Heterogeneity analysis of the human pituitary proteome

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.

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.

Integration of quantitative phosphoproteomics and transcriptomics revealed phosphorylation-mediated molecular events as useful tools for a potential patient stratification and personalized treatment of human nonfunctional pituitary adenomas

Background

Invasiveness is a very challenging clinical problem in nonfunctional pituitary adenomas (NFPAs), and currently, there are no effective invasiveness-related molecular biomarkers. The post-neurosurgery treatment is much different as for invasive and noninvasive NFPAs. The aim of this study was to integrate phosphoproteomics and transcriptomics data to reveal phosphorylation-mediated molecular events for invasive characteristics of NFPAs to achieve a potential tool for patient stratification, and prognostic/predictive assessment to discriminate invasive from noninvasive NFPAs for personalized attitude.

Methods

The 6-plex tandem mass tag (TMT) labeling reagents coupled with TiO₂ enrichment of phosphopeptides and liquid chromatography-tandem mass spectrometry (LC-MS/MS) were used to identify and quantify each phosphoprotein and phosphosite in NFPAs and controls. Differentially expressed genes (DEGs) between invasive NFPA and control tissues were obtained from the Gene Expression Omnibus (GEO) database. The overlapping analysis was performed between phosphoprotiens and invasive DEGs. Gene Ontology (GO) enrichment, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein-protein interaction (PPI) analyses were used to analyze these overlapped molecules.

Results

In total, 1035 phosphoproteins with 2982 phosphorylation sites were identified in NFPAs vs. controls, and 2751 DEGs were identified in invasive NFPAs vs. controls. Overlapping analysis of these phosphoproteins and DEGs exposed 130 overlapped molecules (phosphoproteins; invasive DEGs). GO enrichment and KEGG pathway analyses of 130 overlapped molecules revealed multiple biological processes and signaling pathway network alterations, including cell-cell adhesion, platelet activation, GTPase signaling pathway, protein kinase signaling, calcium signaling pathway, estrogen signaling pathway, glucagon signaling pathway, cGMP-PKG signaling pathway, GnRH signaling pathway, inflammatory mediator regulation of TRP channels, vascular smooth muscle contraction, and Fc gamma R-mediated phagocytosis, which were obviously associated with tumor invasive characteristics. For 130 overlapped molecules, PPI network-based molecular complex detection (MCODE) identified 10 hub molecules, namely SLC2A4, TSC2, AKT1, SCG3, ALB, APOL1, ACACA, SPARCL1, CHGB, and IGFBP5. These hub molecules are involved in multiple signaling pathways and represent potential predictive/prognostic markers in NFPA patients as well as they represent potential therapeutic targets.

Conclusions

This study provided the first large-scale phosphoprotein profiling and phosphorylation-related signaling pathway network alterations in human NFPA tissues. Further, overlapping analysis of phosphoproteins and invasive DEGs revealed the phosphorylation-mediated signaling pathway network changes in invasive NFPAs. These findings are the precious resource for in-depth insight into the molecular mechanisms of NFPAs, as well as for the discovery of effective phosphoprotein biomarkers and therapeutic targets for invasive NFPAs.

Multiomics-Based Signaling Pathway Network Alterations in Human Non-functional Pituitary Adenomas

