Evidence map›Paper›PMID 27600085›Full record

ArticleMicroarrays (Basel, Switzerland)2016

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

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

Open access · goldAbstract read
In one paragraph

Article in Microarrays (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Martin SillDivision of Biostatistics, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 581, 69120 Heidelberg, Germany. m.sill@dkfz.de.
Christoph SchröderDivision of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. schroeder@sciomics.de.
Ying ShenDepartment of General, Visceral and Transplantation Surgery, University Clinic Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany. shenying_0624@outlook.com.
Aseel MarzoqDivision of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. a.marzoq@dkfz.de.
Radovan KomelMedical Faculty, University of Ljubljana, Vrazov Trg 2, 1000 Ljubljana, Slovenia. komel@mf.uni-lj.si.
Jörg D HoheiselDivision of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. j.hoheisel@dkfz.de.
Henrik NienhüserDepartment of General, Visceral and Transplantation Surgery, University Clinic Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany. Henrik.Nienhueser@med.uni-heidelberg.de.
Thomas SchmidtDepartment of General, Visceral and Transplantation Surgery, University Clinic Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany. Thomas1.schmidt@med.uni-Heidelberg.de.
Damjana KastelicDivision of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. kastelic.dkfz@gmail.com.
German Cancer Research Center · DEHeidelberg University · DEUniversity of Ljubljana · SI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

adenocarcinomaaffinity based proteomicsantibody microarraysbiomarker identificationgastric cancer

Identifiers

PMID27600085
PMCPMC5040966
OpenAlexW2462544844

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.