification of nitric oxide-derived oxidants in biological systems

The free radical nitric oxide (NO^•) exerts biological effects through the direct and reversible interaction with specific targets (e.g. soluble guanylate cyclase) or through the generation of secondary species, many of which can oxidize, nitrosate or nitrate biomolecules. The NO^•-derived reactive species are typically short-lived, and their preferential fates depend on kinetic and compartmentalization aspects. Their detection and quantification are technically challenging. In general, the strategies employed are based either on the detection of relatively stable end products or on the use of synthetic probes, and they are not always selective for a particular species. In this study, we describe the biologically relevant characteristics of the reactive species formed downstream from NO^•, and we discuss the approaches currently available for the analysis of NO^•, nitrogen dioxide (NO₂ ^•), dinitrogen trioxide (N₂O₃), nitroxyl (HNO), and peroxynitrite (ONOO^-/ONOOH), as well as peroxynitrite-derived hydroxyl (HO^•) and carbonate anion (CO₃ ^•-) radicals. We also discuss the biological origins of and analytical tools for detecting nitrite (NO₂ ^-), nitrate (NO₃ ^-), nitrosyl-metal complexes, S-nitrosothiols, and 3-nitrotyrosine. Moreover, we highlight state-of-the-art methods, alert readers to caveats of widely used techniques, and encourage retirement of approaches that have been supplanted by more reliable and selective tools for detecting and measuring NO^•-derived oxidants. We emphasize that the use of appropriate analytical methods needs to be strongly grounded in a chemical and biochemical understanding of the species and mechanistic pathways involved.

Proteomic Advances in Glial Tumors through Mass Spectrometry Approaches

Being the fourth leading cause of cancer-related death, glial tumors are highly diverse tumor entities characterized by important heterogeneity regarding tumor malignancy and prognosis. However, despite the identification of important alterations in the genome of the glial tumors, there remains a gap in understanding the mechanisms involved in glioma malignancy. Previous research focused on decoding the genomic alterations in these tumors, but due to intricate cellular mechanisms, the genomic findings do not correlate with the functional proteins expressed at the cellular level. The development of mass spectrometry (MS) based proteomics allowed researchers to study proteins expressed at the cellular level or in serum that may provide new insights on the proteins involved in the proliferation, invasiveness, metastasis and resistance to therapy in glial tumors. The integration of data provided by genomic and proteomic approaches into clinical practice could allow for the identification of new predictive, diagnostic and prognostic biomarkers that will improve the clinical management of patients with glial tumors. This paper aims to provide an updated review of the recent proteomic findings, possible clinical applications, and future research perspectives in diffuse astrocytic and oligodendroglial tumors, pilocytic astrocytomas, and ependymomas.

The HBx-CTTN interaction promotes cell proliferation and migration of hepatocellular carcinoma via CREB1

Hepatitis B virus-encoded X protein (HBx) acts as a tumor promoter during hepatocellular carcinoma (HCC) development, probably by regulating the expression of host proteins through protein–protein interaction. A proteomics approach was used to identify HBx-interacting proteins involved in HBx-induced hepatocarcinogenesis. We validated the proteomics findings by co-immunoprecipitation and confocal microscopy. We performed cell proliferation, migration assays and cell cycle analyses in HCC cells. Finally, we confirmed the clinical significance of our findings in samples from patients. We found that cortactin (CTTN) is a novel HBx-interacting protein, and HBx regulates the expression of CTTN in the HCC cell lines MHCC-LM3 and HepG2. Mechanistically, by upregulating the expression of cAMP response element-binding protein (CREB1) and its downstream targets, such as cyclin D1 and MMP-9, the effects of the HBx-CTTN interaction on the enhancement of cellular proliferation and migration were maintained by inhibiting cell cycle arrest. In addition, we demonstrated that the levels of CTTN and CREB1 were closely correlated in clinical samples from HBV-infected patients with HCC. Overall, our data suggests that HBx contributes to cell migration and proliferation of HCC cells by interacting with CTTN and regulating the expression of CTTN and CREB1. Therefore, the HBx/CTTN/CREB1 axis is a potential novel therapeutic target in HCC.

Quantitative analysis of the mitochondrial proteome in human ovarian carcinomas

Mitochondria play important roles in growth, signal transduction, division, tumorigenesis and energy metabolism in epithelial ovarian carcinomas (EOCs) without an effective biomarker. To investigate the proteomic profile of EOC mitochondrial proteins, a 6-plex isobaric tag for relative and absolute quantification (iTRAQ) proteomics was used to identify mitochondrial expressed proteins (mtEPs) in EOCs relative to controls, followed by an integrative analysis of the identified mtEPs and the Cancer Genome Atlas (TCGA) data from 419 patients. A total of 5115 quantified proteins were identified from purified mitochondrial samples, and 262 proteins were significantly related to overall survival in EOC patients. Furthermore, 63 proteins were identified as potential biomarkers for the development of an EOC, and our findings were consistent with previous reports on a certain extent. Pathway network analysis identified 70 signaling pathways. Interestingly, the results demonstrated that cancer cells exhibited an increased dependence on mitophagy, such as peroxisome, phagosome, lysosome, valine, leucine and isoleucine degradation and fatty acid degradation pathways, which might play an important role in EOC invasion and metastasis. Five proteins (GLDC, PCK2, IDH2, CPT2 and HMGCS2) located in the mitochondrion and enriched pathways were selected for further analysis in an EOC cell line and tissues, and the results confirmed reliability of iTRAQ proteomics. These findings provide a large-scale mitochondrial proteomic profiling with quantitative information, a certain number of potential protein biomarkers and a novel vision in the mitophagy bio-mechanism of a human ovarian carcinoma.

