Shotgun proteomics coupled to nanoparticle-based biomarker enrichment reveals a novel panel of extracellular matrix proteins as candidate serum protein biomarkers for early-stage breast cancer detection.

BACKGROUND: The lack of specificity and high degree of false positive and false negative rates when using mammographic screening for detecting early-stage breast cancer is a critical issue. Blood-based molecular assays that could be used in adjunct with mammography for increased specificity and sensitivity could have profound clinical impact. Our objective was to discover and independently verify a panel of candidate blood-based biomarkers that could identify the earliest stages of breast cancer and complement current mammographic screening approaches. METHODS: We used affinity hydrogel nanoparticles coupled with LC-MS/MS analysis to enrich and analyze low-abundance proteins in serum samples from 20 patients with invasive ductal carcinoma (IDC) breast cancer and 20 female control individuals with positive mammograms and benign pathology at biopsy. We compared these results to those obtained from five cohorts of individuals diagnosed with cancer in organs other than breast (ovarian, lung, prostate, and colon cancer, as well as melanoma) to establish IDC-specific protein signatures. Twenty-four IDC candidate biomarkers were then verified by multiple reaction monitoring (LC-MRM) in an independent validation cohort of 60 serum samples specifically including earliest-stage breast cancer and benign controls (19 early-stage (T1a) IDC and 41 controls). RESULTS: In our discovery set, 56 proteins were increased in the serum samples from IDC patients, and 32 of these proteins were specific to IDC. Verification of a subset of these proteins in an independent cohort of early-stage T1a breast cancer yielded a panel of 4 proteins, ITGA2B (integrin subunit alpha IIb), FLNA (Filamin A), RAP1A (Ras-associated protein-1A), and TLN-1 (Talin-1), which classified breast cancer patients with 100% sensitivity and 85% specificity (AUC of 0.93). CONCLUSIONS: Using a nanoparticle-based protein enrichment technology, we identified and verified a highly specific and sensitive protein signature indicative of early-stage breast cancer with no false positives when assessing benign and inflammatory controls. These markers have been previously reported in cell-ECM interaction and tumor microenvironment biology. Further studies with larger cohorts are needed to evaluate whether this biomarker panel improves the positive predictive value of mammography for breast cancer detection.

Immunoprecipitation and mass spectrometry defines an extensive RBM45 protein-protein interaction network.

The pathological accumulation of RNA-binding proteins (RBPs) within inclusion bodies is a hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). RBP aggregation results in both toxic gain and loss of normal function. Determining the protein binding partners and normal functions of disease-associated RBPs is necessary to fully understand molecular mechanisms of RBPs in disease. Herein, we characterized the protein-protein interactions (PPIs) of RBM45, a RBP that localizes to inclusions in ALS/FTLD. Using immunoprecipitation coupled to mass spectrometry (IP-MS), we identified 132 proteins that specifically interact with RBM45 within HEK293 cells. Select PPIs were validated by immunoblot and immunocytochemistry, demonstrating that RBM45 associates with a number of other RBPs primarily via RNA-dependent interactions in the nucleus. Analysis of the biological processes and pathways associated with RBM45-interacting proteins indicates enrichment for nuclear RNA processing/splicing via association with hnRNP proteins and cytoplasmic RNA translation via eiF2 and eiF4 pathways. Moreover, several other ALS-linked RBPs, including TDP-43, FUS, Matrin-3, and hnRNP-A1, interact with RBM45, consistent with prior observations of these proteins within intracellular inclusions in ALS/FTLD. Taken together, our results define a PPI network for RBM45, suggest novel functions for this protein, and provide new insights into the contributions of RBM45 to neurodegeneration in ALS/FTLD. This article is part of a Special Issue entitled SI:RNA Metabolism in Disease.

In Vitro Transcription/Translation System: A Versatile Tool in the Search for Missing Proteins.

