Robustness and accuracy of high speed LC–MS separations for global peptide quantitation and biomarker discovery☆

Lengqvist, Johan; Andrade, Jorge; Yang, Yang; Alvélius, Gunvor; Lewensohn, Rolf; Lehtiö, Janne

doi:10.1016/j.jchromb.2009.02.052

Cited by 12 publications

(7 citation statements)

References 43 publications

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“…The following studies were all performed using this label-free quantitative approach. The comparison of control and radiated human colon cancer cells proved the reproducibility of this label-free approach [ 18 ]; the serum proteomic profiling of familial adenomatous polyposis patients revealed multiple novel celecoxib-modulated proteins [ 19 ]; proteins significantly associated with metastasis were identified by analyzing paraffin-embedded archival melanomas [ 20 ]; the analysis of 55 clinical serum samples from schizophrenia patients and healthy volunteers identified hundreds of differentially expressed serum proteins [ 21 ]; diagnostic markers and protein signatures were recognized from the serum of Gaucher patients [ 22 ] and the cerebrospinal fluid of schizophrenia patients [ 23 ].…”

Section: Label-free Quantitative Proteomicsmentioning

confidence: 99%

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Mass Spectrometry-Based Label-Free Quantitative Proteomics

Zhu

Smith

Huang

2010

Journal of Biomedicine and Biotechnology

488

438

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In order to study the differential protein expression in complex biological samples, strategies for rapid, highly reproducible and accurate quantification are necessary. Isotope labeling and fluorescent labeling techniques have been widely used in quantitative proteomics research. However, researchers are increasingly turning to label-free shotgun proteomics techniques for faster, cleaner, and simpler results. Mass spectrometry-based label-free quantitative proteomics falls into two general categories. In the first are the measurements of changes in chromatographic ion intensity such as peptide peak areas or peak heights. The second is based on the spectral counting of identified proteins. In this paper, we will discuss the technologies of these label-free quantitative methods, statistics, available computational software, and their applications in complex proteomics studies.

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Section: Label-free Quantitative Proteomicsmentioning

confidence: 99%

“…PepMatch module aligns peptides from different LC-MS runs and detects small quantitative differences between peptides across multiple runs with statistical confidence. Various normalization techniques can be applied to further improve results [ 18 ].…”

Section: Commercially Available Software For Label-free Quantitatimentioning

confidence: 99%

Mass Spectrometry-Based Label-Free Quantitative Proteomics

Zhu

Smith

Huang

2010

Journal of Biomedicine and Biotechnology

488

438

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“…This method uses spectral counting by measuring the frequency with which the peptide of interest has been sequenced by the MS, that is, the number of spectra for each peptide or protein being proportional to the amount of protein in the sample. This method can be used for biomarker discovery which normally requires high sample throughput by comparing peak intensity from multiple LC-MS data [ 22 , 23 ]. Many studies have used label-free proteomics in cancer such as comparative proteomic analysis of non-small cell lung cancer [ 24 ] and proteins associated with metastasis in paraffin-embedded archival melanomas [ 25 ].…”

Section: Advances In Discovery-based Proteomics In Cancermentioning

confidence: 99%

Advances in Proteomic Technologies and Its Contribution to the Field of Cancer

Mesri

2014

Advances in Medicine

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Systematic studies of the cancer genome have generated a wealth of knowledge in recent years. These studies have uncovered a number of new cancer genes not previously known to be causal targets in cancer. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies are not widely available for most cancers. Precision care plans still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics is continuing to make major strides in the discovery of fundamental biological processes as well as more recent transition into an assay platform capable of measuring hundreds of proteins in any biological system. As such, proteomics can translate basic science discoveries into the clinical practice of precision medicine. The proteomic field has progressed at a fast rate over the past five years in technology, breadth and depth of applications in all areas of the bioscience. Some of the previously experimental technical approaches are considered the gold standard today, and the community is now trying to come to terms with the volume and complexity of the data generated. Here I describe contribution of proteomics in general and biological mass spectrometry in particular to cancer research, as well as related major technical and conceptual developments in the field.

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“…Extensive statistical studies have assessed the confidence in protein assignments made by MS, 38,39 but in identifying the best peptide set with which to compare samples, the PRF approach is not blindly statistical as it provides quality control by selection based on a physical expectation of peptide behavior, even when signal magnitude varies greatly between peptides. Differences in total concentration between samples are likewise unimportant.…”

Section: Ratio-of-ratios Optimization For Proportional Signalsmentioning

confidence: 99%

Label-free mass spectrometry exploits dozens of detected peptides to quantify lamins in wildtype and knockdown cells

Swift

Harada

Buxboim

et al. 2013

Nucleus

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L abel-free quantitation and characterization of proteins by mass spectrometry (ms) is now feasible, especially for moderately expressed structural proteins such as lamins that typically yield dozens of tryptic peptides from tissue cells. using standard cell culture samples, we describe general algorithms for quantitative analysis of peptides identified in liquid chromatography tandem mass spectrometry (Lc-ms/ms). the algorithms were foundational to the discovery that the absolute stoichiometry of a-type to b-type lamins scales with tissue stiffness (swift et al., Science 2013). isoform dominance helps make sense of why mutations and changes with age of mechanosensitive lamin-a,c only affect "stiff" tissues such as heart, muscle, bone, or even fat, but not brain. a peak ratio fingerprinting (prf) algorithm is elaborated here through its application to lamin-a,c knockdown. after demonstrating the large dynamic range of prf using calibrated mixtures of human and mouse lysates, we validate measurements of partial knockdown with standard cell biology analyses using quantitative immunofluorescence and immunoblotting. optimal sets of ms-detected peptides as determined by prf demonstrate that the strongest peptide signals are not necessarily the most reliable for quantitation. after lamin-a,c knockdown, prf computes an invariant set of "housekeeping" proteins as part of a broader proteomic analysis that also shows the proteome of mesenchymal stem cells (mscs) is more broadly perturbed than that of a human epithelial cancer line (a549s), with particular variation in nuclear and cytoskeletal proteins. these methods offer exciting prospects for basic and clinical studies of lamin-a,c as well as other ms-detectable proteins.

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Robustness and accuracy of high speed LC–MS separations for global peptide quantitation and biomarker discovery☆

Cited by 12 publications

References 43 publications

Mass Spectrometry-Based Label-Free Quantitative Proteomics

Mass Spectrometry-Based Label-Free Quantitative Proteomics

Advances in Proteomic Technologies and Its Contribution to the Field of Cancer

Label-free mass spectrometry exploits dozens of detected peptides to quantify lamins in wildtype and knockdown cells

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