Comparative proteomics analysis of human pituitary adenomas: current status and future perspectives

Strategy for Identifying a Robust Metabolomic Signature Reveals the Altered Lipid Metabolism in Pituitary Adenoma

Despite the well-established connection between systematic metabolic abnormalities and the pathophysiology of pituitary adenoma (PA), current metabolomic studies have reported an extremely limited number of metabolites associated with PA. Moreover, there was very little consistency in the identified metabolite signatures, resulting in a lack of robust metabolic biomarkers for the diagnosis and treatment of PA. Herein, we performed a global untargeted plasma metabolomic profiling on PA and identified a highly robust metabolomic signature based on a strategy. Specifically, this strategy is unique in (1) integrating repeated random sampling and a consensus evaluation-based feature selection algorithm and (2) evaluating the consistency of metabolomic signatures among different sample groups. This strategy demonstrated superior robustness and stronger discriminative ability compared with that of other feature selection methods including Student's t-test, partial least-squares-discriminant analysis, support vector machine recursive feature elimination, and random forest recursive feature elimination. More importantly, a highly robust metabolomic signature comprising 45 PA-specific differential metabolites was identified. Moreover, metabolite set enrichment analysis of these potential metabolic biomarkers revealed altered lipid metabolism in PA. In conclusion, our findings contribute to a better understanding of the metabolic changes in PA and may have implications for the development of diagnostic and therapeutic approaches targeting lipid metabolism in PA. We believe that the proposed strategy serves as a valuable tool for screening robust, discriminating metabolic features in the field of metabolomics.

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.

Muti-omics integration analysis revealed molecular network alterations in human nonfunctional pituitary neuroendocrine tumors in the framework of 3P medicine

Nonfuctional pituitary neuroendocrine tumor (NF-PitNET) is highly heterogeneous and generally considered a common intracranial tumor. A series of molecules are involved in NF-PitNET pathogenesis that alter in multiple levels of genome, transcriptome, proteome, and metabolome, and those molecules mutually interact to form dynamically associated molecular-network systems. This article reviewed signaling pathway alterations in NF-PitNET based on the analyses of the genome, transcriptome, proteome, and metabolome, and emphasized signaling pathway network alterations based on the integrative omics, including calcium signaling pathway, cGMP-PKG signaling pathway, mTOR signaling pathway, PI3K/AKT signaling pathway, MAPK (mitogen-activated protein kinase) signaling pathway, oxidative stress response, mitochondrial dysfunction, and cell cycle dysregulation, and those signaling pathway networks are important for NF-PitNET formation and progression. Especially, this review article emphasized the altered signaling pathways and their key molecules related to NF-PitNET invasiveness and aggressiveness that are challenging clinical problems. Furthermore, the currently used medication and potential therapeutic agents that target these important signaling pathway networks are also summarized. These signaling pathway network changes offer important resources for insights into molecular mechanisms, discovery of effective biomarkers, and therapeutic targets for patient stratification, predictive diagnosis, prognostic assessment, and targeted therapy of NF-PitNET.

Phosphorylation-Mediated Molecular Pathway Changes in Human Pituitary Neuroendocrine Tumors Identified by Quantitative Phosphoproteomics

