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From the third issue of 2017, Microarrays has changed its name to High-Throughput.

Open AccessArticle
Microarrays 2016, 5(3), 19; doi:10.3390/microarrays5030019

Protein Profiling Gastric Cancer and Neighboring Control Tissues Using High-Content Antibody Microarrays

1
Division of Biostatistics, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 581, 69120 Heidelberg, Germany
2
Division of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
3
Sciomics GmbH, In Neuenheimer Feld 583, 69120 Heidelberg, Germany
4
Department of General, Visceral and Transplantation Surgery, University Clinic Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
5
Medical Faculty, University of Ljubljana, Vrazov Trg 2, 1000 Ljubljana, Slovenia
*
Author to whom correspondence should be addressed.
Academic Editors: Carl A. K. Borrebaeck, Christer Wingren and Ulrika Andreasson Axelsson
Received: 18 April 2016 / Revised: 25 May 2016 / Accepted: 13 June 2016 / Published: 8 July 2016
(This article belongs to the Special Issue Antibody Microarrays in Clinical Proteomics)
View Full-Text   |   Download PDF [1788 KB, uploaded 8 July 2016]   |  

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. View Full-Text
Keywords: gastric cancer; adenocarcinoma; affinity based proteomics; antibody microarrays; biomarker identification gastric cancer; adenocarcinoma; affinity based proteomics; antibody microarrays; biomarker identification
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Sill, M.; Schröder, C.; Shen, Y.; Marzoq, A.; Komel, R.; Hoheisel, J.D.; Nienhüser, H.; Schmidt, T.; Kastelic, D. Protein Profiling Gastric Cancer and Neighboring Control Tissues Using High-Content Antibody Microarrays. Microarrays 2016, 5, 19.

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