Clinical protein mass spectrometry

Liquid chromatography-tandem mass spectrometry in clinical laboratory protein measurement

Proteins are essential components of human cells and tissues, and they are commonly measured in clinical laboratories using immunoassays. However, these assays have certain limitations, such as non-specificity binding, insufficient selectivity, and interference of antibodies. More sensitive, accurate, and efficient technology is required to overcome these limitations. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a powerful analytical tool that provides high sensitivity and specificity, making it superior to traditional methods such as biochemical and immunoassays. While LC-MS/MS has been increasingly used for detecting small molecular analytes and steroid hormones in clinical practice recently, its application for protein or peptide analysis is still in its early stages. Established methods for quantifying proteins and peptides by LC-MS/MS are mainly focused on scientific research, and only a few proteins and peptides can be or have the potential to be detected and applied in clinical practice. Therefore, this article aims to review the clinical applications, advantages, and challenges of analyzing proteins and peptides using LC-MS/MS in clinical laboratories.

Alpha-1-Antitrypsin (A1AT) Proteotyping by LC-MS/MS

The diagnosis of alpha-1-antitrypsin (A1AT) deficiency is established by quantitation of protein concentration in serum (immunoassay) followed by determination of specific allelic variants by phenotyping (isoelectric focusing (IEF) gel electrophoresis) and/or allele-specific genotyping. Various phenotyping and genotyping methodologies are available, and each has their own advantages and disadvantages. As an alternative, mass spectrometry is emerging as a powerful tool in the identification and quantitation of proteins and peptides. The method described here, referred to as proteotyping, is a proteomic method using trypsin digestion and tandem mass spectrometry that detects the most common deficiency alleles, S and Z, associated with A1AT deficiency.This qualitative mass spectrometry method is based on the principle that the S and Z mutations lead to amino acid changes which result in a change in the mass of the A1AT protein. When the A1AT protein is proteolytically digested, multiple peptides are generated, two of which include the sites of the S and Z mutations, respectively. Peptides generated from wild-type A1AT (M alleles) differ in sequence and mass from peptides generated from the S and Z alleles at these two specific locations. The mass difference allows for differentiation of S and Z peptides, representing the deficiency alleles, from non-S and non-Z peptides, representing the wild-type alleles (M). Interpretation of the peptide patterns in conjunction with A1AT quantitation by immunoassay allows for an accurate assessment for the presence of deficiency alleles in the majority of patients.

Artificial Neural Networks Coupled with MALDI-TOF MS Serum Fingerprinting To Classify and Diagnose Pathological Pain Subtypes in Preclinical Models

Pathological pain subtypes can be classified as either neuropathic pain, caused by a somatosensory nervous system lesion or disease, or nociplastic pain, which develops without evidence of somatosensory system damage. Since there is no gold standard for the diagnosis of pathological pain subtypes, the proper classification of individual patients is currently an unmet challenge for clinicians. While the determination of specific biomarkers for each condition by current biochemical techniques is a complex task, the use of multimolecular techniques, such as matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), combined with artificial intelligence allows specific fingerprints for pathological pain-subtypes to be obtained, which may be useful for diagnosis. We analyzed whether the information provided by the mass spectra of serum samples of four experimental models of neuropathic and nociplastic pain combined with their functional pain outcomes could enable pathological pain subtype classification by artificial neural networks. As a result, a simple and innovative clinical decision support method has been developed that combines MALDI-TOF MS serum spectra and pain evaluation with its subsequent data analysis by artificial neural networks and allows the identification and classification of pathological pain subtypes in experimental models with a high level of specificity.

