Evidence map›Paper›PMID 22014164›Full record

ArticleBMC veterinary research2011

Overexpression of α-enolase correlates with poor survival in canine mammary carcinoma.

Pei-Yi Chu, Nicholas C Hsu, Albert T Liao, Neng-Yao Shih, Ming-Feng Hou, Chen-Hsuan Liu

Open access · goldAbstract read
In one paragraph

Article in BMC veterinary research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

10 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Progress in the biological function of alpha-enolase.Animal nutrition (Zhongguo xu mu shou yi xue hui) · 2016
    Review
  7. Article
  8. Article
  9. Article
  10. 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

6 authors at 5 institutions in 1 country.

Pei-Yi ChuDepartment of Pathology, St Martin De Porres Hospital, No 565, Section 2, Daya Road, Chiayi 60069, Taiwan.
Nicholas C Hsu
Albert T Liao
Neng-Yao Shih
Ming-Feng Hou
Chen-Hsuan Liu
National Taiwan University · TWKaohsiung Medical University · TWKaohsiung Medical University Chung-Ho Memorial Hospital · TWNational Health Research Institutes · TWSt. Martin de Porres Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundα-Enolase (ENO1) is a key glycolytic enzyme implicated in the development of many human cancers including breast cancer. Increased expression of ENO1 has recently been reported in estrogen (ER)-positive human breast cancer patients. The present study examined the expression of ENO1 and assessed its significance in canine mammary carcinoma.

resultsImmunohistochemical staining was employed to investigate the expression of ENO1 in 82 cases of canine mammary tumor (32 benign tumors and 50 carcinomas). Quantification of immunohistochemistry was carried out using Quick score and the results showed cytoplasmic ENO1 overexpression in 9 of the 50 carcinomas (18%). Overexpression of ENO1 correlated significantly with shorter cause-specific survival (P = 0.019), but was not associated with ER positivity in canine mammary carcinoma.

conclusionsOur findings suggest that overexpression of ENO1 may be used as a prognostic marker for poor outcome in canine mammary carcinoma.

Indexed as

AnimalsBiomarkersDog DiseasesDogsFemaleGene Expression Regulation, NeoplasticImmunoblottingMammary Glands, AnimalMammary Neoplasms, AnimalPhosphopyruvate HydrataseBiomarkersPhosphopyruvate Hydratase

Identifiers

PMID22014164
PMCPMC3207881
OpenAlexW1990673250

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.