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• W1976231341 abstract "See article on page 1858.The Human Genome Project has revealed that about 22,000–25,000 proteins are encoded in our genome, while about 10,000 proteins are likely to be expressed in any one kind of cell, indicating that only a part of genes in the genome are expressed in a strictly regulated manner.1International Human Genome Sequencing Consortium. Finishing the euchromatic sequence of the human genome. Nature 2004;431931–43145.Google Scholar Therefore, besides genome research, comprehensive analysis of proteins sourced from cells, tissues, and serum, especially concerning changes in their expression level and posttranscriptional modifications according to health and disease, particularly in cancer, has been increasing during the past decade.2de Hoog C.L. Mann M. Proteomics.Annu Rev Genomics Hum Genet. 2004; 5: 267-293Crossref PubMed Scopus (193) Google Scholar Great progress in this field has been supported by the advancement of protein chemistry using high performance mass spectrometry, as represented by the Nobel Prize of 2002. Clinical science has used the obtained database for the development of disease diagnosis and therapeutic markers.What Is Proteomics?The name “proteome” was first described by Wilkins and Williams in their article introducing bacterial gene-product mapping in 1995.3Wasinger V.C. Cordwell S.J. Cerpa-Poljak A. Yan J.X. Gooley A.A. Wilkins M.R. Duncan M.W. Harris R. Williams K.L. Humphery-Smith I. Progress with gene-product mapping of the Mollicutes Mycoplasma genitalium.Electrophoresis. 1995; 16: 1090-1094Crossref PubMed Scopus (807) Google Scholar The proteome (protein + genome), or proteomics, refers to the total protein profile of a cell, a cell organelle, a tissue, an organ, and serum/plasma/body fluid.4Kahn P. New funds plant seeds for genome research effort.Science. 1997; 275: 25-26Crossref PubMed Scopus (1) Google Scholar, 5Swinbanks D. Government backs proteome proposal.Nature. 1995; 378: 653PubMed Google Scholar “Proteomics” as well as “genomics” is a representative of the “omics” era, that additionally includes glycomics and metabolomics. The goal of proteomics is the comprehensive and quantitative determination of protein expression and its changes under pathological situations or drug treatment. Proteomics also seeks to determine 3-dimensional (3-D) protein structure, posttranslational modifications, protein localization, and protein-protein interactions in addition to the protein expression level. Great progress in mass spectrometry (MS) technology from the late 1980s has enabled us to directly measure the molecular weights of endogenous proteins easily and accurately with high throughput.Methods for ProteomicsProteomics research is basically composed of (1) separation of proteins in the proteome, and (2) identification/characterization of individual proteins. Two-dimensional polyacrylamide gel electrophoresis (2-D PAGE), originally developed by Patrick O’Farrel in 1975, is currently the method of choice for resolving the protein components of a proteome.6O’Farrell P.H. High resolution two-dimensional electrophoresis of proteins.J Biol Chem. 1975; 250: 4007-4021Abstract Full Text PDF PubMed Google Scholar This technique combines isoelectric focusing, which separates proteins by their molecular charge in the first dimension, with sodium dodecyl sulfate (SDS)-PAGE, which arranges them according to their molecular weight in the second dimension. It is capable of separating 1000 to 3000 protein spots on a single 2-D gel. Proteins on the gels are visualized by silver staining or recently developed sensitive dyes such as SYPRO ruby. Protein identification by MS relies on the digestion of protein samples into peptide fragments by a sequence-specific protease such as trypsin. Matrix-assisted laser desorption ionization (MALDI) or electrospray ionization mass spectrometry (ESI-MS) are now primarily used.7Roepstorff P. Mass spectrometry in protein studies from genome to function.Curr Opin Biotechnol. 1997; 8: 6-13Crossref PubMed Scopus (166) Google Scholar, 8Yates 3rd, J.R. Mass spectrometry and the age of the proteome.J Mass Spectrom. 1998; 33: 1-19Crossref PubMed Scopus (675) Google Scholar Several initiatives have been started under the Human Proteome Organization (HUPO) to determine liver, brain, serum, and other proteomes.As for pioneering proteomics work on hepatic constituent cells, Kristensen et al9Kristensen D.B. Kawada N. Imamura K. Miyamoto Y. Tateno C. Seki S. Kuroki T. Yoshizato K. Proteome analysis of rat hepatic stellate cells.Hepatology. 2000; 32: 268-277Crossref PubMed Scopus (204) Google Scholar undertook the “classical” proteomics approach to further elucidate the molecular mechanism of hepatic stellate cell activation at the protein level in 2000. Protein populations expressed in quiescent and activated stellate cells were separated by 2-D PAGE and subsequently analyzed using ESI-MS. Such a protein level “differential display” identified 43 proteins that altered their expression levels during the activation process. This study also led to the discovery of cytoglobin, the fourth globin in mammals.10Kawada N. Kristensen D.B. Asahina K. Nakatani K. Minamiyama Y. Seki S. Yoshizato K. Characterization of a stellate cell activation-associated protein (STAP) with peroxidase activity found in rat hepatic stellate cells.J Biol Chem. 2001; 276: 25318-25323Crossref PubMed Scopus (300) Google ScholarUntil recently, global protein separation and identification were thus investigated through 2-D PAGE. However, this technique has several disadvantages. First, only a few thousand proteins can be separated on one gel, whereas more than 10,000 proteins are expected to be expressed in any cell, indicating that less abundant molecules involved in signal transduction and transcription factors are overlooked. Second, basic membranous and high molecular weight proteins are usually difficult to separate by 2-D PAGE. The use of high-performance liquid chromatography (LC) overcomes these problems. In addition, LC can be directly connected to MS/MS, resulting in the automatic, high-throughput and rapid