To investigate the biological role of protein phosphorylation in human nonfunctional pituitary neuroendocrine tumors (NF-PitNETs), proteins extracted from NF-PitNET and control tissues were analyzed with tandem mass tag (TMT)-based quantitative proteomics coupled with TiO₂ enrichment of phosphopeptides. A total of 595 differentially phosphorylated proteins (DPPs) with 1412 phosphosites were identified in NF-PitNETs compared to controls (p < 0.05). KEGG pathway network analysis of 595 DPPs identified nine statistically significant signaling pathways, including the spliceosome pathway, the RNA transport pathway, proteoglycans in cancer, SNARE interactions in vesicular transport, platelet activation, bacterial invasion of epithelial cells, tight junctions, vascular smooth muscle contraction, and protein processing in the endoplasmic reticulum. GO analysis revealed that these DPPs were involved in multiple cellular components (CCs), biological processes (BPs), and molecule functions (MFs). The kinase analysis of 595 DPPs identified seven kinases, including GRP78, WSTF, PKN2, PRP4, LOK, NEK1, and AMPKA1, and the substrate of these kinases could provide new ideas for seeking drug targets for NF-PitNETs. The randomly selected DPP calnexin was further confirmed with immunoprecipitation (IP) and Western blot (WB). These findings provide the first DPP profiling, phosphorylation-mediated molecular network alterations, and the key kinase profiling in NF-PitNET pathogenesis, which are a precious resource for understanding the biological roles of protein phosphorylation in NF-PitNET pathogenesis and discovering effective phosphoprotein biomarkers and therapeutic targets and drugs for the management of NF-PitNETs.

Comparative Proteomic Study Shows the Expression of Hint-1 in Pituitary Adenomas

Pituitary adenomas (PAs) can be unpredictable and aggressive tumors. No reliable markers of their biological behavior have been found. Here, a proteomic analysis was applied to identify proteins in the expression profile between invasive and non-invasive PAs to search for possible biomarkers. A histopathological and immunohistochemical (adenohypophyseal hormones, Ki-67, p53, CD34, VEGF, Flk1 antibodies) analysis was done; a proteomic map was evaluated in 64 out of 128 tumors. There were 107 (84%) invasive and 21 (16%) non-invasive PAs; 80.5% belonged to III and IV grades of the Hardy–Vezina classification. Invasive PAs (n = 56) showed 105 ± 43 spots; 86 ± 32 spots in non-invasive PAs (n = 8) were observed. The 13 most prominent spots were selected and 11 proteins related to neoplastic process in different types of tumors were identified. Hint1 (Histidine triad nucleotide-binding protein 1) high expression in invasive PA was found (11.8 ± 1.4, p = 0.005), especially at high index (>10; p = 0.0002). High Hint1 expression was found in invasive VEGF positive PA (13.8 ± 2.3, p = 0.005) and in Flk1 positive PA (14.04 ± 2.28, p = 0.006). Hint1 is related to human tumorigenesis by its interaction with signaling pathways and transcription factors. It could be related to invasive behavior in PAs. This is the first report on Hint expression in PAs. More analysis is needed to find out the possible role of Hint in these tumors.

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.

MULTIOMIC PATTERNS IN BODY FLUIDS: TECHNOLOGICAL CHALLENGE WITH A GREAT POTENTIAL TO IMPLEMENT THE ADVANCED PARADIGM OF 3P MEDICINE

Liquid biopsy (LB) is defined as a sample of any of body fluids (blood, saliva, tear fluid, urine, sweat, amniotic, cerebrospinal and pleural fluids, cervicovaginal secretion, and wound efflux, amongst others), which can be ex vivo analysed to detect and quantity the target(s) of interest. LB represents diagnostic approach relevant for organ-specific changes and systemic health conditions including both manifested diseases and their prestages such as suboptimal health. Further, experts emphasise that DNA-based analysis alone does not provide sufficient information for optimal diagnostics and effective treatments. Consequently, of great scientific and clinical utility are molecular patterns detected by hybrid technologies such as metabolomic tools and molecular imaging. Future proposed strategies utilise multiomic pillars (generally genome, tanscriptome, proteome, metabolome, epigenome, radiome, and microbiome), system-biological approach, and multivariable algorithms for diagnostic, prognostic, and therapeutic purposes. Current article analyses pros and cons of the mass spectrometry-based technologies, provides eminent examples of a success story "from discovery to clinical application," and demonstrates a "road-map" for the technology-driven paradigm change from reactive to predictive, preventive and personalised medical services as the medicine of the future benefiting the patient and healthcare at large. © 2019 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd. Mass Spec Rev.

