Targeted proteomics for validation of biomarkers in clinical samples

Discovery Proteomics and Absolute Protein Quantification Can Be Performed Simultaneously on an Orbitrap-Based Mass Spectrometer

Mass spectrometry (MS) has steadily moved into the forefront of quantification-centered protein research. Protein cleavage isotope dilution MS is a proven way for quantifying proteins by using an isotope-labeled analogue of a peptide fragment of the parent protein as an internal standard. Parallel reaction monitoring (PRM) has become the go-to approach for such quantification on an Orbitrap-based instrument as it is assumed that the instrument sensitivity is enhanced. We performed a comparative study on data-dependent acquisition (DDA) and PRM-based workflows to quantify egg yolk protein precursors or vitellogenins (VTGs) Aa, Ab, and C in striped bass (Morone saxatilis). VTG proportions serve as a developmental measure of egg quality, possibly changing with the environment, and have been studied as an indicator of the health of North Carolina stocks. Based on single-factor analysis of variance comparisons of mean VTG amounts across fish from the same sample groupings, our results indicate that there is no statistical difference between MS1-based and MS2-based VTG quantification. We further conclude that DDA is able to deliver both discovery data and absolute quantification data in the same experiment.

Clinical Proteomics for Meningioma: An Integrated Workflow for Quantitative Proteomics and Biomarker Validation in Formalin-Fixed Paraffin-Embedded Tissue Samples

Clinical proteomics is a rapidly emerging frontier in laboratory medicine. High-throughput proteomic investigations of biopsy tissues provide mechanistic insights into complex human diseases. For large-scale proteomics, formalin-fixed and paraffin-embedded (FFPE) tissue samples offer a viable alternative to fresh-frozen (FF) tissues that have restricted availability. In this context, meningioma is one of the most common primary brain tumors where innovation in diagnostics and therapeutic targets can benefit from clinical proteomics. We present here an integrated workflow for quantitative proteomics and biomarker validation of meningioma FFPE tissues. Applying label-free quantitative (LFQ) proteomics, we reproducibly (Pearson's correlation: 0.84-0.91) obtained an in-depth proteome coverage (nearly 4000 proteins per sample) from 120 min gradient of single unfractionated mass spectrometry run. Furthermore, building upon LFQ data and literature curated set of meningioma-associated proteins, we validated VIM, AHNAK, and CLU from FFPE tissues using selected reaction monitoring (SRM) assay and compared its performance with FF tissues. This study illustrates how knowledge from label-free proteomics can be integrated for selecting peptides for targeted validation and suggests that FFPE tissues are comparable to FF tissues for SRM assays. This quantitative clinical proteomics workflow is scalable for large-scale clinical diagnostics studies in the future, for example, utilizing the global repository of FFPE tissues in meningioma and possibly in other cancers.

Proteomics and Leishmaniasis: Potential Clinical Applications

Leishmaniases are diseases caused by protozoan parasites of the genus Leishmania. They are endemic in 98 countries, affect around 12 million people worldwide and may present several distinct clinical forms. Unfortunately, there are only a few drugs available for treatment of leishmaniasis, which are toxic and not always effective. Different parasite species and different clinical forms require optimization of the treatment or more specific therapies, which are not available. The emergence of resistance is also a matter of concern. Besides, diagnosis can sometimes be complicated due to atypical manifestations and associations with other pathologies. In this review, proteomic data are presented and discussed in terms of their application in important issues in leishmaniasis such as parasite resistance to chemotherapy, diagnosis of active disease in patients and dogs, markers for different clinical forms, identification of virulence factors, and their potential use in vaccination. It is shown that proteomics has contributed to the discovery of potential biomarkers for prognosis, diagnosis, therapeutics, monitoring of disease progression, treatment follow-up and identification of vaccine candidates for specific diseases. However, the authors believe its capabilities have not yet been fully explored for routine clinical analysis for several reasons, which will be presented in this review.