determination and identification of proteins.11Wolters D.A. Washburn M.P. Yates 3rd, J.R. An automated multidimensional protein identification technology for shotgun proteomics.Anal Chem. 2001; 73: 5683-5690Crossref PubMed Scopus (1557) Google ScholarPosttranslational Modifications of ProteinsPosttranslational modifications of proteins affect protein turnover, localization, activity, or binding interactions. Phosphorylation, acetylation, methylation, glycation, ubiquitination, and lipid modifications are among the most common posttranslational modifications.12Saghatelian A. Cravatt B.F. Assignment of protein function in the postgenomic era.Nat Chem Biol. 2005; 1: 130-142Crossref PubMed Scopus (120) Google Scholar Because a given modification results in a change in the molecular mass of the affected amino acid, MS is the method of choice for characterizing posttranslational modifications, eg, a shift of a Δ mass of 80 Da indicates a phosphate modification.Proteomics of Serum BiomarkersSerum is the best protein sample representative of the whole body condition. Thus, serum proteomics is an area attracting intense interest as it is easily accessible, non-invasive and the serum levels of proteins can be excellent biomarkers of disease. According to HUPO’ Plasma Proteome Project, until now (February 2006), at least 3020 proteins have been identified in human plasma (see http://www.hupo.org/). The latest serum proteomics technique utilizes the ProteinChip system based on surface enhanced laser desorption/ionization (SELDI).13Merchant M. Weinberger S.R. Recent advancements in surface-enhanced laser desorption/ionization-time of flight-mass spectrometry.Electrophoresis. 2000; 21: 1164-1177Crossref PubMed Scopus (670) Google Scholar, 14Wiesner A. Detection of tumor markers with ProteinChip technology.Curr Pharm Biotechnol. 2004; 5: 45-67Crossref PubMed Scopus (113) Google Scholar This technology is composed basically of 3 steps. First, scientists select a ProteinChip array coated with chromatographic properties, such as hydrophobic, hydrophilic, anion exchange, cation exchange, and immobilized-metal affinity surfaces according to their purposes. Second, serums from patients are applied to the ProteinChip arrays. Third, after washing, the arrays are analyzed in the ProteinChip reader, a time-of-flight (TOF)-MS and finally specific MS patterns obtained from patients in a disease category are collected and, if successful, proteins can be identified directly after digestion. This technique is attractive because of its simplicity and clinical applicability. However, MALDI MS of serum often yields breakdown products of highly abundant proteins such as albumin and immunoglobulin. In contrast, many clinical markers, ie, cytokines, are exceedingly rare and are not detected. Nevertheless, the idea of obtaining complex pattern information by MS and statistical techniques to correlate these patterns with disease is extremely attractive and could potentially revolutionize diagnostic practice.Cancer Serum Proteomics for GastroenterologyThere have been several reports aiming to identify serum biomarkers for cancers of the liver, pancreas, and gut. Kawakami et al15Kawakami T. Hoshida Y. Kanai F. Tanaka Y. Tateishi K. Ikenoue T. Obi S. Sato S. Teratani T. Shiina S. Kawabe T. Suzuki T. Hatano N. Taniguchi H. Omata M. Proteomic analysis of sera from hepatocellular carcinoma patients after radiofrequency ablation treatment.Proteomics. 2005; 5: 4287-4295Crossref PubMed Scopus (55) Google Scholar analyzed serum samples collected from 8 patients before and after treatment with radiofrequency ablation for hepatocellular carcinoma by 2-D PAGE and subsequent MS analysis, and found that pro-apolipoprotein, alpha2-HS glycoprotein, apolipoprotein A-IV precursor, and PRO1708/PRO2044 were decreased and seven proteins including leucine-rich alpha 2-glycoprotein and alpha1-antitrypsin were increased after treatment. Schwegler et al16Schwegler E.E. Cazares L. Steel L.F. Adam B.L. Johnson D.A. Semmes O.J. Block T.M. Marrero J.A. Drake R.R. SELDI-TOF MS profiling of serum for detection of the progression of chronic hepatitis C to hepatocellular carcinoma.Hepatology. 2005; 41: 634-642Crossref PubMed Scopus (141) Google Scholar demonstrated using metal affinity protein chips that SELDI-TOF MS serum profiling is able to distinguish HCC from liver disease before as well as during cirrhosis. For pancreatic cancer, Yu et al17Yu K.H. Rustgi A.K. Blair I.A. Characterization of proteins in human pancreatic cancer serum using differential gel electrophoresis and tandem mass spectrometry.J Proteome Res. 2005; 4: 1742-1751Crossref PubMed Scopus (135) Google Scholar used a differential in-gel electrophoresis (DIGE) method and identified 24 unique proteins that were increased and 17 unique proteins that were decreased in cancer serum samples, in which increased levels of apolipoprotein E, alpha-1-antichymotrypsin, and inter-alpha-trypsin inhibitor were found to be associated with pancreatic cancer. In addition, human neutrophile peptides 1, 2 and 3 were isolated as biomarkers for colon cancer in serum.18Albrethsen J. Bogebo R. Gammeltoft S. Olsen J. Winther B. Raskov H. Upregulated expression of human neutrophil peptides 1, 2 and 3 (HNP 1-3) in colon cancer serum and tumours a biomarker study.BMC Cancer. 2005; 5: 8Crossref PubMed Scopus (136) Google ScholarIn this issue of Gastroenterology, Poon et al19Poon T.C.W. Sung J.J.Y. Chow S.M. Ng E.K.W. Yu A.C.W. Chu E.S.H. Hui A.M.Y. Leung W.K. Diagnosis of gastric cancer by serum proteomic fingerprinting.Gastroenterology. 2006; 130: 1858-1864Abstract Full Text Full Text PDF PubMed Scopus (51) Google Scholar report serum biomarkers for gastric cancer identified by SELDI ProteinChip technology. Using IMAC30 and CM10 ProteinChip arrays, the authors compared mass spectra of the serum samples of gastric cancer patient and control groups. As a result, they discovered 5 proteomic features with the mass/charge values of 5098, 8592 (8610), 11468, 11804, and 50140, whose intensities were lowered in postoperative sera. When these 5 markers were combined to generate a diagnostic index, the best sensitivity and specificity of this panel of proteomic markers was 83% and 95%, respectively. Sensitivity improved according to the stage of cancer. As discussed by the Poon et al,19Poon T.C.W. Sung J.J.Y. Chow S.M. Ng E.K.W. Yu A.C.W. Chu E.S.H. Hui A.M.Y. Leung W.K. Diagnosis of gastric cancer by serum proteomic fingerprinting.Gastroenterology. 