Evidence map›Paper›PMID 15720800›Full record

ArticleNeoplasia (New York, N.Y.)

Identification and validation of commonly overexpressed genes in solid tumors by comparison of microarray data.

Christian Pilarsky, Michael Wenzig, Thomas Specht, Hans Detlev Saeger, Robert Grützmann

Open access · goldAbstract readComparative Study
In one paragraph

Article in Neoplasia (New York, N.Y.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 191 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
191citing papers in PubMed, 2 pooled it
3.7field-weighted citation impact, top 6% 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

191 citing papers in PubMed, 2 syntheses or guidelines pooled it, 329 citations in OpenAlex.

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131 more citing papers are in PubMed but not listed here.

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

5 authors at 2 institutions in 2 countries.

Christian PilarskyDepartment of Visceral, Thoracic, and Vascular Surgery, University Hospital Carl Gustav Carus, Dresden, Germany.
Michael Wenzig
Thomas Specht
Hans Detlev Saeger
Robert Grützmann
University Hospital Carl Gustav Carus · DEBio Forschung Austria · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancers originating from epithelial cells are the most common malignancies. No common expression profile of solid tumors compared to normal tissues has been described so far. Therefore we were interested if genes differentially expressed in the majority of carcinomas could be identified using bioinformatic methods. Complete data sets were downloaded for carcinomas of the prostate, breast, lung, ovary, colon, pancreas, stomach, bladder, liver, and kidney, and were subjected to an expression analysis using SAM. In each experiment, a gene was scored as differentially expressed if the q value was below 25%. Probe identifiers were unified by comparing the respective probe sequences to the Unigene build 155 using BlastN. To obtain differentially expressed genes within the set of analyzed carcinomas, the number of experiments in which differential expression was observed was counted. Differential expression was assigned to genes if they were differentially expressed in at least eight experiments of tumors from different origin. The identified candidate genes ADRM1, EBNA1BP2, FDPS, FOXM1, H2AFX, HDAC3, IRAK1, and YY1 were subjected to further validation. Using this comparative approach, 100 genes were identified as upregulated and 21 genes as downregulated in the carcinomas.

Indexed as

Gene ExpressionFemaleGene Expression ProfilingHumansMaleNeoplasmsOligonucleotide Array Sequence AnalysisReproducibility of Results

Identifiers

PMID15720800
PMCPMC1531678
OpenAlexW2014756186

What OpenQuestion holds

Textmetadata
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.