Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.
"Consequently, the current antibody arrays are most suitable for targeted analysis of disease or condition-specific biomarkers [7, 12–14] rather than examining changes in the whole proteome or discovering novel biomarkers. Advances in the field of mass spectrometry (MS) have enabled an alternative way of investigating cellular and plasma protein biomarkers   . Current MS machinery and bioinformatics software are rapidly approaching the sensitivity and dynamic range limits of immunodiagnostic tests  . "
[Show abstract][Hide abstract] ABSTRACT: Plasma proteome is widely used in studying changes occurring in human body during disease or other disturbances. Immunological methods are commonly used in such studies. In recent years, mass spectrometry has gained popularity in high-throughput analysis of plasma proteins. In this study, we tested whether mass spectrometry and iTRAQ-based protein quantification might be used in proteomic analysis of human plasma during liver transplantation surgery to characterize changes in protein abundances occurring during early graft reperfusion. We sampled blood from systemic circulation as well as blood entering and exiting the liver. After immunodepletion of six high-abundant plasma proteins, trypsin digestion, iTRAQ labeling, and cation-exchange fractionation, the peptides were analyzed by reverse phase nano-LC-MS/MS. In total, 72 proteins were identified of which 31 could be quantified in all patient specimens collected. Of these 31 proteins, ten, mostly medium-to-high abundance plasma proteins with a concentration range of 50-2000 mg/L, displayed relative abundance change of more than 10%. The changes in protein abundance observed in this study allow further research on the role of several proteins in ischemia-reperfusion injury during liver transplantation and possibly in other surgery.
BioMed Research International 12/2011; 2011(11):248613. DOI:10.1155/2011/248613 · 2.71 Impact Factor
"Blood-based protein biomarkers indicative of the presence, progression, and phenotype of a tumor are of significant clinical interest for diagnostics and prognostics , , , . One common approach to the discovery of such protein biomarkers is to compare cancer tissues with control materials  and select candidates from a list of proteins that are more abundantly expressed in the cancer tissues; any selected candidate must be then subsequently verified in serum or plasma. As there may be dozens or hundreds of differentially abundant proteins identified in such experiments  researchers must prioritize potential candidates. "
[Show abstract][Hide abstract] ABSTRACT: Tumor-derived, circulating proteins are potentially useful as biomarkers for detection of cancer, for monitoring of disease progression, regression and recurrence, and for assessment of therapeutic response. Here we interrogated how a protein's stability, cellular localization, and abundance affect its observability in blood by mass-spectrometry-based proteomics techniques. We performed proteomic profiling on tumors and plasma from two different xenograft mouse models. A statistical analysis of this data revealed protein properties indicative of the detection level in plasma. Though 20% of the proteins identified in plasma were tumor-derived, only 5% of the proteins observed in the tumor tissue were found in plasma. Both intracellular and extracellular tumor proteins were observed in plasma; however, after normalizing for tumor abundance, extracellular proteins were seven times more likely to be detected. Although proteins that were more abundant in the tumor were also more likely to be observed in plasma, the relationship was nonlinear: Doubling the spectral count increased detection rate by only 50%. Many secreted proteins, even those with relatively low spectral count, were observed in plasma, but few low abundance intracellular proteins were observed. Proteins predicted to be stable by dipeptide composition were significantly more likely to be identified in plasma than less stable proteins. The number of tryptic peptides in a protein was not significantly related to the chance of a protein being observed in plasma. Quantitative comparison of large versus small tumors revealed that the abundance of proteins in plasma as measured by spectral count was associated with the tumor size, but the relationship was not one-to-one; a 3-fold decrease in tumor size resulted in a 16-fold decrease in protein abundance in plasma. This study provides quantitative support for a tumor-derived marker prioritization strategy that favors secreted and stable proteins over all but the most abundant intracellular proteins.
PLoS ONE 07/2011; 6(7):e23090. DOI:10.1371/journal.pone.0023090 · 3.23 Impact Factor
"However, the application of immunoaffinity‐based techniques is severely hindered by the limited availability of antibodies and kits as well as the high cost and lengthy procedure required for the production of specific antibodies and the development of assay kits.  Selected reaction monitoring (SRM) and its extension, multiple reaction monitoring (MRM), have been widely used in the quantification of small molecules.  Recently, these techniques have been adopted for protein/peptide analysis. "
[Show abstract][Hide abstract] ABSTRACT: The validation of putative biomarker candidates has become the major bottle-neck in protein biomarker development. Conventional immunoaffinity methods are limited by the availability of antibodies and kits. Here we demonstrate the feasibility of using selected reaction monitoring (SRM) without isotope labeling to achieve fast and reproducible quantification of serum proteins. The SRM/MRM assays for three standard serum proteins, including ceruloplasmin (CP), serum aymloid A (SAA) and sex hormone binding globulin (SHBG), have good linear ranges, generally 10(3) to 10(4) . There are almost perfect correlations between SRM intensities and the loaded peptide amounts (R(2) is usually ~0.99). Our data suggest that SRM/MRM is able to quantify proteins within the range of 0.2-2 fmol, which is comparable to the commercial ELISA/LUMINEX kits for these proteins. Excellent correlations between SRM/MRM and ELISA/LUMINEX assays were observed for SAA and SHBG (R(2)=0.928 and 0.851, respectively). However, the correlation between SRM/MRM and ELISA for CP is less desirable (R(2)=0.565). The reproducibility for SRM/MRM assays is generally very good but may depend on the proteins/peptides being analyzed (R(2)=0.931 and 0.882 for SAA and SHBG, and 0.723 for CP). The SRM/MRM assay without isotope labeling is a rapid and useful method for protein biomarker validation in a modest number of samples and is especially useful when other assays such as ELISA or LUMINEX are not available.
Rapid Communications in Mass Spectrometry 06/2011; 25(11):1583-8. DOI:10.1002/rcm.5023 · 2.25 Impact Factor
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