How Do Postgenomic Innovations Emerge? Building Legitimacy by Proteomics Standards and Informing the Next-Generation Technology Policy

How do postgenomic innovations emerge and become legitimate? Proteomics, a frequently utilized postgenomic technology, provides a valuable case study of the sociotechnical strategies used by an emergent scientific field to establish its legitimacy and assert political power. Chief among these strategies is standard making, an inherently political process that requires examination through a critical social science lens. We report in this study an original case study from interviews with proteomics scientists and observations at conferences of the Human Proteome Organization and Australasian Proteomics Society over a 5-year period (2011-2015). The study contributes new knowledge on how an emerging postgenomic science uses standard-setting practices to politically legitimize a hitherto contested technology. Drawing on legitimacy theory, we show how proteomics scientists and organizations used standards as strategic tools to establish the legitimacy of this postgenomic field and affirm that proteomics can generate verifiable and reproducible results, thereby establishing it as a legitimate scientific field. Notably, legitimacy can be leveraged, at the same time, to maximize political power vis-à-vis other fields of science and as such embodies power relationships. These data collectively inform the broader context, in which postgenomic innovations emerge and legitimize, both technically and politically, through standards making. These findings have relevance for the design of next generation technology policies by demonstrating that standards are not "just" standards or neutral constructs but also tools to leverage political power of and by science and innovation actors, as shown in this case study of the emerging early phase of proteomics from 2011 to 2015.

Bayesian Classification of Proteomics Biomarkers from Selected Reaction Monitoring Data using an Approximate Bayesian Computation-Markov Chain Monte Carlo Approach

Selected reaction monitoring (SRM) has become one of the main methods for low-mass-range–targeted proteomics by mass spectrometry (MS). However, in most SRM-MS biomarker validation studies, the sample size is very small, and in particular smaller than the number of proteins measured in the experiment. Moreover, the data can be noisy due to a low number of ions detected per peptide by the instrument. In this article, those issues are addressed by a model-based Bayesian method for classification of SRM-MS data. The methodology is likelihood-free, using approximate Bayesian computation implemented via a Markov chain Monte Carlo procedure and a kernel-based Optimal Bayesian Classifier. Extensive experimental results demonstrate that the proposed method outperforms classical methods such as linear discriminant analysis and 3NN, when sample size is small, dimensionality is large, the data are noisy, or a combination of these.

A Combination of DNA-peptide Probes and Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS): A Quasi-Targeted Proteomics Approach for Multiplexed MicroRNA Quantification

The distorted and unique expression of microRNAs (miRNAs) in cancer makes them an attractive source of biomarker. There is much evidence indicating that a panel of miRNAs, termed "miRNA fingerprints", is more specific and informative than an individual miRNA as biomarker. Thus, multiplex assays for simultaneous quantification of multiple miRNAs could be more potent in clinical practice. However, current available assays normally require pre-enrichment, amplification and labeling steps, and most of them are semi-quantitative or lack of multiplexing capability. In this study, we developed a quasi-targeted proteomics assay for multiplexed miRNA quantification by a combination of DNA-peptide probes and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Specifically, the signal of target miRNAs (i.e., miR-21, miR-let7a, miR-200c, miR-125a and miR-15b) was converted into the mass response of reporter peptides by hybridization of miRNAs with DNA-peptide probes and subsequent tryptic digestion to release the peptides. After a careful optimization of conditions related to binding, conjugation, hybridization and multiple reaction monitoring (MRM) detection, the assay was validated for each miRNA and the limit of quantification (LOQ) for all the miRNAs can achieve 1 pM. Moreover, crosstalk between DNA-peptide probes in multiplex assay was sophisticatedly evaluated. Using this quasi-targeted proteomics assay, the level of target miRNAs was determined in 3 human breast cell lines and 36 matched pairs of breast tissue samples. Finally, simplex assay and qRT-PCR were also performed for a comparison. This approach grafts the strategy of targeted proteomics into miRNA quantification and may offer a new way for multiplexed miRNA profiling.

Proteogenomics for the Comprehensive Analysis of Human Cellular and Serum Antibody Repertoires

The vast repertoire of immunoglobulins produced by the immune system is a consequence of the huge amount of antigens to which we are exposed every day. The diversity of these immunoglobulins is due to different mechanisms (including VDJ recombination, somatic hypermutation, and antigen selection). Understanding how the immune system is capable of generating this diversity and which are the molecular bases of the composition of immunoglobulins are key challenges in the immunological field. During the last decades, several techniques have emerged as promising strategies to achieve these goals, but it is their combination which appears to be the fruitful solution for increasing the knowledge about human cellular and serum antibody repertoires.In this chapter, we address the diverse strategies focused on the analysis of immunoglobulin repertoires as well as the characterization of the genomic and peptide sequences. Moreover, the advantages of combining various -omics approaches are discussed through review different published studies, showing the benefits in clinical areas.

