1
|
Liang K, Li Q, Song Z, Zhao K, Su R, Huang S, Guo X, Li Y. Endogenous Plasma Peptides Modulated by Protease in a Time-Dependent Manner as Effective Biomarkers for Preanalytical Quality Control. J Proteome Res 2023; 22:3029-3039. [PMID: 37530177 DOI: 10.1021/acs.jproteome.3c00335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/03/2023]
Abstract
Non-cryopreservation temperature exposure (NCE) is a vital preanalytical factor for assessing plasma quality. NCE can introduce undesirable errors in clinical diagnosis or when developing biomarkers of diseases. Biomarkers that can effectively indicate the changes in sample quality caused by long-term NCE (0-several days) are limited. Low-molecular-weight (LMW) peptides in the plasma are modulated by endogenous proteases. These protease activities are significantly correlated with NCE temperatures and duration, indicating a potential link of these protease reactions with the preanalytical quality of plasma samples. In this study, two groups of plasma samples were aged at room temperature (RT, 57 samples) and 4 °C (69 samples) for different durations (0, 1, 2, 5, and 10 days), and LMW peptidomics were analyzed through nanopore-assisted matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The analysis revealed 10 peptides that consistently exhibited time-dependent changes, which were used to develop multiple-variable models for predicting the changes in sample quality resulting from extended NCE. These biomarker models exhibited outstanding performance in distinguishing poor-quality samples aged at both RT and 4 °C. To validate the findings, tests on samples from validation sets were conducted by analysts who were blinded to the detailed conditions, which revealed a high specificity (94.3-96.9%) and sensitivity (90.5-99.3%). These results indicate the potential of these peptides as novel biomarkers of quality control.
Collapse
Affiliation(s)
- Kai Liang
- Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- Western Institute of Health Data Science, Chongqin 400050, China
| | - Qianqian Li
- Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhijing Song
- Western Institute of Health Data Science, Chongqin 400050, China
| | - Keli Zhao
- Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Rong Su
- Foshan Hospital of Traditional Chinese Medicine, Foshan 528000, China
| | - Shengchun Huang
- Foshan Hospital of Traditional Chinese Medicine, Foshan 528000, China
| | - Xueyan Guo
- Foshan Hospital of Traditional Chinese Medicine, Foshan 528000, China
| | - Yan Li
- Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- Western Institute of Health Data Science, Chongqin 400050, China
| |
Collapse
|
2
|
de Oliveira TM, de Lacerda JTJG, Leite GGF, Dias M, Mendes MA, Kassab P, E Silva CGS, Juliano MA, Forones NM. Label-free peptide quantification coupled with in silico mapping of proteases for identification of potential serum biomarkers in gastric adenocarcinoma patients. Clin Biochem 2020; 79:61-69. [PMID: 32097616 DOI: 10.1016/j.clinbiochem.2020.02.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 01/31/2020] [Accepted: 02/18/2020] [Indexed: 12/27/2022]
Abstract
OBJECTIVES We aimed to identify serum level variations in protein-derived peptides between patients diagnosed with gastric adenocarcinoma (GAC) and non-cancer persons (control) to detect the activity changes of proteases and explore the auxiliary diagnostic value in the context of GAC physiopathology. METHODS The label-free quantitative peptidome approach was applied to identify variants in serum levels of peptides that can differentiate GAC patients from the control group. Peptide sequences were submitted against Proteasix tool predicting proteases potentially involved in their generation. The activity change of proteases was subsequently estimated based on the peptides with significantly altered relative abundance. In turn, activity change prediction of proteases was correlated with relevant protease expression data from the literature. RESULTS A total of 191 peptide sequences generated by the cleavage of 36 precursor proteins were identified. Using the label-free quantification approach, 33 peptides were differentially quantified (adjusted fold change ≥ 1.5 and p-value < 0.05) in which 19 were up-regulated and 14 were down-regulated in GAC samples. Of these peptides, fibrinopeptide A was significantly decreased and its phosphorylated form ADpSGEGDFLAEGGGVR was upregulated in GAC samples. Activity change prediction yielded 10 proteases including 6 Matrix Metalloproteinases (MMPs), Thrombin, Plasmin, and kallikreins 4 and 14. Among predicted proteases in our analysis, MMP-7 was presented as a more promising biomarker associated with useful assays of clinical practice for GAC diagnosis. CONCLUSION Our experimental results demonstrate that the serum levels of peptides were significantly differentiated in GAC physiopathology. The hypotheses built on protease regulation could be used for further investigations to measure proteases and their activity levels that have been poorly studied for GAC diagnosis.