Non-functional pituitary adenoma (NFPA) seriously affects hypothanamus-pituitary-target organ axis system, with a series of molecule alterations in the multiple levels of genome, transcriptome, proteome, and post-translational modifications, and those molecules mutually interact in a molecular-network system. Meta analysis coupled with IPA pathway-network program was used to comprehensively analyze nine sets of documented NFPA omics data, including NFPA quantitative transcriptomics data [280 differentially expressed genes (DEGs)], NFPA quantitative proteomics data [50 differentially expressed proteins (DEPs)], NFPA mapping protein data (218 proteins), NFPA mapping protein nitration data (9 nitroproteins and 3 non-nitrated proteins), invasive NFPA quantitative transriptomics data (346 DEGs), invasive NFPA quantitative proteomics data (57 DEPs), control mapping protein data (1469 proteins), control mapping protein nitration data (8 nitroproteins), and control mapping phosphorylation data (28 phosphoproteins). A total of 62 molecular-networks with 861 hub-molecules and 519 canonical-pathways including 54 cancer-related canonical pathways were revealed. A total of 42 hub-molecule panels and 9 canonical-pathway panels were identified to significantly associate with tumorigenesis. Four important molecular-network systems, including PI3K/AKT, mTOR, Wnt, and ERK/MAPK pathway-systems, were confirmed in NFPAs by PTMScan experiments with altered expression-patterns and phosphorylations. Nineteen high-frequency hub-molecules were also validated in NFPAs with PTMScan experiment with at least 2.5-fold changes in expression or phosphorylation, including ERK, ERK1/2, Jnk, MAPK, Mek, p38 MAPK, AKT, PI3K complex, p85, PKC, FAK, Rac, Shc, HSP90, NFκB Complex, histone H3, AP1, calmodulin, and PLC. Furthermore, mTOR and Wnt pathway-systems were confirmed in NFPAs by immunoaffinity Western blot analysis, with significantly decreased expression of PRAS40 and increased phosphorylation levels of p-PRAS40 (Thr246) in mTOR pathway in NFPAs compared to controls, and with the decreased protein expressions of GSK-3β and GSK-3β, significantly increased phosphorylation levels of p-GSK3α (Ser21) and p-GSK3β (Ser9), and increased expression level of β-catenin in Wnt pathway in NFPAs compared to controls. Those findings provided a comphrensive and large-scale pathway network data for NFPAs, and offer the scientific evidence for insights into the accurate molecular mechanisms of NFPA and discovery of the effective biomarkers for diagnosis, prognosis, and determination of therapeutic targets.

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.

Proteomic Analysis of the Human Anterior Pituitary Gland

The pituitary function is regulated by a complex system involving the hypothalamus and biological networks within the pituitary. Although the hormones secreted from the pituitary have been well studied, comprehensive analyses of the pituitary proteome are limited. Pituitary proteomics is a field of postgenomic research that is crucial to understand human health and pituitary diseases. In this context, we report here a systematic proteomic profiling of human anterior pituitary gland (adenohypophysis) using high-resolution Fourier transform mass spectrometry. A total of 2164 proteins were identified in this study, of which 105 proteins were identified for the first time compared with high-throughput proteomic-based studies from human pituitary glands. In addition, we identified 480 proteins with secretory potential and 187 N-terminally acetylated proteins. These are the first region-specific data that could serve as a vital resource for further investigations on the physiological role of the human anterior pituitary glands and the proteins secreted by them. We anticipate that the identification of previously unknown proteins in the present study will accelerate biomedical research to decipher their role in functioning of the human anterior pituitary gland and associated human diseases.

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.

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.

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.

Proteomic studies in zebrafish liver cells exposed to the brominated flame retardants HBCD and TBBPA

Proteomic effect screening in zebrafish liver cells was performed to generate hypotheses regarding single and mixed exposure to the BFRs HBCD and TBBPA. Responses at sublethal exposure were analysed by two-dimensional gel electrophoresis followed by MALDI-TOF and FT-ICR protein identification. Mixing of HBCD and TBBPA at sublethal doses of individual substances seemed to increase toxicity. Proteomic analyses revealed distinct exposure-specific and overlapping responses suggesting novel mechanisms with regard to HBCD and TBBPA exposure. While distinct HBCD responses were related to decreased protein metabolism, TBBPA revealed effects related to protein folding and NADPH production. Overlapping responses suggest increased gluconeogenesis (GAPDH and aldolase) while distinct mixture effects suggest a pronounced NADPH production and changes in proteins related to cell cycle control (prohibitin and crk-like oncogene). We conclude that mixtures containing HBCD and TBBPA may result in unexpected effects highlighting proteomics as a sensitive tool for detecting and hypothesis generation of mixture effects.

