Quantitative mass spectrometry-based techniques for clinical use: biomarker identification and quantification

Proteomic Characterization of a 3D HER2+ Breast Cancer Model Reveals the Role of Mitochondrial Complex I in Acquired Resistance to Trastuzumab

HER2-targeted therapies, such as Trastuzumab (Tz), have significantly improved the clinical outcomes for patients with HER2+ breast cancer (BC). However, treatment resistance remains a major obstacle. To elucidate functional and metabolic changes associated with acquired resistance, we characterized protein profiles of BC Tz-responder spheroids (RSs) and non-responder spheroids (nRSs) by a proteomic approach. Three-dimensional cultures were generated from the HER2+ human mammary adenocarcinoma cell line BT-474 and a derived resistant cell line. Before and after a 15-day Tz treatment, samples of each condition were collected and analyzed by liquid chromatography-mass spectrometry. The analysis of differentially expressed proteins exhibited the deregulation of energetic metabolism and mitochondrial pathways. A down-regulation of carbohydrate metabolism and up-regulation of mitochondria organization proteins, the tricarboxylic acid cycle, and oxidative phosphorylation, were observed in nRSs. Of note, Complex I-related proteins were increased in this condition and the inhibition by metformin highlighted that their activity is necessary for nRS survival. Furthermore, a correlation analysis showed that overexpression of Complex I proteins NDUFA10 and NDUFS2 was associated with high clinical risk and worse survival for HER2+ BC patients. In conclusion, the non-responder phenotype identified here provides a signature of proteins and related pathways that could lead to therapeutic biomarker investigation.

Cyclic Ion Mobility-Mass Spectrometry and Tandem Collision Induced Unfolding for Quantification of Elusive Protein Biomarkers

Sensitive analytical techniques that are capable of detecting and quantifying disease-associated biomolecules are indispensable in our efforts to understand disease mechanisms and guide therapeutic intervention through early detection, accurate diagnosis, and effective monitoring of disease. Parkinson's Disease (PD), for example, is one of the most prominent neurodegenerative disorders in the world, but the diagnosis of PD has primarily been based on the observation of clinical symptoms. The protein α-synuclein (α-syn) has emerged as a promising biomarker candidate for PD, but a lack of analytical methods to measure complex disease-associated variants of α-syn has prevented its widespread use as a biomarker. Antibody-based methods such as immunoassays and mass spectrometry-based approaches have been used to measure a limited number of α-syn forms; however, these methods fail to differentiate variants of α-syn that display subtle differences in only the sequence and structure. In this work, we developed a cyclic ion mobility-mass spectrometry method that combines multiple stages of activation and timed ion selection to quantify α-syn variants using both mass- and structure-based measurements. This method can allow for the quantification of several α-syn variants present at physiological levels in biological fluid. Taken together, this approach can be used to galvanize future efforts aimed at understanding the underlying mechanisms of PD and serves as a starting point for the development of future protein-structure-based diagnostics and therapeutic interventions.

Altered expression of the L-arginine/nitric oxide pathway in ovarian cancer: metabolic biomarkers and biological implications

MOTIVATION

Ovarian cancer (OC) is a highly lethal gynecological malignancy. Extensive research has shown that OC cells undergo significant metabolic alterations during tumorigenesis. In this study, we aim to leverage these metabolic changes as potential biomarkers for assessing ovarian cancer.

METHODS

A functional module-based approach was utilized to identify key gene expression pathways that distinguish different stages of ovarian cancer (OC) within a tissue biopsy cohort. This cohort consisted of control samples (n = 79), stage I/II samples (n = 280), and stage III/IV samples (n = 1016). To further explore these altered molecular pathways, minimal spanning tree (MST) analysis was applied, leading to the formulation of metabolic biomarker hypotheses for OC liquid biopsy. To validate, a multiple reaction monitoring (MRM) based quantitative LCMS/MS method was developed. This method allowed for the precise quantification of targeted metabolite biomarkers using an OC blood cohort comprising control samples (n = 464), benign samples (n = 3), and OC samples (n = 13).

RESULTS

Eleven functional modules were identified as significant differentiators (false discovery rate, FDR < 0.05) between normal and early-stage, or early-stage and late-stage ovarian cancer (OC) tumor tissues. MST analysis revealed that the metabolic L-arginine/nitric oxide (L-ARG/NO) pathway was reprogrammed, and the modules related to "DNA replication" and "DNA repair and recombination" served as anchor modules connecting the other nine modules. Based on this analysis, symmetric dimethylarginine (SDMA) and arginine were proposed as potential liquid biopsy biomarkers for OC assessment. Our quantitative LCMS/MS analysis on our OC blood cohort provided direct evidence supporting the use of the SDMA-to-arginine ratio as a liquid biopsy panel to distinguish between normal and OC samples, with an area under the ROC curve (AUC) of 98.3%.

CONCLUSION

Our comprehensive analysis of tissue genomics and blood quantitative LC/MSMS metabolic data shed light on the metabolic reprogramming underlying OC pathophysiology. These findings offer new insights into the potential diagnostic utility of the SDMA-to-arginine ratio for OC assessment. Further validation studies using adequately powered OC cohorts are warranted to fully establish the clinical effectiveness of this diagnostic test.

Proteomic Characterization of SAS Cell-Derived Extracellular Vesicles in Relation to Both BPA and Neutron Irradiation Doses

Boron neutron capture therapy (BNCT) is a selective radiotherapy based on nuclear reaction that occurs when ¹⁰B atoms accumulated in cancer cells are irradiated by thermal neutrons, triggering a nuclear fission response leading to cell death. Despite its growing importance in cancer treatment, molecular characterization of its effects is still lacking. In this context, proteomics investigation can be useful to study BNCT effect and identify potential biomarkers. Hence, we performed proteomic analysis with nanoLC-MS/MS (liquid chromatography coupled to tandem mass spectrometry) on extracellular vesicles (EVs) isolated from SAS cultures treated or not with ¹⁰B-boronophenylalanine (BPA) and different doses of neutron irradiation, to study the cellular response related to both boron administration and neutrons action. Despite the interference of fetal bovine serum in the medium, we were able to stratify BPA- and BPA+ conditions and to identify EVs-derived proteins characterizing pathways potentially related to a BNCT effect such as apoptosis, DNA repair and inflammatory response. In particular, KLF11, SERPINA1 and SERPINF2 were up-regulated in BPA+, while POLE and SERPINC1 were up-regulated in BPA-. These results provide the first proteomic investigation of EVs treated with BNCT in different conditions and highlight the potentiality of proteomics for improving biomarkers identification and mechanisms understanding of BNCT.