Collapse
Affiliation(s)
- Talita Mendes de Oliveira
- Department of Medicine, Division of Gastroenterology, Oncology Group, Federal University of São Paulo, São Paulo, SP, Brazil.
| | | | | | - Meriellen Dias
- Department of Chemical Engineering, University of São Paulo, São Paulo, SP, Brazil
| | - Maria Anita Mendes
- Department of Chemical Engineering, University of São Paulo, São Paulo, SP, Brazil
| | - Paulo Kassab
- Digestive Surgical Oncology Division, Santa Casa of São Paulo Medical School, São Paulo, SP, Brazil
| | | | | | - Nora Manoukian Forones
- Department of Medicine, Division of Gastroenterology, Oncology Group, Federal University of São Paulo, São Paulo, SP, Brazil
| |
Collapse
|
3
|
Klont F, Horvatovich P, Govorukhina N, Bischoff R. Pre- and Post-analytical Factors in Biomarker Discovery. Methods Mol Biol 2019; 1959:1-22. [PMID: 30852812 DOI: 10.1007/978-1-4939-9164-8_1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
The translation of promising biomarkers, which were identified in biomarker discovery experiments, to clinical assays is one of the key challenges in present-day proteomics research. Many so-called "biomarker candidates" fail to progress beyond the discovery phase, and much emphasis is placed on pre- and post-analytical variability in an attempt to provide explanations for this bottleneck in the biomarker development pipeline. With respect to such variability, there is a large number of pre- and post-analytical factors which may impact the outcomes of proteomics experiments and thus necessitate tight control. This chapter highlights some of these factors and provides guidance for addressing them on the basis of examples from previously published proteomics studies.
Collapse
Affiliation(s)
- Frank Klont
- Department of Analytical Biochemistry, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands
| | - Peter Horvatovich
- Department of Analytical Biochemistry, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands
| | - Natalia Govorukhina
- Department of Analytical Biochemistry, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands
| | - Rainer Bischoff
- Department of Analytical Biochemistry, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.
| |
Collapse
|
4
|
Moulder R, Bhosale SD, Goodlett DR, Lahesmaa R. Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling. MASS SPECTROMETRY REVIEWS 2018; 37:583-606. [PMID: 29120501 DOI: 10.1002/mas.21550] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 09/26/2017] [Indexed: 05/23/2023]
Abstract
Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.
Collapse
Affiliation(s)
- Robert Moulder
- Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland
| | - Santosh D Bhosale
- Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland
| | | | - Riitta Lahesmaa
- Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland
| |
Collapse
|
5
|
Dufresne J, Florentinus-Mefailoski A, Ajambo J, Ferwa A, Bowden P, Marshall J. Random and independent sampling of endogenous tryptic peptides from normal human EDTA plasma by liquid chromatography micro electrospray ionization and tandem mass spectrometry. Clin Proteomics 2017; 14:41. [PMID: 29234243 PMCID: PMC5721679 DOI: 10.1186/s12014-017-9176-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Accepted: 11/26/2017] [Indexed: 12/12/2022] Open
Abstract
Background Normal human EDTA plasma samples were collected on ice, processed ice cold, and stored in a freezer at – 80 °C prior to experiments. Plasma test samples from the – 80 °C freezer were thawed on ice or intentionally warmed to room temperature. Methods Protein content was measured by CBBR binding and the release of alcohol soluble amines by the Cd ninhydrin assay. Plasma peptides released over time were collected over C18 for random and independent sampling by liquid chromatography micro electrospray ionization and tandem mass spectrometry (LC–ESI–MS/MS) and correlated with X!TANDEM. Results Fully tryptic peptides by X!TANDEM returned a similar set of proteins, but was more computationally efficient, than “no enzyme” correlations. Plasma samples maintained on ice, or ice with a cocktail of protease inhibitors, showed lower background amounts of plasma peptides compared to samples incubated at room temperature. Regression analysis indicated that warming plasma to room temperature, versus ice cold, resulted in a ~ twofold increase in the frequency of peptide identification over hours–days of incubation at room temperature. The type I error rate of the protein identification from the X!TANDEM algorithm combined was estimated to be low compared to a null model of computer generated random MS/MS spectra. Conclusion The peptides of human plasma were identified and quantified with low error rates by random and independent sampling that revealed 1000s of peptides from hundreds of human plasma proteins from endogenous tryptic peptides. Electronic supplementary material The online version of this article (10.1186/s12014-017-9176-7) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Jaimie Dufresne
- Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3 Canada
| | | | - Juliet Ajambo
- Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3 Canada
| | - Ammara Ferwa
- Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3 Canada
| | - Peter Bowden
- Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3 Canada
| | - John Marshall
- Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3 Canada.,Integrated BioBank of Luxembourg, 6 r. Nicolas-Ernest Barblé, Dudelange, 1210 Luxembourg
| |
Collapse
|
6
|
The proteins cleaved by endogenous tryptic proteases in normal EDTA plasma by C18 collection of peptides for liquid chromatography micro electrospray ionization and tandem mass spectrometry. Clin Proteomics 2017; 14:39. [PMID: 29213220 PMCID: PMC5712186 DOI: 10.1186/s12014-017-9174-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Accepted: 11/21/2017] [Indexed: 02/08/2023] Open
Abstract
The tryptic peptides from ice cold versus room temperature plasma were identified by C18 liquid chromatography and micro electrospray ionization tandem mass spectrometry (LC–ESI–MS/MS). Samples collected on ice showed low levels of endogenous tryptic peptides compared to the same samples incubated at room temperature. Plasma on ice contained peptides from albumin, complement, and apolipoproteins and others that were observed by the X!TANDEM and SEQUEST algorithms. In contrast to ice cold samples, after incubation at room temperature, greater numbers of tryptic peptides from well characterized plasma proteins, and from cellular proteins were observed. A total of 583,927 precursor ions and MS/MS spectra were correlated to 94,669 best fit peptides that reduced to 22,287 correlations to the best accession within a gene symbol and to 7174 correlations to at least 510 gene symbols with ≥ 5 independent MS/MS correlations (peptide counts) that showed FDR q-values ranging from E−9 (i.e. FDR = 0.000000001) to E−227. A set of 528 gene symbols identified by X!TANDEM and SEQUEST including C4B showed ≥ fivefold variation between ice cold versus room temperature incubation. STRING analysis of the protein gene symbols observed from endogenous peptides in normal plasma revealed an extensive protein-interaction network of cellular factors associated with cell signalling and regulation, the formation of membrane bound organelles, cellular exosomes and exocytosis network proteins. Taken together the results indicated that a pool of cellular proteins, or protein complexes, in plasma are apparently not stable and degrade soon after incubation at room temperature.
Collapse
|
7
|
Dufresne J, Hoang T, Ajambo J, Florentinus-Mefailoski A, Bowden P, Marshall J. Freeze-dried plasma proteins are stable at room temperature for at least 1 year. Clin Proteomics 2017; 14:35. [PMID: 29093647 PMCID: PMC5659006 DOI: 10.1186/s12014-017-9170-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Accepted: 10/11/2017] [Indexed: 12/23/2022] Open
Abstract
Thirty human EDTA plasma samples from male and female subjects ranging in age from 24 to 74 years were collected on ice, processed ice cold and stored frozen at -80 °C, in liquid nitrogen (LN2), or freeze dried and stored at room temperature in a desiccator (FDRT) or freeze dried and stored at -20 °C for 1 year (FD-20). In a separate experiment, EDTA plasma samples were collected onto ice, processed ice cold and maintained on ice ± protease inhibitors versus incubated at room temperature for up to 96 h. Random and independent sampling by liquid chromatography and tandem mass spectrometry (LC-ESI-MS/MS), as correlated by the MASCOT, OMSSA, X!TANDEM and SEQUEST algorithms, showed that tryptic peptides from complement component 4B (C4B) were rapidly released in plasma at room temperature. Random sampling by LC-ESI-MS/MS showed that peptides from C4B were undetectable on ice, but peptides were cleaved from the mature C4B protein including NGFKSHALQLNNR within as little as 1 h at room temperature. The frequency and intensity of precursors within ± 3 m/z of the C4B peptide NGFKSHALQLNNR was confirmed by automated targeted analysis where the precursors from MS/MS spectra that correlated to the target sequence were analyzed in SQL/R. The C4B preproprotein was processed at the N terminus to release the mature chain that was cleaved on the carboxyl side of the isoprene C2 domain within a polar C terminal sequence of the mature C4B protein, to reveal the thioester reaction site, consistent with LC-ESI-MS/MS and Western blot. Random sampling showed that proteolytic peptides from complement component C4B were rarely observed with long term storage at - 80 °C in a freezer or in liquid nitrogen (LN2), freeze drying with storage at - 20 °C (FD-20 °C) or freeze drying and storage at room temperature (FDRT). Plasma samples maintained at room temperature (RT) showed at least 10-fold to 100-fold greater frequency of peptide correlation to C4B and measured peptide intensity compared to samples on ice for up to 72 h or stored at - 80 °C, LN2, FDRT or FD-20 °C for up to a year.