Clinical proteomics in cancer: Where we are

Proteomics has emerged as a promising field in the post-genomic era. Notwithstanding the great advances provided by gene expression analysis in cancer, the lack of a correlation between gene expression and protein levels has highlighted the need for a proteomic focus on cancer. Although the increasing knowledge regarding cancer biology, a reliable marker to improve diagnosis, prognosis and treatment for cancer patients is not a reality at present. In this review, we address the main considerations regarding proteomics-based studies and their clinical applications on cancer research, highlighting some considerations related to strengths and limitations of proteomics-based studies and its application to clinical practice.

Quantification of microRNA by DNA-Peptide Probe and Liquid Chromatography-Tandem Mass Spectrometry-Based Quasi-Targeted Proteomics

The distorted and unique expression of microRNAs (miRNAs) in cancer makes them an attractive source of biomarkers. However, one of prerequisites for the application of miRNAs in clinical practice is to accurately profile their expression. Currently available assays normally require pre-enrichment, amplification, and labeling steps, and most of them are semiquantitative. In this study, we converted the signal of target miR-21 into reporter peptide by a DNA-peptide probe and the reporter peptide was ultimately quantified using LC-MS/MS-based targeted proteomics. Specifically, substrate peptide GDKAVLGVDPFR containing reporter peptide AVLGVDPFR and tryptic cleavage site (lysine at position 3) was first designed, followed by the conjugation with DNA sequence that was complementary to miR-21. The newly formed DNA-peptide probe was then hybridized with miR-21, which was biotinylated and attached to streptavidin agarose in advance. After trypsin digestion, the reporter peptide was released and monitored by a targeted proteomics assay. The obtained limit of quantification (LOQ) was 1 pM, and the detection dynamic range spanned ∼5 orders of magnitude. Using this assay, the developed quasi-targeted proteomics approach was applied to determine miR-21 level in breast cells and tissue samples. Finally, qRT-PCR was also performed for a comparison. This report grafted the strategy of targeted proteomics into miRNA quantification.

In silico verification and parallel reaction monitoring prevalidation of potential prostate cancer biomarkers

PURPOSE

Targeted proteomics of potential biomarkers is often challenging. Hence, we developed an intermediate workflow to streamline potential urinary biomarkers of prostate cancer (PCa).

MATERIALS & METHODS

Using previously discovered potential PCa biomarkers; we selected proteotypic peptides for targeted validation. Preliminary in silico immunohistochemical and single reaction monitoring (SRM) verification was performed. Successful PTPs were then prevalidated using parallel reaction monitoring (PRM) and reconfirmed in 15 publicly available databases.

RESULTS

Stringency-based targetable potential biomarkers were shortlisted following in silico screening. PRM reveals top 12 potential biomarkers including the top ranking seven in silico verification-based biomarkers. Database reconfirmation showed differential expression between PCa and benign/normal prostatic urine samples.

CONCLUSION

The pragmatic penultimate screening step, described herein, would immensely improve targeted proteomics validation of potential disease biomarkers.

Plasmodium falciparum malaria: proteomic studies

Despite advances in treatment and campaigns for prevention and control of malaria on the various continents where it is still rampant, this disease remains significantly relevant to the contemporary world. Plasmodium falciparum is the organism that is mainly responsible for severe malaria, which is characterized by disturbances in different organs and systems, with possibly fatal outcomes. Although incipient, proteomic studies of malaria have yielded favorable prospects for elucidating the biological aspects of Plasmodium as well as the pathophysiological, diagnostic, prophylactic, and therapeutic mechanisms of the disease. Thus, the aim of the present article is to present a brief review of the applications of proteomic analysis in P. falciparum malaria.

