Reproducibility of Protein Identification of Selected Cell Types in Barrett’s Esophagus Analyzed by Combining Laser-Capture Microdissection and Mass SpectrometryClick to copy article linkArticle link copied!
- Christoph Stingl
- Frederike G. I. van Vilsteren
- Coskun Guzel
- Fiebo J. W. ten Kate
- Mike Visser
- Kausilia K. Krishnadath
- Jacques J. Bergman
- Theo M. Luider
Abstract

Barrett’s esophagus (BE) is associated with increased risk of esophageal adenocarcinoma (EAC) and characterized by replacement of normal esophageal squamous epithelium by columnar epithelium. These alterations are also reflected in changes in the protein-expression profiles of the cell types involved. To separately investigate the proteomes of selected cell-types we combined laser-capture microdissection (LCM) and liquid chromatography−mass spectrometry (LC−MS). Aims were to determine the sensitivity, specificity, and technical reproducibility of the sampling method, and the biological variability within and between biopsies and patients. Frozen biopsies were cryo-sectioned, samples of around 2000 epithelial or stroma cells microdissected, digested and measured by Orbitrap LC−MS. Proteins were then identified by MS/MS database search and quantified by label-free analysis. An average of 366 protein-groups were identified per sample, and more protein-groups were found in epithelial samples than in stromal samples (442 vs 301, p < 0.0001). Altogether, 1254 distinct protein-groups were found, 289 and 88 of them significantly more often in epithelial and stroma samples, respectively. We assessed five different types of reproducibilities (run-to-run, intrabiopsy, biopsy-to-biopsy, experiment-to-experiment, and patient-to-patient) for protein identification and protein quantification. Reproducibility of protein identification ranged from 78 to 57%, and standard deviation of protein quantification was on patient-to-patient level four times higher than for run-to-run. We conclude that sampling around 2000 cells requires groups of 32 samples to detect significant, over 10-fold differences in protein abundances and thus creates a successful compromise between throughput and quality of results. We therefore believe that this method is suitable for investigating protein-expression profiles during carcinogenesis.
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