Quantitative Analysis of Proteome in Non-functional Pituitary Adenomas: Clinical Relevance and Potential Benefits for the Patients

Background: Non-functional pituitary adenoma (NFPA) is a common tumor that occurs in the pituitary gland, and generally without any symptoms at its early stage and without clinical elevation of hormones, which is commonly diagnosed when it grows up to compress its surrounding tissues and organs. Currently, the pathogenesis of NFPA has not been clarified yet. It is necessary to investigate molecular alterations in NFPA, and identify reliable biomarkers and drug therapeutic targets for effective treatments. Methods: Tandem mass tags (TMT)-based quantitative proteomics was used to identify and quantify proteins in NFPAs. GO and KEGG enrichment analyses were used to analyze the identified proteins. Differentially expressed genes (DEGs) between NFPA and control tissues were obtained from GEO datasets. These two sets of protein and gene data were analyzed to obtain overlapped molecules (genes; proteins), followed by further GO and KEGG pathway analyses of these overlapped molecules, and molecular network analysis to obtain the hub molecules with Cytoscape. Two hub molecules (SRC and AKT1) were verified with Western blotting. Results: Totally 6076 proteins in NFPA tissues were identified, and 3598 DEGs between NFPA and control tissues were identified from GEO database. Overlapping analysis of 6076 proteins and 3598 DEGs obtained 1088 overlapped molecules (DEGs; proteins). KEGG pathway analysis of 6076 proteins obtained 114 statistically significant pathways, including endocytosis, and spliceosome signaling pathways. KEGG pathway analysis of 1088 overlapped molecules obtained 52 statistically significant pathways, including focal adhesion, cGMP-PKG pathway, and platelet activation signaling pathways. These pathways play important roles in cell energy supply, adhesion, and maintenance of the tumor microenvironment. According to the association degree in Cytoscape, ten hub molecules (DEGs; proteins) were identified, including GAPDH, ALB, ACACA, SRC, ENO2, CALM1, POTEE, HSPA8, DECR1, and AKT1. Western-blotting analysis confirmed the upregulated expressions of SRC and PTMScan experiment confirmed the increased levels of pAKT1, in NFPAs compared to controls. Conclusions: This study established the large-scale quantitative protein profiling of NFPA tissue proteome. It offers a basis for subsequent in-depth proteomics analysis of NFPAs, and insight into the molecular mechanism of NFPAs. It also provided the basic data to discover reliable biomarkers and therapeutic targets for NFPA patients.

Tumor microenvironment defines the invasive phenotype of AIP-mutation-positive pituitary tumors

The molecular mechanisms leading to aryl hydrocarbon receptor interacting protein (AIP) mutation-induced aggressive, young-onset growth hormone-secreting pituitary tumors are not fully understood. In this study, we have identified that AIP-mutation-positive tumors are infiltrated by a large number of macrophages compared to sporadic tumors. Tissue from pituitary-specific Aip-knockout (Aip^Flox/Flox;Hesx1^Cre/+) mice recapitulated this phenotype. Our human pituitary tumor transcriptome data revealed the "epithelial-to-mesenchymal transition (EMT) pathway" as one of the most significantly altered pathways in AIPpos tumors. Our in vitro data suggest that bone marrow-derived macrophage-conditioned media induces more prominent EMT-like phenotype and enhanced migratory and invasive properties in Aip-knockdown somatomammotroph cells compared to non-targeting controls. We identified that tumor-derived cytokine CCL5 is upregulated in AIP-mutation-positive human adenomas. Aip-knockdown GH3 cell-conditioned media increases macrophage migration, which is inhibited by the CCL5/CCR5 antagonist maraviroc. Our results suggest that a crosstalk between the tumor and its microenvironment plays a key role in the invasive nature of AIP-mutation-positive tumors and the CCL5/CCR5 pathway is a novel potential therapeutic target.

