Literature DB >> 15892168

Method optimisation for peptide profiling of microdissected breast carcinoma tissue by matrix-assisted laser desorption/ionisation-time of flight and matrix-assisted laser desorption/ionisation-time of flight/time of flight-mass spectrometry.

Arzu Umar1, Johannes C H Dalebout, A Mieke Timmermans, John A Foekens, Theo M Luider.   

Abstract

Appropriate methods for the analysis of microdissected solid tumour tissues by matrix-assisted laser desorption/ionisation-time of flight-mass spectrometry (MALDI-TOF MS) are not yet well established. Optimisation of sample preparation was performed first on undissected tissue slices, representing approximately 200 000 cells, which were solubilised either in urea containing buffer, trifluoroethanol/NH4HCO3, 0.1% sodium dodecyl sulphate (SDS) or in 0.1% RapiGest solution, then trypsin digested and analysed by MALDI-TOF MS. Solubilisation in 0.1% SDS resulted in detection of the highest number of sample specific peak signals. Interestingly, there was little overlap in detectable peaks using the different buffers, implying that they can be used complementarily to each other. Additionally, we fractionated tryptic digests on a monolithic high-performance liquid chromatography column. Fractionation of tryptic digest from whole tissue sections resulted in a four-fold increase in the total number of peaks detected. To prove this principle, we used 0.1% SDS to generate peptide patterns from 2000 microdissected tumour and stromal cells from five different breast carcinoma tumours. The tumour and stroma specific peaks could be detected upon comparison of the peptide profiles. Identification of differentially expressed peaks by MALDI-TOF/TOF MS was performed on fractionated tryptic digests derived from a whole tissue slice. In conclusion, we describe a method that is suitable for direct peptide profiling on small amounts of microdissected cells obtained from breast cancer tissues.

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Year:  2005        PMID: 15892168     DOI: 10.1002/pmic.200400128

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  16 in total

1.  A proteome comparison between physiological angiogenesis and angiogenesis in glioblastoma.

Authors:  Dana A M Mustafa; Lennard J Dekker; Christoph Stingl; Andreas Kremer; Marcel Stoop; Peter A E Sillevis Smitt; Johan M Kros; Theo M Luider
Journal:  Mol Cell Proteomics       Date:  2012-01-25       Impact factor: 5.911

2.  An in-solution ultrasonication-assisted digestion method for improved extracellular matrix proteome coverage.

Authors:  Kirk C Hansen; Lauren Kiemele; Ori Maller; Jenean O'Brien; Aarthi Shankar; Jaime Fornetti; Pepper Schedin
Journal:  Mol Cell Proteomics       Date:  2009-04-07       Impact factor: 5.911

3.  Proteomic studies in breast cancer (Review).

Authors:  Xian-Ju Qin; Bruce X Ling
Journal:  Oncol Lett       Date:  2012-01-18       Impact factor: 2.967

4.  Biospecimen reporting for improved study quality (BRISQ).

Authors:  Helen M Moore; Andrea B Kelly; Scott D Jewell; Lisa M McShane; Douglas P Clark; Renata Greenspan; Daniel F Hayes; Pierre Hainaut; Paula Kim; Elizabeth Mansfield; Olga Potapova; Peter Riegman; Yaffa Rubinstein; Edward Seijo; Stella Somiari; Peter Watson; Heinz-Ulrich Weier; Claire Zhu; Jim Vaught
Journal:  J Proteome Res       Date:  2011-06-21       Impact factor: 4.466

5.  Biospecimen Reporting for Improved Study Quality.

Authors:  Helen M Moore; Andrea Kelly; Scott D Jewell; Lisa M McShane; Douglas P Clark; Renata Greenspan; Pierre Hainaut; Daniel F Hayes; Paula Kim; Elizabeth Mansfield; Olga Potapova; Peter Riegman; Yaffa Rubinstein; Edward Seijo; Stella Somiari; Peter Watson; Heinz-Ulrich Weier; Claire Zhu; Jim Vaught
Journal:  Biopreserv Biobank       Date:  2011-04       Impact factor: 2.300

Review 6.  Breast cancer proteomics: a review for clinicians.

Authors:  E R C G N Galvão; L M S Martins; J O Ibiapina; H M Andrade; S J H Monte
Journal:  J Cancer Res Clin Oncol       Date:  2011-04-05       Impact factor: 4.553

7.  Optimization of protein solubilization for the analysis of the CD14 human monocyte membrane proteome using LC-MS/MS.

Authors:  Xiaoying Ye; Donald J Johann; Ramin M Hakami; Zhen Xiao; Zhaojing Meng; Robert G Ulrich; Haleem J Issaq; Timothy D Veenstra; Josip Blonder
Journal:  J Proteomics       Date:  2009-08-24       Impact factor: 4.044

Review 8.  Breast tumor metastasis: analysis via proteomic profiling.

Authors:  Steve Goodison; Virginia Urquidi
Journal:  Expert Rev Proteomics       Date:  2008-06       Impact factor: 3.940

9.  Proteomic Profiling in the Brain of CLN1 Disease Model Reveals Affected Functional Modules.

Authors:  Saara Tikka; Evanthia Monogioudi; Athanasios Gotsopoulos; Rabah Soliymani; Francesco Pezzini; Enzo Scifo; Kristiina Uusi-Rauva; Jaana Tyynelä; Marc Baumann; Anu Jalanko; Alessandro Simonati; Maciej Lalowski
Journal:  Neuromolecular Med       Date:  2015-12-26       Impact factor: 3.843

10.  Identification of a putative protein profile associated with tamoxifen therapy resistance in breast cancer.

Authors:  Arzu Umar; Hyuk Kang; Annemieke M Timmermans; Maxime P Look; Marion E Meijer-van Gelder; Michael A den Bakker; Navdeep Jaitly; John W M Martens; Theo M Luider; John A Foekens; Ljiljana Pasa-Tolić
Journal:  Mol Cell Proteomics       Date:  2009-03-27       Impact factor: 5.911

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