Sampling and Analytical Strategies for Biomarker Discovery Using Mass Spectrometry

There is an often unspoken truth behind the course of scientific investigation that involves not what is necessarily academically worthy of study, but rather what is scientifically worthy in the eyes of funding agencies. The perception of worthy research is, as cost is driven in the simplest sense in economics, often driven by demand. Presently, the demand for novel diagnostic and therapeutic protein biomarkers that possess high sensitivity and specificity is placing major impact on the field of proteomics. The focal discovery technology that is being relied on is mass spectrometry (MS), whereas the challenge of biomarker discovery often lies not in the application of MS but in the underlying proteome sampling and bioinformatic processing strategies. Although biomarker discovery research has been historically technology-driven, it is clear from the meager success in generating validated biomarkers that increasing attention must be placed at the pre-analytic stage, such as sample retrieval and preparation. As diseases vary, so do the combinations of sampling and sample analyses necessary to discover novel biomarkers. In this review, we highlight different strategies used toward biomarker discovery and discuss them in terms of their reliance on technology and methodology

Diagnostic Proteomics: Serum Proteomic Patterns for the Detection of Early Stage Cancers

The ability to interrogate thousands of proteins found in complex biological samples using proteomic technologies has brought the hope of discovering novel disease-specific biomarkers. While most proteomic technologies used to discover diagnostic biomarkers are quite sophisticated, proteomic pattern analysis has emerged as a simple, yet potentially revolutionary, method for the early diagnosis of diseases. Utilizing this technology, hundreds of clinical samples can be analyzed per day and several preliminary studies suggest proteomic pattern analysis has the potential to be a novel, highly sensitive diagnostic tool for the early detection of cancer

Fully automated synthesis of (phospho)peptide arrays in microtiter plate wells provides efficient access to protein tyrosine kinase characterization

BACKGROUND: Synthetic peptides have played a useful role in studies of protein kinase substrates and interaction domains. Synthetic peptide arrays and libraries, in particular, have accelerated the process. Several factors have hindered or limited the applicability of various techniques, such as the need for deconvolution of combinatorial libraries, the inability or impracticality of achieving full automation using two-dimensional or pin solid phases, the lack of convenient interfacing with standard analytical platforms, or the difficulty of compartmentalization of a planar surface when contact between assay components needs to be avoided. This paper describes a process for synthesis of peptides and phosphopeptides on microtiter plate wells that overcomes previous limitations and demonstrates utility in determination of the epitope of an autophosphorylation site phospho-motif antibody and utility in substrate utilization assays of the protein tyrosine kinase, p60(c-src). RESULTS: The overall reproducibility of phospho-peptide synthesis and multiplexed EGF receptor (EGFR) autophosphorylation site (pY1173) antibody ELISA (9H2) was within 5.5 to 8.0%. Mass spectrometric analyses of the released (phospho)peptides showed homogeneous peaks of the expected molecular weights. An overlapping peptide array of the complete EGFR cytoplasmic sequence revealed a high redundancy of 9H2 reactive sites. The eight reactive phospopeptides were structurally related and interestingly, the most conserved antibody reactive peptide motif coincided with a subset of other known EGFR autophosphorylation and SH2 binding motifs and an EGFR optimal substrate motif. Finally, peptides based on known substrate specificities of c-src and related enzymes were synthesized in microtiter plate array format and were phosphorylated by c-Src with the predicted specificities. The level of phosphorylation was proportional to c-Src concentration with sensitivities below 0.1 Units of enzyme. CONCLUSIONS: The ability of this method to interface with various robotics and instrumentation is highly flexible since the microtiter plate is an industry standard. It is highly scalable by increasing the surface area within the well or the number of wells and does not require specialized robotics. The microtiter plate array system is well suited to the study of protein kinase substrates, antigens, binding molecules, and inhibitors since these all can be quantitatively studied at a single uniform, reproducible interface

Proteomic Analysis of Ovarian Cancer Proximal Fluids: Validation of Elevated Peroxiredoxin 1 in Patient Peripheral Circulation

