A list of candidate cancer biomarkers for targeted proteomics

Affibody molecule-mediated depletion of HSA and IgG using different buffer compositions: a 15 min protocol for parallel processing of 1-48 samples

High-abundant plasma proteins pose a challenge in a large number of proteomics-based technologies. Depletion of these high-abundant proteins has proven to be a fruitful strategy to circumvent masking of lower-abundant proteins that could serve as valuable biomarker candidates. However, current strategies often do not meet the throughput requirements of large-scale proteomic studies. In the present paper, a flexible and parallelized method for the depletion of high-abundant proteins is described, allowing the removal of the two most abundant proteins from 48 blood-derived samples in less than 15 min using Affibody molecules as affinity ligands. A sample-processing platform like this should be suitable for a number of proteomics technologies; its flexibility in buffer composition allows for different types of downstream applications.

Fast proteomic protocol for biomarker fingerprinting in cancerous cells

The advance of novel technologies that will enable the detection of large sets of biomarker proteins, to greatly improve the sensitivity and specificity of an assay, represents a major objective in biomedical research. To demonstrate the power of mass spectrometry (MS) detection for large-scale biomarker screening in cancer research, a simple, one-step approach for fast biomarker fingerprinting in complex cellular extracts is described. MCF-7 breast cancer cells were used as a model system. Fast proteomic profiling of whole cellular extracts was achieved on a linear trap quadrupole (LTQ) mass spectrometer by one of the following techniques: (a) data-dependent liquid chromatography (LC)-MS/MS of un-labeled cell extracts, (b) data-dependent LC-MS/MS with pulsed Q dissociation (PQD) detection of iTRAQ labeled samples, and (c) multiple reaction monitoring (MRM)-MS of low abundant proteins that could not be detected with data-dependent MS/MS. The data-dependent LC-MS/MS analysis of MCF-7 cells enabled the identification of 796 proteins (p<0.001) and the simultaneous detection of 156 previously reported putative cancer biomarkers. PQD detection of iTRAQ labeled cells resulted in the detection of 389 proteins and 64 putative biomarkers. MRM-MS analysis enabled the successful monitoring of a panel of low-abundance proteins in one single experiment, highlighting the utility of this technique for targeted analysis in cancer investigations. These results demonstrate that MS-based technologies relying on a one-step separation protocol have the potential to revolutionize biomarker research and screening applications by enabling fast, sensitive and reliable detection of large panels of putative biomarkers. To further stimulate the exploration of proteins that have been previously reported in the literature to be differentially expressed in a variety of cancers, an extensive list of approximately 1100 candidate biomarkers has been compiled and included in the manuscript.

Towards proteome standards: the use of absolute quantitation in high-throughput biomarker discovery

The use of proteomics to profile biological fluids and identify therein biomarkers for cancer and other diseases was initially received with considerable excitement. However, results have fallen short of the expectations. Traditionally, protein biomarkers have been identified by measurement of relative expression changes between case and control samples from which differentially expressed proteins are then considered to represent biomarker candidates. We argue that current individual proteomics-based biomarker discovery studies lack the statistical strength for the identification of high-confidence biomarkers. Instead, multi-group efforts are necessary to facilitate the generation of sufficient sample sizes. This is contingent on the ability to collate and cross-compare data from different studies, which will require the use of a common metric or standards. Though profound, the technical challenges for absolute protein quantification can be overcome. The use of matrix specific, shared standards for absolute quantitation presents an opportunity to facilitate the much needed, but currently impossible, comparisons of different studies. In addition to community-wide approaches to standardize pre-analytical biomarker research studies, it is also important to establish means to integrate experimental data from different studies in order to assess the usefulness of proposed biomarkers with sufficient statistical certainty.

Up-regulated proteins in the fluid bathing the tumour cell microenvironment as potential serological markers for early detection of cancer of the breast