A plasma proteomic approach in patients with heart failure after acute myocardial infarction: insights into the pathogenesis and progression of the disease

Aims

The pathogenesis of disease progression targets for patients with heart failure after acute myocardial infarction was investigated by using plasma proteomics.

Methods

The plasma proteomes of acute myocardial infarction patients with (MI-HF) and without (MI-WHF) heart failure were compared. Each group consisted of 10 patients who were matched for age and sex. The peptides were analyzed by 2-dimensional liquid chromatography coupled to tandem mass spectrometry in a high definition mode. Parallel reaction monitoring (PRM) verified the selected target proteins.

Results

We identified and quantified 2,589 and 2,222 proteins, respectively, and found 117 differentially expressed proteins (DEPs) (≥1.5-fold), when the MI-HF and MI-WHF groups were compared. Of these 51 and 66 were significantly up-regulated and down-regulated, respectively. The significant DEPs was subjected to protein-protein interaction network analysis which revealed a central role of the NF-κB signaling pathway in the MI-HF patients. PRM verified that MB, DIAPH1, VNN1, GOT2, SLC4A1, CRP, CKM, SOD3, F7, DLD, PGAM2, GOT1, UBA7 and HYOU1 were 14 proteins which were highly expressed in MI-HF patients.

Conclusions

These findings showed a group of proteins related to the NF-κB signaling pathway in the pathogenesis of patients with poor outcomes after experiencing MI-HF. These proteins may be useful candidate markers for the diagnosis of MI-HF as well as help to elucidate the pathophysiology of this major cause of mortality in older patients.

Mass Spectrometry Contribution to Pediatric Cancers Research

For over four decades, mass spectrometry-based methods have provided a wealth of information relevant to various challenges in the field of cancers research. These challenges included identification and validation of novel biomarkers for various diseases, in particular for various forms of cancer. These biomarkers serve various objectives including monitoring patient response to the various forms of therapy, differentiating subgroups of the same type of cancer, and providing proteomic data to complement datasets generated by genomic, epigenetic, and transcriptomic methods. The same proteomic data can be used to provide prognostic information and could guide scientists and medics to new and innovative targeted therapies The past decade has seen a rapid emergence of epigenetics as a major contributor to carcinogenesis. This development has given a fresh momentum to MS-based proteomics, which demonstrated to be an unrivalled tool for the analyses of protein post-translational modifications associated with chromatin modifications. In particular, high-resolution mass spectrometry has been recently used for systematic quantification of chromatin modifications. Data generated by this approach are central in the search for new therapies for various forms of cancer and will help in attempts to decipher antitumor drug resistance. To appreciate the contribution of mass spectrometry-based proteomics to biomarkers discovery and to our understanding of mechanisms behind the initiation and progression of various forms of cancer, a number of recent investigations are discussed. These investigations also include results provided by two-dimensional gel electrophoresis combined with mass spectrometry.

Analysis of milk with liquid chromatography–mass spectrometry: a review

As a widely consumed foodstuff, milk and dairy products are increasingly studied over the years. At the present time, milk profiling is used as a benchmark to assess the properties of milk. Modern biomolecular mass spectrometers have become invaluable to fully characterize the milk composition. This review reports the analysis of milk and its components using liquid chromatography coupled with mass spectrometry (LC–MS). LC–MS analysis as a whole will be discussed subdivided into the major constituents of milk, namely, lipids, proteins, sugars and the mineral fraction.

Systems Biology Approach to Investigate Biomarkers, Boron-10 Carriers, and Mechanisms Useful for Improving Boron Neutron Capture Therapy

Systems biology approach, carried out with high-throughput omics technologies, has become a fundamental aspect of the study of complex diseases like cancer. It can molecularly characterize subjects, physiopathological conditions, and interactions, allowing a precise description, to reach personalized medicine. In particular, proteomics, typically performed with liquid chromatography coupled to mass spectrometry, is a powerful tool for systems biology, giving the possibility to perform diagnosis, patient stratification, and prediction of therapy effects. Boron Neutron Capture Therapy (BNCT) is a selective antitumoral radiotherapy based on a nuclear reaction that occurs when ¹⁰B atoms are irradiated by low-energy thermal neutrons, leading to cell death, thanks to the production of high-energy α particles. Since BNCT is recently becoming an important therapy for the treatment of different types of solid tumors such as gliomas, head and neck cancers, and others, it can take advantage of molecular investigation to improve the understanding of effects and mechanisms and so help its clinical applications. In this context, proteomics can provide a better understanding of mechanisms related to BNCT effect, identify potential biomarkers, and individuate differential responses by specific patients, stratifying responders and nonresponders. Another key aspect of BNCT is the study of new potential Boron-10 carriers to improve the selectivity of Boron delivery to tumors and proteomics can be important in this application, studying the effectiveness of new boron delivery agents, including protein-based carriers, also using computational studies that can investigate new molecules, such as boronated monoclonal antibodies, for improving BNCT.

Alteration of EIF2 Signaling, Glycolysis, and Dopamine Secretion in Form-Deprived Myopia in Response to 1% Atropine Treatment: Evidence From Interactive iTRAQ-MS and SWATH-MS Proteomics Using a Guinea Pig Model

Purpose: Atropine, a non-selective muscarinic antagonist, effectively slows down myopia progression in human adolescents and several animal models. However, the underlying molecular mechanism is unclear. The current study investigated retinal protein changes of form-deprived myopic (FDM) guinea pigs in response to topical administration of 1% atropine gel (10 g/L).

Methods: At the first stage, the differentially expressed proteins were screened using fractionated isobaric tags for a relative and absolute quantification (iTRAQ) approach, coupled with nano-liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS) (n = 24, 48 eyes) using a sample pooling technique. At the second stage, retinal tissues from another cohort with the same treatment (n = 12, 24 eyes) with significant ocular changes were subjected to label-free sequential window acquisition of all theoretical mass spectra (SWATH-MS) proteomics for orthogonal protein target confirmation. The localization of Alpha-synuclein was verified using immunohistochemistry and confocal imaging.

