Plasma proteomics-based identification of novel biomarkers in early gastric cancer

BackgroundIdentification and treatment in the early stage can significantly improve the prognosis of gastric cancer (GC). However, to date, there is still no ideal biomarker that can be used for the screening of early stage GC (EGC). The proteomics supported by mass spectrometry offers more possibilities for discovering tumor biomarkers. The aim of this study was to explore candidate protein biomarkers for EGC screening with mass spectrometry and bioinformatics technology.MethodsPlasma samples were collected from 15 EGC patients and 15 healthy controls. After a selective immune-depletion to remove high abundance proteins, plasma samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) combined with the tandem mass tags (TMT) labeling.ResultsA total of 2040 proteins were identified, and 11 proteins were found to be differentially expressed. The results of the logistic regression model and orthogonal signal correction-partial least squares discriminant analysis (OPLS-DA) model showed that the changed proteins identified by plasma proteomics could help distinguish EGC patients from healthy controls.ConclusionThe proteins identified by plasma proteomics using LC-MS/MS combined with TMT labeling could help distinguish EGC from healthy controls.     

Proteomics: clinical applications.

The word proteomics was coined in 1997 to describe the changes in all proteins expressed by a genome. Several sophisticated techniques including two-dimensional electrophoresis, imaging, mass spectrometry, and bioinformatics are used in proteomics to identify, quantify, and characterize proteins. Clinical proteomics is the application ofproteomics techniques to the medical field. The main aim of this methodology is to identify proteins involved in pathological processes and to understand how illness can lead to altered protein expression. Clinical proteomics offers the opportunity and the potential to develop new diagnostic and prognostic tests, to identify new therapeutic targets, and eventually to allow the design of individualized patient treatment. Here we present an overview of proteomics applications to the study of disease and its potential to improve diagnosis and prognosis.     

Introduction to proteomics.

Technological advances in the field of genomics have given rise to the development of a new area called proteomics. Proteomics involves the analysis of all proteins expressed in a genome and uses a combination of sophisticated technologies such as two-dimensional electrophoresis, mass spectrometry and bioinformatics to identify and characterize proteins. This new area offers the potential to discover new biomarkers, improve diagnosis, and improve the prognosis of disease processes. This article presents an overview of proteomics importance and related technologies.     

Functional proteomics: mapping protein-protein interactions and pathways

The function of a protein is defined by its interactions with other proteins and molecules. Mapping of protein interactions can highlight new functionalities for a known protein or can even define the function of novel proteins. With the draft sequence of the human genome now available, it is possible to perform high-throughput mapping of protein-protein interactions in humans, which is termed as functional proteomics. The developments in functional proteomics are particularly timely since pharmaceutical companies are searching for technologies that will strengthen their genomic efforts and prioritize their drug discovery pipeline. In this article we review recent developments in functional proteomics.     

基于质谱的蛋白质组学诊断所面临的挑战

过去的几年中,基于质谱技术的蛋白质组学分析方法已经成为寻找新的疾病标志物的重要手段之一.由于它具有高灵敏度、高通量、快速以及能和生物信息学技术结合同时快速分析大量的蛋白质或多肽的优点,使之成为临床研究的有力工具.然而,最近的一些研究显示,因为这项技术的重复性和数据统计分析等方面的不足而受到了争议.本文介绍了采用该方法进行标志物筛查时在实验设计、质谱技术以及数据分析等方面面临的一些挑战,探讨其在血清或血浆分析中的应用.     

Shotgun proteomics: tools for the analysis of complex biological systems

Recent interest in proteomics has been fueled by the completion of multiple genome projects and ignited by the common need of biologists to rapidly and comprehensively evaluate complex samples of proteins on a global level. 'Shotgun proteomics' refers to the direct analysis of complex protein mixtures to rapidly generate a global profile of the protein complement within the mixture. This approach has been facilitated by the use of multidimensional protein identification technology (MudPIT), which incorporates multidimensional high-pressure liquid chromatography (LC/LC), tandem mass spectrometry (MS/MS) and database-searching algorithms. This review will focus on the most recent advances in methodologies for shotgun proteomics and address the limitations of the application of each to real biological samples.     