2006; 130: 1858-1864Abstract Full Text Full Text PDF PubMed Scopus (51) Google Scholar the findings via serum proteomics could be biased by artifacts related to the nature of the clinical samples, sample storage conditions, experimental details, and the mass spectrometric instruments and/or bioinformatic analyses. Nevertheless, the advantage of the present study is supported by the unique experimental design in which the serum differential proteomic features identified in the discovery set were considered as potential diagnostic markers only if their level were reversed in the postoperative sera. Accordingly, only 6 proteomics features were selected for further validation, increasing the specificity of the assay shown here.It can be said that MS analysis used in the present work leads to the identification of individual proteins listed in this article. As stated by the authors, one of them may be the serum amyloid A isoform, although it cannot be a specific diagnostic marker of gastric cancer because it is also increased in the serum of ovarian cancer, pancreatic cancer, lung cancer, renal cell carcinoma, and so on.20Moshkovskii S.A. Serebryakova M.V. Kuteykin-Teplyakov K.B. Tikhonova O.V. Goufman E.I. Zgoda V.G. Taranets I.N. Makarov O.V. Archakov A.I. Ovarian cancer marker of 11.7 kDa detected by proteomics is a serum amyloid A1.Proteomics. 2005; 5: 3790-3797Crossref PubMed Scopus (98) Google Scholar, 21Juan H.F. Chen J.H. Hsu W.T. Huang S.C. Chen S.T. Yi-Chung Lin J. Chang Y.W. Chiang C.Y. Wen L.L. Chan D.C. Liu Y.C. Chen Y.J. Identification of tumor-associated plasma biomarkers using proteomic techniques from mouse to human.Proteomics. 2004; 4: 2766-2775Crossref PubMed Scopus (78) Google Scholar The remaining 4 gastric cancer-specific proteomic features may be derived from different proteins or their degradation products, which are candidate molecules that are utilized for simple immunoassay. Posttranslational modifications should also be taken into account.Potential ProblemsTo our knowledge, the FDA has not approved any SELDI or other serum profiling proteomics-based technology for clinical use in cancer diagnostics. Although the use of serum profiling in “clinical proteomics” has attracted much attention, especially due to the original work of Petricion22Petricoin 3rd, E.F. Ornstein D.K. Paweletz C.P. Ardekani A. Hackett P.S. Hitt B.A. Velassco A. Trucco C. Wiegand L. Wood K. Simone C.B. Levine P.J. Linehan W.M. Emmert-Buck M.R. Steinberg S.M. Kohn E.C. Liotta L.A. Serum proteomic patterns for detection of prostate cancer.J Natl Cancer Inst. 2002; 94: 1576-1578Crossref PubMed Scopus (657) Google Scholar on ovarian cancer, several attempts to reproduce diagnostic serum patterns between laboratories have failed, and it is also worth mentioning that serum profile variation can be enormous between humans, and even variation within the same individual can be significant with influences such as the menstrual cycle, time of day, fasting, age, inflammation, etc. In addition, SELDI-TOF technology currently used for serum analysis is incapable of detecting any serum component at concentrations of less than 1 μg/mL; this range of concentrations is approximately 1000-fold higher than the concentrations of known tumor markers in circulation (for instance, α-fetoprotein, 150 pmol/L). Thus, the serum discriminatory peaks identified by MS may represent abundant molecules not released into the circulation by very small tumors or their microenvironments.23Diamandis E.P. Analysis of serum proteomic patterns for early cancer diagnosis drawing attention to potential problems.J Natl Cancer Inst. 2004; 96: 353-356Crossref PubMed Scopus (357) Google ScholarIn conclusion, modern proteomics has developed into a powerful tool for clinical screening for cancer diagnosis in the field of gastroenterology. A comprehensive, systemic characterization of circulating proteins in health and disease will greatly facilitate the development of biomarkers for the prevention, diagnosis, and therapy of cancers and other diseases. See article on page 1858. See article on page 1858. See article on page 1858. The Human Genome Project has revealed that about 22,000–25,000 proteins are encoded in our genome, while about 10,000 proteins are likely to be expressed in any one kind of cell, indicating that only a part of genes in the genome are expressed in a strictly regulated manner.1International Human Genome Sequencing Consortium. Finishing the euchromatic sequence of the human genome. Nature 2004;431931–43145.Google Scholar Therefore, besides genome research, comprehensive analysis of proteins sourced from cells, tissues, and serum, especially concerning changes in their expression level and posttranscriptional modifications according to health and disease, particularly in cancer, has been increasing during the past decade.2de Hoog C.L. Mann M. Proteomics.Annu Rev Genomics Hum Genet. 2004; 5: 267-293Crossref PubMed Scopus (193) Google Scholar Great progress in this field has been supported by the advancement of protein chemistry using high performance mass spectrometry, as represented by the Nobel Prize of 2002. Clinical science has used the obtained database for the development of disease diagnosis and therapeutic markers. What Is Proteomics?The name “proteome” was first described by Wilkins and Williams in their article introducing bacterial gene-product mapping in 1995.3Wasinger V.C. Cordwell S.J. Cerpa-Poljak A. Yan J.X. Gooley A.A. Wilkins M.R. Duncan M.W. Harris R. Williams K.L. Humphery-Smith I. Progress with gene-product mapping of the Mollicutes Mycoplasma genitalium.Electrophoresis. 1995; 16: 1090-1094Crossref PubMed Scopus (807) Google Scholar The proteome (protein + genome), or proteomics, refers to the total protein profile of a cell, a cell organelle, a tissue, an organ, and serum/plasma/body fluid.4Kahn P. New funds plant seeds for genome research effort.Science. 