Collapse
Affiliation(s)
- Jaimie Dufresne
- Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3 Canada
| | - Trung Hoang
- Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3 Canada
| | - Juliet Ajambo
- Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3 Canada
| | | | - Peter Bowden
- Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3 Canada
| | - John Marshall
- Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3 Canada.,Integrated BioBank of Luxembourg, 6 r. Nicolas-Ernest Barblé, 1210 Luxembourg, Luxembourg
| |
Collapse
|
8
|
Identification of Tengfu Jiangya Tablet Target Biomarkers with Quantitative Proteomic Technique. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2017; 2017:7594805. [PMID: 28408942 PMCID: PMC5376940 DOI: 10.1155/2017/7594805] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Accepted: 02/08/2017] [Indexed: 12/21/2022]
Abstract
Tengfu Jiangya Tablet (TJT) is a well accepted antihypertension drug in China and its major active components were Uncaria total alkaloids and Semen Raphani soluble alkaloid. To further explore treatment effects mechanism of TJT on essential hypertension, a serum proteomic study was performed. Potential biomarkers were quantified in serum of hypertension individuals before and after taking TJT with isobaric tags for relative and absolute quantitation (iTRAQ) coupled two-dimensional liquid chromatography followed electrospray ionization-tandem mass spectrometry (2D LC-MS/MS) proteomics technique. Among 391 identified proteins with high confidence, 70 proteins were differentially expressed (fold variation criteria, >1.2 or <0.83) between two groups (39 upregulated and 31 downregulated). Combining with Gene Ontology annotation, KEGG pathway analysis, and literature retrieval, 5 proteins were chosen as key target biomarkers during TJT therapeutic process. And the alteration profiles of these 5 proteins were verified by ELISA and Western Blot. Proteins Kininogen 1 and Keratin 1 are members of Kallikrein system, while Myeloperoxidase, Serum Amyloid protein A, and Retinol binding protein 4 had been reported closely related to vascular endothelial injury. Our study discovered 5 target biomarkers of the compound Chinese medicine TJT. Secondly, this research initially revealed the antihypertension therapeutic mechanism of this drug from a brand-new aspect.
Collapse
|
9
|
Mitra V, Govorukhina N, Zwanenburg G, Hoefsloot H, Westra I, Smilde A, Reijmers T, van der Zee AGJ, Suits F, Bischoff R, Horvatovich P. Identification of Analytical Factors Affecting Complex Proteomics Profiles Acquired in a Factorial Design Study with Analysis of Variance: Simultaneous Component Analysis. Anal Chem 2016; 88:4229-38. [PMID: 26959230 DOI: 10.1021/acs.analchem.5b03483] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Complex shotgun proteomics peptide profiles obtained in quantitative differential protein expression studies, such as in biomarker discovery, may be affected by multiple experimental factors. These preanalytical factors may affect the measured protein abundances which in turn influence the outcome of the associated statistical analysis and validation. It is therefore important to determine which factors influence the abundance of peptides in a complex proteomics experiment and to identify those peptides that are most influenced by these factors. In the current study we analyzed depleted human serum samples to evaluate experimental factors that may influence the resulting peptide profile such as the residence time in the autosampler at 4 °C, stopping or not stopping the trypsin digestion with acid, the type of blood collection tube, different hemolysis levels, differences in clotting times, the number of freeze-thaw cycles, and different trypsin/protein ratios. To this end we used a two-level fractional factorial design of resolution IV (2(IV)(7-3)). The design required analysis of 16 samples in which the main effects were not confounded by two-factor interactions. Data preprocessing using the Threshold Avoiding Proteomics Pipeline (Suits, F.; Hoekman, B.; Rosenling, T.; Bischoff, R.; Horvatovich, P. Anal. Chem. 2011, 83, 7786-7794, ref 1) produced a data-matrix containing quantitative information on 2,559 peaks. The intensity of the peaks was log-transformed, and peaks having intensities of a low t-test significance (p-value > 0.05) and a low absolute fold ratio (<2) between the two levels of each factor were removed. The remaining peaks were subjected to analysis of variance (ANOVA)-simultaneous component analysis (ASCA). Permutation tests were used to identify which of the preanalytical factors influenced the abundance of the measured peptides most significantly. The most important preanalytical factors affecting peptide intensity were (1) the hemolysis level, (2) stopping trypsin digestion with acid, and (3) the trypsin/protein ratio. This provides guidelines for the experimentalist to keep the ratio of trypsin/protein constant and to control the trypsin reaction by stopping it with acid at an accurately set pH. The hemolysis level cannot be controlled tightly as it depends on the status of a patient's blood (e.g., red blood cells are more fragile in patients undergoing chemotherapy) and the care with which blood was sampled (e.g., by avoiding shear stress). However, its level can be determined with a simple UV spectrophotometric measurement and samples with extreme levels or the peaks affected by hemolysis can be discarded from further analysis. The loadings of the ASCA model led to peptide peaks that were most affected by a given factor, for example, to hemoglobin-derived peptides in the case of the hemolysis level. Peak intensity differences for these peptides were assessed by means of extracted ion chromatograms confirming the results of the ASCA model.
