Evidence map›Paper›PMID 18000362›Full record

ArticleCytogenetic and genome research2007

Genomic signatures of breast cancer metastasis.

V Urquidi, S Goodison

Open access · bronzeAbstract read
In one paragraph

Article in Cytogenetic and genome research, 2007. 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
0.1field-weighted citation impact, top 38% 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. Article
  4. Review
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

2 authors at 1 institution in 1 country.

V UrquidiDepartment of Medicine, University of Florida, Jacksonville, FL, USA.
S Goodison
University of Florida · US

Funding

Functional Analysis of metastasis-Associated ProteinsR01CA108597 · NCI · UNIVERSITY OF FLORIDA · PI GOODISON, STEVE · 2004 to 2008
$1.3M
NCI NIH HHS R01 CA108597
6 · The paper itself

Abstract

Despite significant advances in the treatment of primary cancer, the ability to predict the metastatic behavior of a patient's cancer, as well as to detect and eradicate such recurrences, remain major clinical challenges in oncology. While many potential molecular biomarkers have been identified and tested previously, none have greatly improved the accuracy of specimen evaluation over routine histopathological criteria and they predict individual outcomes poorly. However, the recent introduction of high-throughput microarray technology has opened new avenues in genomic investigation of cancer, and through application in tissue-based studies and appropriate animal models, has facilitated the identification of gene expression signatures that are associated with the lethal progression of breast cancer. The use of these approaches has the potential to greatly impact our knowledge of tumor biology, to provide efficient biomarkers, and enable development towards customized prognostication and therapies for the individual.

Indexed as

GenomicsAnimalsBiomarkers, TumorBreast NeoplasmsChromosome AberrationsChromosome MappingDisease Models, AnimalHumansKaryotypingNeoplasm MetastasisNucleic Acid HybridizationPrognosisBiomarkers, Tumor

Identifiers

PMID18000362
PMCPMC2546496
OpenAlexW1989043319

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.