Approximately 18% of all human genes purported to encode proteins have not been directly evidenced at the protein level, according to the validation criteria established by neXtProt, and are considered to be "missing" proteins. One of the goals of the Chromosome-Centric Human Proteome Project (C-HPP) is to identify as many of these missing proteins as possible in human samples using mass spectrometry-based methods. To further this goal, a consortium of C-HPP teams (chromosomes 5, 10, 16, and 19) has joined forces to devise new strategies to identify missing proteins by use of a cell-free in vitro transcription/translation system (IVTT). The proposed strategy employs LC-MS/MS data-dependent acquisition (DDA) and targeted selective reaction monitoring (SRM) methods to scrutinize low-complexity samples derived from IVTT. The optimized assays are then applied to identify missing proteins in human cells and tissues. We describe the approach and show proof-of-concept results for development of LC-SRM assays for identification of 18 missing proteins. We believe that the IVTT system, when coupled with downstream mass spectrometric identification, can be applied to identify proteins that have eluded more traditional methods of detection.

Quantitative Proteomic Approach for MicroRNA Target Prediction Based on 18O/16O Labeling.

MOTIVATION: Among many large-scale proteomic quantification methods, 18O/16O labeling requires neither specific amino acid in peptides nor label incorporation through several cell cycles, as in metabolic labeling; it does not cause significant elution time shifts between heavy- and light-labeled peptides, and its dynamic range of quantification is larger than that of tandem mass spectrometry-based quantification methods. These properties offer 18O/16O labeling the maximum flexibility in application. However, 18O/16O labeling introduces large quantification variations due to varying labeling efficiency. There lacks a processing pipeline that warrants the reliable identification of differentially expressed proteins (DEPs). This motivates us to develop a quantitative proteomic approach based on 18O/16O labeling and apply it on Kaposi sarcoma-associated herpesvirus (KSHV) microRNA (miR) target prediction. KSHV is a human pathogenic γ-herpesvirus strongly associated with the development of B-cell proliferative disorders, including primary effusion lymphoma. Recent studies suggest that miRs have evolved a highly complex network of interactions with the cellular and viral transcriptomes, and relatively few KSHV miR targets have been characterized at the functional level. While the new miR target prediction method, photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP), allows the identification of thousands of miR targets, the link between miRs and their targets still cannot be determined. We propose to apply the developed proteomic approach to establish such links. METHOD: We integrate several 18O/16O data processing algorithms that we published recently and identify the messenger RNAs of downregulated proteins as potential targets in KSHV miR-transfected human embryonic kidney 293T cells. Various statistical tests are employed for picking DEPs, and we select the best test by examining the enrichment of PAR-CLIP-reported targets with seed match to the miRs of interest among top ranked DEPs returned by statistical tests. Subsequently, the list of DEPs picked by the selected statistical test is filtered with the criteria that they must have downregulated gene expressions, must have reported as targets by an miR target prediction algorithm SVMcrio, and must have reported as targets by PAR-CLIP. RESULT: We test the developed approach in the problem of finding targets of KSHV miR-K1. The RNAs of three DEPs are identified as miR-K1 targets, among which RAB23 and HNRNPU are novel. Results from both Western blotting and Luciferase reporter assays confirm the novel targets. These results show that the developed quantitative approach based on 18O/16O labeling can be combined with genomic, PAR-CLIP, and target prediction algorithms for the confident identification of KSHV miR targets. The developed approach could also be applied in other applications.

Accurate LC peak boundary detection for ¹6O/¹8O labeled LC-MS data.

In liquid chromatography-mass spectrometry (LC-MS), parts of LC peaks are often corrupted by their co-eluting peptides, which results in increased quantification variance. In this paper, we propose to apply accurate LC peak boundary detection to remove the corrupted part of LC peaks. Accurate LC peak boundary detection is achieved by checking the consistency of intensity patterns within peptide elution time ranges. In addition, we remove peptides with erroneous mass assignment through model fitness check, which compares observed intensity patterns to theoretically constructed ones. The proposed algorithm can significantly improve the accuracy and precision of peptide ratio measurements.

Isolation and characterization of muscle fatigue substance with anti-tumor activities.

