Martin Sill (Author), Christoph Schröder (Author), Ying Shen (Author), Aseel Marzoq (Author), Radovan Komel (Author), Jörg Hoheisel (Author), Henrik Nienhüser (Author), Thomas Schmidt (Author), Damjana Kastelic (Author)

Abstract

In this study, protein profiling was performed on gastric cancer tissue samples in order to identify proteins that could be utilized for an effective diagnosis of this highly heterogeneous disease and as targets for therapeutic approaches. To this end, 16 pairs of postoperative gastric adenocarcinomas and adjacent non-cancerous control tissues were analyzed on microarrays that contain 813 antibodies targeting 724 proteins. Only 17 proteins were found to be differentially regulated, with much fewer molecules than the numbers usually identified in studies comparing tumor to healthy control tissues. Insulin-like growth factor-binding protein 7 (IGFBP7), S100 calcium binding protein A9 (S100A9), interleukin-10 (IL-10) and mucin 6 (MUC6) exhibited the most profound variations. For an evaluation of the proteins' capacity for discriminating gastric cancer, a Receiver Operating Characteristic curve analysis was performed, yielding an accuracy (area under the curve) value of 89.2% for distinguishing tumor from non-tumorous tissue. For confirmation, immunohistological analyses were done on tissue slices prepared from another cohort of patients with gastric cancer. The utility of the 17 marker proteins, and particularly the four molecules with the highest specificity for gastric adenocarcinoma, is discussed for them to act as candidates for diagnosis, even in serum, and targets for therapeutic approaches.

Keywords

rak želodca;adenokarcinom;identifikacija biomarkerjev;gastric cancer;adenocarcinoma;biomarker identification;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL MF - Faculty of Medicine
UDC: 616-006
COBISS: 32738265 Link will open in a new window
ISSN: 2076-3905
Views: 172
Downloads: 49
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Other data

Secondary language: Slovenian
Secondary keywords: rak želodca;adenokarcinom;identifikacija biomarkerjev;
Type (COBISS): Article
Pages: str. 1-12
Volume: ǂVol. ǂ5
Issue: ǂiss. ǂ3
Chronology: 2016
DOI: 10.3390/microarrays5030019
ID: 13582420