Two-dimensional Gel Electrophoresis Coupled with Mass Spectrometry Methods for an Analysis of Human Pituitary Adenoma Tissue Proteome

Human pituitary adenoma (PA) is a common tumor that occurs in the human pituitary gland in the hypothalamus-pituitary-targeted organ axis systems, and may be classified as either clinically functional or nonfunctional PA (FPA and NFPA). NFPA is difficult for early stage diagnosis and therapy due to barely elevating hormones in the blood compared to FPA. Our long-term goal is to use proteomics methods to discover reliable biomarkers for clarification of PA molecular mechanisms and recognition of effective diagnostic, prognostic markers and therapeutic targets. Effective two-dimensional gel electrophoresis (2DE) coupled with mass spectrometry (MS) methods were presented here to analyze human PA proteomes, including preparation of samples, 2D gel electrophoresis, protein visualization, image analysis, in-gel trypsin digestion, peptide mass fingerprint (PMF), and tandem mass spectrometry (MS/MS). 2-Dimensional gel electrophoresis matrix-assisted laser desorption/ionization mass spectrometry PMF (2DE-MALDI MS PMF), 2DE-MALDI MS/MS, and 2DE-liquid chromatography (LC) MS/MS procedures have been successfully applied in an analysis of NFPA proteome. With the use of a high-sensitivity mass spectrometer, many proteins were identified with the 2DE-LC-MS/MS method in each 2D gel spot in an analysis of complex PA tissue to maximize the coverage of human PA proteome.

Human Pituitary Adenoma Proteomics: New Progresses and Perspectives

Pituitary adenoma (PA) is a common intracranial neoplasm that impacts on human health through interfering hypothalamus-pituitary-target organ axis systems. The development of proteomics gives great promises in the clarification of molecular mechanisms of a PA and discovery of effective biomarkers for prediction, prevention, early-stage diagnosis, and treatment for a PA. A great progress in the field of PA proteomics has been made in the past 10 years, including (i) the use of laser-capture microdissection, (ii) proteomics analyses of functional PAs (such as prolactinoma), invasive and non-invasive non-functional pituitary adenomas (NFPAs), protein post-translational modifications such as phosphorylation and tyrosine nitration, NFPA heterogeneity, and hormone isoforms, (iii) the use of protein antibody array, (iv) serum proteomics and peptidomics, (v) the integration of proteomics and other omics data, and (vi) the proposal of multi-parameter systematic strategy for a PA. This review will summarize these progresses of proteomics in PAs, point out the existing drawbacks, propose the future research directions, and address the clinical relevance of PA proteomics data, in order to achieve our long-term goal that is use of proteomics to clarify molecular mechanisms, construct molecular networks, and discover effective biomarkers.

EPMA position paper in cancer: current overview and future perspectives

At present, a radical shift in cancer treatment is occurring in terms of predictive, preventive, and personalized medicine (PPPM). Individual patients will participate in more aspects of their healthcare. During the development of PPPM, many rapid, specific, and sensitive new methods for earlier detection of cancer will result in more efficient management of the patient and hence a better quality of life. Coordination of the various activities among different healthcare professionals in primary, secondary, and tertiary care requires well-defined competencies, implementation of training and educational programs, sharing of data, and harmonized guidelines. In this position paper, the current knowledge to understand cancer predisposition and risk factors, the cellular biology of cancer, predictive markers and treatment outcome, the improvement in technologies in screening and diagnosis, and provision of better drug development solutions are discussed in the context of a better implementation of personalized medicine. Recognition of the major risk factors for cancer initiation is the key for preventive strategies (EPMA J. 4(1):6, 2013). Of interest, cancer predisposing syndromes in particular the monogenic subtypes that lead to cancer progression are well defined and one should focus on implementation strategies to identify individuals at risk to allow preventive measures and early screening/diagnosis. Implementation of such measures is disturbed by improper use of the data, with breach of data protection as one of the risks to be heavily controlled. Population screening requires in depth cost-benefit analysis to justify healthcare costs, and the parameters screened should provide information that allow an actionable and deliverable solution, for better healthcare provision.