Research during the 1950's indicated that exercise played a role in the reduction of tumor growth. In the 1960's our studies confirmed that tumor-bearing rats, exercised to fatigue, demonstrated tumor inhibition. Our further studies isolated an extract (Fatigue Substance, or F-Substance) from rectus femoris muscles of rats which had been electrically stimulated to fatigue. This extract significantly inhibited growth of transplanted rat tumors. Research continued until 1978 when it became apparent the methodology at that time was not able to further identify the substance's active components. Using current technology, we now report on the further isolation and characterization of F-Substance. In cell proliferation assays, extracts from electrically stimulated rat rectus femoris muscles had more significant inhibitory effect on the breast cancer cell line MCF-7 than those isolated from unstimulated muscles. To identify the molecule(s) responsible for the antitumor activity, a rat cytokine antibody array was used to profile the cytokines in the substances. Among the 29 different cytokines contained on the array, 3 showed greater than 3-fold difference between the substances isolated from the stimulated and unstimulated muscles. LIX (also known as CXCL5) is 6-fold higher in the substances isolated from stimulated muscles than those from the unstimulated muscles. TIMP-1 is 4.6 fold higher and sICAM is 3.6 fold higher in the substances from the stimulated muscles. Our results indicated that cytokines released from contracting muscles might be responsible for the antitumor effect of F-Substance.

Differential effects of AKT1(p.E17K) expression on human mammary luminal epithelial and myoepithelial cells.

Recently, we identified a somatic mutation in AKT1, which results in a glutamic acid to lysine substitution (p.Glu17Lys or E17K). E17K mutations appear almost exclusively in breast cancers of luminal origin. Cellular models involving cell lines such as human mammary epithelial and MCF10 are model systems that upon transformation lead to rare forms of human breast cancer. Hence, we studied the effects of E17K using a clinically pertinent luminal cell line model while providing evidence to explain why E17K mutations do not occur in the mammary myoepithelium. Thus the purpose of our study was to perform a functional and differential proteomics study to assess the role of AKT1(E17K) in the development of breast cancer. We used a set of genetically matched nontumorigenic and tumorigenic mammary luminal and myoepithelial cells. We demonstrated that in myoepithelial cells, expression of E17K inhibited growth, migration, and protein synthesis compared with wild-type AKT1. In luminal cells, E17K enhanced cell survival and migration, possibly offering a selective advantage in this type of cell. However, antineoplastic effects of E17K in luminal cells, such as inhibition of growth and protein synthesis, may ultimately be associated with favorable prognosis. Our study illustrates the importance of cellular context in determining phenotypic effects of putative oncogenic mutations.

Targeted quantitative analysis of superoxide dismutase 1 in cisplatin-sensitive and cisplatin-resistant human ovarian cancer cells.

Protein quantification in a complex protein mixture presents a daunting task in biochemical analysis. Antibody-based immunoassays are traditional methods for protein quantification. However, there are issues associated with accuracy and specificity in these assays, especially when the changes are small (e.g., <2-fold). With recent developments in mass spectrometry, monitoring a selected peptide, thus protein, in a complex biological sample has become possible. In this study, we demonstrate a simple mass spectrometry-based method for selective measurement of a moderately low abundant protein, superoxide dismutase 1 (SOD1), in cisplatin-sensitive and cisplatin-resistant human ovarian cancer cells. Selected-reaction-monitoring (SRM) technology was employed to specifically analyze the target peptides in a pair of human ovarian cancer cell lines: 2008/2008-C13*5.25 (cisplatin-sensitive/cisplatin-resistant, respectively). The observed 1.47-fold higher expression in the resistant cell line is consistent with findings by other approaches. This robust liquid chromatography/mass spectrometry (LC/MS) method provides a powerful tool for targeted proteomic verification and/or validation studies.

Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry.

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35-60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies.

Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomics analyses.

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.

Interlaboratory study characterizing a yeast performance standard for benchmarking LC-MS platform performance.