1997; 275: 25-26Crossref PubMed Scopus (1) Google Scholar, 5Swinbanks D. Government backs proteome proposal.Nature. 1995; 378: 653PubMed Google Scholar “Proteomics” as well as “genomics” is a representative of the “omics” era, that additionally includes glycomics and metabolomics. The goal of proteomics is the comprehensive and quantitative determination of protein expression and its changes under pathological situations or drug treatment. Proteomics also seeks to determine 3-dimensional (3-D) protein structure, posttranslational modifications, protein localization, and protein-protein interactions in addition to the protein expression level. Great progress in mass spectrometry (MS) technology from the late 1980s has enabled us to directly measure the molecular weights of endogenous proteins easily and accurately with high throughput. The name “proteome” was first described by Wilkins and Williams in their article introducing bacterial gene-product mapping in 1995.3Wasinger V.C. Cordwell S.J. Cerpa-Poljak A. Yan J.X. Gooley A.A. Wilkins M.R. Duncan M.W. Harris R. Williams K.L. Humphery-Smith I. Progress with gene-product mapping of the Mollicutes Mycoplasma genitalium.Electrophoresis. 1995; 16: 1090-1094Crossref PubMed Scopus (807) Google Scholar The proteome (protein + genome), or proteomics, refers to the total protein profile of a cell, a cell organelle, a tissue, an organ, and serum/plasma/body fluid.4Kahn P. New funds plant seeds for genome research effort.Science. 1997; 275: 25-26Crossref PubMed Scopus (1) Google Scholar, 5Swinbanks D. Government backs proteome proposal.Nature. 1995; 378: 653PubMed Google Scholar “Proteomics” as well as “genomics” is a representative of the “omics” era, that additionally includes glycomics and metabolomics. The goal of proteomics is the comprehensive and quantitative determination of protein expression and its changes under pathological situations or drug treatment. Proteomics also seeks to determine 3-dimensional (3-D) protein structure, posttranslational modifications, protein localization, and protein-protein interactions in addition to the protein expression level. Great progress in mass spectrometry (MS) technology from the late 1980s has enabled us to directly measure the molecular weights of endogenous proteins easily and accurately with high throughput. Methods for ProteomicsProteomics research is basically composed of (1) separation of proteins in the proteome, and (2) identification/characterization of individual proteins. Two-dimensional polyacrylamide gel electrophoresis (2-D PAGE), originally developed by Patrick O’Farrel in 1975, is currently the method of choice for resolving the protein components of a proteome.6O’Farrell P.H. High resolution two-dimensional electrophoresis of proteins.J Biol Chem. 1975; 250: 4007-4021Abstract Full Text PDF PubMed Google Scholar This technique combines isoelectric focusing, which separates proteins by their molecular charge in the first dimension, with sodium dodecyl sulfate (SDS)-PAGE, which arranges them according to their molecular weight in the second dimension. It is capable of separating 1000 to 3000 protein spots on a single 2-D gel. Proteins on the gels are visualized by silver staining or recently developed sensitive dyes such as SYPRO ruby. Protein identification by MS relies on the digestion of protein samples into peptide fragments by a sequence-specific protease such as trypsin. Matrix-assisted laser desorption ionization (MALDI) or electrospray ionization mass spectrometry (ESI-MS) are now primarily used.7Roepstorff P. Mass spectrometry in protein studies from genome to function.Curr Opin Biotechnol. 1997; 8: 6-13Crossref PubMed Scopus (166) Google Scholar, 8Yates 3rd, J.R. Mass spectrometry and the age of the proteome.J Mass Spectrom. 1998; 33: 1-19Crossref PubMed Scopus (675) Google Scholar Several initiatives have been started under the Human Proteome Organization (HUPO) to determine liver, brain, serum, and other proteomes.As for pioneering proteomics work on hepatic constituent cells, Kristensen et al9Kristensen D.B. Kawada N. Imamura K. Miyamoto Y. Tateno C. Seki S. Kuroki T. Yoshizato K. Proteome analysis of rat hepatic stellate cells.Hepatology. 2000; 32: 268-277Crossref PubMed Scopus (204) Google Scholar undertook the “classical” proteomics approach to further elucidate the molecular mechanism of hepatic stellate cell activation at the protein level in 2000. Protein populations expressed in quiescent and activated stellate cells were separated by 2-D PAGE and subsequently analyzed using ESI-MS. Such a protein level “differential display” identified 43 proteins that altered their expression levels during the activation process. This study also led to the discovery of cytoglobin, the fourth globin in mammals.10Kawada N. Kristensen D.B. Asahina K. Nakatani K. Minamiyama Y. Seki S. Yoshizato K. Characterization of a stellate cell activation-associated protein (STAP) with peroxidase activity found in rat hepatic stellate cells.J Biol Chem. 2001; 276: 25318-25323Crossref PubMed Scopus (300) Google ScholarUntil recently, global protein separation and identification were thus investigated through 2-D PAGE. However, this technique has several disadvantages. First, only a few thousand proteins can be separated on one gel, whereas more than 10,000 proteins are expected to be expressed in any cell, indicating that less abundant molecules involved in signal transduction and transcription factors are overlooked. Second, basic membranous and high molecular weight proteins are usually difficult to separate by 2-D PAGE. The use of high-performance liquid chromatography (LC) overcomes these problems. In addition, LC can be directly connected to MS/MS, resulting in the automatic, high-throughput and rapid determination and identification of proteins.11Wolters D.A. Washburn M.P. Yates 3rd, J.R. An automated multidimensional protein identification technology for shotgun proteomics.Anal Chem. 2001; 73: 5683-5690Crossref PubMed Scopus (1557) Google Scholar Proteomics research is basically composed of (1) separation of proteins in the proteome, and (2) identification/characterization