Results: A total of 1,695 proteins (8,875 peptides) were identified with 479 regulated proteins (FC ≥ 1.5 or ≤0.67) found from FDM eyes and atropine-treated eyes receiving 4-weeks drug treatment using iTRAQ-MS proteomics. Combining the iTRAQ-MS and SWATH-MS datasets, a total of 29 confident proteins at 1% FDR were consistently quantified and matched, comprising 12 up-regulated and 17 down-regulated proteins which differed between FDM eyes and atropine treated eyes (iTRAQ: FC ≥ 1.5 or ≤0.67, SWATH: FC ≥ 1.4 or ≤0.71, p-value of ≤0.05). Bioinformatics analysis using IPA and STRING databases of these commonly regulated proteins revealed the involvement of the three commonly significant pathways: EIF2 signaling; glycolysis; and dopamine secretion. Additionally, the most significantly regulated proteins were closely connected to Alpha-synuclein (SNCA). Using immunostaining (n = 3), SNCA was further confirmed in the inner margin of the inner nuclear layer (INL) and spread throughout the inner plexiform layer (IPL) of the retina of guinea pigs.

Conclusion: The molecular evidence using next-generation proteomics (NGP) revealed that retinal EIF2 signaling, glycolysis, and dopamine secretion through SNCA are implicated in atropine treatment of myopia in the FDM-induced guinea pig model.

Discovery and Evaluation of Protein Biomarkers as a Signature of Wellness in Late-Stage Cancer Patients in Early Phase Clinical Trials

TARGET (tumour characterisation to guide experimental targeted therapy) is a cancer precision medicine programme focused on molecular characterisation of patients entering early phase clinical trials. Performance status (PS) measures a patient's ability to perform a variety of activities. However, the quality of present algorithms to assess PS is limited and based on qualitative clinician assessment. Plasma samples from patients enrolled into TARGET were analysed using the mass spectrometry (MS) technique: sequential window acquisition of all theoretical fragment ion spectra (SWATH)-MS. SWATH-MS was used on a discovery cohort of 55 patients to differentiate patients into either a good or poor prognosis by creation of a Wellness Score (WS) that showed stronger prediction of overall survival (p = 0.000551) compared to PS (p = 0.001). WS was then tested against a validation cohort of 77 patients showing significant (p = 0.000451) prediction of overall survival. WS in both sets had receiver operating characteristic curve area under the curve (AUC) values of 0.76 (p = 0.002) and 0.67 (p = 0.011): AUC of PS was 0.70 (p = 0.117) and 0.55 (p = 0.548). These signatures can now be evaluated further in larger patient populations to assess their utility in a clinical setting.

Clinical Assay for the Early Detection of Colorectal Cancer Using Mass Spectrometric Wheat Germ Agglutinin Multiple Reaction Monitoring

Simple Summary

Colorectal cancer (CRC) is currently the third leading cause of cancer death worldwide. Early diagnosis of CRC is important for increasing the opportunity for treatment and receiving a good prognosis. The aim of our study was to develop a detection method that combined wheat germ agglutinin (WGA) chromatography with mass spectrometry (MS) for early detection of CRC. Further, machine learning algorithms and logistic regression were applied to combine multiple biomarkers we discovered. We validated in a population of 286 plasma samples the diagnostic performance of peptides corresponding to WGA-captured protein and its combination, which received a sensitivity of 84.5% and a specificity of 97.5% in the diagnoses of CRC. Proteomic biomarkers combined with algorithms can provide a powerful tool for discriminating patients with CRC and health controls (HCs). Measurements of WGA-captured PF4, ITIH4, and APOE with MS are then useful for early detection of CRC. Additionally, our study revealed the potential of applying lectin chromatography with MS for disease diagnosis.

Abstract

Colorectal cancer (CRC) is currently the third leading cause of cancer-related mortality in the world. U.S. Food and Drug Administration-approved circulating tumor markers, including carcinoembryonic antigen, carbohydrate antigen (CA) 19-9 and CA125 were used as prognostic biomarkers of CRC that attributed to low sensitivity in diagnosis of CRC. Therefore, our purpose is to develop a novel strategy for novel clinical biomarkers for early CRC diagnosis. We used mass spectrometry (MS) methods such as nanoLC-MS/MS, targeted LC-MS/MS, and stable isotope-labeled multiple reaction monitoring (MRM) MS coupled to test machine learning algorithms and logistic regression to analyze plasma samples from patients with early-stage CRC, late-stage CRC, and healthy controls (HCs). On the basis of our methods, 356 peptides were identified, 6 differential expressed peptides were verified, and finally three peptides corresponding wheat germ agglutinin (WGA)-captured proteins were semi-quantitated in 286 plasma samples (80 HCs and 206 CRCs). The novel peptide biomarkers combination of PF4^54–62, ITIH4^429–438, and APOE^198–207 achieved sensitivity 84.5%, specificity 97.5% and an AUC of 0.96 in CRC diagnosis. In conclusion, our study demonstrated that WGA-captured plasma PF4^54–62, ITIH4^429–438, and APOE^198–207 levels in combination may serve as highly effective early diagnostic biomarkers for patients with CRC.

Nano dot blot: An alternative technique for protein identification and quantification in a high throughput format

BACKGROUND

Dot blot technique has been used in a similar way to western blotting, with the major difference being the lack of protein separation with electrophoresis. Protein samples are spotted over a membrane paper, the identification and quantification of a protein is achieved by immunodetection procedures such as colorimetry, fluorescence or chemiluminescence. This technique is widely accepted, but it uses large amounts of sample and antibodies to reveal the presence of the target protein. Significant milestones have been reached to achieve better results with the use of less sample and reagents; however, the ninety-six-well format is still in use.

NEW METHOD

In this work, we propose an innovation to this technique, reducing the amount of sample and antibodies to identify a specific protein when compared to the regular dot blot method. Procedure consists of using a sample volume of approximately 200 nanoliters deposited with a multineedle device developed by our group.

RESULTS

Five samples of standard protein or antigen can be spotted in a Cartesian format to identify and quantify the protein involved in physiological or pathological conditions. In addition, at least five replicates of sample or antigen are used to enable better statistics to calculate the concentration of every standard and the protein present in a sample.

