Large-scale isotype-specific quantification of Serum amyloid A 1/2 by multiple reaction monitoring in crude sera

Screening of novel biomarkers for acute kidney transplant rejection using DIA-MS based proteomics

BACKGROUND

Kidney transplantation is the preferred treatment for patients with end-stage renal disease. However, acute rejection poses a threat to the graft long-term survival. The aim of this study was to identify novel biomarkers to detect acute kidney transplant rejection.

METHODS

The serum proteomic profiling of kidney transplant patients with T cell-mediated acute rejection (TCMR) and stable allograft function (STA) was analyzed using data-independent acquisition mass spectrometry (DIA-MS). The differentially expressed proteins (DEPs) of interest were further verified by enzyme-linked immunosorbent assay (ELISA).

RESULTS

A total of 131 DEPs were identified between STA and TCMR patients, 114 DEPs were identified between mild and severe TCMR patients. The verification results showed that remarkable higher concentrations of serum amyloid A protein 1 (SAA1) and insulin like growth factor binding protein 2 (IGFBP2), and lower fetuin-A (AHSG) concentration were found in TCMR patients when compared with STA patients. We also found higher SAA1 concentration in severe TCMR group when compared with mild TCMR group. The receiver operating characteristics (ROC) analysis further confirmed that combination of SAA1, AHSG, and IGFBP2 had excellent performance in the acute rejection diagnosis.

CONCLUSIONS

Our data demonstrated that serum SAA1, AHSG, and IGFBP2 could be effective biomarkers for diagnosing acute rejection after kidney transplantation. DIA-MS has great potential in biomarker screening of kidney transplantation.

Plasma Proteomics Enable Differentiation of Lung Adenocarcinoma from Chronic Obstructive Pulmonary Disease (COPD)

Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD; thus, the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass-spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel.

Targeted proteomics and specific immunoassays reveal the presence of shared allergens between the zoonotic nematodes Anisakis simplex and Pseudoterranova decipiens

The family Anisakidae, mainly represented by Anisakis simplex s.l. and Pseudoterranova decipiens, encompasses zoonotic nematodes infecting many marine fish. Both are responsible for gastrointestinal disease in humans after ingestion of a live larva by consumption of undercooked fish, and, in the case of A. simplex, an allergic reaction may occur after consuming or even handling infected fish. Due to its phylogenetic relatedness with A. simplex, few studies investigated the allergenic potential of P. decipiens, yet none of them focused on its excretory/secretory (E/S) proteins that easily get missed when working solely on extracts from crushed nematodes. Moreover, these E/S allergens remain behind even when the larva has been removed during fish quality processing. Therefore, the aim was to investigate if Anisakis-like allergens could also be detected in both crushed and E/S P. decipiens protein extract using targeted mass spectrometry analysis and immunological methods. The results confirmed that at least five A. simplex allergens have homologous proteins in P. decipiens; a result that emphasizes the importance of also including E/S protein extracts in proteomic studies. Not only A. simplex, but also P. decipiens should therefore be considered a potential source of allergens that could lead to hypersensitivity reactions in humans.

Identification of main influencing factors on the protein corona composition of PLGA and PLA nanoparticles

Poly(DL-lactic-co-glycolic acid) and poly(DL-lactic acid) are widely used for the preparation of nanoparticles due to favorable characteristics for medical use like biodegradability and controllable degradation behavior. The contact with different media like human plasma or serum leads to the formation of a protein corona that determines the NP's in vivo processing. In this study, the impact of surface end group identity, matrix polymer hydrophobicity, molecular weight, and incubation medium on the protein corona composition was evaluated. Corona proteins were quantified using Bradford assay, separated by SDS-PAGE, and identified via LC-MS/MS. The acquired data revealed that surface end group identity had the most profound effect on corona composition in both quantitative and qualitative terms. Regarding matrix polymer hydrophobicity, adsorption profiles on NP systems with similar physicochemical characteristics resembled each other. The molecular weight of the matrix polymers proved to impact quantity, but not quality of corona bound proteins. The corona of plasma incubated NP showed adsorption of incubation medium-specific proteins but resembled those of serum incubated NP in terms of protein function, average mass and isoelectric point. Overall, the NP physicochemical properties proved to be easily adjustable determining factors of protein corona formation in physiological environments.