Mass spectrometric identification of in vivo nitrotyrosine sites in the human pituitary tumor proteome

The chemically stable tyrosine nitration of a protein involves the addition of a nitro group (-NO(2)) to the phenolic ring of a tyrosine residue, which may be associated with nervous system physiological and pathological processes. Identification of nitrotyrosine sites on a protein could clarify the functional significance of the modification. Due to the rarity of nitrotyrosine sites in a proteome, tandem mass spectrometry, coupled with different techniques that isolate and enrich nitrotyrosine-containing proteins from a pituitary proteome, is currently the most effective method for site identification. Commercially available nitrotyrosine polyclonal/monoclonal antibodies enable one to detect nitrotyrosine-containing proteins in a two-dimensional gel electrophoresis (2DGE) map, and to preferentially enrich nitrotyrosine-containing proteins with immunoprecipitation. Our present protocols have integrated different isolation/enrichment techniques (2DGE; Western blots; nitrotyrosine immunoaffinity precipitation) and two different tandem mass spectrometry methods (MALDI-MS/MS; ESI-MS/MS) to determine the amino acid sequence of nitrotyrosine-containing peptides that derive from nitrated proteins. Bioinformatics tools are then used to correlate nitrotyrosine sites with a functional domain/motif in order to understand the relationship between tyrosine nitration and the structural/functions of proteins.

Minimal sex differences in gene expression in the rat superior olivary complex

A critical issue in large-scale gene expression analysis is the impact of sexually dimorphic genes, which may confound the results when sampling across sexes. Here, we assessed, for the first time, sex differences at the transcriptome level in the auditory brainstem. To this end, microarray experiments covering the whole rat genome were performed in the superior olivary complex (SOC) of 16-day-old Sprague-Dawley rats. Sexually dimorphic genes were identified using two criteria: a 2-fold change and a P-value < 0.05. Only 12 out of 41,374 probes (0.03%) showed sexually dimorphic expression. For comparison, pituitaries from 60-day-old female and male rats were analyzed, as this gland is known to display many sex-specific features. Indeed, almost 40 times more probes, i.e. 460 (1.1%), displayed sexual dimorphism. Quantitative RT-PCR confirmed 47 out of 48 microarray results from both tissues. Taking microarray and qRT-PCR data together, the expression of six genes (Prl, Eif2s3y, Gnrhr, Pomc, Ddx3y, Akr1c6) was higher in the male SOC, whereas two genes were upregulated in the female SOC (LOC302172, Xist). Four of these genes are sex-chromosome linked (Eif2s3y, Ddx3y, LOC302172, Xist). In summary, our data indicate only minor and negligible sex-specific differences in gene expression within the SOC at P16.

Molecular pathogenesis of human prolactinomas identified by gene expression profiling, RT-qPCR, and proteomic analyses

The molecular pathogenesis of prolactinomas has resisted elucidation; with the exception of a RAS mutation in a single aggressive prolactinoma, no mutational changes have been identified. In prolactinomas, a further obstacle has been the paucity of surgical specimens suitable for molecular analysis since prolactionomas are infrequently removed due to the availability and effectiveness of medical therapy. In the absence of mutational events, gene expression changes have been sought and detected. Using high-throughput analysis from a large bank of human pituitary adenomas, we examined these tumors according to their molecular profiles rather than traditional immunohistochemistry. We examined six prolactinomas and eight normal pituitary glands using oligonucleotide GeneChip microarrays, reverse transcription-real time quantitative polymerase chain reaction using 10 prolactinomas, and proteomic analysis to examine protein expression in four prolactinomas. Microarray analyses identified 726 unique genes that were statistically significantly different between prolactinomas and normal glands, whereas proteomic analysis identified four differently up-regulated and 19 down-regulated proteins. Several components of the Notch pathway were altered in prolactinomas, and there was an increased expression of the Pit-1 transcription factor, and the survival factor BAG1 but decreased E-cadherin and N-cadherin expression. Taken together, expression profiling and proteomic analyses have identified molecular features unique to prolactinomas that may contribute to their pathogenesis. In the current era of molecular medicine, these findings greatly enhance our understanding and supercede immunohistochemical diagnosis.