Collapse
Affiliation(s)
- Vikram Mitra
- Analytical Biochemistry, Department of Pharmacy, University of Groningen , A. Deusinglaan 1, 9713 AV Groningen, The Netherlands.,Netherlands Bioinformatics Centre , Geert Grooteplein 28, 6525 GA Nijmegen, The Netherlands.,Netherlands Proteomics Centre , Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Natalia Govorukhina
- Analytical Biochemistry, Department of Pharmacy, University of Groningen , A. Deusinglaan 1, 9713 AV Groningen, The Netherlands.,Netherlands Proteomics Centre , Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Gooitzen Zwanenburg
- Swammerdam Institute for Life Science, University of Amsterdam , The Netherlands, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Huub Hoefsloot
- Swammerdam Institute for Life Science, University of Amsterdam , The Netherlands, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Inge Westra
- Analytical Biochemistry, Department of Pharmacy, University of Groningen , A. Deusinglaan 1, 9713 AV Groningen, The Netherlands
| | - Age Smilde
- Swammerdam Institute for Life Science, University of Amsterdam , The Netherlands, Science Park 904, 1098 XH Amsterdam, The Netherlands.,Netherlands Bioinformatics Centre , Geert Grooteplein 28, 6525 GA Nijmegen, The Netherlands
| | - Theo Reijmers
- Analytical BioSciences, Leiden University , Einsteinweg 55, 2333 CC Leiden, The Netherlands
| | - Ate G J van der Zee
- Department of Gynecology, University Medical Centre Groningen , Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Frank Suits
- IBM T.J. Watson Research Centre , 1101 Kitchawan Road, Yorktown Heights, New York 10598, United States
| | - Rainer Bischoff
- Analytical Biochemistry, Department of Pharmacy, University of Groningen , A. Deusinglaan 1, 9713 AV Groningen, The Netherlands.,Netherlands Bioinformatics Centre , Geert Grooteplein 28, 6525 GA Nijmegen, The Netherlands.,Netherlands Proteomics Centre , Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Péter Horvatovich
- Analytical Biochemistry, Department of Pharmacy, University of Groningen , A. Deusinglaan 1, 9713 AV Groningen, The Netherlands.,Netherlands Bioinformatics Centre , Geert Grooteplein 28, 6525 GA Nijmegen, The Netherlands.,Netherlands Proteomics Centre , Padualaan 8, 3584 CH Utrecht, The Netherlands
| |
Collapse
|
10
|
Horvatovich P, Lundberg EK, Chen YJ, Sung TY, He F, Nice EC, Goode RJ, Yu S, Ranganathan S, Baker MS, Domont GB, Velasquez E, Li D, Liu S, Wang Q, He QY, Menon R, Guan Y, Corrales FJ, Segura V, Casal JI, Pascual-Montano A, Albar JP, Fuentes M, Gonzalez-Gonzalez M, Diez P, Ibarrola N, Degano RM, Mohammed Y, Borchers CH, Urbani A, Soggiu A, Yamamoto T, Salekdeh GH, Archakov A, Ponomarenko E, Lisitsa A, Lichti CF, Mostovenko E, Kroes RA, Rezeli M, Végvári Á, Fehniger TE, Bischoff R, Vizcaíno JA, Deutsch EW, Lane L, Nilsson CL, Marko-Varga G, Omenn GS, Jeong SK, Lim JS, Paik YK, Hancock WS. Quest for Missing Proteins: Update 2015 on Chromosome-Centric Human Proteome Project. J Proteome Res 2015; 14:3415-31. [DOI: 10.1021/pr5013009] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Péter Horvatovich
- Analytical
Biochemistry, Department of Pharmacy, University of Groningen, A. Deusinglaan
1, 9713 AV Groningen, The Netherlands
| | - Emma K. Lundberg
- Science
for Life Laboratory, KTH - Royal Institute of Technology, SE-171 21 Stockholm, Sweden
| | - Yu-Ju Chen
- Institute
of Chemistry, Academia Sinica, 128 Academia Road Sec. 2, Taipei 115, Taiwan
| | - Ting-Yi Sung
- Institute
of Information Science, Academia Sinica, 128 Academia Road Sec. 2, Taipei 115, Taiwan
| | - Fuchu He
- The State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, No. 27 Taiping Road, Haidian District, Beijing 100850, China
| | - Edouard C. Nice
- Department
of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria 3800, Australia
| | - Robert J. Goode
- Department
of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria 3800, Australia
| | - Simon Yu
- Department
of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria 3800, Australia
| | - Shoba Ranganathan
- Department
of Chemistry and Biomolecular Sciences and ARC Centre of Excellence
in Bioinformatics, Macquarie University, Sydney, New South Wales 2109, Australia
| | - Mark S. Baker
- Australian
School of Advanced Medicine, Macquarie University, Sydney, NSW 2109, Australia
| | - Gilberto B. Domont
- Proteomics Unit, Institute of Chemistry, Federal University of Rio de Janeiro, Cidade Universitária, Av Athos da Silveira Ramos 149, CT-A542, 21941-909 Rio de Janeriro, Rj, Brazil
| | - Erika Velasquez
- Proteomics Unit, Institute of Chemistry, Federal University of Rio de Janeiro, Cidade Universitária, Av Athos da Silveira Ramos 149, CT-A542, 21941-909 Rio de Janeriro, Rj, Brazil
| | - Dong Li
- The State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, No. 27 Taiping Road, Haidian District, Beijing 100850, China
| | - Siqi Liu