Targeted mass spectrometry for Serum Amyloid A (SAA) isoform profiling in sequential blood samples from experimentally Staphylococcus aureus infected pigs

Serum amyloid A (SAA) is a well-described acute phase protein induced during the acute phase response (APR) to infection. Four isoform specific genes are found in most mammals. Depending on species, SAA3 and SAA4 are generally preferentially expressed extrahepatically whereas SAA1 and SAA2 are hepatic isoforms dominating the SAA serum pool. Little is known about how specific infections affect the serum SAA isoform profile, as SAA isoform discriminating antibodies are not generally available. An antibody independent, quantitative targeted MS method (Selected Reaction Monitoring, SRM) based on available information on porcine SAA isoform genes was developed and used to profile SAA in serum samples from pigs experimentally infected with Staphylococcus aureus (Sa). While results suggest SAA2 as the main circulating porcine SAA isoform, induced around 10 times compared to non-infected controls, total SAA serum concentrations reached only around 4 μg/mL, much lower than established previously by immunoassays. This might suggest that SAA isoform variants not detected by the SRM method might be present in porcine serum. The assay allows monitoring host responses to experimental infections, infectious diseases and inflammation states in the pig at an unprecedented level of detail. It can also be used in a non-calibrated (relative quantification) format. SIGNIFICANCE: We developed an SRM MS method which for the first time allowed the specific quantification of each of the circulating porcine SAA isoforms (SAA2, SAA3, SAA4). It was found that SAA2 is the dominating circulating isoform of SAA in the pig and that, during the acute phase response to Sa infection SAA2, SAA3 and SAA4 are induced approx. 10, 15 and 2 times, respectively. Absolute levels of the isoforms as determined by SRM MS were much lower than reported previously for total SAA quantified by immunosassays, suggesting the existence of hitherto non-described SAA variants. SRM MS holds great promise for the study of the basic biology of SAA isoforms with the potential to study an even broader range of SAA variants.

Interleukin-1β Induces Intracellular Serum Amyloid A1 Expression in Human Coronary Artery Endothelial Cells and Promotes its Intercellular Exchange

Serum amyloid A (SAA) is an acute-phase protein with important, pathogenic role in the development of atherosclerosis. Since dysfunctional endothelium represents a key early step in atherogenesis, we aimed to determine whether induced human coronary artery endothelial cells (HCAEC) modulate SAA1/2/4 expression and influence intracellular location and intercellular transport of SAA1. HCAEC were stimulated with 1 ng/ml IL-1β, 10 ng/ml IL-6, and/or 1 μM dexamethasone for 24 h. QPCR, Western blots, ELISA, and immunofluorescent labeling were performed for detection of SAA1/2/4 mRNA and protein levels, respectively. In SAA1 transport experiments, FITC- or Cy3-labeled SAA1 were added to HCAEC separately, for 24 h, followed by a combined incubation of SAA1-FITC and SAA1-Cy3 positive cells, with IL-1β and analysis by flow cytometry. IL-1β upregulated SAA1 (119.9-fold, p < 0.01) and SAA2 (9.3-fold; p < 0.05) mRNA expression levels, while mRNA expression of SAA4 was not affected. Intracellular SAA1 was found mainly as a monomer, while SAA2 and SAA4 formed octamers as analyzed by Western blots. Within HCAEC, SAA1/2/4 located mostly to the perinuclear area and tunneling membrane nanotubes. Co-culturing of SAA1-FITC and SAA1-Cy3 positive cells for 48 h showed a significantly higher percentage of double positive cells in IL-1β-stimulated (mean ± SD; 60 ± 4%) vs. non-stimulated cells (48 ± 2%; p < 0.05). IL-1β induces SAA1 expression in HCAEC and promotes its intercellular exchange, suggesting that direct communication between cells in inflammatory conditions could ultimately lead to faster development of atherosclerosis in coronary arteries.

Targeted proteomics reveals serum amyloid A variants and alarmins S100A8-S100A9 as key plasma biomarkers of rheumatoid arthritis

Serum amyloid A (SAA) and S100 (S100A8, S100A9 and S100A12) proteins were previously identified as biomarkers of interest for rheumatoid arthritis (RA). Among SAA family, two closely related isoforms (SAA-1 and SAA-2) are linked to the acute-phase of inflammation. They respectively exist under the form of three (α, β, and γ) and two (α and β) allelic variants. We developed a single run quantitative method for these protein variants and investigated their clinical relevance in the context of RA. The method was developed and validated according to regulations before being applied on plasma coming from RA patients (n = 46), other related inflammatory pathologies (n = 116) and controls (n = 62). Depending on the activity score of RA, SAA1 isoforms (mainly of SAA1α and SAA1β subtypes) were found to be differentially present in plasma revealing their dual role during the development of RA. In addition, the weight of SAA1α in the total SAA response varied from 32 to 80% depending on the pathology studied. A negative correlation between SAA1α and SAA1β was also highlighted for RA early-onset (r = -0.41). SAA2 and S100A8/S100A9 proteins were significantly overexpressed compared to control samples regardless of RA stage. The pathophysiological relevance of these quantitative and qualitative characteristics of the SAA response remains unknown. However, the significant negative correlation observed between SAA1α and SAA1β levels in RA early-onset suggests the existence of still unknown regulatory mechanisms in these diseases.

