A systematic analysis of the effects of increasing degrees of serum immunodepletion in terms of depth of coverage and other key aspects in top‐down and bottom‐up proteomic analyses

Smith, Matthew P. Welberry; Wood, Steven L.; Zougman, Alexandre; Ho, Jenny; Peng, Jianhe; Jackson, David H.; Cairns, David A.; Lewington, Andrew; Selby, Peter J.; Banks, Rosamonde E.

doi:10.1002/pmic.201100005

Cited by 63 publications

(47 citation statements)

References 42 publications

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“…The analyses were made by rank product analysis of the case-control ratios, with the samples considered in relation to time intervals relative to diagnosis and seroconversion (as indicated). a, throughout (n = 19); b, preseroconversion (n = 14); c, 9-12 months preseroconversion; d, 3-6 months preseroconversion; e, postseroconversion and ,1.5 year prediagnosis (n = 19); f, [15][16][17][18] months postseroconversion (n = 14); g, 3-6 months postseroconversion (n = 14). …”

Section: Differences Between the Serum Proteomes Of Children Who Devementioning

confidence: 99%

“…First, we used isobaric tags for relative and absolute quantification (iTRAQ) reagents, which have previously been extensively used in serum proteomics applications, including the development of robust analytical protocols and applied studies up to the scale of hundreds of subjects (15,16). Second, we used a label-free method, which has also been applied in serum proteomics analyses (17,18). The present results reveal a spectrum of changes and differences in the serum protein profiles between children progressing to type 1 diabetes and matched control subjects.…”

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confidence: 99%

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Serum Proteomes Distinguish Children Developing Type 1 Diabetes in a Cohort With HLA-Conferred Susceptibility

et al. 2015

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We determined longitudinal serum proteomics profiles from children with HLA-conferred diabetes susceptibility to identify changes that could be detected before seroconversion and positivity for disease-associated autoantibodies. Comparisons were made between children who seroconverted and progressed to type 1 diabetes (progressors) and those who remained autoantibody negative, matched by age, sex, sample periodicity, and risk group. The samples represented the prediabetic period and ranged from the age of 3 months to 12 years. After immunoaffinity depletion of the most abundant serum proteins, isobaric tags for relative and absolute quantification were used for sample labeling. Quantitative proteomic profiles were then measured for 13 case-control pairs by high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Additionally, a label-free LC-MS/MS approach was used to analyze depleted sera from six case-control pairs. Importantly, differences in abundance of a set of proteins were consistently detected before the appearance of autoantibodies in the progressors. Based on top-scoring pairs analysis, classification of such progressors was observed with a high success rate. Overall, the data provide a reference of temporal changes in the serum proteome in healthy children and children progressing to type 1 diabetes, including new protein candidates, the levels of which change before clinical diagnosis.

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Section: Differences Between the Serum Proteomes Of Children Who Devementioning

confidence: 99%

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confidence: 99%

Serum Proteomes Distinguish Children Developing Type 1 Diabetes in a Cohort With HLA-Conferred Susceptibility

et al. 2015

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“…Methods for removal of highly abundant proteins from other biofluids (e.g., amniotic fluid and synovial fluid) were also described [42,43]. Arguably, immuno-depletion is considered the most effective, reliable and reproducible technique [38,44–47], and is widely used in contemporary biomarker research [48–50]. This increases the identification rate of lower-abundant proteins by an average of two-to four-fold [45] and has been consistently used for removal of abundant proteins from peripheral blood specimens (i.e., plasma and serum).…”

Section: Liquid Chromatography-ms Analysis Of Human Clinical Specimenmentioning

confidence: 99%

Mass Spectrometry in Cancer Biomarker Research: A Case for Immunodepletion of Abundant Blood-Derived Proteins from Clinical Tissue Specimens

