Unleashing the Power of Proteomics to Develop Blood-Based Cancer Markers

BACKGROUND: There is an urgent need for blood-based molecular tests to assist in the detection and diagnosis of cancers at an early stage, when curative interventions are still possible, and to predict and monitor response to treatment and disease recurrence. The rich content of proteins in blood that are impacted by tumor devel-opment and host factors provides an ideal opportunity to develop noninvasive diagnostics for cancer. CONTENT: Mass spectrometry instrumentation has ad-vanced sufficiently to allow the discovery of protein alterations directly in plasma across no less than 7 or-ders of magnitude of protein abundance. Moreover, the use of proteomics to harness the immune response in the form of seropositivity to tumor antigens has the potential to complement circulating protein bio

Towards an integrated proteomic and glycomic approach to finding cancer biomarkers

Advances in mass spectrometry have had a great impact on the field of proteomics. A major challenge of proteomic analysis has been the elucidation of glycan modifications of proteins in complex proteomes. Glycosylation is the most structurally elaborate and diverse type of protein post-translational modification and, because of this, proteomics and glycomics have largely developed independently. However, given that such a large proportion of proteins contain glycan modifications, and that these may be important for their function or may produce biologically relevant protein variation, a convergence of the fields of glycomics and proteomics would be highly desirable. Here we review the current status of glycoproteomic efforts, focusing on the identification of glycoproteins as cancer biomarkers

Disease proteomics

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62680/1/nature01514.pd

Biomarkers for Diagnosis and Prognosis of Sinusoidal Obstruction Syndrome after Hematopoietic Cell Transplantation.

Reliable, non-invasive methods for diagnosing and prognosing sinusoidal obstruction syndrome (SOS) early after hematopoietic cell transplantation (HCT) are needed. We used a quantitative mass spectrometry-based proteomics approach to identify candidate biomarkers of SOS by comparing plasma pooled from 20 patients with and 20 patients without SOS. Of 494 proteins quantified, we selected six proteins [L-Ficolin, vascular-cell-adhesion-molecule-1 (VCAM1), tissue-inhibitor of metalloproteinase-1, von Willebrand factor, intercellular-adhesion-molecule-1, and CD97] based on a differential heavy/light isotope ratio of at least 2 fold, information from the literature, and immunoassay availability. Next, we evaluated the diagnostic potential of these six proteins and five selected from the literature [suppression of tumorigenicity-2 (ST2), angiopoietin-2 (ANG2), hyaluronic acid (HA), thrombomodulin, and plasminogen activator inhibitor-1] in samples from 80 patients. The results demonstrate that together ST2, ANG2

Impact of Protein Stability, Cellular Localization, and Abundance on Proteomic Detection of Tumor-Derived Proteins in Plasma

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

High-throughput genomic technology in research and clinical management of breast cancer. Plasma-based proteomics in early detection and therapy

Protein-based breast cancer biomarkers are a promising resource for breast cancer detection at the earliest and most treatable stages of the disease. Plasma is well suited to proteomic-based methods of biomarker discovery because it is easily obtained, is routinely used in the diagnosis of many diseases, and has a rich proteome. However, due to the vast dynamic range in protein concentration and the often uncertain tissue and cellular origin of plasma proteins, proteomic analysis of plasma requires special consideration compared with tissue and cultured cells. This review briefly touches on the search for plasma-based protein biomarkers for the early detection and treatment of breast cancer

Proteomic Analysis of Ovarian Cancer Cells Reveals Dynamic Processes of Protein Secretion and Shedding of Extra-Cellular Domains

Background: Elucidation of the repertoire of secreted and cell surface proteins of tumor cells is relevant to molecular diagnostics, tumor imaging and targeted therapies. We have characterized the cell surface proteome and the proteins released into the extra-cellular milieu of three ovarian cancer cell lines, CaOV3, OVCAR3 and ES2 and of ovarian tumor cells enriched from ascites fluid. Methodology and Findings: To differentiate proteins released into the media from protein constituents of media utilized for culture, cells were grown in the presence of [ 13 C]-labeled lysine. A biotinylation-based approach was used to capture cell surface associated proteins. Our general experimental strategy consisted of fractionation of proteins from individual compartments followed by proteolytic digestion and LC-MS/MS analysis. In total, some 6,400 proteins were identified with high confidence across all specimens and fractions. Conclusions and Significance: Protein profiles of the cell lines had substantial similarity to the profiles of human ovarian cancer cells from ascites fluid and included protein markers known to be associated with ovarian cancer. Proteomic analysis indicated extensive shedding from extra-cellular domains of proteins expressed on the cell surface, and remarkably high secretion rates for some proteins (nanograms per million cells per hour). Cell surface and secreted proteins identified by indept

Detection of human somatic cell structural gene mutations by two-dimensional electrophoresis

The feasibility of detecting human somatic structural gene mutations by two dimensional electrophoresis has been investigated. A lymphoblastoid cell line was grown as a mass culture in the presence of ethylnitrosourea, after which cells were regrown as single cell clones. A total of 257 polypeptide spots were analyzed in gels derived from 186 clones. Four structural mutations were detected by visual analysis of the gels. Computer analysis of gels corresponding to the mutant clones was also undertaken. At a spot size threshold of 200 spots to be matched using a computer algorithm, all four mutant polypeptides were detected. These results indicate the usefulness of the two-dimensional approach for mutagenesis studies at the protein level.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/38517/1/340020103_ftp.pd