CONCLUSIONS

Hundreds of samples can be deposited in a few minutes and analyzed in a single experimental session. To validate this method, which we called nano dot blot, six proteins involved in the inflammation process were tested in acute and chronic rat models of seizures.

iTRAQ-based proteome profiling revealed the role of Phytochrome A in regulating primary metabolism in tomato seedling

In plants, during growth and development, photoreceptors monitor fluctuations in their environment and adjust their metabolism as a strategy of surveillance. Phytochromes (Phys) play an essential role in plant growth and development, from germination to fruit development. FR-light (FR) insensitive mutant (fri) carries a recessive mutation in Phytochrome A and is characterized by the failure to de-etiolate in continuous FR. Here we used iTRAQ-based quantitative proteomics along with metabolomics to unravel the role of Phytochrome A in regulating central metabolism in tomato seedlings grown under FR. Our results indicate that Phytochrome A has a predominant role in FR-mediated establishment of the mature seedling proteome. Further, we observed temporal regulation in the expression of several of the late response proteins associated with central metabolism. The proteomics investigations identified a decreased abundance of enzymes involved in photosynthesis and carbon fixation in the mutant. Profound accumulation of storage proteins in the mutant ascertained the possible conversion of sugars into storage material instead of being used or the retention of an earlier profile associated with the mature embryo. The enhanced accumulation of organic sugars in the seedlings indicates the absence of photomorphogenesis in the mutant.

THE PRESENT AND FUTURE OF THE MASS SPECTROMETRY-BASED INVESTIGATION OF THE EXOSOME LANDSCAPE

Exosomes are critical intercellular messengers released upon the fusion of multivesicular bodies with the cellular plasma membrane that deliver their cargo in the form of extracellular vesicles. Containing numerous nonrandomly packed functional proteins, lipids, and RNAs, exosomes are vital intercellular messengers that contribute to the physiologic processes of the healthy organism. During the post-genome era, exosome-oriented proteomics have garnered great interest. Since its establishment, mass spectrometry (MS) has been indispensable for the field of proteomics research and has advanced rapidly to interrogate biological samples at a higher resolution and sensitivity. Driven by new methodologies and more advanced instrumentation, MS-based approaches have revolutionized our understanding of protein biology. As the access to online proteomics database platforms has blossomed, experimental data processing occurs with more speed and accuracy. Here, we review recent advances in the technological progress of MS-based proteomics and several new detection strategies for MS-based proteomics research. We also summarize the use of integrated online databases for proteomics research in the era of big data. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Putative serum protein biomarkers for epsilon toxin exposure in mouse model using LC-MS/MS analysis

Epsilon toxin (ETX), produced by Clostridium perfringens Type B or type D strains, is a potential biological and toxin warfare (BTW) agent, largely for its very high toxicity. The toxin is implicated in several animal diseases. Using LC-MS/MS analysis, we report here elucidation of putative serum maker proteins for ETX exposure with an objective of the early diagnosis of intoxication. Of 166 consensus proteins (488 peptides), showing ETX-induced alterations, 119 proteins exhibited increase and 47 proteins showed decreased abundance in serum, as revealed by SWATH (DIA) acquisition on LC-MS/MS and label free quantitative analysis of control and test samples. Complement and coagulation cascade, nitrogen metabolism, negative regulation of peptidase activity, and response to ROS were among the biological processes and pathways perturbed by the ETX exposure. Interaction network indicated enzyme inhibitor activity, detoxification of ROS, and steroid binding functions were the major interaction networks for the proteins with increased abundance, while, hemostasis and structural molecule activity were the prominent networks for the down-regulated proteins. Validation studies were carried out by immunoprecipitation, ELISA, and Western blot analysis of selected proteins to demonstrate diagnostic potential of the putative marker proteins of ETX exposure.

Plasma proteome profiling of freshwater and seawater life stages of rainbow trout (Oncorhynchus mykiss)

The sea-run phenotype of rainbow trout (Oncorhynchus mykiss), like other anadromous salmonids, present a juvenile stage fully adapted to life in freshwater known as parr. Development in freshwater is followed by the smolt stage, where preadaptations needed for seawater life are developed making fish ready to migrate to the ocean, after which event they become post-smolts. While these three life stages have been studied using a variety of approaches, proteomics has never been used for such purpose. The present study characterised the blood plasma proteome of parr, smolt and post-smolt rainbow trout using a gel electrophoresis liquid chromatography tandem mass spectrometry approach alone or in combination with low-abundant protein enrichment technology (combinatorial peptide ligand library). In total, 1,822 proteins were quantified, 17.95% of them being detected only in plasma post enrichment. Across all life stages, the most abundant proteins were ankyrin-2, DNA primase large subunit, actin, serum albumin, apolipoproteins, hemoglobin subunits, hemopexin-like proteins and complement C3. When comparing the different life stages, 17 proteins involved in mechanisms to cope with hyperosmotic stress and retinal changes, as well as the downregulation of nonessential processes in smolts, were significantly different between parr and smolt samples. On the other hand, 11 proteins related to increased growth in post-smolts, and also related to coping with hyperosmotic stress and to retinal changes, were significantly different between smolt and post-smolt samples. Overall, this study presents a series of proteins with the potential to complement current seawater-readiness assessment tests in rainbow trout, which can be measured non-lethally in an easily accessible biofluid. Furthermore, this study represents a first in-depth characterisation of the rainbow trout blood plasma proteome, having considered three life stages of the fish and used both fractionation alone or in combination with enrichment methods to increase protein detection.

Elucidation of protein biomarkers in plasma and urine for epsilon toxin exposure in mouse model

Epsilon toxin (ETX) is the major virulence determinant of C. perfringens type B or type D strains, causing diseases in animals, besides being a listed biological and toxin warfare (BTW) agent. Keeping in mind the high lethality and the rapid onset of clinical manifestations, early diagnosis of epsilon toxin exposure is of paramount importance for implementation of appropriate medical countermeasures. Using a 2DE-MS approach, the present study is the first comprehensive proteomic elucidation of ETX-induced protein markers in the mouse model, providing putative targets for early diagnosis of ETX exposure. A total of 52 unique proteins showing ETX-induced modulations were identified in plasma and urine samples. Fibrinogen, apolipoprotein, serum amyloid protein, plasminogen, serum albumin, glutathione peroxidase, transferrin, major urinary protein 2, haptoglobin, transthyretin, and vitamin D-binding protein were among the proteins observed in more than one dataset with altered abundance after the ETX-intoxication. The predicted localization, function, and interaction of the ETX-modulated proteins in the plasma and urine indicated involvement of multiple pathways; extracellular proteins, followed by macromolecular complexes associated with blood coagulation and plasminogen activating cascade, being the most prominent among others. The putative markers elucidated here warrants further validation and can be of immense value for the early diagnosis of ETX exposure.