et al. 2014

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The discovery of clinically relevant cancer biomarkers using mass spectrometry (MS)-based proteomics has proven difficult, primarily because of the enormous dynamic range of blood-derived protein concentrations and the fact that the 22 most abundant blood-derived proteins constitute approximately 99% of the total plasma protein mass. Immunodepletion of clinical body fluid specimens (e.g., serum/plasma) for the removal of highly abundant proteins is a reasonable and reproducible solution. Often overlooked, clinical tissue specimens also contain a formidable amount of highly abundant blood-derived proteins present in tissue-embedded networks of blood/lymph capillaries and interstitial fluid. Hence, the dynamic range impediment to biomarker discovery remains a formidable obstacle, regardless of clinical sample type (solid tissue and/or body fluid). Thus, we optimized and applied simultaneous immunodepletion of blood-derived proteins from solid tissue and peripheral blood, using clear cell renal cell carcinoma as a model disease. Integrative analysis of data from this approach and genomic data obtained from the same type of tumor revealed concordant key pathways and protein targets germane to clear cell renal cell carcinoma. This includes the activation of the lipogenic pathway characterized by increased expression of adipophilin (PLIN2) along with 'cadherin switching', a phenomenon indicative of transcriptional reprogramming linked to renal epithelial dedifferentiation. We also applied immunodepletion of abundant blood-derived proteins to various tissue types (e.g., adipose tissue and breast tissue) showing unambiguously that the removal of abundant blood-derived proteins represents a powerful tool for the reproducible profiling of tissue proteomes. Herein, we show that the removal of abundant blood-derived proteins from solid tissue specimens is of equal importance to depletion of body fluids and recommend its routine use in the context of biological discovery and/or cancer biomarker research. Finally, this perspective presents the background, rationale and strategy for using tissue-directed high-resolution/accuracy MS-based shotgun proteomics to detect genuine tumor proteins in the peripheral blood of a patient diagnosed with nonmetastatic cancer, employing concurrent liquid chromatography–MS analysis of immunodepleted clinical tissue and blood specimens.

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“…One possible solution for improving the limits of detection of low abundance proteins is to deplete HAP by immobilized antibodies. There are commercially available low pressure LC type and spinfilter type columns with immobilized antibo dies for as many as 20 HAP [18 ], making these products very popular in proteomics research for biomarker discovery [19 ]. Depletion of HAP may also be useful in qCCP, for improving the limits of detection of medium and low abundance proteins in clinical samples.…”

Section: Protein Precipitationmentioning

confidence: 99%

Quantitative Clinical Chemistry Proteomics (qCCP) using mass spectrometry: general characteristics and application

Lehmann

Hoofnagle

Hochstrasser³

et al. 2013

Clinical Chemistry and Laboratory Medicine

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Proteomics studies typically aim to exhaustively detect peptides/proteins in a given biological sample. Over the past decade, the number of publications using pro teomics methodologies has exploded. This was made possible due to the availability of high-quality genomic data and many technological advances in the fields of microfluidics and mass spectrometry. Proteomics in biomedical research was initially used in ‘ functional ’ studies for the identification of proteins involved in pathophysiological processes, complexes and networks. Improved sensitivity of instrumentation facilitated the analysis of even more complex sample types, including human biological fluids. It is at that point the field of clinical proteomics was born, and its fundamental aim was the discovery and (ideally) validation of biomarkers for the diagnosis, prognosis, or therapeutic monitoring of disease. Eventually, it was recognized that the technologies used in clinical proteomics studies [particularly liquid chromatography-tandem mass spectrometry (LC-MS/MS)] could represent an alternative to classical immunochemical assays. Prior to deploying MS in the measurement of peptides/proteins in the clinical laboratory, it seems likely that traditional proteo mics workflows and data management systems will need to adapt to the clinical environment and meet in vitro diagnostic (IVD) regulatory constraints. This defines a new field, as reviewed in this article, that we have termed quantitative Clinical Chemistry Proteomics (qCCP)

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A systematic analysis of the effects of increasing degrees of serum immunodepletion in terms of depth of coverage and other key aspects in top‐down and bottom‐up proteomic analyses

Cited by 63 publications

References 42 publications

Serum Proteomes Distinguish Children Developing Type 1 Diabetes in a Cohort With HLA-Conferred Susceptibility

Serum Proteomes Distinguish Children Developing Type 1 Diabetes in a Cohort With HLA-Conferred Susceptibility

Mass Spectrometry in Cancer Biomarker Research: A Case for Immunodepletion of Abundant Blood-Derived Proteins from Clinical Tissue Specimens

Quantitative Clinical Chemistry Proteomics (qCCP) using mass spectrometry: general characteristics and application

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