Closing the gap between brain banks and proteomics to advance the study of neurodegenerative diseases

Neurodegenerative diseases (NDs), such as Alzheimer's disease and Parkinson's disease, are among the most debilitating neurological disorders, and as life expectancy rises quickly around the world, the scientific and clinical challenges of dealing with them will also increase dramatically, putting increased pressure on the biomedical community to come up with innovative solutions for the understanding, diagnosis, and treatment of these conditions. Despite several decades of intensive research, there is still little that can be done to prevent, cure, or even slow down the progression of NDs in most patients. There is an urgent need to develop new lines of basic and applied research that can be quickly translated into clinical application. One way to do this is to apply the tools of proteomics to well-characterized samples of human brain tissue, but a closer partnership must still be forged between proteomic scientists, brain banks, and clinicians to explore the maximum potential of this approach. Here, we analyze the challenges and potential benefits of using human brain tissue for proteomics research toward NDs.

Assessment of tandem mass spectrometry and high-resolution mass spectrometry for the analysis of bupivacaine in plasma

Triple quadrupole mass spectrometers coupled with high performance liquid chromatography are workhorses in quantitative bioanalyses. They provide substantial benefits including reproducibility, sensitivity and selectivity for trace analysis. Selected reaction monitoring allows targeted assay development but datasets generated contain very limited information. Data mining and analysis of nontargeted high-resolution mass spectrometry profiles of biological samples offer the opportunity to perform more exhaustive assessments, including quantitative and qualitative analysis. The objectives of this study were to test method precision and accuracy, to statistically compare bupivacaine drug concentration in real study samples and to verify if high-resolution and accurate mass data collected in scan mode can actually permit retrospective data analysis, more specifically, extract metabolite related information. The precision and accuracy data presented using both instruments provided equivalent results. Overall, the accuracy ranged from 106.2 to 113.2% and the precision observed was from 1.0 to 3.7%. Statistical comparisons using a linear regression between both methods revealed a coefficient of determination (R(2)) of 0.9996 and a slope of 1.02, demonstrating a very strong correlation between the two methods. Individual sample comparison showed differences from -4.5 to 1.6%, well within the accepted analytical error. Moreover, post-acquisition extracted ion chromatograms at m/z 233.1648 ± 5 ppm (M - 56) and m/z 305.2224 ± 5 ppm (M + 16) revealed the presence of desbutyl-bupivacaine and three distinct hydroxylated bupivacaine metabolites. Post-acquisition analysis allowed us to produce semi-quantitative evaluations of the concentration-time profiles for bupicavaine metabolites.

Modeling and systematic analysis of biomarker validation using selected reaction monitoring

Background

Discovery and validation of protein biomarkers with high specificity is the main challenge of current proteomics studies. Different mass spectrometry models are used as shotgun tools for the discovery of biomarkers. Validation of a set of selected biomarkers from a list of candidates is an important stage in the biomarker identification pipeline. Validation is typically done by triple quadrupole (QQQ) mass spectrometry (MS) running in selected reaction monitoring (SRM) mode. Although the individual modules of this pipeline have been studied, there is little work on integrating the components from a systematic point of view.

Results

This paper analyzes the SRM experiment pipeline in a systematic fashion, by modeling the main stages of the biomarker validation process. The proposed models for SRM and protein mixture are then used to study the effect of different parameters on the final performance of biomarker validation. Sample complexity, purification, peptide ionization, and peptide specificity are among the parameters of the SRM experiment that are studied. We focus on the sensitivity of the SRM pipeline to the working parameters, in order to identify the bottlenecks where time and energy should be spent in designing the experiment.

Conclusions

The model presented in this paper can be utilized to observe the effect of different instrument and experimental settings on biomarker validation by SRM. On the other hand, the model would be beneficial for optimization of the work flow as well as identification of the bottlenecks of the pipeline. Also, it creates the required infrastructure for predicting the performance of the SRM pipeline for a specific setting of the parameters.

Electronic supplementary material

The online version of this article (doi:10.1186/s13637-014-0017-y) contains supplementary material, which is available to authorized users.

Using isolated rat kidney to discover kidney origin biomarkers in urine

The use of targeted proteomics to identify urinary biomarkers of kidney disease in urine can avoid the interference of serum proteins. It may provide better sample throughput, higher sensitivity, and specificity. Knowing which urinary proteins to target is essential for targeted proteomics. In perfusates, there were proteins not found in normal human urine which may become biomarkers with zero background. There were proteins not found in normal human plasma which will not be influenced by other normal organs and will be kidney specific. When compared with existing candidate biomarkers, over 90 % of the kidney origin proteins in urine identified in this study have not been examined as candidate biomarkers of kidney diseases.