Optimal performance of LC-MS/MS platforms is critical to generating high quality proteomics data. Although individual laboratories have developed quality control samples, there is no widely available performance standard of biological complexity (and associated reference data sets) for benchmarking of platform performance for analysis of complex biological proteomes across different laboratories in the community. Individual preparations of the yeast Saccharomyces cerevisiae proteome have been used extensively by laboratories in the proteomics community to characterize LC-MS platform performance. The yeast proteome is uniquely attractive as a performance standard because it is the most extensively characterized complex biological proteome and the only one associated with several large scale studies estimating the abundance of all detectable proteins. In this study, we describe a standard operating protocol for large scale production of the yeast performance standard and offer aliquots to the community through the National Institute of Standards and Technology where the yeast proteome is under development as a certified reference material to meet the long term needs of the community. Using a series of metrics that characterize LC-MS performance, we provide a reference data set demonstrating typical performance of commonly used ion trap instrument platforms in expert laboratories; the results provide a basis for laboratories to benchmark their own performance, to improve upon current methods, and to evaluate new technologies. Additionally, we demonstrate how the yeast reference, spiked with human proteins, can be used to benchmark the power of proteomics platforms for detection of differentially expressed proteins at different levels of concentration in a complex matrix, thereby providing a metric to evaluate and minimize pre-analytical and analytical variation in comparative proteomics experiments.

Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma.

Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low mug/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma.

LC/MS-based quantitative proteomic analysis of paraffin-embedded archival melanomas reveals potential proteomic biomarkers associated with metastasis.

BACKGROUND: Melanoma metastasis status is highly associated with the overall survival of patients; yet, little is known about proteomic changes during melanoma tumor progression. To better understand the changes in protein expression involved in melanoma progression and metastasis, and to identify potential biomarkers, we conducted a global quantitative proteomic analysis on archival metastatic and primary melanomas. METHODOLOGY AND FINDINGS: A total of 16 metastatic and 8 primary cutaneous melanomas were assessed. Proteins were extracted from laser captured microdissected formalin fixed paraffin-embedded archival tissues by liquefying tissue cells. These preparations were analyzed by a LC/MS-based label-free protein quantification method. More than 1500 proteins were identified in the tissue lysates with a peptide ID confidence level of >75%. This approach identified 120 significant changes in protein levels. These proteins were identified from multiple peptides with high confidence identification and were expressed at significantly different levels in metastases as compared with primary melanomas (q-Value<0.05). CONCLUSIONS AND SIGNIFICANCE: The differentially expressed proteins were classified by biological process or mapped into biological system networks, and several proteins were implicated by these analyses as cancer- or metastasis-related. These proteins represent potential biomarkers for tumor progression. The study successfully identified proteins that are differentially expressed in formalin fixed paraffin-embedded specimens of metastatic and primary melanoma.

Label-free mass spectrometry-based protein quantification technologies in proteomic analysis.

Major technological advances have made proteomics an extremely active field for biomarker discovery and validation in recent years. These improvements have lead to an increased emphasis on larger scale, faster and more efficient methods for protein biomarker discoveries in human tissues, cells and biofluids. However, most current proteomic methodologies for biomarker discovery and validation are not highly automated and generally labour intensive and expensive. Improved automation as well as software programs capable of handling a large amount of data are essential in order to reduce the cost of discovery and increase the throughput. In this review, we will discuss and describe the label-free mass spectrometry-based protein quantification technologies and a case study utilizing one of these methods for biomarker discovery.

A multiple reaction monitoring method for absolute quantification of the human liver alcohol dehydrogenase ADH1C1 isoenzyme.

Although significant progress has been made in protein quantification using mass spectrometry during recent years, absolute protein quantification in complex biological systems remains a challenging task in proteomics. The use of stable isotope-labeled standard peptide is the most commonly used strategy for absolute quantification, but it might not be suitable in all instances. Here we report an alternative strategy that employs a stable isotope-labeled intact protein as an internal standard to absolutely quantify the alcohol dehydrogenase (ADH) expression level in a human liver sample. In combination with a new targeted proteomics approach employing the method of multiple reaction monitoring (MRM), we precisely and quantitatively measured the absolute protein expression level of an ADH isoenzyme, ADH1C1, in human liver. Isotope-labeled protein standards are predicted to be particularly useful for measurement of highly homologous isoenzymes such as ADHs where multiple signature peptides can be examined by MRM in a single experiment.