Mass spectrometry in the clinical laboratory. A short journey through the contribution to the scientific literature by CCLM

Mass spectrometry (MS) has been a gold standard in the clinical laboratory for decades. Although historically refined to limited areas of study such as neonatal screening and steroid analysis, technological advancements in the field have resulted in MS becoming more powerful, versatile, and user-friendly than ever before. As such, the potential for the technique in clinical chemistry has exploded. The past two decades have seen advancements in biomarker detection for disease diagnostics, new methods for protein measurement, improved methodologies for reliable therapeutic drug monitoring, and novel technologies for automation and high throughput. Throughout this time, Clinical Chemistry and Laboratory Medicine has embraced the rapidly developing field of mass spectrometry, endeavoring to highlight the latest techniques and applications that have the potential to revolutionize clinical testing. This mini review will highlight a selection of these critical contributions to the field.

Protein markers of spermatogenesis and their potential use in the management of azoospermia

INTRODUCTION

Azoospermia, absence of sperm in the ejaculate is classified as obstructive (OA) and non-obstructive azoospermia (NOA). In OA, sperm are produced, but due to physical obstruction in the male reproductive tract, they are not released in the ejaculate. NOA, on the other hand, is defined as the absence of sperm in the ejaculate due to testicular dysfunction. In NOA, spermatogenesis is frequently preserved in specific sites, and proteomics studies have been employed in order to identify men with preserved spermatogenesis.

AREAS COVERED

Differential protein expression in patients with male infertility is an indicator of impaired spermatogenesis. Here, we reviewed proteins with a potential role as biomarkers of spermatogenesis that could help in the management of non-obstructive and obstructive azoospermia. The following keywords were used for bibliographic research: seminal plasma, proteomics, male infertility, nonobstructive, obstructive, azoospermia, oligospermia.

EXPERT OPINION

Biopsy is an invasive and potentially harmful technique for detecting spermatogenesis in men with OA and NOA. Seminal plasma proteins are highly promising as biomarkers for spermatogenesis. Current literature presents a number of potential candidate biomarkers for determining preserved spermatogenesis.

Detecting Periprosthetic Joint Infection by Using Mass Spectrometry

BACKGROUND

Novel methods for diagnosing periprosthetic joint infection (PJI) are currently being explored. Mass spectrometry (MS) is an approach that can detect whole-protein changes in synovial fluid and may represent a promising method.

METHODS

Between March 2017 and July 2018, we successively collected synovial fluid samples from patients who were undergoing diagnostic hip or knee aspiration because PJI was suspected. A PJI diagnosis was based on the modified Musculoskeletal Infection Society (MSIS) criteria. Cluster analysis and receiver operating characteristic (ROC) curves were used to evaluate the results, which were quantitatively confirmed with parallel reaction monitoring in another patient group who underwent aspiration between August 2018 and January 2019.

RESULTS

A total of 117 synovial samples, including 51 PJI and 66 non-PJI samples, were analyzed with liquid chromatography-tandem MS (LC-MS/MS). The cluster analysis sensitivity and specificity based on differentially expressed proteins were 0.961 (95% confidence interval [CI], 0.854 to 0.993) and 0.924 (95% CI, 0.825 to 0.972), respectively. Myeloid nuclear differentiation antigen (MNDA) and polymorphonuclear leukocyte serine protease 3 (PRTN3) were the 2 most important markers for detecting PJI. The areas under the curves (AUCs) of MNDA and PRTN3 were 0.969 (95% CI, 0.936 to 1.000) and 0.900 (95% CI, 0.844 to 0.956), respectively. When MNDA and PRTN3 were combined as variables of a predictive model to diagnose PJI, the AUC reached 0.975 (95% CI, 0.943 to 1.000). Our parallel reaction monitoring-based quantitative analysis of another 40 synovial samples confirmed this result.

CONCLUSIONS

MS could be a powerful tool for diagnosing PJI using proteome information or 2 specific markers, MNDA and PRTN3. The parallel reaction monitoring strategy simplified the PJI detection process and provided quantitative results with similar conclusions.

CLINICAL RELEVANCE

The clinical application of MS adds a new powerful tool for the diagnosis of PJI, and the parallel reaction monitoring strategy lays a foundation for the clinical application of MS.