Quantum Dot Based Nano-Biosensors for Detection of Circulating Cell Free miRNAs in Lung Carcinogenesis: From Biology to Clinical Translation

Lung cancer is the most frequently occurring malignancy and the leading cause of cancer-related death for men in our country. The only recommended screening method is clinic based low-dose computed tomography (also called a low-dose CT scan, or LDCT). However, the effect of LDCT on overall mortality observed in lung cancer patients is not statistically significant. Over-diagnosis, excessive cost, risks associated with radiation exposure, false positive results and delay in the commencement of the treatment procedure questions the use of LDCT as a reliable technique for population-based screening. Therefore, identification of minimal-invasive biomarkers able to detect malignancies at an early stage might be useful to reduce the disease burden. Circulating nucleic acids are emerging as important source of information for several chronic pathologies including lung cancer. Of these, circulating cell free miRNAs are reported to be closely associated with the clinical outcome of lung cancer patients. Smaller size, sequence homology between species, low concentration and stability are some of the major challenges involved in characterization and specific detection of miRNAs. To circumvent these problems, synthesis of a quantum dot based nano-biosensor might assist in sensitive, specific and cost-effective detection of differentially regulated miRNAs. The wide excitation and narrow emission spectra of these nanoparticles result in excellent fluorescent quantum yields with a broader color spectrum which make them ideal bio-entities for fluorescence resonance energy transfer (FRET) based detection for sequential or simultaneous study of multiple targets. In addition, photo-resistance and higher stability of these nanoparticles allows extensive exposure and offer state-of-the art sensitivity for miRNA targeting. A major obstacle for integrating QDs into clinical application is the QD-associated toxicity. However, the use of non-toxic shells along with surface modification not only overcomes the toxicity issues, but also increases the ability of QDs to quickly detect circulating cell free miRNAs in a non-invasive mode. The present review illustrates the importance of circulating miRNAs in lung cancer diagnosis and highlights the translational prospects of developing QD-based nano-biosensor for rapid early disease detection.

Multiplex Assay for Quantification of Acute Phase Proteins and Immunoglobulin A in Dried Blood Spots

Inflammation is the first line defense mechanism against infection, tissue damage, or cancer development. However, inappropriate inflammatory response may also trigger diseases. The quantification of inflammatory proteins is essential to distinguish between harmful and beneficial immune response. Currently used immunoanalytical assays may suffer specificity issues due to antigen-antibody interaction and possible cross-reactivity of antibody with other protein species. In addition, immunoanalytical assays typically require invasive blood sampling and additional logistics; they are relatively costly and highly challenging to multiplex. We present a multiplex assay based on selected reaction monitoring (SRM) for quantification of seven acute-phase proteins (i.e., SAA1, SAA2-isoform1, SAA4, CRP, A1AT-isoform1, A1AG1, A1AG2) and the adaptive immunity effector IGHA1 in dried blood spots. This type of sample is readily available from all human subjects including newborns. The study utilizes proteotypic isotopically labeled peptides with trypsin-cleavable tag and presents optimized and reproducible workflow and several important practical remarks regarding quantitative SRM assays development. The panel of inflammatory proteins was quantified with sequence specificity capable to differentiate protein isoforms with intra- and interday precision (<16.4% coefficient of variation (CV) and <14.3% CV, respectively). Quantitative results were correlated with immuno-nephelometric assay (typically greater than 0.9 Pearson's R).

Quiescin Sulfhydryl Oxidase 1 (QSOX1) Secreted by Lung Cancer Cells Promotes Cancer Metastasis

As lung cancer shows the highest mortality in cancer-related death, serum biomarkers are demanded for lung cancer diagnosis and its treatment. To discover lung cancer protein biomarkers, secreted proteins from primary cultured lung cancer and adjacent normal tissues from patients were subjected to LC/MS⁻MS proteomic analysis. Quiescin sulfhydryl oxidase (QSOX1) was selected as a biomarker candidate from the enriched proteins in the secretion of lung cancer cells. QSOX1 levels were higher in 82% (51 of 62 tissues) of lung cancer tissues compared to adjacent normal tissues. Importantly, QSOX1 serum levels were significantly higher in cancer patients (p < 0.05, Area Under curve (AUC) = 0.89) when measured by multiple reaction monitoring (MRM). Higher levels of QSOX1 were also uniquely detected in lung cancer tissues, among several other solid cancers, by immunohistochemistry. QSOX1-knock-downed Lewis lung cancer (LLC) cells were less viable from oxidative stress and reduced migration and invasion. In addition, LLC mouse models with QSOX1 knock-down also proved that QSOX1 functions in promoting cancer metastasis. In conclusion, QSOX1 might be a lung cancer tissue-derived biomarker and be involved in the promotion of lung cancers, and thus can be a therapeutic target for lung cancers.