Using an isolated rat kidney model to identify kidney origin proteins in urine

The use of targeted proteomics to identify urinary biomarkers of kidney disease in urine can avoid the interference of serum proteins. It may provide better sample throughput, higher sensitivity, and specificity. Knowing which urinary proteins to target is essential. By analyzing the urine from perfused isolated rat kidneys, 990 kidney origin proteins with human analogs were identified in urine. Of these proteins, 128 were not found in normal human urine and may become biomarkers with zero background. A total of 297 proteins were not found in normal human plasma. These proteins will not be influenced by other normal organs and will be kidney specific. The levels of 33 proteins increased during perfusion with an oxygen-deficient solution compared to those perfused with oxygen. The 75 proteins in the perfusion-driven urine have a significantly increased abundance ranking compared to their ranking in normal human urine. When compared with existing candidate biomarkers, over ninety percent of the kidney origin proteins in urine identified in this study have not been examined as candidate biomarkers of kidney diseases.

Breast cancer biomarkers: proteomic discovery and translation to clinically relevant assays

Although the molecular classification and prognostic assessment of breast tumors based on gene expression profiling is well established, a number of proteomic studies that propose potential breast cancer biomarkers has not yet led to any new diagnostic, prognostic or predictive test in wide clinical use. This review examines the current status of breast cancer biomarkers, discusses sample types (including plasma, tumor tissue, nipple aspirate and ductal lavage, as well as cell culture models) and different electrophoretic and mass spectrometry methods that have been widely used for the discovery of proteomic biomarkers in breast cancer, and also considers several approaches to biomarker validation. The pathway leading from the initial proteomic discovery and validation process to translation into a clinically useful test is also discussed.

Application of selected reaction monitoring for multiplex quantification of clinically validated biomarkers in formalin-fixed, paraffin-embedded tumor tissue

One of the critical gaps in the clinical diagnostic space is the lack of quantitative proteomic methods for use on formalin-fixed, paraffin-embedded (FFPE) tissue. Herein, we describe the development of a quantitative, multiplexed, mass spectrometry-based selected reaction monitoring (SRM) assay for four therapeutically important targets: epidermal growth factor receptor, human EGF receptor (HER)-2, HER3, and insulin-like growth factor-1 receptor. These assays were developed using the Liquid Tissue-SRM technology platform, in which FFPE tumor tissues were microdissected, completely solubilized, and then subjected to multiplexed quantitation by SRM mass spectrometry. The assays were preclinically validated by comparing Liquid Tissue-SRM quantitation of FFPE cell lines with enzyme-linked immunosorbent assay/electrochemiluminescence quantitation of fresh cells (R(2) > 0.95). Clinical performance was assessed on two cohorts of breast cancer tissue: one cohort of 10 samples with a wide range of HER2 expression and a second cohort of 19 HER2 IHC 3+ tissues. These clinical data demonstrate the feasibility of quantitative, multiplexed clinical analysis of proteomic markers in FFPE tissue. Our findings represent a significant advancement in cancer tissue analysis because multiplexed, quantitative analysis of protein targets in FFPE tumor tissue can be tailored to specific oncological indications to provide the following: i) complementary support for anatomical pathological diagnoses, ii) patient stratification to optimize treatment outcomes and identify drug resistance, and iii) support for the clinical development of novel therapies.

Analysis of the formalin-fixed paraffin-embedded tissue proteome: pitfalls, challenges, and future prospectives

Formalin-fixed paraffin-embedded (FFPE) tissues are a real treasure for retrospective analysis considering the amount of samples present in hospital archives, combined with pathological, clinical, and outcome information available for every sample. Although unlocking the proteome of these tissues is still a challenge, new approaches are being developed. In this review, we summarize the different mass spectrometry platforms that are used in human clinical studies to unravel the FFPE proteome. The different ways of extracting crosslinked proteins and the analytical strategies are pointed out. Also, the pitfalls and challenges concerning the quality of FFPE proteomic approaches are depicted. We also evaluated the potential of these analytical methods for future clinical FFPE proteomics applications.