LEVEL OF EVIDENCE

Diagnostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Recent advances in robotic protein sample preparation for clinical analysis and other biomedical applications

Discovery of new protein biomarker candidates has become a major research goal in the areas of clinical chemistry, analytical chemistry, and biomedicine. These important species constitute the molecular target when it comes to diagnosis, prognosis, and further monitoring of disease. However, their analysis requires powerful, selective and high-throughput sample preparation and product (analyte) characterisation approaches. In general, manual sample processing is tedious, complex and time-consuming, especially when large numbers of samples have to be processed (e.g., in clinical studies). Automation via microtiter-plate platforms involving robotics has brought improvements in high-throughput performance while comparable or even better precisions and repeatability (intra-day, inter-day) were achieved. At the same time, waste production and exposure of laboratory personnel to hazards were reduced. In comprehensive protein analysis workflows (e.g., liquid chromatography-tandem mass spectrometry analysis), sample preparation is an unavoidable step. This review surveys the recent achievements in automation of bottom-up and top-down protein and/or proteomics approaches. Emphasis is put on high-end multi-well plate robotic platforms developed for clinical analysis and other biomedical applications. The literature from 2013 to date has been covered.

The Translational Status of Cancer Liquid Biopsies

Abstract

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient’s body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research.

Lay Summary

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient’s body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research.

Ultrasensitive ELISA Developed for Diagnosis

For the diagnosis of disease, the ability to quantitatively detect trace amounts of the causal proteins from bacteria/viruses as biomarkers in patient specimens is highly desirable. Here we introduce a simple, rapid, and colorimetric assay as a de novo, ultrasensitive detection method. This ultrasensitive assay consists of a sandwich enzyme-linked immunosorbent assay (ELISA) and thionicotinamide-adenine dinucleotide (thio-NAD) cycling, forming an ultrasensitive ELISA, in which the signal substrate (i.e., thio-NADH) accumulates in a triangular manner, and the accumulated thio-NADH is measured at its maximum absorption wavelength of 405 nm. We have successfully achieved a limit of detection of ca. 10⁻¹⁸ moles/assay for a target protein. As an example of infectious disease detection, HIV-1 p24 could be measured at 0.0065 IU/assay (i.e., 10⁻¹⁸ moles/assay), and as a marker for a lifestyle-related disease, adiponectin could be detected at 2.3 × 10⁻¹⁹ moles/assay. In particular, despite the long-held belief that the trace amounts of adiponectin in urine can only be detected using a radioisotope, our ultrasensitive ELISA was able to detect urinary adiponectin. This method is highly versatile because simply changing the antibody enables the detection of various proteins. This assay system requires only the measurement of absorbance, thus it requires equipment that is easily obtained by medical facilities, which facilitates diagnosis in hospitals and clinics. Moreover, we describe an expansion of our ultrasensitive ELISA to a non-amplification nucleic acid detection method for nucleic acids using hybridization. These de novo methods will enable simple, rapid, and accurate diagnosis.

Enzyme-linked immunosorbent assay utilizing thin-layered microfluidics

An antibody-immobilized thin-layered glass microfluidic channel with a high surface-to-volume ratio was developed for rapid and sensitive enzyme-linked immunosorbent assay.

Approaches to the discovery of non-invasive urinary biomarkers of prostate cancer

Prostate cancer (PCa) continues to be one of the most common cancers in men worldwide. Prostate specific antigen (PSA) measured in blood has been used for decades as an aid for physicians to detect the presence of prostate cancer. However, the PSA test has limited sensitivity and specificity, leading to unnecessary biopsies, overdiagnosis and overtreatment of patients. For these reasons, there is an urgent need for more accurate PCa biomarkers that can detect PCa with high sensitivity and specificity. Urine is a unique source of potential protein biomarkers that can be measured in a non-invasive way. This review comprehensively summarizes state of the art approaches used in the discovery and validation of urinary biomarkers for PCa. Numerous strategies are currently being used in the discovery of urinary biomarkers for prostate cancer including gel-based separation techniques, mass spectrometry, activity-based proteomic assays and software approaches. Antibody-based approaches remain preferred method for validation of candidate biomarkers with rapidly advancing multiplex immunoassays and MS-based targeted approaches. In the last decade, there has been a dramatic acceleration in the development of new techniques and approaches in the discovery of protein biomarkers for prostate cancer including computational, statistical and data mining methods. Many urinary-based protein biomarkers have been identified and have shown significant promise in initial studies. Examples of these potential biomarkers and the methods utilized in their discovery are also discussed in this review.

Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: An update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry

In the 12 years since the publication of the first Consensus Paper of the WFSBP on biomarkers of neurodegenerative dementias, enormous advancement has taken place in the field, and the Task Force takes now the opportunity to extend and update the original paper. New concepts of Alzheimer's disease (AD) and the conceptual interactions between AD and dementia due to AD were developed, resulting in two sets for diagnostic/research criteria. Procedures for pre-analytical sample handling, biobanking, analyses and post-analytical interpretation of the results were intensively studied and optimised. A global quality control project was introduced to evaluate and monitor the inter-centre variability in measurements with the goal of harmonisation of results. Contexts of use and how to approach candidate biomarkers in biological specimens other than cerebrospinal fluid (CSF), e.g. blood, were precisely defined. Important development was achieved in neuroimaging techniques, including studies comparing amyloid-β positron emission tomography results to fluid-based modalities. Similarly, development in research laboratory technologies, such as ultra-sensitive methods, raises our hopes to further improve analytical and diagnostic accuracy of classic and novel candidate biomarkers. Synergistically, advancement in clinical trials of anti-dementia therapies energises and motivates the efforts to find and optimise the most reliable early diagnostic modalities. Finally, the first studies were published addressing the potential of cost-effectiveness of the biomarkers-based diagnosis of neurodegenerative disorders.

Deuterium- and Tritium-Labelled Compounds: Applications in the Life Sciences

Hydrogen isotopes are unique tools for identifying and understanding biological and chemical processes. Hydrogen isotope labelling allows for the traceless and direct incorporation of an additional mass or radioactive tag into an organic molecule with almost no changes in its chemical structure, physical properties, or biological activity. Using deuterium-labelled isotopologues to study the unique mass-spectrometric patterns generated from mixtures of biologically relevant molecules drastically simplifies analysis. Such methods are now providing unprecedented levels of insight in a wide and continuously growing range of applications in the life sciences and beyond. Tritium (³ H), in particular, has seen an increase in utilization, especially in pharmaceutical drug discovery. The efforts and costs associated with the synthesis of labelled compounds are more than compensated for by the enhanced molecular sensitivity during analysis and the high reliability of the data obtained. In this Review, advances in the application of hydrogen isotopes in the life sciences are described.

Current and Emerging Technologies for Probing Molecular Signatures of Traumatic Brain Injury

Traumatic brain injury (TBI) is understood as an interplay between the initial injury, subsequent secondary injuries, and a complex host response all of which are highly heterogeneous. An understanding of the underlying biology suggests a number of windows where mechanistically inspired interventions could be targeted. Unfortunately, biologically plausible therapies have to-date failed to translate into clinical practice. While a number of stereotypical pathways are now understood to be involved, current clinical characterization is too crude for it to be possible to characterize the biological phenotype in a truly mechanistically meaningful way. In this review, we examine current and emerging technologies for fuller biochemical characterization by the simultaneous measurement of multiple, diverse biomarkers. We describe how clinically available techniques such as cerebral microdialysis can be leveraged to give mechanistic insights into TBI pathobiology and how multiplex proteomic and metabolomic techniques can give a more complete description of the underlying biology. We also describe spatially resolved label-free multiplex techniques capable of probing structural differences in chemical signatures. Finally, we touch on the bioinformatics challenges that result from the acquisition of such large amounts of chemical data in the search for a more mechanistically complete description of the TBI phenotype.