A Graphical Model of Smoking-Induced Global Instability in Lung Cancer

Smoking is the major cause of lung cancer and the leading cause of cancer-related death in the world. The most current view about lung cancer is no longer limited to individual genes being mutated by any carcinogenic insults from smoking. Instead, tumorigenesis is a phenotype conferred by many systematic and global alterations, leading to extensive heterogeneity and variation for both the genotypes and phenotypes of individual cancer cells. Thus, strategically it is foremost important to develop a methodology to capture any consistent and global alterations presumably shared by most of the cancerous cells for a given population. This is particularly true that almost all of the data collected from solid cancers (including lung cancers) are usually distant apart over a large span of temporal or even spatial contexts. Here, we report a multiple non-Gaussian graphical model to reconstruct the gene interaction network using two previously published gene expression datasets. Our graphical model aims to selectively detect gross structural changes at the level of gene interaction networks. Our methodology is extensively validated, demonstrating good robustness, as well as the selectivity and specificity expected based on our biological insights. In summary, gene regulatory networks are still relatively stable during presumably the early stage of neoplastic transformation. But drastic structural differences can be found between lung cancer and its normal control, including the gain of functional modules for cellular proliferations such as EGFR and PDGFRA, as well as the lost of the important IL6 module, supporting their roles as potential drug targets. Interestingly, our method can also detect early modular changes, with the ALDH3A1 and its associated interactions being strongly implicated as a potential early marker, whose activations appear to alter LCN2 module as well as its interactions with the important TP53-MDM2 circuitry. Our strategy using the graphical model to reconstruct gene interaction work with biologically-inspired constraints exemplifies the importance and beauty of biology in developing any bio-computational approach.

Serum amyloid A expression in the breast cancer tissue is associated with poor prognosis

Background

Serum amyloid A (SAA), an acute-phase protein, is expressed primarily in the liver, and recently found also expressed in cancer tissues. However, its expression and prognostic value in breast cancer have not been described.

Results

SAA protein was found expressed in tumor cells in 44.2% cases and in TAM in 62.5% cases. FISH showed more frequent SAA mRNA expression in TAM than in tumor cells (76% versus 12%, p < 0.001), and a significant association between the frequencies of SAA mRNA expression in TAM and tumor cells (r_s = 0.603, p < 0.001). The immunoreactivities of SAA protein in TAM and tumor cells were both associated with lymphovascular invasion and lymph node metastasis. Moreover, SAA-positivity in TAMs was associated with larger tumor-size, higher histological-grade, negative estrogen-receptor and progesterone-receptor statuses, and HER-2 overexpression. It was also linked to worse recurrence-free survival in a multivariable regression model.

Methods

Immunohistochemistry was applied on the tumor tissues from 208 breast cancer patients to evaluate the local SAA-protein expression with additional CD68 stain to identify the tumor-associated macrophage (TAM) on the serial tissue sections. Fluorescent in situ hybridization (FISH) was conducted on serial tissue sections from 25 of the 208 tumors to examine the expression and location of SAA mRNA.

Conclusions

Our results suggested that the TAMs may be a pivotal and main source of SAA production in tumor microenvironment of breast cancer. SAA immunoreactivity in TAM is associated with worse recurrence-free survival, and is therefore a biomarker candidate for postoperative surveillance and perhaps a therapeutic target for breast cancer.

A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research

The fact that cancer is a leading cause of death all around the world has naturally sparked major efforts in the pursuit of novel and more efficient biomarkers that could better serve as diagnostic tools, prognostic predictors, or therapeutical targets in the battle against this type of disease. Mass spectrometry-based proteomics has proven itself as a robust and logical alternative to the immuno-based methods that once dominated the field. Nevertheless, intrinsic limitations of classic proteomic approaches such as the natural gap between shotgun discovery-based methods and clinically applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples other than plasma and serum, which are generally aimed toward prognostic markers. Interestingly, the most common type of targeted approach is based on stable isotope dilution-selected reaction monitoring protocols for quantification of the target molecules. Overall, this reinforces that notion that targeted proteomics has already started to fulfill its role as a groundbreaking strategy that may enable researchers to catapult the number of viable, effective, and validated biomarkers in cancer clinical practice.

Advances in targeted proteomics and applications to biomedical research

Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity (Shi et al., Proteomics, 12, 1074-1092, 2012) herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications in human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data-independent acquisition (DIA) with targeted data extraction on fast scanning high-resolution accurate-mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale quantification of hundreds of target proteins are discussed.

Biomarkers for Bone Tumors: Discovery from Genomics and Proteomics Studies and Their Challenges

Diagnosis of bone tumor currently relies on imaging and biopsy, and hence, the need to find less invasive ways for its accurate detection. More recently, numerous promising deoxyribonucleic acid (DNA) and protein biomarkers with significant prognostic, diagnostic and/or predictive abilities for various types of bone tumors have been identified from genomics and proteomics studies. This article reviewed the putative biomarkers for the more common types of bone tumors (that is, osteosarcoma, Ewing sarcoma, chondrosarcoma [malignant] and giant cell tumor [benign]) that were unveiled from the studies. The benefits and drawbacks of these biomarkers, as well as the technology platforms involved in the research, were also discussed. Challenges faced in the biomarker discovery studies and the problems in their translation from the bench to the clinical settings were also addressed.