Heterogeneity analysis of the proteomes in clinically nonfunctional pituitary adenomas

Background

Clinically nonfunctional pituitary adenomas (NFPAs) without any clinical elevation of hormone and with a difficulty in its early-stage diagnosis are highly heterogeneous with different hormone expressions in NFPA tissues, including luteinizing hormone (LH)-positive, follicle-stimulating hormone (FSH)-positive, LH/FSH-positive, and negative (NF). Elucidation of molecular mechanisms and discovery of biomarkers common and specific to those different subtypes of NFPAs will benefit NFPA patients in early-stage diagnosis and individualized treatment.

Methods

Two-dimensional gel electrophoresis (2DGE) and PDQuest image analyses were used to compare proteomes of different NFPA subtypes (NF-, LH-, FSH-, and LH/FSH-positive) relative to control pituitaries (Con). Differentially expressed proteins (DEPs) were characterized with mass spectrometry (MS). Each set of DEPs in four NFPA subtypes was evaluated with overlap analysis and signaling pathway network analysis with comparison to determine any DEP and pathway network that are common and specific to each NFPA subtype.

Results

A total of 93 differential protein-spots were determined with comparison of each NFPA type (NF-, LH-, FSH-, and LH/FSH-positive) versus control pituitaries. A total of 76 protein-spots were MS-identified (59 DEPs in NF vs. Con; 65 DEPs in LH vs. Con; 63 DEPs in FSH vs. Con; and 55 DEPs in LH/FSH vs. Con). A set of DEPs and pathway network data were common and specific to each NFPA subtype. Four important common pathway systems included MAPK-signaling abnormality, oxidative stress, mitochondrial dysfunction, and cell-cycle dysregulation. However, these pathway systems were, in fact, different among four NFPA subtypes with different protein-expression levels of most of nodes, different protein profiles, and different pathway network profiles.

Conclusions

These result data demonstrate that common and specific DEPs and pathway networks exist in four NFPA subtypes, and clarify proteome heterogeneity of four NFPA subtypes. Those findings will help to elucidate molecular mechanisms of NFPAs, and discover protein biomarkers to effectively manage NFPA patients towards personalized medicine.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-014-0069-6) contains supplementary material, which is available to authorized users.

Pituitary adenoma nitroproteomics: current status and perspectives

Oxidative stress is extensively associated with tumorigenesis. A series of studies on stable tyrosine nitration as a marker of oxidative damage were performed in human pituitary and adenoma. This paper reviews published research on the mass spectrometry characteristics of nitropeptides and nitroproteomics of pituitary controls and adenomas. The methodology used for nitroproteomics, the current status of human pituitary nitroproteomics studies, and the future perspectives are reviewed. Enrichment of those low-abundance endogenous nitroproteins from human tissues or body fluid samples is the first important step for nitroproteomics studies. Mass spectrometry is the essential approach to determine the amino acid sequence and locate the nitrotyrosine sites. Bioinformatics analyses, including protein domain and motif analyses, are needed to locate the nitrotyrosine site within the corresponding protein domains/motifs. Systems biology techniques, including pathway analysis, are necessary to discover signaling pathway networks involving nitroproteins from the systematically global point of view. Future quantitative nitroproteomics will discover pituitary adenoma-specific nitroprotein(s). Structural biology techniques such as X-ray crystallography analysis will solidly clarify the effects of tyrosine nitration on structure and functions of a protein. Those studies will eventually address the mechanisms and biological functions of tyrosine nitration in pituitary tumorigenesis and will discover nitroprotein biomarkers for pituitary adenomas and targets for drug design for pituitary adenoma therapy.