Integrating forward and reverse proteomics to unravel protein function

To date, proteomics approaches have aimed to either identify novel proteins or change in protein expression/modification in various organisms under normal or disease conditions. One major aspect of functional proteomics is to identify protein biological properties in a given context, however, forward proteomics approaches alone cannot complete this goal. Indeed, with the increasing successes of such proteomics-based research strategies and the subsequent increasing amounts of proteins identified with unknown molecular functions, approaches allowing for systematic analyses of protein functions are desired. In this review, we propose to depict the complementarities of forward and reverse proteomics approaches in the definite understanding of protein functions. This dual strategy requires a data integration loop which allows for systematic characterization of protein function(s). The details of the integrative process combining both in silico and experimental resources and tools are presented. Altogether, we believe that the integration of forward and reverse proteomics approaches supported by bioinformatics will provide an efficient path towards systems biology.

Advances and challenges in liquid chromatography-mass spectrometry-based proteomics profiling for clinical applications

Recent advances in proteomics technologies provide tremendous opportunities for biomarker-related clinical applications; however, the distinctive characteristics of human biofluids such as the high dynamic range in protein abundances and extreme complexity of the proteomes present tremendous challenges. In this review we summarize recent advances in LC-MS-based proteomics profiling and its applications in clinical proteomics as well as discuss the major challenges associated with implementing these technologies for more effective candidate biomarker discovery. Developments in immunoaffinity depletion and various fractionation approaches in combination with substantial improvements in LC-MS platforms have enabled the plasma proteome to be profiled with considerably greater dynamic range of coverage, allowing many proteins at low ng/ml levels to be confidently identified. Despite these significant advances and efforts, major challenges associated with the dynamic range of measurements and extent of proteome coverage, confidence of peptide/protein identifications, quantitation accuracy, analysis throughput, and the robustness of present instrumentation must be addressed before a proteomics profiling platform suitable for efficient clinical applications can be routinely implemented.

Separation of proteins with a molecular mass difference of 2 kDa utilizing preparative double-inverted gradient polyacrylamide gel electrophoresis under nonreducing conditions: Application to the isolation of 24 kDa human growth hormone

A method for separating proteins with a molecular mass difference of 2 kDa using SDS-PAGE under nonreducing conditions is presented. A sample mixture containing several human growth hormone (hGH) isoforms was initially separated on a weak anion-exchange column. Fractions rich in 24 kDa hGH as determined by analytical SDS-PAGE were pooled and further separated by cation-exchange chromatography. The fractions pooled from the cation-exchange chromatography contained two hGH isoforms with a 2 kDa molecular mass difference according to SDS-PAGE analysis, 22 and 24 kDa hGH. The 22 and 24 kDa hGH were separated using continuous-elution preparative double-inverted gradient PAGE (PDG-PAGE) under nonreducing conditions. The preparative electrophoresis gel was composed of three stacked tubular polyacrylamide matrices, a 4% stacking gel, a 13-18% linear gradient gel, and a 15-10% linear inverted gradient gel. Fractions containing purified 24 kDa hGH were pooled and Western blot analysis displayed immunoreactivity to antihGH antibodies. PDG-PAGE provides researchers with an electrophoretic technique to preparatively purify proteins under nonreducing conditions with molecular mass differences of 2 kDa.