Targeted proteomics of solid cancers: from quantification of known biomarkers towards reading the digital proteome maps

The concept of personalized medicine includes novel protein biomarkers that are expected to improve the early detection, diagnosis and therapy monitoring of malignant diseases. Tissues, biofluids, cell lines and xenograft models are the common sources of biomarker candidates that require verification of clinical value in independent patient cohorts. Targeted proteomics - based on selected reaction monitoring, or data extraction from data-independent acquisition based digital maps - now represents a promising mass spectrometry alternative to immunochemical methods. To date, it has been successfully used in a high number of studies answering clinical questions on solid malignancies: breast, colorectal, prostate, ovarian, endometrial, pancreatic, hepatocellular, lung, bladder and others. It plays an important role in functional proteomic experiments that include studying the role of post-translational modifications in cancer progression. This review summarizes verified biomarker candidates successfully quantified by targeted proteomics in this field and directs the readers who plan to design their own hypothesis-driven experiments to appropriate sources of methods and knowledge.

Quantification of SAA1 and SAA2 in lung cancer plasma using the isotype-specific PRM assays

The quantification of plasma proteins using the high resolution and accurate mass (HR/AM)-based parallel reaction monitoring (PRM) method provides an immediate benefit over the conventional SRM-based method in terms of selectivity. In this study, multiplexed PRM assays were developed to analyze isotypes of serum amyloid A (SAA) proteins in human plasma with a focus on SAA1 and SAA2. Elevated plasma levels of these proteins in patients diagnosed with lung cancer have been reported in previous studies. Since SAA1 and SAA2 are highly homologous, the available immunoassays tend to overestimate their concentrations due to cross-reactivity. On the other hand, when mass spectrometry (MS)-based assays are used, the presence of the several allelic variants may result in a problem of underestimation. In the present study, eight peptides that represent the target proteins at three different levels: isotype-specific (SAA1α,  SAA 1β,  SAA1γ,  SAA2α,  SAA2β), protein-specific (SAA1 or SAA2), and pan SAA (SAA1 and SAA2) were chosen to differentiate SAAs in lung cancer plasma samples using a panel of PRM assays. The measurement of specific isotypes, leveraging the analytical performance of PRM, allowed to quantify the allelic variants of both target proteins. The isotypes detected were corroborated with the genetic information obtained from the same samples. The combination of SAA2α and SAA2β assays representing the total SAA2 concentration demonstrated a superior analytical outcome than the previously used assay on the common peptide when applied to the detection of lung cancer.

Targeted proteomics for biomarker discovery and validation of hepatocellular carcinoma in hepatitis C infected patients

Hepatocellular carcinoma (HCC)-related mortality is high because early detection modalities are hampered by inaccuracy, expense and inherent procedural risks. Thus there is an urgent need for minimally invasive, highly specific and sensitive biomarkers that enable early disease detection when therapeutic intervention remains practical. Successful therapeutic intervention is predicated on the ability to detect the cancer early. Similar unmet medical needs abound in most fields of medicine and require novel methodological approaches. Proteomic profiling of body fluids presents a sensitive diagnostic tool for early cancer detection. Here we describe such a strategy of comparative proteomics to identify potential serum-based biomarkers to distinguish high-risk chronic hepatitis C virus infected patients from HCC patients. In order to compensate for the extraordinary dynamic range in serum proteins, enrichment methods that compress the dynamic range without surrendering proteome complexity can help minimize the problems associated with many depletion methods. The enriched serum can be resolved using 2D-difference in-gel electrophoresis and the spots showing statistically significant changes selected for identification by liquid chromatography-tandem mass spectrometry. Subsequent quantitative verification and validation of these candidate biomarkers represent an obligatory and rate-limiting process that is greatly enabled by selected reaction monitoring (SRM). SRM is a tandem mass spectrometry method suitable for identification and quantitation of target peptides within complex mixtures independent on peptide-specific antibodies. Ultimately, multiplexed SRM and dynamic multiple reaction monitoring can be utilized for the simultaneous analysis of a biomarker panel derived from support vector machine learning approaches, which allows monitoring a specific disease state such as early HCC. Overall, this approach yields high probability biomarkers for clinical validation in large patient cohorts and represents a strategy extensible to many diseases.

Serum amyloid a truncations in type 2 diabetes mellitus

Serum Amyloid A (SAA) is an acute phase protein complex consisting of several abundant isoforms. The N- terminus of SAA is critical to its function in amyloid formation. SAA is frequently truncated, either missing an arginine or an arginine-serine dipeptide, resulting in isoforms that may influence the capacity to form amyloid. However, the relative abundance of truncated SAA in diabetes and chronic kidney disease is not known.