Multi-parameter systematic strategies for predictive, preventive and personalised medicine in cancer

Cancer is a complex disease that causes the alterations in the levels of gene, RNA, protein and metabolite. With the development of genomics, transcriptomics, proteomics and metabolomic techniques, the characterisation of key mutations and molecular pathways responsible for tumour progression has led to the identification of a large number of potential targets. The increasing understanding of molecular carcinogenesis has begun to change paradigms in oncology from traditional single-factor strategy to multi-parameter systematic strategy. The therapeutic model of cancer has changed from adopting the general radiotherapy and chemotherapy to personalised strategy. The development of predictive, preventive and personalised medicine (PPPM) will allow prediction of response with substantially increased accuracy, stratification of particular patient groups and eventual personalisation of medicine. The PPPM will change the approach to tumour diseases from a systematic and comprehensive point of view in the future. Patients will be treated according to the specific molecular profiles that are found in the individual tumour tissue and preferentially with targeted substances, if available.

A primary proteomic analysis of serum from patients with nonfunctioning pituitary adenoma

OBJECTIVE

The early diagnosis of nonfunctioning pituitary adenoma (NFPA) is difficult. The objective of this study was to find specific protein biomarkers to aid in the early detection of NFPA.

METHODS

Serum samples from 34 patients with NFPA and 34 age- and sex-matched healthy control subjects were analysed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. The spectra were generated, protein peak clustering was performed and classification analyses were carried out using a decision tree classification algorithm.

RESULTS

Nine differentially expressed serum proteins were identified in the patients with NFPA compared with the control subjects. Both the sensitivity and specificity of the decision tree classification algorithm were 82.4% for NFPA.

CONCLUSIONS

Nine new serum protein biomarkers for NFPA were identified. SELDI-TOF-MS coupled with data mining tools might provide a novel approach for the early diagnosis of NFPA and population screening for the disease.

The use of variations in proteomes to predict, prevent, and personalize treatment for clinically nonfunctional pituitary adenomas

Pituitary adenomas account for ∼10% of intracranial tumors, and they cause the compression of nearby structures and the inappropriate expression of pituitary hormones. Unlike functional pituitary adenomas, nonfunctional (NF) pituitary adenomas account for ∼30% of pituitary tumors, and are large enough to cause blindness; because they do not cause any clinical hormone hypersecretion, they are difficult to detect at an early stage; and hypopituitarism results. No effective molecular biomarkers or chemical therapy have been approved for the clinical setting. Because an NF pituitary adenoma is highly heterogeneous, differences in the proteins (the proteome) can distinguish among those heterogeneity structures. The components of a proteome dynamically change as an NF adenoma progresses. Changes in protein expression and protein modifications, individually or in combination, might be biomarkers to predict the disease, monitor the tumor progression, and develop an accurate molecular classification for personalized patient treatment. The modalities of proteomic variation might also be useful in the interventional prevention and personalized treatment of patients to halt the occurrence and progression of NF pituitary adenomas.

Signaling pathway networks mined from human pituitary adenoma proteomics data

Background

We obtained a series of pituitary adenoma proteomic expression data, including protein-mapping data (111 proteins), comparative proteomic data (56 differentially expressed proteins), and nitroproteomic data (17 nitroproteins). There is a pressing need to clarify the significant signaling pathway networks that derive from those proteins in order to clarify and to better understand the molecular basis of pituitary adenoma pathogenesis and to discover biomarkers. Here, we describe the significant signaling pathway networks that were mined from human pituitary adenoma proteomic data with the Ingenuity pathway analysis system.

Methods

The Ingenuity pathway analysis system was used to analyze signal pathway networks and canonical pathways from protein-mapping data, comparative proteomic data, adenoma nitroproteomic data, and control nitroproteomic data. A Fisher's exact test was used to test the statistical significance with a significance level of 0.05. Statistical significant results were rationalized within the pituitary adenoma biological system with literature-based bioinformatics analyses.

