Contribution of Protein Fractionation to Depth of Analysis of the Serum and Plasma Proteomes

Faça, Vitor M.; Pitteri, Sharon J.; Newcomb, Lisa F.; Glukhova, Veronika; Phanstiel, Doug; Krasnoselsky, Alexei L.; Zhang, Qing; Struthers, Jason J.; Wang, Hong; Eng, Jimmy K.; Fitzgibbon, Matt; McIntosh, Martin W.; Hanash, Samir M.

doi:10.1021/pr070233q

Cited by 155 publications

(171 citation statements)

References 29 publications

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“…In addition, separations of intact proteins on the basis of their different masses or other properties can be used to identify different protein isoforms. 5,17 Quantitative analysis based on the number of peptides identified per protein is increasingly used. [6][7][8][9][10] An important consideration with spectrum counting is the fact that small proteins tend to have fewer peptides identified per protein compared with large proteins.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, developments in immunoaffinity depletion of highly abundant proteins and in higher dimensional separation strategies have enabled the plasma proteome to be profiled with greater dynamic range of coverage, allowing proteins at the ng/mL levels to be identified confidently. [2][3][4][5] The ability to estimate the abundance of the identified proteins is also an important goal for proteomic studies aimed at discovering disease biomarkers. Several studies have shown that the total number of peptide hits per protein can be used as a semiquantitative approach.…”

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confidence: 99%

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Comprehensive and quantitative proteome profiling of the mouse liver and plasma

2008

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We report a comprehensive and quantitative analysis of the mouse liver and plasma proteomes. The method used is based on extensive fractionation of intact proteins, further separation of proteins based on their abundance and size, and high-accuracy mass spectrometry. This analysis reached a depth in proteomic profiling not reported to date for a mammalian tissue or a biological fluid, with 7099 and 4727 proteins identified with high confidence in the liver and in the corresponding plasma, respectively. This method allowed for the identification in both compartments of low-abundance proteins such as cytokines, chemokines, and receptors and for the detection in plasma of proteins in the pg/mL concentration range. This method also allowed for semiquantitation of all identified proteins. The calculated abundance scores correlated with the abundance of the corresponding transcripts for the large majority of the proteins identified in the liver. Finally, comparison of the liver and plasma datasets demonstrated that a significant number of proteins identified in the liver can be detected in plasma. These included proteins involved in complement and coagulation, in fatty acid, purine and pyruvate metabolism, in gluconeogenesis and glycolysis, in protein ubiquitination, and in insulin, interleukin-4, epidermal growth factor, and platelet-derived growth factor signaling. Conclusion: This in-depth analysis of the mouse liver and corresponding plasma proteomes provides a strong basis for investigations of liver pathobiology and biology that employ mouse models of hepatic diseases in an effort to better understand, diagnose, treat, and prevent human hepatic diseases. (HEPATOLOGY 2008;47: 1043-1051.)

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Section: Discussionmentioning

confidence: 99%

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Comprehensive and quantitative proteome profiling of the mouse liver and plasma

2008

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“…Other predictors are PSA (prostate cancer) or EGFR (colon cancer). In recent years the focus has shifted toward molecular markers in genetics, epigenetics, the analysis of gene-expression patterns (22), and proteomics (23)(24)(25). The molecular cancer diagnostic is looking at changes on genetic and epigenetic levels (26), translocations (SKY), and variation in copy numbers (array CGH).…”

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confidence: 99%

Novel automated three‐dimensional genome scanning based on the nuclear architecture of telomeres

Klewes

Höbsch

Katzir³

et al. 2010

Cytometry Pt A

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Telomeres, the end of chromosomes, are organized in a nonoverlapping fashion and form microterritories in nuclei of normal cells. Previous studies have shown that normal and tumor cell nuclei differ in their 3D telomeric organization. The differences include a change in the spatial organization of the telomeres, in telomere numbers and sizes and in the presence of telomeric aggregates. Previous attempts to identify the above parameters of 3D telomere organization were semi-automated. Here we describe the automation of 3D scanning for telomere signatures in interphase nuclei based on three-dimensional fluorescent in situ hybridization (3D-FISH) and, for the first time, define its sensitivity in tumor cell detection. The data were acquired with a highthroughput scanning/acquisition system that allows to measure cells and acquire 3D images of nuclei at high resolution with 403 or 603 oil and at a speed of 10,000-15,000 cells h 21 , depending on the cell density on the slides. The automated scanning, TeloScan, is suitable for large series of samples and sample sizes. We define the sensitivity of this automation for tumor cell detection. The data output includes 3D telomere positions, numbers of telomeric aggregates, telomere numbers, and telomere signal intensities. We were able to detect one aberrant cell in 1,000 normal cells. In conclusions, we are able to detect tumor cells based on 3D architectural profiles of the genome. This new tool could, in the future, assist in patient diagnosis, in the detection of minimal residual disease, in the analysis of treatment response and in treatment decisions. '