The application of clinical proteomics to cancer and other diseases.

The term "clinical proteomics" refers to the application of available proteomics technologies to current areas of clinical investigation. The ability to simultaneously and comprehensively examine changes in large numbers of proteins in the context of disease or other changes in physiological conditions holds great promise as a tool to unlock the solutions to difficult clinical research questions. Proteomics is a rapidly growing field that combines high throughput analytical methodologies such as two-dimensional gel electrophoresis and SELDI mass spectrometry methods with complex bioinformatics to study systems biology--the system of interest is defined by the investigator. Even with all its potential, however, studies must be carefully designed in order to differentiate true clinical differences in protein expression from differences originating from variation in sample collection, variation in experimental condition, and normal biological variability. Proteomic analyses are already widely in use for clinical studies ranging from cancer to other diseases such as cardiovascular disease, organ transplant, and pharmacodynamic studies.     

Liver proteomics for therapeutic drug discovery: inhibition of the cyclophilin receptor CD147 attenuates sepsis-induced acute renal failure

OBJECTIVE: Sepsis-induced multi-organ failure continues to have a high mortality. The liver is an organ central to the disease pathogenesis. The objective of this study was to identify the liver proteins that change in abundance with sepsis and subsequently identify new drug targets. DESIGN: Proteomic discovery study and drug target validation. For the proteomics study, three biological replicate mice were used per group. SETTING: Research institute laboratory. SUBJECTS: Three-month-old C57BL/6 mice. INTERVENTIONS: We used a mouse model of sepsis based on cecal ligation and puncture, but with fluid and antibiotic resuscitation. Liver proteins that changed in abundance were identified by difference in gel electrophoresis. We compared liver proteins from 6-hr post-cecal ligation and puncture to sham-operated mice ("early proteins") and 24-hr post-cecal ligation and puncture with 6-hr post-cecal ligation and puncture ("late proteins"). Proteins that changed in abundance were identified by tandem mass spectrometry. We then inhibited the receptor for one protein and determined the effect on sepsis-induced organ dysfunction. RESULTS: The liver proteins that changed in abundance after sepsis had a range of functions such as acute phase response, coagulation, endoplasmic reticulum stress, oxidative stress, apoptosis, mitochondrial electron transfer proteins, and nitric oxide metabolism. We found that cyclophilin increased in abundance after cecal ligation and puncture. When the receptor for this protein, CD147, was inhibited, sepsis-induced renal dysfunction was reduced. There was also a significant reduction in serum cytokine production when CD147 was inhibited. CONCLUSION: By applying proteomics to a clinically relevant mouse model of sepsis, we identified a number of novel proteins that changed in abundance. The inhibition of the receptor for one of these proteins, cyclophilin, attenuated sepsis-induced acute renal failure. The application of proteomics to sepsis research can facilitate the discovery of new therapeutic targets.     

FTICR mass spectrometry in proteomics

Analytical tools that allow rapid screening, low sample consumption and accurate protein identification are of great importance in studies of complex biological samples. Today, mass spectrometry (MS) is a key analytical tools with applications in a wide variety of fields, reaching from the analysis of elemental compositions in various materials to the identification of large protein complexes. One of the fastest growing fields of MS applications is proteomics, or the study of protein expression in an organism. In the traditional proteomic approach, two-dimensional sodium dodecylsulfate polyacrylamide gel electrophoresis is applied for the separation and visualization of proteins. In this review, the use of high resolution Fourier transform ion cyclotron resonance mass spectrometry, including up-front multidimensional liquid separations for 'top down' or 'bottom up' proteomic approaches, are presented.     

