Reliability of Human Serum Protein Profiles Generated with C8 Magnetic Beads Assisted Maldi-TOF Mass Spectrometry

Noo, Mirre E. de; Tollenaar, Rob A.E.M.; Özalp, Aliye; Kuppen, Peter J. K.; Bladergroen, Marco R.; Eilers, Paul H.C.; Deelder, André M.

doi:10.1021/ac050571f

Cited by 89 publications

(84 citation statements)

References 27 publications

(33 reference statements)

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“…Furthermore median valúes have proven to be more robust than averages as scale factors against possible outlying peaks [18]. Taking into account these studies, the normalization used here combines both approaches: it uses local estimators over mjz Windows with rescaling to the median valué of the TIC.…”

Section: Normalizationmentioning

confidence: 99%

Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data

García-Torres

Armañanzas

Bielza

et al. 2013

Information Sciences

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Mass spectrometry (MS) data provide a promising strategy for biomarker discovery. For this purpose, the detection of relevant peakbins in MS data is currently under intense research. Data from mass spectrometry are challenging to analyze because of their high dimensionality and the generally low number of samples available. To tackle this problem, the scientific community is becoming increasingly interested in applying feature subset selection techniques based on specialized machine learning algorithms. In this paper, we present a performance comparison of some metaheuristics: best first (BF), genetic algorithm (GA), scatter search (SS) and variable neighborhood search (VNS). Up to now, all the algorithms, except for GA, have been first applied to detect relevant peakbins in MS data. All these metaheuristic searches are embedded in two different filter and wrapper schemes coupled with Naive Bayes and SVM classifiers.

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Section: Normalizationmentioning

confidence: 99%

Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data

García-Torres

Armañanzas

Bielza

et al. 2013

Information Sciences

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“…However, at the present time no data have been published on this source of variation. Nevertheless, in a previous study our group analyzed pre-analytical and reproducibility issues of our MALDI-TOF approach [31] . The pre-analytical variations corresponded to the logistical conditions in the routine clinical setting; i.e.…”

Section: Analytical Factorsmentioning

confidence: 99%

“…Currently, there is a lot of discussion among several groups on how to establish the best method, because data pre-processing is extremely important. There are complex interactions between baseline subtraction, normalization, noise estimation, and peak identification, and therefore these steps should not be considered in isolation [31,[37][38][39][40] . Another recurring topic for debate is the bioinformatic approach and statistical analysis of protein spectra.…”

Section: Statistical Issuesmentioning

confidence: 99%

Current status and prospects of clinical proteomics studies on detection of colorectal cancer: Hopes and fears

Noo

Tollenaar²,

Deelder³

et al. 2006

WJG

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BACKGROUNDIn order to improve early detection, monitor disease outcome and find targets for more individualised therapy, there is an urgent demand for new biomarkers in oncology. A field of recent interest is clinical proteomics, which has been reported to lead to high sensitivity and specificities for early detection of several solid tumors [1,2] . This emerging field uses mass spectrometry-based protein profiles/ patterns of easy accessible body fluids to distinguish cancer from non-cancer patients. This would offer a solution to the problem of cancer often being diagnosed in late stages, when curative resection of the diseased organ is no longer possible and the disease has already metastasized, thus dropping survival rates dramatically. However, after the initial positive announcements in early 2002, criticisms were raised about several aspects of serum proteomics. In this paper we describe the hopes and fears for the introduction of clinical proteomics for early detection of Colorectal adenocarcinoma (CRC). COLORECTAL CANCERColorectal adenocarcinoma is the third most common type of cancer and the fourth most frequent cause of death due to cancer worldwide. Worldwide almost one million new cases occur annually, amounting to 492 000 related deaths [3] . In developed countries it is the second most common type of tumor, with a lifetime risk of 5%, but its incidence and mortality is now decreasing [4,5] . Surgery is the cornerstone of therapy when the disease is confined to the bowel wall. This results in 70%-80% of patients who have tumors that, when diagnosed, can be resected with curative intent [6] . After curative surgery the five-year survival rate for patients with localised disease is 90%, decreasing to 65% in the case of metastasized disease to the lymph nodes. Adjuvant radiation therapy, chemotherapy, or both are useful in selected patients. Classification of tumors into pathogenetical subtypes with distinct clinical courses enables clinicians to target therapy. For CRC, the TNM staging system remains the gold standard and relies entirely on the morphological appearance of the tumor. However, tumors with similar histopathological characteristics may have different clinical outcomes and responsiveness to therapy [7] . Therefore, more individualised treatment would benefit the patient and may avoid unnecessary morbidity. Nonetheless, early detection of CRC will increase survival the most, in view of the fact that it is well recognized that CRC arises from a multistep sequence of genetic alterations that result EDITORIAL Current status and prospects of clinical proteomics studies on AbstractColorectal adenocarcinoma (CRC) is the third most common type of cancer and the fourth most frequent cause of death due to cancer worldwide. Given the natural history of CRC, early diagnosis appears to be the most appropriate tool to reduce disease-related mortality. A field of recent interest is clinical proteomics, which was reported to lead to high sensitivity and specificities for early detection of several solid...

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“…Matrix-assisted laser desorption/ ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is the potential tool to identify and quantify the various proteins present in mixture [9][10][11][12][13][14][15]. The protein samples are absorbed in the matrix composed of non-volatile material which is then irradiated using lasor beam which thus results in the formation of vaporized ion.…”

Section: Introductionmentioning

confidence: 99%

Identification of Bioactive Peptides in Goat Milk and Their Health Application

Sharma¹,

Rout²,

Kaushik³

et al. 2017

J Adv Dairy Res

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We have identified the bioactive peptides in goat milk using two dimensional gel electrophoresis and mass spectrometry. The milk samples were collected from three healthy breeds of goats at CIRG farms. The milk proteins were isolated using simple centrifugation and were evaluated on the basis of presence of other proteins variants using SDS PAGE and two dimensional gel electrophoresis. The protein profiles of all the milk proteins were same showing the presence of all the major caseins proteins and whey proteins whereas the two dimensional gel electrophoresis resulted gels has shown the presence of various protein spots. These protein spots were analysed under mass spectrometry and found biologically active peptides dipeptidyl peptidase, transcription factor A, Interleukin 12 subunit, oligodendrocyte transcription factor 2. In our study we have reported the biological significance of these peptides identified and their role in human health such as mitochondrial disease, brain malignancies, signaling processes of cytokines and help in generating cytotoxic lymphocyte helps enhance immunity.

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Reliability of Human Serum Protein Profiles Generated with C8 Magnetic Beads Assisted Maldi-TOF Mass Spectrometry

Cited by 89 publications

References 27 publications

Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data

Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data

Current status and prospects of clinical proteomics studies on detection of colorectal cancer: Hopes and fears

Identification of Bioactive Peptides in Goat Milk and Their Health Application

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