- Beijing Institute of Genomics and BGI Shenzhen, No. 1 Beichen West Road, Chaoyang District, Beijing 100101, China
- BGI Shenzhen, Beishan Road, Yantian District, Shenzhen, 518083, China
| | - Quanhui Wang
- Beijing Institute of Genomics and BGI Shenzhen, No. 1 Beichen West Road, Chaoyang District, Beijing 100101, China
| | - Qing-Yu He
- Key Laboratory of Functional Protein
Research of Guangdong
Higher Education Institutes, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Rajasree Menon
- Department of Computational Medicine & Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, Michigan 48109-2218, United States
| | - Yuanfang Guan
- Departments of Computational Medicine & Bioinformatics and Computer Sciences, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, Michigan 48109-2218, United States
| | - Fernando J. Corrales
- ProteoRed-ISCIII,
Biomolecular and Bioinformatics Resources Platform (PRB2), Spanish
Consortium of C-HPP (Chr-16), CIMA, University of Navarra, 31008 Pamplona, Spain
- Chr16 SpHPP Consortium, CIMA, University of Navarra, 31008 Pamplona, Spain
| | - Victor Segura
- ProteoRed-ISCIII,
Biomolecular and Bioinformatics Resources Platform (PRB2), Spanish
Consortium of C-HPP (Chr-16), CIMA, University of Navarra, 31008 Pamplona, Spain
- Chr16 SpHPP Consortium, CIMA, University of Navarra, 31008 Pamplona, Spain
| | - J. Ignacio Casal
- Department
of Cellular and Molecular Medicine, Centro de Investigaciones Biológicas (CIB-CSIC), 28040 Madrid, Spain
| | | | - Juan P. Albar
- Centro Nacional de Biotecnologia (CNB-CSIC), Cantoblanco, 28049 Madrid, Spain
| | - Manuel Fuentes
- Cancer
Research Center. Proteomics Unit and General Service of Cytometry,
Department of Medicine, University of Salmanca-CSIC, IBSAL, Campus Miguel de Unamuno
s/n, 37007 Salamanca, Spain
| | - Maria Gonzalez-Gonzalez
- Cancer
Research Center. Proteomics Unit and General Service of Cytometry,
Department of Medicine, University of Salmanca-CSIC, IBSAL, Campus Miguel de Unamuno
s/n, 37007 Salamanca, Spain
| | - Paula Diez
- Cancer
Research Center. Proteomics Unit and General Service of Cytometry,
Department of Medicine, University of Salmanca-CSIC, IBSAL, Campus Miguel de Unamuno
s/n, 37007 Salamanca, Spain
| | - Nieves Ibarrola
- Cancer
Research Center. Proteomics Unit and General Service of Cytometry,
Department of Medicine, University of Salmanca-CSIC, IBSAL, Campus Miguel de Unamuno
s/n, 37007 Salamanca, Spain
| | - Rosa M. Degano
- Cancer
Research Center. Proteomics Unit and General Service of Cytometry,
Department of Medicine, University of Salmanca-CSIC, IBSAL, Campus Miguel de Unamuno
s/n, 37007 Salamanca, Spain
| | - Yassene Mohammed
- University of Victoria-Genome British Columbia Proteomics
Centre, Vancouver Island
Technology Park, #3101−4464 Markham Street, Victoria, British Columbia V8Z 7X8, Canada
- Center
for Proteomics and Metabolomics, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands
| | - Christoph H. Borchers
- University of Victoria-Genome British Columbia Proteomics
Centre, Vancouver Island
Technology Park, #3101−4464 Markham Street, Victoria, British Columbia V8Z 7X8, Canada
| | - Andrea Urbani
- Proteomics
and Metabonomic, Laboratory, Fondazione Santa Lucia, Rome, Italy
- Department
of Experimental Medicine and Surgery, University of Rome “Tor Vergata”, Rome, Italy
| | - Alessio Soggiu
- Department
of Veterinary Science and Public Health (DIVET), University of Milano, via Celoria 10, 20133 Milano, Italy
| | - Tadashi Yamamoto
- Institute
of Nephrology, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Ghasem Hosseini Salekdeh
- Department of Molecular Systems Biology at Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran, Karaj, Iran
| | | | | | - Andrey Lisitsa
- Orechovich Institute of Biomedical Chemistry, Moscow, Russia
| | - Cheryl F. Lichti
- Department
of Pharmacology and Toxicology, The University of Texas Medical Branch, Galveston, Texas 77555-0617, United States
| | - Ekaterina Mostovenko
- Department
of Pharmacology and Toxicology, The University of Texas Medical Branch, Galveston, Texas 77555-0617, United States
| | - Roger A. Kroes
- Falk Center for Molecular Therapeutics, Department of Biomedical Engineering, Northwestern University, 1801 Maple Ave., Suite 4300, Evanston, Illinois 60201, United States
| | - Melinda Rezeli
- Clinical Protein Science & Imaging, Department of Biomedical Engineering, Lund University, BMC D13, 221 84 Lund, Sweden
| | - Ákos Végvári
- Clinical Protein Science & Imaging, Department of Biomedical Engineering, Lund University, BMC D13, 221 84 Lund, Sweden
| | - Thomas E. Fehniger
- Clinical Protein Science & Imaging, Department of Biomedical Engineering, Lund University, BMC D13, 221 84 Lund, Sweden
| | - Rainer Bischoff
- Analytical
Biochemistry, Department of Pharmacy, University of Groningen, A. Deusinglaan
1, 9713 AV Groningen, The Netherlands
| | - Juan Antonio Vizcaíno
- European Molecular
Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, CB10 1SD, Hinxton, Cambridge, United Kingdom
| | - Eric W. Deutsch
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, Washington 98109, United States
| | - Lydie Lane
- SIB Swiss Institute of Bioinformatics, Geneva, Switzerland
- Department
of Human Protein Science, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Carol L. Nilsson
- Department
of Pharmacology and Toxicology, The University of Texas Medical Branch, Galveston, Texas 77555-0617, United States
| | - György Marko-Varga
- Clinical Protein Science & Imaging, Department of Biomedical Engineering, Lund University, BMC D13, 221 84 Lund, Sweden
| | - Gilbert S. Omenn
- Departments of Computational Medicine & Bioinformatics, Internal Medicine, Human Genetics and School of Public Health, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, Michigan 48109-2218, United States
| | - Seul-Ki Jeong
- Departments of Integrated Omics for Biomedical Science & Biochemistry, College of Life Science and Technology, Yonsei Proteome Research Center, Yonsei University, Seoul, 120-749, Korea
| | - Jong-Sun Lim
- Departments of Integrated Omics for Biomedical Science & Biochemistry, College of Life Science and Technology, Yonsei Proteome Research Center, Yonsei University, Seoul, 120-749, Korea
| | - Young-Ki Paik
- Departments of Integrated Omics for Biomedical Science & Biochemistry, College of Life Science and Technology, Yonsei Proteome Research Center, Yonsei University, Seoul, 120-749, Korea
| | - William S. Hancock
- The
Barnett Institute of Chemical and Biological Analysis, Northeastern University, 140 The Fenway, Boston, Massachusetts 02115, United States
| |
Collapse
|
11
|
Pesek J, Krüger T, Krieg N, Schiel M, Norgauer J, Großkreutz J, Rhode H. Native chromatographic sample preparation of serum, plasma and cerebrospinal fluid does not comprise a risk for proteolytic biomarker loss. J Chromatogr B Analyt Technol Biomed Life Sci 2013; 923-924:102-9. [DOI: 10.1016/j.jchromb.2013.02.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2012] [Revised: 02/01/2013] [Accepted: 02/06/2013] [Indexed: 01/04/2023]
|
12
|
Andersen JD, Boylan KL, Jemmerson R, Geller MA, Misemer B, Harrington KM, Weivoda S, Witthuhn BA, Argenta P, Vogel RI, Skubitz AP. Leucine-rich alpha-2-glycoprotein-1 is upregulated in sera and tumors of ovarian cancer patients. J Ovarian Res 2010; 3:21. [PMID: 20831812 PMCID: PMC2949730 DOI: 10.1186/1757-2215-3-21] [Citation(s) in RCA: 85] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2010] [Accepted: 09/10/2010] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND New biomarkers that replace or are used in conjunction with the current ovarian cancer diagnostic antigen, CA125, are needed for detection of ovarian cancer in the presurgical setting, as well as for detection of disease recurrence. We previously demonstrated the upregulation of leucine-rich alpha-2-glycoprotein-1 (LRG1) in the sera of ovarian cancer patients compared to healthy women using quantitative mass spectrometry. METHODS LRG1 was quantified by ELISA in serum from two relatively large cohorts of women with ovarian cancer and benign gynecological disease. The expression of LRG1 in ovarian cancer tissues and cell lines was examined by gene microarray, reverse-transcriptase polymerase chain reaction (RT-PCR), Western blot, immunocytochemistry and mass spectrometry. RESULTS Mean serum LRG1 was higher in 58 ovarian cancer patients than in 56 healthy women (89.33 ± 77.90 vs. 42.99 ± 9.88 ug/ml; p = 0.0008) and was highest among stage III/IV patients. In a separate set of 193 pre-surgical samples, LRG1 was higher in patients with serous or clear cell ovarian cancer (145.82 ± 65.99 ug/ml) compared to patients with benign gynecological diseases (82.53 ± 76.67 ug/ml, p < 0.0001). CA125 and LRG1 levels were moderately correlated (r = 0.47, p < 0.0001). LRG1 mRNA levels were higher in ovarian cancer tissues and cell lines compared to their normal counterparts when analyzed by gene microarray and RT-PCR. LRG1 protein was detected in ovarian cancer tissue samples and cell lines by immunocytochemistry and Western blotting. Multiple iosforms of LRG1 were observed by Western blot and were shown to represent different glycosylation states by digestion with glycosidase. LRG1 protein was also detected in the conditioned media of ovarian cancer cell culture by ELISA, Western blotting, and mass spectrometry. CONCLUSIONS Serum LRG1 was significantly elevated in women with ovarian cancer compared to healthy women and women with benign gynecological disease, and was only moderately correlated with CA125. Ovarian cancer cells secrete LRG1 and may contribute directly to the elevated levels of LRG1 observed in the serum of ovarian cancer patients. Future studies will determine whether LRG1 may serve as a biomarker for presurgical diagnosis, disease recurrence, and/or as a target for therapy.