Rapid proteome analysis of bronchoalveolar lavage samples of lifelong smokers and never-smokers by micro-scale liquid chromatography and mass spectrometry

BACKGROUND: The aim of this study was to determine whether relative qualitative and quantitative differences in protein expression could be related to smoke exposure or smoke-induced airway inflammation. We therefore explored and characterized the protein components found in bronchoalveolar lavage (BAL) fluid sampled from either lifelong smokers or never-smokers. METHODS: BAL fluid samples obtained by bronchoscopy from 60-year-old healthy never-smokers (n = 18) and asymptomatic smokers (n = 30) were analyzed in either pooled or individual form. Initial global proteomic analysis used shotgun digestion approaches on unfractionated BAL fluid samples (after minimal sample preparation) and separation of peptides by gradient (90-min) liquid chromatography (LC) coupled with on-line linear ion trap quadropole mass spectrometry (LTQ MS) for identification and analysis. RESULTS: LTQ MS identified 481 high- to low-abundance proteins. Relative differences in patterns of BAL fluid proteins in smokers compared with never-smokers were observed in pooled and individual samples as well as by 2-dimensional gel analysis. Gene ontology categorization of all annotated proteins showed a wide spectrum of molecular functions and biological processes. CONCLUSIONS: The described method provides comprehensive qualitative proteomic analysis of BAL fluid protein expression from never-smokers and from smokers at risk of developing chronic obstructive pulmonary disease. Many of the proteins identified had not been detected in previous studies of BAL fluid; thus, the use of LC-tandem MS with LTQ may provide new information regarding potentially important patterns of protein expression associated with lifelong smoking.     

Serum protein fingerprinting

The core technologies in the rapidly expanding field of proteomics have matured to the point where quantitative measurements of thousands of proteins can be conducted, enabling truly global measurements of protein expression. This advent has brought with it the hope of discovering novel biomarkers that promise a renaissance in clinical medicine. To meet this need, many proteomic studies have focused on the identification and subsequent comparative analysis of the thousands of proteins that populate complex biological systems such as serum and tissues. A novel application of mass spectrometry has been in proteomic pattern analysis, which has emerged as an effective method for the early diagnosis of diseases. In stark contrast to 'classical' proteomics, proteomic pattern analysis relies on the pattern of proteins observed, rather than on the discrete identification of a protein. Proteomic pattern technology allows hundreds of clinical samples to be analyzed per day and promises to be a novel, highly sensitive predictive clinical tool to improve diagnostic and prognostic medicine.     

The application of DIGE-based proteomics to renal physiology

Proteomics is seeing increasing use as a means of identifying new mechanistic hypotheses in physiology. Proteomics based on two-dimensional electrophoresis (2-DE) has recently been optimized with the development of Difference Gel Electrophoresis (DIGE). In DIGE-based proteomics, the experimental and control samples are derivatized with different fluorophores and are run in the same gel, thereby minimizing technical variation. DIGE is currently one of the few techniques to perform quantitative proteomics, generating a statistical output to differences in protein abundances. In this review, we discuss the principles of DIGE-based proteomics, including sample preparation, 2-DE, statistical analysis of 2D-gels, and mass spectrometry. Strengths and weaknesses of DIGE are discussed, including possible solutions to overcome certain limitations, such as the identification of low abundance and integral membrane proteins. In addition, we provide a brief synopsis of our recent experiments in which DIGE-based proteomics was applied to study vasopressin signaling in the renal collecting duct. Finally, we illustrate how quantification based on the DIGE approach combined with bioinformatics may facilitate the study of systems biology of the kidney.     