Prolactin Variants in Human Pituitaries and Pituitary Adenomas Identified With Two-Dimensional Gel Electrophoresis and Mass Spectrometry

Human prolactin (hPRL) plays multiple roles in growth, metabolism, development, reproduction, and immunoregulation, which is an important protein synthesized in a pituitary. Two-dimensional gel electrophoresis (2DE) is an effective method in identity of protein variants for in-depth insight into functions of that protein. 2DE, 2DE-based PRL-immunoblot, mass spectrometry, and bioinformatics were used to analyze hPRL variants in human normal (control; n = 8) pituitaries and in five subtypes of pituitary adenomas [NF- (n = 3)-, FSH+ (n = 3)-, LH+ (n = 3)-, FSH+/LH+ (n = 3)-, and PRL+ (n = 3)-adenomas]. Six hPRL variants were identified with different isoelectric point (pI)-relative molecular mass (Mr ) distribution on a 2DE pattern, including variants V1 (pI 6.1; 26.0 kDa), V2 (pI 6.3; 26.4 kDa), V3 (pI 6.3; 27.9 kDa), V4 (pI 6.5; 26.1 kDa), V5 (pI 6.8; 25.9 kDa), and V6 (pI 6.7; 25.9 kDa). Compared to controls, except for variants V2-V6 in PRL-adenomas, V2 in FSH+-adenomas, and V3 in NF--adenomas, the other PRL variants were significantly downregulated in each subtype of pituitary adenomas. Moreover, the pattern of those six PRL variants was significantly different among five subtypes of pituitary adenomas relative to control pituitaries. Different hPRL variants might be involved in different types of PRL receptor-signaling pathways in a given condition. Those findings clearly revealed the existence of six hPRL variants in human pituitaries, and the pattern changes of six hPRL variants among different subtypes of pituitary adenomas, which provide novel clues to further study the functions, and mechanisms of action, of hPRL in human pituitary and in PRL-related diseases, and the potential clinical value in pituitary adenomas.

NTyroSite: Computational Identification of Protein Nitrotyrosine Sites Using Sequence Evolutionary Features

Nitrotyrosine is a product of tyrosine nitration mediated by reactive nitrogen species. As an indicator of cell damage and inflammation, protein nitrotyrosine serves to reveal biological change associated with various diseases or oxidative stress. Accurate identification of nitrotyrosine site provides the important foundation for further elucidating the mechanism of protein nitrotyrosination. However, experimental identification of nitrotyrosine sites through traditional methods are laborious and expensive. In silico prediction of nitrotyrosine sites based on protein sequence information are thus highly desired. Here, we report a novel predictor, NTyroSite, for accurate prediction of nitrotyrosine sites using sequence evolutionary information. The generated features were optimized using a Wilcoxon-rank sum test. A random forest classifier was then trained using these features to build the predictor. The final NTyroSite predictor achieved an area under a receiver operating characteristics curve (AUC) score of 0.904 in a 10-fold cross-validation test. It also significantly outperformed other existing implementations in an independent test. Meanwhile, for a better understanding of our prediction model, the predominant rules and informative features were extracted from the NTyroSite model to explain the prediction results. We expect that the NTyroSite predictor may serve as a useful computational resource for high-throughput nitrotyrosine site prediction. The online interface of the software is publicly available at https://biocomputer.bio.cuhk.edu.hk/NTyroSite/.

The crucial role of multiomic approach in cancer research and clinically relevant outcomes

Cancer with heavily economic and social burden is the hot point in the field of medical research. Some remarkable achievements have been made; however, the exact mechanisms of tumor initiation and development remain unclear. Cancer is a complex, whole-body disease that involves multiple abnormalities in the levels of DNA, RNA, protein, metabolite and medical imaging. Biological omics including genomics, transcriptomics, proteomics, metabolomics and radiomics aims to systematically understand carcinogenesis in different biological levels, which is driving the shift of cancer research paradigm from single parameter model to multi-parameter systematical model. The rapid development of various omics technologies is driving one to conveniently get multi-omics data, which accelerates predictive, preventive and personalized medicine (PPPM) practice allowing prediction of response with substantially increased accuracy, stratification of particular patients and eventual personalization of medicine. This review article describes the methodology, advances, and clinically relevant outcomes of different "omics" technologies in cancer research, and especially emphasizes the importance and scientific merit of integrating multi-omics in cancer research and clinically relevant outcomes.