Lung Cancer Biomarkers

Lung cancer is the most frequently occurring cancer in the world and continually leads in mortality among cancers. The overall 5-year survival rate for lung cancer has risen only 4% (from 12% to 16%) over the past 4 decades, and late diagnosis is a major obstacle in improving lung cancer prognosis. Survival of patients undergoing lung resection is greater than 80%, suggesting that early detection and diagnosis of cancers before they become inoperable and lethal will greatly improve mortality. Lung cancer biomarkers can be used for screening, detection, diagnosis, prognosis, prediction, stratification, therapy response monitoring, and so on. This review focuses on noninvasive diagnostic and prognostic biomarkers. For that purpose, our discussion in this review will focus on biological fluid-based biomarkers. The body fluids include blood (serum or plasma), sputum, saliva, BAL, pleural effusion, and VOC. Since it is rich in different cellular and molecular elements and is one of the most convenient and routine clinical procedures, serum or plasma is the main source for the development and validation of many noninvasive biomarkers. In terms of molecular aspects, the most widely validated ones are proteins, some of which are used in the clinical sector, though in limited accessory purposes. We will also discuss the lung cancer (protein) biomarkers in clinical trials and currently in the validation phase with hundreds of samples. After proteins, we will discuss microRNAs, methylated DNA, and circulating tumor cells, which are being vigorously developed and validated as potential lung cancer biomarkers. The main aim of this review is to provide researchers and clinicians with an understanding of the potential noninvasive lung cancer biomarkers in biological fluids that have recently been discovered.

Structure of HDL: particle subclasses and molecular components

A molecular understanding of high-density lipoprotein (HDL) will allow a more complete grasp of its interactions with key plasma remodelling factors and with cell-surface proteins that mediate HDL assembly and clearance. However, these particles are notoriously heterogeneous in terms of almost every physical, chemical and biological property. Furthermore, HDL particles have not lent themselves to high-resolution structural study through mainstream techniques like nuclear magnetic resonance and X-ray crystallography; investigators have therefore had to use a series of lower resolution methods to derive a general structural understanding of these enigmatic particles. This chapter reviews current knowledge of the composition, structure and heterogeneity of human plasma HDL. The multifaceted composition of the HDL proteome, the multiple major protein isoforms involving translational and posttranslational modifications, the rapidly expanding knowledge of the HDL lipidome, the highly complex world of HDL subclasses and putative models of HDL particle structure are extensively discussed. A brief history of structural studies of both plasma-derived and recombinant forms of HDL is presented with a focus on detailed structural models that have been derived from a range of techniques spanning mass spectrometry to molecular dynamics.

Characterization of lacrimal proline-rich protein 4 (PRR4) in human tear proteome

This study was initiated considering the lack of comprehensive characteristics profile of PRR4 in tears of healthy subjects. Therefore, detailed characterizations of PRR4 from basal tears employing in-gel and in-solution digestions for MS systems are presented herein. First, pooled tear samples (n = 10) were utilized to identify PRR4-rich region/spots in 1DE/2DE gels employing LC-MALDI-MS and 1DE-LC-ESI-LTQ-Orbitrap-MS systems. PRR4-rich region and ten spots with vast polymorphisms (Mr : 17-30 kDa, pI: 3.0-6.6) were identified in 1DE and 2DE gels, respectively. In addition, combinations of four types of PTMs, which are methylation, acetylation, oxidation, and pyroglutamate formation, were identified in these ten PRR4 spots. Furthermore, a targeted data-acquisition approach was utilized to identify PRR4 isoforms in individual tear samples (n = 61) by in-solution digestion combined with a LC-ESI-LTQ-Orbitrap-MS system. Importantly, a new PRR4 isoform designated as PRR4-N3 in addition to PRR4 (gi154448886) and pHL E1F1 (gi1050983) was identified. Moreover, different combinations of these three PRR4 isoforms identified in the individual tear samples could be categorized into six distinguished groups. Conclusively, these findings provide fundamental insight into the complex characteristics profile of PRR4 isoforms and their PTMs in tears of healthy individuals.

Serum-based protein biomarkers for detection of lung cancer

Lung cancer is one of the most common cancers in terms of both incidence and mortality.The major reasons for the increasing number of deaths from lung cancer are late detection and lack of effective therapies. To improve our understanding of lung cancer biology, there is urgent need for blood-based, non-invasive molecular tests to assist in its detection in a cost-effective manner at an early stage when curative interventions are still possible. Recent advances in proteomic technology have provided extensive, high throughput analytical tools for identification, characterization and functional studies of proteomes. Changes in protein expression patterns in response to stimuli can serve as indicators or biomarkers of biological and pathological processes as well as physiological and pharmacological responses to drug treatment, thus aiding in early diagnosis and prognosis of disease. However, only a few biomarkers have been approved by the FDA to date for screening and diagnostic purposes. This review provides a brief overview of currently available proteomic techniques, their applications and limitations and the current state of knowledge about important serum biomarkers in lung cancer and their potential value as prognostic and diagnostic tools.

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers.

The Equine PeptideAtlas: a resource for developing proteomics-based veterinary research

Progress in MS-based methods for veterinary research and diagnostics is lagging behind compared to the human research, and proteome data of domestic animals is still not well represented in open source data repositories. This is particularly true for the equine species. Here we present a first Equine PeptideAtlas encompassing high-resolution tandem MS analyses of 51 samples representing a selection of equine tissues and body fluids from healthy and diseased animals. The raw data were processed through the Trans-Proteomic Pipeline to yield high quality identification of proteins and peptides. The current release comprises 24 131 distinct peptides representing 2636 canonical proteins observed at false discovery rates of 0.2% at the peptide level and 1.4% at the protein level. Data from the Equine PeptideAtlas are available for experimental planning, validation of new datasets, and as a proteomic data mining resource. The advantages of the Equine PeptideAtlas are demonstrated by examples of mining the contents for information on potential and well-known equine acute phase proteins, which have extensive general interest in the veterinary clinic. The extracted information will support further analyses, and emphasizes the value of the Equine PeptideAtlas as a resource for the design of targeted quantitative proteomic studies.