男性不育患者精浆中差异表达蛋白的筛选与鉴定

目的:初步探讨蛋白质组技术在精浆研究中的应用,建立男性少精、无精症患者及健康者精浆双向凝胶电泳图谱;筛查并鉴定三者间的差异表达蛋白质。方法:采用双向凝胶电泳(2-DE)分离少精症、无精症患者和健康者精浆总蛋白,银染显色,ImageMaster 2D Elite软件分析,从中选取差异表达蛋白质,通过基质辅助激光解析电离飞行时间质谱(MALDI-TOF-MS)鉴定差异表达的蛋白质。结果:获得分辨率较好的精浆双向凝胶电泳图谱;得到5个在少精症、无精症患者与健康者精浆中差异有显著性的蛋白质斑点,进行鉴定,结果表明这些特异蛋白分别为Serpin B6(Placental thrombin inhibitor)(Cytoplasmic antiproteinase)(CAP)(Protease inhibitor6)(PI-6)、Septin-1(LARP)(Serologically defined breast cancer antigen NY-BR-24)、Kallikrein-6 precursor(Protease M)(Neurosin)(Zyme)(SP59)、Hemoglobin beta chain、...     

Analysis of albumin-associated peptides and proteins from ovarian cancer patients

BACKGROUND: Albumin binds low-molecular-weight molecules, including proteins and peptides, which then acquire its longer half-life, thereby protecting the bound species from kidney clearance. We developed an experimental method to isolate albumin in its native state and to then identify [mass spectrometry (MS) sequencing] the corresponding bound low-molecular-weight molecules. We used this method to analyze pooled sera from a human disease study set (high-risk persons without cancer, n = 40; stage I ovarian cancer, n = 30; stage III ovarian cancer, n = 40) to demonstrate the feasibility of this approach as a discovery method. METHODS: Albumin was isolated by solid-phase affinity capture under native binding and washing conditions. Captured albumin-associated proteins and peptides were separated by gel electrophoresis and subjected to iterative MS sequencing by microcapillary reversed-phase tandem MS. Selected albumin-bound protein fragments were confirmed in human sera by Western blotting and immunocompetition. RESULTS: In total, 1208 individual protein sequences were predicted from all 3 pools. The predicted sequences were largely fragments derived from proteins with diverse biological functions. More than one third of these fragments were identified by multiple peptide sequences, and more than one half of the identified species were in vivo cleavage products of parent proteins. An estimated 700 serum peptides or proteins were predicted that had not been reported in previous serum databases. Several proteolytic fragments of larger molecules that may be cancer-related were confirmed immunologically in blood by Western blotting and peptide immunocompetition. BRCA2, a 390-kDa low-abundance nuclear protein linked to cancer susceptibility, was represented in sera as a series of specific fragments bound to albumin. CONCLUSION: Carrier-protein harvesting provides a rich source of candidate peptides and proteins with potential diverse tissue and cellular origins that may reflect important disease-related information.     

Proteomics of cryoprotective dehydration in Megaphorura arctica Tullberg 1876 (Onychiuridae: Collembola)

The Arctic springtail, Megaphorura arctica Tullberg 1876 (Onychiuridae: Collembola), is one of the few organisms known to survive the extreme stresses of its environment by using cryoprotective dehydration. We have undertaken a proteomics study comparing M. arctica, acclimated at -2°C, the temperature known to induce the production of the anhydroprotectant trehalose in this species, and -6°C, the temperature at which trehalose expression plateaus, against control animals acclimated at +5°C. Using difference gel electrophoresis, and liquid chromatography tandem mass spectrometry, we identified three categories of differentially expressed proteins with specific functions, up-regulated in both the -2°C and -6°C animals, that were involved in metabolism, membrane transport and protein folding. Proteins involved in cytoskeleton organisation were only up-regulated in the -6°C animals.     

Urinary proteomics

Protein measurement in urine has been used for many years for the diagnosis and monitoring of renal disease. The pattern of urinary protein excretion can be used to identify the cause of the disease and to classify proteinuria. In recent years, proteomics has proven to be a powerful tool in investigation and clinical medicine. Proteomics employs a protein separation method and the identification of proteins using mass spectrometry. One of the objectives of clinical proteomics is the identification of biological markers of disease. To accomplish this, it is necessary to have a normal proteome of the medium in question, which in our case is urine. Comparison of the normal urinary proteome with the urinary proteome from patients with a defined disease can detect proteins expressed differentially from one another. The aim of this review is to present the situation of urinary proteomics, putting special emphasis on its application in the diagnosis of glomerular diseases, renal allograft rejection, urological cancers and urolithiasis.     