Background: Epithelial ovarian cancer (EOC) is the deadliest gynecologic malignancy in the United States. Unfortunately, a validated protein biomarker-screening test to detect early stage disease from peripheral blood has not yet been developed. The present investigation assesses the ability to identify tumor relevant proteins from ovarian cancer proximal fluids, including tissue interstitial fluid (TIF) and corresponding ascites, from patients with papillary serous EOC and translates these findings to targeted blood-based immunoassays. Methodology/Principal Findings: Paired TIF and ascites collected from four papillary serous EOC patients at the time of surgery underwent immunodepletion, resolution by 1D gel electrophoresis and in-gel digestion for analysis by liquid chromatography-tandem mass spectrometry, which resulted in an aggregate identification of 569 and 171 proteins from TIF and ascites, respectively. Of these, peroxiredoxin I (PRDX1) was selected for validation in serum by ELISA and demonstrated to be present and significantly elevated (p = 0.0188) in 20 EOC patients with a mean level of 26.0 ng/mL (±9.27 SEM) as compared to 4.19 ng/mL (±2.58 SEM) from 16 patients with normal/benign ovarian pathology. Conclusions/Significance: We have utilized a workflow for harvesting EOC-relevant proximal biofluids, including TIF and ascites, for proteomic analysis. Among the differentially abundant proteins identified from these proximal fluids, PRDX1 was demonstrated to be present in serum and shown by ELISA to be elevated by nearly 6-fold in papillary serous EOC patients relative to normal/benign patients. Our findings demonstrate the facile ability to discover potential EOC-relevant proteins in proximal fluids and confirm their presence in peripheral blood serum. In addition, our finding of elevated levels of PRDX1 in the serum of EOC patients versus normal/benign patients warrants further evaluation as a tumor specific biomarker for EOC. © 2011 Hoskins et al

Liquid Tissue: Proteomic Profiling of Formalin-Fixed Tissues

Identification and quantitation of candidate biomarker proteins in large numbers of individual tissues is required to validate specific proteins, or panels of proteins, for clinical use as diagnostic, prognostic, toxicological, or therapeutic markers. Mass spectrometry (MS) provides an exciting analytical methodology for this purpose. Liquid Tissue MS protein preparation allows researchers to utilize the vast, already existing, collections offormalin-fixed paraffin-embedded (FFPE) tissues for the procurement of peptides and the analysis across a variety of MS platforms

Preformulation and stability in biological fluids of the retrocyclin RC-101, a potential anti-HIV topical microbicide

<p>Abstract</p> <p>Background</p> <p>RC-101, a cationic peptide retrocyclin analog, has <it>in vitro </it>activity against HIV-1. Peptide drugs are commonly prone to conformational changes, oxidation and hydrolysis when exposed to excipients in a formulation or biological fluids in the body, this can affect product efficacy. We aimed to investigate RC-101 stability under several conditions including the presence of human vaginal fluids (HVF), enabling the efficient design of a safe and effective microbicide product. Stability studies (temperature, pH, and oxidation) were performed by HPLC, Circular Dichroism, and Mass Spectrometry (LC-MS/MS). Additionally, the effect of HVF on formulated RC-101 was evaluated with fluids collected from healthy volunteers, or from subjects with bacterial vaginosis (BV). RC-101 was monitored by LC-MS/MS for up to 72 h.</p> <p>Results</p> <p>RC-101 was stable at pH 3, 4, and 7, at 25 and 37°C. High concentrations of hydrogen peroxide resulted in less than 10% RC-101 reduction over 24 h. RC-101 was detected 48 h after incubation with normal HVF; however, not following incubation with HVF from BV subjects.</p> <p>Conclusions</p> <p>Our results emphasize the importance of preformulation evaluations and highlight the impact of HVF on microbicide product stability and efficacy. RC-101 was stable in normal HVF for at least 48 h, indicating that it is a promising candidate for microbicide product development. However, RC-101 stability appears compromised in individuals with BV, requiring more advanced formulation strategies for stabilization in this environment.</p

An insight into the sialome of the oriental rat flea, Xenopsylla cheopis (Rots)