Novel Molecular Signaling and Classification of Human Clinically Nonfunctional Pituitary Adenomas Identified by Gene Expression Profiling and Proteomic Analyses

Pituitary adenomas comprise 10% of intracranial tumors and occur in about 20% of the population. They cause significant morbidity by compression of regional structures or the inappropriate expression of pituitary hormones. Their molecular pathogenesis is unclear, and the current classification of clinically nonfunctional tumors does not reflect any molecular distinctions between the subtypes. To further elucidate the molecular changes that contribute to the development of these tumors and reclassify them according to the molecular basis, we investigated 11 nonfunctional pituitary adenomas and eight normal pituitary glands, using 33 oligonucleotide GeneChip microarrays. We validated microarray results with the reverse transcription real-time quantitative PCR, using a larger number of nonfunctional adenomas. We also used proteomic analysis to examine protein expression in these nonfunctional adenomas. Microarray analysis identified significant increases in the expression of 115 genes and decreases in 169 genes, whereas proteomic analysis identified 21 up-regulated and 29 down-regulated proteins. We observed changes in expression of SFRP1, TLE2, PITX2, NOTCH3, and DLK1, suggesting that the developmental Wnt and Notch pathways are activated and important for the progression of nonfunctional pituitary adenomas. We further analyzed gene expression profiles of all nonfunctional pituitary subtypes to each other and identified genes that were affected uniquely in each subtype. These results show distinct gene and protein expression patterns in adenomas, provide new insight into the pathogenesis and molecular classification of nonfunctional pituitary adenomas, and suggest that therapeutic targeting of the Notch pathway could be effective for these tumors.

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

This article will review the published research on the elucidation of the mechanisms of pituitary adenoma formation. Mass spectrometry (MS) plays a key role in those studies. Comparative proteomics has been used with the long-term goal to locate, detect, and characterize the differentially expressed proteins (DEPs) in human pituitary adenomas; to identify tumor-related and -specific biomarkers; and to clarify the basic molecular mechanisms of pituitary adenoma formation. The methodology used for comparative proteomics, the current status of human pituitary proteomics studies, and future perspectives are reviewed. The methodologies that are used in comparative proteomics studies of human pituitary adenomas are readily exportable to other different areas of cancer research.

Proteomics analysis of growth hormone isoforms in the human pituitary

In order to elucidate the roles of human growth hormone (hGH) in the normal (control) pituitary and in adenomas, the hGH isoforms in the human pituitary were analyzed with two-dimensional gel electrophoresis, immobilized metal affinity column (Ga(+3)) chromatography, mass spectrometry (MS), and bioinformatics. Twenty-four hGH-containing proteins, with significantly different expression proportions of their isoforms were found. The proportions of isoforms were as follows: isoform 1 (87.5%) > isoform 2 (8.1%) > isoform 3 (3.3%) > isoform 4 (1.1%). Deamidation of asparagine to aspartate was identified with matrix-assisted laser desorption/ionization-time of flight MS. Tandem mass spectrometry data demonstrated that hGH is a phosphoprotein (spot 6); phosphorylation was found at Ser-77 in the tryptic peptide (68)YSFLQNPQTSLCFSESIPTPSNR(90), at Ser-176 in the tryptic peptide (172)FDTNSHNDDALLK(184), and at Ser-132 in the peptide (126)SLVYGASDSNVYDLLK(141). The phosphorylation sites at Ser-77 and Ser-176 were consistent with computer-program predictions (NetPhos). These results provide novel clues for further studies of the functions, and mechanisms of action, of hGH in the human pituitary and in growth hormone-related diseases.

Normalization and analysis of residual variation in two-dimensional gel electrophoresis for quantitative differential proteomics

Although two-dimensional gel electrophoresis (2-DE) has long been a favorite experimental method to screen proteomes, its reproducibility is seldom analyzed with the assistance of quantitative error models. The lack of models of residual distributions that can be used to assign likelihood to differential expression reflects the difficulty in tackling the combined effect of variability in spot intensity and uncertain recognition of the same spot in different gels. In this report we have analyzed a series of four triplicate two-dimensional gels of chicken embryo heart samples at two distinct development stages to produce such a model of residual distribution. In order to achieve this reference error model, a nonparametric procedure for consistent spot intensity normalization had to be established, and is also reported here. In addition to variability in normalized intensity due to various sources, the residual variation between replicates was observed to be compounded by failure to identify the spot itself (gel alignment). The mixed effect is reflected by variably skewed bimodal density distributions of residuals. The extraction of a global error model that accommodated such distribution was achieved empirically by machine learning, specifically by bootstrapped artificial neural networks. The model described is being used to assign confidence values to observed variations in arbitrary 2-DE gels in order to quantify the degree of over-expression and under-expression of protein spots.