of individual proteins. Two-dimensional polyacrylamide gel electrophoresis (2-D PAGE), originally developed by Patrick O’Farrel in 1975, is currently the method of choice for resolving the protein components of a proteome.6O’Farrell P.H. High resolution two-dimensional electrophoresis of proteins.J Biol Chem. 1975; 250: 4007-4021Abstract Full Text PDF PubMed Google Scholar This technique combines isoelectric focusing, which separates proteins by their molecular charge in the first dimension, with sodium dodecyl sulfate (SDS)-PAGE, which arranges them according to their molecular weight in the second dimension. It is capable of separating 1000 to 3000 protein spots on a single 2-D gel. Proteins on the gels are visualized by silver staining or recently developed sensitive dyes such as SYPRO ruby. Protein identification by MS relies on the digestion of protein samples into peptide fragments by a sequence-specific protease such as trypsin. Matrix-assisted laser desorption ionization (MALDI) or electrospray ionization mass spectrometry (ESI-MS) are now primarily used.7Roepstorff P. Mass spectrometry in protein studies from genome to function.Curr Opin Biotechnol. 1997; 8: 6-13Crossref PubMed Scopus (166) Google Scholar, 8Yates 3rd, J.R. Mass spectrometry and the age of the proteome.J Mass Spectrom. 1998; 33: 1-19Crossref PubMed Scopus (675) Google Scholar Several initiatives have been started under the Human Proteome Organization (HUPO) to determine liver, brain, serum, and other proteomes. As for pioneering proteomics work on hepatic constituent cells, Kristensen et al9Kristensen D.B. Kawada N. Imamura K. Miyamoto Y. Tateno C. Seki S. Kuroki T. Yoshizato K. Proteome analysis of rat hepatic stellate cells.Hepatology. 2000; 32: 268-277Crossref PubMed Scopus (204) Google Scholar undertook the “classical” proteomics approach to further elucidate the molecular mechanism of hepatic stellate cell activation at the protein level in 2000. Protein populations expressed in quiescent and activated stellate cells were separated by 2-D PAGE and subsequently analyzed using ESI-MS. Such a protein level “differential display” identified 43 proteins that altered their expression levels during the activation process. This study also led to the discovery of cytoglobin, the fourth globin in mammals.10Kawada N. Kristensen D.B. Asahina K. Nakatani K. Minamiyama Y. Seki S. Yoshizato K. Characterization of a stellate cell activation-associated protein (STAP) with peroxidase activity found in rat hepatic stellate cells.J Biol Chem. 2001; 276: 25318-25323Crossref PubMed Scopus (300) Google Scholar Until recently, global protein separation and identification were thus investigated through 2-D PAGE. However, this technique has several disadvantages. First, only a few thousand proteins can be separated on one gel, whereas more than 10,000 proteins are expected to be expressed in any cell, indicating that less abundant molecules involved in signal transduction and transcription factors are overlooked. Second, basic membranous and high molecular weight proteins are usually difficult to separate by 2-D PAGE. The use of high-performance liquid chromatography (LC) overcomes these problems. In addition, LC can be directly connected to MS/MS, resulting in the automatic, high-throughput and rapid determination and identification of proteins.11Wolters D.A. Washburn M.P. Yates 3rd, J.R. An automated multidimensional protein identification technology for shotgun proteomics.Anal Chem. 2001; 73: 5683-5690Crossref PubMed Scopus (1557) Google Scholar Posttranslational Modifications of ProteinsPosttranslational modifications of proteins affect protein turnover, localization, activity, or binding interactions. Phosphorylation, acetylation, methylation, glycation, ubiquitination, and lipid modifications are among the most common posttranslational modifications.12Saghatelian A. Cravatt B.F. Assignment of protein function in the postgenomic era.Nat Chem Biol. 2005; 1: 130-142Crossref PubMed Scopus (120) Google Scholar Because a given modification results in a change in the molecular mass of the affected amino acid, MS is the method of choice for characterizing posttranslational modifications, eg, a shift of a Δ mass of 80 Da indicates a phosphate modification. Posttranslational modifications of proteins affect protein turnover, localization, activity, or binding interactions. Phosphorylation, acetylation, methylation, glycation, ubiquitination, and lipid modifications are among the most common posttranslational modifications.12Saghatelian A. Cravatt B.F. Assignment of protein function in the postgenomic era.Nat Chem Biol. 2005; 1: 130-142Crossref PubMed Scopus (120) Google Scholar Because a given modification results in a change in the molecular mass of the affected amino acid, MS is the method of choice for characterizing posttranslational modifications, eg, a shift of a Δ mass of 80 Da indicates a phosphate modification. Proteomics of Serum BiomarkersSerum is the best protein sample representative of the whole body condition. Thus, serum proteomics is an area attracting intense interest as it is easily accessible, non-invasive and the serum levels of proteins can be excellent biomarkers of disease. According to HUPO’ Plasma Proteome Project, until now (February 2006), at least 3020 proteins have been identified in human plasma (see http://www.hupo.org/). The latest serum proteomics technique utilizes the ProteinChip system based on surface enhanced laser desorption/ionization (SELDI).13Merchant M. Weinberger S.R. Recent advancements in surface-enhanced laser desorption/ionization-time of flight-mass spectrometry.Electrophoresis. 2000; 21: 1164-1177Crossref PubMed Scopus (670) Google Scholar, 14Wiesner A. Detection of tumor markers with ProteinChip technology.Curr Pharm Biotechnol. 