A Miniaturized Linear Wire Ion Trap with Electron Ionization and Single Photon Ionization Sources

A linear wire ion trap (LWIT) with both electron ionization (EI) and single photon ionization (SPI) sources was built. The SPI was provided by a vacuum ultraviolet (VUV) lamp with the ability to softly ionize organic compounds. The VUV lamp was driven by a pulse amplifier, which was controlled by a pulse generator, to avoid the detection of photons during ion detection. Sample gas was introduced through a leak valve, and the pressure in the system is shown to affect the signal-to-noise ratio and resolving power. Under optimized conditions, the limit of detection (LOD) for benzene was 80 ppbv using SPI, better than the LOD using EI (137 ppbv). System performance was demonstrated by distinguishing compounds in different classes from gasoline. Graphical Abstract ᅟ.

Assay-dependent variability of serum insulin concentrations: a comparison of eight assays

Although insulin measurement is essential for both clinical and research purposes, there is currently no reference method for insulin assays. The aim of this study was to compare results of serum insulin determined by a number of commercially available assays. We compared eight insulin assays by analyzing 165 serum samples. Assays included two chemiluminescence (Roche and DiaSorin), four ELISA (Tosoh, Mercodia, Monobind, and Diametra), and two IRMA (Izotop and BioSource) methods. Each assay was compared with the mean of all assay methods and Bland-Altman difference plots were used to measure agreement between each assay and overall mean. Least squared perpendicular distance regression analysis (Deming's method) was used to calculate slope and intercept for bias and also for each assay vs. mean of eight assays. Findings showed that the lowest and highest median insulin concentrations varied by a factor of 1.8. Maximum and minimum correlations with mean of assays were observed for Roche (0.992) and BioSource (0.844), respectively. Significant bias was observed in six assays. In pairwise comparisons of different assays, the highest and least mean differences were 7.78 μU/mL and -0.14 μU/mL, respectively. In conclusion, serum insulin measurement with different assays showed a maximum of 1.8-fold difference, a point that should be taken into consideration in the interpretation of circulating insulin levels in both clinical and research fields.

Proteomic profile of seminal plasma in adolescents and adults with treated and untreated varicocele

Varicocele, the most important treatable cause of male infertility, is present in 15% of adult males, 35% of men with primary infertility, and 80% of men with secondary infertility. On the other hand, 80% of these men will not present infertility. Therefore, there is a need to differentiate a varicocele that is exerting a deleterious effect that is treatable from a “silent” varicocele. Despite the growing evidence of the cellular effects of varicocele, its underlying molecular mechanisms are still eluding. Proteomics has become a promising area to determine the reproductive biology of semen as well as to improve diagnosis of male infertility. This review aims to discuss the state-of-art in seminal plasma proteomics in patients with varicocele to discuss the challenges in undertaking these studies, as well as the future outlook derived from the growing body of evidence on the seminal proteome.

"RaMassays": Synergistic Enhancement of Plasmon-Free Raman Scattering and Mass Spectrometry for Multimodal Analysis of Small Molecules

SiO₂/TiO₂ core/shell (T-rex) beads were exploited as "all-in-one" building-block materials to create analytical assays that combine plasmon-free surface enhanced Raman scattering (SERS) and surface assisted laser desorption/ionization (SALDI) mass spectrometry (RaMassays). Such a multi-modal approach relies on the unique optical properties of T-rex beads, which are able to harvest and manage light in both UV and Vis range, making ionization and Raman scattering more efficient. RaMassays were successfully applied to the detection of small (molecular weight, M.W. <400 Da) molecules with a key relevance in biochemistry and pharmaceutical analysis. Caffeine and cocaine were utilized as molecular probes to test the combined SERS/SALDI response of RaMassays, showing excellent sensitivity and reproducibility. The differentiation between amphetamine/ephedrine and theophylline/theobromine couples demonstrated the synergistic reciprocal reinforcement of SERS and SALDI. Finally, the conversion of L-tyrosine in L-DOPA was utilized to probe RaMassays as analytical tools for characterizing reaction intermediates without introducing any spurious effects. RaMassays exhibit important advantages over plasmonic nanoparticles in terms of reproducibility, absence of interference and potential integration in multiplexed devices.