Breast cancer is by far the most common diagnosed form of cancer and the leading cause of cancer death in women today. Clinically useful biomarkers for early detection of breast cancer could lead to a significant reduction in mortality. Here we describe a detailed analysis using gel-based proteomics in combination with mass spectrometry and immunohistochemistry (IHC) of the tumour interstitial fluids (TIF) and normal interstitial fluids (NIF) collected from 69 prospective breast cancer patients. The goal of this study was to identify abundant cancer up-regulated proteins that are externalised by cells in the tumour microenvironment of most if not all these lesions. To this end, we applied a phased biomarker discovery research strategy to the analysis of these samples rather than comparing all samples among each other, with inherent inter and intra-sample variability problems. To this end, we chose to use samples derived from a single tumour/benign tissue pair (patient 46, triple negative tumour), for which we had well-matched samples in terms of epithelial cell numbers, to generate the initial dataset. In this first phase we found 110 proteins that were up-regulated by a factor of 2 or more in the TIF, some of which were confirmed by IHC. In the second phase, we carried out a systematic computer assisted analysis of the 2D gels of the remaining 68 TIF samples in order to identify TIF 46 up-regulated proteins that were deregulated in 90% or more of all the available TIFs, thus representing common breast cancer markers. This second phase singled out a set of 26 breast cancer markers, most of which were also identified by a complementary analysis using LC-MS/MS. The expression of calreticulin, cellular retinoic acid-binding protein II, chloride intracellular channel protein 1, EF-1-beta, galectin 1, peroxiredoxin-2, platelet-derived endothelial cell growth factor, protein disulfide isomerase and ubiquitin carboxyl-terminal hydrolase 5 were further validated using a tissue microarray containing 70 malignant breast carcinomas of various grades of atypia. A significant number of these proteins have already been detected in the blood/plasma/secretome by others. The next steps, which include biomarker prioritization based on the hierarchal evaluation of these markers, antibody and antigen development, assay development, analytical validation, and preliminary testing in the blood of healthy and breast cancer patients, are discussed.

UniMaP: finding unique mass and peptide signatures in the human proteome

The uniqueness of a measured molecular mass or peptide sequence plays a very important role in the fields of protein identification and peptide/protein-biomarker investigation. We present a publicly available web application that offers information concerning the uniqueness of one or more molecular masses and one or more peptide sequences in the human proteome. When a sequence is found to be unique in humans, the application is able to search across all species querying whether this sequence is unique, not only in humans but also in other species found in the Swiss-Prot Database. The application is also able to search for unique protein fragments derived computationally from enzymatic digestion driven by certain enzymes. Furthermore, the application can list all the unique masses and peptides of a given protein. Through this application, researchers are able to find unique tags, either on a molecular mass level or on a sequence level. These unique tags are remarkably important in research related to protein identification or biomarker discovery and measurements.

AVAILABILITY

UniMaP web-application is available at http://bioserver-1.bioacademy.gr/Bioserver/UniMaP/

Multiple reaction monitoring-based, multiplexed, absolute quantitation of 45 proteins in human plasma

Mass spectrometry-based multiple reaction monitoring (MRM) quantitation of proteins can dramatically impact the discovery and quantitation of biomarkers via rapid, targeted, multiplexed protein expression profiling of clinical samples. A mixture of 45 peptide standards, easily adaptable to common plasma proteomics work flows, was created to permit absolute quantitation of 45 endogenous proteins in human plasma trypsin digests. All experiments were performed on simple tryptic digests of human EDTA-plasma without prior affinity depletion or enrichment. Stable isotope-labeled standard peptides were added immediately following tryptic digestion because addition of stable isotope-labeled standard peptides prior to trypsin digestion was found to generate elevated and unpredictable results. Proteotypic tryptic peptides containing isotopically coded amino acids ([(13)C(6)]Arg or [(13)C(6)]Lys) were synthesized for all 45 proteins. Peptide purity was assessed by capillary zone electrophoresis, and the peptide quantity was determined by amino acid analysis. For maximum sensitivity and specificity, instrumental parameters were empirically determined to generate the most abundant precursor ions and y ion fragments. Concentrations of individual peptide standards in the mixture were optimized to approximate endogenous concentrations of analytes and to ensure the maximum linear dynamic range of the MRM assays. Excellent linear responses (r > 0.99) were obtained for 43 of the 45 proteins with attomole level limits of quantitation (<20% coefficient of variation) for 27 of the 45 proteins. Analytical precision for 44 of the 45 assays varied by <10%. LC-MRM/MS analyses performed on 3 different days on different batches of plasma trypsin digests resulted in coefficients of variation of <20% for 42 of the 45 assays. Concentrations for 39 of the 45 proteins are within a factor of 2 of reported literature values. This mixture of internal standards has many uses and can be applied to the characterization of trypsin digestion kinetics and plasma protein expression profiling because 31 of the 45 proteins are putative biomarkers of cardiovascular disease.