2004; 5: 45-67Crossref PubMed Scopus (113) Google Scholar This technology is composed basically of 3 steps. First, scientists select a ProteinChip array coated with chromatographic properties, such as hydrophobic, hydrophilic, anion exchange, cation exchange, and immobilized-metal affinity surfaces according to their purposes. Second, serums from patients are applied to the ProteinChip arrays. Third, after washing, the arrays are analyzed in the ProteinChip reader, a time-of-flight (TOF)-MS and finally specific MS patterns obtained from patients in a disease category are collected and, if successful, proteins can be identified directly after digestion. This technique is attractive because of its simplicity and clinical applicability. However, MALDI MS of serum often yields breakdown products of highly abundant proteins such as albumin and immunoglobulin. In contrast, many clinical markers, ie, cytokines, are exceedingly rare and are not detected. Nevertheless, the idea of obtaining complex pattern information by MS and statistical techniques to correlate these patterns with disease is extremely attractive and could potentially revolutionize diagnostic practice. Serum is the best protein sample representative of the whole body condition. Thus, serum proteomics is an area attracting intense interest as it is easily accessible, non-invasive and the serum levels of proteins can be excellent biomarkers of disease. According to HUPO’ Plasma Proteome Project, until now (February 2006), at least 3020 proteins have been identified in human plasma (see http://www.hupo.org/). The latest serum proteomics technique utilizes the ProteinChip system based on surface enhanced laser desorption/ionization (SELDI).13Merchant M. Weinberger S.R. Recent advancements in surface-enhanced laser desorption/ionization-time of flight-mass spectrometry.Electrophoresis. 2000; 21: 1164-1177Crossref PubMed Scopus (670) Google Scholar, 14Wiesner A. Detection of tumor markers with ProteinChip technology.Curr Pharm Biotechnol. 2004; 5: 45-67Crossref PubMed Scopus (113) Google Scholar This technology is composed basically of 3 steps. First, scientists select a ProteinChip array coated with chromatographic properties, such as hydrophobic, hydrophilic, anion exchange, cation exchange, and immobilized-metal affinity surfaces according to their purposes. Second, serums from patients are applied to the ProteinChip arrays. Third, after washing, the arrays are analyzed in the ProteinChip reader, a time-of-flight (TOF)-MS and finally specific MS patterns obtained from patients in a disease category are collected and, if successful, proteins can be identified directly after digestion. This technique is attractive because of its simplicity and clinical applicability. However, MALDI MS of serum often yields breakdown products of highly abundant proteins such as albumin and immunoglobulin. In contrast, many clinical markers, ie, cytokines, are exceedingly rare and are not detected. Nevertheless, the idea of obtaining complex pattern information by MS and statistical techniques to correlate these patterns with disease is extremely attractive and could potentially revolutionize diagnostic practice. Cancer Serum Proteomics for GastroenterologyThere have been several reports aiming to identify serum biomarkers for cancers of the liver, pancreas, and gut. Kawakami et al15Kawakami T. Hoshida Y. Kanai F. Tanaka Y. Tateishi K. Ikenoue T. Obi S. Sato S. Teratani T. Shiina S. Kawabe T. Suzuki T. Hatano N. Taniguchi H. Omata M. Proteomic analysis of sera from hepatocellular carcinoma patients after radiofrequency ablation treatment.Proteomics. 2005; 5: 4287-4295Crossref PubMed Scopus (55) Google Scholar analyzed serum samples collected from 8 patients before and after treatment with radiofrequency ablation for hepatocellular carcinoma by 2-D PAGE and subsequent MS analysis, and found that pro-apolipoprotein, alpha2-HS glycoprotein, apolipoprotein A-IV precursor, and PRO1708/PRO2044 were decreased and seven proteins including leucine-rich alpha 2-glycoprotein and alpha1-antitrypsin were increased after treatment. Schwegler et al16Schwegler E.E. Cazares L. Steel L.F. Adam B.L. Johnson D.A. Semmes O.J. Block T.M. Marrero J.A. Drake R.R. SELDI-TOF MS profiling of serum for detection of the progression of chronic hepatitis C to hepatocellular carcinoma.Hepatology. 2005; 41: 634-642Crossref PubMed Scopus (141) Google Scholar demonstrated using metal affinity protein chips that SELDI-TOF MS serum profiling is able to distinguish HCC from liver disease before as well as during cirrhosis. For pancreatic cancer, Yu et al17Yu K.H. Rustgi A.K. Blair I.A. Characterization of proteins in human pancreatic cancer serum using differential gel electrophoresis and tandem mass spectrometry.J Proteome Res. 2005; 4: 1742-1751Crossref PubMed Scopus (135) Google Scholar used a differential in-gel electrophoresis (DIGE) method and identified 24 unique proteins that were increased and 17 unique proteins that were decreased in cancer serum samples, in which increased levels of apolipoprotein E, alpha-1-antichymotrypsin, and inter-alpha-trypsin inhibitor were found to be associated with pancreatic cancer. In addition, human neutrophile peptides 1, 2 and 3 were isolated as biomarkers for colon cancer in serum.18Albrethsen J. Bogebo R. Gammeltoft S. Olsen J. Winther B. Raskov H. Upregulated expression of human neutrophil peptides 1, 2 and 3 (HNP 1-3) in colon cancer serum and tumours a biomarker study.BMC Cancer. 2005; 5: 8Crossref PubMed Scopus (136) Google ScholarIn this issue of Gastroenterology, Poon et al19Poon T.C.W. Sung J.J.Y. Chow S.M. Ng E.K.W. Yu A.C.W. Chu E.S.H. Hui A.M.Y. Leung W.K. Diagnosis of gastric cancer by serum proteomic fingerprinting.Gastroenterology. 2006; 130: 1858-1864Abstract Full Text Full Text PDF PubMed Scopus (51) Google Scholar report serum biomarkers for gastric cancer identified by SELDI ProteinChip technology. Using IMAC30 and CM10 ProteinChip arrays, the authors compared mass spectra of the serum samples of gastric cancer patient and control groups. As a result, they discovered 5 proteomic features with the mass/charge values of 5098, 8592 (8610), 11468, 11804, and 50140, whose intensities were lowered in postoperative sera. When these 5 markers were combined to generate a diagnostic index, the best sensitivity and specificity of this panel of proteomic markers was 83% and 95%, respectively. Sensitivity improved according to the stage of cancer. As discussed by the Poon et al,19Poon T.C.W. Sung J.J.Y. Chow S.M. Ng E.K.W. Yu A.C.W. Chu E.S.H. Hui A.M.Y. Leung W.K. Diagnosis of gastric cancer by serum proteomic fingerprinting.Gastroenterology. 