Collapse
Affiliation(s)
- John D Andersen
- Department of Laboratory Medicine and Pathology, University of Minnesota, MMC 609, 420 Delaware St, SE Minneapolis, MN, USA.
| | | | | | | | | | | | | | | | | | | | | |
Collapse
|
13
|
Horvatovich PL, Bischoff R. Current technological challenges in biomarker discovery and validation. EUROPEAN JOURNAL OF MASS SPECTROMETRY (CHICHESTER, ENGLAND) 2010; 16:101-121. [PMID: 20065518 DOI: 10.1255/ejms.1050] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
In this review we will give an overview of the issues related to biomarker discovery studies with a focus on liquid chromatography-mass spectrometry (LC-MS) methods. Biomarker discovery is based on a close collaboration between clinicians, analytical scientists and chemometritians/statisticians. It is critical to define the final purpose of a biomarker or biomarker pattern at the onset of the study and to select case and control samples accordingly. This is followed by designing the experiment, starting with the sampling strategy, sample collection, storage and separation protocols, choice and validation of the quantitative profiling platform followed by data processing, statistical analysis and validation workflows. Biomarker candidates that result after statistical validation should be submitted for further validation and, ideally, be connected to the disease mechanism after their identification. Since most discovery studies work with a relatively small number of samples, it is necessary to assess the specificity and sensitivity of a given biomarker-based assay in a larger set of independent samples, preferably analyzed at another clinical center. Targeted analytical methods of higher throughput than the original discovery method are needed at this point and LC-tandem mass spectrometry is gaining acceptance in this field. Throughout this review, we will focus on possible sources of variance and how they can be assessed and reduced in order to avoid false positives and to reduce the number of false negatives in biomarker discovery research.
Collapse
Affiliation(s)
- Peter L Horvatovich
- Analytical Biochemistry, Department of Pharmacy, University of Groningen, A. Deusinglaan 1, 9713 AV Groningen, The Netherlands.
| | | |
Collapse
|
14
|
A label-free nano-liquid chromatography-mass spectrometry approach for quantitative serum peptidomics in Crohn's disease patients. J Chromatogr B Analyt Technol Biomed Life Sci 2009; 877:3127-36. [PMID: 19683480 DOI: 10.1016/j.jchromb.2009.08.003] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2009] [Revised: 07/18/2009] [Accepted: 08/03/2009] [Indexed: 12/28/2022]
Abstract
The identification of serum biomarkers for the diagnosis of inflammatory bowel diseases able to reduce the need for invasive tests represents a major goal in their therapy and follow-up. We report here a methodological approach for the evaluation of specific changes in the serum peptides abundance in healthy (H) and Crohn's disease (CD) subjects, based on a label-free LC ESI/Q-TOF differential mass spectrometry (MS) approach combined with targeted MS/MS analysis. The low molecular weight serum proteins were separated by RP nano-LC ESI/Q-TOF MS and the resulting datasets were aligned with msInspect software. The differently abundant peptides, evaluated using Proteios Software Environment, were identified by MS/MS analysis and database search. The identification of clusters of peptides resulting from proteins (such as fibrinogen-alpha) commonly involved in physiological processes lead to the evaluation of a possible role in CD of specific serum exoproteases. An assay based on synthetic peptides spiked into H, CD and ulcerative colitis (UC) serum samples as substrate, followed by MALDI MS and chemometric analysis of the metabolite patterns has been developed achieving a 100% discrimination between CD, UC and H subjects. The results are promising for the application of this approach as a simple tool for diagnostic aims and biomarker discovery in CD.
Collapse
|