Evidence map›Paper›PMID 25001871›Full record

ArticleCellular oncology (Dordrecht, Netherlands)2014

Identification of novel markers that outperform EpCAM in quantifying circulating tumor cells.

Min-Ji Kim, Na Young Choi, Eun Kyung Lee, Myung-Soo Kang

Abstract read
In one paragraph

Article in Cellular oncology (Dordrecht, Netherlands), 2014. 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
1.0field-weighted citation impact, top 23% 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, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. PSA and beyond: alternative prostate cancer biomarkers.Cellular oncology (Dordrecht, Netherlands) · 2016
    Review
  6. 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

4 authors at 3 institutions in 1 country.

Min-Ji KimSamsung Biomedical Research Institute and Samsung Medical Center, Seoul, Korea, 135-718.
Na Young Choi
Eun Kyung Lee
Myung-Soo Kang
Samsung Medical Center · KRKyungdong University · KRSungkyunkwan University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCirculating tumor cells (CTCs) can be used to predict the spread of cancer to distant sites, to monitor the clinical response to therapy and to predict patient survival. The currently used EpCAM antibody-mediated identification of CTCs may lead to false negative results due to the low level or absence of EpCAM expression in several types of cancer, thus provoking a need to identify novel CTC markers.

methodsThe Cancer Cell Line Encyclopedia (CCLE) microarray dataset, storing 18,915 gene expression profiles across 967 cancer cell lines derived from 25 primary sites, was systematically analyzed. The results obtained were cross-validated using an independent microarray dataset generated from 1,911 clinical cancer specimens derived from 15 different cancers.

resultsThrough bioinformatics analyses we identified, categorized and prioritized three classes of novel markers: pan-CTC markers (n = 45), EpCAM((-/low)) CTC markers (n = 16) and single cancer type-specific markers (n = 74). The pan-CTC markers were significantly, uniformly and constitutively over-expressed in most cancer types, except in cancers of hematopoietic and lymphoid origin. The EpCAM((-/low)) CTC markers were over-expressed in cancers with low or undetectable EpCAM expression levels. Among these, 22 markers were validated in an independent microarray dataset. In addition, 74 markers that were over-expressed in only single cancer types were categorized.

conclusionsThe combined use of these novel markers in conjunction with cancer type-specific markers should be able to quantify CTCs that are not captured by EpCAM antibodies, and to enhance the sensitivity and specificity of CTC detection among admixtures containing leucocytes or other types of contaminants.

Indexed as

AntibodiesAntigens, NeoplasmBiomarkers, TumorCell Adhesion MoleculesCell Line, TumorComputational BiologyDatabases, GeneticEpithelial Cell Adhesion MoleculeHumansNeoplastic Cells, CirculatingAntibodiesAntigens, NeoplasmBiomarkers, TumorCell Adhesion MoleculesEPCAM protein, humanEpithelial Cell Adhesion Molecule

Identifiers

PMID25001871
PMCPMC13004436
OpenAlexW2066330331

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.