Effect of nicotine on lung S-adenosylmethionine and development of Pneumocystis pneumonia

Because S-adenosylmethionine (AdoMet) is required by Pneumocystis carinii in vitro, Pneumocystis infection depletes plasma AdoMet of rats and humans, nicotine reduces AdoMet of guinea pig lungs, and smoking correlates with reduced episodes of Pneumocystis pneumonia (PCP) in AIDS patients, we tested the effect of nicotine treatment on PCP using a rat model. Intraperitoneal infusion of 400 microg of R-(+) nicotine kg(-1) h(-1) intraperitoneal for 21 days caused a 15-fold reduction in lung AdoMet although neither plasma nor liver were changed. Infusion of 4 and 400 microg kg(-1) h(-1) into immunosuppressed rats, beginning when rats were inoculated with P. carinii, caused 85 and 99.88% reductions, respectively, in P. carinii cysts at sacrifice 21 days later; P. carinii nuclei were reduced by 91.2 and >99.99%, respectively. This effect was reversed by concomitant administration of AdoMet with nicotine. Treatment with AdoMet alone increased infection intensity. We conclude that AdoMet is a critical and limiting nutrient for Pneumocystis thus can serve as a therapeutic target for PCP. Regarding the mechanism, nicotine treatment caused no change in rat lung activity of AdoMet synthesizing methionine ATP transferase activity nor was there any evidence of increased AdoMet utilization for methylation reactions. Except of a doubling of putrescine, nicotine treatment also did not change lung polyamine content. However, key polyamine anabolic and catabolic enzymes were upregulated, and there were corresponding changes in polyamine metabolic intermediates. We conclude that chronic nicotine treatment increases lung polyamine catabolic/anabolic cycling and/or excretion leading to increased AdoMet-consuming polyamine biosynthesis and depletion of lung AdoMet.

Proteomics and transcriptomics analyses of secretagogin down-regulation in human non-functional pituitary adenomas

In order to explore the presence of, and the potential role of, secretagogin in human pituitary adenomas, an analytical strategy that integrated comparative proteomics and comparative transcriptomics was used to detect the protein and the mRNA expression, respectively, of secretagogin in human non-functional pituitary adenomas compared to controls. Proteomics methods included two-dimensional gel electrophoresis, 2D gel image analysis, mass spectrometry [matrix-assisted laser desorption/ionization-time of flight-peptide mass fingerprinting (MALDI-TOF PMF) and liquid chromatography-electrospray ionization-quadrupole-ion trap tandem mass spectrometry (LC-ESI-Q-IT MS/MS)], and database analysis. Transcriptomics methods included the GeneChip microarray, image processing, and data analysis. The proteomics and transcriptomics data demonstrated that secretagogin was significantly down-regulated at the protein and mRNA levels, respectively, in the human non-functional (NF) pituitary adenomas (NF-, LH+, FSH+, and FSH+ + LH+). For the secretagogin protein, the expression level was NF- < FSH+ + LH+ < FSH+ < LH+ < Control, with a range of down-regulation of 2.2-6.9 fold in non-functional pituitary adenomas compared to controls, with a significant difference (p < 0.001). For secretagogin mRNA, the expression level was NF- < LH+ < FSH+ + LH+ < FSH+ < Control, with a range of down-regulation of 1.8-18.6 fold in non-functional pituitary adenomas compared to controls that was significant (p < 0.05). The secretagogin protein expression correlated significantly with its mRNA expression. Those results suggest that secretagogin might play a role in human non-functional pituitary adenomas. This novel finding may provide clues to clarify the basic molecular mechanisms of pituitary adenoma formation, and to identify new tumor-related markers.