Trends in the Design of New Isobaric Labeling Reagents for Quantitative Proteomics

Modern mass spectrometry is one of the most frequently used methods of quantitative proteomics, enabling determination of the amount of peptides in a sample. Although mass spectrometry is not inherently a quantitative method due to differences in the ionization efficiency of various analytes, the application of isotope-coded labeling allows relative quantification of proteins and proteins. Over the past decade, a new method for derivatization of tryptic peptides using isobaric labels has been proposed. The labels consist of reporter and balanced groups. They have the same molecular weights and chemical properties, but differ in the distribution of stable heavy isotopes. These tags are designed in such a way that during high energy collision induced dissociation (CID) by tandem mass spectrometry, the isobaric tag is fragmented in the specific linker region, yielding reporter ions with different masses. The mass shifts among the reporter groups are compensated by the balancing groups so that the overall mass is the same for all forms of the reagent. Samples of peptides are labeled with the isobaric mass tags in parallel and combined for analysis. Quantification of individual peptides is achieved by comparing the intensity of reporter ions in the tandem mass (MS/MS) spectra. Isobaric markers have found a wide range of potential applications in proteomics. However, the currently available isobaric labeling reagents have some drawbacks, such as high cost of production, insufficient selectivity of the derivatization, and relatively limited enhancement of sensitivity of the analysis. Therefore, efforts have been devoted to the development of new isobaric markers with increased usability. The search for new isobaric markers is focused on developing a more selective method of introducing a tag into a peptide molecule, increasing the multiplexicity of markers, lowering the cost of synthesis, and increasing the sensitivity of measurement by using ionization tags containing quaternary ammonium salts. Here, the trends in the design of new isobaric labeling reagents for quantitative proteomics isobaric derivatization strategies in proteomics are reviewed, with a particular emphasis on isobaric ionization tags. The presented review focused on different types of isobaric reagents used in quantitative proteomics, their chemistry, and advantages offer by their application.

Proteomic Studies of Psychiatric Disorders

Many diseases result from programming effects in utero. This chapter describes recent advances in proteomic studies which have improved our understanding of the underlying pathophysiological pathways in the major psychiatric disorders, resulting in the development of potential novel biomarker tests. Such tests should be based on measurement of blood-based proteins given the ease of accessibility of this medium and the known connections between the periphery and the central nervous system. Most importantly, emerging biomarker tests should be developed on lab-on-a-chip and other handheld devices to enable point-of-care use. This should help to identify individuals with psychiatric disorders much sooner than ever before, which will allow more rapid treatment options for the best possible patient outcomes.

Application of stable isotope dimethyl labeling for MRM based absolute antigen quantification of influenza vaccine

Determining the precursor/product ion pair and optimal collision energy are the critical steps for developing a multiple reaction monitoring (MRM) assay using triple quadruple mass spectrometer for protein quantitation. In this study, a platform consisting of stable isotope dimethyl labeling coupled with triple-quadruple mass spectrometer was used to quantify the protein components of the influenza vaccines. Dimethyl labeling of both the peptide N-termini and the ϵ-amino group of lysine residues was achieved by reductive amination using formaldehyde and sodium cyanoborohydrate. Dimethylated peptides are known to exhibit dominant a1 ions under gas phase fragmentation in a mass spectrometer. These a1 ions can be predicted from the peptide N-terminal amino acids, and their signals do not vary significantly across a wide range of collision energies, which facilitates the determination of MRM transition settings for multiple protein targets. The intrinsic a1 ions provide sensitivity for acquiring MRM peaks that is superior to that of the typical b/y ions used for native peptides, and they also provided good linearity (R² ≥ 0.99) at the detected concentration range for each peptide. These features allow for the simultaneous quantification of hemagglutinin and neuraminidase in vaccines derived from either embryo eggs or cell cultivation. Moreover, the low abundant ovalbumin residue originated from the manufacturing process can also be determined. The results demonstrate that the stable isotope dimethyl labeling coupled with MRM Mass spectrometry screening of a1 ions (i.e., SIDa-MS) can be used as a high-throughput platform for multiple protein quantification of vaccine products.

Real-time iTRAQ-based proteome profiling revealed the central metabolism involved in nitrogen starvation induced lipid accumulation in microalgae

To understand the post-transcriptional molecular mechanisms attributing to oleaginousness in microalgae challenged with nitrogen starvation (N-starvation), the longitudinal proteome dynamics of Chlorella sp. FC2 IITG was investigated using multipronged quantitative proteomics and multiple reaction monitoring assays. Physiological data suggested a remarkably enhanced lipid accumulation with concomitant reduction in carbon flux towards carbohydrate, protein and chlorophyll biosynthesis. The proteomics-based investigations identified the down-regulation of enzymes involved in chlorophyll biosynthesis (porphobilinogen deaminase) and photosynthetic carbon fixation (sedoheptulose-1,7 bisphosphate and phosphoribulokinase). Profound up-regulation of hydroxyacyl-ACP dehydrogenase and enoyl-ACP reductase ascertained lipid accumulation. The carbon skeletons to be integrated into lipid precursors were regenerated by glycolysis, β-oxidation and TCA cycle. The enhanced expression of glycolysis and pentose phosphate pathway enzymes indicates heightened energy needs of FC2 cells for the sustenance of N-starvation. FC2 cells strategically reserved nitrogen by incorporating it into the TCA-cycle intermediates to form amino acids; particularly the enzymes involved in the biosynthesis of glutamate, aspartate and arginine were up-regulated. Regulation of arginine, superoxide dismutase, thioredoxin-peroxiredoxin, lipocalin, serine-hydroxymethyltransferase, cysteine synthase, and octanoyltransferase play a critical role in maintaining cellular homeostasis during N-starvation. These findings may provide a rationale for genetic engineering of microalgae, which may enable synchronized biomass and lipid synthesis.

Global Cell Proteome Profiling, Phospho-signaling and Quantitative Proteomics for Identification of New Biomarkers in Acute Myeloid Leukemia Patients

The identification of protein biomarkers for acute myeloid leukemia (AML) that could find applications in AML diagnosis and prognosis, treatment and the selection for bone marrow transplant requires substantial comparative analyses of the proteomes from AML patients. In the past years, several studies have suggested some biomarkers for AML diagnosis or AML classification using methods for sample preparation with low proteome coverage and low resolution mass spectrometers. However, most of the studies did not follow up, confirm or validate their candidates with more patient samples. Current proteomics methods, new high resolution and fast mass spectrometers allow the identification and quantification of several thousands of proteins obtained from few tens of μg of AML cell lysate. Enrichment methods for posttranslational modifications (PTM), such as phosphorylation, can isolate several thousands of site-specific phosphorylated peptides from AML patient samples, which subsequently can be quantified with high confidence in new mass spectrometers. While recent reports aiming to propose proteomic or phosphoproteomic biomarkers on the studied AML patient samples have taken advantage of the technological progress, the access to large cohorts of AML patients to sample from and the availability of appropriate control samples still remain challenging.

