Evidence map›Paper›PMID 18173842›Full record

ArticleBMC systems biology2008

Linking the ovarian cancer transcriptome and immunome.

Ronald Rapberger, Paul Perco, Cornelia Sax, Thomas Pangerl, Christian Siehs, Dietmar Pils, Andreas Bernthaler, Arno Lukas, Bernd Mayer, Michael Krainer

Open access · diamondAbstract read
In one paragraph

Article in BMC systems biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 18 citations in OpenAlex.

  1. Observational
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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

10 authors at 3 institutions in 1 country.

Ronald RapbergerInstitute for Theoretical Chemistry, University of Vienna, Währinger Strasse 17, A-1090 Vienna, Austria. ronald.rapberger@univie.ac.at
Paul Perco
Cornelia Sax
Thomas Pangerl
Christian Siehs
Dietmar Pils
Andreas Bernthaler
Arno Lukas
Bernd Mayer
Michael Krainer
Medical University of Vienna · ATUniversity of Vienna · ATEmergenTec (Austria) · AT

Funding

Austrian Science Fund FWF P 17891
6 · The paper itself

Abstract

backgroundAutoantigens have been reported in a variety of tumors, providing insight into the interplay between malignancies and the immune response, and also giving rise to novel diagnostic and therapeutic concepts. Why certain tumor-associated proteins induce an immune response remains largely elusive.

resultsThis paper analyzes the proposed link between increased abundance of a protein in cancerous tissue and the increased potential of the protein for induction of a humoral immune response, using ovarian cancer as an example. Public domain data sources on differential gene expression and on autoantigens associated with this malignancy were extracted and compared, using bioinformatics analysis, on the levels of individual genes and proteins, transcriptional coregulation, joint functional pathways, and shared protein-protein interaction networks. Finally, a selected list of ovarian cancer-associated, differentially regulated proteins was tested experimentally for reactivity with antibodies prevalent in sera of ovarian cancer patients.Genes reported as showing differential expression in ovarian cancer exhibited only minor overlap with the public domain list of ovarian cancer autoantigens. However, experimental screening for antibodies directed against antigenic determinants from ovarian cancer-associated proteins yielded clear reactions with sera.

conclusionA link between tumor protein abundance and the likelihood of induction of a humoral immune response in ovarian cancer appears evident.

Indexed as

Gene Expression ProfilingGene Expression Regulation, NeoplasticAdultAntibody FormationAutoantigensComputational BiologyDatabases, FactualEpitopesFemaleGenes, NeoplasmHumansMeta-Analysis as TopicOvarian NeoplasmsProtein BindingProteinsTranscription FactorsAutoantigensEpitopesProteinsTranscription Factors

Identifiers

PMID18173842
PMCPMC2265674
OpenAlexW2041142934

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.