Evidence map›Paper›PMID 20831783›Full record

ArticleBMC medical genomics2010

Analyzing the regulation of metabolic pathways in human breast cancer.

Gunnar Schramm, Eva-Maria Surmann, Stefan Wiesberg, Marcus Oswald, Gerhard Reinelt, Roland Eils, Rainer König

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

28 citing papers in PubMed, 55 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Gunnar SchrammDepartment of Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, and Bioquant, University of Heidelberg, INF 267, 69120 Heidelberg, Germany.
Eva-Maria Surmann
Stefan Wiesberg
Marcus Oswald
Gerhard Reinelt
Roland Eils
Rainer König
Heidelberg University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTumor therapy mainly attacks the metabolism to interfere the tumor's anabolism and signaling of proliferative second messengers. However, the metabolic demands of different cancers are very heterogeneous and depend on their origin of tissue, age, gender and other clinical parameters. We investigated tumor specific regulation in the metabolism of breast cancer.

methodsFor this, we mapped gene expression data from microarrays onto the corresponding enzymes and their metabolic reaction network. We used Haar Wavelet transforms on optimally arranged grid representations of metabolic pathways as a pattern recognition method to detect orchestrated regulation of neighboring enzymes in the network. Significant combined expression patterns were used to select metabolic pathways showing shifted regulation of the aggressive tumors.

resultsBesides up-regulation for energy production and nucleotide anabolism, we found an interesting cellular switch in the interplay of biosynthesis of steroids and bile acids. The biosynthesis of steroids was up-regulated for estrogen synthesis which is needed for proliferative signaling in breast cancer. In turn, the decomposition of steroid precursors was blocked by down-regulation of the bile acid pathway.

conclusionWe applied an intelligent pattern recognition method for analyzing the regulation of metabolism and elucidated substantial regulation of human breast cancer at the interplay of cholesterol biosynthesis and bile acid metabolism pointing to specific breast cancer treatment.

Indexed as

Bile Acids and SaltsBreast NeoplasmsEstrogensFemaleGene Expression Regulation, NeoplasticHumansMetabolic Networks and PathwaysSteroidsUp-RegulationBile Acids and SaltsEstrogensSteroids

Identifiers

PMID20831783
PMCPMC2945993
OpenAlexW2016806296

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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.