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“…Plasma Experiments-Reference pools of plasma were used in the experiments described here and processed as described previously (32). Briefly, each pool was immunodepleted of the top six most abundant proteins using HU-6 columns (Agilent).…”

Section: Methodsmentioning

confidence: 99%

Identification of Potential Glycan Cancer Markers with Sialic Acid Attached to Sialic Acid and Up-regulated Fucosylated Galactose Structures in Epidermal Growth Factor Receptor Secreted from A431 Cell Line

Taylor

et al. 2013

Molecular & Cellular Proteomics

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We have used powerful HPLC-mass spectrometric approaches to characterize the secreted form of epidermal growth factor receptor (sEGFR). We demonstrated that the amino acid sequence lacked the cytoplasmic domain and was consistent with the primary sequence reported for EGFR purified from a human plasma pool. One of the sEGFR forms, attributed to the alternative RNA splicing, was also confirmed by transcriptional analysis (RNA sequencing). Two unusual types of glycan structures were observed in sEGFR as compared with membrane-bound EGFR from the A431 cell line. The unusual glycan structures were di-sialylated glycans (sialic acid attached to sialic acid) at Asn-151 and N-acetylhexosamine attached to a branched fucosylated galactose with N-acetylglucosamine moieties (HexNAc-(Fuc)Gal-GlcNAc) at Asn-420. These unusual glycans at specific sites were either present at a much lower level or were not observable in membrane-bound EGFR present in the A431 cell lysate. The observation of these di-sialylated glycan structures was consistent with the observed expression of the corresponding ␣-N-acetylneuraminide ␣-2,8-sialyltransferase 2 (ST8SiA2) and ␣-N-acetylneuraminide ␣-2,8-sialyltransferase 4 (ST8SiA4), by quantitative real time RT-PCR. The connectivity present at the branched fucosylated galactose was also confirmed by methylation of the glycans followed by analysis with sequential fragmentation in mass spectrometry. We hypothesize that the presence of such glycan structures could promote secretion via anionic or steric repulsion mechanisms and thus facilitate the observation of these glycan forms in the secreted fractions. We plan to use this model system to facilitate the Cancers are disease-associated with considerable morbidity, such as disease recurrence, anxiety, and side effects of treatment and mortality (1). Early diagnosis often significantly improves survival rates compared with late stage cancer detection, such as for breast, lung, and colon cancers (2-4). Proteins in the blood hold enormous promise for early stage cancer diagnostic tests, but the complexity and dynamic range of blood have confounded the search for cancer biomarkers. Nevertheless, the pressing need for a clinical assay has prompted us to investigate a different approach toward discovering new breast cancer biomarkers circulating in blood (5-7). In addition, the use of a panel of cancer cell lines, representing cancers with different subtypes, could alleviate the difficulty of analyzing the plasma samples directly. Although there is no substitute for the direct study of clinical samples, genetic and molecular aberrations found in cell lines can be translated to similar dysregulations in tumors (8). Cell lines, through the proteins they secrete or shed, should be a complementary model system for the discovery of circulating blood markers. For cancer biomarkers, the change of gene or protein sequence, such as mutation, is often a preclusion for cancers. A similar argument could also be true for the change of protein glycan structures, which re...

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Contribution of Protein Fractionation to Depth of Analysis of the Serum and Plasma Proteomes

Cited by 155 publications

References 29 publications

Comprehensive and quantitative proteome profiling of the mouse liver and plasma

Comprehensive and quantitative proteome profiling of the mouse liver and plasma

Novel automated three‐dimensional genome scanning based on the nuclear architecture of telomeres

Identification of Potential Glycan Cancer Markers with Sialic Acid Attached to Sialic Acid and Up-regulated Fucosylated Galactose Structures in Epidermal Growth Factor Receptor Secreted from A431 Cell Line

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