Will Biomarkers Take Off at Last?

Service, R. F.

doi:10.1126/science.321.5897.1760

Cited by 17 publications

(11 citation statements)

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“…Another study of 18 patients with sepsis found differential protein expression in survivors versus nonsurvivors [78]. These plasma proteins included both known cytokines as well as a group of proteins with unknown functions [78,79]. …”

Section: Proteomicsmentioning

confidence: 99%

“…Presently used proteomics methods mainly sample classical plasma proteins in the range of μg/ml to mg/ml, thereby excluding messengers and proteins leaking from specific diseased tissue leakage products [83]. The abundance of different proteins in blood varies by more than 10 orders of magnitude [79]. In fact, attempts to conduct a large-scale characterization of the human plasma proteome had been disappointing.…”

Section: Proteomicsmentioning

confidence: 99%

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Bench-to-bedside review: Future novel diagnostics for sepsis - a systems biology approach

et al. 2013

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The early, accurate diagnosis and risk stratification of sepsis remains an important challenge in the critically ill. Since traditional biomarker strategies have not yielded a gold standard marker for sepsis, focus is shifting towards novel strategies that improve assessment capabilities. The combination of technological advancements and information generated through the human genome project positions systems biology at the forefront of biomarker discovery. While previously available, developments in the technologies focusing on DNA, gene expression, gene regulatory mechanisms, protein and metabolite discovery have made these tools more feasible to implement and less costly, and they have taken on an enhanced capacity such that they are ripe for utilization as tools to advance our knowledge and clinical research. Medicine is in a genome-level era that can leverage the assessment of thousands of molecular signals beyond simply measuring selected circulating proteins. Genomics is the study of the entire complement of genetic material of an individual. Epigenetics is the regulation of gene activity by reversible modifications of the DNA. Transcriptomics is the quantification of the relative levels of messenger RNA for a large number of genes in specific cells or tissues to measure differences in the expression levels of different genes, and the utilization of patterns of differential gene expression to characterize different biological states of a tissue. Proteomics is the large-scale study of proteins. Metabolomics is the study of the small molecule profiles that are the terminal downstream products of the genome and consists of the total complement of all low-molecular-weight molecules that cellular processes leave behind. Taken together, these individual fields of study may be linked during a systems biology approach. There remains a valuable opportunity to deploy these technologies further in human research. The techniques described in this paper not only have the potential to increase the spectrum of diagnostic and prognostic biomarkers in sepsis, but they may also enable the discovery of new disease pathways. This may in turn lead us to improved therapeutic targets. The objective of this paper is to provide an overview and basic framework for clinicians and clinical researchers to better understand the 'omics technologies' to enhance further use of these valuable tools.

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Section: Proteomicsmentioning

confidence: 99%

Section: Proteomicsmentioning

confidence: 99%

Bench-to-bedside review: Future novel diagnostics for sepsis - a systems biology approach

et al. 2013

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“…These methods are based on one MS feature of abundance such as spectral or peptide count or chromatographic peak area or height values using labelled or label-free approaches (see supplementary notes online for details). How to compare and quantify differential expression remains an important challenge for this field9, 10. To date, MS fragment ion intensities appear only to be used for candidate-based quantification, such as the quantification of small molecules relative to a labelled version of the analyte of interest11.…”

mentioning

confidence: 99%

Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis

et al. 2010

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“…A major cause of this restraint is that quantitative data analysis methodologies in proteomics are immature (1)(2)(3)(4)(5)(6)(7)(8)(9). The large amount of data from mass spectrometry (MS) based protein profiling (10) include a lot of noise and biases arising from biological and chemical variation, sample preparation, instrumental analysis, and data analysis (9).…”

mentioning

confidence: 99%

Enhanced Information Output From Shotgun Proteomics Data by Protein Quantification and Peptide Quality Control (PQPQ)

Forshed

Johansson

Pernemalm

et al. 2011

Molecular & Cellular Proteomics

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We present a tool to improve quantitative accuracy and precision in mass spectrometry based on shotgun proteomics: protein quantification by peptide quality control, PQPQ. The method is based on the assumption that the quantitative pattern of peptides derived from one protein will correlate over several samples. Dissonant patterns arise either from outlier peptides or because of the presence of different protein species. By correlation analysis, protein quantification by peptide quality control identifies and excludes outliers and detects the existence of different protein species. Alternative protein species are then quantified separately. By validating the algorithm on seven data sets related to different cancer studies we show that data processing by protein quantification by peptide quality control improves the information output from shotgun proteomics. Data from two labeling procedures and three different instrumental platforms was included in the evaluation. With this unique method using both peptide sequence data and quantitative data we can improve the quantitative accuracy and precision on the protein level and detect different protein species.

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Will Biomarkers Take Off at Last?

Cited by 17 publications

References 0 publications

Bench-to-bedside review: Future novel diagnostics for sepsis - a systems biology approach

Bench-to-bedside review: Future novel diagnostics for sepsis - a systems biology approach

Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis

Enhanced Information Output From Shotgun Proteomics Data by Protein Quantification and Peptide Quality Control (PQPQ)

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