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.

Biomarker detection technologies and future directions

Biomarkers play a vital role in disease detection and treatment follow-up. It is important to note that diseases in the early stage are typically treated with the greatest probability of success. However, due to various technical difficulties in current technologies for the detection of biomarkers, the potential of biomarkers is not explored completely. Therefore, the developments of technologies, which can enable the accurate detection of prostate cancer at an early stage with simple, experimental protocols are highly inevitable. This critical review evaluates the current methods and technologies used in the detection of biomarkers. The aim of this article is to provide a comprehensive review covering the advantages and disadvantages of the biomarker detection methods. Future directions for the development of technologies to achieve highly selective and sensitive detection of biomarkers for point-of-care applications are also commented on.

Differential expression of serum/plasma proteins in various infectious diseases: specific or nonspecific signatures

Apart from direct detection of the infecting organisms or biomarker of the pathogen itself, surrogate host markers are also useful for sensitive and early diagnosis of pathogenic infections. Early detection of pathogenic infections, discrimination among closely related diseases with overlapping clinical manifestations, and monitoring of disease progression can be achieved by analyzing blood biomarkers. Therefore, over the last decade large numbers of proteomics studies have been conducted to identify differentially expressed human serum/plasma proteins in different infectious diseases with the intent of discovering novel potential diagnostic/prognostic biomarkers. However, in-depth review of the literature indicates that many reported biomarkers are altered in the same way in multiple infectious diseases, regardless of the type of infection. This might be a consequence of generic acute phase reactions, while the uniquely modulated candidates in different pathogenic infections could be indicators of some specific responses. In this review article, we will provide a comprehensive analysis of differentially expressed serum/plasma proteins in various infectious diseases and categorize the protein markers associated with generic or specific responses. The challenges associated with the discovery, validation, and translational phases of serum/plasma biomarker establishment are also discussed.

Global combined precursor isotopic labeling and isobaric tagging (cPILOT) approach with selective MS(3) acquisition

Recently, we reported a novel proteomics quantitation scheme termed "combined precursor isotopic labeling and isobaric tagging (cPILOT)" that allows for the identification and quantitation of nitrated peptides in as many as 12-16 samples in a single experiment. cPILOT offers enhanced multiplexing and posttranslational modification specificity, however excludes global quantitation for all peptides present in a mixture and underestimates reporter ion ratios similar to other isobaric tagging methods due to precursor co-isolation. Here, we present a novel chemical workflow for cPILOT that can be used for global tagging of all peptides in a mixture. Specifically, through low pH precursor dimethylation of tryptic or LysC peptides followed by high pH tandem mass tags, the same reporter ion can be used twice in a single experiment. Also, to improve triple-stage mass spectrometry (MS(3) ) data acquisition, a selective MS(3) method that focuses on product selection of the y1 fragment of lysine-terminated peptides is incorporated into the workflow. This novel cPILOT workflow has potential for global peptide quantitation that could lead to enhanced sample multiplexing and increase the number of quantifiable spectra obtained from MS(3) acquisition methods.

A caspase-3 'death-switch' in colorectal cancer cells for induced and synchronous tumor apoptosis in vitro and in vivo facilitates the development of minimally invasive cell death biomarkers

Novel anticancer drugs targeting key apoptosis regulators have been developed and are undergoing clinical trials. Pharmacodynamic biomarkers to define the optimum dose of drug that provokes tumor apoptosis are in demand; acquisition of longitudinal tumor biopsies is a significant challenge and minimally invasive biomarkers are required. Considering this, we have developed and validated a preclinical 'death-switch' model for the discovery of secreted biomarkers of tumour apoptosis using in vitro proteomics and in vivo evaluation of the novel imaging probe [(18)F]ML-10 for non-invasive detection of apoptosis using positron emission tomography (PET). The 'death-switch' is a constitutively active mutant caspase-3 that is robustly induced by doxycycline to drive synchronous apoptosis in human colorectal cancer cells in vitro or grown as tumor xenografts. Death-switch induction caused caspase-dependent apoptosis between 3 and 24 hours in vitro and regression of 'death-switched' xenografts occurred within 24 h correlating with the percentage of apoptotic cells in tumor and levels of an established cell death biomarker (cleaved cytokeratin-18) in the blood. We sought to define secreted biomarkers of tumor apoptosis from cultured cells using Discovery Isobaric Tag proteomics, which may provide candidates to validate in blood. Early after caspase-3 activation, levels of normally secreted proteins were decreased (e.g. Gelsolin and Midkine) and proteins including CD44 and High Mobility Group protein B1 (HMGB1) that were released into cell culture media in vitro were also identified in the bloodstream of mice bearing death-switched tumors. We also exemplify the utility of the death-switch model for the validation of apoptotic imaging probes using [(18)F]ML-10, a PET tracer currently in clinical trials. Results showed increased tracer uptake of [(18)F]ML-10 in tumours undergoing apoptosis, compared with matched tumour controls imaged in the same animal. Overall, the death-switch model represents a robust and versatile tool for the discovery and validation of apoptosis biomarkers.

Current status and advances in quantitative proteomic mass spectrometry

The accurate quantitation of proteins and peptides in complex biological systems is one of the most challenging areas of proteomics. Mass spectrometry-based approaches have forged significant in-roads allowing accurate and sensitive quantitation and the ability to multiplex vastly complex samples through the application of robust bioinformatic tools. These relative and absolute quantitative measures using label-free, tags, or stable isotope labelling have their own strengths and limitations. The continuous development of these methods is vital for increasing reproducibility in the rapidly expanding application of quantitative proteomics in biomarker discovery and validation. This paper provides a critical overview of the primary mass spectrometry-based quantitative approaches and the current status of quantitative proteomics in biomedical research.

Processing of Mass Spectrometry Data in Clinical Applications

Mass spectrometry-based proteomics has become the leading approach for analyzing complex biological samples at a large-scale level. Its importance for clinical applications is more and more increasing, thanks to the development of high-performing instruments which allow the discovery of disease-specific biomarkers and an automated and rapid protein profiling of the analyzed samples. In this scenario, the large-scale production of proteomic data has driven the development of specific bioinformatic tools to assist researchers during the discovery processes. Here, we discuss the main methods, algorithms, and procedures to identify and use biomarkers for clinical and research purposes. In particular, we have been focused on quantitative approaches, the identification of proteotypic peptides, and the classification of samples, using proteomic data. Finally, this chapter is concluded by reporting the integration of experimental data with network datasets, as valuable instrument for identifying alterations that underline the emergence of specific phenotypes. Based on our experience, we show some examples taking into consideration experimental data obtained by multidimensional protein identification technology (MudPIT) approach.