Middle-down approach: a choice to sequence and characterize proteins/proteomes by mass spectrometry

Owing to rapid growth in the elucidation of genome sequences of various organisms, deducing proteome sequences has become imperative, in order to have an improved understanding of biological processes. Since the traditional Edman method was unsuitable for high-throughput sequencing and also for N-terminus modified proteins, mass spectrometry (MS) based methods, mainly based on soft ionization modes: electrospray ionization and matrix-assisted laser desorption/ionization, began to gain significance. MS based methods were adaptable for high-throughput studies and applicable for sequencing N-terminus blocked proteins/peptides too. Consequently, over the last decade a new discipline called ‘proteomics’ has emerged, which encompasses the attributes necessary for high-throughput identification of proteins. ‘Proteomics’ may also be regarded as an offshoot of the classic field, ‘biochemistry’. Many protein sequencing and proteomic investigations were successfully accomplished through MS dependent sequence elucidation of ‘short proteolytic peptides (typically: 7–20 amino acid residues), which is called the ‘shotgun’ or ‘bottom-up (BU)’ approach. While the BU approach continues as a workhorse for proteomics/protein sequencing, attempts to sequence intact proteins without proteolysis, called the ‘top-down (TD)’ approach started, due to ambiguities in the BU approach, e.g., protein inference problem, identification of proteoforms and the discovery of posttranslational modifications (PTMs). The high-throughput TD approach (TD proteomics) is yet in its infancy. Nevertheless, TD characterization of purified intact proteins has been useful for detecting PTMs. With the hope to overcome the pitfalls of BU and TD strategies, another concept called the ‘middle-down (MD)’ approach was put forward. Similar to BU, the MD approach also involves proteolysis, but in a restricted manner, to produce ‘longer’ proteolytic peptides than the ones usually obtained in BU studies, thereby providing better sequence coverage. In this regard, special proteases (OmpT, Sap9, IdeS) have been used, which can cleave proteins to produce longer proteolytic peptides. By reviewing ample evidences currently existing in the literature that is predominantly on PTM characterization of histones and antibodies, herein we highlight salient features of the MD approach. Consequently, we are inclined to claim that the MD concept might have widespread applications in future for various research areas, such as clinical, biopharmaceuticals (including PTM analysis) and even for general/routine characterization of proteins including therapeutic proteins, but not just limited to analysis of histones or antibodies.

Enhanced sequence coverage, better identification of combinatorial co-occurring PTMs and improved detection of proteoforms are key highlights of middle-down approach and hence, this can be a promiscuous approach for protein sequencing and proteomics.     

iTRAQ多重标记串联质谱技术在乳腺癌细胞侵袭患者HGF表达中的应用

目的探讨iTRAQ多重标记串联质谱技术应用于检测乳腺癌细胞侵袭患者肝细胞生长因子(HGF)表达差异的临床价值。方法选择该院2014年1月至2016年10月收治的35例乳腺癌患者与30例健康者为研究对象,通过iTRAQ标记、质谱检测、搜库以及Scqffold软件分析不同临床分期乳腺癌患者与健康者血清HGF表达差异,并用Western blot验证HGF的差异表达。结果该研究血清样品中共鉴定出蛋白237个,达到严格定量标准的蛋白89个,乳腺癌患者与健康者共筛选出包括HGF在内的差异表达蛋白17个;iTRAQ多重标记串联质谱图谱显示,乳腺癌患者血清HGF表达水平显著高于健康者,差异有统计学意义(P0.05);Western blot结果显示,不同临床分期HGF相对表达水平显著高于健康者,差异有统计学意义(P0.05)。结论iTRAQ多重标记串联质谱技术有助于发现乳腺癌患者癌细胞高表达HGF,对指导临床治疗乳腺癌具有重要意义。