2006; 130: 1858-1864Abstract Full Text Full Text PDF PubMed Scopus (51) Google Scholar the findings via serum proteomics could be biased by artifacts related to the nature of the clinical samples, sample storage conditions, experimental details, and the mass spectrometric instruments and/or bioinformatic analyses. Nevertheless, the advantage of the present study is supported by the unique experimental design in which the serum differential proteomic features identified in the discovery set were considered as potential diagnostic markers only if their level were reversed in the postoperative sera. Accordingly, only 6 proteomics features were selected for further validation, increasing the specificity of the assay shown here.It can be said that MS analysis used in the present work leads to the identification of individual proteins listed in this article. As stated by the authors, one of them may be the serum amyloid A isoform, although it cannot be a specific diagnostic marker of gastric cancer because it is also increased in the serum of ovarian cancer, pancreatic cancer, lung cancer, renal cell carcinoma, and so on.20Moshkovskii S.A. Serebryakova M.V. Kuteykin-Teplyakov K.B. Tikhonova O.V. Goufman E.I. Zgoda V.G. Taranets I.N. Makarov O.V. Archakov A.I. Ovarian cancer marker of 11.7 kDa detected by proteomics is a serum amyloid A1.Proteomics. 2005; 5: 3790-3797Crossref PubMed Scopus (98) Google Scholar, 21Juan H.F. Chen J.H. Hsu W.T. Huang S.C. Chen S.T. Yi-Chung Lin J. Chang Y.W. Chiang C.Y. Wen L.L. Chan D.C. Liu Y.C. Chen Y.J. Identification of tumor-associated plasma biomarkers using proteomic techniques from mouse to human.Proteomics. 2004; 4: 2766-2775Crossref PubMed Scopus (78) Google Scholar The remaining 4 gastric cancer-specific proteomic features may be derived from different proteins or their degradation products, which are candidate molecules that are utilized for simple immunoassay. Posttranslational modifications should also be taken into account. There have been several reports aiming to identify serum biomarkers for cancers of the liver, pancreas, and gut. Kawakami et al15Kawakami T. Hoshida Y. Kanai F. Tanaka Y. Tateishi K. Ikenoue T. Obi S. Sato S. Teratani T. Shiina S. Kawabe T. Suzuki T. Hatano N. Taniguchi H. Omata M. Proteomic analysis of sera from hepatocellular carcinoma patients after radiofrequency ablation treatment.Proteomics. 2005; 5: 4287-4295Crossref PubMed Scopus (55) Google Scholar analyzed serum samples collected from 8 patients before and after treatment with radiofrequency ablation for hepatocellular carcinoma by 2-D PAGE and subsequent MS analysis, and found that pro-apolipoprotein, alpha2-HS glycoprotein, apolipoprotein A-IV precursor, and PRO1708/PRO2044 were decreased and seven proteins including leucine-rich alpha 2-glycoprotein and alpha1-antitrypsin were increased after treatment. Schwegler et al16Schwegler E.E. Cazares L. Steel L.F. Adam B.L. Johnson D.A. Semmes O.J. Block T.M. Marrero J.A. Drake R.R. SELDI-TOF MS profiling of serum for detection of the progression of chronic hepatitis C to hepatocellular carcinoma.Hepatology. 2005; 41: 634-642Crossref PubMed Scopus (141) Google Scholar demonstrated using metal affinity protein chips that SELDI-TOF MS serum profiling is able to distinguish HCC from liver disease before as well as during cirrhosis. For pancreatic cancer, Yu et al17Yu K.H. Rustgi A.K. Blair I.A. Characterization of proteins in human pancreatic cancer serum using differential gel electrophoresis and tandem mass spectrometry.J Proteome Res. 2005; 4: 1742-1751Crossref PubMed Scopus (135) Google Scholar used a differential in-gel electrophoresis (DIGE) method and identified 24 unique proteins that were increased and 17 unique proteins that were decreased in cancer serum samples, in which increased levels of apolipoprotein E, alpha-1-antichymotrypsin, and inter-alpha-trypsin inhibitor were found to be associated with pancreatic cancer. In addition, human neutrophile peptides 1, 2 and 3 were isolated as biomarkers for colon cancer in serum.18Albrethsen J. Bogebo R. Gammeltoft S. Olsen J. Winther B. Raskov H. Upregulated expression of human neutrophil peptides 1, 2 and 3 (HNP 1-3) in colon cancer serum and tumours a biomarker study.BMC Cancer. 2005; 5: 8Crossref PubMed Scopus (136) Google Scholar In this issue of Gastroenterology, Poon et al19Poon T.C.W. Sung J.J.Y. Chow S.M. Ng E.K.W. Yu A.C.W. Chu E.S.H. Hui A.M.Y. Leung W.K. Diagnosis of gastric cancer by serum proteomic fingerprinting.Gastroenterology. 2006; 130: 1858-1864Abstract Full Text Full Text PDF PubMed Scopus (51) Google Scholar report serum biomarkers for gastric cancer identified by SELDI ProteinChip technology. Using IMAC30 and CM10 ProteinChip arrays, the authors compared mass spectra of the serum samples of gastric cancer patient and control groups. As a result, they discovered 5 proteomic features with the mass/charge values of 5098, 8592 (8610), 11468, 11804, and 50140, whose intensities were lowered in postoperative sera. When these 5 markers were combined to generate a diagnostic index, the best sensitivity and specificity of this panel of proteomic markers was 83% and 95%, respectively. Sensitivity improved according to the stage of cancer. As discussed by the Poon et al,19Poon T.C.W. Sung J.J.Y. Chow S.M. Ng E.K.W. Yu A.C.W. Chu E.S.H. Hui A.M.Y. Leung W.K. Diagnosis of gastric cancer by serum proteomic fingerprinting.Gastroenterology. 