Results

For the protein-mapping data, the top pathway networks were related to cancer, cell death, and lipid metabolism; the top canonical toxicity pathways included acute-phase response, oxidative-stress response, oxidative stress, and cell-cycle G2/M transition regulation. For the comparative proteomic data, top pathway networks were related to cancer, endocrine system development and function, and lipid metabolism; the top canonical toxicity pathways included mitochondrial dysfunction, oxidative phosphorylation, oxidative-stress response, and ERK/MAPK signaling. The nitroproteomic data from a pituitary adenoma were related to cancer, cell death, lipid metabolism, and reproductive system disease, and the top canonical toxicity pathways mainly related to p38 MAPK signaling and cell-cycle G2/M transition regulation. Nitroproteins from a pituitary control related to gene expression and cellular development, and no canonical toxicity pathways were identified.

Conclusions

This pathway network analysis demonstrated that mitochondrial dysfunction, oxidative stress, cell-cycle dysregulation, and the MAPK-signaling abnormality are significantly associated with a pituitary adenoma. These pathway-network data provide new insights into the molecular mechanisms of human pituitary adenoma pathogenesis, and new clues for an in-depth investigation of pituitary adenoma and biomarker discovery.

Proteomic analysis of prolactinoma cells by immuno-laser capture microdissection combined with online two-dimensional nano-scale liquid chromatography/mass spectrometry

Background

Pituitary adenomas, the third most common intracranial tumor, comprise nearly 16.7% of intracranial neoplasm and 25%-44% of pituitary adenomas are prolactinomas. Prolactinoma represents a complex heterogeneous mixture of cells including prolactin (PRL), endothelial cells, fibroblasts, and other stromal cells, making it difficult to dissect the molecular and cellular mechanisms of prolactin cells in pituitary tumorigenesis through high-throughout-omics analysis. Our newly developed immuno-laser capture microdissection (LCM) method would permit rapid and reliable procurement of prolactin cells from this heterogeneous tissue. Thus, prolactin cell specific molecular events involved in pituitary tumorigenesis and cell signaling can be approached by proteomic analysis.

Results

Proteins from immuno-LCM captured prolactin cells were digested; resulting peptides were separated by two dimensional-nanoscale liquid chromatography (2D-nanoLC/MS) and characterized by tandem mass spectrometry. All MS/MS spectrums were analyzed by SEQUEST against the human International Protein Index database and a specific prolactinoma proteome consisting of 2243 proteins was identified. This collection of identified proteins by far represents the largest and the most comprehensive database of proteome for prolactinoma. Category analysis of the proteome revealed a widely unbiased access to various proteins with diverse functional characteristics.

Conclusions

This manuscript described a more comprehensive proteomic profile of prolactinomas compared to other previous published reports. Thanks to the application of immuno-LCM combined with online two-dimensional nano-scale liquid chromatography here permitted identification of more proteins and, to our best knowledge, generated the largest prolactinoma proteome. This enlarged proteome would contribute significantly to further understanding of prolactinoma tumorigenesis which is crucial to the management of prolactinomas.

Proteolytic 18O-labeling strategies for quantitative proteomics

A number of proteomic techniques have been developed to quantify proteins in biological systems. This review focuses on the quantitative proteomic technique known as "proteolytic 18O-labeling." This technique utilizes a protease and H(2)18O to produce labeled peptides, with subsequent chromatographic and mass spectrometric analysis to identify and quantify (relative) the proteins from which the peptides originated. The technique determines the ratio of individual protein's expression level between two samples relative to each other, and can be used to quantitatively examine protein expression (comparative proteomics) and post-translational modifications, and to study protein-protein interactions. The present review discusses various aspects of the 18O-labeling technique, including: its history, the advantages and disadvantages of the proteolytic 18O-labeling technique compared to other techniques, enzymatic considerations, the problem of variable incorporation of 18O atoms into peptides with a discussion on recent advancements of the technique to overcome it, computational tools to interpret the data, and a review of the biological applications.