Personalized Proteomics: The Future of Precision Medicine

Medical diagnostics and treatment has advanced from a one size fits all science to treatment of the patient as a unique individual. Currently, this is limited solely to genetic analysis. However, epigenetic, transcriptional, proteomic, posttranslational modifications, metabolic, and environmental factors influence a patient’s response to disease and treatment. As more analytical and diagnostic techniques are incorporated into medical practice, the personalized medicine initiative transitions to precision medicine giving a holistic view of the patient’s condition. The high accuracy and sensitivity of mass spectrometric analysis of proteomes is well suited for the incorporation of proteomics into precision medicine. This review begins with an overview of the advance to precision medicine and the current state of the art in technology and instrumentation for mass spectrometry analysis. Thereafter, it focuses on the benefits and potential uses for personalized proteomic analysis in the diagnostic and treatment of individual patients. In conclusion, it calls for a synthesis between basic science and clinical researchers with practicing clinicians to design proteomic studies to generate meaningful and applicable translational medicine. As clinical proteomics is just beginning to come out of its infancy, this overview is provided for the new initiate.

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era.

Mining the Human Proteome: Biomarker Discovery for Human Cancer and Metastases

As our knowledge of the mechanisms underlying cancer development and progression has increased, so too have more effective, less toxic, and targeted therapies begun to reach the clinic. However, the full impact of these clinical advances and the practical success of the emerging field of precision medicine are dependent on the discovery and validation of sensitive and accurate biomarkers that can enable appropriate and rigorous sample type and patient selection, reliable longitudinal monitoring of therapeutic efficacy, and even risk assessment and early detection. Within the context of this review, we examine state-of-the-art approaches to the discovery and validation of noninvasive cancer biomarkers, with a specific emphasis on those that are protein or protein-associated ones. We also review sample selection strategies, currently utilized proteomic approaches for both discovery and validation requirements, and data analysis standards. Finally, we provide examples of these elements of biomarker discovery and validation from our own biomarker research.

Challenges in biomarker discovery with MALDI-TOF MS

MALDI-TOF MS technique is commonly used in system biology and clinical studies to search for new potential markers associated with pathological conditions. Despite numerous concerns regarding a sample preparation or processing of complex data, this strategy is still recognized as a popular tool and its awareness has risen in the proteomic community over the last decade. In this review, we present comprehensive application of MALDI mass spectrometry with special focus on profiling research. We also discuss major advantages and disadvantages of universal sample preparation methods such as micro-SPE columns, immunodepletion or magnetic beads, and we show the potential of nanostructured materials in capturing low molecular weight subproteomes. Furthermore, as the general protocol considerably affects spectra quality and interpretation, an alternative solution for improved ion detection, including hydrophobic constituents, data processing and statistical analysis is being considered in up-to-date profiling pattern. In conclusion, many reports involving MALDI-TOF MS indicated highly abundant proteins as valuable indicators, and at the same time showed the inaccuracy of available methods in the detection of low abundant proteome that is the most interesting from the clinical perspective. Therefore, the analytical aspects of sample preparation methods should be standardized to provide a reproducible, low sample handling and credible procedure.

What gastric cancer proteomic studies show about gastric carcinogenesis?

Gastric cancer is a complex, heterogeneous, and multistep disease. Over the past decades, several studies have aimed to determine the molecular factors that lead to gastric cancer development and progression. After completing the human genome sequencing, proteomic technologies have presented rapid progress. Differently from the relative static state of genome, the cell proteome is dynamic and changes in pathologic conditions. Proteomic approaches have been used to determine proteome profiles and identify differentially expressed proteins between groups of samples, such as neoplastic and nonneoplastic samples or between samples of different cancer subtypes or stages. Therefore, proteomic technologies are a useful tool toward improving the knowledge of gastric cancer molecular pathogenesis and the understanding of tumor heterogeneity. This review aimed to summarize the proteins or protein families that are frequently identified by using high-throughput screening methods and which thus may have a key role in gastric carcinogenesis. The increased knowledge of gastric carcinogenesis will clearly help in the development of new anticancer treatments. Although the studies are still in their infancy, the reviewed proteins may be useful for gastric cancer diagnosis, prognosis, and patient management.