MRM for the verification of cancer biomarker proteins: recent applications to human plasma and serum

Accurate cancer biomarkers are needed for early detection, disease classification, prediction of therapeutic response and monitoring treatment. While there appears to be no shortage of candidate biomarker proteins, a major bottleneck in the biomarker pipeline continues to be their verification by enzyme linked immunosorbent assays. Multiple reaction monitoring (MRM), also known as selected reaction monitoring, is a targeted mass spectrometry approach to protein quantitation and is emerging to bridge the gap between biomarker discovery and clinical validation. Highly multiplexed MRM assays are readily configured and enable simultaneous verification of large numbers of candidates facilitating the development of biomarker panels which can increase specificity. This review focuses on recent applications of MRM to the analysis of plasma and serum from cancer patients for biomarker verification. The current status of this approach is discussed along with future directions for targeted mass spectrometry in clinical biomarker validation.

Expression of serum amyloid A in uterine cervical cancer

Background

As an acute-phase protein, serum amyloid A (SAA) is expressed primarily in the liver. However, its expression in extrahepatic tissues, especially in tumor tissues, was also demonstrated recently. In our study, we investigated the expression of SAA in uterine cervical carcinomas, and our results suggested its potential as a serum biomarker.

Methods

Quantitative real-time polymerase chain reaction (RT-PCR), immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA) were used to evaluate the SAA gene and protein expression levels in the tissues and sera of patients with non-neoplastic lesions (NNLs), cervical intraepithelial neoplasia (CIN) and cervical carcinoma (CC).

Results

Compared with NNLs, the SAA gene (SAA1 and SAA4) expression levels were significantly higher in uterine CC (mean copy numbers: 138.7 vs. 5.01, P < 0.000; and 1.8 vs. 0.079, P = 0.001, respectively) by real-time PCR. IHC revealed cytoplasmic SAA protein staining in tissues from adenocarcinoma and squamous cell carcinoma of the cervix. The median serum concentrations (μg/ml) of SAA were 6.02 in patients with NNLs and 10.98 in patients with CIN (P = 0.31). In contrast, the median serum SAA concentration was 23.7 μg/ml in uterine CC patients, which was significantly higher than the SAA concentrations of the NNL group (P = 0.002) and the CIN group (P = 0.024).

Conclusions

Our data suggested that SAA might be a uterine CC cell product. High SAA concentrations in the serum of CC patients may have a role in monitoring disease occurrence and could have therapeutic applications.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1433263219102962.

MRM validation of targeted nonglycosylated peptides from N-glycoprotein biomarkers using direct trypsin digestion of undepleted human plasma

A rapid, simple, and reproducible MRM-based validation method for serological glycoprotein biomarkers in clinical use was developed by targeting the nonglycosylated tryptic peptides adjacent to N-glycosylation sites. Since changes in protein glycosylation are known to be associated with a variety of diseases, glycoproteins have been major targets in biomarker discovery. We previously found that nonglycosylated tryptic peptides adjacent to N-glycosylation sites differed in concentration between normal and hepatocellular carcinoma (HCC) plasma due to differences in steric hindrance of the glycan moiety in N-glycoproteins to tryptic digestion (Lee et al., 2011). To increase the feasibility and applicability of clinical validation of biomarker candidates (nonglycosylated tryptic peptides), we developed a method to effectively monitor nonglycosylated tryptic peptides from a large number of plasma samples and to reduce the total analysis time with maximizing the effect of steric hindrance by the glycans during digestion of glycoproteins. The AUC values of targeted nonglycosylated tryptic peptides were excellent (0.955 for GQYCYELDEK, 0.880 for FEDGVLDPDYPR and 0.907 for TEDTIFLR), indicating that these could be effective biomarkers for hepatocellular carcinoma. This method provides the necessary throughput required to validate glycoprotein biomarkers, as well as quantitative accuracy for human plasma analysis, and should be amenable to clinical use.

BIOLOGICAL SIGNIFICANCE

Difficulties in verifying and validating putative protein biomarkers are often caused by complex sample preparation procedures required to determine their concentrations in a large number of plasma samples. To solve the difficulties, we developed MRM-based protein biomarker assays that greatly reduce complex, time-consuming, and less reproducible sample pretreatment steps in plasma for clinical implementation. First, we used undepleted human plasma samples without any enrichment procedures. Using nanoLC/MS/MS, we targeted nonglycosylated tryptic peptides adjacent to N-linked glycosylation sites in N-linked glycoprotein biomarkers, which could be detected in human plasma samples without depleting highly abundant proteins. Second, human plasma proteins were digested with trypsin without reduction and alkylation procedures to minimize sample preparation. Third, trypsin digestion times were shortened so as to obtain reproducible results with maximization of the steric hindrance effect of the glycans during enzyme digestion. Finally, this rapid and simple sample preparation method was applied to validate targeted nonglycosylated tryptic peptides as liver cancer biomarker candidates for diagnosis in 40 normal and 41 hepatocellular carcinoma (HCC) human plasma samples. This strategy provided the necessary throughput required to monitor protein biomarkers, as well as quantitative accuracy in human plasma analysis. From biomarker discovery to clinical implementation, our method will provide a biomarker study platform that is suitable for clinical deployment, and can be applied to high-throughput approaches.