Selective Affinity Enrichment of Nitrotyrosine-Containing Peptides for Quantitative Analysis in Complex Samples

Protein tyrosine nitration by oxidative and nitrate stress is important in the pathogenesis of many inflammatory or aging-related diseases. Mass spectrometry analysis of protein nitrotyrosine is very challenging because the non-nitrated peptides suppress the signals of the low-abundance nitrotyrosine (NT) peptides. No validated methods for enrichment of NT-peptides are currently available. Here we report an immunoaffinity enrichment of NT-peptides for proteomics analysis. The effectiveness of this approach was evaluated using nitrated protein standards and whole-cell lysates in vitro. A total of 1881 NT sites were identified from a nitrated whole-cell extract, indicating that this immunoaffinity-MS method is a valid approach for the enrichment of NT-peptides, and provides a significant advance for characterizing the nitrotyrosine proteome. We noted that this method had higher affinity to peptides with N-terminal nitrotyrosine relative to peptides with other nitrotyrosine locations, which raises the need for future study to develop a pan-specific nitrotyrosine antibody for unbiased, proteome-wide analysis of tyrosine nitration. We applied this method to quantify the changes in protein tyrosine nitration in mouse lungs after intranasal poly(I:C) treatment and quantified 237 NT sites. This result indicates that the immunoaffinity-MS method can be used for quantitative analysis of protein nitrotyrosines in complex samples.

The Unwanted Cell Migration in the Brain: Glioma Metastasis

Cell migration is identified as a highly orchestrated process. It is a fundamental and essential phenomenon underlying tissue morphogenesis, wound healing, and immune response. Under dysregulation, it contributes to cancer metastasis. Brain is considered to be the most complex organ in human body containing many types of neural cells with astrocytes playing crucial roles in monitoring both physiological and pathological functions. Astrocytoma originates from astrocytes and its most malignant type is glioblastoma multiforme (WHO Grade IV astrocytoma), which is capable to infiltrate widely into the neighboring brain tissues making a complete resection of tumors impossible. Very recently, we have reviewed the mechanisms for astrocytes in migration. Given the fact that astrocytoma shares many histological features with astrocytes, we therefore attempt to review the mechanisms for glioma cells in migration and compare them to normal astrocytes, hoping to obtain a better insight into the dysregulation of migratory mechanisms contributing to their metastasis in the brain.

Tyrosine-Nitrated Proteins: Proteomic and Bioanalytical Aspects

SIGNIFICANCE

"Nitroproteomic" is under active development, as 3-nitrotyrosine in proteins constitutes a footprint left by the reactions of nitric oxide-derived oxidants that are usually associated to oxidative stress conditions. Moreover, protein tyrosine nitration can cause structural and functional changes, which may be of pathophysiological relevance for human disease conditions. Biological protein tyrosine nitration is a free radical process involving the intermediacy of tyrosyl radicals; in spite of being a nonenzymatic process, nitration is selectively directed toward a limited subset of tyrosine residues. Precise identification and quantitation of 3-nitrotyrosine in proteins has represented a "tour de force" for researchers. Recent Advances: A small number of proteins are preferential targets of nitration (usually less than 100 proteins per proteome), contrasting with the large number of proteins modified by other post-translational modifications such as phosphorylation, acetylation, and, notably, S-nitrosation. Proteomic approaches have revealed key features of tyrosine nitration both in vivo and in vitro, including selectivity, site specificity, and effects in protein structure and function.

CRITICAL ISSUES

Identification of 3-nitrotyrosine-containing proteins and mapping nitrated residues is challenging, due to low abundance of this oxidative modification in biological samples and its unfriendly behavior in mass spectrometry (MS)-based technologies, that is, MALDI, electrospray ionization, and collision-induced dissociation.

FUTURE DIRECTIONS

The use of (i) classical two-dimensional electrophoresis with immunochemical detection of nitrated proteins followed by protein ID by regular MS/MS in combination with (ii) immuno-enrichment of tyrosine-nitrated peptides and (iii) identification of nitrated peptides by a MIDAS™ experiment is arising as a potent methodology to unambiguously map and quantitate tyrosine-nitrated proteins in vivo. Antioxid. Redox Signal. 26, 313-328.

Partial Immunoblotting of 2D-Gels: A Novel Method to Identify Post-Translationally Modified Proteins Exemplified for the Myelin Acetylome

Post-translational modifications (PTMs) play a key role in regulating protein function, yet their identification is technically demanding. Here, we present a straightforward workflow to systematically identify post-translationally modified proteins based on two-dimensional gel electrophoresis. Upon colloidal Coomassie staining the proteins are partially transferred, and the investigated PTMs are immunodetected. This strategy allows tracking back the immunopositive antigens to the corresponding spots on the original gel, from which they are excised and mass spectrometrically identified. Candidate proteins are validated on the same membrane by immunodetection using a second fluorescence channel. We exemplify the power of partial immunoblotting with the identification of lysine-acetylated proteins in myelin, the oligodendroglial membrane that insulates neuronal axons. The excellent consistency of the detected fluorescence signals at all levels allows the differential comparison of PTMs across multiple conditions. Beyond PTM screening, our multi-level workflow can be readily adapted to clinical applications such as identifying auto-immune antigens or host-pathogen interactions.