Multiplex targeted proteomic assay for biomarker detection in plasma: a pancreatic cancer biomarker case study

Biomarkers are most frequently proteins that are measured in the blood. Their development largely relies on antibody creation to test the protein candidate performance in blood samples of diseased versus nondiseased patients. The creation of such antibody assays has been a bottleneck in biomarker progress due to the cost, extensive time, and effort required to complete the task. Targeted proteomics is an emerging technology that is playing an increasingly important role to facilitate disease biomarker development. In this study, we applied a SRM-based targeted proteomics platform to directly detect candidate biomarker proteins in plasma to evaluate their clinical utility for pancreatic cancer detection. The characterization of these protein candidates used a clinically well-characterized cohort that included plasma samples from patients with pancreatic cancer, chronic pancreatitis, and healthy age-matched controls. Three of the five candidate proteins, including gelsolin, lumican, and tissue inhibitor of metalloproteinase 1, demonstrated an AUC value greater than 0.75 in distinguishing pancreatic cancer from the controls. In addition, we provide an analysis of the reproducibility, accuracy, and robustness of the SRM-based proteomics platform. This information addresses important technical issues that could aid in the adoption of the targeted proteomics platform for practical clinical utility.

Selected reaction monitoring by linear ion-trap mass spectrometry can effectively be applicable to simultaneous quantification of multiple peptides

Selected reaction monitoring (SRM) mass spectrometry (MS) is becoming a popular approach for targeted quantitative proteomics. Triple-quadrupole mass spectrometers have been historically considered as the instrument of choice for this type of quantitative analysis. Recently, however, it has been reported that the SRM MS with a linear ion-trap (LIT) mass spectrometer is rather more appropriate for quantitative analysis of large peptides than the triple-quadrupole ones. In this study, we demonstrate that the SRM MS performed with a LIT mass spectrometer can simultaneously analyze multiple peptides and can quantify specific peptides in biological specimens without the use of stable isotope (SI)-labeled standard peptides. Firstly, a mixture of 10 synthesized peptides derived from yeast proteins and bovine serum albumin (BSA) was simultaneously analyzed by the LIT SRM. The ion peak areas of the 10 peptides were linearly correlated with the input amounts between 1 fmol and 10 pmol. Furthermore, the same peptide mixture spiked into human plasma was analyzed, and a linear response was found. Next, the amount of a BSA tryptic peptide was quantified by using an SI-labeled or a non SI-labeled peptide as an external reference standard. The difference in the quantified amounts of the BSA tryptic peptide was less than 10% between the 2 methods, suggesting that the "externally pulsed" non SI-labeled standard peptides derived from another species are useful. These results indicate that the SRM MS conducted with a LIT mass spectrometer is applicable to targeted quantitative proteomics of peptides at least up to 10 in number.

Proteomics and Down syndrome screening: a validation study

OBJECTIVE

In a previous discovery study, we identified seven potential screening markers for Down syndrome (DS). Here, we report on an extended study to validate the discriminative potential of these markers.

METHODS

Concentrations of the seven analytes were measured using bead-based multiplexed immunoassays in maternal serum from 27 DS pregnancies and 27 matched controls. Control samples were matched to the cases by gestational age (exact day), maternal weight ( ± 5 kg), and maternal age ( ± 1 year) and by closest sample date. Prediction values were obtained for current screening markers [pregnancy-associated plasma protein A (PAPP-A), free beta human chorionic gonadotrophin (fβ-hCG) and nuchal translucency (NT)] and seven markers identified before based on concentration fold ratios between DS and controls. Models were fitted based on data of the discovery study or this study and also tested on both datasets.

RESULTS

A significantly higher fold ratio was only found for epidermal growth factor (EGF) (-1.96; p = 0.006). In the prediction model for the current dataset, EGF improved the detection rate (DR) of DS by 5.7% [at a fixed 5% false-positive rate (FPR)] when added to the currently used screening markers.

CONCLUSIONS

Validation of previously identified biomarkers only confirmed EGF for further consideration as a DS screening marker. This underlines the importance of validating biomarkers; in this study, limiting the range of plausible biomarkers to only one suitable biomarker.