<p>Abstract</p> <p>Background</p> <p>The salivary glands of hematophagous animals contain a complex cocktail that interferes with the host hemostasis and inflammation pathways, thus increasing feeding success. Fleas represent a relatively recent group of insects that evolved hematophagy independently of other insect orders.</p> <p>Results</p> <p>Analysis of the salivary transcriptome of the flea <it>Xenopsylla cheopis</it>, the vector of human plague, indicates that gene duplication events have led to a large expansion of a family of acidic phosphatases that are probably inactive, and to the expansion of the FS family of peptides that are unique to fleas. Several other unique polypeptides were also uncovered. Additionally, an apyrase-coding transcript of the CD39 family appears as the candidate for the salivary nucleotide hydrolysing activity in <it>X.cheopis</it>, the first time this family of proteins is found in any arthropod salivary transcriptome.</p> <p>Conclusion</p> <p>Analysis of the salivary transcriptome of the flea <it>X. cheopis </it>revealed the unique pathways taken in the evolution of the salivary cocktail of fleas. Gene duplication events appear as an important driving force in the creation of salivary cocktails of blood feeding arthropods, as was observed with ticks and mosquitoes. Only five other flea salivary sequences exist at this time at NCBI, all from the cat flea <it>C. felis</it>. This work accordingly represents the only relatively extensive sialome description of any flea species. Sialotranscriptomes of additional flea genera will reveal the extent that these novel polypeptide families are common throughout the Siphonaptera.</p

Supramolecular organizations in the aerobic respiratory chain of Escherichia coli

The organization of respiratory chain complexes in supercomplexes has been shown in the mitochondria of several eukaryotes and in the cell membranes of some bacteria. These supercomplexes are suggested to be important for oxidative phosphorylation efficiency and to prevent the formation of reactive oxygen species. Here we describe, for the first time, the identification of supramolecular organizations in the aerobic respiratory chain of Escherichia coli, including a trimer of succinate dehydrogenase. Furthermore, two heterooligomerizations have been shown: one resulting from the association of the NADH:quinone oxidoreductases NDH-1 and NDH-2, and another composed by the cytochrome bo3 quinol:oxygen reductase, cytochrome bd quinol:oxygen reductase and formate dehydrogenase (fdo). These results are supported by blue native-electrophoresis, mass spectrometry and kinetic data of wild type and mutant E . coli strains

Novel Approaches to Visualization and Data Mining Reveals Diagnostic Information in the Low Amplitude Region of Serum Mass Spectra from Ovarian Cancer Patients

The ability to identify patterns of diagnostic signatures in proteomic data generated by high throughput mass spectrometry (MS) based serum analysis has recently generated much excitement and interest from the scientific community. These data sets can be very large, with high-resolution MS instrumentation producing 1-2 million data points per sample. Approaches to analyze mass spectral data using unsupervised and supervised data mining operations would greatly benefit from tools that effectively allow for data reduction without losing important diagnostic information. In the past, investigators have proposed approaches where data reduction is performed by a priori peak picking and alignment/warping/smoothing components using rule-based signal-to-noise measurements. Unfortunately, while this type of system has been employed for gene microarray analysis, it is unclear whether it will be effective in the analysis of mass spectral data, which unlike microarray data, is comprised of continuous measurement operations. Moreover, it is unclear where true signal begins and noise ends. Therefore, we have developed an approach to MS data analysis using new types of data visualization and mining operations in which data reduction is accomplished by culling via the intensity of the peaks themselves instead of by location. Applying this new analysis method on a large study set of high resolution mass spectra from healthy and ovarian cancer patients, shows that all of the diagnostic information is contained within the very lowest amplitude regions of the mass spectra. This region can then be selected and studied to identify the exact location and amplitude of the diagnostic biomarkers

The Use of Urine Proteomic and Metabonomic Patterns for the Diagnosis of Interstitial Cystitis and Bacterial Cystitis

The advent of systems biology approaches that have stemmed from the sequencing of the human genome has led to the search for new methods to diagnose diseases. While much effort has been focused on the identification of disease-specific biomarkers, recent efforts are underway toward the use of proteomic and metabonomic patterns to indicate disease. We have developed and contrasted the use of both proteomic and metabonomic patterns in urine for the detection of interstitial cystitis (IC). The methodology relies on advanced bioinformatics to scrutinize information contained within mass spectrometry (MS) and high-resolution proton nuclear magnetic resonance (1H-NMR) spectral patterns to distinguish IC-affected from non-affected individuals as well as those suffering from bacterial cystitis (BC). We have applied a novel pattern recognition tool that employs an unsupervised system (self-organizing-type cluster mapping) as a fitness test for a supervised system (a genetic algorithm). With this approach, a training set comprised of mass spectra and 1H-NMR spectra from urine derived from either unaffected individuals or patients with IC is employed so that the most fit combination of relative, normalized intensity features defined at precise m/z or chemical shift values plotted in n-space can reliably distinguish the cohorts used in training. Using this bioinformatic approach, we were able to discriminate spectral patterns associated with IC-affected, BC-affected, and unaffected patients with a success rate of approximately 84%