2006; 130: 1858-1864Abstract Full Text Full Text PDF PubMed Scopus (51) Google Scholar the findings via serum proteomics could be biased by artifacts related to the nature of the clinical samples, sample storage conditions, experimental details, and the mass spectrometric instruments and/or bioinformatic analyses. Nevertheless, the advantage of the present study is supported by the unique experimental design in which the serum differential proteomic features identified in the discovery set were considered as potential diagnostic markers only if their level were reversed in the postoperative sera. Accordingly, only 6 proteomics features were selected for further validation, increasing the specificity of the assay shown here. It can be said that MS analysis used in the present work leads to the identification of individual proteins listed in this article. As stated by the authors, one of them may be the serum amyloid A isoform, although it cannot be a specific diagnostic marker of gastric cancer because it is also increased in the serum of ovarian cancer, pancreatic cancer, lung cancer, renal cell carcinoma, and so on.20Moshkovskii S.A. Serebryakova M.V. Kuteykin-Teplyakov K.B. Tikhonova O.V. Goufman E.I. Zgoda V.G. Taranets I.N. Makarov O.V. Archakov A.I. Ovarian cancer marker of 11.7 kDa detected by proteomics is a serum amyloid A1.Proteomics. 2005; 5: 3790-3797Crossref PubMed Scopus (98) Google Scholar, 21Juan H.F. Chen J.H. Hsu W.T. Huang S.C. Chen S.T. Yi-Chung Lin J. Chang Y.W. Chiang C.Y. Wen L.L. Chan D.C. Liu Y.C. Chen Y.J. Identification of tumor-associated plasma biomarkers using proteomic techniques from mouse to human.Proteomics. 2004; 4: 2766-2775Crossref PubMed Scopus (78) Google Scholar The remaining 4 gastric cancer-specific proteomic features may be derived from different proteins or their degradation products, which are candidate molecules that are utilized for simple immunoassay. Posttranslational modifications should also be taken into account. Potential ProblemsTo our knowledge, the FDA has not approved any SELDI or other serum profiling proteomics-based technology for clinical use in cancer diagnostics. Although the use of serum profiling in “clinical proteomics” has attracted much attention, especially due to the original work of Petricion22Petricoin 3rd, E.F. Ornstein D.K. Paweletz C.P. Ardekani A. Hackett P.S. Hitt B.A. Velassco A. Trucco C. Wiegand L. Wood K. Simone C.B. Levine P.J. Linehan W.M. Emmert-Buck M.R. Steinberg S.M. Kohn E.C. Liotta L.A. Serum proteomic patterns for detection of prostate cancer.J Natl Cancer Inst. 2002; 94: 1576-1578Crossref PubMed Scopus (657) Google Scholar on ovarian cancer, several attempts to reproduce diagnostic serum patterns between laboratories have failed, and it is also worth mentioning that serum profile variation can be enormous between humans, and even variation within the same individual can be significant with influences such as the menstrual cycle, time of day, fasting, age, inflammation, etc. In addition, SELDI-TOF technology currently used for serum analysis is incapable of detecting any serum component at concentrations of less than 1 μg/mL; this range of concentrations is approximately 1000-fold higher than the concentrations of known tumor markers in circulation (for instance, α-fetoprotein, 150 pmol/L). Thus, the serum discriminatory peaks identified by MS may represent abundant molecules not released into the circulation by very small tumors or their microenvironments.23Diamandis E.P. Analysis of serum proteomic patterns for early cancer diagnosis drawing attention to potential problems.J Natl Cancer Inst. 2004; 96: 353-356Crossref PubMed Scopus (357) Google ScholarIn conclusion, modern proteomics has developed into a powerful tool for clinical screening for cancer diagnosis in the field of gastroenterology. A comprehensive, systemic characterization of circulating proteins in health and disease will greatly facilitate the development of biomarkers for the prevention, diagnosis, and therapy of cancers and other diseases. To our knowledge, the FDA has not approved any SELDI or other serum profiling proteomics-based technology for clinical use in cancer diagnostics. Although the use of serum profiling in “clinical proteomics” has attracted much attention, especially due to the original work of Petricion22Petricoin 3rd, E.F. Ornstein D.K. Paweletz C.P. Ardekani A. Hackett P.S. Hitt B.A. Velassco A. Trucco C. Wiegand L. Wood K. Simone C.B. Levine P.J. Linehan W.M. Emmert-Buck M.R. Steinberg S.M. Kohn E.C. Liotta L.A. Serum proteomic patterns for detection of prostate cancer.J Natl Cancer Inst. 2002; 94: 1576-1578Crossref PubMed Scopus (657) Google Scholar on ovarian cancer, several attempts to reproduce diagnostic serum patterns between laboratories have failed, and it is also worth mentioning that serum profile variation can be enormous between humans, and even variation within the same individual can be significant with influences such as the menstrual cycle, time of day, fasting, age, inflammation, etc. In addition, SELDI-TOF technology currently used for serum analysis is incapable of detecting any serum component at concentrations of less than 1 μg/mL; this range of concentrations is approximately 1000-fold higher than the concentrations of known tumor markers in circulation (for instance, α-fetoprotein, 150 pmol/L). Thus, the serum discriminatory peaks identified by MS may represent abundant molecules not released into the circulation by very small tumors or their microenvironments.23Diamandis E.P. Analysis of serum proteomic patterns for early cancer diagnosis drawing attention to potential problems.J Natl Cancer Inst. 2004; 96: 353-356Crossref PubMed Scopus (357) Google Scholar In conclusion, modern proteomics has developed into a powerful tool for clinical screening for cancer diagnosis in the field of gastroenterology. A comprehensive, systemic characterization of circulating proteins in health and disease will greatly facilitate the development of biomarkers for the prevention, diagnosis, and therapy of cancers and other diseases. Diagnosis of Gastric Cancer by Serum Proteomic FingerprintingGastroenterologyVol. 130Issue 6PreviewBackground & Aims Accurate serum biomarkers for gastric cancer currently are lacking. We attempted to identify potential diagnostic serum markers for gastric cancer with the use of the surface-enhanced laser desorption/ionization ProteinChip technology. Methods The study was divided into 3 phases: (1) discovery of potential diagnostic markers using sera of gastric cancer patients and controls, (2) development of a diagnostic model, and (3) independent validation of the diagnostic model using a different cohort of gastric cancer and control patients. Full-Text PDF" @default.
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