Production and use of stable isotope-labeled proteins for absolute quantitative proteomics

In the field of analytical chemistry, stable isotope dilution assays are extensively used in combination with liquid chromatography-mass spectrometry (LC-MS) to provide confident quantification results. Over the last decade, the principle of isotope dilution has been adopted by the proteomic community in order to accurately quantify proteins in biological samples. In these experiments, a protein's concentration is deduced from the ratio between the MS signal of a tryptic peptide and that of a stable isotope-labeled analog, which serves as an internal standard. The first isotope dilution standards introduced in proteomics were chemically synthesized peptides incorporating a stable isotope-tagged amino acid. These isotopically labeled peptide standards, which are currently widely used, are generally added to samples after protein isolation and digestion. Thus, if protein enrichment is necessary, they do not allow correction for protein losses that may occur during sample pre-fractionation, nor do they allow the tryptic digestion yield to be taken into account. To reduce these limitations we have developed the PSAQ (Protein Standard Absolute Quantification) strategy using full-length stable isotope-labeled proteins as quantification standards. These standards and the target proteins share identical biochemical properties. This allows standards to be spiked into samples at an early stage of the analytical process. Thanks to this possibility, the PSAQ method provides highly accurate quantification results, including for samples requiring extensive biochemical pre-fractionation. In this chapter, we describe the production of full-length stable isotope-labeled proteins (PSAQ standards) using cell-free expression devices. The purification and quality control of protein standards, crucial for good-quality and accurate measurements, are also detailed. Finally, application of the PSAQ method to a typical protein quantification assay is presented.

Laboratory Medicine in the Scope of Proteomics and Genomics

Advances in technology, especially in molecular biology, allow for a fast expansion of diagnostic methods in routine clinical practice. New proteomics and genomics technologies could be used for disease specific biomarker discovery and to monitor patient response to the therapy. Genomics and proteomics may also help to establish new, molecular classification of the disease. Applying genomic and proteomic methods to body fluids (serum, cerebrospinal fluid, urine, etc) and tissue extracts would place valuable objective analytical power in the hands of the clinician however validation of those methods is an important issue. The rapid expansion of the diagnostic tools based on developments in proteomic and genomic technologies can be fundamental for the development of personalized medicine.

Proteomic profiling of cancer--opportunities, challenges, and context

The article by Roesch-Ely and colleagues in a recent issue of The Journal of Pathology describes the use of proteomic techniques to examine mucosal biopsies in patients with head and neck squamous cell cancer (HNSCC) and in corresponding control samples. The authors were able to determine the anatomical site of origin of the biopsies based on modelling of multiplex protein datasets, and to use the information to analyse field cancerization as a means of predicting tumour recurrence. Although the study included only a relatively small number of cases, and will require future validation in a larger patient cohort, the results point to the potential of proteomics to increase our understanding of cancer biology, and in this instance to offer clinical value.

Standardization and omics science: technical and social dimensions are inseparable and demand symmetrical study

Standardization is critical to scientists and regulators to ensure the quality and interoperability of research processes, as well as the safety and efficacy of the attendant research products. This is perhaps most evident in the case of "omics science," which is enabled by a host of diverse high-throughput technologies such as genomics, proteomics, and metabolomics. But standards are of interest to (and shaped by) others far beyond the immediate realm of individual scientists, laboratories, scientific consortia, or governments that develop, apply, and regulate them. Indeed, scientific standards have consequences for the social, ethical, and legal environment in which innovative technologies are regulated, and thereby command the attention of policy makers and citizens. This article argues that standardization of omics science is both technical and social. A critical synthesis of the social science literature indicates that: (1) standardization requires a degree of flexibility to be practical at the level of scientific practice in disparate sites; (2) the manner in which standards are created, and by whom, will impact their perceived legitimacy and therefore their potential to be used; and (3) the process of standardization itself is important to establishing the legitimacy of an area of scientific research.

Pooling aqueous humor samples: bias in 2D-LC-MS/MS strategy?

The proteomic analysis of body fluids presents a major challenge in studies of human diseases. Traditional techniques for protein separation require large volumes and large amounts of protein, which may be difficult to obtain for certain fluids, such as the aqueous humor (AH). Two-dimensional liquid chromatography (2D-LC-MS/MS), adapted for peptides separation from complex protein mixtures, provides an alternative approach in proteomic analysis with a potential utility in biomarker research. We investigated several different 2D-LC-MS/MS methods for use with the AH of patients with cataract, traditionally used as a control group in studies of ocular diseases. We compared analyses of individual samples with analyses of pools of proteins or peptides, and found that the investigation strategy used strongly influenced protein identification. We identified 71 proteins related to extracellular proteins highly abundant in serum (e.g., albumin or transferrin) and involved in various functions, such as transport and metabolism, together with intracellular (myeloblastin) or organelle-specific proteins (cytochrome c). An evaluation of the advantages and disadvantages of each method suggested that individual analyses and the use of peptide mixtures should be favored as complementary techniques in the search for biomarkers in ocular diseases.