Planar Functionalized Surfaces for Direct Immunoaffinity Desorption/Ionization Mass Spectrometry

BACKGROUND

Recent studies show that the haptoglobin phenotype in individuals with diabetes mellitus is an important factor for predicting the risk of myocardial infarction, cardiovascular death, and stroke. Current methods for haptoglobin phenotyping include PCR and gel electrophoresis. A need exists for a reliable method for high-throughput clinical applications. Mass spectrometry (MS) can in principle provide fast phenotyping because haptoglobin α 1 and α 2, which define the phenotype, have different molecular masses. Because of the complexity of the serum matrix, an efficient and fast enrichment technique is necessary for an MS-based assay.

METHODS

MALDI plates were functionalized by ambient ion landing of electrosprayed antihaptoglobin antibody. The array was deposited on standard indium tin oxide slides. Fast immunoaffinity enrichment was performed in situ on the plate, which was further analyzed by MALDI-TOF MS. The haptoglobin phenotype was determined from the spectra by embedded software script.

RESULTS

The MALDI mass spectra showed ion signals of haptoglobin α subunits at m/z 9192 and at m/z 15 945. A cohort of 116 sera was analyzed and the reliability of the method was confirmed by analyzing the identical samples by Western blot. One hundred percent overlap of results between the direct immunoaffinity desorption/ionization MS and Western Blot analysis was found.

CONCLUSIONS

MALDI plates modified by antihaptoglobin antibody using ambient ion landing achieve low nonspecific interactions and efficient MALDI ionization and are usable for quick haptoglobin phenotyping.

Proteomic profile of seminal plasma in adolescents and adults with treated and untreated varicocele

Varicocele, the most important treatable cause of male infertility, is present in 15% of adult males, 35% of men with primary infertility, and 80% of men with secondary infertility. On the other hand, 80% of these men will not present infertility. Therefore, there is a need to differentiate a varicocele that is exerting a deleterious effect that is treatable from a "silent" varicocele. Despite the growing evidence of the cellular effects of varicocele, its underlying molecular mechanisms are still eluding. Proteomics has become a promising area to determine the reproductive biology of semen as well as to improve diagnosis of male infertility. This review aims to discuss the state-of-art in seminal plasma proteomics in patients with varicocele to discuss the challenges in undertaking these studies, as well as the future outlook derived from the growing body of evidence on the seminal proteome.

Glycoforms of Immunoglobulin G Based Biopharmaceuticals Are Differentially Cleaved by Trypsin Due to the Glycoform Influence on Higher-Order Structure

It has been reported that glycosylation can influence the proteolytic cleavage of proteins. A thorough investigation of this phenomenon was conducted for the serine protease trypsin, which is essential in many proteomics workflows. Monoclonal and polyclonal immunoglobulin G biopharmaceuticals were employed as model substances, which are highly relevant for the bioanalytical applications. Relative quantitation of glycopeptides derived from the conserved Fc-glycosylation site allowed resolution of biases on the level of individual glycan compositions. As a result, a strong preferential digestion of high mannose, hybrid, alpha2-3-sialylated and bisected glycoforms was observed over the most abundant neutral, fucosylated glycoforms. Interestingly, this bias was, to a large extent, dependent on the intact higher order structure of the antibodies and, consequently, was drastically reduced in denatured versus intact antibodies. In addition, a cleavage protocol with acidic denaturation was tested, which featured reduced hands-on time and toxicity while showing highly comparable results to a published denaturation, reduction, and alkylation based protocol.