Organization and biology of the porcine serum amyloid A (SAA) gene cluster: isoform specific responses to bacterial infection

Serum amyloid A (SAA) is a prominent acute phase protein. Although its biological functions are debated, the wide species distribution of highly homologous SAA proteins and their uniform behavior in response to injury or inflammation in itself suggests a significant role for this protein. The pig is increasingly being used as a model for the study of inflammatory reactions, yet only little is known about how specific SAA genes are regulated in the pig during acute phase responses and other responses induced by pro-inflammatory host mediators. We designed SAA gene specific primers and quantified the gene expression of porcine SAA1, SAA2, SAA3, and SAA4 by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) in liver, spleen, and lung tissue from pigs experimentally infected with the Gram-negative swine specific bacterium Actinobacillus pleuropneumoniae, as well as from pigs experimentally infected with the Gram-positive bacterium Staphylococcus aureus. Our results show that: 1) SAA1 may be a pseudogene in pigs; 2) we were able to detect two previously uncharacterized SAA transcripts, namely SAA2 and SAA4, of which the SAA2 transcript is primarily induced in the liver during acute infection and presumably contributes to circulating SAA in pigs; 3) Porcine SAA3 transcription is induced both hepatically and extrahepatically during acute infection, and may be correlated to local organ affection; 4) Hepatic transcription of SAA4 is markedly induced in pigs infected with A. pleuropneumoniae, but only weakly in pigs infected with S. aureus. These results for the first time establish the infection response patterns of the four porcine SAA genes which will be of importance for the use of the pig as a model for human inflammatory responses, e.g. within sepsis, cancer, and obesity research.

Quantitative pattern analysis of the N-terminally processed isoforms of platelet factor-4 in serum

RATIONALE

Platelet factor 4 (PF4) is a small cytokine belonging to the CXC chemokine family which has been shown to play a role in inflammation and in the regulation of angiogenesis. In general, chemokines are susceptible to proteolytic cleavage in amino and carboxy terminal regions, which usually results in dramatic changes to the chemokine bioactivity. The purpose of this study was to identify various platelet factor-4 (PF4) isoforms caused by proteolytic processing and to quantify their levels in normal serum.

METHODS

First, we identified the N-terminally truncated PF4 isoforms from a standard purified PF4 protein sample by using mass spectrometry (MS) and tandem mass spectrometry (MS/MS) analysis. Then, we used high-performance liquid chromatography (HPLC) to semi-purify PF4 from serum samples, and the levels of the four most abundant PF4 isoforms were quantitatively determined using selected reaction monitoring (SRM) assays on a nano-LC/triple-quadrupole mass spectrometer.

RESULTS

We have identified seven N-terminally processed PF4 isoforms and compared the levels of major PF4 isoforms from nine serum samples. Pro-p1 (EAEEDGDLQCLCVK-; average MW, 7765.2) is the major PF4 isoform in serum whereas the PF4 isoforms, designated Prot-p4 (FASAEAEEDGDLQCLCVK-;average MW, 8141.5), Prot-p3 (SAEAEEDGDLQCLCVK-; average MW, 7923.3), and Prot-p2 (AEEDGDLQCLCVK- ; average MW, 7836.3), are at about 16%, 3%, and 2% levels of the major one, respectively.

CONCLUSIONS

This study is the first report on the levels of N-terminally processed PF4 isoforms in serum. Also, this study shows the usefulness of SRM in determining concentrations of protein isoform variants, which can be often overlooked in immunoassay analysis.

Analysis of protein isoforms: can we do it better?

Protein isoforms/splice variants can play important roles in various biological processes and can potentially be used as biomarkers or therapeutic targets/mediators. Thus, there is a need for efficient and, importantly, accurate methods to distinguish and quantify specific protein isoforms. Since protein isoforms can share a high percentage of amino acid sequence homology and dramatically differ in their cellular concentration, the task for accuracy and efficiency in methodology and instrumentation is challenging. The analysis of intact proteins has been perceived to provide a more accurate and complete result for isoform identification/quantification in comparison to analysis of the corresponding peptides that arise from protein enzymatic digestion. Recently, novel approaches have been explored and developed that can possess the accuracy and reliability important for protein isoform differentiation and isoform-specific peptide targeting. In this review, we discuss the recent development in methodology and instrumentation for enhanced detection of protein isoforms as well as the examples of their biological importance.