Clinical neuroproteomics and biomarkers: from basic research to clinical decision making

Clinical neuroproteomics aims to advance our understanding of disease and injury affecting the central and peripheral nervous systems through the study of protein expression and the discovery of protein biomarkers to facilitate diagnosis and treatment. The general premise of the biomarker field is that in vivo factors present in either tissue or circulating biofluids, reflect pathological changes, and can be identified and analyzed. This approach offers an opportunity to illuminate changes occurring at both the population and patient levels toward the realization of personalized medicine. This review is intended to provide research-driven clinicians with an overview of protein biomarkers of disease and injury for clinical use and to highlight methodology and potential pitfalls. We examine the neuroproteomic biomarker field and discuss the hallmarks and the challenges of clinically relevant biomarker discovery relating to central nervous system pathology. We discuss the issues in the maturation of potential biomarkers from discovery to Food and Drug Administration approval and review several platforms for protein biomarker discovery, including protein microarray and mass spectrometry-based proteomics. We describe the application of microfluidic technologies to the evolution of a robust clinical test. Finally, we highlight several biomarkers currently in use for cancer, ischemia, and injury in the central nervous system. Future efforts using these technologies will result in the maturation of existing and the identification of de novo biomarkers that could guide clinical decision making and advance diagnostic and therapeutic options for the treatment of neurological disease and injury.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.

Detection of biomarkers using recombinant antibodies coupled to nanostructured platforms

The utility of biomarker detection in tomorrow's personalized health care field will mean early and accurate diagnosis of many types of human physiological conditions and diseases. In the search for biomarkers, recombinant affinity reagents can be generated to candidate proteins or post-translational modifications that differ qualitatively or quantitatively between normal and diseased tissues. The use of display technologies, such as phage-display, allows for manageable selection and optimization of affinity reagents for use in biomarker detection. Here we review the use of recombinant antibody fragments, such as scFvs and Fabs, which can be affinity-selected from phage-display libraries, to bind with both high specificity and affinity to biomarkers of cancer, such as Human Epidermal growth factor Receptor 2 (HER2) and Carcinoembryonic antigen (CEA). We discuss how these recombinant antibodies can be fabricated into nanostructures, such as carbon nanotubes, nanowires, and quantum dots, for the purpose of enhancing detection of biomarkers at low concentrations (pg/mL) within complex mixtures such as serum or tissue extracts. Other sensing technologies, which take advantage of 'Surface Enhanced Raman Scattering' (gold nanoshells), frequency changes in piezoelectric crystals (quartz crystal microbalance), or electrical current generation and sensing during electrochemical reactions (electrochemical detection), can effectively provide multiplexed platforms for detection of cancer and injury biomarkers. Such devices may soon replace the traditional time consuming ELISAs and Western blots, and deliver rapid, point-of-care diagnostics to market.

Proteomic analyses of host and pathogen responses during bovine mastitis

The pursuit of biomarkers for use as clinical screening tools, measures for early detection, disease monitoring, and as a means for assessing therapeutic responses has steadily evolved in human and veterinary medicine over the past two decades. Concurrently, advances in mass spectrometry have markedly expanded proteomic capabilities for biomarker discovery. While initial mass spectrometric biomarker discovery endeavors focused primarily on the detection of modulated proteins in human tissues and fluids, recent efforts have shifted to include proteomic analyses of biological samples from food animal species. Mastitis continues to garner attention in veterinary research due mainly to affiliated financial losses and food safety concerns over antimicrobial use, but also because there are only a limited number of efficacious mastitis treatment options. Accordingly, comparative proteomic analyses of bovine milk have emerged in recent years. Efforts to prevent agricultural-related food-borne illness have likewise fueled an interest in the proteomic evaluation of several prominent strains of bacteria, including common mastitis pathogens. The interest in establishing biomarkers of the host and pathogen responses during bovine mastitis stems largely from the need to better characterize mechanisms of the disease, to identify reliable biomarkers for use as measures of early detection and drug efficacy, and to uncover potentially novel targets for the development of alternative therapeutics. The following review focuses primarily on comparative proteomic analyses conducted on healthy versus mastitic bovine milk. However, a comparison of the host defense proteome of human and bovine milk and the proteomic analysis of common veterinary pathogens are likewise introduced.

Identification and quantification of peptides and proteins secreted from prostate epithelial cells by unbiased liquid chromatography tandem mass spectrometry using goodness of fit and analysis of variance

The proteins secreted by prostate cancer cells (PC3(AR)6) were separated by strong anion exchange chromatography, digested with trypsin and analyzed by unbiased liquid chromatography tandem mass spectrometry with an ion trap. The spectra were matched to peptides within proteins using a goodness of fit algorithm that showed a low false positive rate. The parent ions for MS/MS were randomly and independently sampled from a log-normal population and therefore could be analyzed by ANOVA. Normal distribution analysis confirmed that the parent and fragment ion intensity distributions were sampled over 99.9% of their range that was above the background noise. Arranging the ion intensity data with the identified peptide and protein sequences in structured query language (SQL) permitted the quantification of ion intensity across treatments, proteins and peptides. The intensity of 101,905 fragment ions from 1421 peptide precursors of 583 peptides from 233 proteins separated over 11 sample treatments were computed together in one ANOVA model using the statistical analysis system (SAS) prior to Tukey-Kramer honestly significant difference (HSD) testing. Thus complex mixtures of proteins were identified and quantified with a high degree of confidence using an ion trap without isotopic labels, multivariate analysis or comparing chromatographic retention times.

SELDI-TOF MS analysis of alkylphenol exposed Atlantic cod with phenotypic variation in gonadosomatic index

Proteomics is a new and promising approach to evaluate potential effects of pollution. In order to investigate if there is a direct link between the protein expression profiles obtained by the SELDI-TOF MS technology and effects observed at the organism level in fish, plasma samples from unexposed and 20 ppb alkylphenol exposed female Atlantic cod (Gadus morhua) with high phenotypic variation in gonadosomatic index (GSI) were analyzed by SELDI-TOF MS. Principle component analysis (PCA) showed that the major proteomic variation present in the dataset (i.e. 23.6%) could be significantly correlated to the individual variation in GSI, which indicates that SELDI-TOF MS data can reflect effects observed at higher levels of organization in fish. Further exploration of the other principal components revealed an additional proteomic pattern specific for the alkylphenol exposed females. Hence, this study supports the usefulness of SELDI-TOF MS as a proteomic tool in ecotoxicological research.