Enhanced sensitivity for selected reaction monitoring mass spectrometry-based targeted proteomics using a dual stage electrodynamic ion funnel interface

Selected reaction monitoring mass spectrometry (SRM-MS) is playing an increasing role in quantitative proteomics and biomarker discovery studies as a method for high throughput candidate quantification and verification. Although SRM-MS offers advantages in sensitivity and quantification compared with other MS-based techniques, current SRM technologies are still challenged by detection and quantification of low abundance proteins (e.g. present at ∼10 ng/ml or lower levels in blood plasma). Here we report enhanced detection sensitivity and reproducibility for SRM-based targeted proteomics by coupling a nanospray ionization multicapillary inlet/dual electrodynamic ion funnel interface to a commercial triple quadrupole mass spectrometer. Because of the increased efficiency in ion transmission, significant enhancements in overall signal intensities and improved limits of detection were observed with the new interface compared with the original interface for SRM measurements of tryptic peptides from proteins spiked into non-depleted mouse plasma over a range of concentrations. Overall, average SRM peak intensities were increased by ∼70-fold. The average level of detection for peptides also improved by ∼10-fold with notably improved reproducibility of peptide measurements as indicated by the reduced coefficients of variance. The ability to detect proteins ranging from 40 to 80 ng/ml within mouse plasma was demonstrated for all spiked proteins without the application of front-end immunoaffinity depletion and fractionation. This significant improvement in detection sensitivity for low abundance proteins in complex matrices is expected to enhance a broad range of SRM-MS applications including targeted protein and metabolite validation.

Industrialized MS-based proteomics in the search for circulating biomarkers

Proteomics is the study of the expression, structure and function of proteins under a range of cellular conditions. A rapidly evolving component of this field is clinical proteomics, which focuses on proteins involved in human disease and how they are affected by therapeutic intervention. MS is the main analytical technology for identifying and quantifying proteins whose expression is modulated across the normal to disease continuum. Applying this technology to clinical samples, however, is particularly challenging due to high biological variability in the population, a variety of disease stages, nonuniform response to therapy, multiple concomitant treatments and special requirements for handling samples from clinical trials. Given these challenges, an ‘industrialized’ approach is best suited to clinical biomarker development, with its standard operating procedures, process control and ‘chain of custody’. This review will focus, therefore, on MS-based industrialized proteomics for the discovery and verification of circulating candidate clinical protein biomarkers.

Genomic and oncoproteomic advances in detection and treatment of colorectal cancer

Aims

We will examine the latest advances in genomic and proteomic laboratory technology. Through an extensive literature review we aim to critically appraise those studies which have utilized these latest technologies and ascertain their potential to identify clinically useful biomarkers.

Methods

An extensive review of the literature was carried out in both online medical journals and through the Royal College of Surgeons in Ireland library.

Results

Laboratory technology has advanced in the fields of genomics and oncoproteomics. Gene expression profiling with DNA microarray technology has allowed us to begin genetic profiling of colorectal cancer tissue. The response to chemotherapy can differ amongst individual tumors. For the first time researchers have begun to isolate and identify the genes responsible. New laboratory techniques allow us to isolate proteins preferentially expressed in colorectal cancer tissue. This could potentially lead to identification of a clinically useful protein biomarker in colorectal cancer screening and treatment.

Conclusion

If a set of discriminating genes could be used for characterization and prediction of chemotherapeutic response, an individualized tailored therapeutic regime could become the standard of care for those undergoing systemic treatment for colorectal cancer. New laboratory techniques of protein identification may eventually allow identification of a clinically useful biomarker that could be used for screening and treatment. At present however, both expression of different gene signatures and isolation of various protein peaks has been limited by study size. Independent multi-centre correlation of results with larger sample sizes is needed to allow translation into clinical practice.