Microdeposition device interfacing capillary electrochromatography and microcolumn liquid chromatography with matrix-assisted laser desorption/ionization mass spectrometry.

A sample deposition device has been constructed and optimized for interfacing CEC and capillary LC columns to MALDI mass spectrometry. For CEC analysis, the device is composed of an inlet buffer reservoir and an outlet buffer reservoir connected to a matrix reservoir through a connection sleeve. The matrix reservoir is connected to a deposition capillary via another connection sleeve. CEC eluent is transported to the matrix reservoir via a capillary that is connected to the deposition capillary by the connection sleeve inside the matrix reservoir. This connection sleeve also acts as a mixing chamber, allowing the CEC eluent to be mixed with matrix prior to deposition. Complex glycan mixtures can be separated by CEC using hydrophilic-phase monolithic columns, with capillary eluent being deposited on a standard MALDI plate along with a suitable matrix solution. Thousands of discrete, highly homogeneous dots can be generated for a subsequent mass spectrometric analysis. With minor modifications, this device is also applicable to capillary LC of peptides using gradient elution. In this configuration, the outlet of the LC column is connected to a deposition capillary inside a matrix reservoir through a connection sleeve that allows mixing of the LC effluent with an appropriate matrix. The device has been evaluated with the tryptic digests of proteins.

Surfactant-mediated capillary electrochromatography with octadecyl-silica- packed capillary columns for the separation of nonpolar compounds. Case of pyrethroid insecticides.

Capillary electrochromatography (CEC) with octadecyl-silica-packed capillary columns was evaluated in the separation of nonpolar compounds, e.g., pyrethroid insecticides, using surfactant-rich mobile phases. This novel concept is referred to as surfactant-mediated capillary electrochromatography (SM-CEC), and is based on including a charged surfactant, namely sodium di-2-ethylhexyl sulfosuccinate (DOSS), in the mobile phase. Under these conditions, DOSS plays the role of a slowly moving pseudostationary phase so that solutes are partitioned between a mobile phase, a fixed stationary phase and a slowly moving pseudostationary phase. The SM-CEC system was investigated with pyrethroid insecticides over a wide range of DOSS and acetonitrile concentrations in the mobile phase. Pyrethroid insecticides, which are very hydrophobic solutes consisting of geometric isomers and diastereomers, were better resolved in SM-CEC than in straight CEC.

On-column trace enrichment by sequential frontal and elution electrochromatography II. Enhancement of sensitivity by segmented capillaries with z-cell configuration--application to the detection of dilute samples of moderately polar and nonpolar pesticides.

An on-column trace enrichment method for capillary electrochromatography of dilute samples is described. It involves the sequential use of frontal and elution electrochromatography on a segmented capillary column comprising of two contiguous segments each packed with a different sorbent. While the entering segment is for preconcentration by frontal electrochromatography the second segment is much longer and is meant for separation of the enriched analytes in the subsequent elution electrochromatography step. The preconcentration segment is usually packed with a sorbent that affords the highest affinity towards the solutes of interest while the separation segment is packed with a stationary phase that exhibits the highest selectivity and separation efficiency for the analytes. The detection is performed in the UV using a z-cell configuration for achieving an increased path length for detection. The effectiveness of this on-column trace enrichment is demonstrated on dilute samples of moderately polar solutes (e.g., carbamate insecticides) and nonpolar solutes (e.g., pyrethroid insecticides). Under optimal frontal and elution electrochromatography conditions. 817- and 1100-fold sensitivity increase are achieved for permethrin (a pyrethroid insecticide) and methiocarb (a carbamate insecticide), respectively, with a UV detector. The method is demonstrated with real water samples (e.g., tap and lake water samples) spiked with carbamate and pyrethroid insecticides. The limits of detection for the pesticides achieved in tap and lake waters reached 10(-8) to 10(-9) M.