Qualitative and quantitative multiplexed proteomic analysis of complex yeast protein fractions that modulate the assembly of the yeast prion Sup35p

Background

The aggregation of the baker's yeast prion Sup35p is at the origin of the transmissible [PSI⁺] trait. We and others have shown that molecular chaperones modulate Sup35p aggregation. However, other protein classes might be involved in [PSI⁺] formation.

Results

We designed a functional proteomic study that combines two techniques to identify modulators of Sup35p aggregation and describe the changes associated to [PSI⁺] formation. The first allows measuring the effect of fractionated Saccharomyces cerevisiae cytosolic extracts from [PSI⁺] and [psi⁻] yeast cells on Sup35p assembly. The second is a multiplex qualitative and quantitative comparison of protein composition of active and inactive fractions using a gel-free and label-free LC-MS approach. We identify changes in proteins involved in translation, folding, degradation, oxido-reduction and metabolic processes.

Conclusion

Our functional proteomic study provides the first inventory list of over 300 proteins that directly or indirectly affect Sup35p aggregation and [PSI⁺] formation. Our results highlight the complexity of the cellular changes accompanying [PSI⁺] formation and pave the way for in vitro studies aimed to document the effect of individual and/or combinations of proteins identified here, susceptible of affecting Sup35p assembly.

Searching for the noninvasive biomarker holy grail: are urine proteomics the answer?

Recently, biobehavioral nursing scientists have focused their attention on the search for biomarkers or biological signatures to identify patients at risk for various health problems and poor disease outcomes. In response to the national impetus for biomarker discovery, the measurement of biological fluids and tissues has become increasingly sophisticated. Urine proteomics, in particular, may hold great promise for biobehavioral focused nursing scientists for examination of symptom-and syndrome-related research questions. Urine proteins are easily accessible secreted proteins that provide direct and indirect windows into bodily functions. Advances in proteomics and biomarker discovery provide new opportunities to conduct research studies with banked and fresh urine to benefit diagnosis, prognosis, and evaluation of outcomes in various disease populations. This article provides a review of proteomics and a rationale for utilizing urine proteomics in biobehavioral research. It addresses as well some of the challenges involved in data collection and sample preparation.

Proteomic technologies for the identification of disease biomarkers in serum: advances and challenges ahead

Serum is an ideal biological sample that contains an archive of information due to the presence of a variety of proteins released by diseased tissue, and serum proteomics has gained considerable interest for the disease biomarker discovery. Easy accessibility and rapid protein changes in response to disease pathogenesis makes serum an attractive sample for clinical research. Despite these advantages, the analysis of serum proteome is very challenging due to the wide dynamic range of proteins, difficulty in finding low-abundance target analytes due to the presence of high-abundance serum proteins, high levels of salts and other interfering compounds, variations among individuals and paucity of reproducibility. Sample preparation introduces pre-analytical variations and poses major challenges to analyze the serum proteome. The label-free detection techniques such as surface plasmon resonance, microcantilever, few nanotechniques and different resonators are rapidly emerging for the analysis of serum proteome and they have exhibited potential to overcome few limitations of the conventional techniques. In this article, we will discuss the current status of serum proteome analysis for the biomarker discovery and address key technological advancements, with a focus on challenges and amenable solutions.

Identification of serum protein markers for breast cancer relapse with SELDI-TOF MS

Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) was used to screen serum samples to identify protein markers for early breast cancer relapse. We collected 67 serum samples from patients with breast cancer (24 preoperative; 23 postoperative without breast cancer relapse; 20 postoperative with breast cancer relapse). Eight protein peaks varied between the presurgical group and the postsurgical group without breast cancer relapse; 4 protein peaks were differentially expressed between the postsurgical patients without relapse and patients with relapse. The peak at 3964 m/z dropped after surgery and rebounded after relapse (P < 0.01). These results indicate that there are differences in serum protein expression among the three different groups of patients. SELDI-TOF MS could be used to screen blood samples for the early detection of relapse in primary breast cancer patients. Specifically, protein peak at 3964 m/z is a potential biomarker for the detection of early breast cancer relapse.

Clinical proteomics: current status, challenges, and future perspectives

This account will give an overview and evaluation of the current advances in mass spectrometry (MS)-based proteomics platforms and technology. A general review of some background information concerning the application of these methods in the characterization of molecular sizes and related protein expression profiles associated with different types of cells under varied experimental conditions will be presented. It is intended to provide a concise and succinct overview to those clinical researchers first exposed to this foremost powerful methodology in modern life sciences of postgenomic era. Proteomic characterization using highly sophisticated and expensive instrumentation of MS has been used to characterize biological samples of complex protein mixtures with vastly different protein structure and composition. These systems are then used to highlight the versatility and potential of the MS-based proteomic strategies for facilitating protein expression analysis of various disease-related organisms or tissues of interest. Major MS-based strategies reviewed herein include (1) matrix-assisted laser desorption ionization-MS and electron-spray ionization proteomics; (2) one-dimensional or two-dimensional gel-based proteomics; (3) gel-free shotgun proteomics in conjunction with liquid chromatography/tandem MS; (4) Multiple reaction monitoring coupled tandem MS quantitative proteomics and; (5) Phosphoproteomics based on immobilized metal affinity chromatography and liquid chromatography-MS/MS.

Biosensors: the new wave in cancer diagnosis

The earlier cancer can be detected, the better the chance of a cure. Currently, many cancers are diagnosed only after they have metastasized throughout the body. Effective, accurate methods of cancer detection and clinical diagnosis are urgently needed. Biosensors are devices that are designed to detect a specific biological analyte by essentially converting a biological entity (ie, protein, DNA, RNA) into an electrical signal that can be detected and analyzed. The use of biosensors in cancer detection and monitoring holds vast potential. Biosensors can be designed to detect emerging cancer biomarkers and to determine drug effectiveness at various target sites. Biosensor technology has the potential to provide fast and accurate detection, reliable imaging of cancer cells, and monitoring of angiogenesis and cancer metastasis, and the ability to determine the effectiveness of anticancer chemotherapy agents. This review will briefly summarize the current obstacles to early detection of cancer and the expanding use of biosensors as a diagnostic tool, as well as some future applications of biosensor technology.